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. Firstly, attempts were made to separate the enantiomers in reversed-phase mode with a mobile phase that was mass spectrometry compatible. Baseline separation was achieved on a Chiralpak IC column with a mobile phase composed of acetonitrile and aqueous ammonium hydrogen carbonate (5 mM; 80:20, v/v). Data were acquired in multiple reaction monitoring mode with positive electrospray ionization by triple-quadrupole mass spectrometry. Then, overall method validation regarding the linearity, accuracy, precision, extraction recovery, matrix effect, and stability of each enantiomer was performed, and acceptable results were obtained for all of these. Finally, the method developed was applied in an enantioselective pharmacokinetic study of miconazole enantiomers in rats after oral administration of racemic miconazole at doses of 5 and 10 mg/kg. The results demonstrated that (–)-(
R
)-miconazole had a higher concentration than (+)-(
S
)-miconazole in plasma, with a ratio of 1.3–1.7 for both doses. This is the first experimental evidence of enantioselective behavior of miconazole in vivo, and provides a reference for clinical practice and encourages further research into miconazole enantioselective metabolism and drug interactions.
Graphical Abstract
A stereoselective pharmacokinetic study of the miconazole enantiomers was investigated using a novel chiral liquid chromatography–tandem mass spectrometry method. Baseline separation was achieved on Chiralpak IC column, and Chiralcel OJ column was used to collect single enantiomer. A significant difference between the two enantiomers was observed in view of the plasma concentration
An eco-friendly green reaction process was developed to achieve efficient hydrogenation of ethyl levulinate (EL) to
γ
-valerolactone (GVL) over commercial-available Raney Cu catalyst with H
2
as the ...hydrogen source. Raney Cu presented higher catalytic activity among a series of Cu based and Raney type catalysts. The maximum yield of GVL was 98.3% at 160 °C for 3 h. It was found that Raney Cu had great reusability and could be used at least three times without loss of activity. Moreover, the results of XRD, XPS and ICP confirmed the high stability of the catalyst. A possible reaction pathway was also proposed. Ethanol was the main byproduct in this reaction; this study therefore provides a green and efficient method for the conversion of EL to GVL.
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 (Rs = 2.0) was achieved within 7.3 min on a Chiralpak ID column (250 × 4.6 mm, 5 μm) employing acetonitrile–water (60:40, v/v) as the mobile phase at a flow rate of 0.6 mL/min. The acquisition of mass spectrometric data was performed in the multiple reaction monitoring mode coupled with a positive electrospray ionization source. A comprehensive validation of this method was rigorously conducted over the concentration range of 1.00–500.0 ng/mL for both enantiomers. All of the validation data demonstrated that the desirable linearity, sensitivity, accuracy, precision, recovery and stability were attained from the proposed approach. The established method was successfully applied to a stereoselective pharmacokinetic study of lansoprazole enantiomers in rat plasma after oral administration of 3 mg/kg racemic lansoprazole or dexlansoprazole. No chiral inversion was observed during the experimental procedure.
Ultrahigh molecular weight polyethylene (UHMWPE) fiber is widely recognized for its exceptional properties, including high strength-to-weight ratio, toughness, and chemical resistance, making it a ...preferred material for reinforcement in various applications. However, its low melting point, surface inertness, and weak adhesion to polymer matrices have limited its potential use in some fields. Researchers have addressed these shortcomings by focusing on surface modifications through physical treatment or chemical coating, thereby enhancing the versatility of materials in numerous UHMWPE fiber composites. By improving the tribological and interfacial properties of UHMWPE, various applications can be explored, including prosthetic joints, energy-absorbing road safety systems, microelectromechanical system devices, and protective materials for defense and personal thermal management. This review provides a comprehensive overview of the remarkable performance of UHMWPE and its composites, providing insights into its wide array of applications.
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•Research advances in application of anodic materials for (non-)Kolbe electrocatalytic decarboxylation of carboxylic acids is systematically reviewed.•The ideas of modification of ...electrode materials and the reaction mechanism of electrocatalytic decarboxylation of carboxylic acids are discussed in detail.•The challenges to be researched and overcome in this field are summarized and looked into.
Biomass, as the exclusive and abundant organic resources, is considered to be the promising renewable resource. Carboxylic acids are one of the many compounds that can be obtained from raw biomass. Decarboxylation of carboxylic acids into fuels and chemicals via electrochemical method at mild reaction condition has been studied for many years. The (non-)Kolbe reaction, one of the oldest organic electrochemical reactions, is the decarboxylation of carboxylic acids to produce alkanes, alcohols, esters, etc. And electrode materials influence the production of electrocatalytic decarboxylation products from carboxylic acids. Therefore, this work mainly reviews the recent advances in applications of anodic materials for (non-)Kolbe electrocatalytic decarboxylation of carboxylic acids. It discusses the reaction mechanism of (non-) Kolbe electrolytic reaction, and the electrocatalytic oxidation of carboxylic acid using different electrodes and electrolytic systems to synthesize fuels and chemicals. Also, various types of electrode catalysts, such as Pt-based catalysts, C-based catalysts, and other catalysts, are introduced in detail. Finally, the challenges and future trends of the (non-)Kolbe reaction of carboxylic acids are presented. This review found that platinum-based electrocatalysts proved to be the most promising catalysts at present. And in recent years, a variety of synthesis methods have been developed to synthesize small size and high-performance noble metal based amorphous catalysts. Another approach is to study catalysts without platinum electricity, such as Ru, Ir, Ti and carbon materials. The review is helpful in understanding and know the anodic materials and their application in (non-)Kolbe electrocatalytic decarboxylation of carboxylic acids for the readers.
