NAC transcription factor ATAF1 negatively modulates the PIF-regulated hypocotyl elongation under a short-day photoperiod.

Day length modulates hypocotyl elongation in seedlings to optimize their overall fitness. Variations in cell growth-associated genes are regulated by several transcription factors. However, the specific transcription factors through which the plant clock increases plant fitness are still being elucidated. In this study, we identified the no apical meristem, Arabidopsis thaliana-activating factor (ATAF-1/2), and cup-shaped cotyledon (NAC) family transcription factor ATAF1 as a novel repressor of hypocotyl elongation under a short-day (SD) photoperiod. Variations in day length profoundly affected the transcriptional and protein levels of ATAF1. ATAF1-deficient mutant exhibited increased hypocotyl length and cell growth-promoting gene expression under SD conditions. Moreover, ATAF1 directly targeted and repressed the expression of the cycling Dof factor 1/5 (CDF1/5), two key transcription factors involved in hypocotyl elongation under SD conditions. Additionally, ATAF1 interacted with and negatively modulated the effects of phytochrome-interacting factor (PIF), thus inhibiting PIF-promoted gene expression and hypocotyl elongation. Taken together, our results revealed ATAF1-PIF as a crucial pair modulating the expression of key transcription factors to facilitate plant growth during day/night cycles under fluctuating light conditions.

Research on the grasping characteristics of composite-driven double-finger flexible manipulator.

Aiming at the flexible manipulator grasping complex target parts of different shapes, a double-finger flexible manipulator model is proposed. The manipulator is composed of a flexible mechanical finger, a driving component and a position compensation mechanism. It imitates the motion characteristics of human finger joints and follows the principle of double-fingered grasping. According to the structural characteristics of the target contour, the grasping features of the target contour are extracted. Through the motion principle of the flexible manipulator, the kinematic model of the envelope clamping process of the manipulator target is carried out. Finally, the flexible manipulator experimental platform is built to verify the grasping characteristics of the flexible manipulator target. The results show that the manipulator can realize the adaptive grasping of cylinder and cuboid parts, which have high grasping reliability and stability.

Human MHC Class II and Invariant Chain Knock-in Mice Mimic Rheumatoid Arthritis with Allele Restriction in Immune Response and Arthritis Association.

Transgenic mice expressing human major histocompatibility complex class II (MHCII) risk alleles are widely used in autoimmune disease research, but limitations arise due to non-physiologic expression. To address this, physiologically relevant mouse models are established via knock-in technology to explore the role of MHCII in diseases like rheumatoid arthritis. The gene sequences encoding the ectodomains are replaced with the human DRB1*04:01 and 04:02 alleles, DRA, and CD74 (invariant chain) in C57BL/6N mice. The collagen type II (Col2a1) gene is modified to mimic human COL2. Importantly, DRB1*04:01 knock-in mice display physiologic expression of human MHCII also on thymic epithelial cells, in contrast to DRB1*04:01 transgenic mice. Humanization of the invariant chain enhances MHCII expression on thymic epithelial cells, increases mature B cell numbers in spleen, and improves antigen presentation. To validate its functionality, the collagen-induced arthritis (CIA) model is used, where DRB1*04:01 expression led to a higher susceptibility to arthritis, as compared with mice expressing DRB1*04:02. In addition, the humanized T cell epitope on COL2 allows autoreactive T cell-mediated arthritis development. In conclusion, the humanized knock-in mouse faithfully expresses MHCII, confirming the DRB1*04:01 alleles role in rheumatoid arthritis and being also useful for studying MHCII-associated diseases.

Whole-genome resequencing of Chinese indigenous sheep provides insight into the genetic basis underlying climate adaptation.

