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The present study aimed at assessing the mid (MPH) and better (BPH) parents heterosis, potence ratio (PR) and genetic parameters for yield, its components and fiber traits in eighteen F1 hybrids developed by crossing between six lines and three testers using line × tester mating design.Pearson correlation coefficient and principal component analysis (PCA) were used for a better understanding of the relationship during this study. The lines, testers and their F1 hybrids were evaluated in a randomized complete block design (RCBD) with three replications at Sakha Agriculture Research Station, Kafr El-Sheikh Governorate, Egypt, during the 2020 cropping season. The variances due to the sources of variation in line x tester analysis exhibited significant differences for most measured traits.The proportional contribution of line × tester was higher than the individual contribution of lines and testers for most studied traits. The lines G.90x Aus.12 and Uzbekistan as well as the tester G.97 showed superior cotton yield and most studied traits based on mean performance compared to the other parents. The hybrid combinations TNB x G. 94, (G.90x Aus.12) x G.86 and G.96 x G.94 were identified as excellent based on mean performance, MPH, BPH and PCA analysis for cotton yield and most studied traits. Potence ratio exhibited that the hybrid combinations have positive or negative nature for studied traits.Genetic parameters indicated that non-additive gene action effects had a more important role compared to the additive in controlling all the studied traits, except the number of seeds/boll trait. Significant correlation coefficients were found between all possible pairs of mean performances, MPH, BPH (positive) and PR (negative) parameters for most investigated traits. PCA can be used as a suitable method for studying the studied traits and to determine the best hybrids across line x tester analysis. Finally, and based on the results of statistical methods used in this study, the parents and hybrids above are promising enhancement and improvement of cotton productivity and its fiber quality through use in cotton breeding programs in Egypt. [ABSTRACT FROM AUTHOR]

Additive genetic variance in fitness is a prerequisite for adaptive evolution, as a trait must be genetically correlated with fitness to evolve. Despite its relevance, additive genetic variance in fitness has not often been estimated in nature. Here, we investigate additive genetic variance in lifetime and annual fitness components in common terns (Sterna hirundo). Using 28 years of data comprising approximately 6000 pedigreed individuals, we find that additive genetic variances in the zero‐inflated and Poisson components of lifetime fitness were effectively zero but estimated with high uncertainty. Similarly, additive genetic variances in adult annual reproductive success and survival did not differ from zero but were again associated with high uncertainty. Simulations suggested that we would be able to detect additive genetic variances as low as 0.05 for the zero‐inflated component of fitness but not for the Poisson component, for which adequate statistical power would require approximately two more decades (four tern generations) of data collection. As such, our study suggests heritable variance in common tern fitness to be rather low if not zero, shows how studying the quantitative genetics of fitness in natural populations remains challenging, and highlights the importance of maintaining long‐term individual‐based studies of natural populations. [ABSTRACT FROM AUTHOR]

In this paper we provide a probabilistic representation of Lagrange's identity which we use to obtain Papathanasiou-type variance expansions of arbitrary order. Our expansions lead to generalized sequences of weights which depend on an arbitrarily chosen sequence of (non-decreasing) test functions. The expansions hold for univariate target distribution under weak assumptions, in particular they hold for continuous and lattice distributions alike. The weights are studied under different sets of assumptions either on the test functions or on the underlying distributions. Many concrete illustrations for standard probability distributions are provided (including Pearson, Ord, Laplace, Rayleigh, Cauchy, and Levy distributions). [ABSTRACT FROM AUTHOR]

The current study evaluated a bifactor model for the Obsessive-Compulsive Inventory Revised (OCI-R) in two samples, with (n=188) and without (n=408) obsessive-compulsive disorder (OCD). Since the OCI-R has been traditionally conceptualized as a correlated six-factor instrument, our goal was to evaluate the fit of a bifactor model against three competing models (one general factor, six correlated factors and a hierarchical model). Results revealed that the bifactor model presented the best fit and that all OCI-R items were influenced by a general factor and by one of the six dimensions. Model-based reliability estimated via Omega hierarchical for the total score suggested that OCI-R items are multidimensional, with the general obsessive-compulsive (OC) factor accounting for little more than half of the variability in the items of the total score, with the remaining variability accounted for by the specific OC domains and other sources of variance. Measurement invariance of the bifactor model was also supported among those with and without OCD. Implications for better understanding the structure and further use of the OCI-R are discussed. [ABSTRACT FROM AUTHOR]

The investigation advanced the comparative efficiency of Liner Probability Model on paired multivariate data. On the basis of simulation, vector of means having common variance-covariance matrix were taken into account as data sets subjected to analyses. The linear probability model exhibited a more power tool to detect the presence of significant difference among variables compared to the multivariate paired (Hotellings'-T2) t-test. The Linear probability model is 31.33% and 44.67%., more efficient than the usual counterpart containing two and three predictor variables, respectively. It pays further, that under the regression analysis, individual variable is directly identified in relation to its significant contribution to the dependent variable. This observation is tantamount on determining that such vector of mean disparity is not significantly different from zero against the usual hypothesis. This procedure gains added advantage such that a sweeping generalization of whether vector of means are significantly or insignificantly different is avoided. [ABSTRACT FROM AUTHOR]

This paper introduces the ex-ante estimation of the variance risk premium. The novel methodology proposed is applied to forecast variance risk premium in energy markets, capturing the future degree of aversion of investors towards energy variance risks. We analyze the ex-ante variance risk premium of two energy indices, XLE and USO, during the period that spans from 2011 to 2022, and compare them to that of the SPX, the benchmark for the equity market. In the computation of the ex-ante variance risk premium, simple GARCH and Markov-switching GARCH models are exploited to forecast the realized variance, while variance swap rates are retrieved from the volatility indices VXXLE, OVX, and VIX of the three market indices. We find that the ex-ante variance risk premium succeeds to forecast the imminent periods of financial distress empirically detected in the abrupt surges and plunges of the ex-post variance risk premium. In particular, USO shows higher magnitudes of the variance risk premium than XLE and SPX, predicting that investors require on average higher premiums to bear oil variance risks. [ABSTRACT FROM AUTHOR]

Objectives: To develop, validate and evaluate a computerized clinical decision support system (MedReview) that aids medication reviewers with pharmacological decision-making. Methods: This study included three phases; the development phase included computerizing a consolidated medication review algorithm (MedReview), followed by validation and evaluation of MedReview and responding to a web-based survey designed using patient scenarios. Participants had to be 'fully registered' with the Malaysian Pharmacy Board and work full-time at a community pharmacy. Results: MedReview was developed as a web app. It was validated among 100 community pharmacists from May-July 2021 using the Technology Acceptance Model (TAM). There was acceptable content validity and fair inter-rater agreement, and good convergent and discriminant validity. Exploratory factor analysis resulted in five domains to determine the attitude of pharmacists about using MedReview: perceived ease of use, perceived usefulness, intention to use, trust, and personal initiatives and characteristics; the total variance explained by five factors was 76.36%. The survey questionnaire had a high overall reliability value of 0.96. Evaluation of MedReview was based on mean scores of survey items. Of all items included in the survey, the highest mean score (out of 7) was achieved for 'I could use MedReview if it is meaningful/relevant to my daily tasks' (5.78 ± 1.10), followed by 'I could use MedReview if I feel confident that the data returned by MedReview is reliable' (5.77 ± 1.21), and 'I could use MedReview if it protects the privacy of its users' (5.73 ± 1.20). Conclusion: Community pharmacists generally had a positive attitude towards MedReview. They found that MedReview is trustworthy and they had the intention to use it when conducting medication reviews. The adaptation of the TAM in the survey instrument was reliable and internally valid. [ABSTRACT FROM AUTHOR]

