Search Results (1,601)

Tumor-associated Tie2-expressing monocytes/macrophages (TEMs) have been implicated in promoting angiogenesis and metastasis in colorectal cancer (CRC), yet the molecular mechanisms linking TEMs infiltration to tumor metastasis and progression remain incompletely defined. This study investigated the distribution of TEMs in CRC and their association with gene expression profiles, microvessel density (MVD), and clinical outcomes. Immunohistochemistry on 30 formalin-fixed paraffin-embedded (FFPE) primary CRC samples revealed that TEMs, which characteristically express tyrosine kinase with immunoglobulin and epidermal growth factor homology domains 2 (Tie2) receptor and CD14, preferentially localize to perivascular regions and are associated with higher histological grade, tumor size, lymph node metastasis, and increased MVD. However, Tie2⁻/CD14⁺ macrophages and CD68⁺ tumor-associated macrophages (TAMs) showed uniform stromal distribution. Gene set enrichment analysis (GSEA) of in silico transcriptomic datasets of metastatic CRC (mCRC) identified enrichment of pathways related to cell–cell recognition, calcium signaling, transcription regulation, and metalloexopeptidase activity in Tie2⁺/CD14⁺ tumors. Subsequent qRT-PCR validation on FFPE primary CRC samples confirmed significant upregulation of C-C chemokine receptor 7 (CCR7), platelet-derived growth factor A (PDGFRA), CBP/p300-interacting transactivator with glutamic acid/aspartic acid-rich carboxyl-terminal domain 2 (CITED2), and carboxypeptidase E (CPE) in TEMs⁺ regions. Notably, angiopoietin1 (Ang1), but not angiopoietin2 (Ang2), was significantly elevated in TEMs⁺ primary tumors. Kaplan–Meier analysis on 1336 CRC patients indicated that high expression of CITED2, CPE, and Ang2 is associated with reduced overall survival. Collectively, these findings suggest that TEM infiltration is linked to transcriptional regulation, biological processes, and enzymatic programs in CRC, potentially contributing to tumor progression and poor prognosis, and highlight CCR7, PDGFRA, CITED2, CPE, and Ang1 as candidate biomarkers for further mechanistic exploration. Full article

Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition marked by heterogeneous behavioral symptoms and systemic comorbidities, including immune and gastrointestinal dysfunctions. Emerging studies suggest that glycosylation—a fundamental post-translational modification regulating cellular communication and immune responses—may play a role in ASD pathophysiology, yet its contribution remains underexplored. Methods: In this study, we developed an integrative transcriptomic and network analysis framework to investigate glycosylation-related gene expression changes and their functional associations in ASD. Using publicly available datasets from bulk and single-cell RNA sequencing of brain and blood tissues, we focused on four prior-knowledge gene subsets: glycogenes, extracellular matrix glycoproteins, immune response genes, and autism risk genes. Results: Differential expression and pathway enrichment analyses revealed consistent dysregulation of glycosylation pathways, including mucin-type O-glycan biosynthesis, glycosaminoglycan metabolism, GPI-anchor formation, and sialylation, across ASD tissues. These transcriptional changes were functionally linked to altered immune signaling (e.g., IL-17, Toll-like receptor, and complement pathways) and synaptic development pathways, forming a distinct glyco-immune axis. Network analysis identified key glycogenes such as GALNT10, NEU1, LMAN2L, and CHST1 as central molecular nodes, interacting with immune and neuronal regulators. Linkage disequilibrium analysis further revealed ASD-associated SNPs influencing the expression of these glycogenes in both blood and brain tissues. Conclusions: Together, these findings support a model in which disrupted glycosylation contributes to ASD pathophysiology by mediating immune dysregulation and altered neuronal connectivity. This study offers a systems-level framework to understand the molecular complexity of ASD and highlights glycogenes as potential biomarkers and targets for future therapeutic exploration. Full article

