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Specific intestinal metabolites are closely associated with the classification, severity, and necrosis of acute pancreatitis (AP) and provide novel insights for in-depth clinical investigations. In this study, the gut microbiota and metabolites of 49 AP patients at different treatment stages and severities were analysed via 16S rDNA sequencing and untargeted metabolomics to investigate the trends in gut microbiota composition and metabolome profiles observed in patients with severe AP. These findings revealed an imbalance in intestinal flora homeostasis among AP patients characterized by a decrease in probiotics and an increase in opportunistic pathogens, which leads to damage to the intestinal mucosal barrier through reduced short-chain fatty acid (SCFA) secretion and disruption of the intestinal epithelium. This dysbiosis influences energy metabolism, anti-inflammatory responses, and immune regulation, and these results highlight significant differences in energy metabolism pathways. These findings suggest that the differential composition of intestinal flora, along with alterations in intestinal metabolites and metabolic pathways, contribute to the compromised integrity of the intestinal mucosal barrier and disturbances in energy metabolism in patients with severe AP. [ABSTRACT FROM AUTHOR]

In many studies of human diseases, multiple omics datasets are measured. Typically, these omics datasets are studied one by one with the disease, thus the relationship between omics is overlooked. Modeling the joint part of multiple omics and its association to the outcome disease will provide insights into the complex molecular base of the disease. Several dimension reduction methods which jointly model multiple omics and two-stage approaches that model the omics and outcome in separate steps are available. Holistic one-stage models for both omics and outcome are lacking. In this article, we propose a novel one-stage method that jointly models an outcome variable with omics. We establish the model identifiability and develop EM algorithms to obtain maximum likelihood estimators of the parameters for normally and Bernoulli distributed outcomes. Test statistics are proposed to infer the association between the outcome and omics, and their asymptotic distributions are derived. Extensive simulation studies are conducted to evaluate the proposed model. The method is illustrated by modeling Down syndrome as outcome and methylation and glycomics as omics datasets. Here we show that our model provides more insight by jointly considering methylation and glycomics. [ABSTRACT FROM AUTHOR]

Aflatoxins belong to a class of mycotoxins, among which aflatoxin B1 (AFB1) has detrimental effects on the health of both animals and humans. It is associated with long-term exposure-induced carcinogenicity, hepatotoxicity, renal toxicity, neurotoxicity, and immunosuppressive properties, resulting in a variety of diseases. The intestine is the first barrier for human exposure to AFB1, but limited investigations have been conducted to clarify the underlying mechanisms of intestinal cytotoxicity. The mechanism of AFB1-induced cytotoxicity was investigated in this study using an integrated approach combining transcriptome, proteome, and metabolome analysis along with molecular dynamics simulation. After exposing SW480 cells to 50 μM AFB1 for 72 h, the transcriptome, proteome, and metabolome exhibited significant enrichment in pathways associated with oxidative stress, fatty acid and lipid metabolism, and glutathione metabolism. The experimental results demonstrated that AFB1 significantly reduces SW480 cells viability, and induces oxidative stress, calcium overload, mitochondrial damage, and lipid metabolism disorders. [ABSTRACT FROM AUTHOR]

Abstract Specific intestinal metabolites are closely associated with the classification, severity, and necrosis of acute pancreatitis (AP) and provide novel insights for in-depth clinical investigations. In this study, the gut microbiota and metabolites of 49 AP patients at different treatment stages and severities were analysed via 16S rDNA sequencing and untargeted metabolomics to investigate the trends in gut microbiota composition and metabolome profiles observed in patients with severe AP. These findings revealed an imbalance in intestinal flora homeostasis among AP patients characterized by a decrease in probiotics and an increase in opportunistic pathogens, which leads to damage to the intestinal mucosal barrier through reduced short-chain fatty acid (SCFA) secretion and disruption of the intestinal epithelium. This dysbiosis influences energy metabolism, anti-inflammatory responses, and immune regulation, and these results highlight significant differences in energy metabolism pathways. These findings suggest that the differential composition of intestinal flora, along with alterations in intestinal metabolites and metabolic pathways, contribute to the compromised integrity of the intestinal mucosal barrier and disturbances in energy metabolism in patients with severe AP.

Abstract Glycyl-tRNA synthetase (GARS1) is differentially expressed across cancers. In this study, the value of GARS1 in the diagnosis and prognosis of various cancers was comprehensively evaluated by multiple omics integrative pan-cancer analysis and experimental verification. Through Kaplan–Meier, ROC and multiple databases, we explored GARS1 expression and prognostic and diagnostic patterns across cancers. The GARS1 relative reaction network was identified in PPI, GO, KEGG, methylation models and the genetic mutation atlas. Further research on the GARS1 value in bladder urothelial carcinoma (BLCA) was conducted by regression and nomogram models. We further analyzed the correlation between GARS1 and immune markers and cells in BLCA. Finally, in vitro experiments were used to validate GARS1 the oncogenic function of GARS1 in BLCA. We found that GARS1 was highly expressed across cancers, especially in BLCA. GARS1 expression was correlated with poor survival and had high diagnostic value in most tumor types. GARS1 is significantly associated with tRNA-related pathways whose mutation sites are mainly located on tRNA synthetase. In addition, Upregulation of GARS1 was connected with immune cell infiltration and five key MMR genes. M2 macrophages, TAMs, Th1 and T-cell exhaustion, and marker sets associated with GARS1 expression indicated specific immune infiltration in BLCA. Finally, in vitro experiments validated that GARS1 expression promotes BLCA cell proliferation and metastasis and inhibits apoptosis. Overall, GARS1 can be a novel prognostic and immunological biomarker through multiple omics integrative pan-cancer analysis. The expression of GARS1 in BLCA was positively correlated with specific immune infiltration, indicating that GARS1 might be related to the tumor immune microenvironment.