Stevia rebaudiana is one of the most important crops belonging to the Asteraceae family. Stevia is cultivated all over the world as it represents a valid natural alternative to artificial sweeteners thanks to its leaves, which produce steviol glycosides that have high sweetening power and reduced caloric value. In this work, the stevia genome sequence was used to isolate and characterise full-length long-terminal repeat retrotransposons (LTR-REs), which account for more than half of the genome. The Gypsy retrotransposons were twice as abundant as the Copia ones. A disproportionate abundance of elements belonging to the Chromovirus/Tekay lineage was observed among the Gypsy elements. Only the SIRE and Angela lineages represented significant portions of the genome among the Copia elements. The dynamics with which LTR-REs colonised the stevia genome were also estimated; all isolated full-length elements turned out to be relatively young, with a proliferation peak around 1–2 million years ago. However, a different analysis conducted by comparing sequences encoding retrotranscriptase showed the occurrence of an older period in which there was a lot of LTR-RE proliferation. Finally, a group of isolated full-length elements belonging to the lineage Angela was used to analyse the genetic variability in 25 accessions of S. rebaudiana using the Inter-Retrotransposon Amplified Polymorphism (IRAP) protocol. The obtained fingerprints highlighted a high degree of genetic variability and were used to study the genomic structures of the different accessions. It was hypothesised that there are four ancestral subpopulations at the root of the analysed accessions, which all turned out to be admixed. Overall, these data may be useful for genome sequence annotations and for evaluating genetic variability in this species, which may be useful in stevia breeding. [ABSTRACT FROM AUTHOR]

Many important traits in plants, animals, and microbes are polygenic and challenging to improve through traditional marker-assisted selection. Genomic prediction addresses this by incorporating all genetic data in a mixed model framework. The primary method for predicting breeding values is genomic best linear unbiased prediction, which uses the realized genomic relationship or kinship matrix (K) to connect genotype to phenotype. Genomic relationship matrices share information among entries to estimate the observed entries' genetic values and predict unobserved entries' genetic values. One of the main parameters of such models is genomic variance (r2 g), or the variance of a trait associated with a genome-wide sample of DNA polymorphisms, and genomic heritability (h2 g); however, the seminal papers introducing different forms of K often do not discuss their effects on the model estimated variance components despite their importance in genetic research and breeding. Here, we discuss the effect of several standard methods for calculating the genomic relationship matrix on estimates of r2 g and h2 g. With current approaches, we found that the genomic variance tends to be either overestimated or underestimated depending on the scaling and centering applied to the marker matrix (Z), the value of the average diagonal element of K, and the assortment of alleles and heterozygosity (H) in the observed population. Using the average semivariance, we propose a new matrix, KASV, that directly yields accurate estimates of r2 g and h2 g in the observed population and produces best linear unbiased predictors equivalent to routine methods in plants and animals. [ABSTRACT FROM AUTHOR]

In genomewide association study (GWAS) of a complex phenotype, a large number of variants, many with small effect sizes, are found to contribute to the variability of the phenotype. Subsequent to the identification of such variants in a GWAS, it is of interest to estimate the risk jointly conferred by the variants. We propose three different strategies of combining the risk SNPs to calculate an allele dosage score. Using simulations, we evaluate the different measures of allele dosage score with respect to the risk prediction accuracy of a binary trait and the proportion of variance explained for a quantitative trait. For a binary trait, an allele dosage score defined based on log odds ratio performs marginally better than the other two measures. For a quantitative trait, the measure based on the standardized slope coefficient in linear regression of the trait on single-nucleotide polymorphism (SNP) genotypes performs better than the measures using the weights proportional to log P-value and the proportion of variance explained. We demonstrate the utility of these measures using a real data on type 2 diabetes and fasting blood sugar level in a south Indian population. [ABSTRACT FROM AUTHOR]

[Objective] The present paper aimed to analyze the genetic structure and variation of four Channa argus populations and three Albino Channa argus populations from different geographical locations. [Method] The DNA of 350 individuals in all populations was detected by 20 pairs of microsatellite primers. The polymorphism and genetic diversity of all microsatellite markers were analyzed. [Result] All 20 pairs of microsatellite primers detected a total of 356 alleles, the number of alleles (Na）ranged from 4 to 40, with an average of 17.8 alleles per locus. The observed heterozygosity (Ho) was between 0.000 to 0.791, and the mean value was 0.578.The expected heterozygosity (He) ranged from 0.31 to 0.91, with an average value of 0.732.The polymorphic information content (PIC) ranged from 0.271 to 0.901, and the average value was 0.700, the Na, Ho, He, and PIC of all the Channa argus populations were higher than those of the Albino Channa argus populations. The genetic differentiation index(FST) of the seven populations ranged from 0.07 876 to 0.40 303, and the genetic differentiation among all populations reached significant level (P<0.05). We divided four Channa argus populations and three Albino Channa argus populations into two groups by molecular variance analysis (AMOVA）, and found that the genetic variation of these groups was mainly from within individuals, accounting for 69.65% of the total genetic variation. The UPGMA hylogenetic tree showed that the Albino Channa argus and Channa argus were clustered into two independent clades. [Conclusion] In this study, the genetic diversity of four Channa argus populations was higher than three Albino Channa argus populations, the protection of genetic diversity of the three populations should be strengthened to avoid inbreeding. This study provides a theoretical basis for the protection and comprehensive utilization of genetic resources of Channa argus and Albino Channa argus. [ABSTRACT FROM AUTHOR]

Achieving project success is a critical element of project management, and identifying the critical success factors (CSFs) that contribute to it is imperative. Agile project management has gained significant attention due to its flexibility, adaptability, and iterative approach, but achieving project success in agile projects remains a challenge. In order to identify the CSFs that have a significant impact on project outcomes, this study examines the role of CSFs in achieving project success in agile projects. A structured online questionnaire was used to collect data from 109 project managers and team members working on agile projects, which was then analyzed using various statistical methods. According to the study's findings, seven factors significantly influence the success of projects: scope and cost management, leadership, agile analytics techniques, customer involvement, teamwork, planning and scheduling, and effective communication, which account for 71.9% of the total variance explained by the CSFs components. The analysis of Pearson correlation coefficients between CSFs and agile project outcomes indicates a positive correlation between each CSF and the four project outcomes (timeliness, cost, quality, and customer satisfaction). The regression analysis includes two significant predictors: scope and cost management, and planning and scheduling, explaining 67.7% of the variation in project outcomes. The findings provide valuable insights for project managers in the Gaza Strip to enhance project success with agile methods by focusing on CSFs. [ABSTRACT FROM AUTHOR]

Owing to sex-specific reproductive strategies, the mean and variance in annual offspring production may differ between the sexes. In addition, there may be sex-specific changes in reproductive performance with age (e.g. senescence). We used 20 and 50 years of longitudinal data on male and female yellow-bellied marmots, respectively, to investigate sex-specific age effects and genetic variance in annual reproductive success. In both sexes, annual offspring production increased linearly with age until a peak was reached at 7 years. This was followed by a decline in annual offspring production in both sexes, indicative of reproductive senescence. However, the initial increase and the subsequent decline (senescence) in reproductive success were both faster in males compared to females. Genetic variance in annual offspring production was higher in males than in females, but heritability was low for both sexes. Additionally, we found no cross-sex genetic correlation in the number of offspring produced, possibly reflecting sex-specific selection related to the inter-sexual differences in reproductive strategies. There was an effect of year on annual offspring production in both sexes, with a high yearly correlation between the sexes emphasizing the importance of environmental variation in determining fitness. Overall, these results demonstrate the impact of sex-specific reproductive strategies on annual offspring production and suggest that male and female marmots may be evolving to separate phenotypic optima. This study further demonstrates the value and limitations of long-term studies investigating sex-based patterns of ageing in the wild. Significance: This study on yellow-bellied marmots demonstrates the key constraints surrounding the research of age-related changes in reproduction in wild populations, which is especially challenging in males. Among these challenges are high immigration rates which prevent the estimation of exact age and maternal identity. Genetic analysis—the only reliable way to estimate paternity—has only been a recent development, limiting the number of father-son relationships available for analysis. The dataset used in this study is long term (20 years of data on males and 50 on females), partially overcoming these obstacles. Results show that reproductive success declines with age in both sexes, with a faster rate of decline in males compared to females, and is influenced by the environment. Genetically, male and female reproductive success is not correlated, revealing that both sexes may be following separate evolutionary trajectories. [ABSTRACT FROM AUTHOR]

