UBE2C promotes myoblast differentiation and skeletal muscle regeneration through the Akt signaling pathway.

Ubiquitin-conjugation enzyme E2C (UBE2C) is a crucial component of the ubiquitin-proteasome system that is involved in numerous cancers. In this study, we find that UBE2C expression is significantly increased in mouse embryos, a critical stage during skeletal muscle development. We further investigate the function of UBE2C in myogenesis. Knockdown of UBE2C inhibits C2C12 cell differentiation and decreases the expressions of MyoG and MyHC, while overexpression of UBE2C promotes C2C12 cell differentiation. Additionally, knockdown of UBE2C, specifically in the tibialis anterior muscle (TA), severely impedes muscle regeneration in vivo. Mechanistically, we show that UBE2C knockdown reduces the level of phosphorylated protein kinase B (p-Akt) and promotes the degradation of Akt. These findings suggest that UBE2C plays a critical role in myoblast differentiation and muscle regeneration and that UBE2C regulates myogenesis through the Akt signaling pathway.

miR-423-5p Regulates Skeletal Muscle Growth and Development by Negatively Inhibiting Target Gene SRF.

The process of muscle growth directly affects the yield and quality of pork food products. Muscle fibers are created during the embryonic stage, grow following birth, and regenerate during adulthood; these are all considered to be phases of muscle development. A multilevel network of transcriptional, post-transcriptional, and pathway levels controls this process. An integrated toolbox of genetics and genomics as well as the use of genomics techniques has been used in the past to attempt to understand the molecular processes behind skeletal muscle growth and development in pigs under divergent selection processes. A class of endogenous noncoding RNAs have a major regulatory function in myogenesis. But the precise function of miRNA-423-5p in muscle development and the related molecular pathways remain largely unknown. Using target prediction software, initially, the potential target genes of miR-423-5p in the Guangxi Bama miniature pig line were identified using various selection criteria for skeletal muscle growth and development. The serum response factor (SRF) was found to be one of the potential target genes, and the two are negatively correlated, suggesting that there may be targeted interactions. In addition to being strongly expressed in swine skeletal muscle, miR-423-5p was also up-regulated during C2C12 cell development. Furthermore, real-time PCR analysis showed that the overexpression of miR-423-5p significantly reduced the expression of myogenin and the myogenic differentiation antigen (p < 0.05). Moreover, the results of the enzyme-linked immunosorbent assay (ELISA) demonstrated that the overexpression of miR-423-5p led to a significant reduction in SRF expression (p < 0.05). Furthermore, miR-423-5p down-regulated the luciferase activities of report vectors carrying the 3' UTR of porcine SRF, confirming that SRF is a target gene of miR-423-5p. Taken together, miR-423-5p's involvement in skeletal muscle differentiation may be through the regulation of SRF.

Motility-related microRNAs identified in pig seminal plasma exosomes by high-throughput small RNA sequencing.

Boar fertility is a key determinant of the production efficiency of the whole pig breeding industry and boar sperm motility is the seminal parameter with the greatest impact on the fecundity of a sow. Exosomes are small, extracellular vesicles found in many body fluids. Seminal plasma exosomes, which are secreted by the epididymis, prostate, seminal vesicles, and testes, contain a large number of miRNAs, the types and levels of which can reflect the physiological state of source cells. It has been shown that the expression profile of seminal plasma exosomal miRNA differs between low-motility semen and normal semen. The aim of this study was to investigate the relationship between semen motility and exosomal miRNA profiles to obtain information that would allow to predict boar fertility, as well as contribute to the understanding of the mechanisms by which exosomal miRNAs regulate semen motility. Three high-motility (semen motility >90 %) and three low-motility (semen motility <80 %) semen samples were collected from Landrace and Yorkshire boars, respectively, and seminal plasma exosomes were extracted by ultracentrifugation. Exosome characterization was performed using transmission electron microscopy, NTA, and Western blot. The expression profiles of exosomal miRNAs associated with semen motility in the two boar breeds were subsequently determined by small RNA sequencing. The results showed that 297 known miRNAs and 295 novel RNAs were co-expressed in the four groups. Notably, six miRNAs (ssc-miR-122-5p, ssc-miR-486, ssc-miR-451, ssc-miR-345-3p, ssc-miR-362, and ssc-miR-500-5p) were found to be differentially expressed in both boar breeds. Enrichment analysis of the target genes of the differentially expressed miRNAs showed that they were mainly involved in biological processes such as regulation of transcription from RNA polymerase II promoter, regulation of gene expression, and intracellular signal transduction and signaling pathways such as the PI3K-Akt, MAPK, and Ras signaling pathways. The six differentially expressed miRNAs identified in this study have significant potential as noninvasive markers of boar semen motility. Meanwhile, the results of the enrichment analysis provide novel insights into the mechanisms underlying the regulation of semen motility.

