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Background : High body weight variability (BWV) is associated with many metabolic and cardiovascular diseases in adults. The study was designed to explore the baseline characteristics associated with high BWV. Methods : Using a nationally representative database from the Korean National Health Insurance system, 77,424 individuals who underwent five health examinations between 2009 and 2013 were enrolled. BWV was calculated using the body weight recorded at each examination, and the clinical and demographic characteristics associated with high BWV were investigated. High BWV was defined as the highest quartile of coefficient variation in body weight. Results : Subjects with high BWV were younger, more commonly female, less likely to have a high income, and more likely to be a current smoker. Young people under the age of 40 years were more than twice as likely to have high BWV compared with those over 65 years (odds ratio [OR], 2.17; 95% confidence interval [CI], 1.88 to 2.50). The incidence of high BWV was higher in female than in male (OR, 1.67; 95% CI, 1.59 to 1.76). Male with the lowest income had a 1.9-fold higher risk of high BWV compared to male with the highest income (OR, 1.97; 95% CI, 1.81 to 2.13). A high BWV in female was associated with heavy alcohol intake (OR, 1.50; 95% CI, 1.17 to 1.91) and current smoking (OR, 1.97; 95% CI, 1.67 to 2.33). Conclusion : Young people, female, low income, and unhealthy behaviors were independently associated with high BWV. Further research is needed on the mechanisms linking high BWV to detrimental health outcomes.

NADC34-like porcine reproductive and respiratory virus (PRRSV) has had a significant impact on the pig industry, particularly in China. However, the evolutionary characteristics and pathogenicity of NADC34-like PRRSV strains within intensive farming systems are not well understood, particularly regarding the biological characteristic variation of successive outbreaks on a farm. In this study, we conducted continuous surveillance in an intensive farm that experienced a PRRSV outbreak. Two PRRSV strains, GDHZ109/2020 and GDYS162/2022, were isolated and fully sequenced from the same swine farm in Guangdong Province in 2020 and 2022, respectively. Evolutionary analysis based on the ORF5 gene revealed that both strains clustered with NADC34-like strains and shared 96.5% homology. Analysis of the full-length genome and NSP2 gene classified the strains into lineage 1.8, represented by the NADC30 strain. Recombination analysis suggested complex recombination patterns for both strains, involving NADC30-like, NADC34-like, and JXA1-like strains. Although many recombinant regions were nearly identical, there were differences observed in the NSP5–NSP7 region. Pathogenicity experiments conducted on piglets demonstrated that GDHZ109/2020 exhibited higher pathogenicity compared to GDYS162/2022. Piglets in the GDHZ109/2020 infected group had more severe clinical signs and higher mortality. Moreover, analysis of respiratory microbial diversity indicated a significant increase in the abundance of potentially pathogenic microbiota, such as Klebsiella and Erysipelothrix contributing to the respiratory tract of PRRSV-infected piglets, suggesting secondary infections due to differences in immune defense. These findings highlight the importance of NADC34-like recombinant strains' evolution during the farm's epidemic period, which may have contributed to changes in pathogenicity. This study improves our understanding of the current prevalence of PRRSV and provides novel insights into the prevention and control of PRRSV. [ABSTRACT FROM AUTHOR]

An individual's telomere length early in life may reflect or contribute to key life‐history processes sensitive to environmental variation. Yet, the relative importance of genetic and environmental factors in shaping early‐life telomere length is not well understood as it requires samples collected from multiple generations with known developmental histories. We used a confirmed pedigree and conducted an animal model analysis of telomere lengths obtained from nestling house sparrows (Passer domesticus) sampled over a span of 22 years. We found significant additive genetic variation for early‐life telomere length, but it comprised a small proportion (9%) of the total biological variation. Three sources of environmental variation were important: among cohorts, among‐breeding attempts within years, and among nestmates. The magnitude of variation among breeding attempts and among nestmates also differed by cohort, suggesting that interactive effects of environmental factors across time or spatial scales were important, yet we were unable to identify the specific causes of these interactions. The mean amount of precipitation during the breeding season positively predicted telomere length, but neither weather during a given breeding attempt nor date in the breeding season contributed to an offspring's telomere length. At the level of individual nestlings, offspring sex, size and mass at 10 days of age also did not predict telomere length. Environmental effects appear especially important in shaping early‐life telomere length in some species, and more focus on how environmental factors that interact across scales may help to explain some of the variation observed among studies. [ABSTRACT FROM AUTHOR]

The PR domain-containing 9 or PRDM9 is a gene recognized for its fundamental role in meiosis, a process essential for forming reproductive cells. Recent findings have implicated alterations in the PRDM9, particularly its zinc finger motifs, in the onset and progression of cancer. This association is manifested through genomic instability and the misregulation of genes critical to cell growth, proliferation, and differentiation. In our comprehensive study, we harnessed advanced bioinformatic mining tools to delve deep into the intricate relationship between PRDM9F and cancer. We analyzed 136,752 breakpoints and found an undeniable association between specific PRDM9 motifs and the occurrence of double-strand breaks, a phenomenon evidenced in every cancer profile examined. Utilizing R statistical querying and the Regioner package, 55 unique sequence variations of PRDM9 were statistically correlated with cancer, from a pool of 1024 variations. A robust analysis using the Enrichr tool revealed prominent associations with various cancer types. Moreover, connections were noted with specific phenotypic conditions and molecular functions, underlining the pervasive influence of PRDM9 variations in the biological spectrum. The Reactome tool identified 25 significant pathways associated with cancer, offering insights into the mechanistic underpinnings linking PRDM9 to cancer progression. This detailed analysis not only confirms the pivotal role of PRDM9 in cancer development, but also unveils a complex network of biological processes influenced by its variations. The insights gained lay a solid foundation for future research aimed at deciphering the mechanistic pathways of PRDM9, offering prospects for targeted interventions and innovative therapeutic approaches in cancer management. [ABSTRACT FROM AUTHOR]

Pseudotime analysis with single-cell RNA-sequencing (scRNA-seq) data has been widely used to study dynamic gene regulatory programs along continuous biological processes. While many methods have been developed to infer the pseudotemporal trajectories of cells within a biological sample, it remains a challenge to compare pseudotemporal patterns with multiple samples (or replicates) across different experimental conditions. Here, we introduce Lamian, a comprehensive and statistically-rigorous computational framework for differential multi-sample pseudotime analysis. Lamian can be used to identify changes in a biological process associated with sample covariates, such as different biological conditions while adjusting for batch effects, and to detect changes in gene expression, cell density, and topology of a pseudotemporal trajectory. Unlike existing methods that ignore sample variability, Lamian draws statistical inference after accounting for cross-sample variability and hence substantially reduces sample-specific false discoveries that are not generalizable to new samples. Using both real scRNA-seq and simulation data, including an analysis of differential immune response programs between COVID-19 patients with different disease severity levels, we demonstrate the advantages of Lamian in decoding cellular gene expression programs in continuous biological processes. Pseudotime analysis is prevalent in single-cell RNA-seq, but it remains challenging to perform it across multiple samples and experimental conditions. Here, the authors develop Lamian, a computational framework for multi-sample pseudotime analysis that adjusts for biological and technical variation to detect gene program changes along cell trajectories and across conditions. [ABSTRACT FROM AUTHOR]

