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PubMed2025

Comprehensive genomic analysis of antibiotic resistance plasmids in animal-associated Staphylococcus aureus in France.

UNLABELLED: In Staphylococcus aureus, an animal pathogen and zoonotic agent, plasmids play a pivotal role in the acquisition and spread of antibiotic resistance genes (ARGs). This study investigated the plasmid content of 329 S. aureus isolates from livestock and companion animals collected in France between 2010 and 2021. Plasmids (n = 211) were identified from 139 isolates. The major families identified-rep7a, rep20, and rep10-were associated with specific resistance genes (str, cat, blaZ, erm(C)) and exhibited widespread horizontal transfer across different S. aureus sequence types (STs) and animal hosts. In temporal analysis, the rep7a/str and rep7a/cat plasmids circulating in horses were progressively replaced by a rep7a plasmid carrying both str and cat genes. The study also highlighted the presence of mosaic plasmids, which combined elements from different bacterial species/genera, confirming the broad host range of S. aureus plasmids and their ability to acquire ARGs from diverse sources. Moreover, the occurrence of hybrid plasmids (carrying multiple rep genes) underscores the plasticity of these vectors of ARGs. This study emphasizes the need to investigate the mechanisms driving the spread and persistence of antibiotic-resistant plasmids in S. aureus, with a view to developing strategies aimed at combating antibiotic resistance. IMPORTANCE: The spread of antibiotic resistance in Staphylococcus aureus is a growing concern, particularly in animals that can serve as reservoirs for resistant strains. This study highlights the crucial role of plasmids in transmitting resistance genes among different animal hosts and S. aureus lineages. The characterization of 329 isolates collected over 10 years revealed how certain plasmid families are associated with specific resistance genes and how they evolve over time. The occurrence of mosaic and hybrid plasmids further underscores the ability of S. aureus to acquire resistance from diverse bacterial sources. These findings provide key insights into the mechanisms shaping antibiotic resistance in this pathogen and emphasize the fact that understanding plasmid-driven resistance is essential for developing effective interventions to limit the spread of multidrug-resistant S. aureus in both veterinary and human medicine.

Animals↗

PubMed2026

Comprehensive Genomic Analysis of Normal and Cancer Cells Elucidates the Elevated Mutation Burden in Cancer.

Self-renewing normal tissues generate several somatic mutations at each division. Previous studies have reported that cancer cells have more mutations than their normal counterparts. It is not obvious why dramatic differences in mutation burdens between normal tissues and cancers should exist. To fully understand human tumorigenesis, the increase of mutation burden in cancers will have to be understood. Here, we provided a systematic comparison of mutational burdens in normal and cancer cells from five different organs, revealing a four-fold increase of mutation burdens in cancerous vs. non-cancerous cells. Three proposed hypotheses that could account for the increased mutation burdens in cancer are: the classical hypothesis, where driver gene mutations explain the higher mutational burden; the catastrophic hypothesis, where extreme mutational events lead to large-scale genomic alterations; and the tail hypothesis, where differences in baseline mutation rates among individuals account for the differences. Testing through orthogonal observations showed that the observed medians and distributions of mutation burdens in cancers could be explained by the hypotheses to various degrees of significance, and only the tail hypothesis could easily explain the increase in median mutation burdens in the normal tissues of cancer patients compared to the normal tissues of non-cancer patients. Overall, this study characterizes an increased mutation burden across multiple types of cancer compared to normal tissue and provides insights into the contributing factors. A tenable hypothesis proposed in this study involving fundamental differences in baseline mutation rates among individuals could have implications for cancer prevention strategies.

Journal Article↗

PubMed2025

Identification of potential biomarkers and mechanisms for keloid disorder based on comprehensive bioinformatics analysis and machine learning algorithms.

