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At least 433 records · Page 24Linked to original sources

Multi-omics analysis of ubiquitin E2 genes in Setaria: evidence for the roles of E2 genes in various aspects of plant development, stress tolerance, and domestication.

Ubiquitin E2 enzymes (E2s) are critical mediators in the ubiquitination cascade, a post-translational modification process that regulates protein stability, activity, localization, and degradation. Here, we analyzed the E2 gene family in foxtail millet (Setaria italica), integrating comparative genomics, transcriptomics, and functional studies. A total of 52 E2 genes were identified and classified into four subfamilies (UBC, UEV, SCE, and RCE) based on phylogenetic analysis across 49 species. Notably, foxtail millet exhibited significant gene expansion. Tissue-specific expression profiling revealed distinct roles of E2 genes in growth and development. Haplotype and quantitative trait loci analyses demonstrated that several E2 genes, including SiUBC39, are associated with key agronomic traits, such as plant height, flowering time, and stress tolerance. Using CRISPR/Cas9, we validated the functional role of SiUBC39, finding that its disruption led to phenotypes resembling wild species (Setaria viridis), such as early flowering and reduced plant height and grain yield. IP-MS and transcriptome analysis revealed SiUBC39's involvement in growth and development regulation, drought stress response, and immune response. SiPIP2;1 and SiEhd2 were identified as interactors of SiUBC39, explaining its roles in blast resistance and flowering time control. Furthermore, domestication analysis identified an A/G mutation in the SiUBC39 promoter TATA box, distinguishing domesticated and wild haplotypes and highlighting its role in domestication selection. This study underscores the essential roles of E2 genes in regulating crop agronomic traits and stress responses, providing valuable insights for genetic improvement in foxtail millet and other cereals.

Setaria Plant↗

A weakly supervised deep learning-based recurrence prediction and risk stratification of lung adenocarcinoma from pathology whole-slide images.

BACKGROUND: Accurate prediction of postoperative recurrence in lung adenocarcinoma (LUAD) is essential for guiding clinical decision-making and improving patient outcomes. Although various predictive models have been developed, most rely on complex genomic analyses and high-dimensional clinical data. The complexity of these approaches substantially limits their feasibility for routine clinical use. To address this clinical challenge, this study aims to predict postoperative recurrence using routinely available hematoxylin and eosin (H&E)-stained images and characterize the associated biological features. METHODS: A total of 329 patients who underwent curative resection at the First Affiliated Hospital of Wenzhou Medical University (FHWMU) were retrospectively enrolled and randomly assigned to training and internal validation cohorts in a 7:3 ratio. An independent external validation cohort comprising 70 patients from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) was included. Three patch-level feature extractors (Inception_V3, ResNet18, and DenseNet121) were evaluated within a weakly supervised multiple-instance learning (MIL) framework incorporating automated region-of-interest (ROI) detection on segmented whole-slide images (WSIs). Model performance was assessed using the area under the receiver operating characteristic curve (AUC), Kaplan-Meier (KM) survival analysis, and multivariable Cox proportional hazards regression. Transcriptomic profiling and gene set enrichment analysis (GSEA) were conducted to investigate biological differences between risk groups. RESULTS: The model achieved AUCs of 0.923 in the training cohort, 0.891 in the internal validation cohort, and 0.847 in the external validation cohort. The model effectively stratified patients into high- and low-risk groups with significantly different recurrence-free survival (RFS) across all cohorts (all P&#x2009;<&#x2009;0.001) and retained prognostic value within AJCC stages I-III. Transcriptomic analyses revealed consistent enrichment of cell cycle-related pathways and neutrophil extracellular trap (NET) formation in high-risk patients across both institutional and CPTAC cohorts, aligning with distinct biological profiles of the model-derived risk stratification. CONCLUSIONS: This weakly supervised deep learning framework enables accurate and externally validated prediction of postoperative recurrence in LUAD using routinely available histopathological images, and integration of histopathological features with molecular analyses enhances biological interpretability. This work provides a clinically accessible and cost-effective tool for postoperative risk assessment in LUAD patients.

