Search Results (2,723)

Myalgic encephalomyelitis (ME) is characterized by profound fatigue, post-exertional malaise (PEM), and cognitive dysfunction. Despite its clinical significance, the pathophysiology of PEM and disease heterogeneity remain unclear, and no validated biomarkers are available for rapid diagnosis or monitoring. We aimed to develop a screening approach combining label-free Raman spectroscopy (RS) and machine learning modeling (ML) to detect biomolecular changes in blood plasma and differentiate patients with ME from sedentary healthy controls. Blood plasma was collected from 115 patients with ME and 45 controls at rest (T0) and 90 min after a standardized, non-invasive stress test designed to induce PEM. Plasma samples were analyzed by RS, and ML models were developed independently at each time point to differentiate patients with ME and controls. The RS-ML models identified spectral features consistent with contributions from proteins, lipids, and low-molecular-weight metabolites. At T0 and T90, the area under the receiver operating characteristic curve, accuracy, specificity and sensitivity were 0.85 and 0.83, 79% and 84%, 82% and 90%, and 73% and 69%, respectively. RS-ML provides a rapid, low-cost approach to detect ME-associated biomolecular signatures in plasma and capture biochemical alterations associated with standardized stress. Full article

Disease-modifying therapies (DMT)s) for relapsing-remitting multiple sclerosis (RRMS) act through distinct immunological mechanisms, yet the within-patient molecular response programs associated with these therapies remain incompletely defined. Here, we reanalyzed publicly available peripheral blood mononuclear cell (PBMC) miRNA microarray data (GSE230064) using a longitudinal, robustness-focused framework to compare therapy-associated miRNA response patterns following cladribine versus ocrelizumab treatment. Baseline (t0) and 6-month post-treatment (t1) samples were paired within individuals and technical replicates consolidated prior to analysis, yielding a final paired cohort of four cladribine-treated and six ocrelizumab-treated patients. Within each treatment arm, we quantified per-patient Δ-miRNA (t1 − t0) values and prioritized therapy-associated response features using a multi-evidence framework integrating effect direction, magnitude, directional consistency across individuals, and leave-one-out sensitivity. Cladribine treatment was associated with a highly coordinated, directionally concordant upregulation of five miRNAs including hsa-miR-27a-3p, hsa-miR-27b-3p, hsa-miR-503-5p, hsa-miR-148a-3p, and hsa-miR-26a-5p, all exhibiting 100% directional stability across patients and mean Δ-expression values ranging from +0.77 to +1.38. These miRNAs target pathways relevant to MS pathophysiology, including Th17/Treg balance, Wnt-β-catenin signaling, macrophage polarization, and epigenetic immune regulation. In contrast, ocrelizumab elicited a more selective response pattern, with five miRNAs including hsa-miR-100-5p, hsa-miR-410-3p, hsa-miR-432-5p, hsa-miR-296-5p, and hsa-miR-485-3p showing moderate directional stability (83%) and greater inter-individual heterogeneity, consistent with the more targeted mechanism of CD20+ B-cell depletion. Notably, the two treatment-associated signatures were non-overlapping, with hsa-miR-27b-3p representing the only miRNA shared with prior cross-sectional analyses of this dataset. The identified ocrelizumab-associated miRNAs implicate pathways including mTOR/IGF1R signaling, NF-κB regulation, RNA editing, and mitochondrial biogenesis, several of which are dysregulated in progressive MS. Together, these findings demonstrate that cladribine and ocrelizumab induce distinct, treatment-specific miRNA response architectures that reflect their divergent immunological mechanisms. This work establishes a stability-aware analytic template for extracting reproducible longitudinal miRNA signals from small paired RRMS cohorts and provides a ranked set of biologically plausible candidate miRNAs for prospective validation and mechanistic investigation. Full article

