Ventilator-associated pneumonia (VAP) is the most frequent healthcare-associated infection in intensive care units and is associated with high morbidity and mortality. Current diagnostic criteria lack specificity, leading to misclassification and unnecessary antibiotic use. Identifying patient subgroups with a common pathophysiological basis (pneumoclusters) may distinguish true VAP of varying aetiology and severity from non-infectious mimics, enabling more targeted therapy and improved antimicrobial stewardship. ClusterVAP is an exploratory, observational, prospective, multicentre cross-sectional study conducted in intensive care units across Sweden, France, Portugal, Denmark and the UK. Mechanically ventilated patients aged 18 years or older with newly developed clinical signs of lower respiratory tract infection will undergo bronchoalveolar lavage (BAL) or mini BAL sampling on clinical indication. Proteomic profiling using liquid chromatography tandem mass spectrometry will be performed on BAL supernatants. Unsupervised consensus clustering will define pneumoclusters, which will be characterised using clinical, microbiological and radiological data. 30-day outcomes, including mortality, ventilator-free days, antibiotic-free days, intensive care unit-free days and hospital-free days, will be compared across clusters to describe clinical trajectories. Candidate protein biomarkers for pragmatic cluster assignment will be derived using differential expression analysis. Ethical approval will be obtained at all participating sites. Deferred consent will be used where permitted, with subsequent patient or proxy consent according to local regulations. Results will be disseminated through peer-reviewed publications and scientific conferences. NCT07245888.

PurposeObesity is strongly associated with hepatocellular carcinoma (HCC), yet the molecular mechanisms linking them remain unclear. This study aimed to identify mitochondrial metabolism-related genes bridging obesity and HCC and to investigate their role in regulating the metabolic-immune microenvironment.MethodsPublic transcriptomic datasets from obesity (derived from peripheral blood mononuclear cells) and HCC (derived from liver tissue) cohorts were integrated. A multi-step bioinformatic pipeline combining differential expression analysis (DEA), weighted gene co-expression network analysis (WGCNA), and machine learning (ML) algorithms was applied to identify and validate hub genes. Associations with the tumor immune microenvironment were assessed using ssGSEA and correlation analyses.Results27 core genes were identified, significantly enriched in lipid metabolism and immune response pathways. Among these, ML highlighted ACAA1 and ADI1 as downregulated candidate genes. While discovery datasets showed high diagnostic potential, ADI1 exhibited more variable performance in obesity external validation compared to the robust consistency of ACAA1. Downregulation of both genes correlated with effector T/NK cell lipid-mediated functional exhaustion and disrupted networks of immune checkpoints and chemokines, reflecting an immunosuppressive microenvironment.ConclusionsACAA1 and potentially ADI1 are downregulated candidate genes linking obesity to HCC. Their suppression likely drives obesity-related HCC progression by coupling mitochondrial metabolic reprogramming with immunosuppressive tumor microenvironment remodeling, representing potential therapeutic targets.

Oral diseases, including oral cancer, periodontitis, and oral mucosal disorders, pose major global public health challenges and are driven by complex molecular mechanisms. While recent advances in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) have unraveled the heterogeneity of these diseases, integrative analyses remain hindered by severe batch effects, inconsistent metadata annotations, and the fragmentation of public datasets. To address these challenges, we present OralDB (https://compbio.cn/oraldb/), the first comprehensive, standardized, and interactive multimodal transcriptomic resource dedicated to oral diseases. OralDB integrates 73 high-quality datasets spanning 20 oral diseases and 4 omics types (microarray, RNA-seq, scRNA-seq, ST), covering 2,027 tissue-based samples. The platform applies rigorous processing pipelines, including quality control, dimensionality reduction, clustering, and cell-type annotation, and provides interactive analytical modules for gene expression visualization, differential expression, pathway enrichment, gene correlation, and cell-cell interaction analysis. OralDB enables efficient exploration of molecular and cellular features across disease contexts. We demonstrate the platform's utility through case studies of SERPINE2-driven epithelial-mesenchymal transition in oral squamous cell carcinoma and fibroblast-derived CXCL1-mediated myeloid cell recruitment in periodontitis. By facilitating mechanistic insights and supporting translational applications, OralDB offers a robust resource to advance precision research and therapeutic development in oral diseases.