Glycyl-tRNA synthetase (GARS1) is differentially expressed across cancers. In this study, the value of GARS1 in the diagnosis and prognosis of various cancers was comprehensively evaluated by multiple omics integrative pan-cancer analysis and experimental verification. Through Kaplan–Meier, ROC and multiple databases, we explored GARS1 expression and prognostic and diagnostic patterns across cancers. The GARS1 relative reaction network was identified in PPI, GO, KEGG, methylation models and the genetic mutation atlas. Further research on the GARS1 value in bladder urothelial carcinoma (BLCA) was conducted by regression and nomogram models. We further analyzed the correlation between GARS1 and immune markers and cells in BLCA. Finally, in vitro experiments were used to validate GARS1 the oncogenic function of GARS1 in BLCA. We found that GARS1 was highly expressed across cancers, especially in BLCA. GARS1 expression was correlated with poor survival and had high diagnostic value in most tumor types. GARS1 is significantly associated with tRNA-related pathways whose mutation sites are mainly located on tRNA synthetase. In addition, Upregulation of GARS1 was connected with immune cell infiltration and five key MMR genes. M2 macrophages, TAMs, Th1 and T-cell exhaustion, and marker sets associated with GARS1 expression indicated specific immune infiltration in BLCA. Finally, in vitro experiments validated that GARS1 expression promotes BLCA cell proliferation and metastasis and inhibits apoptosis. Overall, GARS1 can be a novel prognostic and immunological biomarker through multiple omics integrative pan-cancer analysis. The expression of GARS1 in BLCA was positively correlated with specific immune infiltration, indicating that GARS1 might be related to the tumor immune microenvironment. [ABSTRACT FROM AUTHOR]

Key message: Methylglyoxal and glyoxalase function a significant role in plant response to heavy metal stress. We update and discuss the most recent developments of methylglyoxal and glyoxalase in regulating plant response to heavy metal stress. Methylglyoxal (MG), a by-product of several metabolic processes, is created by both enzymatic and non-enzymatic mechanisms. It plays an important role in plant growth and development, signal transduction, and response to heavy metal stress (HMS). Changes in MG content and glyoxalase (GLY) activity under HMS imply that they may be potential biomarkers of plant stress resistance. In this review, we summarize recent advances in research on the mechanisms of MG and GLY in the regulation of plant responses to HMS. It has been discovered that appropriate concentrations of MG assist plants in maintaining a balance between growth and development and survival defense, therefore shielding them from heavy metal harm. MG and GLY regulate plant physiological processes by remodeling cellular redox homeostasis, regulating stomatal movement, and crosstalking with other signaling molecules (including abscisic acid, gibberellic acid, jasmonic acid, cytokinin, salicylic acid, melatonin, ethylene, hydrogen sulfide, and nitric oxide). We also discuss the involvement of MG and GLY in the regulation of plant responses to HMS at the transcriptional, translational, and metabolic levels. Lastly, considering the current state of research, we present a perspective on the future direction of MG research to elucidate the MG anti-stress mechanism and offer a theoretical foundation and useful advice for the remediation of heavy metal-contaminated environments in the future. [ABSTRACT FROM AUTHOR]

Aflatoxins belong to a class of mycotoxins, among which aflatoxin B1 (AFB1) has detrimental effects on the health of both animals and humans. It is associated with long-term exposure-induced carcinogenicity, hepatotoxicity, renal toxicity, neurotoxicity, and immunosuppressive properties, resulting in a variety of diseases. The intestine is the first barrier for human exposure to AFB1, but limited investigations have been conducted to clarify the underlying mechanisms of intestinal cytotoxicity. The mechanism of AFB1-induced cytotoxicity was investigated in this study using an integrated approach combining transcriptome, proteome, and metabolome analysis along with molecular dynamics simulation. After exposing SW480 cells to 50 μM AFB1 for 72 h, the transcriptome, proteome, and metabolome exhibited significant enrichment in pathways associated with oxidative stress, fatty acid and lipid metabolism, and glutathione metabolism. The experimental results demonstrated that AFB1 significantly reduces SW480 cells viability, and induces oxidative stress, calcium overload, mitochondrial damage, and lipid metabolism disorders.

In Chinese medicine, the primary considerations revolve around toxicity and effect. The clinical goal is to achieve maximize effect while minimizing toxicity. Nevertheless, both clinical and experimental research has revealed a distinct relationship between these two patterns of action in toxic Traditional Chinese Medicines (TCM). These TCM often exhibit characteristic "double-sided" or "multi-faceted" features under varying pathological conditions, transitioning between effective and toxic roles. This complexity adds a layer of challenge to unraveling the ultimate objectives of Traditional Chinese medicine. To address this complexity, various hypotheses have been proposed to explain the toxicity and effect of Traditional Chinese Medicines. These hypotheses encompass the magic shrapnel theory for effect, the adverse outcome pathway framework, and the indirect toxic theory for toxicity. This review primarily focuses on high-, medium-, and low-toxicity Traditional Chinese Medicines as listed in Chinese Pharmacopoeia. It aims to elucidate the essential intrinsic mechanisms and elements contributing to their toxicity and effectiveness. The critical factors influencing the mechanisms of toxicity and effect are the optimal dosage and duration of TCM administration. However, unraveling the toxic-effect relationships in TCM presents a formidable challenge due to its multi-target and multi-pathway mechanisms of action. We propose the integration of multi-omics technology to comprehensively analyze the fundamental metabolites, mechanisms of action, and toxic effects of TCM. This comprehensive approach can provide valuable insights into the intricate relationship between the effect and toxicity of these TCM. [ABSTRACT FROM AUTHOR]