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). The results indicated that GWAS, TWAS, and FCT identified seven candidate genes for LDM altogether:
was located by GWAS and FCT,
was located by TWAS and FCT, and
,
,
,
, and
were only located by one of the methods. After functional analysis of these candidate genes and referring to the reported studies, we found that they were mainly functional in the progress of the development of the body and the growth of muscle cells. Combining advanced breeding techniques such as gene editing with our study will significantly accelerate the genetic improvement for the future breeding of Huaxi cattle.
Presently, integrating multi-omics information into a prediction model has become a ameliorate strategy for genomic selection to improve genomic prediction accuracy. Here, we set the genomic and ...transcriptomic data as the training population data, using BSLMM, TWAS, and eQTL mapping to prescreen features according to | ^βb|>0, top 1% of phenotypic variation explained (PVE), expression-associated single nucleotide polymorphisms (eSNPs), and egenes (false discovery rate (FDR)<0.01), where these loci were set as extra fixed effects (named GBLUP-Fix) and random effects (GFBLUP) to improve the prediction accuracy in the validation population, respectively. The results suggested that both GBLUP-Fix and GFBLUP models could improve the accuracy of longissimus dorsi muscle (LDM), water holding capacity (WHC), shear force (SF), and pH in Huaxi cattle on average from 2.14 to 8.69%, especially the improvement of GFBLUP-TWAS over GBLUP was 13.66% for SF. These methods also captured more genetic variance than GBLUP. Our study confirmed that multi-omics-assisted large-effects loci prescreening could improve the accuracy of genomic prediction.
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. These results demonstrated that compared with SAT, the gene expression patterns and metabolite contents of VAT and AAT were more consistent. Particularly,
expression, monounsaturated fatty acid (MUFA) and triglyceride (TG) content were higher in SAT, whereas
expression and the contents of saturated fatty acid (SFA), diacylglycerol (DG), and lysoglycerophosphocholine (LPC) were higher in VAT. Notably, in contrast to
, 10 candidates including
,
,
, and
were identified to affect fat deposition through positively regulating MUFA and TG, and negatively regulating SFA, DG, and LPC. These findings uncovered novel gene resources and offered a theoretical basis for future investigation of fat deposition in beef cattle.
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. In this study, we applied TPE to optimize the hyperparameters of Kernel ridge regression (KRR) and support vector regression (SVR). To evaluate the performance of TPE, we compared the prediction accuracy of KRR-TPE and SVR-TPE with the genomic best linear unbiased prediction (GBLUP) and KRR-RS, KRR-Grid, SVR-RS, and SVR-Grid, which tuned the hyperparameters of KRR and SVR by using random search (RS) and grid search (Gird) in a simulation dataset and the real datasets. The results indicated that KRR-TPE achieved the most powerful prediction ability considering all populations and was the most convenient. Especially for the Chinese Simmental beef cattle and Loblolly pine populations, the prediction accuracy of KRR-TPE had an 8.73% and 6.08% average improvement compared with GBLUP, respectively. Our study will greatly promote the application of machine learning in GP and further accelerate breeding progress.
Abstract
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.
Results
We utilized the Cosine kernel to map genomic and transcriptomic data as
$${n}\times {n}$$
n
×
n
symmetric matrix (
G
matrix and
T
matrix), combined with the best linear unbiased prediction (BLUP) for GS. Here, we defined five kernel-based prediction models: genomic BLUP (GBLUP), transcriptome-BLUP (TBLUP), multi-omics BLUP (MBLUP,
$$\boldsymbol M=\mathrm{ratio}\times\boldsymbol G+(1-\mathrm{ratio})\times\boldsymbol T$$
M
=
ratio
×
G
+
(
1
-
ratio
)
×
T
), multi-omics single-step BLUP (mssBLUP), and weighted multi-omics single-step BLUP (wmssBLUP) to integrate transcribed individuals and genotyped resource population. The predictive accuracy evaluations in four traits of the Chinese Simmental beef cattle population showed that (1) MBLUP was far preferred to GBLUP (ratio = 1.0), (2) the prediction accuracy of wmssBLUP and mssBLUP had 4.18% and 3.37% average improvement over GBLUP, (3) We also found the accuracy of wmssBLUP increased with the growing proportion of transcribed cattle in the whole resource population.
Conclusions
We concluded that the inclusion of transcriptome data in GS had the potential to improve accuracy. Moreover, wmssBLUP is accepted to be a promising alternative for the present situation in which plenty of individuals are genotyped when fewer are transcribed.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
