KEGG: kyoto encyclopedia of genes and genomes

Downregulated expression of dual-specificity phosphatase-1 in multiple myeloma as a predictor of poor survival outcomes

OBJECTIVES

Multiple myeloma (MM) is an incurable hematological malignancy, Dual-specificity phosphatase-1 (DUSP1) plays a crucial role in the initiation and progression of various tumors. Here, we aim to elucidate the role of DUSP1 in MM.

METHODS

DUSP1 mRNA expression was analyzed based on public datasets, and protein expression was determined by immunohistochemistry. The association between DUSP1 and clinicopathological characteristics, as well as its impact on survival, were investigated. Protein-protein interaction and gene set enrichment analysis were performed.

RESULTS

Low DUSP1 expression was detected in MM and it was associated with elevated β2-microglobulin, C-reactive protein, creatinine, lactate dehydrogenase, plasma cell ratio, and decreased hemoglobin levels. The DUSP1high group exhibited superior outcomes across clinical endpoints. Univariate and multivariate analyses indicated that low DUSP1 expression was an independent prognostic factor for poor OS (hazard ratio = 0.273). The findings suggested that DUSP1 expression was related to proto-oncogene c-Fos (FOS), heat shock protein family member 1a (HSPA1A), several members of the MAPK family, nuclear receptor subfamily 3, group C, member 1 (NR3C1), and zinc finger protein 36 (ZFP36). DUSP1 mRNA levels were positively correlated with ribosomes and were negatively correlated with oocyte meiosis, one carbon pool by folate, homologous recombination, base excision repair, and pyrimidine metabolism pathways.

DISCUSSION

The potential mechanisms identified through the PPI network analysis could provide insight into how DUSP1 may influence MM.

CONCLUSIONS

Low expression of DUSP1 may be considered a poor prognostic factor for MM patients.

Targeting NEDD8 in pediatric acute myeloid leukemia: an integrated bioinformatics and experimental approach

SUMMARYThis study systematically explored the role of NEDD8 in pediatric acute myeloid leukemia (AML) through patient sample analysis, database mining, and in vitro experiments. Our results demonstrated that NEDD8 was significantly overexpressed in newly diagnosed pediatric AML patients and was associated with poor survival outcomes. Functional enrichment analysis of the TARGET database further revealed a strong correlation between NEDD8 and cancer-related pathways. In vitro experiments showed that NEDD8 knockdown significantly inhibited the proliferation of AML cells (THP-1 and MV4-11) and induced cell cycle arrest. Collectively, these findings highlight the critical role of NEDD8 in pediatric AML pathogenesis and suggest its potential as both a prognostic biomarker and a therapeutic target.

E. coli genetically modified for purine nucleobase release promotes butyrate generation and colonic wound healing during DSS insult

The gut microbiota transforms energy stored as undigestible carbohydrates into a remarkable number of metabolites that fuel intestinal bacterial communities and the host tissue. Colonic epithelial cells at the microbiota-host interface depend upon such microbiota-derived metabolites (MDMs) to satisfy their energy requisite. Microbial dysbiosis eliciting MDM loss contributes to barrier dysfunction and mucosal disease. Recent work has identified a role for microbiota-sourced purines (MSPs), notably hypoxanthine, as an MDM salvaged by the colonic epithelium for nucleotide biogenesis and energy balance. Here, we investigated the role of MSPs in mice during disease-modeled colonic energetic stress using a strain of E. coli genetically modified for enhanced purine nucleobase release (E. coli Mutant). E. coli Mutant colonization protected against DSS-induced tissue damage and permeability while promoting proliferation for wound healing. Metabolite and metagenomic analyses suggested a colonic butyrate-purine nucleobase metabolic axis, wherein the E. coli Mutant provided purine substrate for Clostridia butyrate production and host purine salvage, altogether supplying the host substrate for efficient nucleotide biogenesis and energy balance.

Exploring NamiRNA networks and time-series gene expression in osteogenic differentiation of adipose-derived stem cells

BACKGROUND

Adipose-derived stem cells (ADSCs) are a type of stem cell found in adipose tissue with the capacity to differentiate into multiple lineages, including osteoblasts. The differentiation of ADSCs into osteoblasts underlies osteogenic and pathological cellular basis in osteoporosis, bone damage and repair.

METHODS

Focused on ADSCs osteogenic differentiation, we conducted mRNA, microRNA expression and bioinformatics analysis, including gene differential expression, time series-based trend analysis, functional enrichment, and generates potential nuclear activating miRNAs (NamiRNA) regulatory network. The screened mRNAs in NamiRNA regulatory network were validated with correlation analysis.

RESULTS

The NamiRNA Regulatory Network reveals 4 mRNAs (C12orf61, MIR31HG, NFE2L1, and PCYOX1L) significantly downregulated in differentiated group and may be associated with ADSCs stemness. Furthermore, the significantly upregulated 10 genes (ACTA2, TAGLN, LY6E, IFITM3, NGFRAP1, TCEAL4, ATP5C1, CAV1, RPSA, and KDELR3) were significantly enriched in osteogenic-related pathways, and negatively correlated with ADSCs cell stemness in vitro.

CONCLUSION

These findings uncover potential genes related to ADSCs osteogenic differentiation, and provide theoretical basis for underlying ADSCs osteogenic differentiation and related diseases.

Prediabetes and type 2 diabetes but not obesity are associated with alterations in bile acid related gut microbe-microbe and gut microbe-host community metabolism

The interplay between bile acids (BAs) and metabolic diseases has gained importance in recent years, with a variety of studies investigating their relationship with diverging results. Therefore, in the present study we performed a detailed analysis of BA metabolism in 492 subjects with different metabolic phenotypes. Besides microbiomics and metabolomics this investigation included in silico analysis of community metabolism to examine metabolic interchange between different microbes as well as microbes and the human host. Our findings revealed distinct changes in the BA profiles of patients with diabetes and prediabetes, whereas obesity alone had no influence on circulating BAs. Impaired glycemic control led to increased circulating BAs, a shift toward more secondary BAs, and an increase in the ratio of glycine to taurine-conjugated BAs. Additional analyses revealed that the ratio of glycine to taurine conjugation demonstrated variations between the single BAs, cholic acid (CA), chenodeoxycholic acid (CDCA) and deoxycholic acid (DCA), regardless of the metabolic status, with CA having a higher fraction of taurine conjugation. Furthermore, we found that microbiome alterations are associated with BAs, independent of diabetes or obesity. Analysis of microbial community metabolism revealed differential relative pathway abundance in relation to diabetes, particularly those related to membrane and polyamine synthesis. Increased bacterial cross-feeding of polyamines, galactose, and D-arabinose also coincided with an increase in BA. Notably, our serum metabolome analysis mirrored several of the previously in silico predicted exchanged metabolites, especially amino acid metabolism. Therefore, targeting BA metabolism may be a future approach for the treatment of metabolic diseases, especially prediabetes and type 2 diabetes.

Identification of endoplasmic reticulum stress-related genes as prognostic markers in colon cancer

Endoplasmic reticulum stress (ERS) has been implicated in the pathogenesis of various cancers, including colon cancer, by regulating tumor cell survival, growth, and immune response. However, the specific genes involved in ERS that could serve as prognostic markers in colon cancer remain underexplored. This study aims to identify and validate endoplasmic reticulum stress related genes (ERSRGs) in colon cancer that correlate with patient prognosis, thereby enhancing the understanding of ERS in oncological outcomes and potential therapeutic targeting. We utilized bioinformatics analyses to identify ERSRGs from publicly available colon cancer datasets. Differential expression analysis and survival analysis were performed to assess the prognostic significance of these genes. Validation was conducted through quantitative real-time PCR (RT-qPCR) on selected colon cancer cell lines. Our study identified nine ERS related genes (ASNS, ATF4, ATF6B, BOK, CLU, DDIT3, MANF, SLC39A14, TRAF2) involved in critical pathways including IL-12, PI3K-AKT, IL-7, and IL-23 signaling, and linked to 1-, 3-, and 5-year survival of patients with colon cancer. A multivariate Cox model based on these ERS related genes demonstrated significant prognostic power. Further, TRAF2 strong correlated with immune cells infiltration, suggesting its potential roles in modulating immune responses in the tumor microenvironment. The RT-qPCR validation confirmed the differential expression of these genes in human colon cancer cell lines versus human normal colonic epithelial cell line. The identified ERSRGs could serve as valuable prognostic markers and may offer new insights into the therapeutic targeting of ERS in colon cancer.