Background: Colon cancer is a highly heterogeneous disease, and identifying molecular subtypes can provide insights into deregulated pathways within tumor subsets, which may lead to personalized treatment options. However, most prognostic models are based on single-pathway genes. Methods: In this study, we aimed to identify three clinically relevant subtypes of colon cancer based on multiple signaling pathways-related genes. Integrative multi-omics analysis was used to explain the biological processes contributing to colon cancer aggressiveness, recurrence, and progression. Machine learning methods were employed to identify the subtypes and provide medication guidance for distinct subtypes using the L1000 platform. We developed a robust prognostic model (MKPC score) based on gene pairs and validated it in one internal test set and three external test sets. Risk-related genes were extracted and verified by qPCR. Results: Three clinically relevant subtypes of colon cancer were identified based on multiple signaling pathways-related genes, which had significantly different survival state (Log-Rank test, p<0.05). Integrative multi-omics analysis revealed biological processes contributing to colon cancer aggressiveness, recurrence, and progression. The developed MKPC score, based on gene pairs, was robust in predicting prognosis state (Log-Rank test, p<0.05), and risk-related genes were successfully verified by qPCR (t test, p<0.05). An easy-to-use web tool was created for risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can be extended to other cancer types. Conclusion: In conclusion, our study identified three clinically relevant subtypes of colon cancer and developed a robust prognostic model based on gene pairs. The developed web tool is a valuable resource for researchers and clinicians in risk scoring and therapy stratification in colon cancer patients, and the practical nomogram can be extended to other cancer types. [ABSTRACT FROM AUTHOR]

Increased antibiotic resistance poses a major limitation in tackling inflammatory bowel disease and presents a large challenge for global health care. Antimicrobial peptides (AMPs) are a potential class of antimicrobial agents. Here, we have designed the potential oral route for antimicrobial peptide R7I with anti‐proteolytic properties to deal with bacterial enteritis in mice. The results revealed that R7I protected the liver and gut from damage caused by inflammation. RNA‐Seq analysis indicated that R7I promoted digestion and absorption in the small intestine by upregulating transmembrane transporter activity, lipid and small molecule metabolic processes and other pathways, in addition to upregulating hepatic steroid biosynthesis and fatty acid degradation. For the gut microbiota, Clostridia were significantly reduced in the R7I‐treated group, and Odoribacteraceae, an efficient isoalloLCA‐synthesizing strain, was the main dominant strain, protecting the gut from potential pathogens. In addition, we further discovered that R7I reduced the accumulation of negative organic acid metabolites. Overall, R7I exerted better therapeutic and immunomodulatory potential in the bacterial enteritis model, greatly reduced the risk of disease onset, and provided a reference for the in vivo application of antimicrobial peptides. [ABSTRACT FROM AUTHOR]

Abstract Background Cancer metastasis and recurrence remain major challenges in renal carcinoma patient management. There are limited biomarkers to predict the metastatic probability of renal cancer, especially in the early‐stage subgroup. Here, our study applied robust machine‐learning algorithms to identify metastatic and recurrence‐related signatures across multiple renal cancer cohorts, which reached high accuracy in both training and testing cohorts. Methods Clear cell renal cell carcinoma (ccRCC) patients with primary or metastatic site sequencing information from eight cohorts, including one out‐house cohort, were enrolled in this study. Three robust machine‐learning algorithms were applied to identify metastatic signatures. Then, two distinct metastatic‐related subtypes were identified and verified; matrix remodeling associated 5 (MXRA5), as a promising diagnostic and therapeutic target, was investigated in vivo and in vitro. Results We identified five stable metastasis‐related signatures (renin, integrin subunit beta‐like 1, MXRA5, mesenchyme homeobox 2, and anoctamin 3) from multicenter cohorts. Additionally, we verified the specificity and sensibility of these signatures in external and out‐house cohorts, which displayed a satisfactory consistency. According to these metastatic signatures, patients were grouped into two distinct and heterogeneous ccRCC subtypes named metastatic cancer subtype 1 (MTCS1) and type 2 (MTCS2). MTCS2 exhibited poorer clinical outcomes and metastatic tendencies than MTCS1. In addition, MTCS2 showed higher immune cell infiltration and immune signature expression but a lower response rate to immune blockade therapy than MTCS1. The MTCS2 subgroup was more sensitive to saracatinib, sunitinib, and several molecular targeted drugs. In addition, MTCS2 displayed a higher genome mutation burden and instability. Furthermore, we constructed a prognosis model based on subtype biomarkers, which performed well in training and validation cohorts. Finally, MXRA5, as a promising biomarker, significantly suppressed malignant ability, including the cell migration and proliferation of ccRCC cell lines in vitro and in vivo. Conclusions This study identified five robust metastatic signatures and proposed two metastatic probability clusters with stratified prognoses, multiomics landscapes, and treatment options. The current work not only provided new insight into the heterogeneity of renal cancer but also shed light on optimizing decision‐making in immunotherapy and chemotherapy.

Abstract Increased antibiotic resistance poses a major limitation in tackling inflammatory bowel disease and presents a large challenge for global health care. Antimicrobial peptides (AMPs) are a potential class of antimicrobial agents. Here, we have designed the potential oral route for antimicrobial peptide R7I with anti‐proteolytic properties to deal with bacterial enteritis in mice. The results revealed that R7I protected the liver and gut from damage caused by inflammation. RNA‐Seq analysis indicated that R7I promoted digestion and absorption in the small intestine by upregulating transmembrane transporter activity, lipid and small molecule metabolic processes and other pathways, in addition to upregulating hepatic steroid biosynthesis and fatty acid degradation. For the gut microbiota, Clostridia were significantly reduced in the R7I‐treated group, and Odoribacteraceae, an efficient isoalloLCA‐synthesizing strain, was the main dominant strain, protecting the gut from potential pathogens. In addition, we further discovered that R7I reduced the accumulation of negative organic acid metabolites. Overall, R7I exerted better therapeutic and immunomodulatory potential in the bacterial enteritis model, greatly reduced the risk of disease onset, and provided a reference for the in vivo application of antimicrobial peptides.

