scholarly journals Reference intervals for selected serum biochemistry analytes in cheetahs (Acinonyx jubatus)

2016 ◽  
Vol 87 (1) ◽  
Author(s):  
Gavin C. Hudson-Lamb ◽  
Johan P. Schoeman ◽  
Emma H. Hooijberg ◽  
Sonja K. Heinrich ◽  
Adrian S.W. Tordiffe
Keyword(s):  
Bootstrap Method ◽  
Parametric Method ◽  
Serum Biochemistry ◽  
Reference Intervals ◽  
Dietary Factors ◽  
Future Health ◽  
Baseline Serum ◽  
Acinonyx Jubatus ◽  
Free Ranging ◽  
Non Parametric

Published haematologic and serum biochemistry reference intervals are very scarce for captive cheetahs and even more for free-ranging cheetahs. The current study was performed to establish reference intervals for selected serum biochemistry analytes in cheetahs. Baseline serum biochemistry analytes were analysed from 66 healthy Namibian cheetahs. Samples were collected from 30 captive cheetahs at the AfriCat Foundation and 36 free-ranging cheetahs from central Namibia. The effects of captivity-status, age, sex and haemolysis score on the tested serum analytes were investigated. The biochemistry analytes that were measured were sodium, potassium, magnesium, chloride, urea and creatinine. The 90% confidence interval of the reference limits was obtained using the non-parametric bootstrap method. Reference intervals were preferentially determined by the non-parametric method and were as follows: sodium (128 mmol/L – 166 mmol/L), potassium (3.9 mmol/L – 5.2 mmol/L), magnesium (0.8 mmol/L – 1.2 mmol/L), chloride (97 mmol/L – 130 mmol/L), urea (8.2 mmol/L – 25.1 mmol/L) and creatinine (88 µmol/L – 288 µmol/L). Reference intervals from the current study were compared with International Species Information System values for cheetahs and found to be narrower. Moreover, age, sex and haemolysis score had no significant effect on the serum analytes in this study. Separate reference intervals for captive and free-ranging cheetahs were also determined. Captive cheetahs had higher urea values, most likely due to dietary factors. This study is the first to establish reference intervals for serum biochemistry analytes in cheetahs according to international guidelines. These results can be used for future health and disease assessments in both captive and free-ranging cheetahs.

scholarly journals Build a Better Bootstrap and the RAWR Shall Beat a Random Path to Your Door: Phylogenetic Support Estimation Revisited

2020 ◽  
Author(s):  
Wei Wang ◽  
Kevin J. Liu
Keyword(s):  
State Of The Art ◽  
Bootstrap Method ◽  
Parametric Method ◽  
Open Data ◽  
Bootstrap Support ◽  
Future Research ◽  
Evolutionary Divergence ◽  
Type I ◽  
Support Estimation ◽  
Non Parametric

AbstractMotivationThe standard bootstrap method is used throughout science and engineering to perform general-purpose non-parametric resampling and re-estimation. Among the most widely cited and widely used such applications is the phylogenetic bootstrap method, which Felsenstein proposed in 1985 as a means to place statistical confidence intervals on an estimated phylogeny (or estimate “phylogenetic support”). A key simplifying assumption of the bootstrap method is that input data are independent and identically distributed (i.i.d.). However, the i.i.d. assumption is an over-simplification for biomolecular sequence analysis, as Felsenstein noted. Special-purpose fully parametric or semi-parametric methods for phylogenetic support estimation have since been introduced, some of which are intended to address this concern.ResultsIn this study, we introduce a new sequence-aware non-parametric resampling technique, which we refer to as RAWR (“RAndom Walk Resampling”). RAWR consists of random walks that synthesize and extend the standard bootstrap method and the “mirrored inputs” idea of Landan and Graur. We apply RAWR to the task of phylogenetic support estimation. RAWR’s performance is compared to the state of the art using synthetic and empirical data that span a range of dataset sizes and evolutionary divergence. We show that RAWR support estimates offer comparable or typically superior type I and type II error compared to phylogenetic bootstrap support as well as GUIDANCE2, a state-of-the-art purpose-built fully parametric method. Additional simulation study experiments help to clarify practical considerations regarding RAWR support estimation. We conclude with thoughts on future research directions and the untapped potential for sequence-aware non-parametric resampling and re-estimation.AvailabilityData and software are publicly available under open-source software and open data licenses at: https://gitlab.msu.edu/liulab/[email protected]

scholarly journals Reference intervals for 33 biochemical analytes in healthy Indian population: C-RIDL IFCC initiative

2018 ◽  
Vol 56 (12) ◽  
pp. 2093-2103 ◽  
Author(s):  
Swarup A.V. Shah ◽  
Kiyoshi Ichihara ◽  
Alpa J. Dherai ◽  
Tester F. Ashavaid
Keyword(s):  
Parametric Method ◽  
Reference Intervals ◽  
Specific Reference ◽  
Appreciable Effect ◽  
Test Results ◽  
Gender And Age ◽  
Sources Of Variation ◽  
Overnight Fasting ◽  
Nested Analysis ◽  
Non Parametric

