About all

Ast value: Normal, High, and Low Ranges, Chart & Results

Содержание

Limiting the Testing of AST | American Journal of Clinical Pathology

Abstract

Objectives

Annually, millions of pairs of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) tests are ordered. These enzymes are highly correlated, and ALT is far more specific diagnostically than AST. To reduce AST testing, we suggest measuring AST only when ALT exceeds a predetermined limit.

Methods

We derived the proportions of elevated ASTs that would not be measured based on 15 months of paired inpatient and outpatient ALT and AST data.

Results

For inpatients, a 35 U/L ALT limit for initiating AST testing would reduce AST testing by 51%, missing only 3% and 7.5% of ASTs exceeding 50 U/L and 35 U/L, respectively. In outpatients, AST testing can be reduced by more than 65%, with fewer missed elevated ASTs (0.5% and 2% of the ASTs exceeding 50 U/L and 35 U/L, respectively).

Conclusions

Conservatively, $100 million could be saved annually in the US health care budget by selectively limiting AST testing in just the US outpatient environment.

Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are enzymes commonly ordered to ascertain hepatocyte integrity. ALT and AST are highly concentrated in the liver and catalyze the generation of pyruvic and oxalacetic acid, respectively.1 With hepatocellular injury, these enzymes are released into the plasma, leading to increases in their activity.

With acute liver damage, plasma AST activities are initially higher than ALT due to higher AST activities in the hepatocyte.1 Eventually, ALT activity exceeds AST, with its slower metabolism and longer half-life (47 hours vs 17 hours, respectively), meaning that most patients with liver disease would have an AST/ALT ratio (also called De Ritis ratio) of less than 1.2 Chronic alcohol intake, however, causes mitochondrial AST activity to be increased in plasma.3 Furthermore, patients who abuse alcohol can have decreased pyridoxal-5′-phosphate (vitamin B6), which decreases ALT activity. 4 Overall, the AST/ALT ratio is increased in patients with alcoholic hepatitis, typically with a value greater than 1.5.5 As such, the De Ritis ratio putatively provides extra clinical information supporting the diagnosis of alcoholic hepatitis.

ALT is a more specific indicator of parenchymal liver disease than AST. ALT and AST are both present in high levels in the cytosol of the liver.6 AST is also present in the mitochondria of the liver and has significant activities in muscle, brain, pancreas, lung, kidney, erythrocytes, and leukocytes.7 ALT and AST are usually correlated, implying that a low ALT value would typically accompany a low AST value. Isolated AST elevations are generally due to nonhepatic sources (eg, arising from hemolyzed RBCs).8 In the past, AST has been used as an aid in diagnosing myocardial infarction and skeletal myopathy. For many years, troponin and creatine kinase, respectively, have been superior alternatives.

In many countries, these two tests are often ordered together. In a recent Centers for Disease Control and Prevention review of Medicare Part B–reimbursed laboratory testing, AST and ALT were the most frequently ordered hepatobiliary tests, with approximately 7,500 ALT and 7,500 AST tests ordered annually per 10,000 Medicare patients.9 In Canada and Europe, there is now pushback against AST testing. In 2007, the province of Ontario replaced AST with ALT on its requisition form. Four years later, annual AST testing in Ontario dropped from approximately 5 million to 2 million tests.10 In Sweden, AST is ordered less often than ALT. The ratio of ALT to AST tests ranges from six to 150.11 In Spanish emergency departments, a two-test screen consisting of ALT and alkaline phosphate (ALP) is used to work up hepatobiliary disease.12 This ALT/ALP combination was found to be adequate: ALT for identifying hepatocellular disease and ALP for liver tumors and biliary tract disease. 13

To reduce AST tests that are ordered in tandem with ALT, we propose measuring AST only when ALT exceeds a predetermined limit. In the steady state, hepatobiliary disease associated with an elevated ALT will usually be accompanied with an elevated AST. Conversely, in the absence of alcoholic liver disease, low ALT will usually be accompanied by low AST values. Through retrospective analysis of paired ALT and AST patient data, we determined the proportions of elevated AST that would not be measured based on the ALT limit.

Materials and Methods

We analyzed 15 months of paired AST and ALT test results obtained from a single, large outpatient laboratory (OPL) and Edmonton’s five hospitals, consisting of a university hospital offering tertiary-quaternary care, a tertiary care hospital, and three general hospitals. We computed the reduction in AST testing and the proportions of elevated AST that would be missed as the ALT limit was varied from 0 to 100 U/L. Two limits were used to define an elevated AST:

  1. AST levels exceeding 35 U/L (corresponds roughly to the 90th percentile limits for AST for healthy white, His-panic, and black females and males; see mylaboratoryquality.com/testgraphs2.htm, which summarizes the National Health and Nutrition Exam Survey 01–04)14

  2. AST levels exceeding 50 U/L (corresponds roughly to the 97.5th percentile limits for AST for healthy white and Hispanic males and the 95th percentile limits for healthy black males)14

For the OPL and each hospital, we tabulated the proportions of elevated and nonelevated ASTs that would not be done using a cutoff of 30 U/L for ALT, a common reference limit for males.15

Results

In total, 166,907 pairs of ALT and AST tests were drawn and analyzed between January 4, 2011, and March 31, 2012. The data included 67,953 pairs at OPL, 62,558 at University of Alberta Hospital (UAH), 21,238 at Royal Alexandra Hospital offering tertiary care, 5,210 at Misericordia Community Hospital, 3,809 at Sturgeon Community Hospital, and 7,139 at Grey Nuns Community Hospital. Table 1 shows the results of setting an ALT limit of 30 U/L as a condition for a further AST test. Percentages of AST missed and nonelevated AST eliminated were similar across inpatients. A larger proportion of AST was eliminated in outpatients.

Table 1

Effectiveness of Setting 30 U/L as the ALT Limit for Initiating AST Testing

Table 1

Effectiveness of Setting 30 U/L as the ALT Limit for Initiating AST Testing

Figure 1 shows the proportion of elevated AST tests that are ordered (either exceeding 35 or 50 U/L) and the percentage of AST tests not done in OPL and UAH. Benefits of such conditional analysis are greater in the OPL than at UAH, with greater reductions in AST testing and fewer “positive” AST tests missed.

Figure 1

The blue and red lines demonstrate the proportion of missed aspartate aminotransferase (AST) exceeding 35 U/L and 50 U/L, respectively, at an outpatient laboratory (A) and university hospital (B). The green line represents the proportion of AST not done as a result of the alanine aminotransferase (ALT) time limit (right scale).

Figure 1

The blue and red lines demonstrate the proportion of missed aspartate aminotransferase (AST) exceeding 35 U/L and 50 U/L, respectively, at an outpatient laboratory (A) and university hospital (B). The green line represents the proportion of AST not done as a result of the alanine aminotransferase (ALT) time limit (right scale).

Discussion

Many of today’s chemistry analyzers are capable of reflex testing (ie, automatically adding or excluding a test based on a prior laboratory result). Less AST testing results in two kinds of savings. The most obvious savings originate from the cost of not doing (or buying) the AST test. The second savings originate from tests that are used to follow up the “positive” AST result. AST reagents are relatively inexpensive, typically costing approximately CAD 20 to 30 cents per AST analysis. Assuming an incremental cost model where everything besides reagent costs is fixed, the total incremental savings by eliminating additional AST testing are proportional to the AST tests not performed. If the OPL employed a cutoff of 30 U/L for ALT, the AST testing would be reduced by 65%, corresponding to CAD 8,818 in savings in reagents alone. Similarly, CAD 6,247 can be eliminated at UAH. Using a nonincremental cost model, the savings due to decreased AST testing might also include technologist time, instrument depreciation, overhead, maintenance, and so on. In the case of purchasing AST tests from for-profit laboratories, the savings would be much higher. In 2014, the US Medicare reimbursement for a single AST test was US $7.06.16 Nearly 75% of 49 million Medicare users undergo ALT and AST testing, implying a 50% AST reduction could save up to US $130 million.9,17 Liver function tests including AST and ALT are monitored during statin therapy. It is estimated that the total number of Americans who receive statin therapy is 29. 7 million and growing.18 Thus, for patients receiving statin therapy, if an ALT limit is set so that 50% of AST tests are eliminated, a potential nondiscounted US $105 million can be saved, although a proportion of these savings would be part of the Medicare savings mentioned above.

ALT is not 100% predictive of the AST level, and some “positive” AST results will be missed. Furthermore, the De Ritis ratio can yield some useful clinical data. For example, a high ratio could be indicative of significant recent alcohol consumption or advanced alcoholic hepatitis.19 AST testing might be offered infrequently during a patient’s lifetime along with ALT. Of course, a good patient history of alcohol use should precede the AST ordering.

Compared with Sweden, our proposal only changes the ratio of ALT to AST tests done to around two to three. The selective measurement of AST sends a strong message to our clinicians, that being the inferiority of AST as a diagnostic test. As this message begins to permeate medical practice, AST should be removed from the order form, as was done by Ontario Health for vitamin B12 testing.20

The “Choosing Wisely” initiative aims to reduce medical services that provide minimal benefit to the patient.21 As of October 1, 2014, a total of 73 medical specialty societies, including the American Society of Clinical Pathology, are participating in this program. Choosing Wisely lists multiple services that provide minimal benefits. Recently, Gliwa and Pearson21 recommended expanding the list further to include services that offer only marginal benefits but at much greater costs. We suggest adding AST testing to this list.

References

1





.

AGA technical review on the evaluation of liver chemistry tests

.

Gastroenterology

.

2002

;

123

:

1367

1384

.2






et al.  
.

Biochemical laboratory tests in viral hepatitis and other hepatic diseases

.

Bull World Health Organ

.

1965

;

32

:

59

72

.3






et al. 
.

Serum activity of mitochondrial aspartate aminotransferase: a sensitive marker of alcoholism with or without alcoholic hepatitis

.

Hepatology

.

1984

;

4

:

893

896

.4






et al. 
.

Relationship between pyridoxal 5′-phosphate deficiency and aminotransferase levels in alcoholic hepatitis

.

Gastroenterology

.

1984

;

86

:

632

636

.5






.

The SGOT/SGPT ratio in alcoholic liver disease

.

Acta Med Port

.

1981

;

3

:

255

260

.6






et al. 
.

Serum activity of alanine aminotransferase (ALT) as an indicator of health and disease

.

Hepatology

.

2008

;

47

:

1363

1370

. 7




.

Aspartate aminotransferase activity and isoenzyme proportion in human liver tissues

.

Clin Chem

.

1978

;

24

:

1971

1979

.8





.

The De Ritis ratio: the test of time

.

Clin Biochem Rev

.

2013

;

34

:

117

130

.9






et al. 
.

Trends in laboratory test volumes for Medicare Part B reimbursements, 2000–2010

.

Arch Pathol Lab Med

.

2014

;

138

:

189

203

.11






et al. 
.

Effects of an education programme to change clinical laboratory testing habits in primary care

.

Scand J Prim Health Care

.

1999

;

17

:

238

243

.12






et al. 
.

Primary care use of laboratory tests in Spain: measurement through appropriateness indicators

.

Clin Lab

.

2014

;

60

:

483

490

. 13






et al. 
.

What is the best strategy for investigating abnormal liver function tests in primary care? implications from a prospective study

.

BMJ Open

.

2013

;

3

:

1

10

.15






et al. 
.

Updated definitions of healthy ranges for serum alanine aminotransferase levels

.

Ann Intern Med

.

2002

;

137

:

1

10

.19






et al. 
.

High AST/ALT ratio may indicate advanced alcoholic liver disease rather than heavy drinking

.

Alcohol Alcohol

.

2004

;

39

:

336

339

.21





.

Evidentiary rationales for the Choosing Wisely top 5 lists

.

JAMA

.

2014

;

311

:

1443

1444

.

© American Society for Clinical Pathology

ast — Abstract Syntax Trees — Python 3.10.0 documentation

-- ASDL's 4 builtin types are:
-- identifier, int, string, constant

module Python
{
    mod = Module(stmt* body, type_ignore* type_ignores)
        | Interactive(stmt* body)
        | Expression(expr body)
        | FunctionType(expr* argtypes, expr returns)

    stmt = FunctionDef(identifier name, arguments args,
                       stmt* body, expr* decorator_list, expr? returns,
                       string? type_comment)
          | AsyncFunctionDef(identifier name, arguments args,
                             stmt* body, expr* decorator_list, expr? returns,
                             string? type_comment)

          | ClassDef(identifier name,
             expr* bases,
             keyword* keywords,
             stmt* body,
             expr* decorator_list)
          | Return(expr? value)

          | Delete(expr* targets)
          | Assign(expr* targets, expr value, string? type_comment)
          | AugAssign(expr target, operator op, expr value)
          -- 'simple' indicates that we annotate simple name without parens
          | AnnAssign(expr target, expr annotation, expr? value, int simple)

          -- use 'orelse' because else is a keyword in target languages
          | For(expr target, expr iter, stmt* body, stmt* orelse, string? type_comment)
          | AsyncFor(expr target, expr iter, stmt* body, stmt* orelse, string? type_comment)
          | While(expr test, stmt* body, stmt* orelse)
          | If(expr test, stmt* body, stmt* orelse)
          | With(withitem* items, stmt* body, string? type_comment)
          | AsyncWith(withitem* items, stmt* body, string? type_comment)

          | Match(expr subject, match_case* cases)

          | Raise(expr? exc, expr? cause)
          | Try(stmt* body, excepthandler* handlers, stmt* orelse, stmt* finalbody)
          | Assert(expr test, expr? msg)

          | Import(alias* names)
          | ImportFrom(identifier? module, alias* names, int? level)

          | Global(identifier* names)
          | Nonlocal(identifier* names)
          | Expr(expr value)
          | Pass | Break | Continue

          -- col_offset is the byte offset in the utf8 string the parser uses
          attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)

          -- BoolOp() can use left & right?
    expr = BoolOp(boolop op, expr* values)
         | NamedExpr(expr target, expr value)
         | BinOp(expr left, operator op, expr right)
         | UnaryOp(unaryop op, expr operand)
         | Lambda(arguments args, expr body)
         | IfExp(expr test, expr body, expr orelse)
         | Dict(expr* keys, expr* values)
         | Set(expr* elts)
         | ListComp(expr elt, comprehension* generators)
         | SetComp(expr elt, comprehension* generators)
         | DictComp(expr key, expr value, comprehension* generators)
         | GeneratorExp(expr elt, comprehension* generators)
         -- the grammar constrains where yield expressions can occur
         | Await(expr value)
         | Yield(expr? value)
         | YieldFrom(expr value)
         -- need sequences for compare to distinguish between
         -- x < 4 < 3 and (x < 4) < 3
         | Compare(expr left, cmpop* ops, expr* comparators)
         | Call(expr func, expr* args, keyword* keywords)
         | FormattedValue(expr value, int? conversion, expr? format_spec)
         | JoinedStr(expr* values)
         | Constant(constant value, string? kind)

         -- the following expression can appear in assignment context
         | Attribute(expr value, identifier attr, expr_context ctx)
         | Subscript(expr value, expr slice, expr_context ctx)
         | Starred(expr value, expr_context ctx)
         | Name(identifier id, expr_context ctx)
         | List(expr* elts, expr_context ctx)
         | Tuple(expr* elts, expr_context ctx)

         -- can appear only in Subscript
         | Slice(expr? lower, expr? upper, expr? step)