Background: Low-dose aspirin (LDA) reduces preeclampsia (PE) risk by up to 40%, yet its molecular effects on chorion trophoblast cells (CTCs), a fetal membrane lineage at the feto-maternal interface, remain obscure. CTCs form a structural and immunoregulatory barrier whose dysfunction drives inflammation-associated membrane pathology in PE. Extracellular vesicles (EVs) released by CTCs may encode cellular stress and adaptation states, offering a molecular window into aspirin’s timing-dependent effects on PE risk modification. Methods: Human CTCs were challenged with cigarette smoke extract (CSE) to model oxidative stress-driven PE pathology. Two paradigms were tested: (1) prophylactic aspirin (4 and 40 µg/mL) before and/or flanking the CSE, and (2) therapeutic aspirin after the CSE challenge. The EVs were isolated via ultracentrifugation and size-exclusion chromatography, characterized by nanoparticle tracking and immunoblotting, and profiled by quantitative mass spectrometry. A network pathway analysis and machine learning biomarker selection defined the EV-encoded molecular states. Results: The CTC-derived EVs from the CSE-exposed cells carried a PE-like proteomic signature marked by suppressed VEGF/ECM remodeling, activated TNF-p53 apoptotic signaling, and heightened inflammation. Prophylactic low-dose aspirin shifted the EV cargo toward an EV-encoded signature consistent with preserved angiogenic potential (enrichment of VEGFA, COL1A1, and MMP14) and predicted attenuation of apoptotic and NF-κB pathway activity by an Ingenuity Pathway Analysis. High-dose aspirin produced broad transcriptional suppression without an accompanying pro-angiogenic EV signature. Therapeutic (post-injury) aspirin partially attenuated the injury-associated EV cargo but did not restore the angiogenic EV signature. An exploratory machine learning analysis of EV proteomes identified a candidate prophylactic biomarker panel anchored by HSPA8, SERPINF2, COL4A1, and PLOD1, mapped to the predicted angiogenic recovery and redox-balance pathways. These EV cargo readouts represent the predicted molecular states and require functional validation before clinical interpretation. Conclusions: The CTC-derived EV proteomic signatures capture the dose- and timing-dependent aspirin effects in this in vitro CTC model, positioning the chorion as a candidate pharmacological “secondary responder” favoring cellular resilience over classical anti-inflammatory suppression. As an exploratory hypothesis-generating study, EV-based molecular profiling could provide a foundation for future investigations aimed at stratifying aspirin responders from non-responders, although clinical validation in maternal plasma cohorts will be required before any translational application. Full article

We report a new approach to enhance the photonic response of thin-film topological insulator Bi₂Se₃ by significantly reducing twin domains and antiphase disorder. The strategy employs closely lattice-matched trigonal substrates combined with surface structuring to preferentially seed a single rotational domain before epitaxy. Characterization using optical second harmonic generation (SHG), nonlinear optical tensor analysis, X-ray diffraction, and atomic force microscopy confirms the near-single crystal Bi₂Se₃ heteroepitaxial layers. These results show a clear six-fold symmetric sin²(3ϕ) SHG pattern at normal incidence, and a vanishingly small 100-to-1 peak-height ratio from X-ray pole-scans showing negligible twinning. These results show that this approach can yield near perfect single crystal heteroepitaxial Bi₂Se₃ whose photonic properties converge to those of bulk-grown single crystals. Full article