Crop area estimates based on counting pixels over classified satellite images are a promising application of remote sensing to agriculture. However, such area estimates are biased, and their variance is a function of the error rates of the classification rule. To redress the bias, estimators (direct and inverse) relying on the so-called confusion matrix have been proposed, but analytic estimators for variances can be tricky to derive. This article proposes a bootstrap method for assessing statistical properties of such estimators based on information from a sample confusion matrix. The proposed method can be applied to any other type of estimator that is built upon confusion matrix information. The resampling procedure is illustrated in a small study to assess the biases and variances of estimates using purely pixel counting and estimates provided by both direct and inverse estimators. The method has the advantage of being simple to implement even when the sample confusion matrix is generated under unequal probability sample design. The results show the limitations of estimates based solely on pixel counting as well as respective advantages and drawbacks of the direct and inverse estimators with respect to their feasibility, unbiasedness, and variance. [ABSTRACT FROM AUTHOR]

According to several orbital reflectance spectroscopy studies, numerous widely scattered lunar surface locales feature remarkably high (>98%) abundance of plagioclase. These "pure" anorthosite claims are based on an absorption band at ∼1.25 μm, associated with minor Fe2+ within plagioclase. But utilization of the 1.25 μm band as a direct gauge of plagioclase abundance requires an underlying assumption that plagioclase FeO is uniform across all measured materials. Available data for FeO in lunar plagioclase are in many cases suspect because electron-probe FeO measurements may be inflated by secondary fluorescence from nearby mafic phases. We studied plagioclase FeO in a set of 13 anorthositic lunar rocks, taking care to avoid proximity to mafic phases; or in cases where complete avoidance was not possible without sacrificing representativeness (i.e., fine-grained impact melt rocks with zoned silicates), correcting close-to-mafic analyses for secondary fluorescence (Sugawara, T. [2001], Japanese Mag. Mineral. Petrol. Sci. 30, 159–163). Results for rock-average plagioclase FeO range from 0.030 wt% in plutonic troctolitic anorthosite 76335, to 0.23 wt% in impact-melt rock 14310. In general, as shown by exsolution of mafic silicates from plagioclase within several samples, final plagioclase FeO in lunar plutonic anorthosites is determined by reequilibration during slow postigneous cooling and/or metamorphism. In contrast, four fast-cooled anorthositic impact melt rocks have consistently higher plagioclase FeO, averaging 1.9 times higher in comparison to average plutonic anorthositic rock. Thus, impact melted lunar anorthosite will have far more prominent 1.25 μm absorption than plutonic anorthosite of the same plagioclase abundance. In view of the inconstancy of plagioclase FeO, orbital spectral reflectance using the 1.25 μm absorption band, or the ratio between that band and one or more mafic silicate bands, cannot be precise enough to justify claims of ability to resolve "purest" (98 vol% +) anorthosite from compositions that are high-plagioclase but not that extreme. • Measuring abundance of lunar plagioclase using its 1.25 μm iron band is problematic. • Plagioclase Fe content in lunar highland rocks is highly diverse. • New electron probe data show plutonic plagioclase Fe ranging from 0.030 to 0.137 wt%. • Impact melted (fast-cooled) highland rocks have even higher plagioclase Fe. • Depth of the plagioclase 1.25 μm band is a function of both abundance and Fe content. [ABSTRACT FROM AUTHOR]

The credibility of scientific research has been seriously questioned by the widely claimed "reproducibility crisis". In light of this crisis, there is a growing awareness that the rigorous standardisation of experimental conditions may contribute to poor reproducibility of animal studies. Instead, systematic heterogenisation has been proposed as a tool to enhance reproducibility, but a real-life test across multiple independent laboratories is still pending. The aim of this study was therefore to test whether heterogenisation of experimental conditions by using multiple experimenters improves the reproducibility of research findings compared to standardised conditions with only one experimenter. To this end, we replicated the same animal experiment in 3 independent laboratories, each employing both a heterogenised and a standardised design. Whereas in the standardised design, all animals were tested by a single experimenter; in the heterogenised design, 3 different experimenters were involved in testing the animals. In contrast to our expectation, the inclusion of multiple experimenters in the heterogenised design did not improve the reproducibility of the results across the 3 laboratories. Interestingly, however, a variance component analysis indicated that the variation introduced by the different experimenters was not as high as the variation introduced by the laboratories, probably explaining why this heterogenisation strategy did not bring the anticipated success. Even more interestingly, for the majority of outcome measures, the remaining residual variation was identified as an important source of variance accounting for 41% (CI95 [34%, 49%]) to 72% (CI95 [58%, 88%]) of the observed total variance. Despite some uncertainty surrounding the estimated numbers, these findings argue for systematically including biological variation rather than eliminating it in animal studies and call for future research on effective improvement strategies. An experimenter heterogenisation was not sufficient to prevent idiosyncratic results in a multi-laboratory setting. Astonishingly, neither the experimenter nor the laboratory accounted for the main portion of the observed variation, but a high amount of residual variation in fact remained unexplained despite strict standardisation regimes. [ABSTRACT FROM AUTHOR]

The Gram-negative bacterium Helicobacter pylori colonizes c.a. 50% of human stomachs worldwide and is the major risk factor for gastric adenocarcinoma. Its high genetic variability makes it difficult to identify biomarkers of early stages of infection that can reliably predict its outcome. Moreover, the increasing antibiotic resistance found in H. pylori defies therapy, constituting a major human health problem. Here, we review H. pylori virulence factors and genes involved in antibiotic resistance, as well as the technologies currently used for their detection. Furthermore, we show that next generation sequencing may lead to faster characterization of virulence factors and prediction of the antibiotic resistance profile, thus contributing to personalized treatment and management of H. pylori-associated infections. With this new approach, more and permanent data will be generated at a lower cost, opening the future to new applications for H. pylori biomarker identification and antibiotic resistance prediction. [ABSTRACT FROM AUTHOR]

Identifying adopted Green Super Rice (GSR) under different agro-ecological locations in Pakistan is crucial to sustaining the high productivity of rice. For this purpose, the multi-location trials of GSR were conducted to evaluate the magnitude of genetic variability, heritability, and stability in eight different locations in Pakistan. The experimental trial was laid out in a randomized complete block (RCB) design with three replications at each location. The combined analysis of variance (ANOVA) manifested significant variations for tested genotypes (g), locations (L), years (Y), genotype × year (GY), and genotype × location (GL) interactions revealing the influence of environmental factors (L and Y) on yield traits. High broad-sense heritability estimates were observed for all the studied traits representing low environmental influence over the expression of traits. Noticeably, GSR 48 showed maximum stability than all other lines in the univariate model across the two years for grain yield and related traits data. Multivariate stability analysis characterized GSR 305 and GSR 252 as the highest yielding with optimum stability across the eight tested locations. Overall, Narowal, Muzaffargarh, and Swat were the most stable locations for GSR cultivation in Pakistan. In conclusion, this study revealed that G×E interactions were an important source of rice yield variation, and its AMMI and biplots analysis are efficient tools for visualizing the response of genotypes to different locations. [ABSTRACT FROM AUTHOR]

In socially monogamous species, extra‐pair paternity (EPP) is predicted to increase variance in male reproductive success (RS) beyond that resulting from genetic monogamy, thus, increasing the "opportunity for selection" (maximum strength of selection that can act on traits). This prediction is challenging to investigate in wild populations because lifetime reproduction data are often incomplete. Moreover, age‐specific variances in reproduction have been rarely quantified. We analyzed 21 years of near‐complete social and genetic reproduction data from an insular population of Seychelles warblers (Acrocephalus sechellensis). We quantified EPP's contribution to lifetime and age‐specific opportunities for selection in males. We compared the variance in male genetic RS vs social ("apparent") RS (RSap) to assess if EPP increased the opportunity for selection over that resulting from genetic monogamy. Despite not causing a statistically significant excess (19%) of the former over the latter, EPP contributed substantially (27%) to the variance in lifetime RS, similarly to within‐pair paternity (WPP, 39%) and to the positive WPP‐EPP covariance (34%). Partitioning the opportunity for selection into age‐specific (co)variance components, showed that EPP also provided a substantial contribution at most ages, varying with age. Therefore, despite possibly not playing the main role in shaping sexual selection in Seychelles warblers, EPP provided a substantial contribution to the lifetime and age‐specific opportunity for selection, which can influence evolutionary processes in age‐structured populations. [ABSTRACT FROM AUTHOR]