BACKGROUND: Keloid disorder (KD) encompasses a spectrum of fibroproliferative dermal conditions, the pathogenesis remains complex and incompletely understood. This study sought to identify biomarkers and potential therapeutic targets for KD through an integrative bioinformatics approach and machine learning analysis of RNA sequencing data. METHODS: RNA sequencing was performed on skin tissue samples from 13 patients with KD and 14 healthy controls. Using weighted gene co-expression network analysis and differential expression analysis revealed differentially expressed key module genes, and the CytoHubba plugin identified candidate genes. Subsequently analyzed using least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) methods to pinpoint feature genes associated with KD. Following this, biomarkers were determined through expression level validation, enrichment analysis, and immune infiltration analysis. RESULTS: A total of 420 differentially expressed key module genes were identified, and the top 10 genes with DMNC values were selected as candidate genes. Five feature genes were selected through LASSO and SVM-RFE, with NID2, MFAP2, COL8A1, and P4HA3 showing significant expression differences between KD and control samples, along with consistent expression patterns across datasets, identified as potential biomarkers. These four biomarkers were proved to possess high diagnostic potential, and they were found to exhibit significant positive correlations with one another. Functional enrichment analysis indicated that the primary KEGG pathways associated with these biomarkers included "steroid hormone biosynthesis" and "cytokine-cytokine receptor interaction." Moreover, immune infiltration analysis revealed that the four biomarkers were negatively correlated with type 17 T helper cells and positively correlated with 15 immune cell types, including activated B cells and central memory CD4 T cells. CONCLUSION: In conclusion, NID2, MFAP2, COL8A1, and P4HA3 were identified as key biomarkers for KD, offering new avenues for more targeted and effective diagnostic and therapeutic strategies for managing this condition.

Humans↗

PubMed2026

Shared Genetic Basis, Biological Function and Causal Relationship Between Sleep Traits and Hypothyroidism: Evidence from a Comprehensive Genetic Analysis.

BACKGROUND: This research attempts to clarify whether there are any genetic similarities between sleep traits and hypothyroidism based on publicly accessible large-scale genomewide association studies. METHODS: The methodology included colocalization analysis, cross-phenotype association analysis, and linkage disequilibrium score regression analysis to find common genetic overlap. Through tissue function specificity and functional mapping, we were able to identify the shared genetic level. Genetic instrumental factors were used for causal inference in two-sample univariate and multivariable Mendelian randomization analyses. RESULTS: A hereditary correlation between hypothyroidism and napping during the day and getting up in the morning (rg= -0.0982, P= 0.0007; rg= -0.101, P= 0.0001). MAGI3, and HLA-DRB1 BX296568.1 may be potential targets for shared treatments. Colocalization and tissue-specific analysis demonstrated that the common genes and SNPs were identified in the thyroid, lung, brain, and lymphatic tissues. Functional analysis emphasized the importance of these common genes in processes like as protein transport, inflammatory response, and MHC class II protein synthesis. Furthermore, an association has been established between hypothyroidism and sleep duration (IVW, OR 1.5208; 95% CI 1.1142-2.0758, P=0.0082) and getting up in the morning (IVW, OR 1.8375; 95%CI: 1.4502-2.3284, P=4.73E-07). Furthermore, the reverse MR analysis revealed no causal connection between aberrant sleep traits and hypothyroidism. The enduring impact of insomnia on hypothyroidism persists despite controlling for alcohol consumption and smoking habits. CONCLUSION: Certain genetic correlations between sleep traits and hypothyroidism have been emphasized. These findings may elucidate the origin of comorbidity and have implications for future clinical trials.

Humans↗

PubMed2026

[Comparative analysis of comprehensive treatment outcomes in patients with chronic bacterial prostatitis with the addition of the multicomponent complex AndrOPREN].

INTRODUCTION: Type II chronic bacterial prostatitis is characterized by persistent infection, insufficient efficacy of standard therapy, and a high recurrence rate, which necessitates the search for additional treatment options. AIM: To evaluate the efficacy and safety of adding the multicomponent complex AndrOPREN to comprehensive therapy for type II chronic bacterial prostatitis. MATERIALS AND METHODS: This prospective, comparative, randomized study included 233 patients allocated to the main group (n=126) and the control group (n=107). In both groups, patients received standard therapy; men in the main group additionally received the multi-ingredient complex AndrOPREN at a dose of two capsules of No. 1 and two capsules of No. 2 daily for 1-2 months. The follow-up period was 60 days. Changes in symptoms according to the IPSS and QoL scores, urinalysis parameters, microscopy findings of expressed prostatic secretions, pathogen eradication, and biochemical safety parameters were assessed. RESULTS: Improvement was observed in both groups and was more pronounced in the main group. By day 14, the median IPSS score was 14.0 [12.0; 16.0] vs. 18.0 [15.0; 20.0] in the control group (p<0.001); by day 60, the corresponding values were 7.0 [5.0; 9.0] and 11.0 [9.0; 13.0] (p<0.001). At the end of follow-up, the QoL score was 2.0 [1.0; 2.0] and 3.0 [2.0; 3.0], respectively. No microbial growth was detected in 91.2% and 80.4% of patients, respectively (p=0.026); Escherichia coli eradication was achieved in 91.7% and 76.9%, respectively. No biochemical changes indicative of nephrotoxicity or hepatotoxicity were detected. DISCUSSION: The addition of the multicomponent complex AndrOPREN was associated with more rapid symptom resolution, a reduction in inflammatory changes, restoration of the secretory function of the prostate, and greater microbiological efficacy. CONCLUSION: The addition of the multicomponent complex AndrOPREN to comprehensive therapy for type II chronic bacterial prostatitis improves treatment efficacy while maintaining a favorable safety profile.