Tailoring grain boundary stability of zinc-titanium alloy for long-lasting aqueous zinc batteries.

The detrimental parasitic reactions and uncontrolled deposition behavior derived from inherently unstable interface have largely impeded the practical application of aqueous zinc batteries. So far, tremendous efforts have been devoted to tailoring interfaces, while stabilization of grain boundaries has received less attention. Here, we demonstrate that preferential distribution of intermetallic compounds at grain boundaries via an alloying strategy can substantially suppress intergranular corrosion. In-depth morphology analysis reveals their thermodynamic stability, ensuring sustainable potency. Furthermore, the hybrid nucleation and growth mode resulting from reduced Gibbs free energy contributes to the spatially uniform distribution of Zn nuclei, promoting the dense Zn deposition. These integrated merits enable a high Zn reversibility of 99.85% for over 4000 cycles, steady charge-discharge at 10 mA cm-2, and impressive cyclability for roughly 3500 cycles in Zn-Ti//NH4V4O10 full cell. Notably, the multi-layer pouch cell of 34 mAh maintains stable cycling for 500 cycles. This work highlights a fundamental understanding of microstructure and motivates the precise tuning of grain boundary characteristics to achieve highly reversible Zn anodes.

Isolation of Limosilactobacillus reuteri Strain with Anti-porcine Epidemic Diarrhea Virus from Swine Feces.

Porcine epidemic diarrhea virus (PEDV) causes severe diarrhea diseases in piglets, which has brought huge economic losses to the pig industry. As the dominant Lactobacillus species in the piglet intestine, the antiviral effect of Limosilactobacillus reuteri (L. reuteri) has been reported. Nine L. reuteri strains were isolated and identified from swine feces in this study. The CCK-8 assay examined the anti-PEDV potential of their cell-free supernatant (CFS). Among the nine L. reuteri isolates examined, LRC8 had a higher inhibition rate to PEDV than the other strains. Thus, the biological properties of the LRC8 strain, such as growth ability, acid production ability, acid and bile salt tolerance, and adhesion to IPEC-J2 cells, were evaluated. Besides, the anti-PEDV activity of LRC8-CFS (LRC8 metabolites, LRM) was assessed using plaque reduction assays, indirect immunofluorescence assays, RT-qPCR, and western blotting. The mRNA relative expression levels of inflammatory factors including IL-1ß, IL-6, IL-8, MCP1, and TNF-α were determined by RT-qPCR. The results showed that the LRC8 strain grew well, was resistant to acid, tolerated bile salts, and adhered strongly to IPEC-J2 cells. In addition, treatment with its CFS (LRM) dramatically downregulated the mRNA expression levels of inflammatory cytokines, and in the Vero cell culture, prophylactic, therapeutic, competitive, and direct-inhibitory actions were seen against PEDV. Finally, we explored the anti-PEDV effects of the LRC8 strain in piglets and found that the LRC8 strain effectively relieved the clinical symptoms and intestinal damage of piglets infected by PEDV. To sum up, we found a L. reuteri strain with an anti-PEDV effect.

The unique gut microbiome of giant pandas involved in protein metabolism contributes to the host's dietary adaption to bamboo.

BACKGROUND: The gut microbiota of the giant panda (Ailuropoda melanoleuca), a global symbol of conservation, are believed to be involved in the host's dietary switch to a fibrous bamboo diet. However, their exact roles are still largely unknown. RESULTS: In this study, we first comprehensively analyzed a large number of gut metagenomes giant pandas (n = 322), including 98 pandas sequenced in this study with deep sequencing (Illumina) and third-generation sequencing (nanopore). We reconstructed 408 metagenome-assembled genomes (MAGs), and 148 of which (36.27%) were near complete. The most abundant MAG was classified as Streptococcus alactolyticus. A pairwise comparison of the metagenomes and meta-transcriptomes in 14 feces revealed genes involved in carbohydrate metabolism were lower, but those involved in protein metabolism were greater in abundance and expression in giant pandas compared to those in herbivores and omnivores. Of note, S. alactolyticus was positively correlated to the KEGG modules of essential amino-acid biosynthesis. After being isolated from pandas and gavaged to mice, S. alactolyticus significantly increased the relative abundance of essential amino acids in mice jejunum. CONCLUSIONS: The study highlights the unique protein metabolic profiles in the giant panda's gut microbiome. The findings suggest that S. alactolyticus is an important player in the gut microbiota that contributes to the giant panda's dietary adaptation by more involvement in protein rather than carbohydrate metabolism. Video Abstract.