          -- col_offset is the byte offset in the utf8 string the parser uses
          attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)

    expr_context = Load | Store | Del

    boolop = And | Or

    operator = Add | Sub | Mult | MatMult | Div | Mod | Pow | LShift
                 | RShift | BitOr | BitXor | BitAnd | FloorDiv

    unaryop = Invert | Not | UAdd | USub

    cmpop = Eq | NotEq | Lt | LtE | Gt | GtE | Is | IsNot | In | NotIn

    comprehension = (expr target, expr iter, expr* ifs, int is_async)

    excepthandler = ExceptHandler(expr? type, identifier? name, stmt* body)
                    attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)

    arguments = (arg* posonlyargs, arg* args, arg? vararg, arg* kwonlyargs,
                 expr* kw_defaults, arg? kwarg, expr* defaults)

    arg = (identifier arg, expr? annotation, string? type_comment)
           attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)

    -- keyword arguments supplied to call (NULL identifier for **kwargs)
    keyword = (identifier? arg, expr value)
               attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)

    -- import name with optional 'as' alias. 
    alias = (identifier name, identifier? asname)
             attributes (int lineno, int col_offset, int? end_lineno, int? end_col_offset)

    withitem = (expr context_expr, expr? optional_vars)

    match_case = (pattern pattern, expr? guard, stmt* body)

    pattern = MatchValue(expr value)
            | MatchSingleton(constant value)
            | MatchSequence(pattern* patterns)
            | MatchMapping(expr* keys, pattern* patterns, identifier? rest)
            | MatchClass(expr cls, pattern* patterns, identifier* kwd_attrs, pattern* kwd_patterns)

            | MatchStar(identifier? name)
            -- The optional "rest" MatchMapping parameter handles capturing extra mapping keys

            | MatchAs(pattern? pattern, identifier? name)
            | MatchOr(pattern* patterns)

             attributes (int lineno, int col_offset, int end_lineno, int end_col_offset)

    type_ignore = TypeIgnore(int lineno, string tag)
}

Incremental Predictive Value of Serum AST-to-ALT Ratio for Incident Metabolic Syndrome: The ARIRANG Study

Abstract

Aims

The ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) is of great interest as a possible novel marker of metabolic syndrome. However, longitudinal studies emphasizing the incremental predictive value of the AST-to-ALT ratio in diagnosing individuals at higher risk of developing metabolic syndrome are very scarce. Therefore, our study aimed to evaluate the AST-to-ALT ratio as an incremental predictor of new onset metabolic syndrome in a population-based cohort study.

Material and Methods

The population-based cohort study included 2276 adults (903 men and 1373 women) aged 40–70 years, who participated from 2005–2008 (baseline) without metabolic syndrome and were followed up from 2008–2011. Metabolic syndrome was defined according to the harmonized definition of metabolic syndrome. Serum concentrations of AST and ALT were determined by enzymatic methods.

Results

During an average follow-up period of 2.6-years, 395 individuals (17.4%) developed metabolic syndrome. In a multivariable adjusted model, the odds ratio (95% confidence interval) for new onset of metabolic syndrome, comparing the fourth quartile to the first quartile of the AST-to-ALT ratio, was 0. 598 (0.422–0.853). The AST-to-ALT ratio also improved the area under the receiver operating characteristic curve (AUC) for predicting new cases of metabolic syndrome (0.715 vs. 0.732, P = 0.004). The net reclassification improvement of prediction models including the AST-to-ALT ratio was 0.23 (95% CI: 0.124–0.337, P<0.001), and the integrated discrimination improvement was 0.0094 (95% CI: 0.0046–0.0143, P<0.001).

Conclusions

The AST-to-ALT ratio independently predicted the future development of metabolic syndrome and had incremental predictive value for incident metabolic syndrome.

Citation: Yadav D, Choi E, Ahn SV, Baik SK, Cho Yz, Koh SB, et al. (2016) Incremental Predictive Value of Serum AST-to-ALT Ratio for Incident Metabolic Syndrome: The ARIRANG Study. PLoS ONE 11(8):
e0161304.

https://doi.org/10.1371/journal.pone.0161304

Editor: Sheng-Nan Lu, Chang Gung Memorial Hospital Kaohsiung Branch, TAIWAN

Received: April 20, 2016; Accepted: August 3, 2016; Published: August 25, 2016

Copyright: © 2016 Yadav et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This study was supported in part by a grant of the Korea Centers for Disease Control and Prevention (2005-E71013-00, 2006-E71002-00, 2007-E71013-00, 2008-E71004-00, 2009- E71006-00, 2010-E71003-00). There was no additional external funding received for this study.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Metabolic syndrome is a constellation of several cardiovascular risk factors, including hyperglycemia, obesity, high blood pressure, hypertriglyceridemia, and low HDL cholesterol [1]. It is well reported that metabolic syndrome escalates the risk of type 2 diabetes and cardiovascular disease [2–4]. The deadly consequences and elevated prevalence of metabolic syndrome motivates interest in understanding the causes and risk factors in population-based cohort studies. Besides the well-accepted metabolic syndrome components, diverse risk factors also have been recognized as non-traditional components, such as hyperuricemia, microalbuminuria, and non-alcoholic fatty liver disease (NAFLD) [5–7].

A reduced ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) might be a surrogate measure of NAFLD, and is considered to be another aspect of hyperinsulinemia and insulin resistance [6, 8]. An increased AST-to-ALT ratio is strongly suggestive of alcoholic liver disease, whereas a reduced ratio specifies non-alcoholic steatohepatitis [9]. Recent studies have reported that an increased AST-to-ALT ratio is inversely associated with the future development of metabolic syndrome [10, 11]. However, the clinical utility and ability of the AST-to-ALT ratio in predicting metabolic syndrome and its individual components is not well understood. It is also speculated that this ratio could be used as a predictor of incident metabolic syndrome beyond the information contributed by each component of metabolic syndrome among healthy subjects. We hypothesized that a higher AST-to-ALT ratio would serve as a negative predictor of developing metabolic syndrome.

Hence, we studied the prospective association of the AST-to-ALT ratio with the risk of new-onset of metabolic syndrome and its individual components, as well as the discrimination value of the AST-to-ALT ratio in identifying participants who are likely to develop metabolic syndrome in the future. In addition, we calculated net reclassification improvement (NRI) and integrated discrimination index (IDI) to examine the incremental predictive value of the AST-to-ALT ratio as a novel biomarker for predicting future metabolic syndrome.

Material and Methods

Study population

Our study data were collected from the Korean Genome and Epidemiology Study (KoGES), an ongoing multicenter prospective cohort study designed to estimate the prevalence, incidence, and risk factors related with many disorders such as diabetes, hypertension, and cardiovascular disease [12–14]. The study enrolled adults in the rural region of Wonju and Pyeongchang in South Korea.

The baseline period of this study was from November 2005 to January 2008, and involved 5178 adults (2127 men and 3051 women) aged 40–70 years. The first follow-up study was carried out from April 2008–January 2011 and 3862 (74.6%) participants attended (mean time between appointments = 2.6 years). Participants with missing data (n = 16) and diagnosed with metabolic syndrome at baseline (n = 1543) were excluded. We also excluded 27 subjects with a history of cardiovascular disease at baseline. A total of 2276 individuals were involved in the current analysis (903 men and 1373 women) (Fig 1).

Ethics statement

Written consent was obtained from each participant before the commencement of the study. The protocol was approved by the institutional review board (IRB; CR105024-026) of Wonju Severance Christian Hospital.

Data collection and measurements

The study participants completed a health examination including the lifestyle questionnaire, and a medical history. Body weight and height were measured, with the participants barefooted and lightly dressed, and from these measures body mass index (BMI) was calculated. Waist circumference was measured using tape (SECA-200; SECA, Hamburg, Germany). Blood pressure was monitored from the right arm using a mercury sphygmomanometer (Baumanometer, Copiague, NY, USA) after the participant had rested for at least 5 min in a quiet room. Two consecutive measurements of systolic and diastolic pressure were taken at an interval of at least 5 min, and the average of the readings was used. The data for baseline information on smoking status and current alcohol intake was collected using a self-reported questionnaire (yes/no). The heavy drinker group was defined as those whose alcohol consumption exceeded 30 g/day [15].

After fasting for more than 12 h or overnight, venous blood samples were collected from each participant. Blood glucose, serum HDL-cholesterol, triglyceride, LDL-cholesterol (LDL-C), very low density lipoprotein (VLDL) cholesterol, aspartate transaminase (AST), and alanine transaminase (ALT) were measured by enzymatic methods (ADVIA 1650, Siemens, Tarrytown, NY, USA). High-sensitivity C-reactive protein (hs-CRP) was measured using the Denka Seiken (Tokyo, Japan) assay. Fasting insulin and homeostasis model assessment of insulin resistance (HOMA-IR) were also measured [16].

Definition of metabolic syndrome

The end-point of the study was new onset of metabolic syndrome at the follow-up. The harmonized definition was used to diagnose metabolic syndrome in the participants [17, 18].

Statistical methods

Data in this study are expressed as frequencies with percentage, means with standard deviation, or medians with interquartile range. It has been noted that the ratio of AST-to-ALT is used to classify fatty liver disease as alcoholic or non-alcoholic. In our study, we also analyzed the data with the exclusion of heavy drinkers (n = 177) to reveal the association between heavy drinking and liver injury. AST-to-ALT ratio was evaluated as a prediction tool for different components of metabolic syndrome over 2.6 years of follow-up by logistic regression. The odds ratio with 95% confidence intervals (95% CI) was estimated according to increasing quartiles of the AST-to-ALT ratio. The independent association between the baseline AST-to-ALT ratio and the onset of metabolic syndrome was analyzed by multivariate logistic regression. We utilized three models for the adjustment. First, we executed an age-related analysis. Second, we adjusted for age, BMI, LDL cholesterol, regular exercise, and smoking. Third, we adjusted for the factors in the second analysis with the addition of hs-CRP levels and HOMA-IR.

To calculate the added discrimination or incremental effect contributed by the AST-to-ALT ratio to predict future participants diagnosed with metabolic syndrome beyond the information furnished by the different components of the metabolic syndrome, our study analyzed the areas under the receiver operating characteristic curve (AUC) in models that contained HDL-cholesterol, waist circumference, systolic and diastolic blood pressure, triglycerides, and fasting glucose, with and without the AST-to-ALT ratio. Additionally, we calculated the category-free NRI and IDI for models with and without the AST-to-ALT ratio, to measure the improvement of corrected reclassification and sensitivity based on the addition of the serum AST-to-ALT ratio to the logistic model. NRI represents the difference between the proportion of participants moving up and the proportion of participants moving down for the development of metabolic syndrome, as well as the corresponding difference in proportions for those who did not have metabolic syndrome, by obtaining the difference of these two differences [19]. IDI represents the difference between the integrated difference in sensitivity and the integrated difference in one minus specificity for models with and without the new biomarker [20]. A P-value less than 0.05 was considered statistically significant, and all statistical analyses were accomplished using SAS, version 9.2 (SAS Institute, Cary, NC, USA).

Results

Patient characteristics

After an average follow-up of 2.6 years, 395 (17.4%) participants developed metabolic syndrome. The incidence of metabolic syndrome was similar after excluding heavy drinkers from the study. Baseline characteristics of the study subjects, categorized according to whether or not they had metabolic syndrome at follow-up, are shown in Table 1. Subjects who developed metabolic syndrome at follow-up were older and had significantly higher waist circumference, BMI, fasting blood glucose, blood pressure, LDL cholesterol, triglycerides, and HOMA-IR values than the non-metabolic syndrome participants.

Table 1. Baseline characteristics of the study subjects stratified by incident metabolic syndrome, and evaluation of the AST-to-ALT ratio in relation to the number of metabolic parameters used to define metabolic syndrome at follow-up.

https://doi.org/10.1371/journal.pone.0161304.t001

HDL-cholesterol and the AST-to-ALT ratio were significantly lower in participants who developed metabolic syndrome than in those who did not (all P<0.0001). The prevalence of smoking was significantly higher in the metabolic syndrome group (P<0.05), while there were no significant differences in regular exercise or current alcohol intake between the two groups. The estimates were similar when we excluded heavy drinkers from our analysis, except for smoking status, which nevertheless was found to not be significant. The elevated level of hs-CRP did not show any statistically significant difference between the metabolic syndrome group and the non-metabolic syndrome group. The AST-to-ALT ratio at baseline constantly decreased with the number of metabolic syndrome components developed in study subjects over the 2.6 years of follow-up (P for trend <0.0001). Moreover, we analyzed the data in a cross-sectional manner and the data corroborated the results of the prospective study analysis after 2.6 years of follow-up (Table A and B in S1 Tables).

Multivariate Analysis for Predicting the Risk of Metabolic Syndrome According to Quartile Increment of AST-to-ALT ratio

We divided the study population into quartiles of AST-to-ALT ratios with cut-offs of 1.04, 1.25, and 1.5, and evaluated the association between baseline AST-to-ALT ratio and incident metabolic syndrome and its individual components at the follow-up visit. The incidence of metabolic syndrome in the first quartile of the AST-to-ALT ratio was 25.87%, which was reduced significantly to 18.68%, 12.5%, and 12.2% in the successive quartiles (Table 2). The crude odds ratio for the development of metabolic syndrome, comparing individuals in the fourth quartile with those in the first quartile of the AST-to-ALT ratio, was 0.398 (0.288–0.551, P for trend <0.0001). When the highest quartile of the AST-to-ALT ratio was compared with the first quartile, the age-adjusted odds ratio (95% CI) of metabolic syndrome was 0.364 (0.262–0.505) in all subjects and 0.367 (0.261–0.517) after excluding heavy drinkers. In the multivariate-adjusted model (Table 2), when the highest quartile of the AST-to-ALT ratio was compared to the lowest quartile, the odds ratio for the onset of metabolic syndrome was 0.598 (0.420–0.853, P = 0.0004). The analysis was repeated with the exclusion of heavy drinkers, as shown in Table 2, and the results were consistent. We calculated the odds ratio and 95% CI for incident metabolic syndrome based on the serial change of AST-to -ALT ratio. After adjustment for several confounding factors (i.e., model 3), the odds ratio for incident metabolic syndrome in the highest quartile of serial change of AST-to-ALT ratio compared with the lowest quartile of change in AST-to-ALT ratio was 0.796 (0.570–1.113), P = 0.1751. The study did not observe any significant difference for onset of metabolic syndrome stratified by the serial changes of AST-to-ALT ratio in all participants as well as after excluding heavy drinkers (Table C in S1 Tables). The study also analyzed the odds ratio for incident metabolic syndrome based on the quartiles of ALT and GGT levels (Table D in S1 Tables).

Odds Ratio for Each Component of Metabolic Syndrome Classified by the Baseline AST-to-ALT ratio

Table 3 displays the odds ratios for each component of metabolic syndrome, stratified by the baseline AST-to-ALT ratio. Subjects in the lowest AST-to-ALT ratio quartile had significantly higher odds for abnormal components of metabolic syndrome than those in the other three quartiles. Upon comparison with subjects in the first quartile of the AST-to-ALT ratio, subjects in the fourth quartile had significantly lower odds ratios for metabolic abnormalities, i.e., waist circumference, blood pressure, triglycerides, and blood glucose, in spite of not having any significant differences in HDL cholesterol. The crude odds ratios (95% CI) for large waist circumference, high triglycerides, low HDL cholesterol, elevated blood pressure, and elevated blood glucose were 0.331 (0.25–0.44), 0.450 (0.332–0.611), 0.889 (0.7–1.129), 0.814 (0.631–1.05), and 0.618 (0.451–0.847), respectively. Similar results were obtained after repeating the logistic analysis for subjects who were heavy alcohol drinkers.