Background: In treatment planning for proton therapy a constant Relative Biological Effectiveness (RBE) of 1.1 is used, disregarding variations with linear energy transfer, clinical endpoint, or fractionation. Purpose: To present a methodology to analyze the variation of RBE with fractionation from clinical data of tumor control probability (TCP) and to apply it to study the response of prostate cancer to proton therapy. Methods and materials: We analyzed the dependence of the RBE on the dose per fraction by using the LQ model and the Poisson TCP formalism. Clinical tumor control probabilities for prostate cancer (low and intermediate risk) treated with photon and proton therapy for conventional fractionation (2 Gy(RBE)×37 fractions), moderate hypofractionation (3 Gy(RBE)×20 fractions) and hypofractionation (7.25 Gy(RBE)×5 fractions) were obtained from the literature and analyzed aiming at obtaining the RBE and its dependence on the dose per fraction. Results: The theoretical analysis of the dependence of the RBE on the dose per fraction showed three distinct regions with RBE monotonically decreasing, increasing or staying constant with the dose per fraction, depending on the change of (α, β) values between photon and proton irradiation (the equilibrium point being at (αp/βp) = (αX/βX)(αX/αp)). An analysis of the clinical data showed RBE values that decline with increasing dose per fraction: for low risk RBE≈1.124, 1.119, and 1.102 for 1.82 Gy, 2.73 Gy and 6.59 Gy per fraction (physical proton doses), respectively; for intermediate risk RBE≈1.119 and 1.102 for 1.82 Gy and 6.59 Gy per fraction (physical proton doses), respectively. These values are nonetheless very close to the nominal 1.1 value. Conclusions: In this study, we have presented a methodology to analyze the RBE for different fractionations, and we used it to study clinical data for prostate cancer and evaluate the RBE versus dose per fraction. The analysis shows a monotonically decreasing RBE with increasing dose per fraction, which is expected from the LQ formalism and the changes in (α, β) values between photon and proton irradiation. However, the calculations in this study have to be considered with care as they may be biased by limitations in the modeling assumptions and/or by the clinical data set used for the analysis. [ABSTRACT FROM AUTHOR]

Evolutionary cell biology is an emerging field that explores how cellular processes have been shaped by evolution, and conversely, how cell biological variation has influenced the evolutionary process. Complementing insights from comparative phylogenetics, experimental evolution is now increasingly used in combination with cell biological assays to replay segments of evolutionary history in real time. Formal adoption of experimental evolution into the established evolutionary cell biology toolbox requires an integrated experimental framework with tailored experimental design. Evolutionary cell biology explores the origins, principles, and core functions of cellular features and regulatory networks through the lens of evolution. This emerging field relies heavily on comparative experiments and genomic analyses that focus exclusively on extant diversity and historical events, providing limited opportunities for experimental validation. In this opinion article, we explore the potential for experimental laboratory evolution to augment the evolutionary cell biology toolbox, drawing inspiration from recent studies that combine laboratory evolution with cell biological assays. Primarily focusing on approaches for single cells, we provide a generalizable template for adapting experimental evolution protocols to provide fresh insight into long-standing questions in cell biology. [ABSTRACT FROM AUTHOR]

Background: Laboratory results are influenced by presence and severity of disease, as well as preanalytical factors, analytical variation, and biological variation. Biological variation data for urinary protein: creatinine ratio (UPC) and urine specific gravity (USG) in cats are lacking. Objectives: Determine the biological variation of UPC and USG in cats. Animals: Eighty healthy client‐owned cats. Methods: Prospective study. Urine was collected on days 0, 14, and 56 from all 80 cats to investigate the persistence of borderline or overt proteinuria or suboptimal urine concentration. In 15 of these cats, urine was collected weekly from day 0 to 42 to calculate the index of individuality (II) and reference change value (RCV), and on days 56 and 57 to evaluate day‐to‐day variability of UPC and USG. Results: Borderline or overt proteinuria (UPC ≥0.2) was present in 18/80 (23%) cats at baseline and persisted on 3 occasions in 2 months in 8/18 (44%) cats. Urine concentration was suboptimal at inclusion (USG <1.035) in 8/80 (10%) cats and at all 3 time points during 2 months in 3/8 (38%) cats. The II of UPC and USG indicated intermediate individuality. The 1‐sided RCV was 82% for UPC and 36% for USG. Proteinuria substage was identical on 2 consecutive days in 13/15 (87%) cats, and urine concentrating ability remained the same in all 15 cats. Conclusions and Clinical Importance: A >82% increase in UPC in a healthy cat is not solely attributable to physiological and analytical variation. For USG, a decrease of >36% is considered clinically relevant. [ABSTRACT FROM AUTHOR]

The response of immunogenecity anti‐drug antibody (ADA) generally includes biological and analytical variability. The nature of biological and analytical variations may lead to a variety of symmetric and asymmetric ADA data. As a result, current statistical methods may yield unreliable results because these methods assume special types of symmetric or asymmetric ADA data. In this paper, we survey and compare parametric models that are useful for analyzing a variety of asymmetric data that have rarely been used to calculate assay cut points. These models include symmetric distributions as limiting case; therefore, they are useful in the analysis of a variety of symmetric data. We also investigate two nonparametric approaches that have received little attention in screening cut point calculations. A simulation study was conducted to compare the performance of the methods. We evaluate the methods using four published different types of data, and make recommendations concerning the use of the methods. [ABSTRACT FROM AUTHOR]

The process of building a model or copy of a real-world system and assessing its behaviour under various scenarios is referred to as simulation. Simulation in population genetics is the process of simulating a population's genetic makeup and evolutionary history using mathematical models and computer algorithms. It is important in population genetics for a better understanding of the impact of various evolutionary and demographic scenarios on sequence variation and patterns, it allows investigators to better assess and design analytical methods in the study of disease-associated genetic factors. This is an important tool for studying population genetic diversity and how natural selection, genetic drift, mutation, migration, and other evolutionary forces have influenced the genetic makeup of the population. There are three fundamental frameworks for simulation: coalescent, forward, and resampling methods. Numerous simulators that fit under these frameworks can be compared in terms of their evolutionary and demographic scenarios, computing complexity, and particular applications. Population simulation is becoming increasingly important in evolutionary biology, enabling researchers to explore the effects of various genetic models on genetic diversity and DNA sequence patterns. [ABSTRACT FROM AUTHOR]

Objective In this study, we aimed to evaluate the serum creatinine (SCr) levels with the reference change value (RCV) in patients receiving colistin treatment. Methods We retrospectively recorded the SCr levels of 47 patients receiving colistin treatment before treatment and on days 3 and 7 after treatment. RCV was calculated with the asymmetrical RCV formula (Z  = 1.64, P  < .05). Percent (%) increase in the SCr results of the patients was compared with RCV and values exceeding RCV were regarded as statistically significant. Results The RCV was calculated as 15.6% for SCr. Compared with pretreatment values, SCr value on day 3 was 32/47 and on day 7 it was 36/47; as these results exceeded RCV, they were considered statistically significant. Conclusion Use of RCV in the interpretation of results between serial measurements will provide a more rapid and sensitive method when making decisions. [ABSTRACT FROM AUTHOR]

Single-cell measurements routinely demonstrate high levels of variation between cells, but fewer studies provide insight into the analytical and biological sources of this variation. This is particularly true of chemical cytometry, in which individual cells are lysed and their contents separated, compared to more established single-cell measurements of the genome and transcriptome. To characterize population-level variation and its sources, we analyzed oxidative stress levels in 1278 individual Dictyostelium discoideum cells as a function of exogenous stress level and cell cycle position. Cells were exposed to varying levels of oxidative stress via singlet oxygen generation using the photosensitizer Rose Bengal. Single-cell data reproduced the dose–response observed in ensemble measurements by CE-LIF, superimposed with high levels of heterogeneity. Through experiments and data analysis, we explored possible biological sources of this heterogeneity. No trend was observed between population variation and oxidative stress level, but cell cycle position was a major contributor to heterogeneity in oxidative stress. Cells synchronized to the same stage of cell division were less heterogeneous than unsynchronized cells (RSD of 37–51% vs 93%), and mitotic cells had higher levels of reactive oxygen species than interphase cells. While past research has proposed changes in cell size during the cell cycle as a source of biological noise, the measurements presented here use an internal standard to normalize for effects of cell volume, suggesting a more complex contribution of cell cycle to heterogeneity of oxidative stress. [ABSTRACT FROM AUTHOR]

When the patient's mean (setpoint) concentration of an analyte is unknown and the physician tries to judge the clinical condition from the analyte concentration in two separate specimens taken a time apart, we believe that the two values should be judged against a bivariate reference interval derived from clinically healthy and stable individuals, rather than using univariate reference limits and comparing the difference between the values against reference change values (RCVs). In this work we compared the two models, using s-TSH as an example. We simulated two s-TSH measurement values for 100,000 euthyreot subjects, and plotted the second value against the first, along with a markup of the central 50, 60, 70, 80, 90, and 95 % of the bivariate distribution, in addition to the 2.5 and 97.5 percentile univariate reference limits and the 2.5 and 97.5 percentile RCVs. We also estimated the diagnostic accuracy of the combination of the 2.5 and 97.5 univariate percentile reference limits and the 2.5 and 97.5 percentile RCVs against the central 95 % of the bivariate distribution. Graphically, the combination of the 2.5 and 97.5 univariate reference limits and the 2.5 and 97.5 percentile RCVs did not accurately delineate the central 95 % of the bivariate distribution. Numerically, the sensitivity and specificity of the combination were 80.2 and 92.2 %, respectively. The concentrations of s-TSH measured in two samples taken at separate times from a clinically healthy and stable individual cannot be accurately interpreted using the combination of univariate reference limits and RCVs. [ABSTRACT FROM AUTHOR]