Evaluating the effect of SARS-CoV-2 spike mutations with a linear doubly robust learner.

Driven by various mutations on the viral Spike protein, diverse variants of SARS-CoV-2 have emerged and prevailed repeatedly, significantly prolonging the pandemic. This phenomenon necessitates the identification of key Spike mutations for fitness enhancement. To address the need, this manuscript formulates a well-defined framework of causal inference methods for evaluating and identifying key Spike mutations to the viral fitness of SARS-CoV-2. In the context of large-scale genomes of SARS-CoV-2, it estimates the statistical contribution of mutations to viral fitness across lineages and therefore identifies important mutations. Further, identified key mutations are validated by computational methods to possess functional effects, including Spike stability, receptor-binding affinity, and potential for immune escape. Based on the effect score of each mutation, individual key fitness-enhancing mutations such as D614G and T478K are identified and studied. From individual mutations to protein domains, this paper recognizes key protein regions on the Spike protein, including the receptor-binding domain and the N-terminal domain. This research even makes further efforts to investigate viral fitness via mutational effect scores, allowing us to compute the fitness score of different SARS-CoV-2 strains and predict their transmission capacity based solely on their viral sequence. This prediction of viral fitness has been validated using BA.2.12.1, which is not used for regression training but well fits the prediction. To the best of our knowledge, this is the first research to apply causal inference models to mutational analysis on large-scale genomes of SARS-CoV-2. Our findings produce innovative and systematic insights into SARS-CoV-2 and promotes functional studies of its key mutations, serving as reliable guidance about mutations of interest.

Integration of non-additive genome-wide association study with a multi-tissue transcriptome analysis of growth and carcass traits in Duroc pigs.

Growth and carcass traits are of economic importance in the pig production, which affect pork quality and profitability of finishing pig production. This study used whole-genome and transcriptome sequencing technologies to identify potential candidate genes affecting growth and carcass traits in Duroc pigs. The medium (50-60 k) single nucleotide polymorphism (SNP) arrays of 4 154 Duroc pigs from three populations were imputed to whole-genome sequence data, yielding 10 463 227 markers on 18 autosomes. The dominance heritabilities estimated for growth and carcass traits ranged from 0.000 ± 0.041 to 0.161 ± 0.054. Using non-additive genome-wide association study (GWAS), we identified 80 dominance quantitative trait loci for growth and carcass traits at genome-wide significance (false discovery rate < 5%), 15 of which were also detected in our additive GWAS. After fine mapping, 31 candidate genes for dominance GWAS were annotated, and 8 of them were highlighted that have been previously reported to be associated with growth and development (e.g. SNX14, RELN and ENPP2), autosomal recessive diseases (e.g. AMPH, SNX14, RELN and CACNB4) and immune response (e.g. UNC93B1 and PPM1D). By integrating the lead SNPs with RNA-seq data of 34 pig tissues from the Pig Genotype-Tissue Expression project (https://piggtex.farmgtex.org/), we found that the rs691128548, rs333063869, and rs1110730611 have significantly dominant effects for the expression of SNX14, AMPH and UNC93B1 genes in tissues related to growth and development for pig, respectively. Finally, the identified candidate genes were significantly enriched for biological processes involved in the cell and organ development, lipids catabolic process and phosphatidylinositol 3-kinase signalling (P < 0.05). These results provide new molecular markers for meat production and quality selection of pig as well as basis for deciphering the genetic mechanisms of growth and carcass traits.

An ultrasensitive electrochemical sensor for detecting porcine epidemic diarrhea virus based on a Prussian blue-reduced graphene oxide modified glassy carbon electrode.