Humans↗

PubMed2025

CoDIAC: A comprehensive approach for interaction analysis reveals novel insights into SH2 domain function and regulation.

Protein domains are conserved structural and functional units that serve as building blocks of proteins. Through evolutionary expansion, domain families are represented by multiple members in diverse configurations with other domains, evolving new specificities for their interacting partners. Here, we develop a structure-based interface analysis to comprehensively map domain interfaces from experimental and predicted structures, including interfaces with macromolecules and intraprotein interfaces. We hypothesized that comprehensive contact mapping of domains could yield new insights into domain selectivity, conservation of domain-domain interfaces across proteins, and identify conserved post-translational modifications (PTMs), relative to interaction interfaces, allowing for the inference of specific effects due to PTMs or mutations. We applied this approach to the human SH2 domain family, a modular unit central to phosphotyrosine-mediated signaling, identifying a novel approach to understanding binding selectivity and evidence of coordinated regulation of SH2 domain binding interfaces by tyrosine and serine/threonine phosphorylation and acetylation. These findings suggest multiple signaling systems can regulate protein activity and SH2 domain interactions in a coordinated manner. We provide the extensive features of the human SH2 domain family and this modular approach as an open source Python package for COmprehensive Domain Interface Analysis of Contacts (CoDIAC).

SH2 domains↗

PubMed2025

Using Callus as an Ex Vivo System for Chromatin Analysis.

Next-generation sequencing has revolutionized epigenetics research, enabling a comprehensive analysis of DNA methylation and histone modification profiles to explore complex biological systems at unprecedented depth. Deciphering the intricate epigenetic mechanisms that regulate gene activity presents significant challenges, including the issue of analyzing heterogeneous cell populations in bulk. Bulk analysis introduces bias and can obscure crucial information by averaging readouts from distinct cells. Various approaches have been developed to address this issue, such as cell-type-specific enrichment or single-cell sequencing techniques. However, the need for transgenic lines with fluorescent markers, along with technical challenges such as efficient protoplast isolation and low yield, limits their widespread adoption and use in multi-omic studies. This review discusses the pros and cons of these approaches, providing a valuable basis for selecting the most suitable strategy to minimize heterogeneity. We will also highlight the use of cotyledon-derived callus as an ex vivo system as a simple, accessible, and robust platform for enabling high-throughput multi-omic analyses.

Chromatin↗

PubMed2026

Non-small cell lung cancer and tumor-educated platelets: screening of biomarkers and construction of a prognostic model.