The ratio of tubular maximum reabsorption of phosphate to glomerular filtration rate (TmP/GFR) is used to evaluate renal phosphate transport. TmP/GFR is most probably calculated using the formula described by Kenny and Glen or obtained from the nomogram described by Walton and Bijvoet. Even though the calculation itself is well described, no attention has been given to its measurement uncertainty (MU). The aim of this study is to provide a procedure for evaluating the MU of the Kenny and Glen formula; a procedure which is based on the Evaluation of measurement data – Guide to the expression of uncertainty in measurement (GUM). TmP/GFR is a quantity value calculated from the input of measured values for serum (plasma) phosphate and creatinine, plus measured values of urine phosphate and creatinine. Given the measurement uncertainty associated with these input quantities, the GUM describes the mathematical procedures required to determine the uncertainty of the calculated TmP/GFR. From a medical laboratory perspective, these input uncertainties are the standard deviations of the respective internal quality control estimates for serum and urine phosphate, plus serum and urine creatinine. Based on representative measurements for the input quantities and their associated standard uncertainties, the expanded relative uncertainty for a calculated TmP/GFR is approximately 3.0–4.5 %. With the continued relevance of the TmP/GFR procedure and the use of creatinine clearance as an estimate of GFR, the addition of an uncertainty estimate is important as an adjunct to this diagnostic procedure. [ABSTRACT FROM AUTHOR]

C-peptide and insulin are peptide hormones and their stability is affected by a number of pre-analytical factors. The study aimed to investigate the impact of sample type, storage temperature and time delays before centrifugation and analysis on the stability of C-peptide and insulin. Ten healthy non-diabetic adults in fasting and non-fasting state were enrolled. 40 mL of blood was collected from each participant into SST and dipotassium EDTA tubes. Samples were centrifuged immediately or at timed intervals (8, 12, 48 and 72 h). After baseline measurements on the Roche Cobas e602 analyzer using electrochemiluminescence immunoassays, aliquots were stored at room temperature (RT), 2–8 and −20 °C for 4 h to 30 days. The percentage deviation (PD) from baseline was calculated and a change greater than desirable biological variation total error was considered clinically significant. C-peptide was more stable in separated serum than plasma (PD of −5 vs. −13 %) samples stored at 2–8 °C for 7 days and was most unstable at RT when centrifugation was delayed (PD −46 % in plasma and −74 % in serum after 48 h). Insulin was more stable in plasma than in serum under the different storage conditions with a minimum PD of −1% when stored at −20 °C for 30 days. When samples were kept unspun at RT for 72 h, PD was −23 and −80 % in plasma and serum, respectively. C-peptide was more stable in serum provided the sample was centrifuged immediately and stored in the fridge or freezer while insulin was found to be more stable in EDTA plasma. [ABSTRACT FROM AUTHOR]

Biological variation (BV) plays a crucial role in determining analytical performance specifications, assessing serial measurements of individuals, and establishing the use of population-based reference intervals. Our study aimed to calculate the BV and BV-based quality goals of 25-hydroxyvitamin D3 (25-OH D3), ferritin, folate and vitamin B12 tests. We included a total of 22 apparently healthy volunteers (9 women and 13 men) aged 18-55 years in the study that we conducted in Turkey. Blood samples were collected from the participants once a week for five weeks. Serum ferritin, folate and vitamin B12 levels were measured using immunochemical method, while plasma 25-OH D3 levels were determined using the high-performance liquid chromatography method. Analysis of variance (ANOVA) was used to estimate analytical variation(CVA), within-subject BV(CVI) and between-subject BV(CVG). The individuality index (II) and reference change value (RCV) were calculated based on these data. The CVI of 25-OH D3, ferritin, folate, and vitamin B12 were found to be 1.8% (0.6%-2.5%), 16.9% (14.4%-20.2%), 10.7% (9.2%-12.7%), and 8.6% (6.8%-10.5%), respectively. CVG were 44.2% (34.3%-69.9%), 132% (87.7%-238%), 19.4% (14.4%-28.8%), and 39.6% (29.8%-59.0%) for the same biomarkers, while CVA were 3.2% (2.81%-3.71%), 3.5% (3.1%-4.1%), 4.0% (3.5%-4.6%), and 7.5% (6.6%-8.6%), respectively. The II values for 25-OH D3, ferritin, folate, and vitamin B12 were calculated as 0.04, 0.13, 0.55, and 0.22, respectively. The RCV were 10.2%, 47.8%, 31.7%, and 31.6%, respectively. Because the tests analyzed in this study exhibit high individuality, RCV should be preferred rather than population-based reference ranges in clinical interpretation of results. [ABSTRACT FROM AUTHOR]

Background: Quantification of drug-target binding is critical for confirming that drugs reach their intended protein targets, understanding the mechanism of action, and interpreting dose-response relationships. For covalent inhibitors, target engagement can be inferred by free target levels before and after treatment. Targeted mass spectrometry assays offer precise protein quantification in complex biological samples and have been routinely applied in pre-clinical studies to quantify target engagement in frozen tumor tissues for oncology drug development. However, frozen tissues are often not available from clinical trials so it is critical that assays are applicable to formalin-fixed, paraffin-embedded (FFPE) tissues in order to extend mass spectrometry-based target engagement studies into clinical settings. Methods: Wild-type RAS and RASG12C was quantified in FFPE tissues by a highly optimized targeted mass spectrometry assay that couples high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) with internal standards. In a subset of samples, technical reproducibility was evaluated by analyzing consecutive tissue sections from the same tumor block and biological variation was accessed among adjacent tumor regions in the same tissue section. Results: Wild-type RAS protein was measured in 32 clinical non-small cell lung cancer tumors (622–2525 amol/µg) as measured by FAIMS-PRM mass spectrometry. Tumors with a known KRASG12C mutation (n = 17) expressed a wide range of RASG12C mutant protein (127–2012 amol/µg). The variation in wild-type RAS and RASG12C measurements ranged 0–18% CV across consecutive tissue sections and 5–20% CV among adjacent tissue regions. Quantitative target engagement was then demonstrated in FFPE tissues from 2 xenograft models (MIA PaCa-2 and NCI-H2122) treated with a RASG12C inhibitor (AZD4625). Conclusions: This work illustrates the potential to expand mass spectrometry-based proteomics in preclinical and clinical oncology drug development through analysis of FFPE tumor biopsies. [ABSTRACT FROM AUTHOR]

Background: Relying on freezer stored biospecimens is preferred in epidemiolocal studies exploring environmental pregnancy exposures and later offspring health. Storage duration may increase the pre-analytical variability, potentially adding measurement uncertainty. We investigated evaporation of maternal serum after long-term biobank storage using ions (sodium, Na+; chloride, Cl-) recognized for stability and relatively narrow normal biological reference ranges in human serum. Methods: A chemical analysis study of 275 biobanked second trimester maternal serum from a large Danish pregnancy screening registry. Serum samples were collected between 1985–1995 and stored at -20°C. Ion concentrations were quantified with indirect potentiometry using a Roche Cobas 6000 analyzer and compared according to storage time and normal biological ranges in second trimester. Ion concentrations were also compared with normal biological variation assessed by baseline Na+ and Cl- serum concentrations from a separate cohort of 24,199 non-pregnant women measured before freezing with the same instrument. Results: The overall mean ion concentrations in biobanked serum were 147.5 mmol/L for Na+ and 109.7 for Cl-. No marked linear storage effects were observed according to storage time. Ion concentrations were consistently high across sampling years, especially for specific sampling years, and a relatively large proportion were outside respective normal ranges in second trimester: 38.9% for Na+ and 43.6% for Cl-. Some variation in concentrations was also evident in baseline serum used as quality controls. Conclusions: Elevated ion concentrations suggest evaporation, but independent of storage duration in the present study (27–37 years). Any evaporation may have occurred prior to freezer storage or during the first 27 years. Other pre-analytical factors such as low serum volume have likely influenced the concentrations, particularly given the high within year variability. Overall, we consider the biobanked serum samples internally comparable to enable their use in epidemiological studies. [ABSTRACT FROM AUTHOR]

