Genetic parameters for bull effects on in vitro embryo production (IVP) and relationship between semen quality traits and IVP performance.

In vitro production of embryos (IVP) is increasingly applied in dairy cattle breeding and promises widespread use of females of superior genetic merits. One of the current challenges with implementation of IVP is the variability in blastocyst rates. Several factors contribute to these variabilities, among which is known to be the bull used for oocytes fertilization.

Prediction of body condition in Jersey dairy cattle from 3D-images using machine learning techniques.

The body condition of dairy cows is a crucial health and welfare indicator that is widely acknowledged. Dairy herds with a well-management body condition tend to have more fertile and functional cows. Therefore, routine recording of high-quality body condition phenotypes is required.

Energy balance of dairy cows predicted by mid-infrared spectra data of milk using Bayesian approaches.

Information on dry matter intake (DMI) and energy balance (EB) at the animal and herd level is important for management and breeding decisions. However, routine recording of these traits at commercial farms can be challenging and costly. Fourier-transform mid-infrared (FT-MIR) spectroscopy is a noninvasive technique applicable to a large cohort of animals that is routinely used to analyze milk components and is convenient for predicting complex phenotypes that are typically difficult and expensive to obtain on a large scale.

Age-dependent genetic and environmental variance of semen quality in Nordic Holstein bulls.

The aim of this study was to estimate genetic and environmental parameters, across bull's age, for semen quality traits including pre- and postcryopreservation semen concentration, sperm motility, and sperm viability as well as ejaculate volume and number of doses per ejaculate. A data set on 96,595 ejaculates from 2,831 Nordic Holstein bulls collected between 2006 and 2019 was used. Genetic and environmental parameters were estimated using a random regression model and applying the average-information REML approach.

Supervised learning techniques for dairy cattle body weight prediction from 3D digital images.

The use of automation and sensor-based systems in livestock production allows monitoring of individual cows in real-time and provides the possibility of early warning systems to take necessary management actions against possible anomalies. Among the different RT monitoring parameters, body weight (BW) plays an important role in tracking the productivity and health status. In this study, various supervised learning techniques representing different families of methods in the machine learning space were implemented and compared for performance in the prediction of body weight from 3D image data in dairy cows.

Reliabilities of Genomic Prediction for Young Stock Survival Traits Using 54K SNP Chip Augmented With Additional Single-Nucleotide Polymorphisms Selected From Imputed Whole-Genome Sequencing Data.

This study investigated effects of integrating single-nucleotide polymorphisms (SNPs) selected based on previous genome-wide association studies (GWASs), from imputed whole-genome sequencing (WGS) data, in the conventional 54K chip on genomic prediction reliability of young stock survival (YSS) traits in dairy cattle. The WGS SNPs included two groups of SNP sets that were selected based on GWAS in the Danish Holstein for YSS index (YSS_SNPs, = 98) and SNPs chosen as peaks of quantitative trait loci for the traits of Nordic total merit index in Denmark-Finland-Sweden dairy cattle populations (DFS_SNPs, = 1,541). Additionally, the study also investigated the possibility of improving genomic prediction reliability for survival traits by modeling the SNPs within recessive lethal haplotypes (LET_SNP, n = 130) detected from the 54K chip in the Nordic Holstein.

Genetic parameters of semen quality traits and genetic correlations with service sire nonreturn rate in Nordic Holstein bulls.

Despite the importance of the quality of semen used in artificial insemination to the reproductive success of dairy herds, few studies have estimated the extent of genetic variability in semen quality traits. Even fewer studies have quantified the correlation between semen quality traits and male fertility. In this study, records of 100,058 ejaculates collected from 2,885 Nordic Holstein bulls were used to estimate genetic parameters for semen quality traits, including pre- and postcryopreservation semen concentration, sperm motility and viability, ejaculate volume, and number of doses per ejaculate.

SnCmonolayer with transition metal adatom for gas sensing: a density functional theory studies.