The Additional Contribution of AST-to-ALT ratio to Predicting Risk of High Metabolic Syndrome

The consistency observed in the association between the AST-to-ALT ratio and the risk of metabolic syndrome in the further analysis centered on all subjects in this cohort study. First, we measured the AUC of the AST-to-ALT ratio, ALT, GGT, and AST levels to predict the development of metabolic syndrome (Table E in S1 Tables). The AUCs for AST-to-ALT, ALT, and GGT were 0.611 (0.580–0.642), 0.604 (0.573–0.635), and 0.601(0.571–0.630), respectively. The baseline risk factors of metabolic syndrome and additional AST-to-ALT ratio model are shown in Table 4 to predict the future development of metabolic syndrome obtained with an AUC. The addition of the AST-to-ALT ratios to the models of individual components of metabolic syndrome significantly increased the AUCs. We also evaluated the prediction of new cases of metabolic syndrome by baseline variables of AST-to-ALT ratio over and above the information contributed by individual component of metabolic syndrome. The AUC predicts incident metabolic syndrome employing each component of metabolic syndrome (large waist circumference, high triglycerides, low HDL cholesterol, high blood pressure, and high blood glucose) to be 0.715 (0.688–0.741). After the AST-to-ALT ratio was added to this model, the resulting AUC was 0.732 (95% CI: 0.706–0.758, P = 0.0043) (Fig 2). We also calculated the additional predictive ability of other enzymes ALT, GGT, and AST to predict the future risk of developing metabolic syndrome beyond the information presented by different components of metabolic syndrome (Table F in S1 Tables).

To measure the ability of the baseline AST-to-ALT ratio to predict the future onset of metabolic syndrome, we also calculated the ideal cut-off value of the AST-to-ALT ratio to define a discretional component of metabolic syndrome by the Youden index, which was 1.15 (data not shown). The NRI and IDI for prediction models including AST-to-ALT ratio were 0.23 (95% CI: 0.124–0.337, P<0.0001) and 0.0094 (95% CI: 0.0046–0.0143, p<0.0001).

Discussion

In this longitudinal cohort study, we observed that the serum AST-to-ALT ratio was an independent negative predictor of the onset of metabolic syndrome and its individual components, except for HDL cholesterol, in the general Korean population. This independent relationship between the AST-to-ALT ratio and metabolic syndrome was not gender-biased and was unaffected by the exclusion of heavy drinkers. Moreover, our study showed that the serum AST-to-ALT ratio may improve the predictive power to accurately identify participants with risk for incident metabolic syndrome, beyond the information contributed by each of its components.

The serum AST-to-ALT ratio serves as a proxy measure for NAFLD and was shown to be inversely associated with metabolic syndrome and insulin resistance in clinical and epidemiological studies [9, 21, 22]. Despite strong evidence about the association between the AST-to-ALT ratio and obesity-related metabolic disorders, there have been little data from prospective studies based on the incremental predictive value of the serum AST-to-ALT ratio for the onset of metabolic syndrome [10, 23]. In our study, an increasing AST-to-ALT ratio was correlated with a consistent reduction in the onset of metabolic syndrome and its components. The prospective design, dose-dependent relationship and robustness of the association imply that the AST-to-ALT ratio may play a major role in the future diagnosis of metabolic syndrome.

We found that AUC was improved in the model in which the AST-to-ALT ratio was added to the metabolic syndrome components (0.715 to 0.732, P<0.0043). This indicates that the AST-to-ALT ratio enables the identification of incident metabolic syndrome independent of conventional risk assessment. We also used NRI and IDI to evaluate the prediction performance when the new biomarker (AST-to-ALT ratio) was added to a conventional metabolic syndrome risk model. The category-free NRI was 23% in our prospective cohort, which means that 23% of individuals in our study population were classified in the correct direction. Indeed, both NRI and IDI are more sensitive than AUC for stabilizing improvement in the predictive value [14, 24]. Improvements in the NRI, IDI, and c-statistics revealed that the AST-to-ALT ratio could have clinical importance in screening for the risk of metabolic syndrome, beyond the information suggested by traditional risk factors.

The relationship between metabolic syndrome and NAFLD or liver enzyme levels has been well established by liver biopsies, which are considered the gold standard for diagnosing NAFLD, although we did not use liver biopsies to confirm NAFLD-associated liver damage. Still, AST and ALT have been used as noninvasive surrogate markers of liver damage in epidemiological studies [25, 26] and the serum AST-to-ALT ratio is independently associated with metabolic syndrome and its components, consistent with the results of other studies in people of different ethnic origins [23, 27]. Moreover, some studies have reported that a possible mechanism for the association of the AST-to-ALT ratio with metabolic syndrome could be increased hepatic fat content [28], which adversely affects each component of metabolic syndrome. Another mechanism may involve an inflammatory effect in the liver that impairs insulin signaling, leading to a failure to suppress glucose production, and ultimately hyperglycemia [29–31]. Indeed, our results also indicate that the quartiles of AST-to-ALT ratios significantly predict hyperglycemia.

Recently, one study proposed that the liver enzyme ratio is the best surrogate marker of insulin resistance among non-obese Japanese adults [32]. Our study agrees with studies of particular adjusted models in the Korean and Chinese populations, wherein the liver enzyme ALT was significantly associated with metabolic syndrome, independent of insulin resistance measured by HOMA-IR [33, 34]. However, the above studies were focused on ALT (not AST), so we cannot confirm whether a similar relationship would exist with AST. Here, we used the HOMA index to estimate insulin resistance rather than the hyperinsulinemic-euglycemic clamp, which is invasive and requires a prolonged testing time, although many clinical trials have reported a good correlation between the two procedures for the assessment of insulin resistance [35, 36]. Additionally, we observed an independent association of the AST-to-ALT ratio and new onset of metabolic syndrome after adjustment for the potential inflammatory marker, hs-CRP. A possible explanation for the above result is the interaction between insulin resistance and hs-CRP. Insulin resistance is known to be involved with chronic inflammation, which is distinguished by elevated cytokine release and the activation of pro-inflammatory pathways [37, 38], indicating that insulin resistance may precede elevated hs-CRP by attenuating insulin-induced suppression of hepatic acute-phase plasma protein [39]. The exact mechanism by which insulin resistance, hs-CRP, and metabolic syndrome are related is still not clear in epidemiological studies. The above results and further adjustments suggest that the AST-to-ALT ratio has subsidiary physiopathology, distinct from other established risk factors. Our study clearly defines this uniqueness of the NAFLD marker, the AST-to-ALT ratio, as a prerequisite for diagnosing metabolic syndrome, but further verification is needed from long-term epidemiological studies.

Our study has several limitations. First, this study included middle-aged and elderly people living in rural settings with proportionately higher cases of metabolic syndrome [14]. Nonetheless, our cohort observed a similar pattern in the prevalence of metabolic syndrome to that of the Korean National Health and Nutrition Examination Survey (KNHANES) [12, 40, 41]. Moreover, the lifestyle change in Korea towards the Western pattern seems to be the primary cause for the increasing risk of metabolic syndrome. The time period of our study denoted a rapid increase in the prevalence rate of metabolic syndrome; therefore, it may not be extrapolated to other ethnic populations. Second, our study follow-up period was short, and thus we could not evaluate whether the association between the AST-to-ALT ratio and the onset of metabolic syndrome would endure long-term. Third, we could not eliminate the probability of confounding influences by viral liver disease. However, in previous reports from the third KNHANES, the prevalence of hepatitis B virus (HBV) infection among Korean adults over 40 years of age was 4% (4.2% for men and 3.8% for women [42]). Therefore, this could not have been a major confounder in our study population. Finally, a single assessment of serum AST and ALT is not adequate to examine the extent of liver inflammation, and thus we may have underemphasized the strength of the association.

In conclusion, the results of this study confirm the existence of an independent relationship between the AST-to-ALT ratio (a liver injury marker) and incident metabolic syndrome, as well as its components, in a prospective cohort study. Our findings suggest that the AST-to-ALT ratio should be considered clinically important for the evaluation of future risk of developing metabolic syndrome. This marker may be a useful tool with which clinicians can stratify cardiometabolic risk in population-based studies.

Supporting Information

S1 Tables.

Table A. Baseline characteristics of the study subjects stratified by metabolic syndrome, and evaluation of the AST-to-ALT ratio in relation to the number of individual components of metabolic syndrome at baseline; Table B. Odds ratio and 95% confidence interval (CI) for the prevalence of metabolic syndrome according to the different quartiles of AST-to-ALT ratio; Table C. Odds ratio and 95% confidence interval (CI) for new-onset metabolic syndrome according to serial change quartiles of AST-to-ALT ratios; Table D. Odds ratio and 95% confidence interval (CI) for new-onset of metabolic syndrome according to different quartiles of ALT and GGT levels; Table E. The AUC curve of AST-to-ALT ratio, ALT, GGT, and AST levels to predict the development of metabolic syndrome; Table F. Comparison of the AUC curves for 5 components and additional predictive ability of the AST-to-ALT ratio, ALT, GGT, and AST for the future risk of metabolic syndrome.

https://doi.org/10.1371/journal.pone.0161304.s002

(DOCX)

Acknowledgments

We are very grateful to all the participants in the KoGES-ARIRANG study for their continuing interest and participation in the study.

Author Contributions

  1. Conceptualization: DY JYK SVA SBK.
  2. Data curation: EHC SVA SBK JYK.
  3. Formal analysis: EHC SVA SBK JYK.
  4. Funding acquisition: JYK.
  5. Investigation: DY SVA SBK JYK.
  6. Methodology: DY SVA SBK JYK.
  7. Project administration: EHC JYK.
  8. Resources: DY SVA SBK JHH SKB YZC JYK.
  9. Software: EHC SVA SBK.
  10. Supervision: DY EHC JYK.
  11. Validation: DY EHC SVA SBK JHH SKB YZC YSC KCS JYK.
  12. Visualization: DY EHC JHH YSC JYK.
  13. Writing – original draft: DY EHC JHH SKB YZC YSC KCS JYK.
  14. Writing – review & editing: DY EHC JHH YSC KCS JYK.