"Sex" is often used to describe a suite of phenotypic and genotypic traits of an organism related to reproduction. However, these traits—gamete type, chromosomal inheritance, physiology, morphology, behavior, etc.—are not necessarily coupled, and the rhetorical collapse of variation into a single term elides much of the complexity inherent in sexual phenotypes. We argue that consideration of "sex" as a constructed category operating at multiple biological levels opens up new avenues for inquiry in our study of biological variation. We apply this framework to three case studies that illustrate the diversity of sex variation, from decoupling sexual phenotypes to the evolutionary and ecological consequences of intrasexual polymorphisms. We argue that instead of assuming binary sex in these systems, some may be better categorized as multivariate and nonbinary. Finally, we conduct a meta-analysis of terms used to describe diversity in sexual phenotypes in the scientific literature to highlight how a multivariate model of sex can clarify, rather than cloud, studies of sexual diversity within and across species. We argue that such an expanded framework of "sex" better equips us to understand evolutionary processes, and that as biologists, it is incumbent upon us to push back against misunderstandings of the biology of sexual phenotypes that enact harm on marginalized communities. [ABSTRACT FROM AUTHOR]

Background: There are varied reports on the effect of sample timing on thyroid-stimulating hormone (TSH) interpretation and its role in under- or over-diagnosing subclinical hypothyroidism. This study was undertaken to evaluate the difference in consecutive values of TSH in fasting and post-prandial samples and interpret the clinical relevance of the difference obtained using parameters such as measurement uncertainty (MU) and reference change value (RCV) which are based on analytical and biological variations. Methods: The fasting and post-prandial TSH were evaluated in 30 paired specimens of apparently healthy individuals. TSH was analysed using chemiluminescence technology. MU was calculated from 6-month cumulative internal quality control data, and RCV was obtained from the published literature. Results: The study showed that fasting TSH levels were higher than post-prandial TSH. However, 90% of the difference observed between the pairs at lower concentrations of TSH was within laboratory MU, and 100% of the difference observed at higher concentrations of TSH was within the MU. When the difference obtained was compared with RCV (which includes both analytical and intra-individual variations), the difference was within the RCV across all concentrations. Conclusions: Although TSH values in the fasting specimens were higher than the post-prandial samples, a comparison of the difference obtained with MU and RCV shows that the difference was well within these parameters and hence less likely to be a clinically significant difference. Thus, the RCV of analytes may be used as a guide in the interpretation of consecutive samples or serial measurements of analytes. [ABSTRACT FROM AUTHOR]

The trajectory of human aging varies widely from one individual to the next due to complex interactions between the genome and the environment that influence the aging process. Such differences in age-specific mortality and disease risk among same-aged individuals reflect variation in the pace of biological aging. Certain mechanisms involved in the progression of biological aging originate in the epigenome, where chemical modifications to the genome are able to alter gene expression without modifying the underlying DNA sequence. The epigenome serves as an interface for environmental signals, which are able to "get under the skin" to influence health and aging. A number of the molecular mechanisms involved in the aging process have been identified, although few aging phenotypes have been definitively traced to their underlying molecular causes thus far. In this review, we discuss variation in human biological aging and the epigenome's role in promoting heterogeneity in human longevity and healthspan. [ABSTRACT FROM AUTHOR]

Measurements on clinical chemistry analysers must be verified to demonstrate applicability to their intended clinical use. We verified the performance of measurements on the Siemens Atellica® Solution chemistry analysers against the clinically acceptable analytical performance specifications, CAAPS, including the component of intra-individual biological variation, CVI. The relative standard uncertainty of measurement, i.e. analytical variation, CVA, was estimated for six example measurands, haemoglobin A1c in whole blood (B-HbA1c), albumin in urine (U-Alb), and the following measurands in plasma: sodium (P-Na), pancreatic amylase (P-AmylP), low-density lipoprotein cholesterol (P-LDL-C), and creatinine (P-Crea). Experimental CVA was calculated from single-instrument imprecision using control samples, variation between measurements on parallel instruments, and estimation of bias with pooled patient specimens. Each obtained CVA was compared with previously developed CAAPS. The calculated CVA was 1.4% for B-HbA1c (CAAPS 1.9% for single diagnostic testing, CAAPS 2.0% for monitoring after duplicate tests; IFCC units), 10.9% for U-Alb (CAAPS 44.9%), 1.2% for P-Na (CAAPS 0.6%, after triplicate testing 1.5%), 8.2% for P-AmylP (CAAPS 22.9%). The CVA was 4.9% for P-LDL-C (CAAPS for cardiovascular risk stratification 4.9% after four replicates), and 4.2% for P-Crea (CAAPS 8.0%). Three of the six measurands fulfilled the estimated clinical need. Results from P-Na measurements indicate a general need for improving the P-Na assays for emergency patients. It is necessary to consider CVI when creating diagnostic targets for laboratory tests, as emphasised by the CAAPS estimates of B-HbA1c and P-LDL-C. [ABSTRACT FROM AUTHOR]

This article presents an overview of an alternative approach to the systematization and evolution of biological organisms on the basis of the fractal-cluster theory. It presents the foundations of the fractal-cluster theory for the self-organizing systems of the organism class. Static and dynamic efficiency criteria based on the fractal-cluster relations and the analytical apparatus of nonequilibrium thermodynamics are presented. We introduce a highly sensitive static criterion, D, which determines the deviation in the value of the clusters and subclusters of the fractal-cluster system structures from their reference values. Other static criteria are the fractal-cluster entropy H and the free energy F of an organism. The dynamic criterion is based on Prigogine's theorem and is determined by the second differential of the temporal trend of the fractal-cluster entropy H. By using simulations of the cluster variations for biological organisms in the (H, D, F)-space, the criteria for the fractal-cluster stochastics as well as for energy and evolution laws are obtained. The relationship between the traditional and fractal-cluster approaches for identifying an organism is discussed. [ABSTRACT FROM AUTHOR]

This review article highlights the potential role of KMT2D mutations in developing neurodevelopmental disorders, specifically Kabuki syndrome and schizophrenia. Neurodevelopmental disorders are complex conditions with a multifactorial etiology, but genetic mutations have been shown to play a crucial role in their pathogenesis. Recent studies suggest that KMT2D mutations may contribute to the development of these disorders by interfering with enhancer function and histone monomethylation, which are essential epigenetic mechanisms involved in brain development and function. The review article explores the hypothesis that KMT2D mutations may be a cause or a risk factor for Kabuki syndrome and schizophrenia. The article discusses potential areas of interest, such as the characterization of KMT2D mutations in patient populations and the investigation of their functional impact on gene expression and brain development. Additionally, the article proposes research methods to investigate further the relationship between KMT2D mutations and these disorders, including animal models and the use of cutting-edge technologies such as CRISPR/Cas9. Identifying KMT2D mutations in both Kabuki syndrome and schizophrenia may provide a new avenue for understanding the underlying mechanisms of these disorders and developing new treatments. The potential impact of this research is significant, as it may lead to the development of targeted therapies for individuals with Kabuki syndrome and schizophrenia who harbor KMT2D mutations. Additionally, identifying KMT2D mutations as a risk factor for these disorders may facilitate early detection and intervention, improving outcomes and quality of life for affected individuals and their families. In summary, this review article provides valuable insights into the potential role of KMT2D mutations in the pathogenesis of Kabuki syndrome and schizophrenia. It highlights the importance of further research in this area. [ABSTRACT FROM AUTHOR]