UPLC-MS and multivariate analysis reveal metabolic pathway adaptations to training in professional football players

Metabolomics provides direct insights into biological processes by analyzing metabolites. While univariate and multivariate analyses, alongside pathway and functional analysis tools like mummichog, are commonly employed, integrating these results to interpret biological significance remains a challenge, limiting the potential of metabolomic analyses. This study introduces innovative methods to analyze metabolic adaptations in professional football players using a unique UPLC-TOF-MS dataset comprising 93 urinary samples collected over a 10-month football season. Urinary metabolomic profiles were linked to training load data obtained through an electronic performance tracking system. Three approaches combining multivariate analysis with pathway-level insights were developed. PLS regression p-values integrated with functional metabolic analysis identified training load-associated pathways overlooked by univariate methods. Cluster cross-validation enhanced these insights by assessing the contribution of each pathway to the predictive performance, ranking pathways driving the PLS model. Backward feature elimination refined metabolic features most strongly linked to training load, improving the practicality of findings for targeted biomarker validation. Univariate analyses highlighted alterations in Phenylalanine and Histidine metabolisms related to total external load. Multivariate methods identified additional pathways, including Tryptophan, Purine, and Tyrosine metabolisms, as top contributors to the association between metabolic profiles and training load. Results demonstrate that combining multivariate techniques with functional analysis expands understanding of athletes' metabolic responses, offering more comprehensive biomarker discovery beyond the scope of univariate approaches. These findings underscore the value of integrating multivariate strategies with pathway insights to enhance the biological interpretation of metabolomic data.

Drug-drug interaction prediction based on graph contrastive learning and dual-view fusion

Drug-drug interaction (DDI) is important in drug research and are one of the major causes of morbidity and mortality. The deep learning methods can automatically extract drug features from molecular graphs or drug-related networks, which improves the performance of DDI prediction. However, there is noise and incomplete data in existing datasets, and the volume of dataset is limited. In order to fully utilize the knowledge graph network and the molecular structure, we propose a dual-view fusion model GDF-DDI. In one view, the knowledge graph network and drug similarity network are constructed as the global information, and two graph convolution operations are implemented on both networks to extract drug embeddings. Subsequently, layer wise graph contrastive learning is performed to update the drug embeddings to captures richer semantic information. In the other view, the self-supervised learning is utilized to extract more comprehensive embedding of drugs. The embeddings under two views are concatenated to cover the global and local DDI information. The comparative experiments on two datasets show that our model outperforms other recent and state-of-the-art baselines.

Integrative analysis of exosomal ncRNAs and their regulatory networks in liver cancer progression

Background

Hepatocellular carcinoma (HCC) is a significant global health challenge with complex molecular underpinnings. Recent advancements in understanding the role of non-coding RNAs (ncRNAs) and exosomes in cancer biology have opened new avenues for research into potential diagnostic and therapeutic strategies.

Methods

This study utilized a comprehensive approach to analyze gene expression patterns and regulatory networks in HCC. We integrated RNA sequencing data gathered from both tissue samples and exosomes. The WGCNA and limma R packages were employed to construct co-expression networks and identify differentially expressed ncRNAs, including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs).

Results

Our analysis demonstrated distinct expression profiles of various ncRNAs in HCC, revealing their intricate interactions with cancer-related genes. Key findings include the identification of a network of microRNAs that interact with selected lncRNAs and their potential roles as biomarkers. Moreover, exosomal RNA was shown to effectively reflect tissue-specific gene expression changes.

Conclusions

The results of this study highlight the significance of exosomal ncRNAs in the progression of liver cancer, suggesting their potential as both diagnostic biomarkers and therapeutic targets. Future research should focus on the functional implications of these ncRNAs to further elucidate their roles in HCC and explore their applications in clinical settings.

Scaling metabolic model reconstruction up to the pan-genome level: A systematic review and prospective applications to photosynthetic organisms

Advances in genomics technologies have generated large data sets that provide tremendous insights into the genetic diversity of taxonomic groups. However, it remains challenging to pinpoint the effect of genetic diversity on different traits without performing resource-intensive phenotyping experiments. Pan-genome-scale metabolic models (panGEMs) extend traditional genome-scale metabolic models by considering the entire reaction repertoire that enables the prediction and comparison of metabolic capabilities within a taxonomic group. Here, we systematically review the state-of-the-art methodologies for constructing panGEMs, focusing on used tools, databases, experimental datasets, and orthology relationships. We highlight the unique advantages of panGEMs compared to single-species GEMs in predicting metabolic phenotypes and in guiding the experimental validation of genome annotations. In addition, we emphasize the disparity between the available (pan-)genomic data on photosynthetic organisms and their under-representation in current (pan)GEMs. Finally, we propose a perspective for tackling the reconstruction of panGEMs for photosynthetic eukaryotes that can help advance our understanding of the metabolic diversity in this taxonomic group.

Multi-omics analysis revealed the effects of different astaxanthin sources on the antioxidant properties of Scylla paramamosain

Astaxanthin, a carotenoid present in many organisms, has antioxidant, coloration, and anti-inflammatory benefits, making it a safe and effective feed additive. In this study, Scylla paramamosain fed diets with 100 mg/kg synthetic astaxanthin and 25 mg/kg Haematococcus pluvialis exhibited the best growth performance. Increased astaxanthin levels in the feed also resulted in red coloration of the carapace. Transcriptomic and metabolomic analysis showed that synthetic astaxanthin promoted the metabolism of arachidonic acid (phosphatidycholine (PC, 35:3) and 20-hydroxyarachidonic acid through negative feedback regulation of carotenoids such as adh (alcohol dehydrogenase) and cyp2c (cytochrome p450 2c), thereby improving the antioxidant capacity such as sod1 (Cu/Zn superoxide dismutase), gsh-px (glutathione peroxidase), and bbox1 (gamma-butyrobetaine hydroxylase 1). Nature astaxanthin (Haematococcus Pluvialis) activates mitochondrial energy metabolism (ND2, ND4 and COX1, COX2, COX3) through negative feedback regulation of carotenoids (bcmo1, β-carotene-15,15'-monooxygenase 1), thereby improving the antioxidant capacity of crabs (sod1, fth1 (ferritin heavy chain) and bbox1).

Basil chilling injury: Oxidative stress or energy depletion?

Basil (Ocimum basilicum L.) is susceptible to chilling injury (CI), leading to significant postharvest quality loss. This research aimed to identify key metabolites involved in CI of basil during cold storage to better understand the underlying mechanisms. Metabolite profiles of basil leaves stored at 4 and 12 °C for up to 12 days were quantified by 1H NMR and GC-MS. At 4 °C shelf life was reduced due to CI. At 4 °C, several osmoprotectants, including proline, gamma-aminobutyric acid, trehalose and myo-inositol increased, whereas antioxidants like ascorbic acid and rosmarinic acid decreased; the latter likely due to scavenging reactive oxygen species. During chilling stress, antioxidant defence pathways were upregulated and carbohydrate related energy pathways were downregulated. We suggest that CI in basil associates with redirection of carbohydrate flux towards antioxidant defence systems, leading to energy depletion. This energy depletion is hypothesized as a primary trigger for CI in postharvest basil.

Single-cell RNA sequencing reveals tissue-specific transcriptomic changes induced by perfluorooctanesulfonic acid (PFOS) in larval zebrafish (Danio rerio)

Perfluorooctanesulfonic acid (PFOS) elicits adverse effects on numerous organs and developmental processes but the mechanisms underlying these effects are not well understood. Here, we use single-cell RNA-sequencing to assess tissue-specific transcriptomic changes in zebrafish (Danio rerio) larvae exposed to 16 µM PFOS or dimethylsulfoxide (0.01 %) from 3-72 h post fertilization (hpf). Data analysis was multi-pronged and included pseudo-bulk, untargeted clustering, informed pathway queries, and a cluster curated for hepatocyte biomarkers (fabp10a, and apoa2). Overall, 8.63 % (2390/27698) genes were significantly differentially expressed. Results from untargeted analysis revealed 22 distinct clusters that were manually annotated to specific tissues using a weight-of-evidence approach. The clusters with the highest number of significant differentially expressed genes (DEGs) were digestive organs, muscle, and otolith. Additionally, we assessed the distribution of pathway-specific genes known to be involved in PFOS toxicity: the PPAR pathway, β-oxidation of fatty acids, the Nfe2l2 pathway, and epigenetic modifications by DNA methylation, across clusters and identified the blood-related tissue to be the most sensitive. The curated hepatocyte cluster showed 220 significant DEGs and was enriched for the Notch signaling pathway. These findings provide insights into both established and novel sensitive target tissues and molecular mechanisms of developmental toxicity of PFOS.

Self-assembly of algal-bacterial granules induced by bacterial N-acyl-homoserine lactone variation in response to high-strength pyridine

Algal-bacterial granules (ABGs) system represents a promising technology for organic wastewater treatment due to its high settleability, efficient oxygen transfer, and low-energy consumption. However, the secretion of extracellular polymeric substances (EPS) in algae, which played a key role in self-assembly of ABGs, would be inhibited by concentrated organic wastewater. This study proposed a novel strategy for developing ABGs by inducing bacterial N-acyl-homoserine lactone (AHL) variation through high-strength pyridine application. Results showed that bacterial long-chain AHL concentrations significantly increased in response to high-strength pyridine at 550 mg L-1, inducing the secretion of algal extracellular aromatic proteins and facilitating ABGs construction. The ABGs system achieved over 99 % pyridine removal efficiency and 82 % settleability. Moreover, the proportions of β-sheet and α-helix structures in the extracellular aromatic proteins of ABGs increased, while the random coil structures decreased. This shift in protein structure lowered the surface free energy and energy barriers, which in turn enhanced the surface hydrophobicity and promoted cell adhesion. Furthermore, based on metatranscriptomic analysis, the mechanism for AHL-regulated physiological and behavioral responses between algae and bacteria in ABGs was proposed. This study provides an economically feasible approach to develop efficient and sustainable ABGs systems for industrial wastewater treatment.

