Effects of heat stress on predicted energy balance, fat-to-protein ratio, and milk β-hydroxybutyrate in first-lactation Holstein cattle in Hokkaido, Japan.

Heat stress (HS) reduces dry-matter intake and causes negative energy balance (EB) in Holstein cattle, with consequent deterioration in milk production and wellness. Therefore, the effects of HS can be detected more directly from imbalances in EB than from the consequent changes in production or health traits. EB can be monitored by metabolism-related traits such as predicted EB (PEB), the fat-to-protein ratio (FPR), or β-hydroxybutyrate (BHB) in milk.

Combination of S-1 and the oral ATR inhibitor ceralasertib is effective against pancreatic cancer cells.

Purpose: In our previous study, we found that the Chk1 inhibitor prexasertib enhances the antitumour effect of the oral anticancer drug S-1 against pancreatic cancer cells. In this study, we investigated the effect of combining S-1 and ceralasertib, an oral inhibitor of ATR, which is located upstream of Chk1. Ceralasertib is currently being investigated in multiple clinical trials for various cancers.

Genetic relationship of energy balance predicted from milk traits with fertility in Japanese Holsteins.

We predicted the energy balance of cows from milk traits and estimated the genetic correlations of predicted energy balance (PEB) with fertility traits for the first three lactations. Data included 9,646,606 test-day records of 576,555 Holstein cows in Japan from 2015 to 2019. Genetic parameters were estimated with a multiple-trait model in which the records among lactation stages and parities were treated as separate traits.

Genome-wide search reveals the uniqueness of DNA regions associated with coat color and innate immunity in Hokkaido Native Horse.

Hokkaido Native Horse (HKD) is a horse breed native to Hokkaido in Japan known for the traits such as coat color with no white spots and adaptability to the local cold climate. To examine whether those traits of HKD are conferred at the DNA level, we attempted to identify fixed DNA regions in HKD individuals, that is, the selection signatures of HKD. A comparison of genome-wide single nucleotide polymorphism genotypes in 58 HKD individuals by principal component analysis, and cluster analysis between breeds, including HKD, and within the HKD individuals indicated the genetic independence of HKD as a breed.

Longitudinal genome-wide association analysis using a single-step random regression model for height in Japanese Holstein cattle.

Growth traits, such as body weight and height, are essential in the design of genetic improvement programs of dairy cattle due to their relationship with feeding efficiency, longevity, and health. We investigated genomic regions influencing height across growth stages in Japanese Holstein cattle using a single-step random regression model. We used 72,921 records from birth to 60 mo of age with 4,111 animals born between 2000 and 2016.

[Early Prediction of Support Necessity for Pharmacy Clinical Internship Using Deep Learning].

The duration of undergraduate study was extended in 2006 to six years for pharmaceutical education aimed at training highly qualified pharmacists. Clinical internship in current pharmaceutical education is positioned as being important for fostering the qualities required of a pharmacist, and the support of faculty members is essential. Based on the above, we thought that support from faculty members should be provided easily and positively, which would enrich community pharmacy clinical internships.

Application of single-step single nucleotide polymorphism best linear unbiased predictor model with unknown-parent groups for type traits in Japanese Holsteins.

The objectives of this study were to investigate the computational performance and the predictive ability and bias of a single-step SNP BLUP model (ssSNPBLUP) in genotyped young animals with unknown-parent groups (UPG) for type traits, using national genetic evaluation data from the Japanese Holstein population. The phenotype, genotype, and pedigree data were the same as those used in a national genetic evaluation of linear type traits classified between April 1984 and December 2020. In the current study, 2 data sets were prepared: the full data set containing all entries up to December 2020 and a truncated data set ending with December 2016.

Meta-model of Human Recognition-behavioral Adaptation System.

Scientific modeling is a syllogistic system of definitive premise, sound inference and consistent explanation to understand, define, quantify, visualize or simulate feature of the target. Single-model is defined to an informative representation for identifying a property of a target object/phenomenon, and meta-model integrates the relevant single-models to explain phenomenological realities. Human recognition-behavioral adaptation is an information-metabolism system to maintain homeostasis of human-self, and that has been investigated in neurological, psychiatric and psychological aspects.

Is single-step genomic REML with the algorithm for proven and young more computationally efficient when less generations of data are present?

Efficient computing techniques allow the estimation of variance components for virtually any traditional dataset. When genomic information is available, variance components can be estimated using genomic REML (GREML). If only a portion of the animals have genotypes, single-step GREML (ssGREML) is the method of choice.

Invited review: Unknown-parent groups and metafounders in single-step genomic BLUP.

Single-step genomic BLUP (ssGBLUP) is a method for genomic prediction that integrates matrices of pedigree (A) and genomic (G) relationships into a single unified additive relationship matrix whose inverse is incorporated into a set of mixed model equations (MME) to compute genomic predictions. Pedigree information in dairy cattle is often incomplete. Missing pedigree potentially causes biases and inflation in genomic estimated breeding values (GEBV) obtained with ssGBLUP.

Metafounders May Reduce Bias in Composite Cattle Genomic Predictions.

Metafounders are pseudo-individuals that act as proxies for animals in base populations. When metafounders are used, individuals from different breeds can be related through pedigree, improving the compatibility between genomic and pedigree relationships. The aim of this study was to investigate the use of metafounders and unknown parent groups (UPGs) for the genomic evaluation of a composite beef cattle population.

Investigating the persistence of accuracy of genomic predictions over time in broilers.

Accuracy of genomic predictions is an important component of the selection response. The objectives of this research were: 1) to investigate trends for prediction accuracies over time in a broiler population of accumulated phenotypes, genotypes, and pedigrees and 2) to test if data from distant generations are useful to maintain prediction accuracies in selection candidates. The data contained 820K phenotypes for a growth trait (GT), 200K for two feed efficiency traits (FE1 and FE2), and 42K for a carcass yield trait (CY).