This study developed a novel, ultrasensitive sandwich-type electrochemical immunosensor for detecting the porcine epidemic diarrhea virus (PEDV). By electrochemical co-deposition of graphene and Prussian blue, a Prussian blue-reduced graphene oxide-modified glassy carbon electrode was made, further modified with PEDV-monoclonal antibodies (mAbs) to create a new PEDV immunosensor using the double antibody sandwich technique. The electrochemical characteristics of several modified electrodes were investigated using cyclic voltammetry (CV). We optimized the pH levels and scan rate. Additionally, we examined specificity, reproducibility, repeatability, accuracy, and stability. The study indicates that the immunosensor has good performance in the concentration range of 1 × 101.88 to 1 × 105.38 TCID50/mL of PEDV, with a detection limit of 1 × 101.93 TCID50/mL at a signal-to-noise ratio of 3σ. The composite membranes produced via co-deposition of graphene and Prussian blue effectively increased electron transport to the glassy carbon electrode, boosted response signals, and increased the sensitivity, specificity, and stability of the immunosensor. The immunosensor could accurately detect PEDV, with results comparable to real-time quantitative PCR. This technique was applied to PEDV detection and served as a model for developing additional immunosensors for detecting hazardous chemicals and pathogenic microbes.

Development and application of an efficient genomic mating method to maximize the production performances of three-way crossbred pigs.

Creating synthetic lines is the standard mating mode for commercial pig production. Traditional mating performance was evaluated through a strictly designed cross-combination test at the 'breed level' to maximize the benefits of production. The Duroc-Landrace-Yorkshire (DLY) three-way crossbred production system became the most widely used breeding scheme for pigs. Here, we proposed an 'individual level' genomic mating procedure that can be applied to commercial pig production with efficient algorithms for estimating marker effects and for allocating the appropriate boar-sow pairs, which can be freely accessed to public in our developed HIBLUP software at https://www.hiblup.com/tutorials#genomic-mating. A total of 875 Duroc boars, 350 Landrace-Yorkshire sows and 3573 DLY pigs were used to carry out the genomic mating to assess the production benefits theoretically. The results showed that genomic mating significantly improved the performances of progeny across different traits compared with random mating, such as the feed conversion rate, days from 30 to 120 kg and eye muscle area could be improved by -0.12, -4.64 d and 2.65 cm2, respectively, which were consistent with the real experimental validations. Overall, our findings indicated that genomic mating is an effective strategy to improve the performances of progeny by maximizing their total genetic merit with consideration of both additive and dominant effects. Also, a herd of boars from a richer genetic source will increase the effectiveness of genomic mating further.

Nonsynonymous SNPs within C7H15orf39 and NOS2 are associated with boar semen quality.

Spermatogenesis is the developmental process that produces spermatozoa. The aim of this study was to investigate the single nucleotide polymorphisms (SNPs) within C7H15orf39 and NOS2 genes and to determine the correlations between two SNPs and semen quality in Duroc boars (n = 604). The polymerase chain reaction-restriction fragment length polymorphisms (PCR-RFLP) method was used for genotyping the selected two nonsynonymous SNPs. The significant correlation was observed between two SNPs (rs80969873: g.58385473 G > A within C7H15orf39; rs325865291: g.44175445 G > A within NOS2) and semen traits in Duroc boars. This study indicates the SNPs in C7H15orf39 and NOS2 may be the potential molecular marker for improving the semen quality traits in Duroc boars.

Difference analysis of intestinal microbiota and metabolites in piglets of different breeds exposed to porcine epidemic diarrhea virus infection.

The gut microbial composition of the Luchuan (LC) piglet, one of China's native breeds, has rarely been studied, especially when compared to other breeds. This study developed a porcine epidemic diarrhea virus (PEDV) infection model in LC and Largewhite (LW) piglets, and analyzed the patterns and differences of intestinal microbial communities and metabolites in piglets of these two breeds after infection. The diarrhea score, survival time, and distribution of viral antigens in the intestine of piglets infected with PEDV differed among breeds, with the jejunal immunohistochemistry score of LW piglets being significantly higher than that of LC piglets (P < 0.001). The results of 16S rRNA sequencing showed differences in microbial diversity and community composition in the intestine of piglets with different breeds between PEDV infection piglets and the healthy controls. There were differences in the species and number of dominant phyla and dominant genera in the same intestinal segment. The relative abundance of Shigella in the jejunum of LC piglets after PEDV infection was significantly lower than that of LW piglets (P < 0.05). The key microorganisms differed in the microbiota were Streptococcus alactolyticus, Roseburia faecis, Lactobacillus iners, Streptococcus equi, and Lactobacillus mucosae (P < 0.05). The non-targeted metabolite analysis revealed that intestinal metabolites showed great differences among the different breeds related to infection. Spearman correlation analysis was conducted to examine any links between the microbiota and metabolites. The metabolites in the intestine of different breeds related to infection were mainly involved in arginine biosynthesis, synaptic vesicle cycle, nicotinic acid and nicotinamide metabolism and mTOR signaling pathway, with significantly positive or negative correlations (P < 0.05) between the various microorganisms. This study provides a theoretical foundation for investigating the application of core microorganisms in the gut of piglets of different breeds in the digestive tracts of those infected with PEDV, and helps to tackle the antimicrobial resistance problem further.