Early cancer detection using minimally invasive biomarkers remains a significant challenge, particularly in early-stage disease, where circulating tumor DNA is often below the limit of detection. Extracellular vesicles (EVs), which are actively secreted by viable cancer cells and carry tumor-associated proteins, represent a promising alternative target for liquid biopsy. In this study, we developed EV-finder^®, a conceptual framework for the direct detection of EV-associated proteins in serum using proximity extension assay (PEA) technology. Unlike conventional EV-based analytical methods that require prior EV isolation or enrichment, the EV-finder approach enables direct profiling of EV-associated proteins from small serum volumes without an EV isolation step, thereby simplifying the analytical workflow while preserving EV-derived molecular information. Using serum samples from patients with five cancer types (n = 193) and independent healthy controls (n = 138), we established a two-step supervised machine learning framework for cancer detection and tissue-of-origin prediction. The screening model demonstrated promising discriminative performance, with an AUC of 0.985, sensitivity of 0.929, and specificity of 0.957. Notably, no false positives were observed in an external Japanese control cohort, whereas 4 of 29 Korean control samples were classified as cancer-positive. Analysis of EV-associated protein profiles identified both pan-cancer and cancer-type-specific signatures, supporting their value for multi-cancer detection. Collectively, these findings demonstrate the potential feasibility of direct detection of EV-associated proteins from serum using PEA technology and highlight its potential as a scalable and minimally invasive strategy for multi-cancer screening. Full article

Background/Objectives: Prostate cancer (PCa) remains a prevalent malignancy among men, often complicated by recurrence and unfavorable clinical outcomes. Consequently, precise risk stratification and timely clinical intervention are paramount. Initially, we delineated distinct expression profiles of histone modification regulators via unsupervised clustering, identifying PCa subtypes with divergent survival probabilities and biological phenotypes. Subsequently, we sought to develop a prognostic gene signature, derived from the transcriptomic variations among these regulator-defined subtypes, to predict outcomes in PCa patients following radical prostatectomy (RP). Methods: Clinical and transcriptomic data from PCa cohorts were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) repositories for comprehensive analysis. Subtypes driven by histone modification regulators were established using unsupervised consensus clustering, followed by in-depth characterization of their molecular features and associated pathways. A risk-scoring model was then developed to evaluate its prognostic efficacy in this patient population. Results: Stratification based on histone modification regulators yielded four distinct PCa subtypes exhibiting heterogeneous survival outcomes, functional pathways, and genomic mutational landscapes. Following rigorous feature selection, a 21-gene risk signature (HIS_score)—comprising MXD3, CCDC28B, COL11A2, SLC39A5, GPT, DNASE1L2, PIF1, KRTAP5-9, TTLL10, KRTAP5-1, KRTAP5-10, HAGHL, MSLNL, AMH, NKAIN4, CCDC114, SLC9A3, SULT1E1, ALB, SLC6A14, and RPE65—was constructed. Survival analyses demonstrated that patients assigned to the high HIS_score cohort experienced significantly worse clinical outcomes compared to their low-score counterparts. Furthermore, we integrated this signature into a novel clinical nomogram to facilitate individualized prognostic assessments. Conclusions: Derived from transcriptomic disparities between extreme epigenetic subtypes, the HIS_score and its associated nomogram serve as robust prognostic instruments. These tools effectively encapsulate the downstream transcriptional sequelae of histone modification dysregulation, offering clinicians a valuable framework to accurately predict post-RP outcomes and expedite the formulation of personalized therapeutic strategies. Full article

Background: Glioblastoma (GBM) is characterized by pronounced transcriptional plasticity and a highly structured immune microenvironment, yet the molecular features associated with tumor-state transitions and immune remodeling remain incompletely understood. Methods: We used an integrative multi-omics framework to examine how secreted phosphoprotein 1 (SPP1) relates to tumor microenvironment organization in human gliomas. Results: Single-cell analyses associated SPP1 with myeloid populations, mesenchymal-like (MES-like) malignant states, inflammatory regulatory programs, and inferred ligand–receptor co-expression patterns involving SPP1–CD44 and SPP1–integrin pairs. Spatial transcriptomic analyses showed that SPP1-high regions were enriched for estimated myeloid abundance, MES-like tumor signal, and ECM/angiogenic programs, supporting an SPP1-associated spatial mesenchymal–myeloid program in GBM. Computational perturbation analyses provided network-level support for SPP1–CD44-associated stress-responsive programs. HPA immunohistochemistry provided tissue-level protein context for SPP1 and related mesenchymal/receptor-associated components. Ivy GAP analysis showed enrichment of SPP1-associated features in core-like anatomic compartments, and CODEX spatial protein imaging provided antibody-panel-based contextual support for mesenchymal–myeloid-associated features. In the TCGA-GBM cohort, elevated SPP1 expression and an SPP1-associated mesenchymal signature were associated with poorer overall survival. Conclusions: These findings support an inferential model in which SPP1 is associated with spatial mesenchymal–myeloid organization in GBM and nominate SPP1-associated programs as candidate readouts of tumor plasticity, inflammatory myeloid remodeling, and spatial tumor microenvironment organization. Full article