References

  1. 1.
    Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C. Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004;109(3):433–8. Epub 2004/01/28. pmid:14744958.
  2. 2.
    Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M, et al. Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes care. 2001;24(4):683–9. Epub 2001/04/24. pmid:11315831.
  3. 3.
    Lorenzo C, Okoloise M, Williams K, Stern MP, Haffner SM. The metabolic syndrome as predictor of type 2 diabetes: the San Antonio heart study. Diabetes care. 2003;26(11):3153–9. Epub 2003/10/28. pmid:14578254.
  4. 4.
    Hunt KJ, Resendez RG, Williams K, Haffner SM, Stern MP. National Cholesterol Education Program versus World Health Organization metabolic syndrome in relation to all-cause and cardiovascular mortality in the San Antonio Heart Study. Circulation. 2004;110(10):1251–7. Epub 2004/08/25. pmid:15326061.
  5. 5.
    Invitti C, Maffeis C, Gilardini L, Pontiggia B, Mazzilli G, Girola A, et al. Metabolic syndrome in obese Caucasian children: prevalence using WHO-derived criteria and association with nontraditional cardiovascular risk factors. Int J Obes (Lond). 2006;30(4):627–33. Epub 2006/03/30. pmid:16570092.
  6. 6.
    Marchesini G, Brizi M, Bianchi G, Tomassetti S, Bugianesi E, Lenzi M, et al. Nonalcoholic fatty liver disease: a feature of the metabolic syndrome. Diabetes. 2001;50(8):1844–50. Epub 2001/07/27. pmid:11473047.
  7. 7.
    Zhang ML, Gao YX, Wang X, Chang H, Huang GW. Serum uric acid and appropriate cutoff value for prediction of metabolic syndrome among Chinese adults. J Clin Biochem Nutr. 2013;52(1):38–42. Epub 2013/01/24. pmid:23341696; PubMed Central PMCID: PMCPmc3541417.
  8. 8.
    Cortez-Pinto H, Camilo ME, Baptista A, De Oliveira AG, De Moura MC. Non-alcoholic fatty liver: another feature of the metabolic syndrome? Clin Nutr. 1999;18(6):353–8. Epub 2000/01/15. pmid:10634920.
  9. 9.
    Sorbi D, Boynton J, Lindor KD. The ratio of aspartate aminotransferase to alanine aminotransferase: potential value in differentiating nonalcoholic steatohepatitis from alcoholic liver disease. The American journal of gastroenterology. 1999;94(4):1018–22. Epub 1999/04/14. pmid:10201476.
  10. 10.
    Lee K, Yang JH. Which liver enzymes are better indicators of metabolic syndrome in adolescents: the Fifth Korea National Health and Nutrition Examination Survey, 2010. Metab Syndr Relat Disord. 2013;11(4):229–35. Epub 2013/03/05. pmid:23451816.
  11. 11.
    Perera S, Lohsoonthorn V, Jiamjarasrangsi W, Lertmaharit S, Williams MA. Association between elevated liver enzymes and metabolic syndrome among Thai adults. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2008;2(3):171–8.
  12. 12.
    Koh SB, Park JK, Yoon JH, Chang SJ, Oh SS, Kim JY, et al. Preliminary report: a serious link between adiponectin levels and metabolic syndrome in a Korean nondiabetic population. Metabolism: clinical and experimental. 2010;59(3):333–7. Epub 2009/10/03. pmid:19796779.
  13. 13.
    Koh SB, Yoon J, Kim JY, Yoo BS, Lee SH, Park JK, et al. Relationships between serum adiponectin with metabolic syndrome and components of metabolic syndrome in non-diabetic Koreans: ARIRANG study. Yonsei medical journal. 2011;52(2):234–41. Epub 2011/02/15. pmid:21319340; PubMed Central PMCID: PMCPMC3051212.
  14. 14.
    Kim JY, Ahn SV, Yoon JH, Koh SB, Yoon J, Yoo BS, et al. Prospective study of serum adiponectin and incident metabolic syndrome: the ARIRANG study. Diabetes care. 2013;36(6):1547–53. Epub 2013/01/01. pmid:23275369; PubMed Central PMCID: PMCPMC3661834.
  15. 15.
    Rosell M, De Faire U, Hellenius ML. Low prevalence of the metabolic syndrome in wine drinkers—is it the alcohol beverage or the lifestyle? European journal of clinical nutrition. 2003;57(2):227–34. Epub 2003/02/07. pmid:12571653.
  16. 16.
    Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412–9. Epub 1985/07/01. pmid:3899825.
  17. 17.
    Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120(16):1640–5. Epub 2009/10/07. pmid:19805654.
  18. 18.
    Yadav D, Lee ES, Kim HM, Choi E, Lee EY, Lim JS, et al. Prospective study of serum uric acid levels and incident metabolic syndrome in a Korean rural cohort. Atherosclerosis. 2015;241(1):271–7. Epub 2015/05/11. pmid:25957887.
  19. 19.
    Pencina MJ, D’Agostino RB Sr., Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Statistics in medicine. 2011;30(1):11–21. Epub 2011/01/05. pmid:21204120; PubMed Central PMCID: PMCPmc3341973.
  20. 20.
    Steyerberg EW, Vickers AJ, Cook NR, Gerds T, Gonen M, Obuchowski N, et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology (Cambridge, Mass). 2010;21(1):128–38. Epub 2009/12/17. pmid:20010215; PubMed Central PMCID: PMCPmc3575184.
  21. 21.
    Targher G, Day CP, Bonora E. Risk of cardiovascular disease in patients with nonalcoholic fatty liver disease. The New England journal of medicine. 2010;363(14):1341–50. Epub 2010/10/01. pmid:20879883.
  22. 22.
    Sidorenkov O, Nilssen O, Grjibovski AM. Metabolic syndrome in Russian adults: associated factors and mortality from cardiovascular diseases and all causes. BMC public health. 2010;10:582. Epub 2010/10/06. pmid:20920226; PubMed Central PMCID: PMCPMC2955695.
  23. 23.
    Hanley AJ, Williams K, Festa A, Wagenknecht LE, D’Agostino RB Jr., Haffner SM. Liver markers and development of the metabolic syndrome: the insulin resistance atherosclerosis study. Diabetes. 2005;54(11):3140–7. Epub 2005/10/27. pmid:16249437.
  24. 24.
    Pencina MJ, D’Agostino RB Sr., D’Agostino RB Jr., Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Statistics in medicine. 2008;27(2):157–72; discussion 207–12. Epub 2007/06/15. pmid:17569110.
  25. 25.
    Clark JM, Diehl AM. Nonalcoholic fatty liver disease: an underrecognized cause of cryptogenic cirrhosis. Jama. 2003;289(22):3000–4. Epub 2003/06/12. pmid:12799409.
  26. 26.
    Clark JM, Brancati FL, Diehl AM. The prevalence and etiology of elevated aminotransferase levels in the United States. The American journal of gastroenterology. 2003;98(5):960–7. Epub 2003/06/18. pmid:12809815.
  27. 27.
    Tzima N, Pitsavos C, Panagiotakos DB, Chrysohoou C, Polychronopoulos E, Skoumas J, et al. Adherence to the Mediterranean diet moderates the association of aminotransferases with the prevalence of the metabolic syndrome; the ATTICA study. Nutrition & metabolism. 2009;6:30. Epub 2009/08/01. pmid:19642977; PubMed Central PMCID: PMCPMC2726146.
  28. 28.
    Browning JD, Szczepaniak LS, Dobbins R, Nuremberg P, Horton JD, Cohen JC, et al. Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity. Hepatology (Baltimore, Md). 2004;40(6):1387–95. Epub 2004/11/27. pmid:15565570.
  29. 29.
    Malnick SD, Beergabel M, Knobler H. Non-alcoholic fatty liver: a common manifestation of a metabolic disorder. QJM: monthly journal of the Association of Physicians. 2003;96(10):699–709. Epub 2003/09/23. pmid:14500857.
  30. 30.
    Hotamisligil GS. Inflammatory pathways and insulin action. International journal of obesity and related metabolic disorders: journal of the International Association for the Study of Obesity. 2003;27 Suppl 3:S53–5. Epub 2004/01/06. pmid:14704746.
  31. 31.
    Hsueh WA, Quinones MJ. Role of endothelial dysfunction in insulin resistance. The American journal of cardiology. 2003;92(4A):10J–7J. Epub 2003/09/06. pmid:12957322.
  32. 32.
    Kawamoto R, Kohara K, Kusunoki T, Tabara Y, Abe M, Miki T. Alanine aminotransferase/aspartate aminotransferase ratio is the best surrogate marker for insulin resistance in non-obese Japanese adults. Cardiovascular diabetology. 2012;11:117. Epub 2012/10/02. pmid:23020992; PubMed Central PMCID: PMCPMC3499385.
  33. 33.
    Yun JE, Kim SY, Kang HC, Lee SJ, Kimm H, Jee SH. Alanine aminotransferase is associated with metabolic syndrome independently of insulin resistance. Circulation journal: official journal of the Japanese Circulation Society. 2011;75(4):964–9. Epub 2011/02/10. pmid:21304212.
  34. 34.
    Xu Y, Bi YF, Xu M, Huang Y, Lu WY, Gu YF, et al. Cross-sectional and longitudinal association of serum alanine aminotransaminase and gamma-glutamyltransferase with metabolic syndrome in middle-aged and elderly Chinese people. Journal of diabetes. 2011;3(1):38–47. Epub 2011/01/05. pmid:21199427.
  35. 35.
    Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes care. 2000;23(1):57–63. Epub 2000/06/17. pmid:10857969.
  36. 36.
    Emoto M, Nishizawa Y, Maekawa K, Hiura Y, Kanda H, Kawagishi T, et al. Homeostasis model assessment as a clinical index of insulin resistance in type 2 diabetic patients treated with sulfonylureas. Diabetes care. 1999;22(5):818–22. Epub 1999/05/20. pmid:10332688.
  37. 37.
    Wellen KE, Hotamisligil GS. Obesity-induced inflammatory changes in adipose tissue. The Journal of clinical investigation. 2003;112(12):1785–8. Epub 2003/12/18. pmid:14679172; PubMed Central PMCID: PMCPMC297006.
  38. 38.
    Ryu SY, Kim KS, Park J, Kang MG, Han MA. The association between circulating inflammatory markers and metabolic syndrome in Korean rural adults. Journal of preventive medicine and public health = Yebang Uihakhoe chi. 2008;41(6):413–8. Epub 2008/11/28. pmid:19037171.
  39. 39.
    Campos SP, Baumann H. Insulin is a prominent modulator of the cytokine-stimulated expression of acute-phase plasma protein genes. Molecular and cellular biology. 1992;12(4):1789–97. Epub 1992/04/01. pmid:1372389; PubMed Central PMCID: PMCPMC369622.
  40. 40.
    Kim Y. The Korea National Health and Nutrition Examination Survey (KNHANES): current status and challenges. Epidemiology and health. 2014;36:e2014002. Epub 2014/05/20. pmid:24839580.
  41. 41.
    Lim S, Shin H, Song JH, Kwak SH, Kang SM, Won Yoon J, et al. Increasing prevalence of metabolic syndrome in Korea: the Korean National Health and Nutrition Examination Survey for 1998–2007. Diabetes care. 2011;34(6):1323–8. Epub 2011/04/21. pmid:21505206; PubMed Central PMCID: PMCPmc3114326.
  42. 42.
    Ministry of Health & Welfare. The Third Korea National Health and Nutrition Examination Survey (KNHANES III), 2005: Health Examination. Seoul, Korea: Ministry of Health & Welfare; 2006.

Designers Fountain 6021-AST Value Collection Wall Sconces with Accent Caps, European Gold/Distressed Bronze, White – Wall Scones


Price: $41.25$41.25

+ $51.28
shipping

$51.28 Shipping & Import Fees Deposit to Russian Federation Details

Available at a lower price from other sellers that may not offer free Prime shipping.

Power Source Corded-electric
Material Stone
Style Modern
Mounting Type Protruding
Special Feature Three finish caps included: Distressed Bronze, European Gold, and Sandstone

  • Make sure this fits by entering your model number.
  • Scavo glass shade and 3 accent caps included (distressed bronze, European gold, sandstone)
  • Steel construction built to last
  • Uses (1) 100 watt bulb not included
  • Easy to install up or down

› See more product details

GWAS of serum ALT and AST reveals an association of SLC30A10 Thr95Ile with hypermanganesemia symptoms

  • 1.

    Asrani, S. K., Devarbhavi, H., Eaton, J. & Kamath, P. S. Burden of liver diseases in the world. J. Hepatol. 70, 151–171 (2019).

    PubMed 
    Article 

    Google Scholar 

  • 2.

    Younossi, Z. M. et al. Changes in the prevalence of the most common causes of chronic liver diseases in the United States from 1988 to 2008. Clin. Gastroenterol. Hepatol. 9, 524–530.e1; quiz e60. (2011).

    PubMed 
    Article 

    Google Scholar 

  • 3.

    Plenge, R. M., Scolnick, E. M. & Altshuler, D. Validating therapeutic targets through human genetics. Nat. Rev. Drug Disco. 12, 581–594 (2013).

    CAS 
    Article 

    Google Scholar 

  • 4.

    Stevens, J. L. & Baker, T. K. The future of drug safety testing: expanding the view and narrowing the focus. Drug Disco. Today 14, 162–167 (2009).

    Article 

    Google Scholar 

  • 5.

    Deaton, A. M. et al. Rationalizing secondary pharmacology screening using human genetic and pharmacological evidence. Toxicol. Sci. 167, 593–603 (2019).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 6.

    van Beek, J. H. et al. The genetic architecture of liver enzyme levels: GGT, ALT and AST. Behav. Genet 43, 329–339 (2013).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 7.

    Pratt, D. S. & Kaplan, M. M. Evaluation of abnormal liver-enzyme results in asymptomatic patients. N. Engl. J. Med. 342, 1266–1271 (2000).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 8.

    Rahmioglu, N. et al. Epidemiology and genetic epidemiology of the liver function test proteins. PLoS ONE 4, e4435 (2009).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 9.

    Pilia, G. et al. Heritability of cardiovascular and personality traits in 6,148 Sardinians. PLoS Genet. 2, e132 (2006).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 10.

    Makkonen, J., Pietilainen, K. H., Rissanen, A., Kaprio, J. & Yki-Jarvinen, H. Genetic factors contribute to variation in serum alanine aminotransferase activity independent of obesity and alcohol: a study in monozygotic and dizygotic twins. J. Hepatol. 50, 1035–1042 (2009).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 11.

    Nilsson, S. E., Read, S., Berg, S. & Johansson, B. Heritabilities for fifteen routine biochemical values: findings in 215 Swedish twin pairs 82 years of age or older. Scand. J. Clin. Lab. Invest. 69, 562–569 (2009).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 12.

    Bathum, L. et al. Evidence for a substantial genetic influence on biochemical liver function tests: results from a population-based Danish twin study. Clin. Chem. 47, 81–87 (2001).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 13.

    Targher, G. Elevated serum gamma-glutamyltransferase activity is associated with increased risk of mortality, incident type 2 diabetes, cardiovascular events, chronic kidney disease and cancer—a narrative review. Clin. Chem. Lab. Med. 48, 147–157 (2010).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 14.

    Chambers, J. C. et al. Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma. Nat. Genet. 43, 1131–1138 (2011).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 15.

    Young, K. A. et al. Genome-wide association study identifies loci for liver enzyme concentrations in Mexican Americans: The GUARDIAN Consortium. Obes. (Silver Spring) 27, 1331–1337 (2019).

    CAS 
    Article 

    Google Scholar 

  • 16.

    Park, T. J. et al. Genome-wide association study of liver enzymes in korean children. Genomics Inf. 11, 149–154 (2013).

    Article 

    Google Scholar 

  • 17.

    Moon, S. et al. The Korea Biobank Array: design and identification of coding variants associated with blood biochemical traits. Sci. Rep. 9, 1382 (2019).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 18.

    Kanai, M. et al. Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases. Nat. Genet. 50, 390–400 (2018).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 19.

    Kamatani, Y. et al. Genome-wide association study of hematological and biochemical traits in a Japanese population. Nat. Genet. 42, 210–215 (2010).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 20.

    Kim, Y. J. et al. Large-scale genome-wide association studies in East Asians identify new genetic loci influencing metabolic traits. Nat. Genet. 43, 990–995 (2011).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 21.

    Prins, B. P. et al. Genome-wide analysis of health-related biomarkers in the UK Household Longitudinal Study reveals novel associations. Sci. Rep. 7, 11008 (2017).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 22.

    Namjou, B. et al. GWAS and enrichment analyses of non-alcoholic fatty liver disease identify new trait-associated genes and pathways across eMERGE Network. BMC Med. 17, 135 (2019).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 23.

    Gurdasani, D. et al. Uganda genome resource enables insights into population history and genomic discovery in Africa. Cell 179, 984–1002.e1036 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 24.

    Gilly, A. et al. Very low-depth whole-genome sequencing in complex trait association studies. Bioinformatics 35, 2555–2561 (2019).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 25.

    Romeo, S. et al. Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease. Nat. Genet 40, 1461–1465 (2008).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 26.

    Abul-Husn, N. S. et al. A Protein-Truncating HSD17B13 Variant and Protection from Chronic Liver Disease. N. Engl. J. Med. 378, 1096–1106 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 27.

    Seve, M., Chimienti, F., Devergnas, S. & Favier, A. In silico identification and expression of SLC30 family genes: an expressed sequence tag data mining strategy for the characterization of zinc transporters’ tissue expression. BMC Genomics 5, 32 (2004).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 28.

    Tuschl, K. et al. Syndrome of hepatic cirrhosis, dystonia, polycythemia, and hypermanganesemia caused by mutations in SLC30A10, a manganese transporter in man. Am. J. Hum. Genet. 90, 457–466 (2012).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 29.

    Brna, P., Gordon, K., Dooley, J. M. & Price, V. Manganese toxicity in a child with iron deficiency and polycythemia. J. Child Neurol. 26, 891–894 (2011).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 30.

    Gospe, S. M. Jr. et al. Paraparesis, hypermanganesaemia, and polycythaemia: a novel presentation of cirrhosis. Arch. Dis. Child 83, 439–442 (2000).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 31.

    Lechpammer, M. et al. Pathology of inherited manganese transporter deficiency. Ann. Neurol. 75, 608–612 (2014).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 32.

    Quadri, M. et al. Mutations in SLC30A10 cause parkinsonism and dystonia with hypermanganesemia, polycythemia, and chronic liver disease. Am. J. Hum. Genet. 90, 467–477 (2012).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 33.

    Sahni, V. et al. Case report: a metabolic disorder presenting as pediatric manganism. Environ. Health Perspect. 115, 1776–1779 (2007).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 34.

    Tuschl, K. et al. Hepatic cirrhosis, dystonia, polycythaemia and hypermanganesaemia—a new metabolic disorder. J. Inherit. Metab. Dis. 31, 151–163 (2008).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 35.

    Brantly, M., Nukiwa, T. & Crystal, R. G. Molecular basis of alpha-1-antitrypsin deficiency. Am. J. Med 84, 13–31 (1988).

    PubMed 
    Article 

    Google Scholar 

  • 36.

    Weedon, M. N. et al. Use of SNP chips to detect rare pathogenic variants: retrospective, population based diagnostic evaluation. BMJ 372, n214 (2021).

    Google Scholar 

  • 37.

    Dewey, F. E. et al. Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study. Science 354, aaf6814 (2016).

    PubMed 
    Article 
    CAS 

    Google Scholar 

  • 38.

    Partnership, A. M. Common Metabolic Diseases Knowledge Portal, http://hugeamp.org/ Accessed December 2020.

  • 39.

    Emdin, C. A. et al. A missense variant in Mitochondrial Amidoxime Reducing Component 1 gene and protection against liver disease. PLoS Genet. 16, e1008629 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 40.

    Speliotes, E. K. et al. Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits. PLoS Genet 7, e1001324 (2011).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 41.

    Strunz, T. et al. A mega-analysis of expression quantitative trait loci (eQTL) provides insight into the regulatory architecture of gene expression variation in liver. Sci. Rep. 8, 5865 (2018).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 42.

    Ng, E. et al. Genome-wide association study of toxic metals and trace elements reveals novel associations. Hum. Mol. Genet. 24, 4739–4745 (2015).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 43.

    Corre, T. et al. Common variants in CLDN14 are associated with differential excretion of magnesium over calcium in urine. Pflug. Arch. 469, 91–103 (2017).

    CAS 
    Article 

    Google Scholar 

  • 44.

    Kichaev, G. et al. Leveraging polygenic functional enrichment to improve GWAS power. Am. J. Hum. Genet. 104, 65–75 (2019).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 45.