A Standardized Framework for Better Understanding of Phenotypic Differences within Bacterial Phyla Based on Protein Domain.

We propose a standardized framework to classify target species based on their protein domains, which can be utilized in different contexts, like eukaryotes and prokaryotes. In this study, by applying the framework to the bacterial kingdom as an implementation example and comparing the results with the current taxonomy standards at the phylum level, we came to the conclusion that the sequence of domains rather than the content of domains in a protein and the presence of one domain rather than the number of occurrences of one domain play more important roles in deciding bacterial phenotypes as well as matching the current taxonomy. In addition, the comparison also helps us to better focus on the species that conflict with the current phylum category, as well as to further investigate their phenotypic or genotypic differences. IMPORTANCE A 3-step framework was designed which can be applied to clustering species based on their protein domains, and different candidate models are proposed in each step for better adaptation of various scenarios. We show its implementation for the bacterial kingdom as an example, which helps us to find the most appropriate model combination that will best reflect the relationship between domains and phenotypes in this context. In addition, identifying species that are distant in the results but should be closely related phylogenetically can help us to focus on the mismatch for better understanding of their key phenotypic or genotypic differences.

Metabolomic analysis reveals spermatozoa and seminal plasma differences between Duroc and Liang guang Small-spotted pig.

The Liang guang Small-spotted pig is a well-known Chinese indigenous pig that is valued for its exceptional meat quality. However, the Liang guang Small-spotted pig has a lower semen storage capacity, shorter storage time and worse semen quality compared to Duroc. Pig sperm used for artificial insemination (AI) loses part of vitality and quality when being stored in commercial solutions. Serious vitality losses and short shelf life of the semen are particularly prominent in Liang guang Small-spotted pig. In this study, the metabolites in seminal plasma and spermatozoa of Duroc and Liang guang Small-spotted pigs were identified using UHPLC-Q-TOF/MS technology. The findings indicated forty distinct metabolites concentrating on energy metabolic substrates and antioxidant capacity in Liang guang Small-spotted pig and Duroc seminal plasma, including D-Fructose, succinate, 2-dehydro-3-deoxy-d-gluconate, alanine betaine, citrate, carnitine, acetylcarnitine and so on. Seventeen different metabolites were explored, with a focus on glycerophospholipid metabolism in Liang guang Small-spotted pig and Duroc spermatozoa, primarily including glycerol 3-phosphate, acetylcarnitine, phosphatidylcholine (PC) 16:0/16:0, palmitoyl sphingomyelin, acetylcholine, choline, glycerophosphocholine, betaine, L-carnitine, creatinine and others. This study reveals the metabolite profile of spermatozoa and seminal plasma among different pig breeds and might be valuable for understanding the mechanisms that lead to sperm storage capacity. Metabolites involved in energy metabolism, antioxidant capacity and glycerophospholipid metabolism might be key to the poor sperm storage capacity in Liang guang Small-spotted pig.

ECG signal classification based on deep CNN and BiLSTM.