The gut microbiota regulates host physiology and drives extraintestinal diseases through the gut–X axis. Bile acids (BAs) function as key mediators of this interorgan crosstalk by activating nuclear and membrane receptors (FXR, TGR5, PXR, VDR). Traditional Chinese Medicine (TCM) demonstrates efficacy across multiple organ systems through multi-component formulations. This narrative review synthesizes evidence from preclinical and clinical studies supporting that TCM exerts systemic protection via strategic modulation of the microbiota–BA–host receptor axis, which functions as a core regulatory circuit within a larger network of microbial metabolites. Mechanistically, representative TCM formulas remodel gut microbial ecology and reinforce intestinal barrier integrity, leading to optimized BA profiles. These favorable BA signatures engage tissue-specific receptor signaling to resolve inflammation, mitigate fibrosis, and restore metabolic homeostasis across the gut–heart, gut–kidney, gut–liver, gut–bone, and gut–endocrine axes. Support for this causal relationship is provided by microbiota depletion, fecal transplantation, and multi-omics studies, collectively suggesting that TCM’s benefits are microbiota-dependent and at least partially BA-mediated. Moreover, context-dependent modulation of BA receptors, such as differential regulation of FXR, enables TCM to achieve pathology-specific outcomes. Current evidence is derived predominantly from preclinical models, and clinical data remain lacking. Nonetheless, the microbiota–BA–organ axis thus provides a potential framework for understanding TCM’s systemic actions and establishes a molecular basis for developing microbiome-informed precision therapeutics. Future directions include patient stratification and precision intervention design inspired by TCM’s ecological modulation strategies. Full article

Background: Recruitment and activation of monocyte-derived macrophages (MoMFs) sustain cholangitis in primary biliary cholangitis (PBC), but whether MoMFs amplify inflammation through ferroptosis remains unclear. We defined ferroptotic programs in MoMFs and evaluated the calpain/ACSL4 axis as a regulatory and therapeutic node. Methods: We analysed a public human liver single-cell RNA sequencing (scRNA-seq) dataset and examined MoMF-associated ACSL4 and 4-hydroxynonenal (4-HNE) signals in CD11b⁺CD68⁺ cells by multiplex immunofluorescence. We used a 2OA–BSA-induced PBC-like mouse model to assess liver injury, inflammation and ferroptosis-related markers and tested Liproxstatin-1 (Lip-1), rosiglitazone (ROSI) or the calpain inhibitor PD150606. Bone marrow-derived macrophages (BMDMs) from control and PBC mice were profiled and challenged with RSL3, with or without Ferrostatin-1 (Fer-1), ROSI or PD150606. Results: MoMFs were expanded in PBC livers and showed the strongest induction of ferroptosis signatures, centered on ACSL4, with enhanced inflammatory crosstalk with cholangiocytes. Human PBC tissues showed increased CD11b⁺CD68⁺ cells positive for ACSL4 or 4-HNE. In PBC-like mice, malondialdehyde (MDA) increased and glutathione (GSH) decreased, and macrophages showed greater colocalization with ferroptosis markers; Lip-1, ROSI or PD150606 improved liver biochemistry, reduced inflammation scores and limited macrophage infiltration. PBC-derived BMDMs upregulated ACSL4 and CAPN1/2 and were more sensitive to RSL3; Fer-1, ROSI or PD150606 attenuated ferroptosis-associated molecular changes. Conclusions: MoMF ferroptosis is prominently engaged in PBC, and our findings implicate a pharmacologically tractable calpain/ACSL4 axis that may contribute to macrophage ferroptotic susceptibility and inflammatory liver injury. Full article