    Astle, W. J. et al. The allelic landscape of human blood cell trait variation and links to common complex disease. Cell 167, 1415–1429.e1419 (2016).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 46.

    Tian, D. et al. GWAS Atlas: a curated resource of genome-wide variant-trait associations in plants and animals. Nucleic Acids Res 48, D927–D932 (2020).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 47.

    Kim, S. K. Identification of 613 new loci associated with heel bone mineral density and a polygenic risk score for bone mineral density, osteoporosis and fracture. PLoS ONE 13, e0200785 (2018).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 48.

    Morris, J. A. et al. An atlas of genetic influences on osteoporosis in humans and mice. Nat. Genet. 51, 258–266 (2019).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 49.

    Kemp, J. P. et al. Identification of 153 new loci associated with heel bone mineral density and functional involvement of GPC6 in osteoporosis. Nat. Genet. 49, 1468–1475 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 50.

    Parisinos, C. A. et al. Genome-wide and Mendelian randomisation studies of liver MRI yield insights into the pathogenesis of steatohepatitis. J. Hepatol.https://doi.org/10.1016/j.jhep.2020.03.032 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 51.

    Trieb, M. et al. Liver disease alters high-density lipoprotein composition, metabolism and function. Biochim. Biophys. Acta 1861, 630–638 (2016).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 52.

    Aguet, F. et al. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 (2020)

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 53.

    Ramachandran, P. et al. Resolving the fibrotic niche of human liver cirrhosis at single-cell level. Nature 575, 512–518 (2019).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 54.

    MacParland, S. A. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 55.

    Aizarani, N. et al. A human liver cell atlas reveals heterogeneity and epithelial progenitors. Nature 572, 199–204 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 56.

    Leyva-Illades, D. et al. SLC30A10 is a cell surface-localized manganese efflux transporter, and parkinsonism-causing mutations block its intracellular trafficking and efflux activity. J. Neurosci. 34, 14079–14095 (2014).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 57.

    Yuan, X. et al. Population-based genome-wide association studies reveal six loci influencing plasma levels of liver enzymes. Am. J. Hum. Genet. 83, 520–528 (2008).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 58.

    Liu, Y. et al. Genome-wide study links PNPLA3 variant with elevated hepatic transaminase after acute lymphoblastic leukemia therapy. Clin. Pharm. Ther. 102, 131–140 (2017).

    CAS 
    Article 

    Google Scholar 

  • 59.

    Whitfield, J. B. et al. Biomarker and genomic risk factors for liver function test abnormality in hazardous drinkers. Alcohol Clin. Exp. Res. 43, 473–482 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 60.

    Xu, C. F. et al. HLA-B*57:01 Confers susceptibility to pazopanib-associated liver injury in patients with cancer. Clin. Cancer Res. 22, 1371–1377 (2016).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 61.

    Feder, J. N. et al. A novel MHC class I-like gene is mutated in patients with hereditary haemochromatosis. Nat. Genet. 13, 399–408 (1996).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 62.

    Kozlitina, J. et al. Exome-wide association study identifies a TM6SF2 variant that confers susceptibility to nonalcoholic fatty liver disease. Nat. Genet. 46, 352–356 (2014).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 63.

    Holmen, O. L. et al. Systematic evaluation of coding variation identifies a candidate causal variant in TM6SF2 influencing total cholesterol and myocardial infarction risk. Nat. Genet. 46, 345–351 (2014).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 64.

    Liu, Y. L. et al. TM6SF2 rs58542926 influences hepatic fibrosis progression in patients with non-alcoholic fatty liver disease. Nat. Commun. 5, 4309 (2014).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 65.

    Buch, S. et al. A genome-wide association scan identifies the hepatic cholesterol transporter ABCG8 as a susceptibility factor for human gallstone disease. Nat. Genet. 39, 995–999 (2007).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 66.

    Ferkingstad, E. et al. Genome-wide association meta-analysis yields 20 loci associated with gallstone disease. Nat. Commun. 9, 5101 (2018).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 67.

    Tsutsumi, S. et al. The novel gene encoding a putative transmembrane protein is mutated in gnathodiaphyseal dysplasia (GDD). Am. J. Hum. Genet. 74, 1255–1261 (2004).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 68.

    Penttila, S. et al. Eight new mutations and the expanding phenotype variability in muscular dystrophy caused by ANO5. Neurology 78, 897–903 (2012).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 69.

    Hayes, M. G. et al. Identification of HKDC1 and BACE2 as genes influencing glycemic traits during pregnancy through genome-wide association studies. Diabetes 62, 3282–3291 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 70.

    Guo, C. et al. Coordinated regulatory variation associated with gestational hyperglycaemia regulates expression of the novel hexokinase HKDC1. Nat. Commun. 6, 6069 (2015).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 71.

    Sherry, S. T., Ward, M. & Sirotkin, K. dbSNP-database for single nucleotide polymorphisms and other classes of minor genetic variation. Genome Res. 9, 677–679 (1999).

    CAS 
    PubMed 

    Google Scholar 

  • 72.

    Arnold, L. M., Hirsch, I., Sanders, P., Ellis, A. & Hughes, B. Safety and efficacy of esreboxetine in patients with fibromyalgia: a fourteen-week, randomized, double-blind, placebo-controlled, multicenter clinical trial. Arthritis Rheum. 64, 2387–2397 (2012).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 73.

    Zogzas, C. E., Aschner, M. & Mukhopadhyay, S. Structural elements in the transmembrane and cytoplasmic domains of the metal transporter SLC30A10 are required for its manganese efflux activity. J. Biol. Chem. 291, 15940–15957 (2016).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 74.

    Park, J. H. et al. SLC39A8 Deficiency: a disorder of manganese transport and glycosylation. Am. J. Hum. Genet. 97, 894–903 (2015).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 75.

    Tuschl, K. et al. Mutations in SLC39A14 disrupt manganese homeostasis and cause childhood-onset parkinsonism-dystonia. Nat. Commun. 7, 11601 (2016).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 76.

    Scheiber, I. F., Wu, Y., Morgan, S. E. & Zhao, N. The intestinal metal transporter ZIP14 maintains systemic manganese homeostasis. J. Biol. Chem. 294, 9147–9160 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 77.

    Mercadante, C. J. et al. Manganese transporter Slc30a10 controls physiological manganese excretion and toxicity. J. Clin. Invest 129, 5442–5461 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 78.

    Katz, N. & Rader, D. J. Manganese homeostasis: from rare single-gene disorders to complex phenotypes and diseases. J. Clin. Invest 129, 5082–5085 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 79.

    Pavlides, M. et al. Multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease severity. Liver Int. 37, 1065–1073 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 80.

    Pavlides, M. et al. Multiparametric magnetic resonance imaging predicts clinical outcomes in patients with chronic liver disease. J. Hepatol. 64, 308–315 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 81.

    Kim, Y. High signal intensities on T1-weighted MRI as a biomarker of exposure to manganese. Ind. Health 42, 111–115 (2004).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 82.

    Bae, Y. J. & Kim, M. H. Manganese supplementation improves mineral density of the spine and femur and serum osteocalcin in rats. Biol. Trace Elem. Res. 124, 28–34 (2008).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 83.

    Strause, L. G., Hegenauer, J., Saltman, P., Cone, R. & Resnick, D. Effects of long-term dietary manganese and copper deficiency on rat skeleton. J. Nutr. 116, 135–141 (1986).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 84.

    Roadmap Epigenomics, C. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

    Article 
    CAS 

    Google Scholar 

  • 85.

    Crossgrove, J. & Zheng, W. Manganese toxicity upon overexposure. NMR Biomed. 17, 544–553 (2004).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 86.

    O’Neal, S. L. & Zheng, W. Manganese toxicity upon overexposure: a decade in review. Curr. Environ. Health Rep. 2, 315–328 (2015).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 87.

    Chen, J. Y., Tsao, G. C., Zhao, Q. & Zheng, W. Differential cytotoxicity of Mn(II) and Mn(III): special reference to mitochondrial [Fe-S] containing enzymes. Toxicol. Appl. Pharmacol. 175, 160–168 (2001).

  • 88.

    Schizophrenia Working Group of the Psychiatric Genomics, C. Biological insights from 108 schizophrenia-associated genetic loci. Nature 511, 421–427 (2014).

    ADS 
    Article 
    CAS 

    Google Scholar 

  • 89.

    Costas, J. The highly pleiotropic gene SLC39A8 as an opportunity to gain insight into the molecular pathogenesis of schizophrenia. Am. J. Med Genet. B Neuropsychiatr. Genet 177, 274–283 (2018).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 90.

    Mealer, R. G. et al. The schizophrenia risk locus in SLC39A8 alters brain metal transport and plasma glycosylation. Sci. Rep. 10, 13162 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 91.

    Krieger, D. et al. Manganese and chronic hepatic encephalopathy. Lancet 346, 270–274 (1995).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 92.

    Rajoriya, N., Brahmania, M. & Feld, J, J. Implications of manganese in chronic acquired hepatocerebral degeneration. Ann. Hepatol. 18, 274–278 (2019).

  • 93.

    Burkhard, P. R., Delavelle, J., Du Pasquier, R. & Spahr, L. Chronic parkinsonism associated with cirrhosis: a distinct subset of acquired hepatocerebral degeneration. Arch. Neurol. 60, 521–528 (2003).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 94.

    Anagianni, S. & Tuschl, K. Genetic disorders of manganese metabolism. Curr. Neurol. Neurosci. Rep. 19, 33 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 95.

    Ebert, B. L. & Bunn, H. F. Regulation of the erythropoietin gene. Blood 94, 1864–1877 (1999).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 96.

    Tyson, G. L. & El-Serag, H. B. Risk factors for cholangiocarcinoma. Hepatology 54, 173–184 (2011).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 97.

    Razumilava, N. & Gores, G. J. Cholangiocarcinoma. Lancet 383, 2168–2179 (2014).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 98.

    Kim, A. Modulation of MnSOD in cancer:epidemiological and experimental evidence. Toxicol. Res 26, 83–93 (2010).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 99.

    Landrum, M. J. et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 42, D980–D985 (2014).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 100.

    Stamelou, M. & Bhatia, K. P. A new treatable genetic disorder of manganese metabolism causing dystonia-parkinsonism and cirrhosis: the “new” Wilson’s disease? Mov. Disord. 27, 962 (2012).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 101.

    Bastarache, L. et al. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 359, 1233–1239 (2018).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 102.

    Hou, Y.-C. C. et al. Precision medicine advancements using whole genome sequencing, noninvasive whole body imaging, and functional diagnostics. bioRxiv, 497560. Preprint at https://doi.org/10.1101/497560 (2018).

  • 103.

    Bellenguez, C. et al. A robust clustering algorithm for identifying problematic samples in genome-wide association studies. Bioinformatics 28, 134–135 (2012).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 104.

    Zhou, W. et al. Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nat. Genet. 50, 1335–1341 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 105.

    Nioi, P. et al. Variant ASGR1 associated with a reduced risk of coronary artery disease. N. Engl. J. Med. 374, 2131–2141 (2016).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 106.

    McCaw, Z. R., Lane, J. M., Saxena, R., Redline, S. & Lin, X. Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies. Biometrics 76, 1262–1272 (2020).

    MathSciNet 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 107.

    Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203–209 (2018).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 108.

    Turner, S. D. qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. Journal of Open Source Software 3, 731 (2018).

    ADS 
    Article 

    Google Scholar 

  • 109.

    Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 110.

    Zhou, W. (2018) https://github.com/weizhouUMICH/SAIGE/issues/43.

  • 111.

    Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 112.

    Yin, L. A high-quality drawing tool designed for Manhattan plot of genomic analysis, https://github.com/YinLiLin/R-CMplot (2018).

  • 113.

    Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 114.

    McLaren, W. et al. The ensembl variant effect predictor. Genome Biol. 17, 122 (2016).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 115.

    Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 116.

    Consortium, G. T. et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).

    Article 

    Google Scholar 

  • 117.

    Võsa, U. et al. Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis. bioRxiv, 447367. Preprint at https://doi.org/10.1101/447367 (2018).

  • 118.

    Buniello, A. et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 47, D1005–D1012 (2019).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 119.

    Van Hout, C. V. et al. Exome sequencing and characterization of coding variation in 49,960 individuals in the UK Biobank. Nature 586, 749–756 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 120.

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 121.

    Picard, http://broadinstitute.github.io/picard/.

  • 122.

    WeCall, https://github.com/Genomicsplc/wecall.

  • 123.

    Lin, M. F. et al. GLnexus: joint variant calling for large cohort sequencing. bioRxiv, 343970. Preprint at https://doi.org/10.1101/343970 (2018).

  • 124.

    Loh, P. R., Kichaev, G., Gazal, S., Schoech, A. P. & Price, A. L. Mixed-model association for biobank-scale datasets. Nat. Genet. 50, 906–908 (2018).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 125.

    Gordon, M. & Lumley, T. forestplot: Advanced Forest Plot Using ‘grid’ Graphics. R package version 1 (2015).

  • 126.

    Ward, L. D. & Kellis, M. HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease. Nucleic Acids Res. 44, D877–D881 (2016).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 127.

    Zhao, Y., Feresin, R. G., Falcon-Perez, J. M. & Salazar, G. Differential targeting of SLC30A10/ZnT10 heterodimers to endolysosomal compartments modulates EGF-induced MEK/ERK1/2 activity. Traffic 17, 267–288 (2016).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 128.

    Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J. & Kircher, M. CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res 47, D886–D894 (2019).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 129.

    Vaser, R., Adusumalli, S., Leng, S. N., Sikic, M. & Ng, P. C. SIFT missense predictions for genomes. Nat. Protoc. 11, 1–9 (2016).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 130.

    Adzhubei, I. A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • Changes in alt, ast and alp values of plasma and serum samples stored at refrigerator (4 0c) and room temperature (32 0c) for up to five days

    • O.K Nwosu

    • G.S Aloh

    • J.L Ihedioha

    Keywords:

    Liver enzymes, Liver malfunction, Blood collection, Stability, Temperature

    Abstract

    This study investigated the time-related changes in the alanine aminotransferase (ALT), aspartate aminotransferase (AST) and alkaline phosphatase (ALP) values of serum and plasma samples stored at refrigerator (2 – 8oC, average of 40C) and room temperature (30-340C, average of 320C) for a period of 120 hours (5 days). Blood samples were obtained from a total of 20 patients that presented with cases of liver malfunction at the Ebonyi State University Teaching Hospital, Abakaliki, Nigeria. The enzyme assays were carried out immediately upon sample collection and separation to obtain the baseline value (BV), and thereafter at specified time intervals across the 120 hours. Results showed that values not significantly different (p > 0.05) from the BV can be obtained from serum and plasma samples within the specified storage durations at the different temperatures as follows: For serum ALT, 40C – 48 hours, 320C – 16 hours; plasma ALT, 40C – 36 hours, 320C –10 hours; serum AST, 40C – 36 hours, 320C – 10hours; plasma AST, 40C – 36 hours, 320C – 8 hours; serum and plasma ALP, 40C – 30 hours, 32oC – 10 hours. All the enzymes were found to be more stable in refrigerated samples than in those kept at room temperature; also the enzymes were more stable in serum than in plasma for all the storage temperatures. It was concluded that in general, reliable values for serum and plasma ALT, AST and ALT (values not significantly different from the BV) can be obtained from refrigerated samples if analysed within 30 hours of blood collection and separation, while for samples kept at room temperatures (320C) analysis should be carried out within 8 hours. Beyond these time points (30 hours for refrigerated samples and 8 hours for samples kept at room temperature) values obtained for the serum and plasma enzymes studied were significantly different (P<0.05) from the BV and therefore not reliable for diagnosis.