Humans↗

Integrated dual transcriptome sequencing and experimental validation reveal potential mechanisms of baicalin against pneumocystis pneumonia in immunosuppressed rats.

BACKGROUND: Pneumocystis pneumonia (PCP) remains a major cause of morbidity and mortality in immunocompromised individuals. Although baicalin (Ba), a natural bioactive flavonoid, has demonstrated protective and therapeutic effects against PCP, its molecular mechanisms remain undefined. We employed dual RNA sequencing (dual RNA-seq) to characterize host and pathogen transcriptional responses to Ba treatment in an immunosuppressed rat model of PCP. METHODS: Comparative transcriptomic analyses identified differentially expressed genes in both the host and Pneumocystis, followed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analyses. Candidate targets were further investigated using network pharmacology, protein-protein interaction analysis, molecular docking, and molecular dynamics simulations. Key findings were validated by immunohistochemistry, enzyme-linked immunosorbent assay, and quantitative PCR. RESULTS: Ba markedly remodeled host and pathogen transcriptomes. Host transcriptomic analyses showed that Ba attenuated inflammatory and oxidative stress responses by modulating immune-related pathways, including Toll-like receptor, NF-&#x3ba;B, cytokine-cytokine receptor interaction, chemokine signaling, Th17 cell differentiation, and antigen processing and presentation. Experimental validation demonstrated that Ba reduced pulmonary expression of indoleamine 2,3-dioxygenase 1 (IDO1), Toll-like receptor 2 (TLR2), and TLR4 while increasing nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream antioxidant enzyme heme oxygenase-1 (HO-1). Pathogen transcriptomic analysis identified Pneumocystis Rtt109 (PcRtt109), a fungal histone acetyltransferase, as a potential pathogen-specific target that was significantly downregulated after Ba treatment. Molecular docking and molecular dynamics simulations supported stable interactions between Ba and IDO1, Nrf2, TLR2, TLR4, and PcRtt109, with the strongest predicted binding observed for PcRtt109. CONCLUSION: Dual RNA-seq revealed that Ba exerts anti-PCP activity through coordinated modulation of host and pathogen molecular networks. Its therapeutic effects are associated with suppression of inflammatory signaling, enhancement of antioxidant defenses, and inhibition of a fungal virulence-associated target. These findings provide mechanistic insights into host-pathogen interactions during PCP and support Ba as a potential therapeutic candidate for PCP.

Nrf2↗

Identification and genetic validation of potential therapeutic targets for pulmonary hypertension through multi-omics causal inference.

Pulmonary hypertension (PH) underscores the urgent need for novel therapeutic targets. This study aimed to employ a proteome-wide Mendelian randomization (MR) approach to systematically identify circulating proteins causally associated with PH, thereby providing genetically validated candidate targets for drug development. We adopted a 2-sample MR design, integrating large-scale plasma proteomic quantitative trait loci (pQTL) data (encompassing 4148 proteins) and summary statistics from a large-scale PH genome-wide association study (2047 cases, 8301 controls). Candidate targets were screened through a multilayered analytical pipeline comprising proteomic MR, transcriptomic MR, and summary-data-based Mendelian randomization. The ultimately identified MR-Identified Causal Candidate Targets (MR-ICTs) underwent rigorous Bayesian colocalization analysis, followed by biological characterization through functional enrichment analysis, single-cell transcriptomics, and phenome-wide association studies. Through robust genetic causal inference, this study provides that circulating proteins such as LYZ, GREM2, NID1, and PF4V1 play causal roles in PH pathogenesis. These findings offer a set of rigorously genetically validated, high-priority therapeutic targets for developing novel PH treatments, specifically addressing key pathological mechanisms such as innate immunity, BMP signaling pathway dysregulation, and platelet activation. Our multi-dimensional analysis ultimately identified 6 MR-ICTs causally associated with PH. Notably, the causal associations for lysozyme C (LYZ), gremlin-2 (GREM2), nidogen-1 (NID1), and platelet factor 4 variant 1 (PF4V1) were stringently validated by Bayesian colocalization analysis (posterior probability for hypothesis 4 [PPH4], indicating a shared causal variant, > 0.99). Functional enrichment analysis revealed significant involvement of these targets in immune response and TGF-&#x3b2; signaling pathways. Single-cell analysis further elucidated their cell-type-specific expression, with LYZ predominantly expressed in monocytes and PF4V1 almost exclusively in platelets.