Dinoflagellates are amongst the most abundant and diverse groups of plankton in surface waters and contribute to food web productivity and C:N:P biogeochemistry. Here we analyse the C:N:P of marine, autotrophic, planktonic dinoflagellates compiled from culture data from the scientific literature and test if dinoflagellate C:N:P differs from the Redfield ratio, and whether variability in C:N:P is associated with three traits: cell size, wall structure and toxin production. We find the average C:N:P of dinoflagellates is 90:12:1; higher in C:N, and lower in C:P and N:P than the canonical Redfield ratio. In aggregate the three traits examined here account for between 20–31% while taxonomic order accounts for between 37–38% of the variance in C:N:P. Smaller-sized and thecate taxa are higher in C:N, C:P and N:P than larger-size and athecate taxa. Species known to be able to produce C-rich toxins tend to be higher in C:P and N:P while species known to be able to produce N-rich toxins are lower in C:N, C:P and N:P relative to non-toxic species. These results indicate that any average estimate of dinoflagellate C:N:P will be influenced by the relative number of taxa with these traits. [ABSTRACT FROM AUTHOR]

The (co)variance components and corresponding phenotypic and genetic parameters for growth traits and wool traits of economic importance were estimated in the Alpine Merino sheep population maintained at Gansu Provincial Sheep Breeding Technology Extension Station in northwestern China. Data from a maximum of 49,474 animals sired by 526 rams and born from 22,531 ewes over 20 years from 2000 to 2019 were used in this study. Birth type, age of dam, birth year, sex and/or management group, and age at measurement were initially fitted as fixed effects in an animal model with various random effects. Genetic groups were defined for all animals by the sire breed and breed genotype interacted with dam‐strain flocks and were fitted as one of the random effects. Analyses were conducted using a residual maximum likelihood procedure (ASReml). Seven different animal models were fitted for all traits, and the most appropriate model with relevant random effects was selected through log‐likelihood ratio testing. After identifying the appropriate model through single‐trait analysis, bivariate analyses were used to obtain the phenotypic and genetic correlations among the traits. The estimates of additive direct heritability for birth weight (BWT), weaning weight (WWT), preweaning growth rate (prwADG), postweaning growth rate (powADG), yearling body weight (YWT), average fibre diameter (AFD), greasy fleece weight (GFW), clean fleece weight (CFW), yield (YLD), yearling wool staple length (YSL), coefficient of variation of average fibre diameter (FDcv) and wool visual fineness counts (VFC) were 0.30, 0.18, 0.18, 0.20, 0.29, 0.20, 0.19, 0.20, 0.35, 0.19, 0.16 and 0.13, respectively, with standard errors ranging from 0.02 to 0.05. The corresponding ratios of genetic group variance to additive genetic variance were significant and, respectively, 0.35, 0.80, 0.62, 0.26, 0.13, 1.06, 0.38, 0.64, 0.09, 0.12, 0.06 and 0.58. These results suggest for these traits that there is potential to exploit both the additive genetic variation and between genetic group variation although for most traits the between group variation was smaller than the variation within groups. Favourable genetic correlations were found among the growth traits, and between growth traits and fleece production traits, and among wool traits GFW, CFW, YSL and YLD. This study provides the required estimates of genetic parameters of both growth and wool traits of the new breed for the design of more effective breeding programmes. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the use of feeding behavior in conjunction with gut microbiome sampled at two growth stages in predicting growth and body composition traits of finishing pigs. Six hundred and fifty-one purebred boars of three breeds: Duroc (DR), Landrace (LR), and Large White (LW), were studied. Feeding activities were recorded individually from 99 to 163 days of age. The 16S rRNA gene sequences were obtained from each pig at 123 ± 4 and 158 ± 4 days of age. When pigs reached market weight, body weight (BW), ultrasound backfat thickness (BF), ultrasound loin depth (LD), and ultrasound intramuscular fat (IMF) content were measured on live animals. Three models including feeding behavior (Model_FB), gut microbiota (Model_M), or both (Model_FB_M) as predictors, were investigated. Prediction accuracies were evaluated through cross-validation across genetic backgrounds using the leave-one-breed-out strategy and across rearing environments using the leave-one-room-out approach. The proportions of phenotypic variance of growth and body composition traits explained by feeding behavior ranged from 0.02 to 0.30, and from 0.20 to 0.52 when using gut microbiota composition. Overall prediction accuracy (averaged over traits and time points) of phenotypes was 0.24 and 0.33 for Model_FB, 0.27 and 0.19 for Model_M, and 0.40 and 0.35 for Model_FB_M for the across-breed and across-room scenarios, respectively. This study shows how feeding behavior and gut microbiota composition provide non-redundant information in predicting growth in swine. [ABSTRACT FROM AUTHOR]

Near-term projections of climate change are subject to substantial uncertainty from internal climate variability. Here we present an approach to reduce this uncertainty by sub-selecting those ensemble members that more closely resemble observed patterns of ocean temperature variability immediately prior to a certain start date. This constraint aligns the observed and simulated variability phases and is conceptually similar to initialization in seasonal to decadal climate predictions. We apply this variability constraint to large multi-model projection ensembles from the Coupled Model Intercomparison Project phase 6 (CMIP6), consisting of more than 200 ensemble members, and evaluate the skill of the constrained ensemble in predicting the observed near-surface temperature, sea-level pressure and precipitation on decadal to multi-decadal time scales. We find that the constrained projections show significant skill in predicting the climate of the following ten to twenty years, and added value over the ensemble of unconstrained projections. For the first decade after applying the constraint, the global patterns of skill are very similar and can even outperform those of the multi-model ensemble mean of initialized decadal hindcasts from the CMIP6 Decadal Climate Prediction Project (DCPP). In particular for temperature, larger areas show added skill in the constrained projections compared to DCPP, mainly in the Pacific and some neighboring land regions. Temperature and sea-level pressure in several regions are predictable multiple decades ahead, and show significant added value over the unconstrained projections for forecasting the first two decades and the 20-year averages. We further demonstrate the suitability of regional constraints to attribute predictability to certain ocean regions. On the example of global average temperature changes, we confirm the role of Pacific variability in modulating the reduced rate of global warming in the early 2000s, and demonstrate the predictability of reduced global warming rates over the following 15 years based on the climate conditions leading up to 1998. Our results illustrate that constraining internal variability can significantly improve the accuracy of near-term climate change estimates for the next few decades. [ABSTRACT FROM AUTHOR]

Genetic selection has been an effective strategy to improve calving traits including stillbirth in dairy cattle. The primary objectives of the present study were to characterize stillbirth data and determine the feasibility of implementing routine genetic evaluations of stillbirth in five non-Holstein dairy breeds, namely Ayrshire, Guernsey, Milking Shorthorn, Brown Swiss, and Jersey. An updated sire-maternal grandsire threshold model was used to estimate genetic parameters and genetic values for stillbirth. Stillbirth data with the birth years of dams from 1995 to 2018 were extracted from the United States national calving ease database maintained by the Council on Dairy Cattle Breeding. The extracted stillbirth records varied drastically among the five dairy breeds. There were approximately 486K stillbirth records for Jersey and more than 80K stillbirth records for Brown Swiss. The direct and maternal heritability estimates of stillbirth were 6.0% (4.5–7.6%) and 4.7% (3.3–6.1%) in Jersey and 6.8% (3.2–10.5%) and 1.1% (0.6–2.9%) in Brown Swiss. The estimated genetic correlations between direct and maternal genetic effects for stillbirth were −0.15 (−0.38 to −0.08) in Jersey and −0.35 (−0.47 to −0.12) in Brown Swiss. The estimated genetic parameters for stillbirth in these two breeds were within close ranges of previous studies. The reliabilities of predicted transmitting abilities in Jersey and Brown Swiss increased substantially, thanks to the substantial increase in available stillbirth data in the past 10 years. The stillbirth records for Ayrshire, Guernsey, and Milking Shorthorn, which ranged approximately between 3K and 12K, are insufficient to implement reliable routine genetic evaluations of stillbirth in these three dairy breeds. Estimated genetic (co)variances and genetic values deviated considerably from the reported ranges of previous studies, and the reliabilities of predicted transmitting abilities were low in these three breeds. In conclusion, routine genetic evaluations of stillbirth are feasible in Brown Swiss and Jersey. However, reliable genetic evaluations of stillbirth in Ayrshire, Guernsey, and Milking Shorthorn require further data collection on stillbirth. [ABSTRACT FROM AUTHOR]