Newborn metabolomic signatures of maternal vanadium exposure and reduced birth size

Prenatal exposure to vanadium has been associated with reduced birth size, however, the specific molecular mechanism underlying this effect remains largely unexplored. We measured vanadium in maternal plasma during early pregnancy, and characterized metabolomics profiling in cord blood among 1020 mother-infant pairs from the Wuhan Healthy Baby Cohort, China. After adjusting for potential confounders, a 2-fold increase in maternal plasma vanadium concentration was associated with a decrease of 25.1 g (95 % CI: -45.1, -5.1) and 0.429 g/cm (95 % CI -0.758 to -0.101) in birth weight and weight-for-length (WFL), respectively. Of the 423 metabolites detected, 42 metabolites and 10 metabolic pathways were significantly linked to both vanadium and birth size. The effect of vanadium on reduced birth weight and WFL was significantly mediated by 14 metabolites, including 2 hormones (cortisol and corticosterone), 1 amino acid (lysine), and 11 lipids, with a mediating effect range of 7 % to 17 %. In addition, the lysine degradation pathway significantly mediated a 19 % change in the association between vanadium exposure and both lower birth weight and WFL. Higher maternal vanadium exposure was linked to reduced birth size, and the perturbed metabolites and pathways involved in hormones, amino acids, oxidative stress, and lipid peroxidation may explain the mechanism.

Integrative multi-omics analysis reveals liver-gut axis adaptation in high-altitude goats

The liver-gut axis is an important regulatory axis for the host's metabolic functions. The study of liver gene expression, changes in metabolic products and the regulation of gut microbial communities in plateau animals under harsh environments can reveal the mechanisms by which Tibetan goats adapt to the plateau environment. This study employs transcriptome, metabolome and metagenomic analyses to reveal the differences in genes, metabolism, and gut microbiota between Jianzhou big-eared goats (JBG) and Xizang cashmere goats (TCG), which is of significant importance for improving survival models of high-altitude ruminants. The results showed that there were 553 DEGs in the liver of JBG and TCG. Hepatic metabolomic analysis revealed significant differences in metabolic activity between the JBG and TCG groups, with notable increases in glycerophospholipid and retinol metabolic pathways. The gut microbiota, including Andreesenia, Dielma, Oscillibacter, Agrobacterium, Hyella and Thermosinus, interact with liver metabolites and can regulate the high-altitude adaptability of goats. This study reveals that TCG enhance immune regulation and energy utilization efficiency by regulating liver gene expression, modulating metabolic pathways, and improving gut microbiota, thereby helping TCG maintain healthy survival capabilities in hypoxic and high-radiation environments.

RNA‑seq analysis of predictive markers associated with glutamine metabolism in thyroid cancer

The incidence of thyroid cancer (TC) increases year by year. It is necessary to construct a prognostic model for risk stratification and management of TC patients. Glutamine metabolism is essential for tumor progression and the tumor microenvironment. The present study aimed to develop a predictive model for TC using a glutamine metabolism gene set. Differentially expressed genes in cells with high glutamine metabolism levels from single cell RNA‑sequencing data were compared with genes differentially expressed between normal and TC tissues from The Cancer Genome Atlas Program data. Through Boruta feature selection methods and multivariate Cox regression, six crucial genes were identified for a risk‑scoring system to develop a prognostic model. The role of each gene was verified in TC cells in vitro. A risk‑scoring system was developed according to the glutamine gene set to forecast the overall survival of TC patients. This risk score could stratify TC patients and minimize unnecessary surgeries and invasive treatments. In addition, signal induced proliferation associated 1 like 2 (SIPA1L2), an important gene in the prognostic model, knockdown in TPC‑1 and BCPAP cell lines enhanced TC cell proliferation, migration and invasion. A risk model was developed based on a glutamine metabolism gene set. The model has reference values for TC stratification.

Gene expression profiles of Chinese medaka (Oryzias sinensis) primary hepatocytes in response to estrone (E1), 17β-estradiol (E2) and estriol (E3)

The natural estrogens, including estrone (E1), 17β-estradiol (E2), and estriol (E3), are frequently detected in aquatic environment at relatively high levels. The most commonly used biomarkers for estrogens are mainly expressed in the liver of fish. Analyses of the global gene profiling in fish liver cells under estrogens treatment will provide precise toxicogenomic information of the natural estrogens which is still not well known. In this study, we developed methods for isolation and culture of primary hepatocytes from liver tissue of male Chinese medaka (Oryzias sinensis), and analyzed the global gene expression profiling in the primary hepatocytes treated with E1 (1, 10, and 100 nmol/L), E2 (0.01, 0.1, 1, 10, and 100 nmol/L), and E3 (1, 10, and 100 nmol/L) using RNA-seq. It was found that 175, 248, and 218 genes were differentially expressed in the E1, E2, and E3 groups, respectively. These differentially expressed genes (DEGs) were mainly enriched in Gene Ontology (GO) terms of "response to estradiol", "response to estrogen", and "lipid transport". Of the DEGs, vitellogenin genes, including vtg1, vtg2, and vtg3, were the mostly up-regulated and followed by zona pellucida genes which include zp2.3, zp2l1 and zp3a.2. In addition, genes of slc41a1, zp2.1, esr1, pkd1l1, fam20ca, best3, etc. were also obviously up-regulated by the estrogens in concentration-dependent patterns. RT-qPCR was used to validate the results of RNA-seq and found that vtg2 should be the best biomarker gene for estrogen study, which could well response to natural estrogens and weak estrogenic chemical, propyl 4-hydroxybenzoate.

Total plasma cfDNA methylation in pediatric kidney transplant recipients provides insight into acute allograft rejection pathophysiology

Cell-free DNA (cfDNA) is a marker of organ injury and immune response. DNA methylation is an epigenetic regulator of gene expression. Here, we elucidate total plasma cfDNA methylation from kidney transplant recipients in presence versus absence of rejection. In doing so, we exploit cfDNA as a real-time biomarker to define molecular pathways of rejection. Twenty plasma cfDNA samples from pediatric kidney transplant recipients were collected at allograft biopsy. Differentially methylated cytosine residues (>20 % methylation difference, q-value <0.05) were identified in presence (N = 7) versus absence (N = 9) of acute rejection. Separate analyses were performed comparing borderline rejection (N = 4) to rejection and non-rejection. In rejection versus non-rejection, there were 1269 differentially methylated genes corresponding to 533 pathways. These numbers were 4-13× greater than comparisons against borderline samples. Enriched pathways between rejection and non-rejection samples were related to immune cell/inflammatory response, lipid metabolism, and tryptophan-kynurenine metabolism, suggesting differential methylation of these pathways contributes to rejection.

Gonadal transcriptome analysis of Opsariichthys bidens reveals sex-associated genes

Opsariichthys bidens is a unique economically important freshwater fish in China. Male O. bidens grow faster than females, and male fish have attractive blue-green stripes on the body surface during the breeding period. The breeding of all-male stocks can significantly improve the efficiency of breeding. To accelerate the breeding of all-male stocks, additional studies of the mechanism regulating sex differentiation and gonad development are needed. In this study, transcriptome sequencing of the ovaries and testes of O. bidens was performed using Illumina high-throughput sequencing. The results revealed a total of 21,703 differentially expressed genes, including 8645 up-regulated genes and 5880 down-regulated genes expressed in the ovary compared with the testis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed multiple differentially expressed genes involved in sex differentiation and gonad development. Eight differentially expressed genes (zp3, cyp19a, hsd17b1, msh4, dmrt1, rspo2, kif23, and gdf9) that play a key role in sex differentiation and gonadal development were selected for RT-qPCR validation. The expression levels of selected genes in the testes and ovaries were significantly different (P < 0.05). zp3, cyp19a, hsd17b1, and gdf9 were female-biased genes, and msh4, dmrt1, rspo2, and kif23 were male-biased genes. zp3, cyp19a, hsd17b, and msh4 were only slightly expressed in the kidney and liver, and dmrt1, rspo2, kif23, and gdf9 were all expressed in gill, kidney, and liver tissue. None of the genes were expressed in the heart or muscle. In this study, differentially expressed genes related to the sex determination and differentiation of O. bidens were identified. Overall, our findings provide important data for future studies of the molecular mechanisms of sex differentiation and gonad development of O. bidens and will aid the breeding of all-male species.