Multiple myeloma (MM) is a heterogeneous hematologic cancer marked by clonal plasma cell expansion in the bone marrow. Although treatments have improved, relapse remains common due to clonal evolution, tumor microenvironment changes, ultimately leading to drug resistance. This study utilized single-cell RNA sequencing data analysis to explore immune microenvironment dynamics during MM progression and relapse, aiming to uncover key pathways and cellular interactions correlated with disease relapse. ScRNA-seq data from 20 MM patients (10 primary, 2 remission, 8 relapsed) from the GEO dataset GSE223060 were analyzed. After quality control and batch correction, cells were clustered and annotated. Differential gene expression and functional enrichment analyses were conducted to explore cellular functions. Pseudotime analysis was used to trace plasma cell differentiation, and cell-cell communication was analyzed. Immunohistochemistry and flow cytometry were used for validation.60,234 high-quality single cells were classified into 12 distinct populations. Relapsed MM showed increased T cell infiltration and decreased plasma cells. Relapsed samples had more regulatory T cells (Tregs) and impaired CD8 + T cells. MIF was identified as a key regulator in plasma cell evolution, linked to B cell receptor and interferon-alpha signaling. Enhanced MIF pathway activity was noted between plasma cells and CD8 + T cells in relapsed MM. Increased MIF expression was confirmed in relapsed tissues. Our findings reveal profound immune microenvironment remodeling in relapsed MM, characterized by MIF-mediated signaling, NF-κB suppression, and CD8⁺ T cell dysfunction. These results provide new insights into the mechanisms of MM relapse and highlight potential therapeutic targets for preventing disease relapse.

Invasive aspergillosis (IA) is a leading cause of mortality despite antifungal therapy. Current biomarkers for treatment monitoring and outcome prediction are limited, with host biomarkers showing potential in other fungal diseases but not in IA yet. Here, we aimed to identify circulating immunological biomarkers for treatment monitoring and outcome prediction for IA. In this European Confederation of Medical Mycology (ECMM) multicenter study, we prospectively evaluated a cohort of 51 patients with probable or proven IA with underlying hematological malignancies. Serial serum samples, collected over a three-week period, were analyzed using the Olink Target 96 Inflammation panel. Differential expression analyses were performed to identify potential biomarkers associated treatment responses at days 7 and 30, in addition to survival analysis for outcome prediction. During the first days of treatment, all significantly differentially expressed proteins were upregulated in patients showing clinical improvement compared to those with worsening disease, with the exception of CCL23. Multiple proteins significantly correlated with the need to switch from primary to salvage antifungal therapy. For late treatment response, MMP-10 emerged as predictor, with consistent lower expression levels in patients demonstrating clinical improvement during weeks 2 and 3. Moreover, low serum concentrations of CXCL6 at week 2 and MMP-10 at week 3 were associated with higher survival probability. The dynamic regulation of immune markers in different disease states the use in predicting responses to antifungal treatment, depending on the goal of the assessment. Future studies should validate these biomarkers and establish their usefulness in clinical practice.

Sézary syndrome (SS) and leukaemic mycosis fungoides (MF) are aggressive cutaneous T-cell lymphomas (CTCLs) with poor prognosis and limited treatment options. Single-cell RNA sequencing (scRNA-seq) offers an opportunity to dissect malignant heterogeneity and immune dysregulation yet has been underutilized in leukaemic CTCL. To define transcriptional heterogeneity within malignant T cells, identify immunomodulatory signals shaping the tumour microenvironment and uncover actionable vulnerabilities in SS and leukaemic MF. We analysed 144,321 peripheral blood mononuclear cells from 22 patients (SS or leukaemic MF) and 7 healthy controls using scRNA-seq, with CITE-seq and TCR-seq in subsets. Public and prospectively collected datasets were integrated after rigorous per-sample quality control, batch correction and malignancy assignment. Differential gene expression and cell-cell communication analyses were performed using complementary modelling approaches with correction for sparsity and multiple testing. Three transcriptionally distinct malignant T-cell (MTC) subtypes were identified: central memory-like (MTC CM), effector/effector memory-like (MTC E/EM) and regulatory-like (MTC Reg), each with unique expression programmes and putative vulnerabilities. MTC CM, the dominant population, expressed central memory markers, Th2/Th22 skewing and a broader KIR repertoire (KIR3DL2, KIR3DL1, KIR2DL3) than previously reported. MTC E/EM and MTC Reg were enriched for NR4A1 and ITGB1, respectively. Cell-cell communication analysis revealed KIR-MHC-I signalling and suggested that MTC-derived TNF and IL-10 may drive JAK/STAT pathway activity in non-T cells, indicating an underrecognized dimension of tumour-induced immune reprogramming. This is one of the most comprehensive single-cell studies of leukaemic CTCL to date. We uncover new malignant T-cell states, broaden the known repertoire of KIR expression, and propose mechanisms of immune evasion that may contribute to treatment resistance. These findings lay the groundwork for subtype-specific and microenvironment-informed therapeutic strategies in Sézary syndrome, with potential implications for guiding targeted therapy selection but require validation in larger, independent cohorts.