Background: Stress at workplace keep individual at extreme pressure and leads to exhaustion and inability to deal with stressful situation which causes burnout. Continuous stress on workplace causes multiple physical as well as psychological manifestations. Due to more demanding job nurses are more prone to burnout syndrome at workplace. Early assessment and timely interventions to overcome burnout are key for more productive work output. The objective of the present study was to develop Burnout Syndrome Assessment Scale (BOSAS) for nurses. Materials and Methods: A methodological design was carried out to develop BOSAS in different phases. Modified Delphi technique used for content validity. Reliability was calculated in terms of internal stability and stability of scale. Validity was measured in terms of face, content, criterion, and construct validity. Results: There were a total of 20 items in the final draft. Internal consistency was checked by Cronbach's alpha which was 0.94. Test-retest reliability of scale was found 0.93. Pearson's correlation was used to check inter-item correlation which was found between 0.20 and 0.40. The content validity index was 0.93. Concurrent criterion validity of scale was 0.82. Construct validity was analyzed by factor analysis, all items were loaded in 5 factors and accounted for 64.95% of variance. Conclusion: BOSAS has good validity and reliability and it can be used to assess and identify burnout among nurses. [ABSTRACT FROM AUTHOR]

Landraces are repositories for potential beneficial traits which could be used to develop varieties with enhanced qualities. Optimal utilization of the available large collection of landraces of African yam bean (AYB) presently conserved at the Genetic Resource Center, International Institute of Tropical Agriculture, Ibadan (GRC-IITA), requires an assessment of the magnitude and nature of genetic diversity within the germplasm. One hundred and ninety-six AYB accessions were evaluated during the 2018 and 2019 cropping seasons in three agro-ecologies of Nigeria, using a 14 × 14 triple lattice design. The accessions were assessed for fourteen agronomic traits. Accession, environment, and accession × environment interaction effects were significant (p < 0.05) for all the traits. Variances due to environment and accession × environment interaction were higher than the genotypic variances. Similarly, estimates of phenotypic coefficient of variation (PCV) were higher than genotypic coefficient of variation (GCV) for all traits. Broad-sense heritability ranged from 17.1% (days to maturity) to 66.4% (seed length). Seed yield per plant had positive significant genotypic correlation with all the studied traits, except pod length and seed length. The first three principal components accounted for 59.7% of the total variation among the accessions and comprised of the 14 traits. Five major clusters were delineated based on phenotypic characteristics. Genetic variation was present among the AYB accessions, and these results will be useful for setting breeding goals and conservation approaches. [ABSTRACT FROM AUTHOR]

Various indices have been reported regarding heart rate variability (HRV), but many of them correlate to each other, suggesting the existence of the underlying common factors. We tried to extract factors underlying HRV indices and investigated their features. Using big data of 24-h electrocardiogram (ECG) called Allostatic State Mapping by Ambulatory ECG Repository (ALLSTAR), we calculated 4 time-domain, 4 frequency-domain, and 2 nonlinear HRV indices and the amplitude of cyclic variation of heart rate (Acv) in 113,793 men and 140,601 women with sinus rhythm ECG. Factor analysis revealed that there were two factors with eigenvalue ≥ 1 by which 91% of variance among the HRV indices was explained. Factor 1 that was strongly contributed by very-low frequency, low frequency (LF), and high frequency (HF) components and Acv and it increased with age from 0 to 20 year, then decreased until 65 year, and increased slightly after 80 year. It also increased with daily physical activity at the mild level of activity. Factor 2 that was contributed strongly by scaling exponent α1 and LF-to-HF ratio increased with age until 35 year, plateaued between 35 and 55 year, and decreased thereafter. It also increased with mild to moderate physical activity. HRV indices are constituted by two common factors relating to cardiac vagal function and complexity of heart rate dynamics, respectively, which differ in the relationships with age and physical activity from each other. Although many indices have been proposed for HRV, their constituent factors may be a few. [ABSTRACT FROM AUTHOR]

In this study, it was aimed to determine the efficiency of REML, MINQUE and MIVQUE methods, which are frequently used methods in estimating genetic parameters, in the estimation of variance components when the covariance factor is included in the model. Balanced and normally distributed data obtained by simulation were used in the study. A mixed model with both fixed and chance factors was used in the estimation of variance components. Dry period for milk yield and dam's live weight for birth weight were determined as covariates. In comparing the variance components obtained by the methods, the criteria of having a small environmental variance and a small ratio of environmental variance to total variance were taken as basis. When the methods were compared, the best results for both milk yield and birth weight were obtained with the MINQUE method when the covariate was included in the model. However, the negative variance was obtained with the MINQUE method. In the MIVQUE method, the increase in environmental variance as a result of the inclusion of the covariate in the model was determined as the negative side of this method. In cases where covariance factors were included or not included in the mixed model, the results of the REML method were found to be better and more reliable than the MINQUE and MIVQUE methods when estimating the genetic parameter in the balanced and normally distributed data. [ABSTRACT FROM AUTHOR]

The notion that men are more variable than women has become embedded into scientific thinking. For mental traits like personality, greater male variability has been partly attributed to biology, underpinned by claims that there is generally greater variation among males than females in non‐human animals due to stronger sexual selection on males. However, evidence for greater male variability is limited to morphological traits, and there is little information regarding sex differences in personality‐like behaviours for non‐human animals. Here, we meta‐analysed sex differences in means and variances for over 2100 effects (204 studies) from 220 species (covering five broad taxonomic groups) across five personality traits: boldness, aggression, activity, sociality and exploration. We also tested if sexual size dimorphism, a proxy for sex‐specific sexual selection, explains variation in the magnitude of sex differences in personality. We found no significant differences in personality between the sexes. In addition, sexual size dimorphism did not explain variation in the magnitude of the observed sex differences in the mean or variance in personality for any taxonomic group. In sum, we find no evidence for widespread sex differences in variability in non‐human animal personality. [ABSTRACT FROM AUTHOR]

Detecting quantitative trait loci (QTL) and estimating QTL variances (represented by the squared QTL effects) are two main goals of QTL mapping and genome-wide association studies (GWAS). However, there are issues associated with estimated QTL variances and such issues have not attracted much attention from the QTL mapping community. Estimated QTL variances are usually biased upwards due to estimation being associated with significance tests. The phenomenon is called the Beavis effect. However, estimated variances of QTL without significance tests can also be biased upwards, which cannot be explained by the Beavis effect; rather, this bias is due to the fact that QTL variances are often estimated as the squares of the estimated QTL effects. The parameters are the QTL effects and the estimated QTL variances are obtained by squaring the estimated QTL effects. This square transformation failed to incorporate the errors of estimated QTL effects into the transformation. The consequence is biases in estimated QTL variances. To correct the biases, we can either reformulate the QTL model by treating the QTL effect as random and directly estimate the QTL variance (as a variance component) or adjust the bias by taking into account the error of the estimated QTL effect. A moment method of estimation has been proposed to correct the bias. The method has been validated via Monte Carlo simulation studies. The method has been applied to QTL mapping for the 10-week-body-weight trait from an F2 mouse population. Author summary: One of the goals of QTL mapping and GWAS is to quantify the size of a QTL, which is measured by the QTL variance or the proportion of trait variance explained by the QTL. The effect of a QTL appears in a linear or linear mixed model as a regression coefficient and defined as a fixed effect. The estimated QTL variance in conventional QTL mapping studies takes the square of the estimated QTL effect. This is a biased estimate of QTL variance. An unbiased estimate of the QTL variance should be obtained by (1) treating the QTL effect as random and estimating the variance of the random effect or (2) adjusting the squared estimated QTL effect by the squared estimation error. We proved that the two methods are identical. We further proved that the usual R2 (goodness of fit) in regression analysis is equivalent to the biased QTL heritability while the adjusted R2 is equivalent to the bias corrected QTL heritability. [ABSTRACT FROM AUTHOR]