3D-printed β-TCP scaffold as a bone-mimicking environment for an engineered model of osteosarcoma: In vitro properties and transcriptomic insights

In the face of advancements in osteosarcoma research, existing preclinical models - including in vitro (i.e., two- and three-dimensional cell cultures, organoids) and in vivo approaches (i.e., xenografts, animal models) - are often characterised by low translatability, limiting their predictive power for clinical outcomes. This study investigated the potential use of a 3D-printed β-tricalcium phosphate (β-TCP) scaffold as a bone-mimicking environment in an advanced in vitro osteosarcoma preclinical model. The compatibility of the scaffold with osteosarcoma cell spheroids, endothelial cells, and primary bone marrow-derived mesenchymal stem cells (pBMSCs) was evaluated along with its physicochemical characteristics. Transcriptomic analysis of pBMSCs on the scaffolds revealed gene expression profiles indicating pronounced extracellular matrix organisation and minor osteogenic activity. The model effectively replicated significant aspects of the tumour microenvironment in a tri-culture system, with dynamic perfusion enhancing metabolic activity. The developed scaffold-based model was employed in the doxorubicin cytotoxicity test. The physiological significance of the tri-culture was demonstrated by its distinct doxorubicin accumulation, in contrast to spheroid monocultures. Despite the limitations of the proposed approach regarding efficient vascularisation of the model, this study highlights the potential of 3D-printed β-TCP scaffolds in tumour modelling to support physiologically relevant preclinical models.

W-GA nanodots with multienzyme activities alleviate the inflammatory microenvironment in the treatment of acute wounds

Acute wounds present a significant clinical challenge due to delayed healing, which is often exacerbated by elevated levels of reactive oxygen species (ROS). These high ROS concentrations hinder the natural healing process, leading to prolonged recovery and increased risk of complications. W-GA nanodots, synthesized via a simple coordination method, have emerged as promising solutions, demonstrating multifunctional enzymatic activity that effectively scavenges ROS. To explore the underlying mechanisms of ROS-induced oxidative stress, we conducted RNA sequencing on macrophages exposed to H2O2. The results revealed significant regulation of key stress response pathways, including substantial upregulation of the "p53 signaling pathway" and the "HIF-1 signaling pathway," both of which are essential for cellular adaptation to oxidative stress. By alleviating oxidative stress, W-GA nanodots not only accelerate wound repair but also improve overall healing outcomes. Notably, RNA sequencing of animal tissue samples revealed that W-GA nanodots activate the "Wnt signaling pathway," further promoting wound healing. These findings underscore the potential of W-GA nanodots as a novel therapeutic strategy for enhancing wound healing and treating oxidative stress-related conditions, positioning them as promising candidates for future clinical applications in wound care and inflammatory diseases.

Identification of key genes linking bisphenols exposure and breast cancer

Breast cancer (BC) is one of the most common types of cancer and is caused by the complex interplay of genetic and environmental factors, such as an unhealthy lifestyle, family history of illness, reproductive factors, and ageing. However, increasing evidence has revealed that manufactured organic pollutants such as bisphenols are closely related to BC. Bisphenols exposure can promote the progression of BC through multiple complicated and variable molecular mechanisms. Reanalysis of existing data on this topic may reveal molecular markers with clinical value. In this study, we identified four key genes [keratin 14 (KRT14), keratin 5 (KRT5), acyl-CoA synthetase long chain family member 1 (ACSL1) and matrix metallopeptidase 1 (MMP1)] related to both bisphenols exposure and BC by employing the Comparative Toxicogenomics Database (CTD) and The Cancer Genome Atlas Cervical Cancer (TCGA-CESC) dataset; notably, KRT14 expression exhibited the most significant difference between tumour and normal tissues. Further analysis of the functions and biological processes associated with KRT14 and related regulatory molecules revealed that bisphenols exposure induces BC-promoting characteristics and aggressive behaviour-related signaling pathways, such as the steroid biosynthesis, Forkhead box (FOXO) and prolactin signaling pathways. To confirm the expression and biological effects of KRT14, we conducted relevant experiments. In vitro studies revealed that bisphenols such as bisphenol A (BPA) exposure significantly affected the proliferation, migration, and invasion of MCF-7 cells by inhibiting KRT14 expression. Similarly, we also observed a decrease in KRT14 expression in BPA induced abnormal breast tissue in mice. In summary, our study revealed potential genes and pathways associated with bisphenols exposure in BC.

Mechanistic insights into chloroethene dechlorination by Dehalococcoides mccartyi strain CWV2: A multi-omics perspective

This study provides an in-depth investigation of the novel Dehalococcoides mccartyi (Dhc) strain CWV2, isolated from Taiwan, for its effectiveness in dechlorinating various chloroethenes, including PCE, TCE, DCEs, and VC, to ethene. Through multi-omics analyses, including genomic, transcriptomic, translatomic and proteomic profiling, we uncovered the mechanisms behind TCE dechlorination by strain CWV2. The genomic analysis identified key reductive dehalogenase (RDase) genes, pceA and vcrA, which enhance our understanding of the versatile dechlorination pathways in Dhc. Ribosome profiling provided detailed insights into the translational regulation of vcrA, revealing sophisticated genetic control over protein synthesis. Complementary BN-PAGE and proteomic analyses identified key RDase VcrA, offering further insights into the activity of the organohalide respiration (OHR) complex within CWV2 and its metabolic pathways. Multi-omics analyses provide a comprehensive understanding of the mechanisms behind TCE dechlorination and organohalide respiration, offering valuable insights to advance bioremediation strategies for chloroethene-contaminated environments.

miRNA and piRNA differential expression profiles in Alzheimer's disease: A potential source of pathology and tool for diagnosis

Alzheimer's Disease (AD) is the most prevalent form of dementia and one of the leading causes of death in the United States, and despite our best efforts and recent advancements, a treatment that stops or substantially slows its progression has remained elusive. Small extracellular vesicles (sEVs), hold the potential to alleviate some of the common issues in the field by serving to better differentiate AD and non-AD individuals. These vesicles could provide insights into therapeutic targets, and potentially an avenue towards early detection. We compared the sEV cargo profiles of AD and non-AD brains (n = 6) and identified significant differences in both the micro RNA (miRNA) and Piwi-interacting RNA (piRNA) cargo through sEV isolation from temporal cortex tissue, followed by small RNA sequencing, and differential expression analysis. Differentially expressed miRNAs targeting systems relevant to AD included miR-206, miR-4516, miR-219a-5p, and miR-486-5p. Significant piRNAs included piR-6,565,525, piR-2,947,194, piR-7,181,973, and piR-7,326,987. These targets warrant further study for their potential role in the progression of AD pathology by dysregulating cellular activity; additionally, future large-scale studies of neuronal sEV miRNA profiles may facilitate the development of diagnostic tools which can aid in clinical trial design and recruitment. Longitudinal analysis of sEV data, perhaps accessible through plasma surveyance, will help determine at what point these miRNA and/or piRNA profiles begin to diverge between AD and non-AD individuals.

The immune defense response and immune-related genes expression in Odontobutis potamophila infected by Aeromonas salmonicida

Aeromonas salmonicida belongs to the Aeromonas family, which could widely infect economic fish, causing diseases and huge economic losses. Recently, A. salmonicida was also detected in diseased Odontobutis potamophila. Transcriptomic model of A. salmonicida-infected O. potamophila was analyzed to reveal immune response. A total of 113,282 unigenes were obtained and annotated in six databases. After 12 h of infection with A. salmonicides, a total of 614 differentially expressed genes (DEGs) (355 up-regulated genes and 259 down-regulated genes) were identified in the head kidney tissues. Following 24 h of infection, a total of 1689 DEGs were detected in the head kidney tissues, including 313 up-regulated genes and 1376 down-regulated genes. GO and KEGG pathway analyses were conducted to provide functional insights and a clearer understanding of the signal transduction pathways associated with the DEGs. Further analysis of the complement and coagulation cascades pathway and PPAR signaling pathway exhibited that the expression of immune genes was widely activated at the beginning of A. salmonicides infection. Additionally, six DEGs were randomly selected and validated using quantitative real-time PCR, showing expression patterns consistent with the high-throughput sequencing data. These results offer important insights that enhance the understanding of immune response in O. potamophila against A. salmonicida infection.

A comprehensive transcriptome based meta-analysis to unveil the aggression nexus of oral squamous cell carcinoma

Lymph node metastasis in oral cancer (OC) complicates management due to its aggressive nature and high risk of recurrence, underscoring the need for biomarkers for early detection and targeted therapies. However, the drivers of this aggressive phenotype remain unclear due to the variability in gene expression patterns. To address this, an integrative meta-analysis of six publicly available transcriptomic profiles, categorized by lymph nodal status, is conducted. Key determinants of disease progression are identified through functional characterization and the TopConfects ranking approach of nodal associated differentially expressed genes (DEGs). To explore the critical nexus between lymph node metastasis and OC recurrence, significant metastatic genes were cross-analysed with literature-derived genes exhibiting aberrant methylation patterns in OC recurrence. Their clinical relevance and expression patterns were then validated in an external dataset from the TCGA head and neck cancer cohort. The analysis identified elevated expression of genes involved in extracellular matrix remodelling and immune response, while the expression of genes related to cellular differentiation and barrier functions was reduced, driving the transition to nodal positivity. The highest-ranked gene, MMP1, showed a log-fold change (LFC) of 4.946 (95 % CI: 3.71, 6.18) in nodal-negative samples, which increased to 5.899 (95 % CI: 4.80, 6.99) in nodal-positive samples, indicating consistent elevation across disease stages. In contrast, TMPRSS11B was significantly downregulated, with an LFC of -5.512 (95 % CI: -6.63, -4.38) in nodal-negative samples and -5.898 (95 % CI: -7.15, -4.64) in nodal-positive samples. Furthermore, MEIS1, down-regulated in nodal-positive status, was found to exhibit hypermethylation at CpG sites associated with OC recurrence. This study represents the first transcriptomic meta-analysis to explore the intersection of lymph node metastasis and OC recurrence, identifying MEIS1 as a potential key contributor. These comprehensive insights into disease trajectories offer potential biomarkers and therapeutic targets for future treatment strategies.