Simple Summary: This is the first report of biological variation data in guinea pigs for biochemical analytes (measurands) routinely measured during health screening. Information on biological variation provides an insight into whether the observed value for the biochemical analyte is significant or not for that individual. This information is also used to determine whether population-based reference intervals are appropriate to aid in interpreting blood biochemistry results. Biological variation is defined as the within-subject and between-subject random fluctuation around a homeostatic point. In this study, we have calculated the index of individuality, which helps to understand whether subject-based or population-based reference intervals are more appropriate, in order to better identify significant changes in the same subject over time (e.g., during the follow-up period). Our results show that population-based reference intervals should be used on their own only for creatinine and potassium. Individual reference intervals should be used only for glucose. All other markers will require an interpretation that considers both subject-based and population-based reference intervals. It is important to note that most of the biochemical results in the healthy guinea pigs enrolled in our study had biochemical results outside the published reference intervals; thus, information on biological variation helps clinicians and researchers with the interpretation of biochemical profiles. Biological variation (BV) describes the physiological random fluctuation around a homeostatic set point, which is a characteristic of all blood measurands (analytes). That variation may impact the clinical relevance of the changes that are observed in the serial results for an individual. Biological variation is represented mathematically by the coefficient of variation (CV) and occurs within each individual (CVI) and between individuals in a population (CVG). Biological variation data can be used to assess whether population-based reference or subject-based reference intervals should be used for the interpretation of laboratory results through the calculation of the index of individuality (IoI). This study aimed to determine the biological variations, calculate the IoI and reference change values (RCV) of clinical chemistry analytes in an outbred strain colony of Hartley guinea pigs (GPs), and set the quality specifications for clinical chemistry analytes. Blood was collected from 16 healthy adult laboratory colony GPs via jugular venipuncture at weekly intervals over six weeks. All the samples were frozen and analyzed in a single run. Analytical, CVI, and CVG biological variations, together with the IoI and RCV, were calculated for each measurand. Based on the estimated BV, the calculated IoI was low for glucose, so individual reference intervals (RCV) should be used. The majority of the measurands should be interpreted using both population-based and subject-based reference intervals as the IoIs were intermediate. [ABSTRACT FROM AUTHOR]

The Cancer Genome Atlas (TCGA) has classified papillary thyroid carcinoma (PTC) into indolent RAS-like and aggressive BRAF-like based on its distinct driver gene mutations. This retrospective study aimed to assess clinicopathology and pERK1/2 expression variations between BRAF-like and RAS-like PTCs and establish predictive models for BRAFV600E and RAS-mutated PTCs. A total of 222 PTCs underwent immunohistochemistry staining to assess pERK1/2 expression and Sanger sequencing to analyze the BRAF and RAS genes. Multivariate logistic regression was employed to develop prediction models. Independent predictors of the BRAFV600E mutation include a nuclear score of 3, the absence of capsules, an aggressive histology subtype, and pERK1/2 levels exceeding 10% (X2 = 0.128, p > 0.05, AUC = 0.734, p < 0.001). The RAS mutation predictive model includes follicular histology subtype and pERK1/2 expression > 10% (X2 = 0.174, p > 0.05, AUC = 0.8, p < 0.001). We propose using the prediction model concurrently with four potential combination group outcomes. PTC cases included in a combination of the low-BRAFV600E-scoring group and high-RAS-scoring group are categorized as RAS-like (adjOR = 4.857, p = 0.01, 95% CI = 1.470–16.049). PTCs included in a combination of the high-BRAFV600E-scoring group and low-RAS-scoring group are categorized as BRAF-like PTCs (adjOR = 3.091, p = 0.001, 95% CI = 1.594–5.995). The different prediction models indicate variations in biological behavior between BRAF-like and RAS-like PTCs. [ABSTRACT FROM AUTHOR]

Background: Diabetes is a serious metabolic disorder and many medicinal plants are used in traditional medicine to manage it. This study aimed to evaluate the therapeutic effects of Vernonia calvoana (V. calvoana) extract fractions on streptozotocin-induced diabetic rat models. In this study, we first investigated the binding affinity of ligands from extracts of V. calvoana crystal structure proteins using a molecular docking approach. Furthermore, the in silico predictions were validated by in vitro and in vivo biochemical evaluations to ascertain the efficacy of these extract fractions. The in vitro antioxidant activity of the fractions was evaluated using DPPH, FRAP, SOD, and LPx scavenging. For biological activity, extract fractions of V. calvoana and metformin (400 mg and 500 mg/kg body weight, respectively) were administered to diabetic rats for 21 days after induction and confirmation of diabetes. Results: The radical scavenger activities of the fractions showed a good dose-dependent reaction activity. A significant reduction in hyperglycemia, hyperlipidemia, nephrotoxicity, and hepatotoxicity was observed in all experimental treated groups. Improved hematological and histopathological changes were also observed. Conclusion: The In silico analyses revealed that all the compounds from extract fractions of V. calvoana have varying binding affinity for PFK and lipoprotein lipase, with some showing higher affinity than the standard drug, further validating the biological activity of the plant. The results of this study indicated that V. calvoana extracts might have potential value in treating complications arising from diabetes mellitus. [ABSTRACT FROM AUTHOR]

Pinellia ternata (Thunb.) Breit. (Araceae), a significant medicinal plant, has been used to treat various diseases for centuries. Terahertz radiation (THZ) is located between microwaves and infrared rays on the electromagnetic spectrum. THZ possesses low single-photon energy and a spectral fingerprint, but its effects on plant growth have not yet been investigated. The study's primary objective was to examine the transcriptome and metabolome databases of the SY line to provide a new perspective for identifying genes associated with resistance and growth promotion and comprehending the underlying molecular mechanism. Variations in the biological characteristics of P. ternata grown under control and experimental conditions were analyzed to determine the effect of THZ. Compared with the control group, phenotypic variables such as leaf length, petiole length, number of leaves, leaf petiole diameter, and proliferation coefficient exhibited significant differences. P. ternata response to THZ was analyzed regarding the effects of various coercions on root exudation. The experimental group contained considerably more sugar alcohol than the control group. The transcriptome analysis revealed 1,695 differentially expressed genes (DEGs), including 509 upregulated and 1,186 downregulated genes. In the KEGG-enriched plant hormone signaling pathway, there were 19 differentially expressed genes, 13 of which were downregulated and six of which were upregulated. In the metabolomic analysis, approximately 416 metabolites were uncovered. There were 112 DEMs that were downregulated, whereas 148 were upregulated. The P. ternata leaves displayed significant differences in phytohormone metabolites, specifically in brassinolide (BR) and abscisic acid (ABA). The rise in BR triggers alterations in internal plant hormones, resulting in faster growth and development of P. ternata. Our findings demonstrated a link between THZ and several metabolic pathway processes, which will enhance our understanding of P. ternata mechanisms. [ABSTRACT FROM AUTHOR]

Climate change and climate variability are affecting marine mammal species and these impacts are projected to continue in the coming decades. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species using currently available information. We conducted a trait-based climate vulnerability assessment using expert elicitation for 108 marine mammal stocks and stock groups in the western North Atlantic, Gulf of Mexico, and Caribbean Sea. Our approach combined the exposure (projected change in environmental conditions) and sensitivity (ability to tolerate and adapt to changing conditions) of marine mammal stocks to estimate vulnerability to climate change, and categorize stocks with a vulnerability index. The climate vulnerability score was very high for 44% (n = 47) of these stocks, high for 29% (n = 31), moderate for 20% (n = 22), and low for 7% (n = 8). The majority of stocks (n = 78; 72%) scored very high exposure, whereas 24% (n = 26) scored high, and 4% (n = 4) scored moderate. The sensitivity score was very high for 33% (n = 36) of these stocks, high for 18% (n = 19), moderate for 34% (n = 37), and low for 15% (n = 16). Vulnerability results were summarized for stocks in five taxonomic groups: pinnipeds (n = 4; 25% high, 75% moderate), mysticetes (n = 7; 29% very high, 57% high, 14% moderate), ziphiids (n = 8; 13% very high, 50% high, 38% moderate), delphinids (n = 84; 52% very high, 23% high, 15% moderate, 10% low), and other odontocetes (n = 5; 60% high, 40% moderate). Factors including temperature, ocean pH, and dissolved oxygen were the primary drivers of high climate exposure, with effects mediated through prey and habitat parameters. We quantified sources of uncertainty by bootstrapping vulnerability scores, conducting leave-one-out analyses of individual attributes and individual scorers, and through scoring data quality for each attribute. These results provide information for researchers, managers, and the public on marine mammal responses to climate change to enhance the development of more effective marine mammal management, restoration, and conservation activities that address current and future environmental variation and biological responses due to climate change. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive analysis of spiking neural networks (SNNs) and their mathematical models for simulating the behavior of neurons through the generation of spikes. The study explores various models, including LIF and NLIF, for constructing SNNs and investigates their potential applications in different domains. However, implementation poses several challenges, including identifying the most appropriate model for classification tasks that demand high accuracy and low-performance loss. To address this issue, this research study compares the performance, behavior, and spike generation of multiple SNN models using consistent inputs and neurons. The findings of the study provide valuable insights into the benefits and challenges of SNNs and their models, emphasizing the significance of comparing multiple models to identify the most effective one. Moreover, the study quantifies the number of spiking operations required by each model to process the same inputs and produce equivalent outputs, enabling a thorough assessment of computational efficiency. The findings provide valuable insights into the benefits and limitations of SNNs and their models. The research underscores the significance of comparing different models to make informed decisions in practical applications. Additionally, the results reveal essential variations in biological plausibility and computational efficiency among the models, further emphasizing the importance of selecting themost suitablemodel for a given task. Overall, this study contributes to a deeper understanding of SNNs and offers practical guidelines for using their potential in real-world scenarios. [ABSTRACT FROM AUTHOR]