BACKGROUND: Chinese indigenous sheep are valuable resources with unique features and characteristics. They are distributed across regions with different climates in mainland China; however, few reports have analyzed the environmental adaptability of sheep based on their genome. We examined the variants and signatures of selection involved in adaptation to extreme humidity, altitude, and temperature conditions in 173 sheep genomes from 41 phenotypically and geographically representative Chinese indigenous sheep breeds to characterize the genetic basis underlying environmental adaptation in these populations. RESULTS: Based on the analysis of population structure, we inferred that Chinese indigenous sheep are divided into four groups: Kazakh (KAZ), Mongolian (MON), Tibetan (TIB), and Yunnan (YUN). We also detected a set of candidate genes that are relevant to adaptation to extreme environmental conditions, such as drought-prone regions (TBXT, TG, and HOXA1), high-altitude regions (DYSF, EPAS1, JAZF1, PDGFD, and NF1) and warm-temperature regions (TSHR, ABCD4, and TEX11). Among all these candidate genes, eight ABCD4, CNTN4, DOCK10, LOC105608545, LOC121816479, SEM3A, SVIL, and TSHR overlap between extreme environmental conditions. The TSHR gene shows a strong signature for positive selection in the warm-temperature group and harbors a single nucleotide polymorphism (SNP) missense mutation located between positions 90,600,001 and 90,650,001 on chromosome 7, which leads to a change in the protein structure of TSHR and influences its stability. CONCLUSIONS: Analysis of the signatures of selection uncovered genes that are likely related to environmental adaptation and a SNP missense mutation in the TSHR gene that affects the protein structure and stability. It also provides information on the evolution of the phylogeographic structure of Chinese indigenous sheep populations. These results provide important genetic resources for future breeding studies and new perspectives on how animals can adapt to climate change.

Decreased IL-4 is the risk factor of depression in patients with Takayasu arteritis.

Objective: Depression is a common complication in Takayasu arteritis (TA). Disorders of the immune system play an important role in both diseases. This study aimed to clarify the feature of cytokines in TA patients with depression. Methods: In this cross-sectional study, serum cytokines were tested in 40 TA patients and 11 healthy controls using the Bio-Plex Magpix System (Bio-Rad®). The state of depression was measured by the Zung Self-Rating Depression Scale (SDS) in TA patients. Logistic regression analysis was performed to find the risk factors of depression in patients with TA. Results: TA patients with depression had higher ESR, hsCRP, NIH, and ITAS.A than patients without depression (16.00 [10.00, 58.50]mm/H vs. 7.50 [4.50, 17.75]mm/H, p = 0.013; 7.60 [2.32, 46.52]mg/L vs. 0.71 [0.32, 4.37]mg/L, p = 0.001; 2.00 [2.00, 3.00] vs. 1.00 [0.00, 2.00], p = 0.007; 7.00 [4.00, 9.50] vs. 1.50 [0.00, 5.75], p = 0.012, respectively). Additionally, the lower age of onset and levels of IL-4, IL-13, eotaxin, and IP-10 were observed in the depressed group compared with the non-depressed (23.50 [19.25, 32.50]pg./ml vs. 37.00 [23.25, 42.50]pg./ml, p = 0.017; 2.80 [2.17, 3.18]pg./ml vs. 3.51 [3.22, 4.66]pg./ml, p < 0.001; 0.66 [0.60, 1.12]pg./ml vs. 1.04 [0.82, 1.25]pg./ml, p = 0.008; 46.48 [37.06, 61.75]pg./ml vs. 69.14 [59.30, 92.80]pg./ml, p = 0.001; 184.50 [138.23, 257.25]pg./ml vs. 322.32 [241.98, 412.60]pg./ml, p = 0.005, respectively). The lower level of IL-4 and age of onset were the independent risk factors for depression in TA patients (OR [95% CI] 0.124 [0.018, 0.827], p = 0.031; 0.870 [0.765, 0.990], p = 0.035, respectively). Conclusion: Our data suggested that lower cytokine levels, especially IL-4, might be involved in the development of TA patients with depression. Clinicians can probably use serum IL-4 level testing as a potential indicator of depression in TA.

Whole-Genome Scanning for Selection Signatures Reveals Candidate Genes Associated with Growth and Tail Length in Sheep.