Cutting-edge technologies illuminate the neural landscape of cancer: Insights into tumor development

Neurogenesis constitutes a pivotal facet of malignant tumors, wherein cancer and its therapeutic interventions possess the ability to reconfigure the nervous system, establishing a pathologic feedback loop that exacerbates tumor progression. Recent strides in high-resolution imaging, single-cell analysis, multi-omics technologies, and experimental models have opened unprecedented avenues in cancer neuroscience. This comprehensive review summarizes the latest advancements of these emerging technologies in elucidating the biological mechanisms underlying tumor initiation, invasion, metastasis, and the dynamic heterogeneity of the tumor microenvironment(TME), with a specific focus on neuron-glial-tumor interactions in glioblastoma(GBM) and other neurophilic cancers. Moreover, we innovatively propose target screening processes based on sequencing technologies and database frameworks. It rigorously evaluates ongoing clinical trial drugs and efficacy while spotlighting characteristic cells in the central and peripheral TME, consolidating cancer biomarkers pivotal for future targeted therapies and management strategies. By integrating these cutting-edge findings, this review aims to offer fresh insights into tumor-nervous system interactions, establishing a robust foundation for forthcoming clinical advancements.

Skin transcriptome of lenok trout (Brachymystax lenok) provides new insight on lectin genes and immune response mechanisms to Aeromonas salmonicida infection

Brachymystax lenok is an economically valuable cold-water fish species that has shown lower morbidity during pathogen outbreaks compared to other cold-water species. To elucidate the innate immune mechanisms in B. lenok in response to Aeromonas salmonicida infection, the transcriptome sequencing of the skin was performed. A total of 297,142 unigenes were generated, with 64.21 % (190,809) successfully annotated. Differential expression analysis identified 9238 differentially expressed genes (DEGs), with significant enrichment in immune-related pathways, including NOD-like receptor, C-type lectin receptor, and Toll-like receptor signalling pathways. These pathways may play crucial role in pathogen recognition, immune activation, inflammation, and the induction of adaptive immune responses in B. lenok. Further analysis revealed significant upregulation of pro-inflammatory cytokines, complement system components, and antimicrobial peptides such as hepcidin and cathelicidin, highlighting their pivotal roles in B. lenok's immune defense. Moreover, a notable finding was the dynamic expression of various lectin families, including C-type lectins, plectins, galectin-3, and β-galactoside-binding lectins, which are involved in pathogen recognition, immune modulation, and cell signalling. Lectins may also contribute to resistance mechanisms by affecting bacterial membrane permeability, disrupting vital metabolic processes, and enhancing synergy with antimicrobial peptides. In the pathological experiments, histological examination correlated the upregulation of inflammatory mediators and complement components with tissue damage, immune cell infiltration, and lesion development, further supporting the involvement of these genes in the immune response. These results will enrich the information in understanding the immune response in B. lenok, and provide basic data for the following proteomics and functional assays that can verify the protein-level activity of these immune-related genes and clarify their specific roles in host defense and resistance mechanisms. This comprehensive transcriptome analysis provides insights into the immune response mechanisms of B. lenok, with particular emphasis on the role of lectins in pathogen recognition and resistance. These findings offer a foundation for further research on immune mechanisms in fish and the development of therapeutic strategies to mitigate infections in aquaculture.

Analysis of ferroptosis-related key genes and regulatory networks in diabetic foot ulcers

BACKGROUND

Diabetic foot ulcers (DFUs) is a severe complication of diabetes. Recent evidence suggests that ferroptosis, a form of regulated necrosis, may play a significant role in the progression of DFU. However, the precise molecular mechanisms remain elusive.

OBJECTIVE

This study aims to identify ferroptosis-related genes (FRGs) and the signaling pathways involved in DFU progression by analyzing the gene expression profiles of DFU.

METHODS

Differentially expressed genes (DEGs) were identified by analyzing gene expression data from two DFU-related datasets (GSE38396, and GSE143735). FRGs were collected from both datasets and the literature. DEGs were then intersected with FRGs to identify ferroptosis-related differentially expressed genes (FRDEGs) in DFU. Functional enrichment analysis, protein-protein interaction (PPI) network analysis, receiver operating characteristic (ROC) curve analysis, and regulatory network interaction analysis (including mRNA-miRNA, mRNA-transcription factor (TF), and mRNA-drug interactions) were performed on the FRDEGs. Additionally, immune infiltration analysis was conducted using CIBERSORTx. Finally, skin tissue samples from clinical patients were collected, and the expression levels of FRDEGs in DFU samples were validated through reverse transcription quantitative real-time PCR (RT-qPCR), immunohistochemistry (IHC) and Immunofluorescence (IF), to uncover potential new targets for the diagnosis and treatment of DFU.

RESULTS

A total of 14 DFUs samples (non-healing group) and 12 control samples (healing group) were obtained in this study. We identified 276 DEGs in DFUs samples compared to controls, with 121 up-regulated and 155 down-regulated genes. By intersecting DEGs with ferroptosis-related genes, we identified 10 FRDEGs (AURKA, CTH, FBLN1, FTL, GLS2, KDM5C, MYH9, PCNA, PYCR1, and SPARC). The GO and KEGG analysis results showed that FRDEGs were mainly enriched in biological processes such as amino acid biosynthesis and tight junction pathways. Further analysis of FRDEGs identified ten hub genes closely associated with 112 TFs, 34 miRNAs, and 50 drugs or molecular compounds. Additionally, RT-qPCR validation of skin tissue samples from 8 DFU patients and 8 controls showed that AURKA were significantly up-regulated in DFU, IHC and IF analysis further demonstrated elevated AURKA protein expression in DFU samples. Moreover, AURKA was identified as a potential diagnostic marker for diabetic wound healing, with high diagnostic accuracy based on ROC curve analysis (AUC = 0.950 in the combined dataset, and AUC = 0.881 in the validation dataset). These findings highlight AURKA as a key gene involved in ferroptosis and a potential target for the diagnosis and monitoring of DFUs.

CONCLUSION

This study identified FRDEGs associated with DFUs, highlighting AURKA as a key diagnostic marker. These findings offer valuable insights into the molecular mechanisms driving DFUs and suggest potential therapeutic targets for their management.

Immunomodulatory roles of autophagic flux and IFIT in human ectocervical cells upon Trichomonas vaginalis infection

Trichomonas vaginalis (Tv) is the causative agent of trichomoniasis, the most common non-viral sexually transmitted infection worldwide. Despite its high prevalence, the mechanisms underlying Tv-induced inflammatory responses remain poorly understood. Herein, we investigated the signaling pathways mediating Tv-induced inflammation in ectocervical cells (Ects). We initially measured the production of various cytokines using a multiplex immunoassay, revealing a significant increase in IL-6, IL-8, IP-10, and CXCL1 secretion in Ects upon Tv infection. We then assessed the role of autophagy in regulating Tv-induced inflammation in Ects by using autophagy inhibitors and small interfering RNA targeting LC3B (si-LC3B) to block different stages of autophagy. Our findings indicated that Tv-induced autophagic flux mediates the secretion of proinflammatory cytokines in Ects. Additionally, blocking autophagosome formation via si-LC3B increases IL-6 and IP-10 levels while reducing IL-8 secretion. To further identify novel pathways involved in Tv-induced inflammation in Ects, we conducted a time-series proteomic analysis using 2D-LC-MS/MS. Intriguingly, we noticed robust activation of antiviral-related pathways in Ects after 8 h of Tv stimulation. Specifically, the most enriched proteins in these pathways were tetratricopeptide repeats (IFIT) family proteins (IFIT1, IFIT2, and IFIT3). Functional validation revealed that IFIT3 positively regulates downstream IL-8 and IP-10 secretion. Furthermore, we proved that si-LC3B enhanced IFIT expression in Ects upon Tv infection, suggesting that autophagy negatively regulates IFIT expression. Collectively, this study demonstrates that Tv infection induces autophagic flux and IFIT overexpression to modulate inflammatory responses in Ects, providing novel insights into the inflammatory mechanisms governing trichomoniasis.

Emission of CO2 enhanced by thiamethoxam and cadmium in agricultural soil

The coexistence of neonicotinoid insecticide thiamethoxam (TMX) and heavy metal cadmium (Cd) is quite common in agricultural soils, yet their effects on the emission of greenhouse gas CO2 remain insufficiently studied. To address this issue, microcosms spiked with singe or combined TMX (20 mg/kg) and Cd (20 mg/kg) in soil were studied for 90 days. It turned out that single TMX (+12.13 %) and Cd (+22.76 %) both stimulated the emission of CO2, and the combined TMX and Cd exhibited synergic effect (+51.00 %). The presence of Cd reduced the attenuation of TMX (-3.32 %), while the presence of TMX increased the attenuation of Cd (+3.11 %). The relative abundances of bacteria Sphingomonas, Devosia, Erythrobacter, Phaselicystis, Woeseia, FFCH7168, Rhizorhapis, Hamadaea and genes related to sugar metabolism, glycolysis and the TCA cycle were found positively correlated to CO2 emission in the studied microcosms (p < 0.05). Results from this study provide scientific basis for developing sound environmental policies that aim to reduce CO2 emission from agricultural soils.