Hypertension, Pulmonary↗

Changes in gene expression in macrophages infected with Mycobacterium tuberculosis: a combined transcriptomic and proteomic approach.

We investigated the changes which occur in gene expression in the human macrophage cell line, THP1, at 1, 6 and 12 hr following infection with Mycobacterium tuberculosis. The analysis was carried out at the transcriptome level, using microarrays consisting of 375 human genes generally thought to be involved in immunoregulation, and at the proteomic level, using two-dimensional gel electrophoresis and mass spectrometry. The analysis of the transcriptome using microarrays revealed that many genes were up-regulated at 6 and 12 hr. Most of these genes encoded proteins involved in cell migration and homing, including the chemokines interleukin (IL)-8, osteopontin, monocyte chemotactic protein-1 (MCP-1), macrophage inflammatory protein-1alpha (MIP-1alpha), regulated on activation, normal, T-cell expressed and secreted (RANTES), MIP-1beta, MIP-3alpha, myeloid progenitor inhibitory factor-1 (MPIF-1), pulmonary and activation regulated chemokine (PARC), growth regulated gene-beta (GRO-beta), GRO-gamma, MCP-2, I-309, and the T helper 2 (Th2) and eosinophil-attracting chemokine, eotaxin. Other genes involved in cell migration which were up-regulated included the matrix metalloproteinase MMP-9, vascular endothelial growth factor (VEGF) and its receptor Flk-1, the chemokine receptor CCR3, and the cell adhesion molecules vesicular cell adhesion molecule-1 (VCAM-1) and integrin a3. In addition to the chemokine response, genes encoding the proinflammatory cytokines IL-1beta (showing a 433-fold induction), IL-2 and tumour necrosis factor-alpha (TNF-alpha), were also found to be induced at 6 and/or 12 hr. It was more difficult to detect changes using the proteomic approach. Nevertheless, IL-1beta was again shown to be strongly up-regulated. The enzyme manganese superoxide dismutase was also found to be strongly up-regulated; this enzyme was found to be macrophage-, rather than M. tuberculosis, derived. The heat-shock protein hsp27 was found to be down-regulated following infection. We also identified a mycobacterial protein, the product of the atpD gene (thought to be involved in the regulation of cytoplasmic pH) in the infected macrophage extracts.

Chemokines↗

Fasting-refeeding regimes induce compensatory growth and muscle transcriptomic remodeling in juvenile Qihe gibel carp (Carassius gibelio var. Qihe).