Compared to Chinese indigenous sheep, Western sheep have rapid growth rate, larger physique, and higher meat yield. These excellent Western sheep were introduced into China for crossbreeding to expedite the enhancement of production performance and mutton quality in local breeds. Here, we investigated population genetic structure and genome-wide selection signatures among the Chinese indigenous sheep and the introduced sheep based on whole-genome resequencing data. The PCA, N-J tree and ADMIXTURE results showed significant genetic difference between Chinese indigenous sheep and introduced sheep. The nucleotide diversity (π) and linkage disequilibrium (LD) decay results indicated that the genomic diversity of introduced breeds were lower. Then, Fst & π ratio, XP-EHH, and de-correlated composite of multiple signals (DCMS) methods were used to detect the selection signals. The results showed that we identified important candidate genes related to growth rate and body size in the introduced breeds. Selected genes with stronger selection signatures are associated with growth rate (CRADD), embryonic development (BVES, LIN28B, and WNT11), body size (HMGA2, MSRB3, and PTCH1), muscle development and fat metabolism (MSTN, PDE3A, LGALS12, GGPS1, and SAR1B), wool color (ASIP), and hair development (KRT71, KRT74, and IRF2BP2). Thus, these genes have the potential to serve as candidate genes for enhancing the growth traits of Chinese indigenous sheep. We also identified tail-length trait-related candidate genes (HOXB13, LIN28A, PAX3, and VEGFA) in Chinese long-tailed breeds. Among these genes, HOXB13 is the main candidate gene for sheep tail length phenotype. LIN28A, PAX3, and VEGFA are related to embryonic development and angiogenesis, so these genes may be candidate genes for sheep tail type traits. This study will serve as a foundation for further genetic improvement of Chinese indigenous sheep and as a reference for studies related to growth and development of sheep.

Identification of potential cell death-related biomarkers for diagnosis and treatment of osteoporosis.

BACKGROUND: This study aimed to identify potential biomarkers for the diagnosis and treatment of osteoporosis (OP). METHODS: Data sets were downloaded from the Gene Expression Omnibus database, and differentially programmed cell death-related genes were screened. Functional analyses were performed to predict the biological processes associated with these genes. Least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), and random forest (RF) machine learning algorithms were used to screen for characteristic genes, and receiver operating characteristics were used to evaluate the diagnosis of disease characteristic gene values. Gene set enrichment analysis (GSEA) and single-sample GSEA were conducted to analyze the correlation between characteristic genes and immune infiltrates. Cytoscape and the Drug Gene Interaction Database (DGIdb) were used to construct the mitochondrial RNA-mRNA-transcription factor network and explore small-molecule drugs. Reverse transcription real-time quantitative PCR (RT-qPCR) analysis was performed to evaluate the expression of biomarker genes in clinical samples. RESULTS: In total, 25 differential cell death genes were identified. Among these, two genes were screened using the LASSO, SVM, and RF algorithms as characteristic genes, including BRSK2 and VPS35. In GSE56815, the area under the receiver operating characteristic curve of BRSK2 was 0.761 and that of VPS35 was 0.789. In addition, immune cell infiltration analysis showed that BRSK2 positively correlated with CD56dim natural killer cells and negatively correlated with central memory CD4 + T cells. Based on the data from DGIdb, hesperadin was associated with BRSK2, and melagatran was associated with VPS35. BRSK2 and VPS35 were expectably upregulated in OP group compared with controls (all p < 0.05). CONCLUSIONS: BRSK2 and VPS35 may be important diagnostic biomarkers of OP.

Genomic structure analysis and construction of DNA fingerprint for four sheep populations.