BACKGROUND: Lung cancer is a leading cause of cancer-related mortality worldwide, emphasizing the urgent need for effective early detection strategies. Traditional Chinese medicine (TCM) provides a unique perspective on tumor pathogenesis, focusing on concepts such as "long-term stasis leading to accumulation". Tumor-educated platelets (TEPs) offer potential as biomarkers due to their ability to reflect cancer heterogeneity and facilitate less invasive diagnostic approaches. This study aims to identify TEP-related prognostic biomarkers for non-small cell lung cancer (NSCLC) and to construct and validate a multigene prognostic model by integrating platelet transcriptomic data with tumor tissue datasets. METHODS: We performed comprehensive analysis of gene expression datasets obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories to characterize transcriptomic differences among lung cancer specimens, normal tissue samples, and TEPs. Using R software, we identified Differentially expressed genes (DEGs) and subsequently applied a multi-stage analytical pipeline to TEP-associated DEGs, incorporating univariate Cox proportional hazards regression, least absolute shrinkage and selection operator (LASSO) regression, multivariate Cox regression, and stepwise regression modeling to pinpoint genes with prognostic significance. These prognostically relevant genes served as the foundation for developing a risk stratification model. We computed individual risk scores across both training and validation cohorts, enabling patient stratification into high- and low-risk categories. Model robustness was assessed through internal cross-validation and external validation procedures, while predictive performance was quantified using risk calibration metrics and receiver operating characteristic (ROC) curve analysis. RESULTS: Through systematic bioinformatics screening, we identified a four-gene prognostic signature comprising NELL2, C4orf48, PRAM1, and KLHL35, which served as the foundation for developing our risk stratification algorithm. Rigorous internal cross-validation and external cohort validation substantiated the moderate predictive performance of this signature. Comprehensive clinicopathological correlation analysis revealed that elevated risk indices, advanced pathological staging (stage III-IV), increased primary tumor dimensions, regional lymph node metastasis, and distant organ dissemination each demonstrated statistically significant associations with diminished overall survival (OS) outcomes in lung cancer patients. The clinical nomogram exhibited acceptable calibration, with calibration plots showing reasonable concordance between predicted and observed survival probabilities across all time points. Discriminative capacity assessment via time-dependent ROC analysis yielded area under the curve (AUC) values consistently surpassing 0.6, confirming moderate prognostic discrimination. Furthermore, decision curve analysis (DCA) demonstrated that our integrated multi-gene model conferred potential net clinical benefit compared to individual prognostic variables across the full spectrum of clinically relevant threshold probabilities (0-1 range), thereby establishing its potential utility for risk-informed clinical decision-making. CONCLUSIONS: This study identified NELL2, C4orf48, PRAM1, and KLHL35 as candidate TEP-related prognostic biomarkers for non-small cell lung cancer (NSCLC). The developed prognostic model shows preliminary potential for patient stratification, but its clinical application, particularly as a platelet-based liquid biopsy tool, requires further validation in independent TEP-based cohorts.

Tumor-educated platelets (TEPs)↗

PubMed2024

GRable Version 1.0: A Software Tool for Site-Specific Glycoform Analysis With Improved MS1-Based Glycopeptide Detection With Parallel Clustering and Confidence Evaluation With MS2 Information.

High-throughput intact glycopeptide analysis is crucial for elucidating the physiological and pathological status of the glycans attached to each glycoprotein. Mass spectrometry-based glycoproteomic methods are challenging because of the diversity and heterogeneity of glycan structures. Therefore, we developed an MS1-based site-specific glycoform analysis method named "Glycan heterogeneity-based Relational IDentification of Glycopeptide signals on Elution profile (Glyco-RIDGE)" for a more comprehensive analysis. This method detects glycopeptide signals as a cluster based on the mass and chromatographic properties of glycopeptides and then searches for each combination of core peptides and glycan compositions by matching their mass and retention time differences. Here, we developed a novel browser-based software named GRable for semi-automated Glyco-RIDGE analysis with significant improvements in glycopeptide detection algorithms, including "parallel clustering." This unique function improved the comprehensiveness of glycopeptide detection and allowed the analysis to focus on specific glycan structures, such as pauci-mannose. The other notable improvement is evaluating the "confidence level" of the GRable results, especially using MS2 information. This function facilitated reduced misassignment of the core peptide and glycan composition and improved the interpretation of the results. Additional improved points of the algorithms are "correction function" for accurate monoisotopic peak picking; one-to-one correspondence of clusters and core peptides even for multiply sialylated glycopeptides; and "inter-cluster analysis" function for understanding the reason for detected but unmatched clusters. The significance of these improvements was demonstrated using purified and crude glycoprotein samples, showing that GRable allowed site-specific glycoform analysis of intact sialylated glycoproteins on a large-scale and in-depth. Therefore, this software will help us analyze the status and changes in glycans to obtain biological and clinical insights into protein glycosylation by complementing the comprehensiveness of MS2-based glycoproteomics. GRable can be freely run online using a web browser via the GlyCosmos Portal (https://glycosmos.org/grable).

Glycopeptides↗

PubMed2024

A comprehensive meta-analysis of tissue resident memory T cells and their roles in shaping immune microenvironment and patient prognosis in non-small cell lung cancer.

Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint and stimulatory genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification.

Humans↗

PubMed2025

U2AF1 mutations rescue deleterious exon skipping induced by KRAS mutations.