Compensatory growth, an important adaptive response in fish, holds considerable potential for improving feeding efficiency in aquaculture. To identify an optimal fasting-refeeding strategy for juvenile Qihe gibel carp (Carassius gibelio var. Qihe) and to clarify the mechanisms underlying the compensatory growth, we divided two-month-old fish into four groups, namely S0 group (continuous feeding for 28&#xa0;days), S2 group (4&#xa0;cycles of 2-day fasting followed by 5-day refeeding), S4 group (fasting for 4&#xa0;days followed by refeeding for 24&#xa0;days), and S8 group (fasting for 8&#xa0;days followed by refeeding for 20&#xa0;days), then growth performance, muscle tissue morphology, biochemical responses, and muscle transcriptomic profiles under different feeding regimes were investigated. After a 28-day aquaculture experiment, fish in the S4 group exhibited significantly greater body length and weight than those in the S0, S2, and S8 groups, indicating over-compensatory growth. Histological analysis further showed that muscle growth in the S4 group was mainly associated with myofiber hyperplasia. Different feeding regimes also induced distinct changes in hepatic antioxidant and metabolic enzyme activities, as well as intestinal digestive enzyme activities. Transcriptome analysis revealed that the forkhead box O (FoxO) signaling pathway was significantly enriched during compensatory growth. Key genes, including serum/glucocorticoid regulated kinase 1 (sgk1) and insulin receptor substrate 1 (irs1), were predicted to play important roles in this process. Overall, these results indicate that fasting for 4&#xa0;days followed by refeeding for 24&#xa0;days (the S4 regime) is the optimal strategy for inducing compensatory growth in juvenile Qihe gibel carp. This study provides new insights into the morphological, physiological, and molecular basis of compensatory growth and offers a scientific foundation for developing efficient and sustainable feeding strategies for this species.

Animals↗

LINC01871-Mediated Sensitivity to Cyclin-Dependent Kinase 4/6 Inhibitors in Human Breast Cancer.

Breast cancer remains the most frequently diagnosed malignancy in women, and resistance to cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors limits long-term treatment efficacy. This study aimed to identify long non-coding RNAs (lncRNAs) associated with predicted sensitivity to CDK4/6 inhibitors and to investigate their biological functions in breast cancer. Transcriptomic data from The Cancer Genome Atlas (TCGA) and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) database were integrated, and drug sensitivity was predicted using the oncoPredict algorithm. Candidate lncRNAs were identified through differential expression analysis, weighted gene co-expression network analysis, prognostic analysis, and machine learning. The biological functions of LINC01871 were subsequently evaluated using in vitro and in vivo experiments. Sixty-two lncRNAs associated with predicted sensitivity to ribociclib and palbociclib were identified, and six core lncRNAs were selected. LINC01871 showed the highest discriminatory performance for predicted drug sensitivity. Overexpression of LINC01871 was associated with increased sensitivity of breast cancer cells to ribociclib and palbociclib, inhibition of cell proliferation, promotion of apoptosis, and suppression of nuclear factor kappa B (NF-&#x3ba;B) signaling. Single-cell transcriptomic analysis demonstrated high LINC01871 expression in T cells and natural killer (NK) cells, while transcriptome-based immune infiltration analyses showed that high LINC01871 expression was associated with increased immune infiltration. These findings identify LINC01871 as a candidate biomarker of sensitivity to CDK4/6 inhibitors and demonstrate its tumor-suppressive effects in breast cancer. Further clinical and mechanistic studies are required to validate its predictive value and therapeutic relevance.

Humans↗

A pan-cancer analysis of MEX3D in human tumors.

BACKGROUND: MEX3D, a member of the MEX3 RNA-binding protein family, has emerged as a potential regulatory molecule in cancer. However, its role across different tumor types remains largely unexplored. METHODS: We conducted a pan-cancer analysis of MEX3D using transcriptomic and proteomic data from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Expression patterns, clinical correlations, survival outcomes, genetic alterations, RNA modification associations, immune infiltration, and functional enrichment were systematically evaluated. RESULTS: MEX3D was significantly dysregulated in numerous cancers at both mRNA and protein levels. Its expression correlated with tumor stage in ACC, LIHC, OV, SKCM, and THCA. Elevated MEX3D expression was associated with poor overall survival (OS) and disease-specific survival (DSS) in multiple malignancies, including ACC, LGG, LUAD, and MESO. Genetic alteration analysis revealed frequent amplifications and mutations, particularly in SARC and OV. MEX3D was positively correlated with RNA modification-related genes (m1A, m5C, m6A) and immune regulatory genes such as CD276, TGFB1, VEGFA, and ICOSLG. Additionally, MEX3D expression showed significant associations with tumor mutational burden (TMB), microsatellite instability (MSI), and cancer-associated fibroblast infiltration. Functional enrichment analyses indicated that MEX3D-related genes are involved in reproductive cellular processes, RNA binding, the Hippo signaling pathway, and microRNA-related oncogenic pathways. CONCLUSION: This pan-cancer analysis highlights the heterogeneous expression and cancer-specific prognostic significance of MEX3D. MEX3D is associated with immune infiltration, immune regulatory genes, RNA modification-related genes, TMB/MSI, and pathways involved in gene regulation and tumor progression. These findings suggest that MEX3D may participate in cancer-specific post-transcriptional and microenvironmental regulatory networks.