Background/Objectives: MSS-CRC comprises a heterogeneous group of tumors generally considered “immune cold” due to limited neoantigen generation and T-cell exclusion or inactivation. Current evidence indicates that the composition of T and B immune cells within the tumor microenvironment represents a prognostically relevant factor, significantly associated with both tumor expression profiles and molecular subtypes. Methods: We conducted an exploratory analysis to identify prognostically relevant immune cell components in this group of tumors and to investigate corresponding differences in RNA-based bulk expression and high-resolution spatial transcriptomic profiles. Results: A total of 254 localized mismatch repair-proficient colorectal cancer cases were evaluated. Our findings revealed PD-L1 expression as a robust independent prognostic biomarker associated with favorable outcomes in this specific population. Bulk RNA expression analysis showed that PD-L1-negative tumors exhibited an expression profile consistent with abundant cancer-associated fibroblast infiltration, increased matrix stiffness, and impaired immune activation—features consistent with tumor progression and poorer clinical outcomes. In contrast, PD-L1-positive tumors displayed stromal programs enriched in immune activation and controlled remodeling, consistent with an immunologically active microenvironment. Spatial transcriptomics added an additional layer of evidence, revealing that epithelial to mesenchymal transition-related programs can dominate stromal niches in PD-L1-negative tumors, particularly within macrophage-enriched stromal regions. Conclusions: Our observations suggest an association between PD-L1 expression on immune cells and immune-activated versus mesenchymal-dominant states, potentially occurring within macrophage-enriched stromal niches. These results provide insight into the biological mechanisms underlying disease progression and highlight tumor-associated macrophages as a potential therapeutic target to overcome immune resistance, particularly in PD-L1-negative MSS-CRC tumors. Full article

Breast carcinoma is a major cause of cancer-related mortality among women worldwide. Identifying novel molecular targets remains essential, particularly for aggressive triple-negative breast cancer (TNBC). Leucine-rich alpha-2-glycoprotein 1 (LRG1) has been linked to tumor progression and angiogenesis, but its molecular mechanisms in breast cancer are poorly defined. We evaluated the effects of recombinant human LRG1 (rhLRG1) on cell viability and migration in MDA-MB-231 TNBC cells and performed transcriptomic profiling followed by functional enrichment analyses using GenArise, Cytoscape, and R-based tools. RhLRG1 treatment significantly increased cell viability and migration. Transcriptomic analysis revealed activation of key oncogenic cascades, including the PI3K/AKT, MAPK, and RAS signaling pathways. Hub-gene analysis identified upregulated genes involved in proliferation (NRAS, STAT5B, IGF2), angiogenesis (PGF, ANGPT2), and apoptosis (CASP8, BAD), whereas downregulated genes were associated with apoptotic resistance (BCL2, MCL1) and adhesion (LAMB1, ITGB4). Functional enrichment highlighted LRG1’s role in the bioinformatic analysis of differentially expressed genes that were obtained from microarray assays. LRG1 remodels the tumor microenvironment by promoting proliferation, angiogenesis, and apoptotic sensitivity while repressing resistance-related genes. These findings position LRG1 as a potential diagnostic biomarker and therapeutic target for advanced breast carcinoma. Full article

Exercise adaptation depends on overload that is resolved by recovery, yet the same biology becomes maladaptive when immune, endocrine, metabolic, and muscle-centered stress signals fail to normalize. Exercise-induced maladaptation represents a systems-level failure of biological resolution, with direct relevance to disease-like dysregulation. Functional overreaching, non-functional overreaching, and overtraining syndrome remain difficult to diagnose because no single biomarker provides adequate specificity, temporal stability, or clinical portability. This narrative review synthesizes human and mechanistic evidence across proteomics, transcriptomics, metabolomics, endocrine profiling, extracellular vesicles, and mitochondrial quality-control biology to define the molecular architecture most relevant to athlete monitoring. Across these layers, the most coherent signatures cluster in immune-acute-phase activation, redox-buffering strain, endocrine drift, altered substrate availability, excitation–contraction dysfunction, integrated stress-response signaling, and defects in autophagy–mitophagy and lysosomal remodeling. Three translational elements emerge from this synthesis: a systems-convergence model of recovery failure, a staged biomarker deployment hierarchy, and a provisional recovery failure index. The practical priority is therefore not a solitary marker, but serial phenotype-anchored multimarker panels that connect circulating signals with muscle-centered biology and support decision-making before prolonged recovery failure becomes entrenched. Full article