The Yongdeng Qishan sheep (QS) is a sheep population found locally in China. To gain in-depth knowledge of its population characteristics, three control groups were chosen, comprising the Lanzhou fat-tailed sheep (LFT), TAN sheep (TAN), and Minxian black fur sheep (MBF), inhabiting the nearby environments. This study genotyped a total of 120 individuals from four sheep populations: QS, LFT, TAN, and MBF. Using Specific-Locus Amplified Fragment Sequencing, we conducted genetic diversity, population structure, and selective sweep analysis, and constructed the fingerprint of each population. In total, there were 782 535 single nucleotide polymorphism (SNP) variations identified, with most being situated within regions that are intergenic or intronic. The genetic diversity analysis revealed that the QS population exhibited lower genetic diversity compared to the other three populations. Consistent results were obtained from the principal component, phylogenetic tree, and population structure analysis, indicating significant genetic differences between QS and the other three populations. However, a certain degree of differentiation was observed within the QS population. The linkage disequilibrium (LD) patterns among the four populations showed clear distinctions, with the QS group demonstrating the most rapid LD decline. Kinship analysis supported the findings of population structure, dividing the 90 QS individuals into two subgroups consisting of 23 and 67 individuals. Selective sweep analysis identified a range of genes associated with reproduction, immunity, and adaptation to high-altitude hypoxia. These genes hold potential as candidate genes for marker-assisted selection breeding. Additionally, a total of 86 523 runs of homozygosity (ROHs) were detected, showing non-uniform distribution across chromosomes, with chromosome 1 having the highest coverage percentage and chromosome 26 the lowest. In the high-frequency ROH islands, 79 candidate genes were associated with biological processes such as reproduction and fat digestion and absorption. Furthermore, a DNA fingerprint was constructed for the four populations using 349 highly polymorphic SNPs. In summary, our research delves into the genetic diversity and population structure of QS population. The construction of DNA fingerprint profiles for each population can provide valuable references for the identification of sheep breeds both domestically and internationally.

Effects of adding Allium mongolicum Regel powder and yeast cultures to diet on rumen microbial flora of Tibetan sheep (Ovis aries).

The purpose of this experiment was to study the effect of Allium mongolicum Regel powder (AMR) and yeast cultures (YC) on rumen microbial diversity in Tibetan sheep in different Ecological niches. A total of 40 male Tibetan lambs with an initial weight of 18.56 ± 1.49 kg (6 months old) were selected and divided into four groups (10 sheep/pen; n = 10). In the Control Group, each animal was grazed for 8 h per day, in Group I, each animal was supplemented with 200 g of concentrate per day, in Group II, each animal was supplemented with 200 g of concentrate and 10 g of AMR per day, in Group III, each animal was supplemented with 200 g of concentrate and 20 g of YC per day. The experiment lasted 82 days and consisted of a 7-day per-feeding period and a 75-day formal period. The results indicated that at the phylum level, the abundance of Bacteroidota and Verrucomimicrobiota in L-Group II and L-Group III was increased, while the abundance of Proteobacteria was decreased in the LA (Liquid-Associated) groups. The proportion of F/B in S-Group II and S-Group III was increased compared to S-Group I and S-CON in the SA (Soild-Associated) group. At the genus level, the abundance of uncultured_rumen_bacterium and Eubacterium_ruminantium_group in L-Group II and L-Group III was increased. Furthermore, while the abundance of Rikenellaceae_RC9_gut_group was decreased in the LA, the abundance of Prevotella and Eubacterium_ruminantium_group was increased in the S-Group II and S-Group III compared to S-Group I and S-CON. The abundance of probable_genus_10 was the highest in S-Group II in the SA group. After the addition of YC and AMR, there was an increase in rumen microbial abundance, which was found to be beneficial for the stability of rumen flora and had a positive impact on rumen health.