Background: Genomic selection has revolutionized genetic improvement in animals and plants, but little is known about its long-term effects. Here, we investigated the long-term effects of genomic selection on response to selection, genetic variance, and the genetic architecture of traits using stochastic simulations. We defined the genetic architecture as the set of causal loci underlying each trait, their allele frequencies, and their statistical additive effects. We simulated a livestock population under 50 generations of phenotypic, pedigree, or genomic selection for a single trait, controlled by either only additive, additive and dominance, or additive, dominance, and epistatic effects. The simulated epistasis was based on yeast data. Results: Short-term response was always greatest with genomic selection, while response after 50 generations was greater with phenotypic selection than with genomic selection when epistasis was present, and was always greater than with pedigree selection. This was mainly because loss of genetic variance and of segregating loci was much greater with genomic and pedigree selection than with phenotypic selection. Compared to pedigree selection, selection response was always greater with genomic selection. Pedigree and genomic selection lost a similar amount of genetic variance after 50 generations of selection, but genomic selection maintained more segregating loci, which on average had lower minor allele frequencies than with pedigree selection. Based on this result, genomic selection is expected to better maintain genetic gain after 50 generations than pedigree selection. The amount of change in the genetic architecture of traits was considerable across generations and was similar for genomic and pedigree selection, but slightly less for phenotypic selection. Presence of epistasis resulted in smaller changes in allele frequencies and less fixation of causal loci, but resulted in substantial changes in statistical additive effects across generations. Conclusions: Our results show that genomic selection outperforms pedigree selection in terms of long-term genetic gain, but results in a similar reduction of genetic variance. The genetic architecture of traits changed considerably across generations, especially under selection and when non-additive effects were present. In conclusion, non-additive effects had a substantial impact on the accuracy of selection and long-term response to selection, especially when selection was accurate. [ABSTRACT FROM AUTHOR]

The body conformation traits, which support higher production and longer productive life are very important to breed future dairy buffaloes. Bayesian multiple-trait analysis was performed in biometric traits of Murrah buffaloes to estimate the (co)variance components using an animal model and Gibbs sampling. The model included the fixed effects of parity, season of calving, period of calving, and age group at the time of recording of traits. Random effects included were additive genetic and residual effects. Posterior means of heritability distribution for body length (BL), height at wither (HW), rump width (RW), hip bone distance (HBD), rump slope (RS), brisket distance (BD), navel flap length (NFL) and average skin thickness (AST) were 0.45, 0.56, 0.56, 0.60, 0.48, 0.44, 0.53, and 0.53, respectively. Genetic correlation estimates ranged from -0.64 (RS and NFL) to 0.53 (HDB and HW) and residual correlation estimates ranged from -0.35 (RS and BL) to 0.57 (RS and HW). Results of the current study indicated that all considered linear type traits have a lot of genetic variabilities, which can be used for selection and genetic improvement of Murrah buffaloes in future. [ABSTRACT FROM AUTHOR]

A spurious negative genetic correlation between direct and maternal effects of weaning weight (WW) in beef cattle has historically been problematic for researchers and industry. Previous research has suggested the covariance between sires and herds may be contributing to this relationship. The objective of this study was to estimate the variance components (VC) for WW in American Angus with and without sire by herd (S×H) interaction effect when genomic information is used or not. Five subsets of ~100k animals for each subset were used. When genomic information was included, genotypes were added for 15,637 animals. Five replicates were performed. Four different models were tested, namely, M1: without S×H interaction effect and with covariance between direct and maternal effect (⁠ σ a m ⁠) ≠ 0; M2: with S×H interaction effect and σ a m ≠ 0; M3: without S×H interaction effect and with σ a m = 0; M4: with S×H interaction effect and σ a m = 0. VC were estimated using the restricted maximum likelihood (REML) and single-step genomic REML (ssGREML) with the average information algorithm. Breeding values were computed using single-step genomic BLUP for the models above and one additional model, which had the covariance zeroed after the estimation of VC (M5). The ability of each model to predict future breeding values was investigated with the linear regression method. Under REML, when the S×H interaction effect was added to the model, both direct and maternal genetic variances were greatly reduced, and the negative covariance became positive (i.e. when moving from M1 to M2). Similar patterns were observed under ssGREML, but with less reduction in the direct and maternal genetic variances and still a negative covariance. Models with the S×H interaction effect (M2 and M4) had a better fit according to the Akaike information criteria. Breeding values from those models were more accurate and had less bias than the other three models. The rankings and breeding values of artificial insemination sires (N = 1,977) greatly changed when the S×H interaction effect was fit in the model. Although the S×H interaction effect accounted for 3% to 5% of the total phenotypic variance and improved the model fit, this change in the evaluation model will cause severe reranking among animals. [ABSTRACT FROM AUTHOR]

Multitrait models can increase the accuracy of breeding value prediction and reduce bias due to selection by using traits measured before and after it has occurred. However, as the number of traits grows, a similar trend is expected for the number of parameters to be estimated, which directly affects the computing power and the amount of data required. The aim of the present study was to apply reduced rank (principal components model—PCM) and factor analytical models (FAM), to estimate (co)variance components for nineteen traits, jointly evaluated in a single analysis in Campolina horses. A total of 18 morphometric traits (MT) and one gait visual score (GtS), along with genealogical records of 48,806 horses, were analysed under a restricted maximum likelihood framework. Nine PCM, nine FAM and one standard multitrait model (MTM) were fitted to the data and compared to find the best suitable model. Based on Bayesian information criterion, the best model was the FAM option, considering five common factors (FAM5). After performing an intraclass analysis, none of MT were genetically negatively correlated, whereas GtS was negatively related to all MT, except for the genetic correlations among GtS and BLL, and between GtS and BLLBL (0.01 and 0.10 respectively). From all MT, two traits were derived computing ratios involving other traits, those had negative correlations with others MT, but all favourable for selection. Similar patterns were observed between the genetic parameters obtained from MTM and FAM5 respectively. The heritability estimates ranged from 0.09 (head width) to 0.47 (height at withers). Our results indicated that FAM was efficient to reduce the multitrait analysis dimensionality, and therefore, traits can be combined based on the first three eigenvectors from the additive genetic (co)variance matrix. In addition, there was sufficient genetic variation for selection, benefiting its potential implementation in a breeding program. [ABSTRACT FROM AUTHOR]

The present research aimed at investigating the quality characteristics of ready to cook shrimp analog prepared from Pangasionodon hypophthalmus alkaline‐saline washed surimi under vacuum packaging (VP) conditions at refrigerated temperature (3 ± 1°C). The normal packaging was used as a control (C). During the storage period, the pH of the C samples correlated positively with total volatile base nitrogen and peroxide value. The results demonstrated that VP (24.65 mg N %) significantly (p <.05) delayed total volatile base nitrogen in comparison with the C (19.39 mg N %) at the end of 21 days of storage. The psychrophilic microorganisms were detected from the 9th (C) and 12th (VP) day onward. The obtained data were subjected to principal component analysis and the total variance explained by the two factors for the shrimp analogs stored for different days was 86.8%. The results indicated that VP shrimp analogs had a better shelf‐life when stored at 3 ± 1°C. Novelty impact statement: In recent years, there has been an increase in demand for value‐added fish‐based products. Food industries are adopting novel processing and cooking processes to develop an array of items in order to accomplish consumers' changing preferences. The findings of this study will have a substantial impact on the food industry by enabling the manufacture of novel products such as shrimp analogs produced from surimi of low‐cost pangasius fish with enhanced nutritional content. The preparation process is simple, appealing, affordable, unique, and sustainable. According to the findings of the current study, vacuum packaging is helpful in extending the shelf‐life of the shrimp analog during refrigerated storage. [ABSTRACT FROM AUTHOR]