Changes in genomic predictions when new information is added.

The stability of genomic evaluations depends on the amount of data and population parameters. When the dataset is large enough to estimate the value of nearly all independent chromosome segments (~10K in American Angus cattle), the accuracy and persistency of breeding values will be high. The objective of this study was to investigate changes in estimated breeding values (EBV) and genomic EBV (GEBV) across monthly evaluations for 1 yr in a large genotyped population of beef cattle.

Comparison of models for missing pedigree in single-step genomic prediction.

Pedigree information is often missing for some animals in a breeding program. Unknown-parent groups (UPGs) are assigned to the missing parents to avoid biased genetic evaluations. Although the use of UPGs is well established for the pedigree model, it is unclear how UPGs are integrated into the inverse of the unified relationship matrix (H-inverse) required for single-step genomic best linear unbiased prediction.

Validation of single-step GBLUP genomic predictions from threshold models using the linear regression method: An application in chicken mortality.

The objective of this study was to determine whether the linear regression (LR) method could be used to validate genomic threshold models. Statistics for the LR method were computed from estimated breeding values (EBVs) using the whole and truncated data sets with variances from the reference and validation populations. The method was tested using simulated and real chicken data sets.

Bias and accuracy of dairy sheep evaluations using BLUP and SSGBLUP with metafounders and unknown parent groups.

Background: Bias has been reported in genetic or genomic evaluations of several species. Common biases are systematic differences between averages of estimated and true breeding values, and their over- or under-dispersion. In addition, comparing accuracies of pedigree versus genomic predictions is a difficult task.

Beef trait genetic parameters based on old and recent data and its implications for genomic predictions in Italian Simmental cattle.

This study aimed to evaluate the changes in variance components over time to identify a subset of data from the Italian Simmental (IS) population that would yield the most appropriate estimates of genetic parameters and breeding values for beef traits to select young bulls. Data from bulls raised between 1986 and 2017 were used to estimate genetic parameters and breeding values for four beef traits (average daily gain [ADG], body size [BS], muscularity [MUS], and feet and legs [FL]). The phenotypic mean increased during the years of the study for ADG, but it decreased for BS, MUS, and FL.

Single-Step Genomic Evaluations from Theory to Practice: Using SNP Chips and Sequence Data in BLUPF90.

Single-step genomic evaluation became a standard procedure in livestock breeding, and the main reason is the ability to combine all pedigree, phenotypes, and genotypes available into one single evaluation, without the need of post-analysis processing. Therefore, the incorporation of data on genotyped and non-genotyped animals in this method is straightforward. Since 2009, two main implementations of single-step were proposed.

Bcl-2/Bcl-xL inhibitor navitoclax increases the antitumor effect of Chk1 inhibitor prexasertib by inducing apoptosis in pancreatic cancer cells via inhibition of Bcl-xL but not Bcl-2.

In our previous study, we showed that prexasertib, a checkpoint kinase 1 (Chk1) inhibitor, enhances the effects of standard drugs for pancreatic cancer, including gemcitabine (GEM), S-1, and the combination of GEM and S-1 (GS). The combination of prexasertib and GS has a strong antitumor effect and induces apoptosis in pancreatic cancer cells by downregulating anti-apoptotic protein Bcl-2. In the present study, we investigated the combined effect of GEM, S-1, and prexasertib with a selective Bcl-2 inhibitor (venetoclax) and a non-selective Bcl-2 inhibitor (navitoclax) in SUIT-2 pancreatic cancer cells.

Indirect predictions with a large number of genotyped animals using the algorithm for proven and young.

Reliable single-nucleotide polymorphisms (SNP) effects from genomic best linear unbiased prediction BLUP (GBLUP) and single-step GBLUP (ssGBLUP) are needed to calculate indirect predictions (IP) for young genotyped animals and animals not included in official evaluations. Obtaining reliable SNP effects and IP requires a minimum number of animals and when a large number of genotyped animals are available, the algorithm for proven and young (APY) may be needed. Thus, the objectives of this study were to evaluate IP with an increasingly larger number of genotyped animals and to determine the minimum number of animals needed to compute reliable SNP effects and IP.

Variance components using genomic information for 2 functional traits in Italian Simmental cattle: Calving interval and lactation persistency.

Functional traits, such as fertility and lactation persistency, are becoming relevant breeding goals for dairy cattle. Fertility is a key element for herd profitability and animal welfare; in particular, calving interval (CIN) is an indicator of female fertility that can be easily recorded. Lactation persistency (LPE; i.

Changes in genetic parameters for fitness and growth traits in pigs under genomic selection.

Genomic selection increases accuracy and decreases generation interval, speeding up genetic changes in the populations. However, intensive changes caused by selection can reduce the genetic variation and can strengthen undesirable genetic correlations. The purpose of this study was to investigate changes in genetic parameters for fitness traits related with prolificacy (FT1) and litter survival (FT2 and FT3), and for growth (GT1 and GT2) traits in pigs over time.

Accuracy of genomic BLUP when considering a genomic relationship matrix based on the number of the largest eigenvalues: a simulation study.

Background: The dimensionality of genomic information is limited by the number of independent chromosome segments (M), which is a function of the effective population size. This dimensionality can be determined approximately by singular value decomposition of the gene content matrix, by eigenvalue decomposition of the genomic relationship matrix (GRM), or by the number of core animals in the algorithm for proven and young (APY) that maximizes the accuracy of genomic prediction. In the latter, core animals act as proxies to linear combinations of M.