Skeletal muscle satellite cells (SMSCs) are essential for embryonic myogenesis and postnatal muscle regeneration; however, their cellular heterogeneity and transcriptional dynamics during avian development remain largely unexplored. Here, we performed single-cell RNA sequencing (scRNA-seq) on 42,886 cells isolated from goose leg muscles across four embryonic stages (E13, E15, E18, and E23), with each stage comprising pooled tissues from four female embryos. Unbiased clustering resolved 22 transcriptionally distinct clusters representing six major cell types—satellite cells, myocytes, fibro-adipogenic progenitors, endothelial cells, immune cells, and Schwann cells—with satellite cells being the most abundant. Satellite cells were further subdivided into three functional states (quiescent, activated, and proliferative/differentiating), which followed a continuous, linear pseudotime trajectory from early to late embryonic stages. This trajectory was marked by a progressive downregulation of stemness-associated regulators (e.g., PAX7) and upregulation of myogenic commitment and differentiation factors (e.g., MYF5, MYOD1, and MYOG), faithfully mirroring chronological development. Cell–cell communication analysis revealed that quiescent satellite cells exhibited the most extensive intercellular signaling networks (e.g., FGFR, Ephrin, collagen, CADM), whereas activated and proliferative/differentiating cells showed progressively diminished communication capacity. Across developmental stages, the contribution intensities of key signaling pathways—including SEMA6, CDH, FGF, LAMININ, MK, MPZ, CADM, FN1, and COLLAGEN—varied significantly among satellite cell states, indicating state-specific responsiveness to microenvironmental cues. Collectively, these findings demonstrate that satellite cells dynamically coordinate extrinsic signal integration with intrinsic differentiation programs to achieve orderly myogenic progression. This study provides a high-resolution single-cell atlas of goose SMSC development, uncovering subpopulation heterogeneity, state-specific molecular signatures, and key signaling pathways, with important implications for avian muscle biology and genetic improvement of poultry. Full article

MicroRNAs (miRNAs) are a highly conserved class of small (19–25 nucleotides) non-coding RNAs that play critical roles in post-translational gene regulation. Dysregulation of miRNA expression has been widely implicated in the development and progression of numerous diseases, particularly cancer, positioning them as promising candidates for diagnostic and prognostic applications. In parallel, miRNAs are frequently detected in extracellular vesicles (EVs), where they contribute to intercellular communication and have emerged as attractive non-invasive biomarkers. Importantly, EV-associated miRNA profiles do not always directly mirror intracellular miRNA abundance. While altered cellular expression can influence EV-miRNA content, selective and regulated sorting mechanisms also actively shape EV cargo composition. These include sequence- and motif-based recognition elements (such as EXOmotifs), RNA-binding proteins (including hnRNPA2B1, YBX1, and SYNCRIP), and lipid-associated pathways such as ceramide-dependent mechanisms. Together, these processes enable the preferential packaging of specific miRNAs into EVs, independent of their relative cellular expression levels. This review therefore integrates both perspectives: it summarizes current evidence supporting dysregulated miRNAs detected in EVs as disease-associated biomarkers and critically examines the molecular mechanisms governing miRNA sorting into EVs. By clarifying the interplay between cellular miRNA dysregulation and active EV loading processes, we highlight the complexity underlying EV-miRNA signatures and underscore the need for standardized mechanistic frameworks to improve their translational utility in cancer diagnostics and beyond. Full article