Cold shock proteins are small, highly conserved nucleic acid-binding proteins that help bacteria adapt to stress conditions. Aeromonas salmonicida subspecies salmonicida is a psychotropic, Gram-negative intracellular fish pathogen that causes furunculosis in fish. The role of cold shock proteins in the stress response in marine pathogens like A. salmonicida is unknown. In this study, we reported the role of cold shock protein A (CspA) in A. salmonicida physiology, stress response, and virulence in lumpfish (Cyclopterus lumpus). A. salmonicida ΔcspA was characterized using phenotypic tests and transcriptomics. A. salmonicida ΔcspA showed a reduction in survival at low temperatures (0 and 4ºC) and in ox bile containing (5%) conditions. Differential gene expression analysis showed 632 dysregulated genes in ΔcspA. Among these 632 differentially expressed genes (DEGs), 413 were upregulated, and 219 were downregulated. Most downregulated genes were related to the type III secretion system (T3SS). However, A. salmonicida ΔcspA was not fully attenuated in the lumpfish host but delayed fish mortality and reduced tissue colonization after systemic infection in contrast to the wild type strain. Overall, this study provides novel insight into the roles of CspA in virulence and the physiology of A. salmonicida.

Aicardi-Goutières syndrome (AGS) is a genetic type I interferon (IFN)-mediated disease characterized by neurological involvement with onset in utero or in childhood. Here, we analyze peripheral blood samples from patients bearing AGS-causing mutations in ADAR1, RNASEH2B or SAMHD1 using single-cell transcriptomics and targeted metabolomics. Using machine-learning approaches and differential gene expression analysis, we identified a loss of transcription factor hypoxia induced factor 1 α (HIF-1α) expression and activity associated with features of a metabolic switch favoring oxidative phosphorylation and glutathione metabolism over glycolysis in monocytes and dendritic cells. Evidences of mitochondrial stress and accumulation of cytosolic double-stranded DNA and RNA were also found. The energy metabolic switch was confirmed at the metabolic level in primary peripheral blood mononuclear cells of AGS patients. Chemical stabilization of HIF-1α using a synthetic drug in in vitro cellular models of AGS, reversed the energy metabolic switch towards glycolysis, attenuated mitochondrial stress, and markedly reduced the IFN response and IP-10 production. We therefore propose that an energy metabolic switch contributes to chronic inflammation in AGS and that targeting this pathway might represent a potential therapeutic approach.