Rac Family Small GTPase 3 (Rac3) is a member of the Rho family of small GTP-binding proteins which play critical roles in the occurrence, progression, and metastasis of various tumors. Nevertheless, previous studies have focused on a single type of human cancer, so that the roles of Rac3 in different cancer types have not been sufficiently clarified. With the progress of biological detection and bioinformatics technology, the emerging cancer genomics databases make it possible to perform a pan-cancer analysis. Therefore, for the first time, we performed multiple omics analysis to investigate the roles of Rac3 in differential expression, survival prognosis, mutative status, DNA methylation, functions, immune infiltration, and immunotherapy across 33 human cancer types. We found that Rac3 expression was abnormal in 17 cancer types and significantly different in both molecular and immune subtypes of 10 cancers (p0.5) than three standardized biomarkers of tumor immune responses and was associated with cytotoxic T-cell levels (CTLs) and the risk of immunotherapeutic responses in three cancer types. Collectively, our study contributes to a comprehensive and integrative understanding of the oncogenic roles of Rac3 across human cancers and offers a new clue for treatment strategies.

In biology, molecular terms with the suffix "-omics" refer to disciplines aiming at the collective characterization of pools of molecules derived from different layers (DNA, RNA, proteins, metabolites) of living organisms using high-throughput technologies. Such omics analyses have been widely implemented in poultry research in recent years. This first part of a bipartite review on omics technologies in poultry health and productivity examines the use of multiple omics and multi-omics techniques in poultry research. More specific present and future applications of omics technologies, not only for the identification of specific diagnostic biomarkers, but also for potential future integration in the daily monitoring of poultry production, are discussed in part 2. Approaches based on omics technologies are particularly used in poultry research in the hunt for genetic markers of economically important phenotypical traits in the host, and in the identification of key bacterial species or functions in the intestinal microbiome. Integrative multi-omics analyses, however, are still scarce. Host physiology is investigated via genomics together with transcriptomics, proteomics and metabolomics techniques, to understand more accurately complex production traits such as disease resistance and fertility. The gut microbiota, as a key player in chicken productivity and health, is also a main subject of such studies, investigating the association between its composition (16S rRNA gene sequencing) or function (metagenomics, metatranscriptomics, metaproteomics, metabolomics) and host phenotypes. Applications of these technologies in the study of other host-associated microbiota and other host characteristics are still in their infancy. [ABSTRACT FROM AUTHOR]

Glycolipid metabolic disorder is a serious threat to human health. Dark tea is a kind of traditional Chinese tea, which may regulate the glycolipid metabolic disorders. Dark tea extract (DTE) is the water extraction obtained from dark tea. Compared with traditional dark tea, DTE has the benefits of convenient consumption and greater potential for promoting health. However, the regulation of DTE on glycolipid metabolism and its molecular mechanism is rarely investigated. In our study, DTE was used as raw material to study the effect and molecular mechanism of its intervention on the glycolipid metabolic in db/db diabetic mice by using multiomics analysis and modern biological techniques. (1) DTE could significantly reduce fasting glucose in diabetic db/db mice, and the higher dose group has a better effect. Histopathological examination showed that DTE slightly improve the number of islets and decrease the number of islet β cells in the pancreatic tissue in db/db mice. (2) RNA-Seq was used to analyze the gene expression in liver tissue. In terms of biological processes, DTE mainly affected the inflammation and fatty acid metabolism. In terms of cell components, the lipoprotein and respiratory chain are mainly affected. In the aspect of molecular function, DTE mainly affected the redox related enzyme activity, iron ion binding and glutathione transferase. Arachidonic acid metabolism pathway, glutathione metabolism and PPAR signaling pathway were enriched by DTE with the results of KEGG pathway enrichment. In addition, real-time PCR results confirmed that DTE could significantly activate key genes of PPAR signaling pathway like Fabp1, Cyp4a1, Ehhadh, Cyp4a32, Aqp7 and Me1. (3) 16s rDNA showed that DTE could significantly decrease the ratio of Firmicutes/Bacteroidetes and the abundance of Proteobacteria, and increased the relative abundance of Verrucomicrobia at the phylum level. At the genus level, the relative abundance of Akkermansia, Prevotellaceae, Bacteroides and Alloprevotella was significantly increased after DTE treatment. This study provides multiomics molecular evidence for the intervention effect of DTE on abnormal glucose and lipid metabolism and the application of precise nutritional diet intervention of dark tea extract.

A high-carbohydrate diet lowers the rearing cost and decreases the ammonia emission into the environment, whereas it can induce liver injury, which can reduce harvest yields and generate economic losses in reared fish species. Macroalgae Saccharina japonica (SJ) has been reported to improve anti-diabetic, but the protective mechanism of dietary SJ against liver injury in fish fed a high-carbohydrate diet has not been studied. Therefore, a 56-day nutritional trial was designed for swamp eel Monopterus albus, which was fed with the normal diet [20% carbohydrate, normal carbohydrate (NC)], a high carbohydrate diet (32% carbohydrate, HC), and a HC diet supplemented with 2.5% SJ (HC-S). The HC diet promoted growth and lowered feed coefficient (FC), whereas it increased hepatosomatic index (HSI) when compared with the NC diet in this study. However, SJ supplementation increased iodine contents in muscle, reduced HSI, and improved liver injury, such as the decrease of glucose (GLU), total bile acid (TBA), and alanine aminotransferase (ALT) in serum, and glycogen and TBA in the liver. Consistently, histological analysis showed that SJ reduced the area of lipid droplet, glycogen, and collagen fiber in the liver (p < 0.05). Thoroughly, the underlying protective mechanisms of SJ supplementation against HC-induced liver injury were studied by liver transcriptome sequencing coupled with pathway analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the differentially expressed genes (DEGs), such as the acetyl-coenzyme A synthetase (acss1), alcohol dehydrogenase (adh), interferon-induced protein with tetratricopeptide repeats 1 (ifit1), aldo-keto reductase family 1 member D1 (akr1d1), cholesterol 7-alpha-monooxygenase (cyp7a1), and UDP-glucuronosyltransferase (ugt), indicated that the pathway of glycolysis/gluconeogenesis was the main metabolic pathway altered in the HC group compared with the NC group. Meanwhile, hepatitis C, primary BA biosynthesis, and drug metabolism-cytochrome P450 were the three main metabolic pathways altered by SJ supplementation when compared with the HC group. Moreover, the BA-targeted metabolomic analysis of the serum BA found that SJ supplementation decreased the contents of taurohyocholic acid (THCA), taurochenodeoxycholic acid (TCDCA), taurolithocholic acid (TLCA), nordeoxycholic acid (NorDCA), and increased the contents of ursocholic acid (UCA), allocholic acid (ACA), and chenodeoxycholic acid (CDCA). In particular, the higher contents of UCA, ACA, and CDCA regulated by SJ were associated with lower liver injury. Overall, these results indicate that the 2.5% supplementation of SJ can be recommended as a functional feed additive for the alleviation of liver injury in swamp eel-fed high-carbohydrate diets.