Abstract Background In 2011, the IFCC Committee on Reference Intervals and Decision Limits (C-RIDL) initiated a worldwide multicenter study on references values facilitating the implementation of country-specific reference intervals (RIs). There has been no well-designed RI study in India. This study aims to derive RIs for 33 major biochemical analytes in carefully selected healthy Indians as defined in C-RIDL protocol. Methods A total of 512 healthy Indians were recruited. Sera collected from overnight fasting blood samples were measured collectively for the analytes. Multiple regression analysis (MRA) and nested analysis of variance (ANOVA) were used to identify the potential sources of variation (SV) of test results. RI were derived by both parametric and non-parametric methods for comparison. The need for secondary exclusion by latent abnormal values exclusion (LAVE) method was examined. Results MRA results indicated that both age and BMI were apparent SV for many analytes in both sexes. ANOVA revealed that partition of RIs by gender and age was required for 17 analytes (TC, HDL-C, TG, hsCRP, ALB, AST, ALT, ALP, GGT, TBil, Urea, CRE, UA, Fe, TTR, CK and IgM) and 5 (Glu, ALB, TC, ALP and Urea), respectively. RIs by parametric method were generally narrower than by non-parametric method, reflecting distorted peripheral distributions of test results. The LAVE method had no appreciable effect on RIs possibly due to inconsistency among abnormal values of related analytes. Conclusions This study has for the first time provided comprehensive RIs information in healthy Indians. The final RIs adopted were those derived by parametric method without LAVE procedure.

Establishment of reference intervals of clinical chemistry analytes for the adult population in Saudi Arabia: a study conducted as a part of the IFCC global study on reference values

2016 ◽  
Vol 54 (5) ◽  
Author(s):  
Anwar Borai ◽  
Kiyoshi Ichihara ◽  
Abdulaziz Al Masaud ◽  
Waleed Tamimi ◽  
Suhad Bahijri ◽  
...  
Keyword(s):  
Reference Values ◽  
Clinical Chemistry ◽  
Adult Population ◽  
Parametric Method ◽  
Reference Intervals ◽  
Test Results ◽  
Upper Limits ◽  
High Prevalence ◽  
Global Study ◽  
Non Parametric

AbstractBackground:This study is a part of the IFCC-global study to derive reference intervals (RIs) for 28 chemistry analytes in Saudis.Method:Healthy individuals (n=826) aged ≥18 years were recruited using the global study protocol. All specimens were measured using an Architect analyzer. RIs were derived by both parametric and non-parametric methods for comparative purpose. The need for secondary exclusion of reference values based on latent abnormal values exclusion (LAVE) method was examined. The magnitude of variation attributable to gender, ages and regions was calculated by the standard deviation ratio (SDR). Sources of variations: age, BMI, physical exercise and smoking levels were investigated by using the multiple regression analysis.Results:SDRs for gender, age and regional differences were significant for 14, 8 and 2 analytes, respectively. BMI-related changes in test results were noted conspicuously for CRP. For some metabolic related parameters the ranges of RIs by non-parametric method were wider than by the parametric method and RIs derived using the LAVE method were significantly different than those without it. RIs were derived with and without gender partition (BMI, drugs and supplements were considered).Conclusions:RIs applicable to Saudis were established for the majority of chemistry analytes, whereas gender, regional and age RI partitioning was required for some analytes. The elevated upper limits of metabolic analytes reflects the existence of high prevalence of metabolic syndrome in Saudi population.

scholarly journals Establishment of reference intervals of biochemical analytes for South African adults: a study conducted as part of the IFCC global multicentre study on reference values

2021 ◽  
pp. 8-23
Author(s):  
FC Smit ◽  
K Ichihara ◽  
J George ◽  
E Blanco-Blanco ◽  
M Hoffmann ◽  
...  
Keyword(s):  
South African ◽  
Reference Values ◽  
Clinical Chemistry ◽  
Parametric Method ◽  
Density Lipoprotein ◽  
Reference Intervals ◽  
Mixed Ancestry ◽  
Serum Samples ◽  
Age Related ◽  
Non Parametric