Background: HER2-low breast cancer is a biologically heterogeneous subgroup in which hormone receptor (HR) expression critically shapes prognosis and treatment, but the underlying regulatory mechanisms remain unclear. MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression and may contribute to HR heterogeneity. This study aimed to identify deregulated miRNAs and associated gene networks distinguishing HER2-low/HR-positive from HER2-low/HR-negative tumors, elucidating the molecular mechanisms underlying this divergence. Methods: Differential expression analyses of miRNAs and genes were performed using Wilcoxon tests and DESeq2 (|log2FC| > 1; FDR-adjusted p-value < 0.05). Survival analyses were conducted using Cox proportional hazards models to evaluate the individual miRNAs and miRNA signature. Functional enrichment analyses, including GO, KEGG and Reactome pathways, were performed. Correlation analysis and the miRNA target prediction were integrated to identify regulatory interactions. Results: Comparisons between HER2-low/HR-positive and HER2-low/HR-negative tumors identified 165 significantly deregulated miRNAs and 170 strongly deregulated genes. Intersection analysis highlighted miR-9-5p, miR-532-5p and miR-576-5p as specifically associated with HR-negative status. Survival analyses showed non-significant trends for the overall survival and progression-free interval. Functional enrichment analysis revealed hormone-related pathways in HR-positive tumors and immune, inflammatory and proliferative pathways in HR-negative tumors. Integrative correlation and target prediction analyses identified two miRNA–mRNA regulatory axes, miR-576-5p/TGFBI and miR-9-5p/POU2F2. Conclusions: Our study demonstrated that HER2-low breast cancer exhibits distinct miRNA and gene expression profiles, which highlight different transcriptomic profiles according to HR status for the first time. Specific miRNA–gene networks may drive transcriptional heterogeneity, serving as potential biomarkers for stratification and as therapeutic targets. These findings provide insight into the molecular basis of HER2-low tumor diversity and support future development of HR-directed therapeutic strategies.

Transcriptomic and proteomic assessment of radiation injury and dose-rate dependency in white blood cells.

Integrated bioinformatics and machine learning deciphering IL12RB2 and FYN as key immune biomarkers in brucellosis.

Plasticizer mixture exposure-induced preeclampsia pathogenesis: Integrated single-cell and bulk transcriptomics, network toxicology, and molecular docking insights.

Transcriptomic insights into the antimicrobial effect of Pediococcus pentosaceus on multidrug-resistant Pseudomonas aeruginosa.

Two novel iron metabolism-related genes identified as diagnostic indicators in substantia nigra of patients with Parkinson's disease.

Integrated miRNA and mRNA analysis in gills of Amur ide (Leuciscus waleckii) reveals novel insights into the molecular regulatory mechanism of alkaline acclimation.

Transcriptome integration analysis of shared biomarkers and common immune mechanisms in SLE and PSO.

Molecular markers of pediatric cholesteatoma: A gene expression comparison with adult tissue.

Dihydromyricetin improves DSS-induced colitis and behavioral disorders by regulating the microbiota-gut-brain axis balance and inhibiting the activation of NLRP3 inflammasome.

Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurodegenerative motor neuron disease with a pathophysiology that features dysregulated natural killer (NK) cells that are capable of damaging neurons. Although NK cells are associated with ALS progression and survival, their specific characteristics and how these characteristics change over the course of disease is unknown. The current study examines NK cell gene expression during ALS with the goal of identifying dysregulated genes and pathways in NK cells over the course of disease in order to identify potential new therapeutic targets. ALS participants with an El Escorial ALS diagnosis were recruited from the University of Michigan Pranger ALS Clinic, and control participants were recruited via internet-based notifications. Blood was collected from participants and NK cells were isolated from participants with ALS at two timepoints (baseline and longitudinal) and age- and sex-matched healthy controls at one timepoint. RNA was extracted from the NK cells and quantified using a transcript-counting technology for 578 immune-related genes. Differential gene expression analysis was used to identify individual genes that were dysregulated in ALS at baseline and longitudinally, While GO and KEGG pathway analyses were performed to identify dysregulated pathways at both timepoints. NK cells from participants with ALS (n=36, median age 62.6 years (54.5-69.4), 50% female) showed a 2-fold or greater reduced expression of four pro-inflammatory genes at baseline relative to control participants (N=35, median age 64.3 years (55.2-71.8), 51% female) including IFNG, FCGR1A/B, and FAS; in ALS participants over 130 genes showed a 2-fold change in expression. Dysregulated genes and pathways at the later timepoint were related to cell polarization, activation, signaling, and cell-cell adhesion. In particular, genes associated with classical Type 1 inflammation decreased while Type 2 genes increased. NK cells grow more dysregulated with ALS progression, shifting from a classical Type 1 phenotype to a Type 2 phenotype, though a larger study will be needed to confirm these initial findings. The findings also suggest NK cells contribute to early, but not late, ALS progression. Targeting specific NK cell pathways during early ALS may be a viable therapeutic strategy.

Development of an integrative cross-omics approach for conceptual adverse outcome pathway network construction.