Biomarker↗

Ossicle occurrence characteristics and related molecular mechanisms in the sea cucumber Apostichopus japonicus.

To investigate the morphogenetic pattern and molecular mechanism of ossicle formation in the sea cucumber Apostichopus japonicus, this study systematically examined the morphological development and temporal sequence of spicules using the NaClO maceration method, in-situ squash preparation and microscopic observation. Comparative transcriptome sequencing was performed between doliolaria and pentactula larvae to screen differentially expressed genes (DEGs) related to ossicles formation, followed by pathway enrichment analysis. The function of the candidate key gene papilin-like was verified using siRNA-mediated gene silencing. The results were as follows: 1) Ossicles of A. japonicus first appeared at the late auricularia stage, initiating as X-shaped ossicles at the base of the oral tentacles. The number of X-shaped ossicles increased dramatically during the doliolaria stage. X-shaped ossicles were gradually replaced by table-shaped and rosette-shaped ossicles at the pentactula stage, suggesting that X-shaped ossicles may differentiate into these two ossicle types. The morphology of table-shaped ossicles showed a "simple-complex-simple" pattern with development. 2) Key genes related to ossicles formation, including CA1, COL1A2, and papilin-like, were identified by transcriptome analysis. After papilin-like knockdown, abnormal morphologies were observed in table-shaped ossicles of 1-year-old A. japonicus, such as spine-like protrusions on the outer margin of the disc and loss of table legs, confirming its crucial roles in maintaining ossicle morphology. This study clarified the morphological development pattern of ossicles in A. japonicus and identified a key regulatory gene (papilin-like) involved in ossicle morphogenesis, providing preliminary insights into the underlying molecular regulatory mechanism. These findings enrich our understanding on ossicles formation in echinoderms, and provide important morphological and molecular biological information for further studies on the developmental mechanism of ossicles in A. japonicus.

Animals↗

Full-length single-cell spatial transcriptomics reveals spatial and cell-type-specific transcript isoforms in the primate brain.

The primate brain exhibits complex RNA alternative splicing heterogeneity crucial for functional complexity, yet systematic spatial isoform characterization has been lacking. We developed Fullscope-seq, a full-length single-molecule large field-of-view spatial transcriptomics sequencing method at single-cell resolution, based on programmed concatenation cDNA for multiple long-read sequencing platforms. Applying Fullscope-seq to the macaque brain, we uncovered thousands of genes exhibiting differential transcript usage (DTU) across cortical layers, cell types and brain regions. Fullscope-seq resolved hundreds of major isoform switches across distinct brain regions and identified DTUs between superficial and deep cortical layers. Cortical layer-specific DTUs showed cell-composition dependence, whereas regional DTUs were regulated according to both cellular composition and spatial contexts. These isoform variations showed substantial enrichment for neuropsychiatric disorder-associated genes and were conserved across platforms and species. Our study establishes a scalable framework for spatial isoform analysis and provides a resource for understanding transcriptomic diversity in complex tissues.

Animals↗

Integrative Multi-Omics Analysis of Stem Growth Habit Divergence in Wild Soybean (Glycine soja).

