Multi-omics analysis on the mechanism of the effect of Isatis leaf on the growth performance of fattening sheep.

Introduction: This study evaluated the effects of Isatis Leaf (ISL) on the growth performance, gastrointestinal tissue morphology, rumen and intestinal microbiota, rumen, serum and urine metabolites, and rumen epithelial tissue transcriptome of fattening sheep. Methods: Twelve 3.5-month-old healthy fattening sheep were randomly divided into two groups, each with 6 replicates, and fed with basal diet (CON) and basal diet supplemented with 80 g/kg ISL for 2.5 months. Gastrointestinal tract was collected for histological analysis, rumen fluid and feces were subjected to metagenomic analysis, rumen fluid, serum, and urine for metabolomics analysis, and rumen epithelial tissue for transcriptomics analysis. Results: The results showed that in the ISL group, the average daily gain and average daily feed intake of fattening sheep were significantly lower than those of the CON group (P < 0.05), and the rumen ammonia nitrogen level was significantly higher than that of the CON group (P < 0.01). The thickness of the reticulum and abomasum muscle layer was significantly increased (P < 0.05). At the genus level, the addition of ISL modified the composition of rumen and fecal microorganisms, and the relative abundance of Methanobrevibacter and Centipeda was significantly upregulated in rumen microorganisms, The relative abundance of Butyrivibrio, Saccharofermentans, Mogibacterium, and Pirellula was significantly downregulated (P < 0.05). In fecal microorganisms, the relative abundance of Papillibacter, Pseudoflavonifractor, Butyricicoccus, Anaerovorax, and Methanocorpusculum was significantly upregulated, while the relative abundance of Roseburia, Coprococcus, Clostridium XVIII, Butyrivibrio, Parasutterella, Macellibacteroides, and Porphyromonas was significantly downregulated (P < 0.05). There were 164, 107, and 77 different metabolites in the rumen, serum, and urine between the ISL and CON groups (P < 0.05). The differential metabolic pathways mainly included thiamine metabolism, niacin and nicotinamide metabolism, vitamin B6 metabolism, taurine and taurine metabolism, beta-Alanine metabolism and riboflavin metabolism. These metabolic pathways were mainly involved in the regulation of energy metabolism and immune function in fattening sheep. Transcriptome sequencing showed that differentially expressed genes were mainly enriched in cellular physiological processes, development, and immune regulation. Conclusion: In summary, the addition of ISL to the diet had the effect of increasing rumen ammonia nitrogen levels, regulating gastrointestinal microbiota, promoting body fat metabolism, and enhancing immunity in fattening sheep.

Multi-Omics Analysis of the Mechanism of Mentha Haplocalyx Briq on the Growth and Metabolic Regulation of Fattening Sheep.

Mentha haplocalyx Briq (MHB) and its components have been proven to improve the growth performance of livestock and poultry. The aim of this experiment was to investigate the effects of MHB addition on growth performance, rumen and fecal microbiota, rumen fluid, serum and urine metabolism, and transcriptomics of rumen epithelial cells in meat sheep. Twelve Hu sheep were selected for the experiment and fed with basic diet (CON) and a basal diet supplemented with 80 g/kg DM of Mentha haplocalyx Briq (MHB). The experimental period was 10 weeks with the first 2 weeks as the pre-trial period. The results showed that compared with the CON group, the average daily weight gain of meat sheep in the MHB group increased by 20.1%; the total volatile fatty acid (VFA) concentration significantly increased (p < 0.05); The thickness of the cecal mucosal layer was significantly reduced (p < 0.01), while the thickness of the colonic mucosal layer was significantly increased (p < 0.05), the length of ileal villi significantly increased (p < 0.01), the thickness of colonic mucosal layer and rectal mucosal muscle layer significantly increased (p < 0.05), and the thickness of cecal mucosal layer significantly decreased (p < 0.05); The serum antioxidant capacity has increased. At the genus level, the addition of MHB changed the composition of rumen and fecal microbiota, increased the relative abundance of Paraprevotella, Alloprevotella, Marinilabilia, Saccharibacteria_genera_incertae_sedis, Subdivision5_genera_incertae_sedis and Ornatilinea in rumen microbiota, and decreased the relative abundance of Blautia (p < 0.05). The relative abundance of Prevotella, Clostridium XlVb and Parasutterella increased in fecal microbiota, while the relative abundance of Blautia and Coprococcus decreased (p < 0.05). There were significant differences in the concentrations of 105, 163, and 54 metabolites in the rumen, serum, and urine between the MHB group and the CON group (p < 0.05). The main metabolic pathways of the differences were pyrimidine metabolism, taurine and taurine metabolism, glyceride metabolism, and pentose phosphate pathway (p < 0.05), which had a significant impact on protein synthesis and energy metabolism. The transcriptome sequencing results showed that differentially expressed genes were mainly enriched in immune regulation, energy metabolism, and protein modification. Therefore, adding MHB improved the growth performance of lambs by altering rumen and intestinal microbiota, rumen, serum and urine metabolomics, and transcriptome.