The mechanisms by which somatic mutations of splicing factors, such as U2AF1S34F in lung adenocarcinoma, contribute to cancer pathogenesis are not well understood. Here, we used prime editing to modify the endogenous U2AF1 gene in lung adenocarcinoma cells and assessed the resulting impact on alternative splicing. These analyses identified KRAS as a key target modulated by U2AF1S34F. One specific KRAS mutation, G12S, generates a cryptic U2AF1 binding site that leads to skipping of KRAS exon 2 and generation of a non-functional KRAS transcript. Expression of the U2AF1S34F mutant reverts this exon skipping and restores KRAS function. Analysis of cancer genomes reveals that U2AF1S34F mutations are enriched in KRASG12S-mutant lung adenocarcinomas. A comprehensive analysis of splicing factor/oncogene mutation co-occurrence in cancer genomes also revealed significant co-enrichment of KRASQ61R and U2AF1I24T mutations. Experimentally, KRASQ61R mutation leads to KRAS exon 3 skipping, which in turn can be rescued by the expression of U2AF1I24T. Our findings provide evidence that splicing factor mutations can rescue splicing defects caused by oncogenic mutations. More broadly, they demonstrate a dynamic process of cascading selection where mutational events are positively selected in cancer genomes as a consequence of earlier mutations.

Journal Article↗

PubMed2026

Machine learning-based integration develops a novel lysosome-related prognostic signature associated with prognosis and immune infiltration landscape in acute myeloid leukemia.

BACKGROUND: Lysosomes are essential for intracellular degradation and recycling, and changes in their function significantly contribute to tumor growth. Nonetheless, the exact role of lysosome-related genes (LRGs) in the pathogenesis of acute myeloid leukemia (AML) is still inadequately comprehended. METHODS: Differentially expressed LRGs (DE-LRGs) between AML and control groups were identified using AML-related data extracted from the Gene Expression Omnibus (GEO). The LRGs-related prognostic genes were identified and the risk model was established using univariate COX regression analysis and machine learning algorithms, based on the data obtained from The Cancer Genome Atlas (TCGA). Subsequently, we performed comprehensive analyses regarding clinical features, functional pathways, immune microenvironment, and chemotherapeutic drugs sensitivity between the high- and low-risk groups. Reverse transcription Quantitative polymerase chain reaction (RT-qPCR) and western blot were adopted to validate the expression of prognostic genes in human bone marrow-derived cell line HS-27 A and human AML cell line MOLM-13. RESULTS: Through comprehensive analysis, a risk model was developed utilizing ten LRGs (ATP6V0E2, CALCRL, TMEM165, GZMB, HCK, TCIRG1, CD1D, GPRASP1, ABCA1, and NAGA), and this model was further validated using GEO datasets. Significant differences in clinical characteristics, functional pathways, immune microenvironment characteristics, and chemotherapeutic drug sensitivity were observed between the two risk groups In vitro validation experiment illustrated that the expression trends of ATP6V0E2, TMEM165, and ABCA1 were consistent with our bioinformatics analysis. CONCLUSION: Our study demonstrates that lysosome-associated signature might forecast the prognosis of AML patients and offer guidance for subsequent immunotherapy and chemotherapy strategies.

Acute myeloid leukemia↗

PubMed2024

Exploring Regulatory Roles of Transposable Elements in EMT and MET through Data-Driven Analysis: Insights from regulaTER.

Gene expression is regulated at the transcriptional and translational levels and a plethora of epigenetic mechanisms. Regulation of gene expression by transposable elements is well documented. However, a comprehensive analysis of their regulatory roles is challenging due to the lack of dedicated approaches to define their contribution. Here, we present regulaTER, a new R library dedicated to deciphering the regulatory potential of transposable elements in a given phenotype. regulaTER utilizes a variety of genomics data of any origin and combines gene expression level information to predict the regulatory roles of transposable elements. We further validated its capabilities using data generated from an epithelial-mesenchymal and mesenchymal-epithelial transition cellular model. regulaTER stands out as an essential asset for uncovering the impact of transposable elements on the regulation of gene expression, with high flexibility to perform a range of transposable element-focused analyses. Our results also provided insights on the contribution of the MIR and B element subfamilies in regulating EMT and MET through the FoxA transcription factor family. regulaTER is publicly available and can be downloaded from https://github.com/karakulahg/regulaTER.