Thyroid eye disease (TED) has brought great physical and mental trauma to patients worldwide. Although a few potential signaling pathways have been reported, knowledge of TED remains limited. Our objective is to explore the fundamental mechanism of TED and identify potential therapeutic targets using diverse approaches. To perform a range of bioinformatic analyses, such as identifying differentially expressed genes (DEGs), conducting enrichment analysis, establishing nomograms, analyzing weighted gene correlation network analysis (WGCNA), and studying immune infiltration, the datasets GSE58331, GSE105149, and GSE9340 were integrated. Further validation was conducted using qPCR, western blot, and immunohistochemistry techniques. Eleven ferroptosis-related DEGs derived from the lacrimal gland were originally screened. Their high diagnostic value was proven, and diagnostic prediction nomogram models with high accuracy and robustness were established by using machine learning. A total of 15 hub gene-related DEGs were identified by WGCNA. Through CIBERSORTx, we uncovered five immune cells highly correlated with TED and found several special associations between these immune cells and the above DEGs. Furthermore, EGR2 from the thyroid sample was revealed to be closely negatively correlated with most DEGs from the lacrimal gland. High expression of APOD, COPB2, MYH11, and MYCN, as well as CD4/CD8 T cells and B cells, was verified in the periorbital adipose tissues of TED patients. To summarize, we discovered a new gene signature associated with ferroptosis that has a critical impact on the development of TED and provides valuable insights into immune infiltration. These findings might highlight the new direction and therapeutic strategies of TED.

Prostate cancer (PC) is the most common non-cutaneous malignancy among men in the western world. However, heterogeneity remains a pressing clinical problem. The least absolute shrinkage and selection operator (LASSO) was used to screen the prognostic signature. Weighted correlation network analysis (WGCNA) was used to identify the target genes associated with high-risk characteristics. Gene set enrichment analysis was used to suggest the molecular mechanism of MYBL2 in PC. In addition, in vitro experiments were carried out to validate the role of MYBL2 in PC. Ten DNA methylation sites were selected as the prognostic signature. A high expression of MYBL2 was associated with a poor prognosis in PC patients. The effect of MYBL2 in PC was related to KRAS, AKT, IL21, and ATM. MYBL2 facilitates the proliferation, migration, invasion, and metastasis of PC cells. We developed a DNA methylation 10-CpG prognostic signature to predict the prognosis of PC patients. And the high expression of MYBL2 in PC may be related to poor prognosis. [ABSTRACT FROM AUTHOR]

Summary: Meat quality improvement is of great interest to researchers in pig breeding and many researchers have identified abundant associated quantitative trait loci, genes and polymorphisms (QTXs) for fat‐related traits. However, it is challenging to determine credible candidate genes from a mass of associations. The efficiency of identification of credible candidate genes in these QTXs is restricted by limited integration analyses of data from multiple omics. In this study, we constructed a 'candidate gene map' of fat‐related traits in pigs based on published literature and the latest genome. In total, 6,861 QTXs, which covered 9,323 genes on the pig genome, were used. Combining the QTX hotspots and pathway analysis, we identified 180 candidate genes that may regulate the fat‐related traits, and choose PNPLA2, PPARG, SREBF1, ACACA, PPARD and PPARA as credible candidate genes. In addition, we discussed the importance of incorporating transcriptome data and genomic data in causal gene identification, and the multi‐omics information can effectively improve the credibility of identified candidate genes. [ABSTRACT FROM AUTHOR]

Abstract To assess the impacts of man-made extremely low-frequency electromagnetic field (ELF-EMF) on soil ecosystems, the soil nematode was applied as a biological indicator to characterize ecotoxicity of ELF-EMF. In this paper, a soil-living model organism, Caenorhabditis elegans (C. elegans) was exposed to 50 Hz, 3 mT ELF-EMF. The integrated lipidome, proteome and transcriptome analysis were applied to elucidate physiological acclimations. Lipidomic analysis showed that ELF-EMF exposure induced significant alterations of 64 lipids, including significant elevation of triacylglycerols (TGs). Proteome results implied 157 changed protein expressions under ELF-EMF exposure. By transcriptomic analysis, 456 differently expressed genes were identified. Gene Ontology (GO) function and pathway analyses showed lipidomic alteration, mitochondrial dysfunction and the stress defense responses following ELF-EMF exposure in C. elegans. Conjoint analysis of proteome and transcriptome data showed that a higher expression of genes (sip-1 , mtl-1 and rpl-11.1 , etc.) were involved in stress defense responses to ELF-EMF exposure. These results indicated that ELF-EMF can induce effects on soil nematodes, mainly through disturbing lipid metabolism such as increasing TGs content, and eliciting stress defense responses. This study provided a new understanding in ELF-EMF exposure effects on soil nematodes and suggested a potential way of interpreting ELF-EMF influences on soil ecosystems. Highlights • Applied multi-omics methods to study the effects of ELF-EMF on C. elegans. • Lipid metabolic and stress-defense responses were induced by ELF-EMF exposure. • Soil nematod es were applied as a biological indicator. • Provided a potential way to assess ELF-EMF influences on soil ecosystems. [ABSTRACT FROM AUTHOR]