Deciphering the antidepressant effects of Rosa damascena essential oil mediated through the serotonergic synapse signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Rosa damascena is an ancient plant with significance in both medicine and perfumery that have a variety of therapeutic properties, including antidepressant, anti-anxiety, and anti-stress effects. Rose damascena essential oil (REO) has been used to treat depression, anxiety and other neurological related disorders in Iranian traditional medicine. However, its precise mechanism of action remains elusive. AIM OF THE STUDY: The aim of this study was to investigate the impact and mechanism underlying the influence of REO on chronic unpredictable mild stress (CUMS) rats. MATERIALS AND METHODS: Gas chromatography-mass spectrometry (GC-MS) technique coupling was used to analyze of the components of REO. A CUMS rat model was replicated to assess the antidepressant effects of varying doses of REO. This assessment encompassed behavioral evaluations, biochemical index measurements, and hematoxylin-eosin staining. For a comprehensive analysis of hippocampal tissues, we employed transcriptomics and incorporated weighting coefficients by means of network pharmacology. These measures allowed us to explore differentially expressed genes and biofunctional pathways affected by REO in the context of depression treatment. Furthermore, GC-MS metabolomics was employed to assess metabolic profiles, while a joint analysis in Metscape facilitated the construction of a network elucidating the links between differentially expressed genes and metabolites, thereby elucidating potential relationships and clarifying key pathways regulated by REO. Finally, the expression of relevant proteins in the key pathways was determined through immunohistochemistry and Western blot analysis. Molecular docking was utilized to investigate the interactions between active components and key targets, thereby validating the experimental results. RESULTS: REO alleviated depressive-like behavior, significantly elevated levels of the neurotransmitter 5-hydroxytryptamine (5-HT), and reduced hippocampal neuronal damage in CUMS rats. This therapeutic effect may be associated with the modulation of the serotonergic synapse signaling pathway. Furthermore, REO rectified metabolic disturbances, primarily through the regulation of amino acid metabolic pathways. Joint analysis revealed five differentially expressed genes (EEF1A1, LOC729197, ATP8A2, NDST4, and GAD2), suggesting their potential in alleviating depressive symptoms by modulating the serotonergic synapse signaling pathway and tryptophan metabolism. REO also modulated the 5-HT2A-mediated extracellular regulated protein kinases-cAMP-response element binding protein-brain-derived neurotrophic factor (ERK-CREB-BDNF) pathway. In addition, molecular docking results indicated that citronellol, geraniol and (E,E)-farnesol in REO may serve as key active ingredients responsible for its antidepressant effects. CONCLUSIONS: This study is the first to report that REO can effectively alleviate CUMS-induced depression-like effects in rats. Additionally, the study offers a comprehensive understanding of its intricate antidepressant mechanism from a multi-omics and multi-level perspective. Our findings hold promise for the clinical application and further development of this essential oil.

Predictive value of machine learning models for lymph node metastasis in gastric cancer: A two-center study.

BACKGROUND: Gastric cancer is one of the most common malignant tumors in the digestive system, ranking sixth in incidence and fourth in mortality worldwide. Since 42.5% of metastatic lymph nodes in gastric cancer belong to nodule type and peripheral type, the application of imaging diagnosis is restricted. AIM: To establish models for predicting the risk of lymph node metastasis in gastric cancer patients using machine learning (ML) algorithms and to evaluate their predictive performance in clinical practice. METHODS: Data of a total of 369 patients who underwent radical gastrectomy at the Department of General Surgery of Affiliated Hospital of Xuzhou Medical University (Xuzhou, China) from March 2016 to November 2019 were collected and retrospectively analyzed as the training group. In addition, data of 123 patients who underwent radical gastrectomy at the Department of General Surgery of Jining First People's Hospital (Jining, China) were collected and analyzed as the verification group. Seven ML models, including decision tree, random forest, support vector machine (SVM), gradient boosting machine, naive Bayes, neural network, and logistic regression, were developed to evaluate the occurrence of lymph node metastasis in patients with gastric cancer. The ML models were established following ten cross-validation iterations using the training dataset, and subsequently, each model was assessed using the test dataset. The models' performance was evaluated by comparing the area under the receiver operating characteristic curve of each model. RESULTS: Among the seven ML models, except for SVM, the other ones exhibited higher accuracy and reliability, and the influences of various risk factors on the models are intuitive. CONCLUSION: The ML models developed exhibit strong predictive capabilities for lymph node metastasis in gastric cancer, which can aid in personalized clinical diagnosis and treatment.

ATP homeostasis and signaling in plants.