Stem architecture is a major determinant of lodging resistance, biomass accumulation, and harvest efficiency in soybean. However, the molecular features associated with contrasting stem growth habits in wild soybean remain incompletely characterised. Here, we performed an integrated transcriptomic, metabolomic, and epigenomic analysis of stem growth-habit divergence in wild soybean, comparing the wild-type accession ZYD7068 with contrasting vining and erect mutant lines derived from carbon-ion beam mutagenesis. Pairwise transcriptomic comparisons identified between 20&#x2009;311 and 28&#x2009;705 differentially expressed genes per contrast, with a core set of 2672 genes consistently altered across the comparisons. Functional enrichment, gene set variation analysis, and gene set enrichment analysis converged on xylem and phloem pattern formation as a prominent molecular pathway associated with growth-habit divergence. Random forest analysis identified BBR-BPC and ARF transcription factor families as major molecular discriminators, while metabolomic profiling revealed distinct metabolic profiles involving amino-acid-derived and lipid-associated metabolites. Whole-genome bisulfite sequencing revealed context-specific DNA methylation differences, including substantial variation in CHG methylation among erect mutant lines. Integrated network and in silico perturbation analyses prioritised four candidate genes associated with vascular development for future functional validation. Together, these results provide a multi-layer molecular resource for investigating stem growth-habit divergence in G. soja and establish testable candidate pathways and genes for subsequent functional studies and soybean improvement.

glycine soja↗

Spatial analysis reveals the evolving organization of IDH-mutant glioma.

Adult diffuse gliomas are composed of malignant cell states interwoven with the non-malignant brain microenvironment. Here, we combine spatial transcriptomics and spatial proteomics of isocitrate dehydrogenase (IDH)-mutant gliomas to define organizational principles across histological grades. In low-grade tumors, spatial organization is shaped by underlying brain anatomy. We identify a functional white-gray matter junction that restricts cortical invasion and is associated with marked changes in tumor composition and cellular phenotypes. This junction is preferentially traversed by oligodendrocyte progenitor (OPC)-like malignant cells, suggesting a role in tumor expansion. In contrast, tumors with intermediate histological features are largely disorganized, with few recurring interactions between cancer cell states and microenvironmental cell types. In high-grade tumors, hypoxia-associated structure emerges, resembling IDH-wild-type glioblastoma. Together, these findings reveal two independent axes of spatial organization-from anatomy-driven structure in low-grade tumors to hypoxia-driven organization in high-grade tumors-and establish a framework linking tumor grade to recurrent spatial interactions.

Isocitrate Dehydrogenase↗

GSK3B inhibition partially reverses brain ethanol-induced transcriptomic changes in C57BL/6J mice: Expression network co-analysis with human genome-wide association studies.

Alcohol use disorder (AUD) is a chronic behavioral disease with greater than 50% of its risk due to complex genetic contributions. Existing pharmacological and behavioral treatments for AUD are minimally effective and underutilized. Animal model behavioral genetics and human genome-wide association studies have begun to identify individual genes contributing to the progressive compulsive consumption of ethanol that occurs with AUD, promising possible new therapeutic targets. Our laboratory has previously identified Gsk3b as a central member in a network of ethanol-responsive genes in mouse prefrontal cortex, which altered ethanol consumption with genetic manipulation and was also significantly associated with risk for alcohol dependence in human genome-wide association studies. Here we perform detailed brain RNA sequencing transcriptomic studies to characterize a highly specific and clinically available GSK3B pharmacological inhibitor, tideglusib, as a possible therapeutic for clinical trials on treatment of AUD. A model of chronic intermittent ethanol consumption was used to study gene expression changes in prefrontal cortex and nucleus accumbens in the presence or absence of tideglusib treatment. Multivariate analysis of differentially expressed genes showed that tideglusib largely reversed ethanol- induced expression changes for two prominent clusters of genes in both prefrontal cortex and nucleus accumbens. Bioinformatic analysis showed these genes to have prominent roles in neuronal functioning and synaptic activity. Additionally, mouse brain differential gene expression data was analyzed together with human protein-protein interaction and genome-wide association studies on AUD to derive networks responding to tideglusib and relevant to human genetic risk for alcohol dependence. These studies identified discrete networks significantly enriched with genes provisionally associated with AUD, and provide key information on central hubs of such networks. Together these studies document tideglusib as a major modulator of chronic ethanol consumption-evoked brain gene expression signatures, and identify possible new targets for therapeutic modulation of AUD.

