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Previous study revealed that isocitrate dehydrogenase (NADP (+)) 2, mitochondrial (IDH2), lactate dehydrogenase A (LDHA), and lactate dehydrogenase B (LDHB) genes were significantly differentially expressed in liver tissues of Holstein cows among different lactation periods and associated with lipid and protein metabolism; hence, they were considered as candidates for milk production traits. Herein, the genetic effects of the three genes on milk yield, fat, and protein traits were studied by association analysis using 926 Chinese Holstein cows from 45 sire families. As a result, five single nucleotide polymorphisms (SNPs) in IDH2, one in LDHA, and three in LDHB were identified by re-sequencing, and subsequently, they were genotyped in 926 Chinese Holstein cows by genotyping by target sequencing (GBTS). With the animal model, single-locus association analysis revealed that four SNPs in IDH2 and one SNP in LDHA were significantly associated with milk, fat, and protein yields (p ≤ 0.0491), and three SNPs in LDHB were associated with milk yield, milk fat yield, and fat percentage (p ≤ 0.0285). Further, four IDH2 SNPs were found to form a haplotype block significantly associated with milk yield, fat yield, protein yield, and protein percentage (p ≤ 0.0249). In addition, functional predictions indicated that one SNP in LDHA, g.26304153G>A, may affect transcription factor binding and two SNPs, g.88544541A>G and g.88556310T>C could alter LDHB mRNA secondary structure. In summary, this study profiled the significant genetic effects of IDH2, LDHA, and LDHB on milk yield and composition traits and provided referable genetic markers for genomic selection programs in dairy cattle. [ABSTRACT FROM AUTHOR]

Enhancing the energy storage properties of dielectric polymer capacitor films through composite materials has gained widespread recognition. Among the various strategies for improving dielectric materials, nanoscale coatings that create structurally controlled multiphase polymeric films have shown great promise. This approach has garnered considerable attention in recent years due to its effectiveness. This review examines surface-coated polymer composites used for dielectric energy storage, discussing their dielectric properties, behaviors, and the underlying physical mechanisms involved in energy storage. The review thoroughly examines the fabrication methods for nanoscale coatings and the selection of coating materials. It also explores the latest advancements in the rational design and control of interfaces in organic–inorganic, organic–organic, and heterogeneous multiphase structures. Additionally, the review delves into the structure–property relationships between different interfacial phases and various interface structures, analyzing how nanoscale coatings the impact dielectric constant, breakdown strength, conduction and charge transport mechanisms, energy density and efficiency, thermal stability, and electrothermal durability of polymeric capacitor films. Moreover, the review summarizes relevant simulation methods and offers computational insights. The potential practical applications and characteristics of such nanoscale coating techniques are discussed, along with the existing challenges and practical limitations. Finally, the review concludes with a summary and outlook, highlighting potential research directions in this rapidly evolving field. [ABSTRACT FROM AUTHOR]

Cis-regulatory elements (CREs) play a pivotal role in orchestrating interactions with trans-regulatory factors such as transcription factors, RNA-binding proteins, and noncoding RNAs. These interactions are fundamental to the molecular architecture underpinning complex and diverse biological functions in living organisms, facilitating a myriad of sophisticated and dynamic processes. The rapid advancement in the identification and characterization of these regulatory elements has been marked by initiatives such as the Encyclopedia of DNA Elements (ENCODE) project, which represents a significant milestone in the field. Concurrently, the development of CRE detection technologies, exemplified by massively parallel reporter assays, has progressed at an impressive pace, providing powerful tools for CRE discovery. The exponential growth of multimodal functional genomic data has necessitated the application of advanced analytical methods. Deep learning algorithms, particularly large language models, have emerged as invaluable tools for deconstructing the intricate nucleotide sequences governing CRE function. These advancements facilitate precise predictions of CRE activity and enable the de novo design of CREs. A deeper understanding of CRE operational dynamics is crucial for harnessing their versatile regulatory properties. Such insights are instrumental in refining gene therapy techniques, enhancing the efficacy of selective breeding programs, pushing the boundaries of genetic innovation, and opening new possibilities in microbial synthetic biology. [ABSTRACT FROM AUTHOR]