BACKGROUND: Currently, cardiovascular disease has become a major disease endangering human health, and the number of such patients is growing. Electrocardiogram (ECG) is an important basis for {medical doctors to diagnose the cardiovascular disease, which can truly reflect the health of the heart. In this context, the contradiction between the lack of medical resources and the surge in the number of patients has become increasingly prominent. The use of computer-aided diagnosis of cardiovascular disease has become particularly important, so the study of ECG automatic classification method has a strong practical significance. METHODS: This article proposes a new method for automatic identification and classification of ECG.We have developed a dense heart rhythm network that combines a 24-layer Deep Convolutional Neural Network (DCNN) and Bidirectional Long Short-Term Memory (BiLSTM) to deeply mine the hierarchical and time-sensitive features of ECG data. Three different sizes of convolution kernels (32, 64 and 128) are used to mine the detailed features of the ECG signal, and the original ECG is filtered using a combination of wavelet transform and median filtering to eliminate the influence of noise on the signal. A new loss function is proposed to control the fluctuation of loss during the training process, and convergence mapping of the tan function in the range of 0-1 is employed to better reflect the model training loss and correct the optimization direction in time. RESULTS: We applied the dataset provided by the 2017 PhysioNet/CINC challenge for verification. The experiment adopted ten-fold cross validation,and obtained an accuracy rate of 89.3[Formula: see text] and an F1 score of 0.891. CONCLUSIONS: This article proposes its own method in the aspects of ECG data preprocessing, feature extraction and loss function design. Compared with the existing methods, this method improves the accuracy of automatic ECG classification and is helpful for clinical diagnosis and self-monitoring of atrial fibrillation.

Small RNA expression patterns in seminal plasma exosomes isolated from semen containing spermatozoa with cytoplasmic droplets versus regular exosomes in boar semen.

Multiple physiological pathways are controlled by exosomes. Exosomes may be found in seminal plasma where they carry functional molecules to the sperm, such as microRNAs (miRNAs). Sperm cytoplasmic droplets (CDs) are remnants of cytoplasm, and their migration is a morphological characteristic of epididymal maturation. However, miRNA expression patterns in seminal plasma exosomes found in semen containing spermatozoa with CDs versus regular exosomes in boar semen have not been examined. In this study, seminal plasma exosomes were isolated from semen containing spermatozoa with CDs and miRNA expression profiles were analyzed. A total of 348 known and 206 new miRNAs were identified. Sixteen miRNAs were significantly differentially expressed. Of these, 13 miRNAs (ssc-miR-101, ssc-miR-148a-5p, ssc-miR-184, ssc-miR-202-3p, ssc-miR-221-5p, ssc-miR-2483, ssc-miR-29a-3p, ssc-miR-29c, ssc-miR-31, ssc-miR-362, ssc-miR-500-5p, ssc-miR-542-3p, and ssc-miR-769-5p) were significantly upregulated, whereas three miRNAs (ssc-miR-1249, ssc-miR-155-5p, and ssc-miR-296-5p) were significantly downregulated. GO and KEGG pathway analyses showed that these targeted genes were enriched for functions such as metabolic process, reproductive process, proteasome, ubiquitin mediated proteolysis, and oxidative phosphorylation. Therefore, seminal plasma exosomes are predicted to play a key role in the regulation of sperm CDs.

Genome-Wide Association Study of Meat Quality Traits in a Three-Way Crossbred Commercial Pig Population.

Meat quality is an important trait for pig-breeding programs aiming to meet consumers' demands. Geneticists must improve meat quality based on their understanding of the underlying genetic mechanisms. Previous studies showed that most meat-quality indicators were low-to-moderate heritability traits; therefore, improving meat quality using conventional techniques remains a challenge. Here, we performed a genome-wide association study of meat-quality traits using the GeneSeek Porcine SNP50K BeadChip in 582 crossbred Duroc × (Landrace × Yorkshire) commercial pigs (249 males and 333 females). Meat conductivity, marbling score, moisture, meat color, pH, and intramuscular fat (IMF) content were investigated. The genome-wide association study was performed using both fixed and random model Circulating Probability Unification (FarmCPU) and a mixed linear model (MLM) with the rMVP software. The genomic heritability of the studied traits ranged from 0.13 ± 0.07 to 0.55 ± 0.08 for conductivity and meat color, respectively. Thirty-two single-nucleotide polymorphisms (SNPs) were identified for meat quality in the crossbred pigs using both FarmCPU and MLM. Among the detected SNPs, five, nine, seven, four, six, and five were significantly associated with conductivity, IMF, marbling score, meat color, moisture, and pH, respectively. Several candidate genes for meat quality were identified in the detected genomic regions. These findings will contribute to the ongoing improvement of meat quality, meeting consumer demands and improving the economic outlook for the swine industry.

ß-FeOOH: a new anode for potassium-ion batteries.

Potassium-ion batteries (PIBs) hold great potential in large-scale energy storage systems. Here, ß-FeOOH is employed as an anode for PIBs, exhibiting high capacity and good cycling stability. The study of potassium storage mechanism discloses that ß-FeOOH turns into an amorphous structure in the first discharge process, and remains stable in the amorphous state in the subsequent cycles.