Background/Objectives: Pancreatic ductal adenocarcinoma (PDAC) is characterized by an extensive desmoplastic microenvironment; however, reproducible stromal-associated biomarkers linked to disease progression remain limited. This study therefore aimed to identify and validate a biologically relevant stromal/extracellular matrix (ECM)-associated candidate biomarker for PDAC. Methods: Three GEO bulk transcriptomic PDAC cohorts (GSE15471, GSE16515, and GSE62452) were integrated for differential expression, functional enrichment, protein–protein interaction, and hub-gene analyses. Candidates identified as a promising biomarker were further evaluated using the following: public proteomic and survival resources; head-to-head receiver operating characteristic (ROC) comparisons against COL1A1, COL3A1, and COL5A1; a progression cohort (GSE43288); and single-nucleus RNA sequencing data (GSE202051). Results: Among 206 shared differentially expressed genes, COL5A2 was the only consensus hub retained across multiple network-ranking methods. COL5A2 protein expression was found to be elevated in tumor tissue and associated with worse overall and disease-free survival. In ROC analyses, COL5A2 exhibited stable tumor-versus-non-tumor discrimination across GSE15471, GSE16515, and GSE62452 (AUC = 0.932, 0.760, and 0.782, respectively) and significantly outperformed COL3A1 in two cohorts. In GSE43288, COL5A2 expression increased along the normal–pancreatic intraepithelial neoplasia–PDAC axis and remained positively associated with ECM and cancer-associated fibroblast (CAF) signature scores after adjustment for disease group. Reanalysis of GSE202051 restricted to the original 18 untreated PDAC specimens revealed that COL5A2 expression was concentrated in fibroblast-lineage compartments, with CAFs accounting for the largest overall contribution and myCAFs demonstrating the strongest per-specimen expression enrichment. Conclusions: COL5A2 is a reproducible stromal/ECM-associated candidate biomarker linked to PDAC progression, with predominant expression in fibroblast/CAF compartments. Full article

Gliomas are aggressive brain tumors with poor prognosis. The contribution of Toxoplasma gondii (T. gondii)-related transcriptional programs to glioma remains unclear. We identified T. gondii infection-related genes from neuroepithelial cell transcriptomes, mapped them to TCGA and CGGA glioma datasets, and validated their expression via RT-qPCR. A prognostic signature (TGRisk) was constructed via Cox and LASSO regression and validated across independent cohorts. Functional, immune, and drug sensitivity analyses were conducted. Forty infection-related genes were identified, enriched in stress responses, microRNA regulation, ribosome biogenesis, and metabolism. The 13-gene TGRisk model significantly separated survival between high- and low-risk groups. A nomogram combining TGRisk with clinical features improved prediction accuracy. High-risk tumors showed immune activation and higher infiltration of CD8⁺ T cells, Tregs, macrophages, and neutrophils, while low-risk tumors showed enhanced neuronal signaling and NK cell activity. Drug sensitivity prediction suggested low-risk patients were more responsive to temozolomide and bortezomib, whereas high-risk patients were more sensitive to dasatinib and ruxolitinib. We developed a novel T. gongdii infection-related gene signature that stratifies glioma patients by prognosis, immune features, and therapeutic vulnerabilities. These findings suggest host–T. gondii interactions and a potential biomarker for patient stratification and personalized therapy. Full article

Clinically robust molecular biomarkers for depression have remained elusive, despite extensive transcriptomic research. This gap is consequential: depression is prevalent and heterogeneous, yet objective measures to quantify burden, stratify patients, and track recovery remain limited. Here, we review evidence that intron retention (IR) can serve as a homeostatic state variable—and therefore a sensitive biomarker—reporting stress adaptation and recovery at an upstream regulatory layer, often preceding or outperforming differential gene expression (DEG) readouts. Mechanistically, IR enables bidirectional fine-tuning of effective gene output: increased IR (IncIR) can throttle output under overload, whereas decreased IR (DecIR) releases this brake to restore gene output. Because these shifts are reversible and treatment-responsive, IR signatures can function not only as disease markers but also as pharmacodynamic metrics for blood-based monitoring of drug response and recovery. To evaluate the clinical utility of IR, we use depression as a proof of concept and focus on two interventions: (i) the Kampo formula hangekobokuto (HKT), which is associated with IR normalization consistent with reduced peripheral inflammatory load; and (ii) ketamine, where IR patterns measured before ketamine treatment in non-responders are linked to stronger innate-immune/antiviral activity, suggesting a higher inflammatory load that may limit treatment benefit. Finally, we discuss transdiagnostic extensions beyond depression, using early cognitive decline (mild cognitive impairment, MCI) as a stringent, biologically distal test case for blood-based IR/DI readouts and motivating independent cohort replication and longitudinal validation. Full article