In Chinese medicine, the primary considerations revolve around toxicity and effect. The clinical goal is to achieve maximize effect while minimizing toxicity. Nevertheless, both clinical and experimental research has revealed a distinct relationship between these two patterns of action in toxic Traditional Chinese Medicines (TCM). These TCM often exhibit characteristic "double-sided" or "multi-faceted" features under varying pathological conditions, transitioning between effective and toxic roles. This complexity adds a layer of challenge to unraveling the ultimate objectives of Traditional Chinese medicine. To address this complexity, various hypotheses have been proposed to explain the toxicity and effect of Traditional Chinese Medicines. These hypotheses encompass the magic shrapnel theory for effect, the adverse outcome pathway framework, and the indirect toxic theory for toxicity. This review primarily focuses on high-, medium-, and low-toxicity Traditional Chinese Medicines as listed in Chinese Pharmacopoeia. It aims to elucidate the essential intrinsic mechanisms and elements contributing to their toxicity and effectiveness. The critical factors influencing the mechanisms of toxicity and effect are the optimal dosage and duration of TCM administration. However, unraveling the toxic-effect relationships in TCM presents a formidable challenge due to its multi-target and multi-pathway mechanisms of action. We propose the integration of multi-omics technology to comprehensively analyze the fundamental metabolites, mechanisms of action, and toxic effects of TCM. This comprehensive approach can provide valuable insights into the intricate relationship between the effect and toxicity of these TCM., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Deng, Xiong, Hu, Chen, Zhang, Ma and Zhao.)

Increased antibiotic resistance poses a major limitation in tackling inflammatory bowel disease and presents a large challenge for global health care. Antimicrobial peptides (AMPs) are a potential class of antimicrobial agents. Here, we have designed the potential oral route for antimicrobial peptide R7I with anti-proteolytic properties to deal with bacterial enteritis in mice. The results revealed that R7I protected the liver and gut from damage caused by inflammation. RNA-Seq analysis indicated that R7I promoted digestion and absorption in the small intestine by upregulating transmembrane transporter activity, lipid and small molecule metabolic processes and other pathways, in addition to upregulating hepatic steroid biosynthesis and fatty acid degradation. For the gut microbiota, Clostridia were significantly reduced in the R7I-treated group, and Odoribacteraceae , an efficient isoalloLCA-synthesizing strain, was the main dominant strain, protecting the gut from potential pathogens. In addition, we further discovered that R7I reduced the accumulation of negative organic acid metabolites. Overall, R7I exerted better therapeutic and immunomodulatory potential in the bacterial enteritis model, greatly reduced the risk of disease onset, and provided a reference for the in vivo application of antimicrobial peptides., Competing Interests: The authors declare no competing interests., (© 2022 The Authors. Bioengineering & Translational Medicine published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers.)

Glycolipid metabolic disorder is a serious threat to human health. Dark tea is a kind of traditional Chinese tea, which may regulate the glycolipid metabolic disorders. Dark tea extract (DTE) is the water extraction obtained from dark tea. Compared with traditional dark tea, DTE has the benefits of convenient consumption and greater potential for promoting health. However, the regulation of DTE on glycolipid metabolism and its molecular mechanism is rarely investigated. In our study, DTE was used as raw material to study the effect and molecular mechanism of its intervention on the glycolipid metabolic in db/db diabetic mice by using multiomics analysis and modern biological techniques. (1) DTE could significantly reduce fasting glucose in diabetic db/db mice, and the higher dose group has a better effect. Histopathological examination showed that DTE slightly improve the number of islets and decrease the number of islet β cells in the pancreatic tissue in db/db mice. (2) RNA-Seq was used to analyze the gene expression in liver tissue. In terms of biological processes, DTE mainly affected the inflammation and fatty acid metabolism. In terms of cell components, the lipoprotein and respiratory chain are mainly affected. In the aspect of molecular function, DTE mainly affected the redox related enzyme activity, iron ion binding and glutathione transferase. Arachidonic acid metabolism pathway, glutathione metabolism and PPAR signaling pathway were enriched by DTE with the results of KEGG pathway enrichment. In addition, real-time PCR results confirmed that DTE could significantly activate key genes of PPAR signaling pathway like Fabp1, Cyp4a1, Ehhadh, Cyp4a32, Aqp7 and Me1 . (3) 16s rDNA showed that DTE could significantly decrease the ratio of Firmicutes/Bacteroidetes and the abundance of Proteobacteria , and increased the relative abundance of Verrucomicrobia at the phylum level. At the genus level, the relative abundance of Akkermansia, Prevotellaceae, Bacteroides and Alloprevotella was significantly increased after DTE treatment. This study provides multiomics molecular evidence for the intervention effect of DTE on abnormal glucose and lipid metabolism and the application of precise nutritional diet intervention of dark tea extract., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wang, Hu, Yi, Wen, Lv, Shi and Zeng.)