Genome selection (GS) technology is an important means to improve the genetic improvement of dairy cows, and the mining and application of functional genes and loci for important traits is one of the important bases for accelerating genetic improvement. Our previous study found that the apolipoprotein A5 (APOA5) and AKT serine/threonine kinase 3 (AKT3) genes were differentially expressed in the liver tissue of Chinese Holstein cows at different lactation stages and influenced milk component synthesis and metabolism, so we considered these two genes as the candidates affecting milk production traits. In this study, we found in total six single nucleotide polymorphisms (SNPs), three in APOA5 and three in AKT3. Subsequent association analysis showed that the six SNPs were significantly associated with milk yield, fat yield, protein yield, or fat percentage (p ≤ 0.05). Three SNPs in APOA5 formed a haplotype block, which was found to be significantly associated with milk yield, fat yield, and protein yield (p ≤ 0.05). In addition, four SNPs were proposed to be functional mutations affecting the milk production phenotype, of which three, 15:g.27446527C>T and 15:g.27447741A>G in APOA5 and 16:g.33367767T>C in AKT3, might change the transcription factor binding sites (TFBSs), and one is a missense mutation, 15:g.27445825T>C in APOA5, which could alter the secondary structure and stability of mRNA and protein. In summary, we demonstrated the genetic effects of APOA5 and AKT3 on milk production traits, and the valuable SNPs could be used as available genetic markers for dairy cattle's GS. [ABSTRACT FROM AUTHOR]

Simple Summary: This study aimed to identify genetic variants related to differences in milk production in Chinese Holstein cows. By analyzing specific genes involved in lipid metabolism, researchers identified variants linked to the milk, fat, and protein yield cows produce over time. They also found patterns in these genetic variations that could affect how the genes work together. The results of this study suggest that these genetic markers could be useful for selecting cows with better milk-production traits. Additionally, the findings could help scientists better understand how these genes influence milk production, potentially leading to improved strategies for breeding dairy cattle. Overall, this research provides valuable insights into enhancing milk production in dairy farming, which could ultimately benefit both farmers and consumers. Our preliminary research proposed the cytochrome P450 family 7 subfamily A member 1 (CYP7A1) and hydroxyacyl-coenzyme A dehydrogenase trifunctional multienzyme complex beta subunit (HADHB) genes as candidates for association with milk-production traits in dairy cattle because of their differential expression across different lactation stages in the liver tissues of Chinese Holstein cows and their potential roles in lipid metabolism. Hence, we identified single-nucleotide polymorphisms (SNPs) of the CYP7A1 and HADHB genes and validated their genetic effects on milk-production traits in a Chinese Holstein population with the goal of providing valuable genetic markers for genomic selection (GS) in dairy cattle, This study identified five SNPs, 14:g.24676921A>G, 14:g.24676224G>A, 14:g.24675708G>T, 14:g.24665961C>T, and 14:g.24664026A>G, in the CYP7A1 gene and three SNPs, 11:g.73256269T>C, 11:g.73256227A>C, and 11:g.73242290C>T, in HADHB. The single-SNP association analysis revealed significant associations (p value ≤ 0.0461) between the eight SNPs of CYP7A1 and HADHB genes and 305-day milk, fat and protein yields. Additionally, using Haploview 4.2, we found that the five SNPs of CYP7A1 formed two haplotype blocks and that the two SNPs of HADHB formed one haplotype block; notably, all three haplotype blocks were also significantly associated with milk, fat and protein yields (p value ≤ 0.0315). Further prediction of transcription factor binding sites (TFBSs) based on Jaspar software (version 2023) showed that the 14:g.24676921A>G, 14:g.24675708G>T, 11:g.73256269T>C, and 11:g.73256227A>C SNPs could alter the 5′ terminal TFBS of the CYP7A1 and HADHB genes. The 14:g.24665961C>T SNP caused changes in the structural stability of the mRNA for the CYP7A1 gene. These alterations have the potential to influence gene expression and, consequently, the phenotype associated with milk-production traits. In summary, we have confirmed the genetic effects of CYP7A1 and HADHB genes on milk-production traits in dairy cattle and identified potential functional mutations that we suggest could be used for GS of dairy cattle and in-depth mechanistic studies of animals. [ABSTRACT FROM AUTHOR]

Nano-ZrO2 has a high atomic active surface and is used as catalyst carrier. The traditional method of preparing ZrO2 nanofibers is electrostatic spinning, which has the problems of high cost and high equipment requirements. In order to solve the shortcomings of traditional preparation methods and prepare excellent ZrO2 nanofibers, a series of ZrO2 nanofibers were prepared based on hydrothermal method by changing the types of reactants, the ratio of reactants to organic additives, solvents, reaction time and other relevant parameters, to explore the growth mechanism of ZrO2 nanofibers, providing a new idea for the preparation of ZrO2 nanofibers on the active surface of altiplano.