DNA Transposable Elements↗

PubMed2026

Human Umbilical Cord Mesenchymal Stem Cells in Metabolic Dysfunction-associated Fatty Liver Disease (MAFLD) Therapy: Mechanisms, Clinical Efficacy, and Future Perspectives.

There is currently no approved drug treatment for metabolic dysfunction-related fatty liver disease (MAFLD). Umbilical cord-derived mesenchymal stem cells (UC-MSCs) show therapeutic potential, but their mechanism of action is remains incompletely understood. Different from previous reviews that focused on a single pathway, this article presents three important contributions: First, it constructs an integrated "multi-target synergy network" model, clarifying how UC-MSCs coordinate and regulate the inflammatory, metabolic and fibrotic processes through the interactions between the AMPK/mTOR, Nrf2/HO-1 and TGF-β/Smad pathways; Second, it systematically assesses recent clinical trials (2022-2025), identifying several unaddressed barriers to transformation, including the lack of histological endpoint indicators, batch-to-batch differences, and the absence of dose exploration studies; Third, we integrate the latest developments from 2024 to 2025, particularly mitochondrial transfer (mediated by tunnel nanotubes and accompanied by quantitative efficacy data) and exosome circular RNA networks [Formula: see text], which have not been covered in previous reviews. Based on the above analysis, we also propose specific suggestions for standardized GMP production, mandatory genomic stability testing, and long-term safety registration. This review provides a comprehensive analysis of elaborates on the treatment of MAFLD with UC-MSCs from a mechanistic and translational perspective, based on the extensive updates of relevant literature.

Humans↗

PubMed2026

Atopic dermatitis and the risk of osteoporosis and fractures: a meta-analysis of cohort studies.

BACKGROUND: This meta-analysis aims to evaluate the risk of osteoporosis and fractures in patients with atopic dermatitis (AD) by synthesizing data from cohort studies. We also provide a comprehensive analysis of fracture risks across different severities of AD and anatomical sites. METHODS: Following the PRISMA 2020 guidelines, a systematic search was conducted in PubMed, Embase, and the Cochrane Library up to May 30, 2025. Studies that investigated the relationship between AD and osteoporosis or fractures were included in the analysis. Data extraction and screening were performed independently by two reviewers. Study quality was assessed using the Newcastle-Ottawa Scale (NOS). A random-effects meta-analysis was applied, alongside sensitivity and subgroup analyses. Publication bias was evaluated using funnel plots and Egger's test. RESULTS: Ten cohort studies, involving 368 to over 2 million AD patients, were included. NOS scores ranged from 7 to 8, indicating generally high study quality. The pooled analysis revealed a 56% increased risk of osteoporosis (OR = 1.56, 95% CI: 1.14-2.13; I2 = 99.9%, p < 0.0001) and an 8% increased risk of all-cause fractures (OR = 1.08, 95% CI: 1.05-1.10; I2 = 82.1%, p < 0.0001) in AD patients. Subgroup analyses demonstrated a progressive increase in fracture risk with the severity of AD. Specific risks were significantly higher for vertebral fractures (OR = 1.14, 95% CI: 1.08-1.20; I2 = 67.3%, p = 0.009) and lower limb fractures (OR = 1.11, 95% CI: 1.08-1.13; I2 = 65.0%, p = 0.014). Sensitivity analyses confirmed the robustness of these findings, and no significant publication bias was detected (p = 0.316). CONCLUSION: AD is associated with an increased risk of osteoporosis and fractures, particularly among patients with severe AD and those experiencing vertebral or lower limb fractures. These findings highlight the importance of targeted bone health monitoring in the clinical management of AD patients.Registration: (PROSPERO: CRD420251066550).

Humans↗

PubMed2025

Comparative analysis of DREB gene family in buckwheat: the role of FtDREB02 in the delphinidin biosynthesis and drought stress response.