Journal Article↗

Species-specific transcriptomic changes upon respiratory syncytial virus infection in cotton rats.

The cotton rat (Sigmodon) is the gold standard pre-clinical small animal model for respiratory viral pathogens, especially for respiratory syncytial virus (RSV). However, without a reference genome or a published transcriptome, studies requiring gene expression analysis in cotton rats are severely limited. The aims of this study were to generate a comprehensive transcriptome from multiple tissues of two species of cotton rats that are commonly used as animal models (Sigmodon fulviventer and Sigmodon hispidus), and to compare and contrast gene expression changes and immune responses to RSV infection between the two species. Transcriptomes were assembled from lung, spleen, kidney, heart, and intestines for each species with a contig N50&#x2009;>&#x2009;1600. Annotation of contigs generated nearly 120,000 gene annotations for each species. The transcriptomes of S. fulviventer and S. hispidus were then used to assess immune response to RSV infection. We identified 238 unique genes that are significantly differentially expressed, including several genes implicated in RSV infection (e.g., Mx2, I27L2, LY6E, Viperin, Keratin 6A, ISG15, CXCL10, CXCL11, IRF9) as well as novel genes that have not previously described in RSV research (LG3BP, SYWC, ABEC1, IIGP1, CREB1). This study presents two comprehensive transcriptome references as resources for future gene expression analysis studies in the cotton rat model, as well as provides gene sequences for mechanistic characterization of molecular pathways. Overall, our results provide generalizable insights into the effect of host genetics on host-virus interactions, as well as identify new host therapeutic targets for RSV treatment and prevention.

Animals↗

Cardiovascular Complications Are Increased in Inflammatory Bowel Disease: A Path Toward Achievement of a Personalized Risk Estimation.

Background/Objectives: The global burden of inflammatory bowel diseases (IBDs) continues to rise, with up to 50% of patients experiencing extraintestinal manifestations. Cardiovascular diseases (CVDs) are of particular concern, ranking as the second leading cause of mortality in this population. Despite a comparatively lower prevalence of traditional cardiovascular (CV) risk factors, the persistent inflammatory milieu and immune dysregulation inherent to IBD may contribute to heightened CVD risk. In this study, following a review of the current literature, an ongoing prospective trial designed to clarify CV risk profiles in IBD patients is detailed. Methods: A cohort of patients with IBD is being enrolled for comprehensive baseline evaluation of CV risk factors, lifestyle metrics, and disease characteristics. The incidence of major adverse cardiovascular events (MACEs) will be tracked and contrasted with a gender- and age-matched non-IBD cohort over a 2-year follow-up period. In cases of MACE occurrence, a multi-omics analysis-including genomic, proteomic, transcriptomic, and microbiome profiling-will be performed, along with a parallel evaluation in matched IBD controls without MACE. An artificial intelligence (AI) framework will support the analysis of this complex dataset. Results: To date, over 150 patients with IBD have been enrolled, and detailed phenotypic data and biological samples have been collected. Conclusions: We aim to introduce an IBD-specific correction factor for existing CV risk scores upon study completion. This is particularly relevant for individuals under 40 years of age, who are often inadequately assessed by current risk stratification models.

Crohn&#x2019;s disease↗

Complement Activation Linked to Type II Interferon Signaling in Still Disease.