    Keywords: Liver enzymes, Liver malfunction, Blood collection, Stability, Temperature

    Copyright: Creative Commons Attribution CC.

    This license lets others distribute, remix, tweak, and build upon your work, even commercially, as long as they credit you for the original creation. This is the most accommodating of licenses offered. Recommended for maximum dissemination and use of licensed materials. View License Deed | View Legal Code Authors can also self-archive their manuscripts immediately and enable public access from their institution’s repository. This is the final corrected version that has been accepted for publication and which typically includes author-incorporated changes suggested during submission, peer review and in editor-author communications.

    Mean ALT and AST values according to the causes. 

    SEN-Virus is a DNA virus which is related to acute post-transfusion hepatitis and the prevalence with the clinical importance and also the genetic characterization are still much unknown in Iraq; therefore, this study was designed. This study was included three main approaches, the first is diagnostic, at which determination of hepatitis C virus in the blood among patients with thalassemia was achieved. The second part is the molecular part, which included measurement of virus-viral load for patients with hepatitis C using Reverse Transcriptase-Real Time technique. In addition to, use of conventional PCR technique, to investigate SEN-virus genotypes either D or H or both of them. Further, to study genome sequencing using phylogenetic analysis of SEN-V clones by nearest neighbor sequencing method. The third one includes the physiological and biochemical aspects, which included the evaluation of enzymatic and non-enzymatic antioxidants in addition to measuring the levels of liver enzymes and their effect on liver damage in
    patients.

    male) were

    A total of 200 -thalassemia patients (104 female and 96

    included in this study. They were referred to the Hereditary Blood Disease

    male, 50

    0/Baghdad and 100 (5

    Al-Karama Teaching Hospital/Center

    female) healthy blood donors and randomly selected persons were collected from Iraqi National Center of Blood Transfusion and randomly chosen from
    the community during the period from March to August 2017. HCV was identified preliminary by Rapid immunochromatographic
    assay which is a qualitative detection of anti-HCV antibody in patients sera. Enzyme-Linked Immunosorbent Assay for detection of anti-HCV antibody was also done as a confirmatory test. Further, assay procedure for
    biochemical tests including Alanine aminotransferase, Aspartate

    I
    aminotransferase, Alkaline phosphatase, Total serum bilirubin, Gamma-glutamyltransferase and Total protein (Albumin and Globulin) were done by
    using automatic chemistry analyzer instrument (MNCHIP) for each serum

    On the other hand, specimen from patients and healthy subject individuals.

    measurement of non-enzymatic antioxidant which includes vitamin C, and vitamin E. Further, enzymatic based antioxidantike human glutathione peroxidase levels were also achieved by ELISA technique.
    HCV RNA and SENV-DNA extraction were done by SaMag-12 automatic nucleic acid extraction system. HCV Real-Time PCR was used for the amplification of the quantitative detection of hepatitis C virus in human plasma. Further, SENV-DNA was also amplified by nested conventional
    PCR.

    One hundred patients with a well previous diagnosis of HCV infection

    were submitted to rapid immunochromatographic and ELISA to confirm HCV infection, revealed confirmed result positive rapid immunochromatographic and ELISA assay for all clinical samples. Also, the other 100 thalassemic patients and 100 healthy subjects (control) were
    yielded negative ELISA tests results for HCV antibody in their sera. Regarding viral load, the quantity of virus, out of 100 positive ELISA-
    anti-HCV antibodies, 72 (72%) were positive for RT- PCR considering the assay threshold for our procedure was <13 IU/ml. The mean of viral load in these patients was 545806 ±1009799 IU/ml and 1997176 ±3802206
    Copies/ml. Twenty-eight (28%) of the patients who showed negative viral load and positive anti-hepatitis C antibody by ELISA were considered as undetectable viral load patients.
    SENV was detected in 163 out of 200 (81.5%) thalassemia patients

    and 11 out of 100 (11.0%) blood donors. The results of our study showed that the most important SENV genotypes were SENV-D and SENV-H and there
    were patients infected with D genotype or H genotype alone, while there were patients co-infected with D and H. The results revealed that there was a substantial increase in SENV-D, SENV-H and SENV-D and H in thalassemia patients without HCV infection 59(34.0%), 11(6.4%), 14(8.0%) respectively than those in thalassemia patients with HCV infection 44(25.3%), 14(8.0%),
    21(12.0%) and healthy subjects 7(4.0%), 4(2.3%), 0(0.0%) respectively. According to SENV and HCV co-infection status, patients thalassemia
    group had been subdivided four subgroups, SENV positive and positive HCV as subgroup I , SENV positive and HCV negative as subgroup II, SENV negative and HCV positive as subgroup III, SENV and negative and HCV negative as subgroup IV. Healthy subjects also had been subdivided into two subgroups according to SENV infection, SENV positive (subgroup V) and finally SENV negative (subgroup VI).
    As for the physiological and biochemical aspect, the statistical analysis revealed that there was a significant decrease in the mean level of serum vitamin E, C, and GPX of thalassemia group among cases, as compare with healthy subjects. There was also a significant increase in ALT, AST, ALP, and TSB
    activity in the first (I) subgroup compared to other subgroups. The study results of sequencing part of this study revealed that in phylogenetic analysis, each branch have the same DNA sequences and that means the virus had been transmitted most probably via blood transfusion as a result of the compatibility of DNA sequences between donors and thalassemia patients and D sequence of the co-infected persons with SENV D and H is the same sequence of D genotype of the SENV-D infected person and with the
    observations of similarity with neighboring countries.

    Calories Starry Night Candy, Donko. Chemical composition and nutritional value.

    Chemical composition and nutritional analysis

    Nutritional value and chemical composition

    “Starry night sweets, Donko” .

    The table shows the content of nutrients (calories, proteins, fats, carbohydrates, vitamins and minerals) per 100 grams of edible part.

    Nutrient Quantity Norm ** % of the norm
    in 100 g
    % of the norm
    100 kcal
    100% of the norm
    Caloric value 400 kcal 1684 kcal 23.8% 6% 421 g
    Proteins 1.5 g 76 g 2% 0.5% 5067 g
    Fats 10 g 56 g 17.9% 4.5% 560 g
    Carbohydrates 77 g 219 g 35.2% 8.8% 284 g
    Organic acids 0.3 g ~
    Dietary fiber 2.3 g 20 g 11.5% 2.9% 870 g
    Water 6.6 g 2273 g 0.3% 0.1% 34439 g
    Ash 0.3 g ~
    Vitamins
    Vitamin B1, thiamine 0.01 mg 1.5 mg 0.7% 0.2% 15000 g
    Vitamin B2, riboflavin 0.03 mg 1.8 mg 1.7% 0.4% 6000 g
    Vitamin E, alpha tocopherol, TE 0.2 mg 15 mg 1.3% 0.3% 7500 g
    Vitamin PP, NE 0.5 mg 20 mg 2.5% 0.6% 4000 g
    Niacin 0.2 mg ~
    Macronutrients
    Potassium, K 100 mg 2500 mg 4% 1% 2500 g
    Calcium, Ca 18 mg 1000 mg 1.8% 0.5% 5556 g
    Magnesium, Mg 27 mg 400 mg 6.8% 1.7% 1481 g
    Sodium, Na 26 mg 1300 mg 2% 0.5% 5000 g
    Phosphorus, P 41 mg 800 mg 5.1% 1.3% 1951 g
    Microelements
    Iron, Fe 1.6 mg 18 mg 8.9% 2.2% 1125 g
    Digestible carbohydrates
    Starch and dextrins 4.1 g ~
    Mono- and disaccharides (sugars) 77.7 g max 100 g
    Saturated fatty acids
    Saturated fatty acids 5 g max 18.7 g

    Energy value Candy Starry night, Donko is 400 kcal.

    Main source: Created in the application by the user. More details.

    ** This table shows the average norms of vitamins and minerals for an adult.If you want to know the norms taking into account your gender, age and other factors, then use the application
    “My Healthy Diet”.

    Caloric content of Starry Night cake. Chemical composition and nutritional value.

    Chemical composition and analysis of nutritional value

    Nutritional value and chemical composition

    “cake” “Starry night” “.

    The table shows the content of nutrients (calories, proteins, fats, carbohydrates, vitamins and minerals) per 100 grams of edible part.

    Nutrient Quantity Norm ** % of the norm
    in 100 g
    % of the norm
    100 kcal
    100% of the norm
    Caloric value 174.1 kcal 1684 kcal 10.3% 5.9% 967 g
    Proteins 2.9 g 76 g 3.8% 2.2% 2621 g
    Fats 2.5 g 56 g 4.5% 2.6% 2240 g
    Carbohydrates 31.5 g 219 g 14.4% 8.3% 695 g

    Energy value cake “Starry night” is 174.1 kcal.

    Main source: Created in the application by the user. More details.

    ** This table shows the average norms of vitamins and minerals for an adult. If you want to know the norms taking into account your gender, age and other factors, then use the application
    “My Healthy Diet”.

    Frank Herbert’s Guide to the World of Dunes

    World of “Dune”

    Frank Herbert wrote many works, but the opus magnum of his work became the cycle “Chronicles of Dune” in six books.The story of the struggle of powerful clans for the possession of a rare resource that is located on a planet with an oppressed population, in terms of dynamics, scale and reasoning regarding the nature of power, can only be compared with the epic “A Song of Ice and Fire” by George Martin and “Foundation” by Isaac Asimov.

    The action of “Dune” takes place in the distant future, which has already survived the uprising of machines, which is why a ban is imposed on artificial intelligence here, and the structure of society is feudal. The Universe Emperor Shaddam IV of House Corrino takes control of the Desert Arrakis, also known as Dune, to Duke Leto Atreides.The planet, famous for its harsh climatic conditions, is the only deposit of the main value in the universe – melange.

    Melange (or spice) is a drug that slows down aging, and at the same time fuel for ships, allowing you to travel in outer space at speeds faster than light. But, perhaps, the key property of the spice is that with its help it is possible to foresee the future – and this gives the owner of the resource unlimited power.

    Melange is also impossible to synthesize: it is produced only by the formidable giant worms that live in the deserts of Dune.

    Why would the emperor give the duke the treasure on which his power and the economy of the universe depend? This is where Machiavellian intrigues, traps and “plans within plans” begin: there is nothing better than, under the pretext of a reward, eliminating a potential competitor to the throne, pitting him against a longtime enemy who previously held a monopoly on the spice.

    In a conspiracy with the emperor, Baron Harkonnen, who previously controlled Dune, kills the duke, but does not manage to get to his 15-year-old son and heir Paul Atreides, the main character of the book.Together with his mother, Paul flees into the desert, where he meets the local population – the Fremen. Subsequently, he becomes not just their leader, but a spiritual leader and liberator. The heir plans not only to regain his home, but also to make the Fremen dream come true – to green Arrakis.

    close

    100%

    Still from the film “Dune” (2021)

    Warner Bros.

    Dune Ecology

    The sandy planet story emerged when Herbert came to Oregon to write an article on dune control, a highly successful US government greening project.And although the material was never published, the author became seriously interested in the influence of the environment on religious thinking and the culture of society. As a result, immediately after its publication in 1965, readers and the press dubbed “Dune” the first novel about ecology (not long before that, the work also appeared in the popular journal Analog Science Fiction).

    Herbert was not the first writer to address this topic, but in his work, ecology has become not just an exotic place for combat, but the spiritual core of the plot.In the novel, the economy and politics of the universe, as well as the religion and culture of the local population, depend on the ecosystem of the planet.

    From the point of view of economics, the spice here is an analogue of oil, its value leads to wars and the exploitation of the indigenous population, who die during extraction. Subsequently, it turned out that the science fiction writer managed to predict the oil crises and the associated war in the Middle East.

    Dune was greatly influenced by the scientific work Silent Spring by Rachel Carson (1962).In it, the author opposed environmental experiments and the use of pesticides in the agricultural industry, leading to soil destruction. Herbert himself supported criticism of the Green Revolution for another reason: in the 1970s, he worked as an environmental consultant in Vietnam and Pakistan. There, he also made a documentary about field work, opposing the use of environmental weapons.

    By the way, the writer himself called himself a “techno-farmer”, since one of his dwellings was an environmental project that clearly demonstrates the benefits of solar and wind energy, peat cultivation and other eco-alternatives.Later, however, Herbert spoke about ecology as a speculative topic that became a “haven for demagogues.”

    close

    100%

    Frank Herbert

    AP

    Politics of “Dune”

    In the first book of the series, it seems that this is another story about a superhero who puts the interests of the people above his own. However, already in the next parts it turns out that in fact Paul Atreides is an antihero who started a “jihad” in his universe.This plot twist once amazed John Campbell, editor-in-chief of Analog Science Fiction, that he flatly refused to publish a sequel in the magazine. At the same time, Herbert scattered “clues” about how Paul’s rise to power would end in his debut novel. This, in particular, is indicated by the lines “For your people there is no more terrible misfortune than falling into the hands of hero “, which the planetary ecologist of Dune Liet Kines recalls before his death. At the end of the story, the same refrain sounded, indicating that Arrakis was “struck” by hero like a serious illness.

    As a journalist, Herbert was not indifferent to the events of his time: his distrust of the authorities was caused not only by the Watergate scandal, but also by the lies of the American government about the events in Vietnam. The hidden threat in following a charismatic leader is reflected in the Dune cycle.

    Paradoxically, Herbert considered John F. Kennedy to be such a dangerous hero in real life: supposedly, against the background of odious figures (like Hitler), the danger of positive characters for society is not so obvious.According to the writer, Kennedy’s rival Richard Nixon did the main thing – he made people ask questions, and not blindly follow the leaders.

    Herbert was firsthand familiar with the world of politics: in the White House he worked as a speechwriter for one of the senators, spoke at the hearings of Joseph McCarthy against the US Army, and even ran for governor of American Samoa. Even before the Game of Thrones phenomenon, the author described in detail the fierce struggle for power among various structures, showing that there are no ideal heroes – and that even a good leader coming to power can have dire consequences.

    close

    100%

    Still from the film “Dune” (2021)

    Warner Bros.

    Religion “Dunes”

    The theme of “messianic hunger” in the saga is one of the main ones. Herbert described the term as “the pathological state of humanity, awaiting the arrival of a hero or a messiah to shoulder the responsibility of solving problems.” The writer came up with the image of the young messiah Paul Atreides on the basis of the essays “Seven Pillars of Wisdom” by the British diplomat Thomas Lawrence and the campaigns of Alexander the Great.

    The myth of the messiah is constructed in such a way that there are no unexpected moments for the reader. From the very beginning, it is known that Duke Leto will die, and his son Paul will become the leader of the Fremen and will meet his beloved Chani, whom he saw in his dreams. However, knowing the future does not save the heroes from mistakes, but often, on the contrary, leads them into the trap of prediction.

    The disaster that Paul will unwittingly bring is the desire to give the Fremen their dream – the evergreen Arrakis. Subsequently, however, climate change will destroy the “desert dragons” – giant worms that produce melange.The Fremen themselves will also change: from an independent and proud tribe with unique traditions, they will become weak and cunning people cursing the coming of the Atreides dynasty to power. All their cultural trappings will become echoes of the past, gathering dust in the museum of Arrachin – the capital of Dune.