Reduced volumes in brain regions of interest (ROIs), primarily from adult samples, are associated with posttraumatic stress disorder (PTSD). We extended this work to children using data from the Adolescent Brain Cognitive Development (ABCD) Study® (N = 11,848; Mage = 9.92). Structural equation modeling and an elastic-net (EN) machine-learning approach were used to identify potential effects of traumatic events (TEs) on PTSD symptoms (PTSDsx) directly, and indirectly via the volumes 300 subcortical and cortical ROIs. We then estimated the genetic and environmental variation in the phenotypes. TEs were directly associated with PTSDsx (r = 0.92) in children, but their indirect effects (r < 0.0004)—via the volumes of EN-identified subcortical and cortical ROIs—were negligible at this age. Additive genetic factors explained a modest proportion of the variance in TEs (23.4%) and PTSDsx (21.3%), and accounted for most of the variance of EN-identified volumes of four of the five subcortical (52.4–61.8%) three of the nine cortical ROIs (46.4–53.3%) and cerebral white matter in the left hemisphere (57.4%). Environmental factors explained most of the variance in TEs (C = 61.6%, E = 15.1%), PTSDsx (residual-C = 18.4%, residual-E = 21.8%), right lateral ventricle (C = 15.2%, E = 43.1%) and six of the nine EN-identified cortical ROIs (C = 4.0–13.6%, E = 56.7–74.8%). There is negligible evidence that the volumes of brain ROIs are associated with the indirect effects of TEs on PTSDsx at this age. Overall, environmental factors accounted for more of the variation in TEs and PTSDsx. Whereas additive genetic factors accounted for most of the variability in the volumes of a minority of cortical and in most of subcortical ROIs. [ABSTRACT FROM AUTHOR]

Cross-trait polygenic risk score (PRS) method has gained popularity for assessing genetic correlation of complex traits using summary statistics from biobank-scale genome-wide association studies (GWAS). However, empirical evidence has shown a common bias phenomenon that highly significant cross-trait PRS can only account for a very small amount of genetic variance (R2 can be < 1 % ) in independent testing GWAS. The aim of this paper is to investigate and address the bias phenomenon of cross-trait PRS in numerous GWAS applications. We show that the estimated genetic correlation can be asymptotically biased toward zero. A consistent cross-trait PRS estimator is then proposed to correct such asymptotic bias. In addition, we investigate whether or not SNP screening by GWAS p-values can lead to improved estimation and show the effect of overlapping samples among GWAS. We analyze GWAS summary statistics of reaction time and brain structural magnetic resonance imaging-based features measured in the Pediatric Imaging, Neurocognition, and Genetics study. We find that the raw cross-trait PRS estimators heavily underestimate the genetic similarity between cognitive function and human brain structures (mean R 2 = 1.32 % ), whereas the bias-corrected estimators uncover the moderate degree of genetic overlap between these closely related heritable traits (mean R 2 = 22.42 % ). Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement. [ABSTRACT FROM AUTHOR]

We investigate vertex levels of containment in a random hypergraph grown in the spirit of a recursive tree. We consider a local profile tracking the evolution of the containment of a particular vertex over time, and a global profile concerned with counts of the number of vertices of a particular containment level. For the local containment profile, we obtain the exact mean, variance, and probability distribution in terms of standard combinatorial quantities such as generalized harmonic numbers and Stirling numbers of the first kind. Asymptotically, we observe phases: the early vertices have an asymptotically normal distribution, intermediate vertices have a Poisson distribution, and late vertices have a degenerate distribution. As for the global containment profile, we establish an asymptotically normal distribution for the number of vertices at the smallest containment level as well as their covariances with the number of vertices at the second smallest containment level and the variances of these numbers. The orders in the variance–covariance matrix establish concentration laws. [ABSTRACT FROM AUTHOR]

Let T be the regular tree in which every vertex has exactly $d\ge 3$ neighbours. Run a branching random walk on T, in which at each time step every particle gives birth to a random number of children with mean d and finite variance, and each of these children moves independently to a uniformly chosen neighbour of its parent. We show that, starting with one particle at some vertex 0 and conditionally on survival of the process, the time it takes for every vertex within distance r of 0 to be hit by a particle of the branching random walk is $r + ({2}/{\log(3/2)})\log\log r + {\mathrm{o}}(\log\log r)$. [ABSTRACT FROM AUTHOR]

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Background & aimsUniversal one-time antibody testing for hepatitis C virus (HCV) infection has been recommended by the centers for disease control (CDC) and the United States preventative services task force (USPSTF) for Americans born 1945-1965 (birth cohort). Limited data exists addressing national HCV testing practices. We studied patterns and predictors of HCV testing across the U.S. within the birth cohort utilizing data from the national corporate data warehouse of the U.S. Veterans Administration (VA) health system.MethodsTesting was defined as any HCV test including antibody, RNA or genotype performed during 2000-2013.ResultsOf 6,669,388 birth cohort veterans, 4,221,135 (63%) received care within the VA from 2000-2013 with two or more visits. Of this group, 2,139,935 (51%) had HCV testing with 8.1% HCV antibody and 5.4% RNA positive. Significant variation in testing was observed across centers (range: 7-83%). Older, male, African-Americans, with established risk factors and receiving care from urban centers of excellence were more likely to be tested. Among veterans free of other established risk factors (HIV negative, HBV negative, ALT ⩽40U/L, FIB-4 ⩽1.45, or APRI 3.25) with >30-43% having positive HCV RNA but >16-20% yet to undergo testing for HCV.ConclusionsSignificant disparities are observed in HCV testing within the United States VA health system. Examination of the predictors of testing and HCV positivity may help inform national screening policies.Lay summaryAnalysis of United States Veterans Administration data show significant disparities in hepatitis C virus testing of veterans born 1945-1965 (birth cohort). A fifth of those not tested had evidence of advanced liver fibrosis. Our data suggests some predictors for this disparity and will potentially help inform future policy measures in the era of universal birth cohort testing for HCV.

Aesthetic chills, broadly defined as a somatic marker of peak emotional-hedonic responses, are experienced by individuals across a variety of human cultures. Yet individuals vary widely in the propensity of feeling them. These individual differences have been studied in relation to demographics, personality, and neurobiological and physiological factors, but no study to date has explored the genetic etiological sources of variation. To partition genetic and environmental sources of variation in the propensity of feeling aesthetic chills, we fitted a biometrical genetic model to data from 14,127 twins (from 8995 pairs), collected by the Netherlands Twin Register. Both genetic and unique environmental factors accounted for variance in aesthetic chills, with heritability estimated at 0.36 ([0.33, 0.39] 95% CI). We found females more prone than males to report feeling aesthetic chills. However, a test for genotype x sex interaction did not show evidence that heritability differs between sexes. We thus show that the propensity of feeling aesthetic chills is not shaped by nurture alone, but it also reflects underlying genetic propensities. [ABSTRACT FROM AUTHOR]

It has been proven that the random regression model has a great advantage over the repeatability model in longitudinal data analysis. At present, the random regression model has been used as a standard analysis method in longitudinal data analysis. The aim of this study was to estimate the variance components and heritability of semen traits over the reproductive lifetime of boars. The study data, including 124,941 records from 3,366 boars, were collected from seven boar AI centers in South China between 2010 and 2019. To evaluate alternative models, we compared different polynomial orders of fixed, additive, and permanent environment effects in total 216 models using Bayesian Information Criterions. The result indicated that the best model always has higher-order polynomials of permanent environment effect and lower-order polynomials of fixed effect and additive effect regression. In Landrace boars, the heritabilities ranged from 0.18 to 0.28, 0.06 to 0.43, 0.03 to 0.14, and 0.05 to 0.24 for semen volume, sperm motility, sperm concentration, and abnormal sperm percentage, respectively. In Large White boars, the heritabilities ranged from 0.20 to 0.26, 0.07 to 0.15, 0.10 to 0.23, and 0.06 to 0.34 for semen volume, sperm motility, sperm concentration, and abnormal sperm percentage, respectively. [ABSTRACT FROM AUTHOR]