State-space assessment models (SSMs) have garnered attention recently because of their ability to estimate time variation in biological and fisheries processes such as recruitment, natural mortality, catchability, and selectivity. However, current SSMs cannot model time-varying growth internally nor accept length data, limiting their use. Here, we expand the Woods Hole Assessment Model to incorporate new approaches to modelling changes in growth using a combination of parametric and nonparametric approaches while fitting to length and weight data. We present these new features and apply them to data for three important Alaskan stocks with distinct data and model needs. We conduct a "self-test" simulation experiment to ensure the unbiasedness and statistical efficiency of model estimates and predictions. This research presents the first SSM that can be applied when length data are a key source of information, variation in growth is an essential part of the dynamics of the assessed stock, or when linking climate variables to growth in hindcasts or forecasts is relevant. Consequently, the state-space approach and growth estimation can be applied to more fish stocks worldwide, facilitating real-world applications and implementation of simulation experiments for performance evaluation of SSMs for the many stocks whose assessments rely on length data. [ABSTRACT FROM AUTHOR]

Objective: To identify suitable reference genes for gene expression studies in rat dorsal root ganglia (DRG) neurons. Methods: The raw cycle threshold (Ct) values of 12 selected reference genes were obtained via quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) in neurons at different developmental stages or under different treatments. Two strategies were employed to screen the most stable reference genes: the genes were ranked according to the coefficient of biological variation and further validated using geNorm and NormFinder programs. The stable and unstable reference genes were subsequently used as internal controls to assess their effects on target gene expression. Results: All reference genes showed varying degrees of fluctuation in Ct values during the growth process of neurons or after different treatments. 18S ribosomal RNA (Rn18s) and ß-actin (Actb) exhibited the most significant changes, while ubiquitin C (Ubc), hypoxanthine phosphoribosyl transferase (Hprt), and mitochondrial ribosomal protein L10 (Mrpl10) showed relatively minor changes. The most stable and unstable genes obtained by different evaluation methods varied slightly. Overall, Actb was found to be the most unstable reference gene, while Hprt was the relatively most stable reference gene. The use of unstable reference genes Actb and ankyrin repeat domain 27 (Ankrd27) as internal controls led to high variability within the control group, ultimately affecting the determination of target gene expression. In contrast, the stable reference gene Hprt had small inter-assay variation and high stability. Conclusions: Our observations indicate that Hprt is a proper endogenous reference gene for qRT-PCR analysis in rat DRG neurons and thus provides a critical molecular basis for the genetic characterization in neurological disorders. [ABSTRACT FROM AUTHOR]

Background: Despite being the most performed laboratory endocrine investigation, the optimum use of thyroid tests (thyrotropin [TSH] and thyroid hormone [TH] measurement) is open to question and the interpretation of the results from these tests can be ambiguous. The American Thyroid Association (ATA) with its expertise support the endeavor of the U.S. Centers for Disease Control (CDC) and the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) to improve and maintain standardization and harmonization of thyroid testing. ATA mandated an international interdisciplinary working group panel to survey the status of thyroid testing by reviewing the recent literature to revise or update the criteria as needed in mutual agreement and to inform clinical care. Summary: This review represents the conclusions on the clinical use of current routine TSH and TH (thyroxine [T4] and triiodothyronine [T3]) assays, taking into account geographic differences in disease prevalence and clinical and laboratory practice among writing members. The interaction between physiological, pathophysiological, and pharmacological factors and thyroid assays can affect their measurements and confound result interpretation. These factors need to be considered in the clinical context of the patient for appropriate test ordering and result interpretation. Despite significant advances in laboratory methods over the past 50 years, routine thyroid assays remain susceptible to idiosyncratic analytical interference that may produce spurious results. Improved standardization needs to be demonstrated through ongoing international efforts before results from different assays can be considered equivalent. Emerging technology (e.g., mass spectrometry) shows promise for improved analytical performance, but more evidence of its clinical utility and improved throughput is required before it can be considered for routine use. Close clinical–laboratory collaboration is encouraged to overcome and avoid the pitfalls in thyroid testing as well as resolve clinically discrepant results. The evidence base supporting the conclusions of this review is summarized in four detailed online technical supplements. Conclusions: Over the past five decades, testing for TSH, T4, and T3 has evolved from manual radioisotopic immunoassays to nonisotopic multiplexed immunometric assays using highly automated equipment. Despite these technical advances, physicians and laboratorians performing these analyses must understand limitations of these methods to properly order tests and interpret results. [ABSTRACT FROM AUTHOR]

Background and Objectives: Room temperature‐stored platelets (RTPs) maximize platelet viability but limit shelf life. The aims of this study were to investigate the impact of donor variability on cold‐stored platelets (CSPs) and RTP, to determine whether RTP quality markers are appropriate for CSP. Materials and Methods: Double platelet donations (n = 10) were collected from consented regular male donors stored in 100% plasma. A full blood count, donor age, weight, height and body mass index (BMI) were collected at the time of donation. Platelet donations were split equally into two bags, and assigned to non‐agitated CSP or agitated RTP. The quality and function of platelets were assessed throughout the standard 7 days of storage and at expiry (day 8). Non‐parametric statistical analyses were used to analyse results given the small sample size. Results: As expected, there were significant differences between CSP and RTP throughout storage including a reduction in CSP concentration as well as a loss of swirling. Furthermore, a significant increase in CSP exhibiting activation and apoptotic markers was observed. Platelet concentrations were further impacted by donor BMI, and donors with the highest BMI (>29) had the lowest platelet concentration and activation response at the end of CSP storage. Conclusion: Platelet quality and functionality play a vital role in transfusion outcomes; however, blood components are inherently variable. This study demonstrated, for the first time, the specific impact of donor BMI on CSP quality and function and highlights the requirement for novel quality markers for assessing CSPs. [ABSTRACT FROM AUTHOR]

Lactate is produced in the human body during physical activity and elimination takes time with a half-life of approximately 18 min. We, therefore, investigated the potential impact of resting time (RT) duration on lactate concentration in our outpatient venipuncture clinic for all lactate requests during a 4½-year period. All samples drawn for venous lactate analysis during a 4½-year period in our hospital outpatient venipuncture clinics were included in this study. RT was reported electronically at each visit. Results from a total of 831 samples were obtained for further analysis. We found varying lactate concentrations across resting time <15min (median 1.6 mmol/L, IQR[1.2–2.1] mmol/L), between <15 min and >30 min (median 1.4 mmol/L, IQR[1.0–1.9] mmol/L) and for >30 min (median 1.3 mmol/L, IQR[1.0–1.7] mmol/L). There was a significant difference between <15 min versus 15–30 min (p = 0.015), which gives a 17.7% higher lactate from 15–30 min to <15 min. There was a significant 28.3% increase in mean lactate concentration from >30min to <15min (p < 0.0001) when corrected for age. We found that lactate concentration was dependent on RT in the outpatient clinic. The difference was clinically significant. Based on the results of this study, we, therefore, conclude that a 15 min waiting time before venipuncture for lactate sampling in an outpatient clinic is of clinical importance. [ABSTRACT FROM AUTHOR]