The gas sensing properties of pristine SnCmonolayer and different transition metal adatom (TM-SnC, where TM = Fe, Co, Ni, Cu, Ru, Rh, Pd and Ag) was investigated using van der Waals corrected density functional theory. The understanding and potential of use of SnCmonolayers as sensors or adsorbent for CO, CO, NO, NOand SOgaseous molecules is evaluated by calculating the adsorption and desorption energetics. From the calculated adsorption energies, we found that the pristine SnCmonolayer and 3TM has desirable properties for removal of the considered molecules based on their high adsorption energy, however the 4TM is applicable as recoverable sensors.

Vitamin B and transcobalamin in bovine milk: Genetic variation and genome-wide association with loci along the genome.

In human nutrition, bovine milk is an essential source of bioavailable vitamin B and B-binding proteins, including transcobalamin. In this study, we estimated genetic parameters for milk content of vitamin B and transcobalamin using milk samples from 341 and 663 Danish Holstein cows, respectively. Additionally, we conducted whole-genome association analysis to identify SNP and genes associated with vitamin B and transcobalamin.

Factors Associated with the Death of Preterm Babies Admitted to Neonatal Intensive Care Units in Ethiopia: A Prospective, Cross-sectional, and Observational Study.

To determine the risk factors for death among preterm neonates. . The data set used was derived from a prospective, multi-center, observational clinical study conducted in 5 tertiary hospitals in Ethiopia from July, 2016 to May, 2018.

Novel approach to incorporate information about recessive lethal genes increases the accuracy of genomic prediction for mortality traits.

The genetic underpinnings of calf mortality can be partly polygenic and partly due to deleterious effects of recessive lethal alleles. Prediction of the genetic merits of selection candidates should thus take into account both genetic components contributing to calf mortality. However, simultaneously modeling polygenic risk and recessive lethal allele effects in genomic prediction is challenging due to effects that behave differently.

Controlling the electronic and optical properties of HfS mono-layers lanthanide substitutional doping: a DFT+ study.

Two dimensional HfS is a material with potential applications in the field of photo-catalysis and advanced solid state devices. Density functional theory with the Hubbard parameter (DFT+) calculations were carried out to investigate the structural, electronic and optical properties of lanthanide dopant atoms (LN = La, Ce, Pr, Nd, Pm, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu) in the HfS mono-layer. The calculated electronic band gap for a pristine HfS mono-layer is 1.

Predictive ability of host genetics and rumen microbiome for subclinical ketosis.

Subclinical metabolic disorders such as ketosis cause substantial economic losses for dairy farmers in addition to the serious welfare issues they pose for dairy cows. Major hurdles in genetic improvement against metabolic disorders such as ketosis include difficulties in large-scale phenotype recording and low heritability of traits. Milk concentrations of ketone bodies, such as acetone and β-hydroxybutyric acid (BHB), might be useful indicators to select cows for low susceptibility to ketosis.

Combining multi-population datasets for joint genome-wide association and meta-analyses: The case of bovine milk fat composition traits.

In genome-wide association studies (GWAS), sample size is the most important factor affecting statistical power that is under control of the investigator, posing a major challenge in understanding the genetics underlying difficult-to-measure traits. Combining data sets available from different populations for joint or meta-analysis is a promising alternative to increasing sample sizes available for GWAS. Simulation studies indicate statistical advantages from combining raw data or GWAS summaries in enhancing quantitative trait loci (QTL) detection power.

New 2D Structural Materials: Carbon-Gallium Nitride (CC-GaN) and Boron-Gallium Nitride (BN-GaN) Heterostructures-Materials Design Through Density Functional Theory.

New class of ternary nanohetrostructures have been proposed by mixing 2D gallium nitride (GaN) with graphene and 2D hexagonal boron nitride (BN) with an aim towards desgining innovative 2D materials for applications in electronics and other industries. The structural stability and electronic properties of these nanoheterostructures have been analyzed using first-principles based calculations done in the framework of density functional theory. Different structure patterns have been analyzed to identify the most stable structures.