Integrative analyses of circulating microRNA expression profile in hexavalent chromium exposed workers - A cross-sectional study within the SafeChrom project

BACKGROUND

Exposure to hexavalent chromium (Cr(VI)) can occur during occupational activities and leading lung cancer. MicroRNA (miRNA) plays an important part in carcinogenesis. Whether Cr(VI) exposure causes cancer-related miRNA changes is yet uncharacterized.

METHODS

This study included 89 Cr(VI) exposed workers and 47 controls. MiRNAs were extracted from plasma followed by library preparations, miRNA sequencing, and differentially expressed miRNAs (DEMs) analysis. To understand the underlying biological functions, we used bioinformatics approaches, and qPCR was performed to validate the expression of potential target genes.

RESULTS

A total of 2100 miRNAs were detected. In the exposed workers, 59 DEMs were identified: 21 up-regulated and 38 down-regulated. Target genes for both up- and down-regulated DEMs were significantly enriched in: miRNAs in cancer, small cell lung cancer and non-small cell lung cancer. Protein-protein interactions showed a high number of interactions, in which CCNE2, CDK4 and E2F1 were predicted as hub genes, and the messenger RNA expression of those genes was significantly higher in the exposed workers compared with controls.

CONCLUSIONS

Our study suggests that low-to-moderate Cr(VI) exposure results in differential expression of lung-cancer-related miRNAs and associated target genes. Further studies are needed to validate our findings and clarify whether these changes predict cancer risk.

Investigating the molecular mechanism of purslane‑based vitiligo treatment using network pharmacology, molecular docking and in vitro analyses

Purslane is a traditional Chinese medicine with a long‑standing history of efficacy in the management of dermatological conditions such as vitiligo. However, the molecular mechanisms underlying its therapeutic effects on vitiligo remain unclear. Therefore, the present study explored these mechanisms using network pharmacology, molecular docking and in vitro experiments. Following the screening process, seven principal active components were identified, namely kaempferol, hesperetin, luteolin, quercetin, arachidonic acid, cycloartenol and β‑sitosterol. In addition, six key targets, namely AKT1, tumor protein p53, peroxisome proliferator‑activated receptor γ (PPARG), estrogen receptor 1, prostaglandin‑endoperoxidase synthase 2 and mitogen‑activated protein kinase 1, and eight pathways in purslane‑based vitiligo treatment were identified. Network pharmacology and molecular docking demonstrated that flavonoids are the key components of purslane likely to mitigate oxidative stress damage in vitiligo. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the phosphatidylinositol 3‑kinase (PI3K)/AKT, p53 and PPARG signaling pathways are associated with purslane components and vitiligo. In vitro experiments revealed that purslane total flavones (PTF) increased cell viability, decreased ROS levels and increased antioxidant enzyme activities in H2O2‑induced B16F10 cells. In addition, PTF activated the PI3K/AKT signaling pathway in H2O2‑induced B16F10 cells, and the antioxidant effect of PTF was attenuated by a PI3K/AKT inhibitor. In conclusion, the findings of the present study suggest that the flavonoids of purslane contribute, at least in part, to its therapeutic effectiveness in vitiligo by mitigating oxidative stress in melanocytes through the PI3K/AKT signaling pathway.

Investigation and validation of genes associated with endoplasmic reticulum stress in diabetic retinopathy using various machine learning algorithms

BACKGROUND

Diabetic retinopathy (DR) is a common complication of diabetes, with Endoplasmic reticulum stress (ERS) playing a key role in cellular adaptation, injury, or apoptosis, impacting disease pathology. This study aimed to identify early diagnostic markers for personalized DR treatment.

METHODS

DR and healthy control (HC) samples were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed ERS-related genes (DE-ERSRGs) were identified, and machine learning algorithms were used to pinpoint DR-specific feature DE-ERSRGs (FDE-ERSRGs). Diagnostic accuracy was assessed using ROC curve analysis. Further analyses included differential expression, co-expression, GO functional, KEGG pathway enrichment, and immune cell infiltration profiling in DR.

RESULTS

A total of 55 DE-ERSRGs were initially identified, and after further analysis, two key FDE-ERSRGs, SELENOS and heat shock protein family A member 5 (HSPA5), were highlighted due to their robust differential expression patterns between DR and healthy controls. Both genes exhibited high diagnostic potential, with AUC values of 0.792 and 0.799, respectively, indicating their promise as biomarkers for DR. Additionally, we examined the differential and co-expression patterns of DE-ERSRGs between high- and low-expression groups. We investigated the molecular functions and biological pathways associated with DR, analyzed immune cell infiltration differences between DR and HC groups, and assessed their correlation with FDE-ERSRGs.

CONCLUSIONS

Our findings provide new insights into the molecular mechanisms and metabolic pathways involved in DR, potentially paving the way for the identification of novel diagnostic and immunotherapeutic biomarkers.

Telomere-to-telomere gap-free genome assembly provides genetic insight into the triterpenoid saponins biosynthesis in Platycodon grandiflorus

Platycodon grandiflorus has been widely used in Asia as a medicinal herb and food because of its anti-inflammatory and hepatoprotective properties. P. grandiflorus has important clinical value because of the active triterpenoid saponins in its roots. However, the biosynthetic pathway of triterpenoid saponins in P. grandiflorus remains unclear, and the related genes remain unknown. Therefore, in this study, we assembled a high-quality and integrated telomere-to-telomere P. grandiflorus reference genome and combined time-specific transcriptome and metabolome profiling to identify the cytochrome P450s (CYPs) responsible for the hydroxylation processes involved in triterpenoid saponin biosynthesis. Nine chromosomes were assembled without gaps or mismatches, and nine centromeres and 18 telomere regions were identified. This genome eliminated redundant sequences from previous genome versions and incorporated structural variation information. Comparative analysis of the P. grandiflorus genome revealed that P. grandiflorus underwent a core eudicot γ-WGT event. We screened 211 CYPs and found that tandem and proximal duplications may be crucial for the expansion of CYP families. We outlined the proposed hydroxylation steps, likely catalyzed by the CYP716A/72A/749A families, in platycodin biosynthesis and identified three PgCYP716A, seven PgCYP72A, and seven PgCYP749A genes that showed a positive correlation with platycodin biosynthesis. By establishing a T2T assembly genome, transcriptome, and metabolome resource for P. grandiflorus, we provide a foundation for the complete elucidation of the platycodins biosynthetic pathway, which consequently leads to heterologous bioproduction, and serves as a fundamental genetic resource for molecular-assisted breeding and genetic improvement of P. grandiflorus.

Serum metabolites and inflammation predict brain functional connectivity changes in Obsessive-Compulsive disorder

Currently, our understanding of the metabolic and immune pathways involved in obsessive-compulsive disorder (OCD), as well as the precise mechanisms by which metabolism and immunity impact brain activity and function, is limited. This study aimed to examine the alterations in serum metabolites, inflammatory markers, brain activity, and brain functional connectivity (FC) among individuals with OCD and investigate the relationship between these factors. The study included 55 individuals with moderate-to-severe OCD (either drug-naïve or not taking medication for at least eight weeks) and 54 healthy controls (HCs). The High-Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS) technique was used to detect serum metabolites, whereas the enzyme-linked immunosorbent assay (ELISA) was utilized to identify inflammatory markers. The FC of the brain was investigated using resting-state functional magnetic resonance immaging(rs-fMRI). The findings demonstrated that individuals with OCD exhibited significant alterations in 11 metabolites compared to HCs. In particular, 10 of these metabolites exhibited an increase, while one metabolite displayed a decrease. Additionally, individuals with OCD experienced a marked elevation in the levels of five inflammatory factors (TNF-α, IL-1β, IL-2, IL-6, and IL-12). Rs-fMRI analysis revealed that individuals with OCD exhibited atypical FC in various brain regions, such as the postcentral gyrus, angular gyrus, and middle temporal gyrus. These specific brain areas are closely associated with sensory-motor processing, cognitive control, and emotion regulation. Further stepwise multiple regression analysis revealed that serum metabolite levels, particularly phosphatidylcholine, and inflammatory markers such as IL-1β could predict alterations in brain FC among individuals diagnosed with OCD. In summary, this study uncovered that individuals with OCD exhibit alterations in serum metabolites, inflammatory markers, brain activity, and FC. The findings suggest that these metabolites and inflammatory markers might play a role in the development and progression of OCD by affecting brain activity and the FC of neural networks.