Applying genetic practice to current medicine has become more common and necessary in the prognosis, diagnosis and outcome of a myriad of diseases and disorders. Despite the general awareness of its importance, genetic knowledge still lacks direct application in daily orthodontic practice. The aim was to identify multiple genetic associations with orofacial phenotypes, highlight the importance of genetic influence in orthodontics, and describe challenges and gaps in integrating genetic knowledge in clinical practice. In the process, the influence of environmental factors on orofacial development and treatment is underscored, hence the role of epigenetics in regulating gene expression and tissue remodeling. [ABSTRACT FROM AUTHOR]

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Introduction: People with a low or high haemoglobin glycation index (HGI) have lower or higher HbA1c than other people with the same FPG. This study compared the prevalence of prediabetes based on FPG, 2hOGTT and HbA1c in people with low, moderate or high HGI. Methods: Prediabetes was diagnosed based on ADA cutpoints in 10,488 NHANES participants without self‐reported diabetes. HGI was calculated as the difference between a participant's observed HbA1c and a predicted HbA1c where predicted HbA1c = 0.024 FPG + 3.1. Participants were divided into low (HGI < −0.15%), moderate (HGI −0.15% to +0.15%) and high (HGI > +0.15%) HGI subgroups. Results: The prevalence of prediabetes was 42.4% based on FPG, 27.2% based on HbA1c and 17.2% based on 2hOGTT. FPG and HbA1c thus overdiagnosed prediabetes by 25.2% and 10.0%, respectively, compared to the OGTT gold standard. Prevalence was (1) similar in low, moderate and high HGI participants based on 2hOGTT, (2) highest in low HGI participants based on FPG, and (3) highest in high HGI participants based on HbA1c. Among participants with mismatched FPG and HbA1c, OGTT was normal in (1) 79.5% of participants with normal FPG but prediabetic HbA1c (mean HGI = +0.53%), and (2) 75.2% of participants with normal HbA1c but prediabetic FPG (mean HGI = −0.30%). Conclusions: FPG overdiagnosed prediabetes in people with low HGI. HbA1c overdiagnosed prediabetes in people with high HGI. Clinical use of HGI could improve prediabetes diagnosis and help health care providers avoid inappropriate or delayed treatment of people with extremes of HGI. [ABSTRACT FROM AUTHOR]

Introduction: Although fetal biometry measurements aid in an accurate estimation of GA in the early second trimester, the biological variations of size lead to these parameters' accuracy to vary as the age of the fetus advanced, making it challenging to date a fetus accurately in the late second or third trimester. Therefore, this study conducted to assess correlation of foetal kidney length with gestational age in third trimester of pregnancy. Methodology: This was a cross-sectional observational study conducted among 120 pregnant women in the 3rd trimester. For obtaining foetal kidney length, longitudinal section was taken in sagittal plane using ultrasound. Results: Out of total 120 cases, the left kidney length (LKL) is slightly higher than the right kidney length (RKL). Mean kidney lengths (MKL) rose consistently with gestational age, from 27.18 ± 2.2O mm at 28 weeks to -8.O ± l.8O mm at -9 weeks. RKL, LKL and MKL were positively correlated with gestational age. R squared (R2) value was 0.769 which is a good fit and indicates that this regression model explains 76.9% changes in GA with MKL. Conclusion: Foetal kidney length is a reliable measure of gestational age. Measuring the foetal mean kidney length using ultrasound is a simple technique to determine the gestational age. In third trimester pregnancy with uncertain LMP, the length of the foetal kidneys may be extremely helpful in determining gestational age. [ABSTRACT FROM AUTHOR]

Background: Cats commonly develop thyroid disease but little is known about the long‐term biological variability of serum thyroid hormone and thyrotropin (thyroid‐stimulating hormone; TSH) concentrations. Objectives: We aimed to determine the long‐term biological variation of thyroid hormones and TSH in clinically healthy cats. Methods: A prospective, observational study was carried out. Serum samples for analysis of total thyroxine (T4, by radioimmunoassay [RIA] and homogenous enzyme immunoassay [EIA]), triiodothyronine (T3), free T4 (by dialysis), and TSH were obtained every 8 weeks for 1 year from 15 healthy cats, then frozen until single‐batch analysis. Coefficients of variation (CV) within individual cats (CVI) and among individual cats (CVG), as well as the variation between duplicates (ie, analytical variation [CVA]) were determined with restricted maximum likelihood estimation. The indices of individuality (IoI) and reference change values (RCVs) for each hormone were calculated. Results: Some thyroid hormones showed similar (total T4 by EIA) or greater (TSH) interindividual relative to intraindividual variation resulting in intermediate to high IoI, consistent with previous studies evaluating the biological variation of these hormones weekly for 5–6 weeks. By contrast, total T4 (by RIA) and free T4 had a low IoI. Total T3 had a high ratio of CVA to CVI; therefore, interindividual variation could not be distinguished from analytical variation. No seasonal variability in the hormones could be demonstrated. Conclusions: Clinicians might improve the diagnosis of feline thyroid disease by establishing baseline concentrations for analytes with intermediate‐high IoI (total T4, TSH) for individual cats and applying RCVs to subsequent measurements. [ABSTRACT FROM AUTHOR]

Background: Biological variation (BV) of urinary (U) biochemical analytes has not been described in absolute terms, let alone as a ratio of the U‐creatinine or fractional excretion in healthy dogs. These analytes are potential diagnostic tools for different types of kidney damage and electrolyte disorders in dogs. Objectives: We aimed to investigate the BV of specific gravity, osmolality, creatinine, urea, protein, glucose, chloride, sodium, potassium, calcium, and phosphate in urine from healthy pet dogs. Methods: Blood and urine samples from 13 dogs were collected once weekly for 8 weeks. Samples were analyzed in duplicate and in randomized order. For each sample, U‐analyte and serum concentrations were measured, and U‐analyte/U‐creatinine and fractional excretion (FE) were calculated. Components of variance, estimated by restricted maximum likelihood, were used to determine within‐subject variation (CVI), between‐subject variation (CVG), and analytical variation (CVA). Index of individuality (II) and reference change values were calculated. Results: CVI for all urine analytes varied between 12.6% and 35.9%, except for U‐sodium, U‐sodium/U‐Cr, and FE‐sodium, which had higher CVIs (59.5%‐60.7%). For U‐protein, U‐sodium, U‐potassium, U‐sodium/U‐creatinine, FE‐urea, FE‐glucose, FE‐sodium, FE‐potassium, and FE‐phosphate II were low, indicating that population‐based RIs were appropriate. The remaining analytes had an intermediate II, suggesting that population‐based RIs should be used with caution. Conclusion: This study presents information on the biological variation of urinary and serum biochemical analytes from healthy dogs. These data are important for an appropriate interpretation of laboratory results. [ABSTRACT FROM AUTHOR]

Background: To ensure valid results of big data research in the medical field, the input laboratory results need to be of high quality. We aimed to establish a strategy for evaluating the quality of laboratory results suitable for big data research. Methods: We used Korean Association of External Quality Assessment Service (KEQAS) data to retrospectively review multicenter data. Seven measurands were analyzed using commutable materials: HbA1c, creatinine (Cr), total cholesterol (TC), triglyceride (TG), alpha-fetoprotein (AFP), prostate-specific antigen (PSA), and cardiac troponin I (cTnI). These were classified into three groups based on their standardization or harmonization status. HbA1c, Cr, TC, TG, and AFP were analyzed with respect to peer group values. PSA and cTnI were analyzed in separate peer groups according to the calibrator type and manufacturer, respectively. The acceptance rate and absolute percentage bias at the medical decision level were calculated based on biological variation criteria. Results: The acceptance rate (22.5%–100%) varied greatly among the test items, and the mean percentage biases were 0.6%–5.6%, 1.0%–9.6%, and 1.6%–11.3% for all items that satisfied optimum, desirable, and minimum criteria, respectively. Conclusions: The acceptance rate of participants and their external quality assessment (EQA) results exhibited statistically significant differences according to the quality grade for each criterion. Even when they passed the EQA standards, the test results did not guarantee the quality requirements for big data. We suggest that the KEQAS classification can serve as a guide for building big data. [ABSTRACT FROM AUTHOR]

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.