OBJECTIVE: Still disease (SD) is an autoinflammatory syndrome characterized by innate immune dysregulation. Although complement can drive inflammation, its involvement in SD remains to be defined. Thus, we aimed to assess complement activation in SD. METHODS: Complement was assessed using transcriptomic, proteomic, and in vitro approaches. RNA sequencing of monocytes was performed in healthy donors (n&#xa0;=&#xa0;15), those with nonsystemic juvenile idiopathic arthritis (JIA; n&#xa0;=&#xa0;8), patients with SD at onset (n&#xa0;=&#xa0;19) and remission (n&#xa0;=&#xa0;18), and those with macrophage activation syndrome (n&#xa0;=&#xa0;2). Whole-blood NanoString analysis of complement and interferon (IFN)-related gene expression was conducted in patients with SD (active n&#xa0;=&#xa0;41, inactive n&#xa0;=&#xa0;33) and JIA (n > 600). Complement products and inflammatory mediators were measured by Luminex and enzyme-linked immunosorbent assay. Functional complement activity was evaluated in SD (active n&#xa0;=&#xa0;30, inactive n&#xa0;=&#xa0;67) and JIA sera (n&#xa0;=&#xa0;12). In vitro assays examined monocytic C1q induction and complement-mediated CD8+ T cell activation. RESULTS: Transcriptomic analysis of monocytes from patients with SD at onset revealed enrichment of the complement cascade compared with patients in remission (adjusted P&#xa0;=&#xa0;3.7&#x2009;&#xd7;&#x2009;10-36), ranking among the top 10 up-regulated pathways. Classical complement genes (C1QB/C1QC) were markedly up-regulated in onset SD compared with patients with remission SD and JIA. Patients with active SD showed increased C1q, C3a, C5a, and terminal complement complex protein levels, with enhanced functional classical complement activity. Whole-blood C1QB/C1QC expression correlated with IFN-related markers, including interleukin-18, CXCL9, and CXCL10. Recombinant IFN-&#x3b3; induced monocytic C1q, whereas C1q enhanced IFN-&#x3b3; production by CD8+ T cells, supporting a feed-forward loop. CONCLUSION: SD is characterized by complement activation with marked up-regulation of C1q, which is closely linked to IFN-&#x3b3;/type II signaling.

Journal Article↗

Deep learning-based multimodal pathogenomics integration for precision cancer prognosis.

BACKGROUND: Recent studies have revealed valuable prognostic insights in haematoxylin and eosin (H&E)-stained histological sections and transcriptomic profiles, suggesting potential applications in machine learning. However, existing methods lack sufficient intra- and inter-modal interactions, and face challenges in clinical validation due to incomplete multimodal data. METHODS: We proposed PathoGems (PathoGenomics-based integrative survival prediction), a weakly-supervised, interpretable multimodal learning framework that integrates histology and genomic profiles for precise cancer prognosis prediction. To evaluate the robustness of PathoGems, we initially curated a dataset of 1965 cases across four cohorts from The Cancer Genome Atlas (TCGA), including breast, colorectal, glioblastoma, and esophageal cancers. For external validation, PathoGems was further evaluated on four independent cohorts, consisting of 76 breast cancer and 41 esophageal squamous cell carcinoma cases from Zhejiang Cancer Hospital, as well as 102 colorectal cancer and 58 glioblastoma cases from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). RESULTS: PathoGems effectively stratified patients into favorable and unfavorable risk groups, revealing significant differences in histological patterns, genomic features, and overall survival (log-rank test, p&#x2009;<&#x2009;0.05). Moreover, the model&#x2019;s predictions are further supported by visualization and transcriptomic analysis, enhancing interpretability and reliability. CONCLUSIONS: By fusing histological and clinicogenomic multimodal models, PathoGems will provide a solid foundation for developing an innovative tool that aids clinicians in making informed decisions and selection personalized treatment strategies for cancer patients.

Humans↗