Chronic kidney disease is rising worldwide, and kidney transplantation remains the preferred modality of kidney replacement therapy. However, long-term graft survival continues to be limited by chronic alloimmune injury, particularly antibody-mediated rejection (ABMR) and its chronic active form. This narrative review synthesizes contemporary evidence on the immunopathogenesis, epidemiology, diagnosis, and management of kidney allograft rejection, with a deliberate focus on studies from the last five years and on United States and European cohorts. We summarize current concepts of T cell–mediated rejection (TCMR), ABMR, mixed and donor-specific antibody (DSA)–negative phenotypes, and the evolution of the Banff classification, highlighting how chronic active ABMR has emerged as a leading cause of death-censored graft loss. We then critically appraise the conventional diagnostic triad of creatinine/eGFR, DSA, and biopsy and review emerging tools, including donor-derived cell-free DNA, urinary chemokines such as CXCL9 and CXCL10, additional blood- and urine-based biomarkers, and biopsy transcriptomics. We also examine how artificial intelligence and machine learning may support digital pathology, multimodal risk prediction, and data integration, while recognizing the current challenges of biological interpretability, external validation, and clinical implementation. Finally, we propose a rejection-focused precision-medicine framework and outline key research gaps, including multicenter validation, trial-ready endpoints, and governance for AI-enabled pathways. Overall, the field is moving from isolated diagnostic signals toward integrated, biologically informed, and clinically actionable approaches to rejection detection and risk stratification. Full article

Background: This study investigates the role of N6-methyladenosine (m6A) regulators in osteoporosis (OP) and their interplay with the immune microenvironment, aiming to identify potential m6A-related biomarkers for OP risk assessment and treatment. Methods: Transcriptomic data from GEO datasets were analyzed for differential expression of 22 m6A regulators and immune infiltration patterns. Consensus clustering and m6Ascore grouping defined molecular subtypes, while machine learning algorithms identified potential biomarkers, leading to the construction and validation of a nomogram. Experimental validation involved peripheral blood monocytes (PBMCs) transcriptome sequencing and Western blot of bone tissue. Results: FTO, HNRNPC, and METTL4 were upregulated, while CBLL1 and YTHDF2 were downregulated in OP, with two distinct m6A modification patterns and immune phenotypes identified. METTL4, HIRA, MATN4, and YTHDF2 were selected as potential biomarkers, and the nomogram demonstrated favorable predictive performance in training and external datasets. Single-cell RNA sequencing confirmed the cellular distribution of these biomarkers. HIRA heterogeneity in Marrow Mesenchymal Stem Cells (BMSCs) was associated with distinct cell–cell communication patterns. Transcriptome sequencing confirmed HIRA RNA downregulation in OP PBMCs, and Western blot verified decreased HIRA protein in OP bone tissue. Conclusions: This study establishes a potential m6A-related biomarker signature for OP and provides multi-level experimental evidence that HIRA is a consistently downregulated biomarker, linking epigenetic modification to immune dysregulation in osteoporosis. Full article

Background: Infective endocarditis (IE) affects both native and prosthetic heart valves, the endocardial surface, as well as cardiac implantable electronic devices. Identifying specific IE biomarkers for its early risk stratification remains crucial, particularly in cases with blood culture-negative endocarditis. Methods: Eleven native heart valves obtained from IE and calcific aortic valve disease (CAVD) patients were analyzed. Immunohistochemical analysis of a pan-leukocyte marker (CD45), macrophage marker (CD68), T-lymphocyte marker (CD3), B-lymphocyte marker (CD19), neutrophil myeloperoxidase (MPO), and marker of vascular endothelial cells (CD31) was performed. Differentially expressed genes (DEGs) were identified by whole-transcriptome sequencing; proteomic profiling was performed by dot-blotting. Results: The immunophenotyping demonstrates the infiltration of macrophages and neutrophils, as well as occasional T-lymphocytes in the IE-affected aortic valves, and the CAVD-affected heart valves were characterized by the absence of neutrophils. For the whole-transcriptome sequencing, 157 DEGs were identified: 124 DEGs were upregulated, and 33 genes were downregulated in the IE-affected heart valves compared to the CAVD-affected ones. According to the dot-blotting, 35 cytokines were identified in the studied heart valves, but only 21 molecules were expressed in both IE and CAVD-affected heart valves. Analysis of proteases and their inhibitors allowed the identification of 13 protease molecules and 18 enzyme inhibitor molecules in all examined heart valves. Conclusions: The results of the present study can help to improve our understanding of the IE pathogenesis. In addition, we identified the candidate cellular and molecular-genetic features of IE-affected native heart valves. Full article

