MAK: a machine learning framework improved genomic prediction via multi-target ensemble regressor chains and automatic selection of assistant traits.

Incorporating the genotypic and phenotypic of the correlated traits into the multi-trait model can significantly improve the prediction accuracy of the target trait in animal and plant breeding, as well as human genetics. However, in most cases, the phenotypic information of the correlated and target trait of the individual to be evaluated was null simultaneously, particularly for the newborn. Therefore, we propose a machine learning framework, MAK, to improve the prediction accuracy of the target trait by constructing the multi-target ensemble regression chains and selecting the assistant trait automatically, which predicted the genomic estimated breeding values of the target trait using genotypic information only.

Incorporating genome-wide and transcriptome-wide association studies to identify genetic elements of longissimus dorsi muscle in Huaxi cattle.

Locating the genetic variation of important livestock and poultry economic traits is essential for genetic improvement in breeding programs. Identifying the candidate genes for the productive ability of Huaxi cattle was one crucial element for practical breeding. Based on the genotype and phenotype data of 1,478 individuals and the RNA-seq data of 120 individuals contained in 1,478 individuals, we implemented genome-wide association studies (GWAS), transcriptome-wide association studies (TWAS), and Fisher's combined test (FCT) to identify the candidate genes for the carcass trait, the weight of longissimus dorsi muscle (LDM).

Transcriptomics and Lipid Metabolomics Analysis of Subcutaneous, Visceral, and Abdominal Adipose Tissues of Beef Cattle.

Fat deposition traits are influenced by genetics and environment, which affect meat quality, growth rate, and energy metabolism of domestic animals. However, at present, the molecular mechanism of fat deposition is not entirely understood in beef cattle. Therefore, the current study conducted transcriptomics and lipid metabolomics analysis of subcutaneous, visceral, and abdominal adipose tissue (SAT, VAT, and AAT) of Huaxi cattle to investigate the differences among these adipose tissues and systematically explore how candidate genes interact with metabolites to affect fat deposition.

Dehydrogenation of Cyclohexanones to Phenols: A Mini Review.

Background: Phenol and its derivatives are important intermediates in the chemical industry, especially the pharmaceutical and electronic industries. The synthesis of phenols has attracted the attention of scientists due to their importance. Dehydrogenation of cyclohexanones is one of the promising aromatization strategies for phenols manufacture because the raw materials are low cost and stable.

Improving Genomic Prediction with Machine Learning Incorporating TPE for Hyperparameters Optimization.

Depending on excellent prediction ability, machine learning has been considered the most powerful implement to analyze high-throughput sequencing genome data. However, the sophisticated process of tuning hyperparameters tremendously impedes the wider application of machine learning in animal and plant breeding programs. Therefore, we integrated an automatic tuning hyperparameters algorithm, tree-structured Parzen estimator (TPE), with machine learning to simplify the process of using machine learning for genomic prediction.

Incorporating kernelized multi-omics data improves the accuracy of genomic prediction.

Background: Genomic selection (GS) has revolutionized animal and plant breeding after the first implementation via early selection before measuring phenotypes. Besides genome, transcriptome and metabolome information are increasingly considered new sources for GS. Difficulties in building the model with multi-omics data for GS and the limit of specimen availability have both delayed the progress of investigating multi-omics.

Integrating genomics and transcriptomics to identify candidate genes for subcutaneous fat deposition in beef cattle.

Fat deposition is a complex economic trait regulated by polygenic genetic basis and environmental factors. Therefore, integrating multi-omics data to uncover its internal regulatory mechanism has attracted extensive attention. Here, we performed genomics and transcriptomics analysis to detect candidates affecting subcutaneous fat (SCF) deposition in beef cattle.

A high-performance and stable Cu/Beta for adsorption-catalytic oxidation in-situ destruction of low concentration toluene.

Finding a cost-effective treatment to remove of low concentrations of volatile organic compounds (VOCs) is still a challenge. In this study, a Cu/Beta material was developed for in situ adsorption-catalytic oxidation of low concentrations of toluene. The results showed that the addition of Cu enhanced the adsorption and catalytic oxidation of toluene by Beta zeolite.

Enantioselective analysis of lansoprazole in rat plasma by LC-MS/MS: Application to a stereoselective pharmacokinetic study.

A rapid, sensitive and enantioselective method was developed and fully validated for the separation and determination of lansoprazole enantiomers in rat plasma by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The analytes and the internal standard (esomeprazole) were both extracted from plasma samples by liquid-liquid extraction with diethyl ether-dichloromethane (70:30; v/v). Satisfactory resolution (R  = 2.

Enantioselective separation and determination of miconazole in rat plasma by chiral LC-MS/MS: application in a stereoselective pharmacokinetic study.

Miconazole has one chiral center, and consists of two enantiomers. In this study, a novel chiral liquid chromatography-tandem mass spectrometry method was developed for enantioselective separation and determination of miconazole in rat plasma. For the first time, the enantioselective pharmacokinetics of miconazole was investigated by the current method.

Carboxymethyl β-cyclodextrin as chiral selector in capillary electrophoresis: Enantioseparation of 16 basic chiral drugs and its chiral recognition mechanism associated with drugs' structural features.

Herein we present the enantioseparation of 10 cardiovascular agents and six bronchiectasis drugs including propranolol, carteolol, metoprolol, atenolol, pindolol, esmolol, bisoprolol, bevantolol, arotinolol, sotalol, clenbuterol, procaterol, bambuterol, tranterol, salbutamol and terbutaline sulfate using carboxymethyl-β-cyclodextrin (CM-β-CD) as chiral selector. To our knowledge, there is no literature about using CM-β-CD for separating carteolol, esmolol, bisoprolol, bevantolol, arotinolol, procaterol, bambuterol and tranterol. During the course of work, changes in pH, CM-β-CD concentration, buffer type and concentration were studied in relation to chiral resolution.