Objective: This study was conducted as a part of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) global study for establishing reference intervals (RIs) of common laboratory tests for the South African population considering gender, ethnicity, age and body mass index (BMI). Methods: The researchers recruited 1 143 apparently healthy volunteers aged 18–65: 551 African (Afr) and 592 non-African (NAfr) (comprising 383 Caucasian and 209 Mixed Ancestry). Serum samples were measured for 40 chemistry and immunochemistry analytes. The standard deviation ratio (SDR) guided the need for partitioning reference values according to gender, ethnicity and age using a threshold of ≥ 0.4. The latent abnormal values exclusion (LAVE) method was applied to reduce influences of latent diseases before deriving RIs using both parametric and non-parametric methods. Results: Based on SDRsex, males showed higher albumin, uric acid, creatinine, AST, CK and ferritin. Based on SDRRC, Afr compared to NAfr showed (i) higher total protein, amylase, CRP, immunoglobulin G and A and (ii) lower total bilirubin, total cholesterol, low-density lipoprotein cholesterol (LDL-C), ALT and cholinesterase. Both age-related changes in glucose and LDL-C, and BMI-related changes in ALT, ALP and LDH were more prominent in NAfr. RIs were determined according to gender, age and ethnicity. The LAVE method was effective in lowering the upper RI limits (UL) of nutritional markers such as γGT and CRP. Compared to the non-parametric method, the parametric method gave narrower confidence intervals of ULs for analytes with skewed distributions. Conclusion: Establishing RIs by considering ethnicity was essential in many analytes in South Africa. Age and BMI-related changes differed greatly between Afr and NAfr.

scholarly journals Circulant Singular Spectrum Analysis to Monitor the State of the Economy in Real Time

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1169
Author(s):  
Juan Bógalo ◽  
Pilar Poncela ◽  
Eva Senra
Keyword(s):  
Business Cycles ◽  
Real Time ◽  
Parametric Method ◽  
Singular Spectrum Analysis ◽  
The State ◽  
Signal Extraction ◽  
Alternative Procedure ◽  
State Of The Economy ◽  
Regular Patterns ◽  
Non Parametric

Real-time monitoring of the economy is based on activity indicators that show regular patterns such as trends, seasonality and business cycles. However, parametric and non-parametric methods for signal extraction produce revisions at the end of the sample, and the arrival of new data makes it difficult to assess the state of the economy. In this paper, we compare two signal extraction procedures: Circulant Singular Spectral Analysis, CiSSA, a non-parametric technique in which we can extract components associated with desired frequencies, and a parametric method based on ARIMA modelling. Through a set of simulations, we show that the magnitude of the revisions produced by CiSSA converges to zero quicker, and it is smaller than that of the alternative procedure.

scholarly journals Modeling Post-Liberalized European Gas Market Concentration—A Game Theory Perspective

Forecasting ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. 1-16
Author(s):  
Hassan Hamie ◽  
Anis Hoayek ◽  
Hans Auer
Keyword(s):  
Game Theory ◽  
Statistical Tests ◽  
Parametric Method ◽  
Linear Complementarity Problems ◽  
Market Concentration ◽  
Cournot Equilibrium ◽  
Gas Markets ◽  
Gas Market ◽  
Equilibrium Test ◽  
Non Parametric

The question of whether the liberalization of the gas industry has led to less concentrated markets has attracted much interest among the scientific community. Classical mathematical regression tools, statistical tests, and optimization equilibrium problems, more precisely non-linear complementarity problems, were used to model European gas markets and their effect on prices. In this research, the parametric and nonparametric game theory methods are employed to study the effect of the market concentration on gas prices. The parametric method takes into account the classical Cournot equilibrium test, with assumptions on cost and demand functions. However, the non-parametric method does not make any prior assumptions, a factor that allows greater freedom in modeling. The results of the parametric method demonstrate that the gas suppliers’ behavior in Austria and The Netherlands gas markets follows the Nash–Cournot equilibrium, where companies act rationally to maximize their payoffs. The non-parametric approach validates the fact that suppliers in both markets follow the same behavior even though one market is more liquid than the other. Interestingly, our findings also suggest that some of the gas suppliers maximize their ‘utility function’ not by only relying on profit, but also on some type of non-profit objective, and possibly collusive behavior.

Hematologic and serum biochemistry reference intervals using defined ASCVP methodology for laboratory natal multimammate mice (Mastomys natalensis)

2021 ◽  
pp. 002367722110185
Author(s):  
Brian J Smith ◽  
Patrick W Hanley ◽  
Ousmane Maiga ◽  
Maarit N Culbert ◽  
Marissa J Woods ◽  
...  
Keyword(s):  
Complete Blood Count ◽  
Age Groups ◽  
Serum Biochemistry ◽  
Reference Intervals ◽  
Laboratory Research ◽  
Data Sets ◽  
Mastomys Natalensis ◽  
Complete Blood Counts ◽  
Multimammate Mice ◽  
Female Laboratory

Complete blood count, serum chemistry values, and biological reference intervals were compared between two age groups (34–49 and 84–120 days old) of healthy male and female laboratory raised natal multimammate mice ( Mastomys natalensis). Blood was collected via cardiocentesis under isoflurane anesthesia. Data sets of machine automated complete blood counts and clinical chemistries were analyzed. Significant differences between sex and age groups of the data sets were defined. The baseline hematologic and serum biochemistry values described here can improve interpretation of laboratory research using natal multimammate mice.

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