Determining the proportion of a population at risk of inadequate or excessive nutrient intake is a crucial step in planning and managing nutrition intervention programs. Multiple days of 24-h dietary intake data per subject allow for adjustment of modeled usual nutrient intake distributions for the proportion of total variance in intake attributable to within-individual variation (WIV:total). When only single-day dietary data are available, an external adjustment factor can be used; however, WIV:total may vary by population, and use of incorrect WIV:total ratios may influence the accuracy of prevalence estimates and subsequent program impacts. WIV:total values were compiled from publications and from reanalyses of existing datasets to describe variation in WIV:total across populations and settings. The potential impact of variation in external WIV:total on estimates of prevalence of inadequacy was assessed through simulation analyses using the National Cancer Institute 1-d method. WIV:total values were extracted from 40 publications from 24 countries, and additional values were calculated from 15 datasets from 12 nations. Wide variation in WIV:total (from 0.02 to 1.00) was observed in publications and reanalyses. Few patterns by population characteristics were apparent, but WIV:total varied by age in children (< vs. >1 y) and between rural and urban settings. Simulation analyses indicated that estimates of the prevalence of inadequate intake are sensitive to the selected ratio in some cases. Selection of an external WIV:total estimate should consider comparability between the reference and primary studies with regard to population characteristics, study design, and statistical methods. Given wide variation in observed ratios with few discernible patterns, the collection of ≥2 days of intake data in at least a representative subsample in population dietary studies is strongly encouraged. In the case of single-day dietary studies, sensitivity analyses are recommended to determine the robustness of prevalence estimates to changes in the variance ratio.

This article is a reply to a review of a previous manuscript regarding the interpretation of the dilute Russell viper venom time screen to confirm ratio (SCR) and "normalized" SCR (nSCR) for diagnosing lupus anticoagulant (LA). The authors assert that reference range studies to establish the upper limit of normal (ULN) for SCR are not necessary when reagent lots change, as the observed variation is small and does not consider the biological variation in ULN. They also argue that a difference of 0.04 in the ULN is too small to warrant a change in interpretation. The authors conclude that SCR normalization was of no clinical benefit in their patient population and that lot-to-lot variation in the SCR cutoff value is unlikely to be detected. [Extracted from the article]

Mixed-effects models are becoming common in psychological science. Although they have many desirable features, there is still untapped potential. It is customary to view homogeneous variance as an assumption to satisfy. We argue to move beyond that perspective, and to view modeling within-person variance as an opportunity to gain a richer understanding of psychological processes. The technique to do so is based on the mixed-effects location scale model that can simultaneously estimate mixed-effects submodels to both the mean (location) and within-person variance (scale). We develop a framework that goes beyond assessing the submodels in isolation of one another and introduce a novel Bayesian hypothesis test for mean-variance correlations in the distribution of random effects. We first present a motivating example, which makes clear how the model can characterize mean-variance relations. We then apply the method to reaction times (RTs) gathered from 2 cognitive inhibition tasks. We find there are more individual differences in the within-person variance than the mean structure, as well as a complex web of structural mean-variance relations. This stands in contrast to the dominant view of within-person variance (i.e., "noise"). The results also point toward paradoxical within-person, as opposed to between-person, effects: several people had slower and less variable incongruent responses. This contradicts the typical pattern, wherein larger means tend to be associated with more variability. We conclude with future directions, spanning from methodological to theoretical inquires, that can be answered with the presented methodology. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Conservation efforts have led to the recovery of the endangered mountain gorilla populations. Due to their limited potential for spatial expansion, population densities increased, which may alter the epidemiology of infectious diseases. Recently, clinical gastrointestinal illnesses linked to helminth infections have been recorded in both gorilla populations. To understand drivers and patterns of helminth infections we quantified strongylid and tapeworm infections across both Virunga Massif and Bwindi populations using fecal egg counts. We assessed the impact of age, sex, group size, season and spatial differences used as a proxy, which reflects observed variation in the occurrence of gastrointestinal problems, vegetation types, gorilla subpopulation growth and associated social structure on helminth infections. We revealed striking geographic differences in strongylid infections with higher egg counts mostly in areas with high occurrences of gastrointestinal disease. Increased helminth egg counts were also associated with decreasing group size in some areas. Observed spatial differences may reflect mutual effects of variations in subpopulation growth rates, gorilla social structure, and vegetation associated with altitude across mountain gorilla habitat. Helminth infection intensities in Virunga gorillas were lowest in the youngest and the oldest animals. Elucidating parasite infection patterns of endangered species with low genetic diversity is crucial for their conservation management.

BackgroundLittle is known about the concordance of atopy with asthma COPD overlap. Among individuals with COPD, a better understanding of the phenotypes characterized by asthma overlap and atopy is needed to better target therapies.Research questionWhat is the overlap between atopy and asthma status among individuals with COPD, and how are categories defined by the presence of atopy and asthma status associated with clinical and radiologic phenotypes and outcomes in the Genetic Epidemiology of COPD Study (COPDGene) and Subpopulation and Intermediate Outcome Measures in COPD Study (SPIROMICS)?Study design and methodsFour hundred three individuals with COPD from SPIROMICS and 696 individuals from COPDGene with data about specific IgEs to 10 common allergens and mixes (simultaneous assessment of combination of allergens in similar category) were included. Comparison groups were defined by atopic and asthma status (neither, atopy alone, atopic asthma, nonatopic asthma, with atopy defined as any positive specific IgE (≥0.35 KU/L) to any of the 10 allergens or mixes and asthma defined as self-report of doctor-diagnosed current asthma). Multivariable regression analyses (linear, logistic, and zero inflated negative binomial where appropriate) adjusted for age, sex, race, lung function, smoking status, pack-years smoked, and use of inhaled corticosteroids were used to determine characteristics of groups and relationship with outcomes (exacerbations, clinical outcomes, CT metrics) separately in COPDGene and SPIROMICS, and then adjusted results were combined using meta-analysis.ResultsThe prevalence of atopy was 35% and 36% in COPD subjects from SPIROMICS and COPDGene, respectively, and less than 50% overlap was seen between atopic status with asthma in both cohorts. In meta-analysis, individuals with nonatopic asthma had the most impaired symptom scores (effect size for St. George's Respiratory Questionnaire total score, 4.2; 95% CI, 0.4-7.9; effect size for COPD Assessment Test score, 2.8; 95% CI, 0.089-5.4), highest risk for exacerbations (incidence rate ratio, 1.41; 95% CI, 1.05-1.88) compared with the group without atopy or asthma. Those with atopy and atopic asthma were not at increased risk for adverse outcomes.InterpretationAsthma and atopy had incomplete overlap among former and current smokers with COPD in COPDGene and SPIROMICS. Nonatopic asthma was associated with adverse outcomes and exacerbation risk in COPD, whereas groups having atopy alone and atopic asthma had less risk.

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2020. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Background: This study was a prospective cadaver-derived skeletal study looking at the skeletal remains of a modern human population. The complete arcuate foramen (AF) is an anatomical variant of the atlas vertebra with a complete osseous bridge over the groove for the vertebral artery (VA). Awareness of the anatomic variations of the atlas related to the course of the VA, such as the AF, is important because the course and variations of VAs are critical to spine surgeons. We aimed to detect the prevalence of AF in sub-Saharan African subjects. Materials and methods: We analyzed the prevalence of AF in 120 atlas vertebrae from the Raymond A Dart Collection of the University of the Witwatersrand, Johannesburg, South Africa. Results: Twelve (13.3 %) atlases of the 90 that were from sub-Saharan African ancestry subjects presented at least one AF: the presence of AF frequency was 6.7 % in the Sotho sample, 23.3 % in the Xhosa sample and 10.0 % in the Zulu sample. However, no significant difference was found in their distribution regarding the presence of AF ratios (p = 0.221). The AF frequency was 3.3 % in the South African Caucasian subjects. No significant differences were found in their distribution regarding the presence of AF ratios between the Caucasian and the Sotho (p = 1.000), Zulu (p = 0.612) and Xhosa (p = 0.052) samples. Conclusions: Our research shows a tendency for a higher AF presence in Xhosa subjects. It has increased the knowledge of the AF prevalence in sub-Saharan Africa, drastically increasing the population.