Objectives: To overcome the limitations of invasive diagnostic approaches for ulcerative colitis (UC) diagnosis, this study integrates liquid chromatography–mass spectrometry (LC–MS)-based serum metabolomics with mucosal transcriptomics to elucidate the interplay between systemic metabolic perturbations and neuroendocrine signaling in UC pathogenesis. Methods: Serum metabolites and mucosal differentially expressed genes (DEGs) were identified through multi-omics profiling. Key neurotransmitter receptor-related genes (NRRGs) were prioritized using three machine learning algorithms: LASSO, Random Forest, and SVM-RFE. A three-gene diagnostic nomogram was developed and rigorously validated across multiple independent cohorts (GSE48958, GSE73661) using receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA). Results: The integrated analysis revealed 334 dysregulated metabolites and 3093 DEGs, both converging on the serotonergic synapse pathway. Specific molecular alterations were uncovered, including tryptophan depletion linked to the downregulation of SLC6A4, concomitant with abnormal serotonin accumulation and PTGS2-mediated inflammatory responses. The three-gene signature, HTR3C, RPS6KA6, and NETO2, formed a highly robust diagnostic model, achieving an area under the ROC curve (AUC) exceeding 0.96 in both the training cohort and external validation sets. Conclusions: This multi-omics study delineates a neuroimmune mechanism in UC centered on dysregulation of the serotonergic synapse. The resulting three-gene nomogram identifies a candidate biomarker signature that demonstrates strong discriminative potential; however, given the exceptionally high performance metrics, these findings should be interpreted as a preliminary diagnostic framework rather than a clinically validated tool, and its efficacy relative to standard markers like CRP or fecal calprotectin requires further investigation in prospective real-world cohorts. Nonetheless, this study provides critical mechanistic insights into gut–brain axis dysfunction in UC. Full article

High ammonia nitrogen stress significantly compromises the survival of Litopenaeus vannamei under low-salinity conditions. However, existing studies predominantly focus on ammonia nitrogen responses under single stressors or normal seawater salinity. The molecular regulatory mechanisms, metabolic remodeling patterns, and key pathway interactions in shrimp subjected to high ammonia nitrogen stress under low-salinity environment remain unclear. In this study, we employed integrated transcriptomic and metabolomic analyses to unveil the underlying molecular responses and metabolic biomarkers in the gills of L. vannamei to ammonia stress under low-salinity conditions. First, L. vannamei underwent low-salinity acclimation from 30‰ to 5‰ salinity and was then reared for one week to acclimate to the experimental environment. Subsequently, shrimp were treated with 42.32 mg/L ammonia nitrogen for a consecutive 96 h period. Integrated transcriptomic and metabolomic analyses elucidated the stress response patterns in the gills of L. vannamei under low-salinity ammonia nitrogen exposure. Specifically, 352, 802, and 140 differentially expressed genes (DEGs) were identified at 12 h, 48 h, and 96 h post-exposure, respectively. GO and KEGG enrichment analyses revealed that the significant DEGs were primarily enriched in six major pathways: autophagy, immune-related pathway, ABC transporter, fatty acid degradation and metabolism, metabolic pathway, and PPAR signaling pathway. Metabolomic profiling identified numerous differentially accumulated metabolites (DAMs) in both positive and negative ion modes, with significantly altered DAMs mainly consisting of organic acids and their derivatives, phospholipids, and other related metabolites. Key DAMs included taurine, guanosine, 1-palmitoyl-sn-glycero-3-phosphocholine, pseudouridine, and betaine. Integrative multi-omics analysis revealed that L. vannamei mediates stress responses by modulating five core pathways under low-salinity/high-ammonia-nitrogen dual stress: fatty acid degradation and metabolism (e.g., acyl-CoA dehydrogenase short chain (Acads), acetyl-CoA acetyltransferase 2 (ACAT2)), autophagy (e.g., autophagy-related protein 101-like (atg101)), immune regulation pathway (e.g., V-type proton ATPase subunit H-like (VhaSFD), actin-5C-like (Act5C)), metabolic pathway (e.g., molybdopterin synthase catalytic subunit-like (Mocs2B), cytochrome P450 2U1-like (Cyp2b1)), and ABC transporter (e.g., ATP-binding cassette sub-family D member 3-like (ABCD3), ATP-binding cassette sub-family B member 10 (ABCB10)). Through characterization of these core pathways, this study reveals the fundamental mechanisms by which L. vannamei responds to high ammonia nitrogen stress following low-salinity acclimation, providing a theoretical foundation for estuarine shrimp farming. Full article