    Ultimately, the disappearance of the spice threatens the very existence of the ruling elite, using the drug in religious rituals. And although the heroes of “Dune” have an ecumenical Bible, they themselves perceive it as a code of ethics and a collection of meditation practices.Because religion for them is an instrument of power. The exceptions are the Freemen, who practice Zen Buddhism and Sunnism, as well as the school of mentats, who rely on the computational abilities of science.

    The eclecticism of worldviews is embodied in the language of the book, replete with concepts from Buddhism, Judaism, Christian and Muslim religions. This confusion is characteristic of the “humanitarian” science fiction of the “new wave”, which instead of describing a technocratic future focuses on social problems.It is with this that the inter-genre of “Dune” is connected, combining medieval elements of fantasy and science fiction.

    close

    100%

    Still from the film “Dune” (2021)

    Warner Bros.

    Stories of screen adaptations

    The adaptation of “Dune” suffered the same fate as the novel by the writer, which was rejected by more than 20 book publishers. The scale of Herbert’s idea, the confusion of terminology, the philosophical “stuffing”, as well as the weak technological capabilities of previous years literally “buried in the sands” the plans of Hollywood studios.

    The first attempt to bring Dune to the screen was made back in 1971 by APJ. According to the plans of producer Arthur Jacobs, the director’s chair was to be taken by David Lin, who previously directed the Oscar-winning film “Lawrence of Arabia” in the desert.

    After the project was frozen, the rights to film adaptation were bought by producer Michel Seydoux. He entrusted Herbert’s brainchild to the Chilean surrealist director Alejandro Jodorowski. His unrealized project is still considered the most ambitious attempt to film Dune, which went down in film history as the “greatest masterpiece not yet filmed.”

    The film, as conceived by the director, was to become a “galactic version of Afghanistan.” Salvador Dali, Orson Welles, Charlotte Rampling, Dan O’Bannon and other stars could have taken part in the creation of the picture, and the groups Magma and Pink Floyd were invited to write the music for the picture. Storyboards and concept art for the script were made by such talented artists as Hans Giger, Criss Foss and Jean Giraud “Moebius”.

    However, the amount of $ 5 million was not enough to realize the film masterpiece, so after 2.5 years of production hell, the project was curtailed.Subsequently, the storyboards for “Dune” were sold to many Hollywood studios, so today you can find visual references in many films: “Flash Gordon”, “Masters of the Universe”, “Alien”, “Beetlejuice”, “Indiana Jones: In Search of the Lost ark “,” The Fifth Element “,” Prometheus “and others. The documentary film “Dune” by Jodorowski by Frank Pavich was also made about the impact of the adaptation on the film industry.

    When producer Dino De Laurentiis bought the film rights, Ridley Scott was supposed to direct the film.The director even started writing the script, but after seven months of work abandoned the project in favor of an adaptation of Philip Dick’s novel, creating Blade Runner.

    Then the choice of the producer fell on David Lynch. The metaphysical subtext of the work attracted the surrealist director: for the sake of Dune, he did not accept George Lucas’s proposal for the VI episode of Star Wars.

    However, Lynch’s grand scheme turned out to be a failure at the box office – even though Herbert worked as a film consultant.The discontent of the audience and critics was caused by the inaccessibility of the plot, the eccentricity and cruelty of some episodes. Inflated expectations of the audience also influenced (they were associated with a powerful advertising campaign and the announced budget). Despite all the introductions, the visual and storytelling of the film was boring compared to competing Star Wars.

    Lynch himself, by the way, was removed from the final editing, and without his participation many important scenes were cut from the film. All this led to the fact that the prologue of the tape was opened with a close-up of the head of Princess Irulan – the chronicler of The Chronicle of Dune, who explained the plot of the book for more than five minutes.Lynch’s supporters, not wanting to put up with the failure of the idol, argued that “Dune”, in principle, cannot be filmed. In turn, Herbert defended the film adaptation, emphasizing that he liked everything about it, except for the ending: it could not rain on Arrakis.

    The next hope was a series adaptation for the Sci-Fi channel, which, however, was also not destined to become canon. Unlike Lynch’s film, John Harrison’s Dune miniseries focused not on the metaphysical side of the book, but on the intrigues of the great houses.

    Finally, Greg Yaitanes became the first director who dared to film the next two sagas – as a continuation of the Harrison series. Their shooting took place in a pavilion, and not in the desert, and the plot itself deviated somewhat from the source. Despite this, viewers generally appreciated his work positively.

    close

    100%

    Still from the film “Dune” (1984)

    Estudios Churubusco Azteca S.A.

    Star Wars for adults

    Why is Dune interesting today? The strength of the book lies in the fact that it turns out to be much deeper than its popular retelling – “Star Wars”.

    Even Lucas himself has repeatedly admitted that Herbert’s Dune was one of his sources of inspiration.

    So, in both works, the main character, who was supposed to save the world, goes over to the side of evil, unleashing a war in the universe. And, for example, Paul Atreides’ wife Chani dies in childbirth, giving birth to two twins – a boy and a girl.Also, in the Star Wars draft, Princess Leia was transporting the melange, not the Death Star plan, while Han Solo was the spice smuggler.

    There were other identical details: the similarities between Tatooine and Arrakis, the English anagram of the names Leia and Alia (Paul Atreides’ younger sister), Jedi practices, and the Bene Gesserit abilities.

    close

    100%

    Still from the movie “Star Wars: Episode 4 – A New Hope” (1977)

    Lucasfilm

    Dune Villeneuve

    The adaptation of Denis Villeneuve, one of the most anticipated films of 2021, has every chance of becoming canon.This is supported by the modern technical capabilities that the director’s predecessors did not have, and the superstar cast of actors (Timothy Chalamet, Rebecca Ferguson, Oscar Isaac, Josh Brolin, Jason Momoa, Zendea, Stellan Skarsgard, Javier Bardem, Dave Batista), and the absence timing restrictions.

    Villeneuve’s Dune will not be limited to one film – it will be followed by at least a sequel and an HBO series. And there it is no longer so far to a full-scale cinematic universe (similar to the same “Star Wars”) – fortunately, there is more than enough material written by both Herbert himself and his son Brian in collaboration with science fiction writer Kevin Anderson.

    Caloric content Puff yeast dough Star Bread House. Chemical composition and nutritional value.

    Chemical composition and nutritional analysis

    Nutritional value and chemical composition

    “Yeast puff pastry Star Bread House” .

    The table shows the content of nutrients (calories, proteins, fats, carbohydrates, vitamins and minerals) per 100 grams of edible part.

    Nutrient Quantity Norm ** % of the norm
    in 100 g
    % of the norm
    100 kcal
    100% of the norm
    Caloric value 414 kcal 1684 kcal 24.6% 5.9% 407 g
    Proteins 7.3 g 76 g 9.6% 2.3% 1041 g
    Fats 20.9 g 56 g 37.3% 9% 268 g
    Carbohydrates 48.6 g 219 g 22.2% 5.4% 451 g

    Energy value Puff yeast dough Star Bread House is 414 kcal.

    Main source: Created in the application by the user. More details.

    ** This table shows the average norms of vitamins and minerals for an adult. If you want to know the norms taking into account your gender, age and other factors, then use the application
    “My Healthy Diet”.

    90,000 Star team.How Netflix survived the economic crisis with talented employees

    Reed Hastings, co-owner and CEO of Netflix, tells the story of the streaming giant for the first time in his book No Rules. The Unique Culture of Netflix ”, which is published by Mann, Ivanov & Ferber in July. The author claims that the company has grown into a giant of the entertainment industry thanks to its corporate culture. It has only two principles – freedom and responsibility, and together they allow Netflix to remain one of the most innovative companies in the world.In the excerpt we are posting, you will learn how the company laid off a third of its team during the dot-com crisis in the 2000s, but was able to survive thanks to its remaining stellar employees.

    In the 1990s, I often borrowed videotapes from a Blockbuster rental shop on our street. Usually I would choose two or three films at once and return quickly so as not to pay for long-term use. One day I decided to clean up my desk and found a cassette under the papers, which I looked at a few weeks ago, but forgot to return.When I took it to the rental shop, they charged me $ 40! I felt like a complete idiot.

    I remembered this incident and became thoughtful. Long-term rental was the main profit for Blockbuster. If your business model requires you to instill in your customers a sense of mental inferiority, will they be loyal? Maybe there is a way to make sure people enjoy watching movies at home without forcing them to pay a fortune for accidental delays?

    In early 1997, after the sale of Pure Software, Mark Randolph and I started thinking about a mail-order service.Amazon was already doing pretty well with books back then – why don’t we give it a try with movies? Customers would rent cassettes through our site and return them by regular mail. Then we found out: shipping a cassette one way costs four dollars. An expensive pleasure. You could forget about the big market. But then a friend told me about a new invention – the DVD. “It’s like a computer disc, only with a movie,” he explained. I rushed to the nearest post office and sent myself some CDs (I couldn’t get a DVD for the experiment).Each shipment cost me 32 cents. I returned home to Santa Cruz and waited impatiently. Two days later, whole and unharmed discs were in my mailbox.

    In May 1998, we launched Netflix, the world’s first virtual DVD rental service. We had 30 employees and 925 films in the catalog – almost the entire DVD range available at the time. Until 1999, the company was headed by Mark Randolph; then I replaced him, and he became one of the directors. By the beginning of 2001, we already had about 400,000 subscribers and 120 people on the staff.I tried not to repeat the mistakes made in Pure Software. We didn’t overuse controls this time around, and I wouldn’t call then-Netflix an ideal place to work. But the company developed, it went on, the employees were happy.

    Lessons from the crisis

    In the spring of 2001, a crisis broke out: the first Internet bubble burst; thousands of dot-coms went broke and left the market. The inflow of investments dried up, and we could not attract the necessary additional financing.The indicators went into negative territory. A third of the team had to be cut. Despondency reigned in the office. Mark and I, and Patti McCord (she came with me from Pure Software and became the head of HR), began to study the personal files of employees. We had no frankly bad workers. So we decided to split the team into two groups: 80 stars, which we will leave in the company in any case, and 40 middle peasants, with whom we can part. Those who literally gushed with ideas, worked hard and fruitfully, fit into the team well, we immediately sent them to the star folder.It was more difficult with borderline cases. The team had, for example, excellent colleagues and friends, but ordinary workers. And there were those who worked tirelessly, but did not always make the right decisions and needed constant supervision. There were very talented and diligent people, but at the same time whiners and pessimists. Most of them had to be parted.

    The solution was not easy for us every time. Before the massive layoff, my wife began to notice that I was very worn out. She was right.I was afraid that employees would completely lose motivation. I had no doubt that after we fire their friends and colleagues, those who remain will decide that the company does not give its employees a dime. Of course, everyone will be angry. Worse, those who remain will have to take on the functions of the dismissed, and the atmosphere will heat up to the limit. We already do not have enough money. Can we afford a further drop in morale?

    Day X has come. As I expected, it was terrible. The dismissed ones sobbed, shouted and slammed doors.By noon, the “massacre” was over, and I began to wait for the second wave – the rebellion of the abandoned … But, despite the tears shed and general sadness, everything was unexpectedly quiet. And after a few days, the atmosphere in general improved dramatically – I could not really understand why. We had just cut the budget and laid off a third of the team, but the office was literally seething with excitement, energy and new ideas.

    A few months later, the holiday season began. DVDs were in high demand that Christmas, and by early 2002 our rental business was back on track.The workload had unexpectedly grown, and the people at the company were still 30% fewer. To my amazement, those same 80 people tackled all tasks with unprecedented enthusiasm. I had to work harder, but the mood was excellent, and not only among ordinary employees. I myself was literally eager to work in the morning. Every day I gave a lift to Patty McCord’s office, and with a big smile she literally drove into the car: – Reed, what’s going on? It feels like we’re all in love. Maybe we have something with hormones and it will soon pass?

    Patti has chosen a very precise look.Our entire office seemed to be full of people passionately in love with their work. I am not a supporter of mass layoffs, and fortunately! – We at Netflix have never had to take such drastic measures again. But in those days and months after the 2001 crisis, my understanding of employee motivation and managerial responsibility changed fundamentally. It was a revelation for me. For the first time, I realized the role that talent concentration plays in the life of a company. All subsequent successes are largely due to the lessons of that period.Before exploring these lessons in detail, you need to introduce the reader to Patty, because she has played a key role in the development of the company for more than ten years, and now her student Jessica Neal is in charge of Netflix’s personnel. I met Patti while still at Pure Software. In 1994, she called the office and asked to speak to the CEO. At that time my younger sister answered our calls and switched her directly to me.

    Patty was born and raised in Texas, as I immediately guessed from her speech.She said she currently works for software and hardware company Sun Microsystems, but would like to move to Pure Software and head the HR department. I invited her for a cup of coffee. In the first half of our meeting, I did not understand anything from what Patty said. When I asked her about the approach to personnel issues, she said: “I believe that every worker should be able to share their contribution to the work of the company and their personal aspirations. As a HR manager, I see my job as helping you and the entire management team develop emotional intelligence and increase employee engagement.

    My head was spinning. I was young and uncouth, so I waited for a moment and put in the word: – Was that the language of the Eichars? I do not understand anything. If you want to work for our company, you have to learn to speak like a human being. Patty was offended in the best of feelings, and she did not hesitate to tell me about it. That evening, her husband asked her how the interview went, and she replied: “Bad. Got a fuck with the general. But I really liked how she directly expressed her opinion, and I took her to work.Since then, we have been united by a strong and honest friendship, which did not end even after Patty left Netflix. Maybe the secret is that we are very different: I am a cracker-mathematician and a straightforward computer scientist, she is an excellent psychologist and storyteller. When I look at the team, I see numbers and algorithms that drive human interaction. And Patty sees emotions and subtle nuances of interpersonal relationships that are beyond my reach.

    Patty worked at Pure Software until I sold the company and soon moved to Netflix.After the massive layoff in 2001, Patty and I racked our brains for a long time, trying to understand why the atmosphere in the company changed so dramatically for the better after the downsizing, and how this charge of general vigor can be maintained. We came to the conclusion that the reason for the change must be found in the sharp increase in what Patty called “concentration of talent.”

    Talent Concentration

    Everyone has a grain of talent. When we had 120 employees, there were both incredibly gifted people and simply talented people among them.It can be said that the total amount of talent distributed among the staff in the company was quite large. After the layoffs, when the 80 most capable people remained in the state, the amount of talent in general declined, but its concentration increased. We soon discovered that a company with a high concentration of talent is the place where everyone wants to work. Stars love to be surrounded by other stars. Our employees learned a lot from each other, and the teams coped with tasks faster and more efficiently.This inspired and spurred individual employees, the performance of the entire company grew. When the best of the best are gathered in the team, the quality of work reaches a new, downright transcendental level. Working with gifted colleagues is joyful and exciting – both when there are seven thousand of you, and when there are only eighty.

    Looking back, I understand: only one or two average peasants in the team discourage everyone. If you have five excellent employees and two average ones, they are sure to:

    – they will take away the energy from the leaders, and there will be less time for the best employees;

    – will lower the quality of discussions and the general intellectual level of the team;

    – will force others to look for workarounds so as not to work with them, which will reduce the efficiency of the process;

    – will alienate from your company those for whom self-realization is truly important;

    – Will exacerbate the problem by demonstrating to the whole team that you are satisfied with a mediocre job.