ATP is the primary form of energy for plants, and a shortage of cellular ATP is generally acknowledged to pose a threat to plant growth and development, stress resistance, and crop quality. The overall metabolic processes that contribute to the ATP pool, from production, dissipation, and transport to elimination, have been studied extensively. Considerable evidence has revealed that in addition to its role in energy supply, ATP also acts as a regulatory signaling molecule to activate global metabolic responses. Identification of the eATP receptor DORN1 contributed to a better understanding of how plants cope with disruption of ATP homeostasis and of the key points at which ATP signaling pathways intersect in cells or whole organisms. The functions of SnRK1α, the master regulator of the energy management network, in restoring the equilibrium of the ATP pool have been demonstrated, and the vast and complex metabolic network mediated by SnRK1α to adapt to fluctuating environments has been characterized. This paper reviews recent advances in understanding the regulatory control of the cellular ATP pool and discusses possible interactions among key regulators of ATP-pool homeostasis and crosstalk between iATP/eATP signaling pathways. Perception of ATP deficit and modulation of cellular ATP homeostasis mediated by SnRK1α in plants are discussed at the physiological and molecular levels. Finally, we suggest future research directions for modulation of plant cellular ATP homeostasis.

Comparison of Machine Learning and Logic Regression Algorithms for Predicting Lymph Node Metastasis in Patients with Gastric Cancer: A two-Center Study.

OBJECTIVES: This two-center study aimed to establish a model for predicting the risk of lymph node metastasis in gastric cancer patients using machine learning (ML) and logistic regression (LR) algorithms, and to evaluate its predictive performance in clinical practice. METHODS: Data of a total of 369 patients who underwent radical gastrectomy in the Department of General Surgery of Affiliated Hospital of Xuzhou Medical University (Xuzhou, China) from March 2016 to November 2019 were collected and retrospectively analyzed as the training group. In addition, data of 123 patients who underwent radical gastrectomy in the Department of General Surgery of Jining First People's Hospital (Jining, China) were collected and analyzed as the verification group. Besides, 7 ML and logistic models were developed, including decision tree, random forest, support vector machine (SVM), gradient boosting machine (GBM), naive Bayes, neural network, and LR, in order to evaluate the occurrence of lymph node metastasis in patients with gastric cancer. The ML model was established following 10 cross-validation iterations within the training dataset, and subsequently, each model was assessed using the test dataset. The model's performance was evaluated by comparing the area under the receiver operating characteristic curve of each model. RESULTS: Compared with the traditional logistic model, among the 7 ML algorithms, except for SVM, the other models exhibited higher accuracy and reliability, and the influences of various risk factors on the model were more intuitive. CONCLUSION: For the prediction of lymph node metastasis in gastric cancer patients, the ML algorithm outperformed traditional LR, and the GBM algorithm exhibited the most robust predictive capability.

Basis with RNA-Seq and WGCNA to explore the effect of Frankincense essential oil on dextran sodium sulfate-induced ulcerative colitis through MAPK/NF-κB signaling.

PURPOSE: Frankincense has been shown in studies to have healing benefits for people with ulcerative colitis (UC). However, its underlying mechanisms have not been fully investigated. The objective of this study was to explore the potential molecular mechanisms of Frankincense essential oil (FREO) in improving dextran sodium sulfate (DSS)-induced UC from multiple perspectives. METHODS: The FREO components were analyzed by GC-MS, and the interactions between the key active components and the mechanism of FREO were determined based on RNA-seq, "quantity-effect" weighting coefficient network pharmacology, WGCNA and pharmacodynamic experiments. The protection of FREO against DSS-induced UC mice was assessed by behavioral and pathological changes through mice. The expression of pro-inflammatory cytokines was measured using enzyme-linked immunosorbent assay. The expression of MAPK and NF-κB-related proteins by the Western Blotting and immunohistochemistry method. RESULTS: Treatment with FREO significantly improved the symptoms of weight loss, diarrhea, stool blood, and colon shortening in UC mice. Reduced intestinal mucosal damage and the degree of inflammatory cell infiltration in the colon. Decreased TNF-α and IL-6 levels in mice's serum and inhibited phosphorylation of ERK, p65 in MAPK and NF-κB signaling. CONCLUSION: FREO may decrease the inflammatory response to reduce the symptoms of UC by modulating the MAPK/ NF-κB pathway. This may be due to the synergistic interaction of the effective ingredient Hepten-2-yl tiglate, 6-methyl-5-, Isoneocembrene A and P-Cymene. This study provides a promising drug candidate and a new concept for the treatment of UC.