Major causes of death in preterm infants in selected hospitals in Ethiopia (SIP): a prospective, cross-sectional, observational study.

Background: Neonatal deaths now account for 47% of all deaths in children younger than 5 years globally. More than a third of newborn deaths are due to preterm birth complications, which is the leading cause of death. Understanding the causes and factors contributing to neonatal deaths is needed to identify interventions that will reduce mortality.

Reliability of genomic prediction for milk fatty acid composition by using a multi-population reference and incorporating GWAS results.

Background: Large-scale phenotyping for detailed milk fatty acid (FA) composition is difficult due to expensive and time-consuming analytical techniques. Reliability of genomic prediction is often low for traits that are expensive/difficult to measure and for breeds with a small reference population size. An effective method to increase reference population size could be to combine datasets from different populations.

Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition.

Background: The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation.

A Prospective Study of Causes of Illness and Death in Preterm Infants in Ethiopia: The SIP Study Protocol.

Background: With nearly 15 million annual preterm births globally, preterm birth is the most common cause of neonatal death. Forty to 60 % of neonatal deaths are directly or indirectly associated with preterm mortality. As countries aim to meet the Sustainable Development Goals to reduce neonatal mortality, significant reductions in preterm mortality are needed.

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.

Background: Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome.

Estimation of genetic parameters and detection of chromosomal regions affecting the major milk proteins and their post translational modifications in Danish Holstein and Danish Jersey cattle.

Background: In the Western world bovine milk products are an important protein source in human diet. The major proteins in bovine milk are the four caseins (CN), αS1-, αS2-, β-, and k-CN and the two whey proteins, β-LG and α-LA. It has been shown that both the amount of specific CN and their isoforms including post-translational modifications (PTM) influence technological properties of milk.

Establishment of reference intervals of thyroid function tests from cord blood of neonates in two selected hospitals, Addis Ababa, Ethiopia.

Background: Reference intervals are affected by different factors such as lifestyle, ethnicity, age/developmental stage, gender, nutrition and other environmental factors (Clin Biochem Rev: 29,2008). Therefore, it is obvious that it should be established for every population in different regions even within a country. Then the aim of this study is to establish population specific reference intervals of thyroid stimulating hormone, free thyroxine and free triidothyronine levels of cord blood.

Short communication: Multi-trait estimation of genetic parameters for milk protein composition in the Danish Holstein.

Genetic parameters were estimated for the major milk proteins using bivariate and multi-trait models based on genomic relationships between animals. The analyses included, apart from total protein percentage, αS1-casein (CN), αS2-CN, β-CN, κ-CN, α-lactalbumin, and β-lactoglobulin, as well as the posttranslational sub-forms of glycosylated κ-CN and αS1-CN-8P (phosphorylated). Standard errors of the estimates were used to compare the models.

Spontaneous breaking of spatial and spin symmetry in spinor condensates.

Parametric amplification of quantum fluctuations constitutes a fundamental mechanism for spontaneous symmetry breaking. In our experiments, a spinor condensate acts as a parametric amplifier of spin modes, resulting in a twofold spontaneous breaking of spatial and spin symmetry in the amplified clouds. Our experiments permit a precise analysis of the amplification in specific spatial Bessel-like modes, allowing for the detailed understanding of the double symmetry breaking.

Parametric amplification of vacuum fluctuations in a spinor condensate.

Parametric amplification of vacuum fluctuations is crucial in modern quantum optics, enabling the creation of squeezing and entanglement. We demonstrate the parametric amplification of vacuum fluctuations for matter waves using a spinor F=2 87Rb condensate. Interatomic interactions lead to correlated pair creation in the mF=±1 states from an initial mF=0 condensate, which acts as a vacuum for mF≠0.