Background: Cancer metastasis and recurrence remain major challenges in renal carcinoma patient management. There are limited biomarkers to predict the metastatic probability of renal cancer, especially in the early-stage subgroup. Here, our study applied robust machine-learning algorithms to identify metastatic and recurrence-related signatures across multiple renal cancer cohorts, which reached high accuracy in both training and testing cohorts., Methods: Clear cell renal cell carcinoma (ccRCC) patients with primary or metastatic site sequencing information from eight cohorts, including one out-house cohort, were enrolled in this study. Three robust machine-learning algorithms were applied to identify metastatic signatures. Then, two distinct metastatic-related subtypes were identified and verified; matrix remodeling associated 5 (MXRA5), as a promising diagnostic and therapeutic target, was investigated in vivo and in vitro., Results: We identified five stable metastasis-related signatures (renin, integrin subunit beta-like 1, MXRA5, mesenchyme homeobox 2, and anoctamin 3) from multicenter cohorts. Additionally, we verified the specificity and sensibility of these signatures in external and out-house cohorts, which displayed a satisfactory consistency. According to these metastatic signatures, patients were grouped into two distinct and heterogeneous ccRCC subtypes named metastatic cancer subtype 1 (MTCS1) and type 2 (MTCS2). MTCS2 exhibited poorer clinical outcomes and metastatic tendencies than MTCS1. In addition, MTCS2 showed higher immune cell infiltration and immune signature expression but a lower response rate to immune blockade therapy than MTCS1. The MTCS2 subgroup was more sensitive to saracatinib, sunitinib, and several molecular targeted drugs. In addition, MTCS2 displayed a higher genome mutation burden and instability. Furthermore, we constructed a prognosis model based on subtype biomarkers, which performed well in training and validation cohorts. Finally, MXRA5, as a promising biomarker, significantly suppressed malignant ability, including the cell migration and proliferation of ccRCC cell lines in vitro and in vivo., Conclusions: This study identified five robust metastatic signatures and proposed two metastatic probability clusters with stratified prognoses, multiomics landscapes, and treatment options. The current work not only provided new insight into the heterogeneity of renal cancer but also shed light on optimizing decision-making in immunotherapy and chemotherapy., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. Cancer Innovation published by John Wiley & Sons Ltd on behalf of Tsinghua University Press.)

A high-carbohydrate diet lowers the rearing cost and decreases the ammonia emission into the environment, whereas it can induce liver injury, which can reduce harvest yields and generate economic losses in reared fish species. Macroalgae Saccharina japonica (SJ) has been reported to improve anti-diabetic, but the protective mechanism of dietary SJ against liver injury in fish fed a high-carbohydrate diet has not been studied. Therefore, a 56-day nutritional trial was designed for swamp eel Monopterus albus , which was fed with the normal diet [20% carbohydrate, normal carbohydrate (NC)], a high carbohydrate diet (32% carbohydrate, HC), and a HC diet supplemented with 2.5% SJ (HC-S). The HC diet promoted growth and lowered feed coefficient (FC), whereas it increased hepatosomatic index (HSI) when compared with the NC diet in this study. However, SJ supplementation increased iodine contents in muscle, reduced HSI, and improved liver injury, such as the decrease of glucose (GLU), total bile acid (TBA), and alanine aminotransferase (ALT) in serum, and glycogen and TBA in the liver. Consistently, histological analysis showed that SJ reduced the area of lipid droplet, glycogen, and collagen fiber in the liver ( p < 0.05). Thoroughly, the underlying protective mechanisms of SJ supplementation against HC-induced liver injury were studied by liver transcriptome sequencing coupled with pathway analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the differentially expressed genes (DEGs), such as the acetyl-coenzyme A synthetase (acss1) , alcohol dehydrogenase ( adh) , interferon-induced protein with tetratricopeptide repeats 1 ( ifit1) , aldo-keto reductase family 1 member D1 ( akr1d1 ), cholesterol 7-alpha-monooxygenase (cyp7a1) , and UDP-glucuronosyltransferase (ugt) , indicated that the pathway of glycolysis/gluconeogenesis was the main metabolic pathway altered in the HC group compared with the NC group. Meanwhile, hepatitis C, primary BA biosynthesis, and drug metabolism-cytochrome P450 were the three main metabolic pathways altered by SJ supplementation when compared with the HC group. Moreover, the BA-targeted metabolomic analysis of the serum BA found that SJ supplementation decreased the contents of taurohyocholic acid (THCA), taurochenodeoxycholic acid (TCDCA), taurolithocholic acid (TLCA), nordeoxycholic acid (NorDCA), and increased the contents of ursocholic acid (UCA), allocholic acid (ACA), and chenodeoxycholic acid (CDCA). In particular, the higher contents of UCA, ACA, and CDCA regulated by SJ were associated with lower liver injury. Overall, these results indicate that the 2.5% supplementation of SJ can be recommended as a functional feed additive for the alleviation of liver injury in swamp eel-fed high-carbohydrate diets., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yu, Wang, Cai, Zhang, Hu, Wang, Yang, Peng, Huo, Zhang and Zhou.)

Hepatic lipid accumulation (HLA) is a major risk factor for the development of liver diseases in cultured fish species, which can lead to severe health problems and decrease harvest yields, thus result in economic losses. Macroalgae Saccharina japonica (SJ) has been reported to reduce HLA in mammals, but effects and underlying mechanism of dietary SJ on HLA in fish remain elusive. This study aimed to investigate the effect of dietary SJ on HLA of black seabream (A. schlegelii), an important marine economic fish. Juvenile black seabream (2.78 ± 0.16 g) was fed diets with three levels of SJ (0, 2.5 and 10%) for 90 days, and then blood and liver tissues were extracted for biochemical, histological and multiple-omic analyses. This study demonstrated that dietary supplementation of 2.5% and 10% SJ improved HLA-related parameters, including reducing serum lipid content and the activity of aminotransferase. Meanwhile, histological analysis showed that dietary SJ reduced lipid vacuoles in hepatocytes. The transcriptomic analysis of differentially expressed genes (DEG) showed that all the DEG in primary bile acid biosynthesis and biosynthesis of unsaturated fatty acids were down-regulated in SJ2.5% group and SJ10% group, respectively. Besides, all the DEG in regulation of autophagy were up-regulated in SJ2.5% and SJ10% groups compared with SJ0% group. Moreover, the metabolomic analysis of the differentially expressed metabolites (DEM) found that lipid metabolism was the main type of pathway in SJ supplementation groups. Furthermore, the analysis of both of DEG and DEM co-enriched in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway related to lipid metabolism found that the significant enriched pathways were primary bile acid biosynthesis, glycerophospholipid metabolism, biosynthesis of unsaturated fatty acids and fatty acid biosynthesis metabolism in SJ2.5% and SJ10% groups compared with SJ0% group. However, there were no pathways co-enriched between SJ10% and SJ2.5% group. In short, 2.5% and 10% SJ supplementation diets may reduce serum lipid content and HLA of black seabream through promoting autophagy and inhibiting the synthesis of fatty acids and bile acids. • Both 2.5% and 10% Saccharina japonica diets reduced liver lipid in black seabream. • Hepatic lipid metabolism was significantly affected by dietary Saccharina japonica. • Primary bile acid biosynthesis was the key pathway in hepatic lipid metabolism. [ABSTRACT FROM AUTHOR]