Assessing base-resolution DNA mechanics on the genome scale.

Intrinsic DNA properties including bending play a crucial role in diverse biological systems. A recent advance in a high-throughput technology called loop-seq makes it possible to determine the bendability of hundred thousand 50-bp DNA duplexes in one experiment. However, it's still challenging to assess base-resolution sequence bendability in large genomes such as human, which requires thousands of such experiments. Here, we introduce 'BendNet'-a deep neural network to predict the intrinsic DNA bending at base-resolution by using loop-seq results in yeast as training data. BendNet can predict the DNA bendability of any given sequence from different species with high accuracy. To explore the utility of BendNet, we applied it to the human genome and observed DNA bendability is associated with chromatin features and disease risk regions involving transcription/enhancer regulation, DNA replication, transcription factor binding and extrachromosomal circular DNA generation. These findings expand our understanding on DNA mechanics and its association with transcription regulation in mammals. Lastly, we built a comprehensive resource of genomic DNA bendability profiles for 307 species by applying BendNet, and provided an online tool to assess the bendability of user-specified DNA sequences (http://www.dnabendnet.com/).

Diagnosis and Prediction of Endometrial Carcinoma Using Machine Learning and Artificial Neural Networks Based on Public Databases.

Endometrial carcinoma (EC), a common female reproductive system malignant tumor, affects thousands of people with high morbidity and mortality worldwide. This study was aimed at developing a prediction model for the diagnosis of EC in the general population. First, we obtained datasets GSE63678, GSE106191, and GSE115810 from the Gene Expression Omnibus (GEO) database, dataset GSE17025 from the GEO database, and the RNA sequence of EC from The Cancer Genome Atlas (TCGA) database to constitute the training, test, and validation groups, respectively. Subsequently, the 96 most significantly differentially expressed genes (DEGs) were identified and analyzed for function and pathway enrichment in the training group. Next, we acquired the disease-specific genes by random forest and established an artificial neural network for the diagnosis. Receiver operating characteristic (ROC) curves were utilized to identify the signature across the three groups. Finally, immune infiltration was analyzed to reveal tumor-immune microenvironment (TIME) alterations in EC. The top 96 DEGs (77 down-regulated and 19 up-regulated genes) were primarily enriched in the interleukin-17 signaling pathway, protein digestion and absorption, and transcriptional misregulation in cancer. Subsequently, 14 characterizing genes of EC were identified by random forest. In the training, test, and validation groups, the artificial neural network was constructed with high diagnostic accuracies of 0.882, 0.864, and 0.839, respectively, and areas under the ROC curve (AUCs) of 0.928, 0.921, and 0.782, respectively. Finally, resting and activated mast cells were found to have increased in TIME. We constructed an artificial diagnostic model with excellent reliability for EC and uncovered variations in the immunological ecosystem of EC through integrated bioinformatics approaches, which might be potential diagnostic targets for EC.

The Protein Kinase R Inhibitor C16 Alleviates Sepsis-Induced Acute Kidney Injury Through Modulation of the NF-κB and NLR Family Pyrin Domain-Containing 3 (NLPR3) Pyroptosis Signal Pathways.

BACKGROUND Protein kinase R (PKR) is implicated in the inflammatory response to bacterial infection while the role of PKR in sepsis-induced acute kidney injury (AKI) is largely unknown. This study aimed to investigate the effects of the specific PKR inhibitor C16 (C13H8N4OS) on lipopolysaccharide (LPS)-induced AKI, and its mechanisms of action. MATERIAL AND METHODS C57BL/6J mice were injected intraperitoneally with C16 or vehicle 1 h before the LPS challenge and then injected intraperitoneally with LPS or 0.9% saline. After the LPS challenge, histopathological damage, renal function, and levels of proinflammatory cytokines were assessed. All the related signaling pathways were analyzed. RESULTS C16 effectively inhibited LPS-induced renal elevation of proinflammatory cytokines and chemokines. C16 prevented NF-kappaB activation and suppressed the PKR/eIF2alpha signaling pathway in AKI after the LPS challenge. Furthermore, C16 significantly inhibited pyroptosis during AKI, as evidenced by decreased renal levels of apoptosis-associated speck-like protein; NACHT, LRR, NLR Family Pyrin Domain-Containing 3; caspase-1; interleukin (IL)-1ß; and IL-18. CONCLUSIONS Our findings suggest that inhibition by C16 ameliorated LPS-induced renal inflammation and injury, at least partly through modulation of the pyroptosis signal pathway in the kidney.