Yeast culture repairs rumen epithelial injury by regulating microbial communities and metabolites in sheep.

This study delves into the impact of yeast culture (YC) on rumen epithelial development, microbiota, and metabolome, with the aim of investigating YC's mechanism in regulating rumen fermentation. Thirty male lambs of Hu sheep with similar age and body weight were selected and randomly divided into three groups with 10 lambs in each group. Lambs were fed a total mixed ration [TMR; rough: concentrate (R:C) ratio ≈ 30:70] to meet their nutritional needs. The experiment adopted completely randomized design (CRD). The control group (CON) was fed the basal diet with high concentrate, to which 20 g/d of YC was added in the low dose YC group (LYC) and 40 g/d of YC in the high dose YC group (HYC). The pretrial period was 14 days, and the experimental trial period was 60 days. At the end of a 60-day trial, ruminal epithelial tissues were collected for histomorphological analysis, and rumen microorganisms were analyzed by 16S rDNA sequencing and rumen metabolites by untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics techniques. The results showed that YC improved rumen papilla development and increased rumen papilla length (p < 0.05), while decreased cuticle thickness (p < 0.05). The 16S rDNA sequencing results showed that YC reduced the relative abundance of Prevotella_1 (p < 0.05), while significantly increased the relative abundance of Ruminococcaceae_UCG-005, uncultured_bacterium_f_Lachnospiraceae, and Ruminococcus_1 genus (p < 0.05). Metabolomics analysis showed that YC changed the abundance of metabolites related to amino acid metabolism, lipid metabolism and vitamin metabolism pathways in the rumen. In summary, YC might maintain rumen health under high-concentrate diet conditions by changing rumen microbiota structure and fermentation patterns, thereby affecting rumen metabolic profiles and repairing rumen epithelial injury.

Prickly Ash Seeds improve immunity of Hu sheep by changing the diversity and structure of gut microbiota.

Prickly Ash Seeds (PAS), as a traditional Chinese medicinal herb, have pharmacological effects such as anti-asthma, anti-thrombotic, and anti-bacterial, but their impact on gut microbiota is still unclear. This study used a full-length 16 s rRNA gene sequencing technique to determine the effect of adding PAS to the diet on the structure and distribution of gut microbiota in Hu sheep. All lambs were randomly divided into two groups, the CK group was fed with a basal ration, and the LZS group was given a basal diet with 3% of PAS added to the ration. The levels of inflammatory factors (IL-10, IL-1ß, and TNF-α) in intestinal tissues were measured by enzyme-linked immunosorbent assay (ELISA) for Hu sheep in the CK and LZS group. The results indicate that PAS can increase the diversity and richness of gut microbiota, and can affect the community composition of gut microbiota. LEfSe analysis revealed that Verrucomicrobiota, Kiritimatiella, WCHB 41, and uncultured_rumen_bacterium were significantly enriched in the LZS group. KEGG pathway analysis found that LZS was significantly higher than the CK group in the Excretory system, Folding, sorting and degradation, and Immune system pathways (p < 0.05). The results of ELISA assay showed that the level of IL-10 was significantly higher in the LZS group than in the CK group (p < 0.05), and the levels of TNF-α and IL-1ß were significantly higher in the CK group than in the LZS group (p < 0.05). LEfSe analysis revealed that the dominant flora in the large intestine segment changed from Bacteroidota and Gammaproteobacteria to Akkermansiaceae and Verrucomicrobiae after PAS addition to Hu sheep lambs; the dominant flora in the small intestine segment changed from Lactobacillales and Aeriscardovia to Kiritimatiellae and WCHB1 41. In conclusion, the addition of PAS to sheep diets can increase the number and types of beneficial bacteria in the intestinal tract, improve lamb immunity, and reduce intestinal inflammation. It provides new insights into healthy sheep production.