Many traits are subject to assortative mating, with recent molecular genetic findings confirming longstanding theoretical predictions that assortative mating induces long range dependence across causal variants. However, all marker-based heritability estimators implicitly assume mating is random. We provide mathematical and simulation-based evidence demonstrating that both method-of-moments and likelihood-based estimators are biased in the presence of assortative mating and derive corrected heritability estimators for traits subject to assortment. Finally, we demonstrate that the empirical patterns of estimates across methods and sample sizes for real traits subject to assortative mating are congruent with expected assortative mating-induced biases. For example, marker-based heritability estimates for height are 14% – 23% higher than corrected estimates using UK Biobank data. Methods for estimating heritability, the fraction of variance attributable to genetic factors, assume random mating. Here, the authors show that under assortative mating, when mate choice reflects phenotypic similarity, these methods produce overestimates. [ABSTRACT FROM AUTHOR]

Estimating genetic parameters of quantitative traits is a prerequisite for animal breeding. In honeybees, the genetic variance separates into queen and worker effects. However, under data paucity, parameter estimations that account for this peculiarity often yield implausible results. Consequently, simplified models that attribute all genetic contributions to either the queen (queen model) or the workers (worker model) are often used to estimate variance components in honeybees. However, the causes for estimations with the complete model (colony model) to fail and the consequences of simplified models for variance estimates are little understood. We newly developed the necessary theory to compare parameter estimates that were achieved by the colony model with those of the queen and worker models. Furthermore, we performed computer simulations to quantify the influence of model choice, estimation algorithm, true genetic parameters, rates of controlled mating, apiary sizes, and phenotype data completeness on the success of genetic parameter estimations.We found that successful estimations with the colony model were only possible if at least some of the queens mated controlled on mating stations. In that case, estimates were largely unbiased if more than 20% of the colonies had phenotype records. The simplified queen and worker models proved more stable and yielded plausible parameter estimates for almost all settings. Results obtained from these models were unbiased when mating was uncontrolled, but with controlled mating, the simplified models consistently overestimated heritabilities. This study elucidates the requirements for variance component estimation in honeybees and provides the theoretical groundwork for simplified honeybee models. [ABSTRACT FROM AUTHOR]

The purpose of this study was to understand the integration and clinical practice stress of nursing students and to understand the relationship with department satisfaction. Data collection was from June to July 2021. Data were collected through questionnaires consisting of scales of integration, clinical practice stress, and departmental satisfaction, targeting 3rd and 4th grade nursing students who have had more than one clinical practice experience. A total of 394 copies were analyzed using the SPSS program to analyze the data. As a result of the study, integration showed a positive correlation with department satisfaction (r=.412, p<.01) and a negative correlation with clinical practice stress (r=-.193, p<.01). The predictive factors affecting the department satisfaction of nursing students were integration (β=.406, p<.001) and admission motivation (β=.166, p=.006), which accounted for 20% of the total variance. Integration Performance It was confirmed that the motivation for entering the nursing department affects department satisfaction. In order to increase the department satisfaction of nursing students, it is thought that it is necessary to operate an integration promotion program and department adaptation program from the early stage of admission. [ABSTRACT FROM AUTHOR]

Background: The association between bivariate variables may not necessarily be homogeneous throughout the whole range of the variables. We present a new technique to describe inhomogeneity in the association of bivariate variables.Methods: We consider the correlation of two normally distributed random variables. The 45° diagonal through the origin of coordinates represents the line on which all points would lie if the two variables completely agreed. If the two variables do not completely agree, the points will scatter on both sides of the diagonal and form a cloud. In case of a high association between the variables, the band width of this cloud will be narrow, in case of a low association, the band width will be wide. The band width directly relates to the magnitude of the correlation coefficient. We then determine the Euclidean distances between the diagonal and each point of the bivariate correlation, and rotate the coordinate system clockwise by 45°. The standard deviation of all Euclidean distances, named "global standard deviation", reflects the band width of all points along the former diagonal. Calculating moving averages of the standard deviation along the former diagonal results in "locally structured standard deviations" and reflect patterns of "locally structured correlations (LSC)". LSC highlight inhomogeneity of bivariate correlations. We exemplify this technique by analyzing the association between body mass index (BMI) and hip circumference (HC) in 6313 healthy East German adults aged 18 to 70 years.Results: The correlation between BMI and HC in healthy adults is not homogeneous. LSC is able to identify regions where the predictive power of the bivariate correlation between BMI and HC increases or decreases, and highlights in our example that slim people have a higher association between BMI and HC than obese people.Conclusion: Locally structured correlations (LSC) identify regions of higher or lower than average correlation between two normally distributed variables. [ABSTRACT FROM AUTHOR]

Aims: Intrapatient variability (IPV) was previously defined as coefficient of variation (CV) or standard deviation of tacrolimus (Tac) exposure while none of them was easily being interpreted and translated into clinical practice after kidney transplantation. Methods: We developed a novel Tac variability score (TVS) to evaluate IPV by calculating the frequency of clinically significant changes of Tac trough levels after kidney transplantation. Multivariate Cox proportional analyses were conducted to compare the impact of TVS and CV on transplant outcomes. Results: A total of 1343 patients were divided into high TVS (>0.30) and low TVS (<0.30) groups, and low CV (<0.30) and high CV (>0.30) groups. Univariate analyses showed that high TVS (hazard ratio [HR]: 2.323, 95% confidence interval [CI]: 1.455–3.709) and high CV (HR: 1.606, 95%CI: 1.044–2.471) were associated with inferior graft survival. However, only TVS was an independent predictor for graft failure in multivariate analyses (HR: 1.972, 95%CI: 1.2–3.24), and the correlation maintained in high CV (P =.020) and low CV (P =.037) subgroups, while CV failed to predict graft loss in neither low (P =.387) nor high TVS (P =.600) subgroups. In addition, TVS had a higher correlation with graft survival in patients with Tac exposure within the therapeutic range and the correlation was less influenced by mean Tac trough levels. Conclusion: TVS is a novel measure of Tac IPV with higher correlation with graft survival and more convenience in clinical use than CV after kidney transplantation. [ABSTRACT FROM AUTHOR]

This study aimed to explore the prevalence of sleep disturbances among preschool children in rural areas of China and identify the underlying associated factors. A cross-sectional study was conducted in rural areas of Anhui Province, China, from September 2019 to January 2020. The caregivers of children from 26 kindergartens completed the demographic questionnaire, the Children's Sleep Habits Questionnaire (CSHQ), the Strengths and Difficulties Questionnaire (SDQ), the Self-rating Anxiety Scale (SAS), and the adapted Identification and Management of Feeding Difficulties (IMFeD) tool. One-way analysis of variance, independent-samples t-test, and hierarchical multiple linear regression were conducted to explore the potential influencing factors of sleep disturbances in preschool children. For the specific sleep disturbances based on each subscale of the CSHQ, bedtime resistance (54.9%) and sleep anxiety (47.9%) were the most common types of sleep disturbances, followed by daytime sleepiness (21.3%), sleep duration (20.8%), parasomnias (16.5%), sleep-onset delay (12.6%), night wakings (12.2%) and sleep-disordered breathing (10.3%). The ages of children, children's emotional/behavioral problems, children's feeding difficulties, inconsistent parenting attitudes of parents, poor parenting styles, non-parent caregivers, and caregiver anxiety contributed significantly to the CSHQ total score, accounting for approximately 27.1% (R2 = 0.271) of the variance. Our study indicates that the prevalence of sleep disturbances among preschool children in rural areas of China is quite high. Furthermore, the potential risk factors are complicated, including factors related to both children and their caregivers. [ABSTRACT FROM AUTHOR]