Network-Based Integrative Analysis to Identify Key Genes and Corresponding Reporter Biomolecules for Triple-Negative Breast Cancer

BACKGROUND

The malignant neoplasm of the TNBC is the leading cause of death among Indian women. Recent studies identified the global burden of TNBC affecting approximately more than 40 percent of all BC cases in women worldwide. The absence of expression of receptors such as ER, PR, and HER2 characterizes TNBC.

OBJECTIVES

Due to the lack of specific targets, standard treatment options for TNBC are limited. This integrative study aims to identify key genes and provide insights into the underlying molecular mechanisms of TNBC, which can potentially lead to the development of more effective therapeutic strategies.

MATERIAL AND METHODOLOGY

This study integrates PPI and WGCNA analysis of TNBC-related datasets (GSE52194 and GSE58135) to identify key genes. Subsequently, downstream analysis is conducted to explore potential therapeutic targets for TNBC.

RESULTS

The present study renders the potential 13 key genes (PLCG2, CXCL10, CDK1, STAT1, IL6, PLK1, CCNB1, AURKA, NDC80, EGFR, 1L1B, FN1, BUB1B), along with their associated 6 TFs and 20 miRNAs, as reporter biomolecules around which the most significant changes occur. There were some miRNAs hsa-mir-449b-5p, hsa-let-7b-5p, hsa-mir-26a-5p, hsa-mir-155-5p, hsa-mir-24-3p, hsa-mir-212-3p, hsa-mir-21-5p, hsa-mir-210-3p and hsa-mir-20a-5p whose association with other cancers and other BC subtypes have been reported but their association with TNBC need to be explored. Further, enrichment and cumulative survival analysis support the disease association of identified key genes with TNBC.

CONCLUSION

This integrative analysis could be regarded for experimental inspection as it provides the platform for future researchers in drug designing and biomarker discovery for TNBC diagnosis and treatment.

Untargeted metabolomics reveals novel metabolites in Lotus japonicus roots during arbuscular mycorrhiza symbiosis

Arbuscular mycorrhiza (AM) improves mineral nutrient supply, stress tolerance, and growth of host plants through re-programing of plant physiology. We investigated the effect of AM on the root secondary metabolome of the model legume Lotus japonicus using untargeted metabolomics. Acetonitrile extracts of AM and control roots were analysed using ultra-high-performance liquid chromatography-electrospray ionization-ion mobility-time-of-flight-mass spectrometry (UPLC-ESI-IM-ToF-MS). We characterized AM-regulated metabolites using co-chromatography with authentic standards or isolation and structure identification from L. japonicus roots using preparative high-performance liquid chromatography and nuclear magnetic resonance spectroscopy. Arbuscular mycorrhiza triggered major changes in the root metabolome, with most features representing unknown compounds. We identified three novel polyphenols: 5,7-dihydroxy-4'-methoxycoumaronochromone (lotuschromone), 4-hydroxy-2-(2'-hydroxy-4'-methoxyphenyl)-6-methoxybenzofuran-3-carbaldehyde (lotusaldehyde), and 7-hydroxy-3,9-dimethoxypterocarp-6a-ene (lotuscarpene). Further AM-enhanced secondary metabolites included the previously known lupinalbin A and B, ayamenin D, biochanin A, vestitol, acacetin, coumestrol, and betulinic acid. Lupinalbin A, biochanin A, ayamenin D, liquiritigenin, isoliquiritigenin, lotuscarpene, medicarpin, daidzein, genistein, and 2'-hydroxygenistein inhibited Rhizophagus irregularis spore germination upon direct application. Our results show that AM enhances the production of polyphenols in L. japonicus roots and highlights a treasure trove of numerous unknown plant secondary metabolites awaiting structural identification and functional characterization.

Intervention effects of greenspace exposure on human microbiota: A randomized controlled trial in Chinese young adults

Enriching human microbiota has been proposed as a mechanism by which greenspace exposure improves human health. The existing evidence is scarce with few studies able to evaluate causality. We conducted a randomized controlled trial of 30 healthy undergraduate students to explore the intervention effects of greenspace on human gut and oral microbiota alpha-diversity, composition, differential genera and functional pathways. The study participants were divided into three groups, including outdoor greenspace (GS) group, outdoor non-greenspace (NGS) group, and indoor group, who visited a park, an open space without vegetation, and a classroom, respectively, for two hours per day over seven days. Differences in microbial alpha-diversity and composition across various groups were tested using Wilcoxon test and permutational multivariate analysis of variance, respectively. Linear discriminant analysis effect size analysis was performed to test differences in genera and functional pathways. Greenspace intervention significantly increased gut microbiota alpha-diversity, especially the observed Amplicon Sequence variant indexes and the Faith indexes (both p < 0.05). In addition, the intervention substantially changed the composition of gut microbiota, of which the relative abundances of potentially beneficial bacteria increased. Further, the greenspace intervention affected several functional pathways of gut microbiota, including "substance dependence", "specific types of cancer", and "viral infectious diseases". However, we did not find any significant effect of greenspace intervention on oral microbiota. Our results suggest that greenspace intervention diversifies the gut microbiota and alters its composition. These findings could help to reinforce the potential of increasing people's access to greenspace as a public health intervention.

Disentangling a genome-wide mosaic of conflicting phylogenetic signals in Western Rattlesnakes

Species tree inference is often assumed to be more accurate as datasets increase in size, with whole genomes representing the best-case-scenario for estimating a single, most-likely speciation history with high confidence. However, genomes may harbor a complex mixture of evolutionary histories among loci, which amplifies the opportunity for model misspecification and impacts phylogenetic inference. Accordingly, multiple distinct and well-supported phylogenetic trees are often recovered from genome-scale data, and approaches for biologically interpreting these distinct signatures are a major challenge for evolutionary biology in the age of genomics. Here, we analyze 32 whole genomes of nine taxa and two outgroups from the Western Rattlesnake species complex. Using concordance factors, topology weighting, and concatenated and species tree analyses with a chromosome-level reference genome, we characterize the distribution of phylogenetic signal across the genomic landscape. We find that concatenated and species tree analyses of autosomes, the Z (sex) chromosome, and mitochondrial genome yield distinct, yet strongly supported phylogenies. Analyses of site-specific likelihoods show additional patterns consistent with rampant model misspecification, a likely consequence of several evolutionary processes. Together, our results suggest that a combination of historic and recent introgression, along with natural selection, recombination rate variation, and cytonuclear co-evolution of nuclear-encoded mitochondrial genes, underlie genome-wide variation in phylogenetic signal. Our results highlight both the power and complexity of interpreting whole genomes in a phylogenetic context and illustrate how patterns of phylogenetic discordance can reveal the impacts of different evolutionary processes that contribute to genome-wide variation in phylogenetic signal.

A Novel Neutrophil Extracellular Trap Signature Predicts Patient Chemotherapy Resistance and Prognosis in Lung Adenocarcinoma

Chemoresistance is a key obstacle in the long-term survival of patients with locally and advanced lung adenocarcinoma (LUAD). This study used bioinformatic analysis to reveal the chemoresistance of gene-neutrophil extracellular traps (NETs) associated with LUAD. RNA sequencing data and LUAD expression patterns were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, respectively. The GeneCards database was used to identify NETosis-related genes (NRGs). To identify hub genes with significant and consistent expression, differential analysis was performed using the TCGA-LUAD and GEO datasets. LUAD subtypes were determined based on these hub genes, followed by prognostic analysis. Immunological scoring and infiltration analysis were conducted using NETosis scores (N-scores) derived from the TCGA-LUAD dataset. A clinical prognostic model was established and analyzed, and its clinical applications explored. Twenty-two hub genes were identified, and consensus clustering was used to identify two subgroups based on their expression levels. The Kaplan-Meier (KM) curves demonstrated statistically significant differences in prognosis between the two LUAD subtypes. Based on the median score, patients were further divided into high and low N-score groups, and KM curves showed that the N-scores were more precise at predicting the prognosis of patients with LUAD for overall survival (OS). Immunological infiltration analysis revealed significant differences in the abundances of 10 immune cell infiltrates between the high and low N-score groups. Risk scores indicated significant differences in prognosis between the two extreme score groups. The risk scores for the prognostic model also indicated significant differences between the two groups. The results provide new insights into NETosis-related differentially expressed genes (NRDEGs) associated with chemotherapy resistance in patients with LUAD. The established prognostic model is promising and could help with clinical applications to evaluate patient survival and therapeutic efficiency.

Precision nutrition: Is tailor‑made dietary intervention a reality yet? (Review)

Precision nutrition (PN) is an emerging field of science recognizing the variability in how individuals respond to different nutrients, driven by their unique biological makeup. The central aim of PN is to tailor dietary interventions to improve individual health, prevent disease and manage existing health conditions based on specific biological characteristics. The present review aimed to provide an overview of available multi-omics platforms that can be applied to extracting data from biological materials in the context of PN. Additionally, it proposed an updated pipeline for handling and integrating these data. A comprehensive search of academic publications was conducted across multiple databases, focusing on recent advances in PN, including its challenges and opportunities. Following this preparatory step, a data handling protocol for different omics layers was compiled to develop an up-to-date multi-omics pipeline applicable to PN. The successful implementation of PN requires a systems-level understanding of human physiological networks, their plasticity, variations in response to dietary exposures and the ability to classify population subgroups based on their nutritional needs. The realization of PN may currently seem distant due to several limitations such as the lack of ongoing large-scale epidemiological studies, challenges in database curation, the high cost of omics analysis and ethical concerns. A key advancement to this field would be the development of next-generation biomarkers connecting nutrition to chronic diseases. These biomarkers would help classify individuals at risk of diet-related conditions and quantify the dose-response relationships between individuals or groups of interacting nutrients and the onset and progression of diseases.