Whole Genome Resequencing Reveals Selection Signals Related to Wool Color in Sheep.

Wool color is controlled by a variety of genes. Although the gene regulation of some wool colors has been studied in relative depth, there may still be unknown genetic variants and control genes for some colors or different breeds of wool that need to be identified and recognized by whole genome resequencing. Therefore, we used whole genome resequencing data to compare and analyze sheep populations of different breeds by population differentiation index and nucleotide diversity ratios (Fst and θπ ratio) as well as extended haplotype purity between populations (XP-EHH) to reveal selection signals related to wool coloration in sheep. Screening in the non-white wool color group (G1 vs. G2) yielded 365 candidate genes, among which PDE4B, GMDS, GATA1, RCOR1, MAPK4, SLC36A1, and PPP3CA were associated with the formation of non-white wool; an enrichment analysis of the candidate genes yielded 21 significant GO terms and 49 significant KEGG pathways (p < 0.05), among which 17 GO terms and 21 KEGG pathways were associated with the formation of non-white wool. Screening in the white wool color group (G2 vs. G1) yielded 214 candidate genes, including ABCD4, VSX2, ITCH, NNT, POLA1, IGF1R, HOXA10, and DAO, which were associated with the formation of white wool; an enrichment analysis of the candidate genes revealed 9 significant GO-enriched pathways and 19 significant KEGG pathways (p < 0.05), including 5 GO terms and 12 KEGG pathways associated with the formation of white wool. In addition to furthering our understanding of wool color genetics, this research is important for breeding purposes.

The Importance of Expert Knowledge for Automatic Modulation Open Set Recognition.

Automatic modulation classification (AMC) is an important technology for the monitoring, management, and control of communication systems. In recent years, machine learning approaches are becoming popular to improve the effectiveness of AMC for radio signals. However, the automatic modulation open-set recognition (AMOSR) scheme that aims to identify the known modulation types and recognize the unknown modulation signals is not well studied. Therefore, in this paper, we propose a novel multi-modal marginal prototype framework for radio frequency (RF) signals (MMPRF) to improve AMOSR performance. First, MMPRF addresses the problem of simultaneous recognition of closed and open sets by partitioning the feature space in the way of one versus other and marginal restrictions. Second, we exploit the wireless signal domain knowledge to extract a series of signal-related features to enhance the AMOSR capability. In addition, we propose a GAN-based unknown sample generation strategy to allow the model to understand the unknown world. Finally, we conduct extensive experiments on several publicly available radio modulation data, and experimental results show that our proposed MMPRF outperforms the state-of-the-art AMOSR methods.

Whole-Genome Resequencing Reveals Selection Signal Related to Sheep Wool Fineness.

Wool fineness affects the quality of wool, and some studies have identified about forty candidate genes that affect sheep wool fineness, but these genes often reveal only a certain proportion of the variation in wool thickness. We further explore additional genes associated with the fineness of sheep wool. Whole-genome resequencing of eight sheep breeds was performed to reveal selection signals associated with wool fineness, including four coarse wool and four fine/semi-fine wool sheep breeds. Multiple methods to reveal selection signals (Fst and θπ Ratio and XP-EHH) were applied for sheep wool fineness traits. In total, 269 and 319 genes were annotated in the fine wool (F vs. C) group and the coarse wool (C vs. F) group, such as LGR4, PIK3CA, and SEMA3C and NFIB, OPHN1, and THADA. In F vs. C, 269 genes were enriched in 15 significant GO Terms (p < 0.05) and 38 significant KEGG Pathways (p < 0.05), such as protein localization to plasma membrane (GO: 0072659) and Inositol phosphate metabolism (oas 00562). In C vs. F, 319 genes were enriched in 21 GO Terms (p < 0.05) and 16 KEGG Pathways (p < 0.05), such as negative regulation of focal adhesion assembly (GO: 0051895) and Axon guidance (oas 04360). Our study has uncovered genomic information pertaining to significant traits in sheep and has identified valuable candidate genes. This will pave the way for subsequent investigations into related traits.