[Display omitted] • A systems-level approach allows untangling AD upstream pathomechanistic alterations. • Multi-omics approaches hold the potential to generate genetic/biological signatures. • Omics point out a failure of multi-level networks underlying AD pathophysiology. • Multi-omics data integration helps generate information on AD pathomechanisms. • Emerging neuroimaging-omics will help track trajectories of individuals at risk. Alzheimer's disease (AD) is characterized by non-linear, genetic-driven pathophysiological dynamics with high heterogeneity in biological alterations and disease spatial-temporal progression. Human in-vivo and post-mortem studies point out a failure of multi-level biological networks underlying AD pathophysiology, including proteostasis (amyloid-β and tau), synaptic homeostasis, inflammatory and immune responses, lipid and energy metabolism, oxidative stress. Therefore, a holistic, systems-level approach is needed to fully capture AD multi-faceted pathophysiology. Omics sciences – genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics – embedded in the systems biology (SB) theoretical and computational framework can generate explainable readouts describing the entire biological continuum of a disease. Such path in Neurology is encouraged by the promising results of omics sciences and SB approaches in Oncology, where stage-driven pathway-based therapies have been developed in line with the precision medicine paradigm. Multi-omics data integrated in SB network approaches will help detect and chart AD upstream pathomechanistic alterations and downstream molecular effects occurring in preclinical stages. Finally, integrating omics and neuroimaging data – i.e. , neuroimaging-omics – will identify multi-dimensional biological signatures essential to track the clinical-biological trajectories, at the subpopulation or even individual level. [ABSTRACT FROM AUTHOR]

Preterm birth (PTB) is a leading global cause of infant mortality. Risk factors include genetics, lifestyle choices and infection. Understanding the mechanism of PTB could aid the development of novel approaches to prevent PTB. This study aimed to investigate the metabolic biomarkers of PTB in early pregnancy and the association of significant metabolites with participant genotypes. Maternal sera collected at 16 and 20 weeks of gestation, from women who previously experienced PTB (high-risk) and women who did not (low-risk controls), were analysed using 1H nuclear magnetic resonance (NMR) metabolomics and genome-wide screening microarray. ANOVA and probabilistic neural network (PNN) modelling were performed on the spectral bins. Metabolomics genome-wide association (MGWAS) of the spectral bins and genotype data from the same participants was applied to determine potential metabolite-gene pathways. Phenylalanine, acetate and lactate metabolite differences between PTB cases and controls were obtained by ANOVA and PNN showed strong prediction at week 20 (AUC = 0.89). MGWAS identified several metabolite bins with strong genetic associations. Cis-eQTL analysis highlighted TRAF1 (involved in the inflammatory pathway) local to a non-coding SNP associated with lactate at week 20 of gestation. MGWAS of a well-defined cohort of participants highlighted a lactate-TRAF1 relationship that could potentially contribute to PTB., (© 2021 The Author(s).)

The availability of large-scale repositories and integrated cancer genome efforts have created unprecedented opportunities to study and describe cancer biology. In this sense, the aim of translational researchers is the integration of multiple omics data to achieve a better identification of homogeneous subgroups of patients in order to develop adequate diagnostic and treatment strategies from the personalized medicine perspective. So far, existing integrative methods have grouped together omics data information, leaving out individual omics data phenotypic interpretation. Here, we present the Massive and Integrative Gene Set Analysis (MIGSA) R package. This tool can analyze several high throughput experiments in a comprehensive way through a functional analysis strategy, relating a phenotype to its biological function counterpart defined by means of gene sets. By simultaneously querying different multiple omics data from the same or different groups of patients, common and specific functional patterns for each studied phenotype can be obtained. The usefulness of MIGSA was demonstrated by applying the package to functionally characterize the intrinsic breast cancer PAM50 subtypes. For each subtype, specific functional transcriptomic profiles and gene sets enriched by transcriptomic and proteomic data were identified. To achieve this, transcriptomic and proteomic data from 28 datasets were analyzed using MIGSA. As a result, enriched gene sets and important genes were consistently found as related to a specific subtype across experiments or data types and thus can be used as molecular signature biomarkers. [ABSTRACT FROM AUTHOR]

Human cancer classification is currently based on the idea of cell of origin, light and electron microscopic attributes of the cancer. What is not yet integrated into cancer classification are the functional attributes of these cancer cells. Recent innovative techniques in biology have provided a wealth of information on the genomic, transcriptomic and proteomic changes in cancer cells. The emergence of the concept of cancer stem cells needs to be included in a classification model to capture the known attributes of cancer stem cells and their potential contribution to treatment response, and metastases. The integrated model of cancer classification presented here incorporates all morphology, cancer stem cell contributions, genetic, and functional attributes of cancer. Integrated cancer classification models could eliminate the unclassifiable cancers as used in current classifications. Future cancer treatment may be advanced by using an integrated model of cancer classification.