Clinical and genomic landscape of hepatocellular carcinoma subtypes with various proportions of nonleukocyte stromal cells.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignancies and inflicts high mortality worldwide. The effect of tumor microenvironment components on HCC oncogenesis remains unknown. In particular, the nonleukocyte portion of the stromal fraction (SF) is poorly understood. METHODS: We comprehensively evaluated the proportional cell counts and gene expression data from The Cancer Genome Atlas (TCGA) to examine the contributions of cell components to the tumor microenvironment. Single-cell sequencing data from the Gene Expression Omnibus (GEO) were also analyzed to verify the association between the nonleukocyte SF and genes. We classified HCC using a hierarchical clustering method based on diversity of nonleukocyte SF-related gene expression among different components, and we used an appropriate GEO dataset to verify the clusters with a support vector machine (SVM) model. The prognosis of subtypes and their relationship with tumor microenvironmental cell proportions, clinicopathogenesis factors, and other indicators were evaluated. RESULTS: Based on linear regression, 711 genes related to nonleukocyte SF were selected from the TCGA dataset. We classified HCC into three subtypes using genes related to the nonleukocyte SF. Additionally, the GEO single-cell sequencing data confirmed the relationship between genes and the nonleukocyte SF. The tumor microenvironment of Type 2 contained the most significant mutually reinforcing interaction between the nonleukocyte SF and tumor cells. Meanwhile, Type 2 patients had the poorest prognosis and the most severe tumor-node-metastasis (TNM) stages, histological grades, etc. The analysis based on the GEO dataset verified the classification results with an SVM model. Type 2 was associated with worse clinicopathological characteristics, including tumor grading and staging, than the other types. In addition, the pathway analysis revealed that signals related to the SF and cell proliferation were significantly enhanced in Type 2 compared to the other group, which consisted of Types 1 and 3. CONCLUSION: The nonleukocyte SF in the tumor microenvironment contributed greatly to HCC oncogenesis. We can use these HCC classification criteria to stratify patients into subtypes for personalized treatment.

Exploration of the effects of the CYCLOPS gene RBM17 in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most lethal and malignant tumours worldwide. New therapeutic targets for HCC are urgently needed. CYCLOPS (copy number alterations yielding cancer liabilities owing to partial loss) genes have been noted to be associated with cancer-targeted therapies. Therefore, we intended to explore the effects of the CYCLOPS gene RBM17 on HCC oncogenesis to determine if it could be further used for targeted therapy. METHODS: We collected data on 12 types of cancer from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) queries for comparison with adjacent non-tumour tissues. RBM17 expression levels, clinicopathological factors and survival times were analysed. RNAseq data were downloaded from the Encyclopaedia of DNA Elements database for molecular mechanism exploration. Two representative HCC cell models were built to observe the proliferation capacity of HCC cells when RBM17 expression was inhibited by shRBM17. Cell cycle progression and apoptosis were also examined to investigate the pathogenesis of RBM17. RESULTS: Based on 6,136 clinical samples, RBM17 was markedly overexpressed in most cancers, especially HCC. Moreover, data from 442 patients revealed that high RBM17 expression levels were related to a worse prognosis. Overexpression of RBM17 was related to the iCluster1 molecular subgroup, TNM stage, and histologic grade. Pathway analysis of RNAseq data suggested that RBM17 was involved in mitosis. Further investigation revealed that the proliferation rates of HepG2 (P = 0.003) and SMMC-7721 (P = 0.030) cells were significantly reduced when RBM17 was knocked down. In addition, RBM17 knockdown also arrested the progression of the cell cycle, causing cells to halt at the G2/M phase. Increased apoptosis rates were also found in vitro. CONCLUSION: These results suggest that RBM17 is a potential therapeutic target for HCC treatment.

Inhibition of brain-type glycogen phosphorylase ameliorates high glucose-induced cardiomyocyte apoptosis via Akt-HIF-1α activation.