Dehydration response element binding (DREB) transcription factors play a pivotal role in plant abiotic stress responses, but its evolutionary and functional characterization in buckwheat remains unexplored. Here, we conducted a comprehensive analysis of the DREB gene family across three buckwheat species, revealing segmental duplication as the primary driver of family expansion and potential purifying selection during evolution. A FtDREB02 gene, classified as group A2, was identified through genome-wide association analysis (GWAS) on drought tolerance and delphinidin content. Functional validation in Arabidopsis thaliana and the hairy root of Tartary buckwheat (Fagopyrum tataricum) demonstrated that overexpression of this gene promotes delphinidin biosynthesis and enhances plant resistance to water scarcity. Through the integration of DAP-seq and PEG transcriptome cluster analysis, a FtANS candidate was screened. Functional studies showed that FtDREB02 regulates delphinidin content by binding directly to DRE elements of the FtANS promoter. This research identifies and comprehensively analyzes the DREB family within buckwheat species, elucidating the regulatory mechanisms of FtDREB02 in controlling flavonoid biosynthesis and drought resistance, providing potential genetic resources for breeding buckwheat varieties with excellent agronomic traits.

Anthocyanins↗

PubMed2024

Metagenome-based diversity and functional analysis of culturable microbes in sugarcane.

UNLABELLED: Sugarcane is a key crop for sugar and energy production, and understanding the diversity of its associated microbes is crucial for optimizing its growth and health. However, there is a lack of thorough investigation and use of microbial resources in sugarcane. This study conducted a comprehensive analysis of culturable microbes and their functional features in different tissues and rhizosphere soil of four diverse sugarcane species using metagenomics techniques. The results revealed significant microbial diversity in sugarcane's tissues and rhizosphere soil, including several important biomarker bacterial taxa identified, which are reported to engage in several processes that support plant growth, such as nitrogen fixation, phosphate solubilization, and the production of plant hormones. The Linear discriminant analysis Effect Size (LEfSe) studies identified unique microbial communities in different parts of the same sugarcane species, particularly Burkholderia, which exhibited significant variations across the sugarcane species. Microbial analysis of carbohydrate-active enzymes (CAZymes) indicated that genes related to sucrose metabolism were mostly present in specific bacterial taxa, including Burkholderia, Pseudomonas, Paraburkholderia, and Chryseobacterium. This study improves understanding of the diversities and functions of endophytes and rhizosphere soil microbes in sugarcane. Moreover, the approaches and findings of this study provide valuable insights for microbiome research and the use of comparable technologies in other agricultural fields. IMPORTANCE: This work utilized metagenomics techniques for conducting a comprehensive examination of culturable microbes and their functional characteristics in various tissues and rhizosphere soil of four distinct sugarcane species. This study enhances comprehension of the diversity and functions of endophytes and rhizosphere soil microbes in sugarcane. Furthermore, the methodologies and discoveries of this work offer new perspectives for microbiome investigation and the use of similar technologies in other agricultural fields.

Saccharum↗

PubMed2026

Identification of Freezing-Responsive microRNAs and Their Targets in Chinese Jujube by Small RNA and Degradome Sequencing.

The jujube tree fruit remains a primary fruit in northern China, yet its geographical distribution and yield are significantly constrained by freezing stress during winter. Numerous studies have highlighted the pivotal regulatory function of microRNAs (miRNAs) in plant responses to low-temperature stress. Nevertheless, the specific miRNAs involved in the response to low temperatures and their associated gene networks in Ziziphus jujuba Mill are not well understood. In this investigation, we utilized high-throughput sequencing to analyze small RNA libraries from branches subjected to temperatures of 4 °C and -30 °C. Our analysis identified a total of 342 miRNAs, comprising 123 known miRNAs and 219 novel miRNAs. The differential expression analysis revealed that under low-temperature conditions, 177 miRNAs underwent significant changes. Among them, specific upregulation of miR319 in the less cold-resistant variety and miR6483 in sensitive variety was observed. By employing degradome sequencing, we identified a total of 1551 target genes corresponding to 3059 unique miRNA target interaction pairs involving 299 miRNAs. Functional analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways indicated that these target genes are primarily associated with transcriptional regulation, metabolic pathways, and genetic information processing. Through a comprehensive analysis, we pinpointed 11 genes corresponding to 9 miRNAs that are implicated in jujube tree cold stress, and 7 target genes of 7 miRNAs were confirmed by 5'-RACE analysis. These miRNAs are likely to exert crucial regulatory functions in the context of jujube tree cold stress. This study is the first to systematically identify miRNAs and their target genes in the response of Ziziphus jujuba Mill to low-temperature stress, which provides important resources for in-depth analysis of the molecular mechanism of jujube tree cold resistance and for cold-resistant breeding.

Ziziphus↗