    For the best employees, the main thing at work is not a comfortable office, not a cool gym, and not free sushi at lunchtime. The main thing is the joy that you are surrounded by talented people who help you grow professionally and personally. When every member of the team is a star, overall metrics skyrocket as employees educate and motivate each other.

    Quality is contagious

    [Narrated by the ex-head of Netflix HR – Approx.Ed.]

    After a massive layoff in 2001, Reed found that the quality of work, both high and low, was contagious. If the team has average people, many employees who could become real stars also work averagely. And if you have got enthusiastic and gambling hard workers, everyone will push the rest to new achievements.

    University of New South Wales professor Will Phelps conducted a fascinating experiment that clearly showed how contagious behavior can be in the workplace.He gathered several groups of four students and asked each team to complete some administrative task in 45 minutes – an academic hour. The teams that did the best job were promised a $ 100 reward. In some groups, without the knowledge of the rest of the students, actors were introduced, and each was assigned a strictly defined role: a “lazy person” who quickly loses interest in work, puts his feet on the table and begins to send messages; A “skeptic critic” who reacts rudely to every idea and constantly makes remarks like “Are you kidding me ?!” and “What were you just taught ?!”; A “depressed whiner” who looks like his beloved cat passed away yesterday – he complains that the task is prohibitively difficult, out loud doubts that the team can win, and from time to time drops his head in his hands.

    The actors played naturally, the other participants in the experiment did not even suspect that the strangers who had come out of nowhere were not ordinary students. Almost immediately, Phelps discovered that even when group members are exceptionally smart and talented, the destructive “hooking” behavior dramatically lowers the performance of the entire team. The results of dozens of experiments carried out over several months were similar: the groups with the “sent Cossack” in the composition lagged behind the leaders by 30–40%. Phelps’s results refuted the previous idea that individual members of the group perceive the norms and values ​​of the collective and over time begin to adapt to them – just the inverse relationship has come to light.The behavior of one person soon began to affect the entire team, although the participants in the experiment spent no more than 45 minutes together.

    Phelps remarked: “Surprisingly, the band has exactly followed the manner of our actor every time.” If the fake student played the role of a lazy person, the rest lost interest in the project, and someone soon announced that they did not see the point in the task at hand. If the actor was rude and snapped, the other members of the group also began to quarrel, allowed themselves to offend their comrades, and spoke in a raised voice.But the most deplorable sight could be observed in groups with an embedded “whiner”. Will Phelps comments: “I have a videotape of one of these bands stuck in my mind. At first, all participants sit upright – cheerful, energetic, ready to take on an interesting job. In the end, everyone is literally lying on their desks with their heads in their hands. ”

    Phelps’s experiment clearly demonstrated what Patty and I found out in practice back in 2001. If you have a few average people in your workgroup, their attitudes are likely to spread across the entire team, lowering the overall performance.Unsurprisingly, after the massive downsizing we had to do at Netflix, the company has taken it to a whole new level. Phelps’ experience reminds us that the underperforming employee is not an isolated problem. This is a potential problem for the entire team. The behavior of the “brake” will inevitably slow down the rest.

    Surely most of us have seen such cases. I had a similar experience when I was 12 years old. I was born in 1960 in Massachusetts and as a child did not shine with any talents, and indeed did not stand out among my peers.When I was in third grade, our family moved to Washington. At first everything went well, and at the new school I made a lot of friends. However, in the sixth grade, a new boy, Kevin, came to us, and constant fights began. Generally speaking, Kevin didn’t bully or bully any of us. But he, otherwise unremarkable, in some incomprehensible way managed to create an atmosphere around him in which conflicts flared up by themselves. I did not want to fight at all, but I could not sit on the sidelines: they would tease me, and the shame would be worse than the fight itself.Moreover, it was important not just to wave fists, but to win, crush the enemy. Without Kevin, the relationship in our class would be much better and healthier. When my father announced that we would be returning to Massachusetts soon, I could not wait for the cherished day.

    After the 2001 layoffs, we realized that Netflix used to have a handful of people creating an unhealthy atmosphere around them. Many of them did not perform their tasks in the best way, thereby giving the rest a signal: here you can not strain yourself.It is not surprising that the entire team lost enthusiasm under such conditions. After realizing something about the climate in the workplace, in 2002 Patty and I made a commitment to ourselves that our number one task now is to maintain a high concentration of talent and the benefits it provides at all costs. We will hire the best people and pay the most in our segment. We will instill in leaders of any link the freedom and responsibility (C&O), which will allow them to get rid of employees whose behavior or performance leaves much to be desired in time.I set myself a goal: to ensure that the entire staff of Netflix, from technical staff to senior management, is staffed with only the most conscientious and productive people.

    This is the most important point; can be said to be a starting point in the history of Netflix. A dynamic, innovative environment begins with what we have decided to call the creation of a stellar team – recruiting talented employees with a diverse experience and approach who are able to generate new ideas, perform large-scale and responsible tasks and jointly achieve high results.Moreover, the rest of the principles will not work until this first point is set.

    Cocktail “Stardust” recipe – European cuisine: Drinks. “Food”

    Cocktail “Stardust” recipe – European cuisine: Drinks. “Food”

    + Selection of recipes

    Ingredients, detailsSelect recipes

    Include ingredientsExclude ingredientsPopular ingredients

    PumpkinSuccuisSuper paprikaPork Beef

    Recipe type

    Show 0 recipes Clear all 9000R: 3,784 minutes

    Add to recipe book30

    Add
    photos The author of the recipe

    Subscribe

    The classic version of “Stardust” is made with vodka and is often served in a shot.In addition to vodka, it includes peach schnapps, pineapple juice and grenadine syrup.

    Energy value per serving

    Caloric content

    Proteins

    Fats

    Carbohydrates

    kcal

    grams

    grams

    grams

    * Calorie content 40486 mln 9000 Scotland

    10 ml

    Orange liqueur

    10 ml

    Preparation instructions

    3 minutes

    Print

    1Prepare all the ingredients.

    2Pour all ingredients into a mixing glass.

    3Add ice cubes.

    4Stir and pour into a serving glass.

    Recipe tip You can use any other bitter you like instead of Angostura.

    Popular Searches:

    Comments (0):

    Read Also:

    Chef Recipes

    Similar Recipes By Tula Gingerbread

    3 Ingredients

    Add to Recipe Book

    Author: Katerina Book

    6 Recipes 90

    Author: Food

    5 ingredients

    Add to recipe book

    Author: Food

    5 ingredients

    Add to recipe book

    Author: Food

    6 ingredients

    Add to recipe book Author: Food

    6 ingredients

    Add to recipe book

    Author: Solntseva Marianna

    5 ingredients

    Add to recipe book

    Author: Food

    4 ingredients

    Add to recipe book : Solntseva Marianna

    3 ingredients

    D Add to recipe book

    Author: Food

    6 ingredients

    Add to recipe book

    Author: Solntseva Marianna

    4 ingredients

    Add to recipe book

    Author: Food

    5 ingredients

    to the recipe book

    Report an error

    © EDA.RU “, 2021. ALL RIGHTS RESERVED. FOR PERSONS OVER 18 YEARS OLD.

    how hotels are assigned categories / City news / Moscow website

    In 2016, 17.5 million tourists visited the capital. This year it is expected that their number will approach 18 million, and next year it will grow even more thanks to the World Cup, the main city of which will be the Russian capital. To comfortably accommodate everyone, Moscow is developing a hotel chain, opening new hotels and renovating old ones.

    Since 2013, hotels in the capital have been officially assigned star categories. Hotels of the cities hosting the World Cup must receive them without fail.

    Now the stars are not just stickers at the entrance, cut out of colored paper by the administrator, and their number does not depend on the greed of the hotel owners. In different countries they are distributed in different ways, there are also international principles. According to the rules approved by the Ministry of Culture, there are six star categories in Russia: “no stars”, “one”, “two”, “three”, “four” and “five stars”.

    Which category a particular hotel will receive is decided by representatives of special accredited organizations. They carefully check it for many parameters and give points, by the sum of which the category is determined. For large and small hotels, the requirements are slightly different; hotels that occupy historical buildings have their own nuances.

    The “Star” category is valid for only three years, and at the end of the term, the entire verification procedure – building, rooms, personnel – must be repeated.

    Today, more than a thousand Moscow hotels and other accommodation facilities have passed the classification and received the categories: “five stars” (30 objects), “four stars” (82 objects), “three stars” (212 objects), “two stars” (110 objects ), “One star” (46 properties), “no stars” and mini-hotels (606 properties).

    For classified hotels in Moscow, there are exemptions on property tax of organizations, calculated on the basis of cadastral value. The minimum area of ​​the room stock multiplied by a factor of “two” is exempt from taxation.

    What exactly is the difference between each category of stardom can be found out by studying the order of the Ministry of Culture of Russia, which spells out the classification rules. It is this document that the experts are guided by when assigning points to hotels.

    Unrated

    It is easiest for hotels to get this category. There are not many requirements: the building must have a sign, it must be equipped with an emergency lighting system, and guests can always count on hot and cold tap water, heating and ventilation.

    If you have settled in such a hotel, you will find a landline telephone in the lobby and a staff call button in the room. In hotels without stars, as well as with one and two stars, the area of ​​a single room must be at least nine square meters, and a double room must be at least 12 square meters. If the room is designed for a larger number of guests, each of them should have from 4.5 to six square meters – depending on whether the hotel is open seasonally or all year round.

    For hostels, there are slightly different requirements: the area of ​​the room in them must be at least four square meters per bed (single or bunk), and the distance from the upper back of a bunk bed to the ceiling must be at least 75 centimeters.

    Toilets in unrated hotels are generally located in the lobby. Each floor should have one shared toilet for 10 people, but at least two – male and female. One shared bathroom or shower is installed for 20 people living in rooms without a bath or shower. Each of them should have showers and toilet cubicles, a washbasin with hot and cold water, a mirror, a dressing table, soap, clothes hooks and a waste basket.

    In public areas there is a reception and accommodation service, a TV set, furniture and a wardrobe.

    Among the services that guests of starless hotels can count on are accommodation at any time of the day, receiving correspondence, storing valuables in the administration’s safe, luggage storage, calling an ambulance, and using a first-aid kit. You can also ask to wake you up in the morning for an iron and ironing board.

    According to the rules, rooms must be cleaned daily, while making the bed. Bed linen is changed every five days, towels every three days.

    * One-star hotels

    The basic requirements for the next category are basically the same, with only a few clarifications.For example, single and double rooms must account for at least 25 percent of the total number of rooms. True, this rule does not exclude the presence of family rooms for three or more people, of which at least two are adults.

    Also, 25 percent of rooms in one-star hotels should have their own bathrooms with washbasins, toilets, bathtubs or showers. The area of ​​the bathroom must be at least 1.7 square meters. But this requirement does not apply to hotels located in buildings – objects of cultural heritage.In hot climates, 1-star hotels should provide room fans.

    This category also has its own requirements for halls: their area should be from nine to 25 square meters. In addition, the staff should have their own premises – this is a dining room, and bathrooms, and changing rooms, rest rooms and utility rooms.

    Continental breakfast from 07:00 to 10:00 is added to the list of services, and the hotel staff has written standards of work.

    ** Two stars

    As the number of stars increases, so does the list of requirements.To get two stars, single and double rooms must already make up 50 percent of all hotel offers. Also, half of the rooms should have their own bathrooms, the area of ​​which can no longer be less than 2.5 square meters.

    The rooms should have an internal telephone connection (for the hotel), and the area of ​​the common halls will increase to 20-40 square meters.

    Two-star hotels may already have restaurants or cafes. Moreover, if they have a separate entrance, there must be a separate sign with the name.

    At the request of guests, the staff can help bring luggage from the car to the room and from the room to the car. The maids will change bed linen here more often – once every three days. In addition, two-star hotel staff must wear uniforms and service badges.

    *** Three stars

    The most numerous category of Moscow hotels is medium. Such hotels differ from the previous ones even outwardly: buildings and signs are always illuminated at night, there is a short-term parking area nearby, the entrance for guests is separate from the service one.

    Additional equipment requirements include a stationary generator, forced ventilation system, burglar alarms, video surveillance in public areas and corridors, as well as a backup hot water supply system – in case the main one is turned off by utilities. Elevators in three-star hotels should be available, if the building is higher than three floors, it should take no more than 45 seconds to wait for them.

    Telephone communication in the rooms – both internal and city, and from the phones in the lobbies you can call another city or another country.

    Single and double rooms in three-star hotels make up 100 percent of the total number of rooms. Among them may come across multi-room and connecting numbers. The area of ​​a single room must be at least 12 square meters, and a double room must be at least 15 square meters. Private bathrooms are in each of them.

    The area of ​​the hotel hall is already from 30 to 80 square meters. It contains armchairs, sofas, chairs and tables with newspapers and magazines. In the common areas of the three-star hotels, you can find carpets, plants, art compositions and individual safe boxes for storing guests’ valuables.

    Bed linen is changed here, as in a two-star hotel, every three days, and towels are changed more often every day. Guests can also use the services of washing, dry cleaning, minor repairs of clothes, postal and telegraph services, exchange currency, call a taxi, get tourist information and clean shoes using a special machine.

    Guests are offered several options for meals: an extended breakfast, two or three meals a day. Guests don’t even need to go out to eat: Three-star hotels offer room service and a 24-hour menu in the morning.

    * *** Four stars

    Another star is given to hotels for even greater guest comfort. To prevent them from getting wet in the rain or snow, a protective visor should be installed on the way from the car, and an air-thermal curtain should be installed at the entrance to the building to protect it from the cold.

    In areas with insufficient quality drinking water, hotels are equipped with a special installation for its treatment. All rooms have air conditioning systems all year round.

    Four-star hotel elevators are installed in buildings over two floors. Their waiting time should not exceed 30 seconds, and the cabins are equipped for radio broadcasts. In addition to the passenger, the hotel should have a service and freight elevators.

    Guests will be able to call another city or country directly from their room. In addition, there will be internet in public areas.

    The area of ​​single rooms in a four-star hotel cannot be less than 14 square meters, double rooms – less than 16.The bathroom should be 3.8 square meters. The rooms are provided with increased soundproofing – thanks to special doors, windows and coatings, the noise level cannot exceed 35 dB. Having settled in such a room, you can independently regulate the temperature using a thermostat. Your bed linen will be changed every two days.

    The area of ​​common halls can be up to 120 square meters. They serve drinks and music. In the public areas of the hotels there are also sports and fitness centers with gyms, a swimming pool or sauna with a mini-pool, shops and kiosks, a business center with computers, photocopiers and meeting rooms.

    The hotel restaurant may have several halls, as well as a nightclub, bars and cafes. There is a doorman, a tour guide, a guide-translator and a search service for guests. At their request, they can send or receive a fax, arrange a meeting and seeing off, iron their clothes. Guests can count on car rental, booking tickets for various types of transport, as well as theaters, sports and entertainment events. It is mandatory to deliver luggage from the car to the room and back in four-star hotels.

    Guests are provided with meals around the clock, and they can have breakfast on the “buffet” system from 07:00 to 10:00. Room service is also becoming available around the clock.

    ***** Five stars

    There are not many hotels in Moscow yet that have the highest category – of course, getting it is the most difficult because of the high requirements. At least five percent of the room stock here should be occupied by rooms of the highest category: suites, apartments, deluxe, junior suite, studio.These are large rooms with additional functions: a suite, for example, must be at least 75 square meters, from three or more living rooms (living room, dining room, study and bedroom with a non-standard wide double bed), apartments – from two or more rooms with a total area of ​​40 square meters, with a kitchenette.