Background/Objectives: Oral squamous cell carcinoma (OSCC) commonly arises from oral potentially malignant disorders (OPMDs), yet reliable molecular biomarkers that predict malignant transformation remain scarce. Because epithelial carcinogenesis follows similar multistep trajectories across multiple organs, pan-cancer transcriptional analyses may reveal conserved pathways relevant to early oral tumorigenesis. This study aimed to identify shared transcriptional signatures across carcinomas and evaluate their applicability to precancerous-to-carcinoma progression. Methods: Bulk RNA-seq data from five carcinomas (lung, colon, breast, prostate, and head and neck squamous cell carcinoma, HNSCC) were obtained from TCGA to identify shared differentially expressed genes (DEGs) (|log₂FC| ≥ 2; FDR < 0.05). Functional enrichment, clustering, and gene–pathway network analyses characterized conserved biological processes. Independent GEO datasets containing premalignant and malignant samples, including OPMD and OSCC cohorts, were examined to assess early-stage relevance. Results: A conserved 45-gene signature was identified, enriched for transcriptional regulation, chromatin organization, and RNA polymerase II-mediated processes. Regulatory hubs, including ZIC5, MYBL2, ONECUT2, POU4F1, and PDX1, and strong upregulation of cancer-testis antigens (MAGEA3, MAGEA6, MAGEC2) were notable. Integration with premalignant datasets revealed 13 genes consistently dysregulated across early lesions, involving pathways such as cell differentiation, apoptosis, and lipid transport. Several genes remained altered from normal tissue through OPMD to OSCC, supporting their potential as stable biomarkers. Conclusions: This study identifies conserved transcriptional programs shared across epithelial cancers and detectable in OPMDs. These findings highlight promising biomarker and regulatory candidates for improving early detection and risk stratification of oral precancer, addressing a critical unmet need in OSCC prevention and clinical management. Full article

Tuberculosis–diabetes mellitus (TB-DM) is increasingly recognized as a syndemic in which chronic metabolic dysregulation amplifies tuberculosis severity, delays treatment response, and increases relapse and mortality. However, conventional systemic correlates soluble cytokines and bulk whole-blood transcriptomic signatures often appear broadly similar between TB and TB-DM. This highlights a key gap: clinically meaningful immune dysfunction in TB-DM likely resides in specific lung and blood cell states that are poorly resolved by bulk assays. Small extracellular vesicles (EVs) in plasma and bronchoalveolar lavage (BAL) provide a tractable “liquid biopsy” layer because their RNA and protein cargo can integrate information from infected macrophages, neutrophils, and epithelial/endothelial compartments, and may also include pathogen-derived components. Yet most EV studies remain bulk and cell-agnostic, and interpretation is constrained by heterogeneous vesicle mixtures, selective cargo packaging, and co-isolated non-vesicular contaminants, issues that are especially problematic for nucleic-acid claims without rigorous controls. In this targeted narrative review (2010–2026), we argue that single-cell and multimodal immune reference atlases, including scRNA-seq/CITE-seq, provide a needed scaffold to link EV cargo patterns to specific immune cell states, pathways, and anatomic compartments in TB-DM, enabling prioritized candidates and testable hypotheses. We outline three complementary frameworks: reference-atlas anchoring to project EV cargo modules onto atlas-defined immune states; orthogonal triangulation combining computational inference with immunoaffinity enrichment, targeted validation, and functional assays; and cautious use of “droplet-era” extracellular signals as hypothesis-generating priors for EV-producing states. Implemented in longitudinal, clinically annotated cohorts with standardized EV workflows, atlas-guided EV profiling could yield cell-of-origin–resolved biomarkers of TB-DM immunopathology and treatment response, while prioritizing mechanistically plausible targets for host-directed intervention. Full article