Brain-type glycogen phosphorylase (pygb) is one of the rate-limiting enzymes in glycogenolysis that plays a crucial role in the pathogenesis of type 2 diabetes mellitus. Here we investigated the role of pygb in high-glucose (HG)-induced cardiomyocyte apoptosis and explored the underlying mechanisms, by using the specific pygb inhibitors or pygb siRNA. Our results show that inhibition of pygb significantly attenuates cell apoptosis and oxidative stress induced by HG in H9c2 cardiomyocytes. Inhibition of pygb improved glucose metabolism in cardiacmyocytes, as evidenced by increased glycogen content, glucose consumption, and glucose transport. Mechanistically, pygb inhibition activates the Akt-GSK-3ß signaling pathway and suppresses the activation of NF-κB in H9c2 cells exposed to HG. Additionally, pygb inhibition promotes the expression and the translocation of hypoxia-inducible factor-1α (HIF-1α) after HG stimulation. However, the changes in glucose metabolism and HIF-1α activation mediated by pygb inhibition are significantly reversed in the presence of the Akt inhibitor MK2206. In conclusion, this study found that inhibition of pygb prevents HG-induced cardiomyocyte apoptosis via activation of Akt-HIF-α.

Identification of key pathways and biomarkers in anaplastic thyroid cancer using an integrated analysis.

PURPOSE: Thyroid carcinoma (THCA) is one of the most common endocrine tumours with high morbidity worldwide. Anaplastic thyroid cancer (ATC) is the most fatal and has the poorest prognosis of the four THCA types, as it lacks effective treatments. Early screening of ATC is problematic and so identifying ATC biomarkers is increasingly crucial. METHODS: We performed a systematic search of the thyroid transcriptome in the Gene Expression Omnibus (GEO) database and an integrative analysis of gene expression profiles. Moreover, we conducted a pathway enrichment analysis in ATC using the WEB-based GEne SeT AnaLysis Toolkit. We identified the intersections of all the differentially expressed genes (DEGs) between ATC and normal samples and DEGs between ATC and non-ATC samples in the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Finally, we used Cytoscape software to visualize the protein-protein interaction (PPI) network. RESULTS: Six gene expression datasets containing 131 thyroid cancer samples and 98 normal control samples were collected to identify the significant DEGs. A total of 1489 DEGs were identified between ATC and normal samples, and 522 DEGs between ATC and non-ATC samples. ATC showed a greater association with the cell cycle. The Principal component analysis (PCA) results revealed 222 genes with substantial contributions to the identification of ATC. CONCLUSION: Cell cycle plays a decisive role in the high mortality rate of ATC. TOP2A, NUSAP1, PBK, KIF15, CENPF, CEP55, CDK1, CCNB2, CDCA8 and CDC20 were identified as hub genes.

Mechanism insight of pollutant degradation and bromate inhibition by Fe-Cu-MCM-41 catalyzed ozonation.

A flexible catalyst, Fe-Cu-MCM-41, was employed to enhance diclofenac (DCF) mineralization and inhibit bromate formation in catalytic ozonation process. Greater TOC removal was achieved in Fe-Cu-MCM-41/O3 process (78%) than those in Fe-MCM-41/O3 (65%), Cu-MCM-41/O3 (73%) and sole ozonation (42%). But it was interesting that both Cu-MCM-41/O3 and Fe-MCM-41/O3 achieved 93% bromate inhibition efficiency, only 71% inhibition efficiency was observed in Fe-Cu-MCM-41/O3. Influence of pH, TBA/NaHSO3 and detection of by-products were conducted to explore the mechanism. By Pyridine adsorption-IR and XPS, a relationship was found among activity of catalysts, Lewis acid sites and electron transfer effect between Fe (II/III) and Cu (I/II). Fe-Cu-MCM-41 promoted ozone decomposition to generate OH, which accounted for enhanced DCF mineralization. The consumption of aqueous O3 also suppressed the oxidative of Br- and HBrO/Br-. More HBrO/BrO- accumulated in catalytic ozonation process and less bromate generated. Bromate formation in Fe-Cu-MCM-41/O3 process was sensitive with pH value, the acidic condition was not favor for bromate formation. Both DCF mineralization and bromate inhibition were influenced by surface reaction. Moreover, Fe-Cu-MCM-41 showed excellent catalytic performance in suppressing the accumulation of carboxylic acid, especially for oxalic acid. Nearly no oxalic acid was detected during Fe-Cu-MCM-41/O3 process.

An improved algorithm of temperature compensation for a near infrared multiple-acquisition system based on two-dimensional regression analysis.

The near infrared (NIR) spectroscopy analytical technique is one of the most advanced and promising tools in many domains. NIR acquisition is easily influenced by temperature, thereby affecting qualitative and quantitative analyses. In this paper, a temperature compensation model was established between NIR signals and output voltage values based on two-dimensional regression analysis. The effectiveness of the proposed compensation scheme was experimentally demonstrated by the measurement of six super luminescent diode sources at 293-313 K. The coefficient of variation was decreased 2-fold with this compensation algorithm. The results indicated that it was suitable for various NIR spectral acquisition systems with lower complexity and a higher signal-noise-ratio after being applied to an acousto-optic-tunable-filter system.