Effect of miR-10a on the proliferation and differentiation of yak adipocyte precursors

The fat content of yak meat is significantly correlated with the meat quality, and an appropriate fat content helps to improve the texture of the meat. The involvement of miR-10a in regulating the differentiation and proliferation of various cell types has been reported. Therefore, in this study, the effects of miR-10a on lipid droplet accumulation were investigated by transfection of yak adipocyte precursors with an miR-10a inhibitor, followed by Oil Red O, BODIPY, EdU staining, and cell cycle analysis of the transfected and control cells. The relative expression of lipogenic marker genes was determined by RT-qPCR to clarify the effect of miR-10a on the differentiation and proliferation of yak adipocyte precursors. Mature adipocytes were collected for transcriptome analysis to identify differentially expressed target genes and the association of these genes with adipogenic pathways was investigated by GO and KEGG enrichment analyses. In addition, the phylogeny and expression profiles of miR-10a were analyzed in various yak tissues. The results showed that miR-10a could inhibit the differentiation and promote the proliferation of yak adipocyte precursors. Analysis of the RNA-Seq results showed that miR-10a inhibitor and inhibitor NC had six differentially expressed genes: FABP4, AKR1B7, IGF2, ROCK1, IFNB1, and PLA2G3. These genes were found to be involved in the regulation of adipogenesis, with IGF2 and IFNB1 being upregulated in the PI3K-Akt signaling pathway, which is activated upon stimulation by IGF2 and IFNB1 and inhibits the differentiation and promotes the proliferation of yak adipocytes precursor, which in turn affected adipogenesis. Moreover, phylogenetic analysis indicated that miR-10a evolved relatively recently in yak and sheep, while tissue expression profiles showed that miR-10a was highly expressed in yak lung tissues.

CD44 is a nexus between prognosis and therapeutics for brain cancer management

BACKGROUND

Brain tumors, both primary and metastatic, are the main cause of cancer-associated mortality leading to patients' poor quality-of-life that remain as a global challenge. This study aims to identify the hub molecular controlling brain cancer progression, and establish corresponding prognostic index and therapeutic modality for improved brain cancer management.

METHOD

We performed pan-cancer analysis unifying 9 publicly available datasets of cancers metastasized to the brain from different organs to identify the hub gene feasible for brain cancer prognosis. We conducted a series of computational analysis of the identified hub gene in primary gliomas to assess its diagnostic value. We investigated the potency and safety of cold atmospheric plasma (CAP) in treating brain cancers via targeting this hub molecule both in vitro and in vivo using glioma cells as the disease model.

RESULTS

We identified CD44 as the nexus of brain cancer prognosis and therapeutics that should be applicable to both primary and metastatic brain cancers. We, in addition, constructed a CD44-dependent unified index for brain cancer overall survival prognosis; and proposed CAP as a highly promising approach for arresting brain cancers via targeting CD44.

CONCLUSIONS

We are the first to characterize the relevance of CD44 with brain cancers by integrating its values on prognosis and therapeutics, as well as unifying its application scenarios in primary and metastatic brain cancers. Our work may spark innovative theranostic design for improved brain cancer management besides solutions provided by this study.

TriDeNT : Triple deep network training for privileged knowledge distillation in histopathology

Computational pathology models rarely utilise data that will not be available for inference. This means most models cannot learn from highly informative data such as additional immunohistochemical (IHC) stains and spatial transcriptomics. We present TriDeNT , a novel self-supervised method for utilising privileged data that is not available during inference to improve performance. We demonstrate the efficacy of this method for a range of different paired data including immunohistochemistry, spatial transcriptomics and expert nuclei annotations. In all settings, TriDeNT outperforms other state-of-the-art methods in downstream tasks, with observed improvements of up to 101%. Furthermore, we provide qualitative and quantitative measurements of the features learned by these models and how they differ from baselines. TriDeNT offers a novel method to distil knowledge from scarce or costly data during training, to create significantly better models for routine inputs.

The genomic insights of intertidal adaptation in Bryopsis corticulans

Many marine green algae thrive in intertidal zones, adapting to complex light environments that fluctuate between low underwater light and intense sunlight. Exploring their genomic bases could help to comprehend the diversity of adaptation strategies in response to environmental pressures. Here, we developed a novel and practical strategy to assemble high-confidence algal genomes and sequenced a high-quality genome of Bryopsis corticulans, an intertidal zone macroalga in the Bryopsidales order of Chlorophyta that originated 678 million years ago. Comparative genomic analyses revealed a previously overlooked whole genome duplication event in a closely related species, Caulerpa lentillifera. A total of 100 genes were acquired through horizontal gene transfer, including a homolog of the cryptochrome photoreceptor CRY gene. We also found that all four species studied in Bryopsidales lack key photoprotective genes (LHCSR, PsbS, CYP97A3, and VDE) involved in the xanthophyll cycle and energy-dependent quenching processes. We elucidated that the expansion of light-harvesting antenna genes and the biosynthesis pathways for siphonein and siphonaxanthin in B. corticulans likely contribute to its adaptation to intertidal light conditions. Our study unraveled the underlying special genetic basis of Bryopsis' adaptation to intertidal environments, advancing our understanding of plant adaptive evolution.

Haplotype-resolved genome of Agastache rugosa (Huo Xiang) provides insight into monoterpenoid biosynthesis and gene cluster evolution

Monoterpenoids are small volatile molecules produced by many plants that have applications in consumer products and healthcare. Plants from the mint family (Lamiaceae) are prodigious producers of monoterpenoids, including a chemotype of Agastache rugosa (Huo Xiang), which produces pulegone and isomenthone. We sequenced, assembled and annotated a haplotype-resolved chromosome-scale genome assembly of A. rugosa with a monoterpene chemotype. This genome assembly revealed that pulegone biosynthesis genes are in a biosynthetic gene cluster, which shares a common origin with the pulegone gene cluster in Schizonepeta tenuifolia. Using phylogenetics and synteny analysis, we describe how the clusters in these two species diverged through inversions and duplications. Using Hi-C analysis, we identified tentative evidence of contact between the pulegone gene cluster and an array of pulegone reductases, with both regions also enriched in retrotransposons. This genome and its analysis add valuable and novel insights to the organization and evolution of terpenoid biosynthesis in Lamiaceae.

Microbiota modulation and microbial metabolites produced during the in vitro colonic fermentation of Psidium guajava species

The interaction between gut microbiota and its metabolites is a growing area of research. Therefore, this study analyzed the bioactive compound profile of the indigestible fraction (IF) from Psidium species and evaluated its effects on microbiota composition during in vitro colonic fermentation. Hydroxycinnamic acids, hydroxybenzoic acids, and ellagitannins were the predominant phenolic compounds, with P. friedrichsthalianum ('Cas') exhibiting the highest concentrations. During in vitro colonic fermentation, a reduction in bacterial genera such as Enterobacteriaceae and Klebsiella was observed, while Faecalibacterium, Oscillibacter, Dialister, and Ruminococcaceae positively correlated with phenolic microbial metabolites. These findings suggest that the IF of Psidium species modulates gut microbiota composition and potentially contributes to the production of beneficial metabolites during human colonic fermentation, reinforcing the role of whole fruit consumption as a comprehensive matrix of nutrients and bioactive compounds beneficial to gut health.

Downregulating FGGY carbohydrate kinase domain containing promotes cell senescence by activating the p53/p21 signaling pathway in colorectal cancer

Carbohydrate kinases serve an oncogenic role in several types of cancer; however, the function of FGGY carbohydrate kinase domain containing (FGGY) in colorectal cancer (CRC) remains unknown. The present study investigated the function and possible molecular mechanisms of FGGY in CRC. The results showed that elevated levels of FGGY mRNA and protein were observed in CRC tissues, and a higher expression of FGGY was associated with advanced N stage and reduced overall survival time in patients with CRC. Silencing FGGY inhibited the viability of CRC cells by inducing cell cycle arrest and promoting apoptosis in vitro, thereby attenuating tumor growth in a xenograft mouse model. FGGY knockdown also enriched the senescence‑associated heterochromatin foci (SAHF) pathway and p53 pathway, as further confirmed by enhancing senescence‑associated β‑galactosidase (SA‑β‑gal) activity, with increased levels of SAHF‑associated proteins HP1γ and trimethylation of H3K9 (H3k9me3) in CRC cells, as well as upregulation of p53 and its downstream protein p21. Furthermore, p53 knockout rescued FGGY knockdown‑mediated reductions in cell viability, SA‑β‑gal activity, and the levels of HP1γ and H3k9me3 in CRC cells. These findings indicated that FGGY could act as a newly identified potential oncogene in CRC, partially through regulating the p53/p21 signaling pathway and altering cell senescence.