Neonicotinoids are among the most widely used classes of insecticides worldwide. However, growing evidence links their exposure to metabolic disturbances, including DNA damage, endocrine disruption, and hepatic dysfunction. In this study, transcriptomic analyses were applied to investigate the gene expression changes induced by two neonicotinoids, clothianidin and thiacloprid. Our results revealed distinct treatment-driven transcriptional signatures, characterized by the upregulation of gene sets enriched in pathways associated with mitochondrial regulation, neuronal signaling, and neurodegeneration-related molecular processes, alongside the downregulation of genes involved in core metabolic processes. In addition, neonicotinoid exposure modulated gene sets associated with xenobiotic detoxification, immune response, cell proliferation, and cell adhesion. Notably, clothianidin and thiacloprid induced compound-specific transcriptional profiles, despite sharing a common mechanism of action. Furthermore, combined exposure resulted in gene expression patterns that differed from those observed with individual treatments. Together, these findings demonstrate that neonicotinoids can elicit divergent molecular responses, highlighting the importance of compound-specific toxicological assessment in non-target species. Full article

Neuroscience is a rapidly advancing field; however, a comprehensive understanding of brain function at the molecular, cellular, and systems levels remains incomplete. Neurological and psychiatric disorders represent a major global health burden, highlighting the need for improved diagnostic and therapeutic strategies. Cerebrospinal fluid (CSF) is one of the most informative biofluids for investigating central nervous system (CNS) pathology due to its close biochemical relationship with brain tissue. Recent advances in neurometabolomics, defined as the comprehensive analysis of small-molecule metabolites in CSF, have been driven by the development of highly sensitive and informative mass spectrometry-based techniques. These approaches enable the identification of disease-associated metabolic signatures. This review summarizes current chromatography–mass spectrometry-based methods used in both untargeted and targeted CSF metabolomics, with particular emphasis on their analytical performance, reproducibility, and limitations. Special attention is given to method standardization and validation, as well as to the identification of reliable metabolic biomarkers for the diagnosis and monitoring of neurological disorders, including neurodegenerative, psychiatric, oncological, and neuroinflammatory diseases. Full article

Objectives: Diminished ovarian reserve (DOR) significantly compromises in vitro fertilization (IVF) success. Although systemic markers such as anti-Müllerian hormone (AMH) serve as valuable clinical indicators of the ovarian reserve, they lack the sensitivity to reflect the qualitative deterioration of the follicular microenvironment. Therefore, in this study, we aimed to characterize the inflammatory proteome of follicular fluid (FF) to establish a high-performance auxiliary diagnostic model for DOR. Methods: Utilizing the ultra-sensitive Olink proximity extension assay, we quantified 92 inflammation-related proteins in the FF of 88 participants (67 with DOR and 21 normal controls). Differentially expressed proteins (DEPs) were identified, and their relationships with key clinical indices were evaluated. A robust predictive signature was refined through integrated Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest algorithms, with diagnostic performance assessed via 10-fold cross-validation. Results: Thirty-five DEPs were significantly dysregulated in the FF of patients with DOR, demonstrating strong associations with serum AMH and basal estradiol concentrations. A minimized diagnostic panel comprising four core proteins, adenosine deaminase (ADA), vascular endothelial growth factor A (VEGFA), eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1), and matrix metalloproteinase-1 (MMP-1), was established. This multivariable model achieved an excellent area under the receiver operating characteristic curve (AUC) of 0.953. Conclusions: The identified four-protein signature reflects localized chronic inflammation and early pathophysiological shifts in the DOR follicular microenvironment. As a high-performance molecular index, this panel could complement conventional systemic assessments, provide a reliable means of evaluating follicular viability, and optimize individualized therapeutic strategies. Full article

Micro- and nanoscale mass sensing is crucial for applications such as molecular detection and wearable monitoring. However, the observation of mass perturbations in flexible composite structures requires systematic theoretical evaluation. This study develops a dual-mode vibration-based mass-sensing model based on a film–substrate composite strip. By releasing and re-stretching pre-strain in the soft substrate, the ribbon can reversibly switch between a two-dimensional flat configuration (Mode 1) and a three-dimensional buckled configuration (Mode 2), leading to distinct dynamic responses. Under a finite-deformation Euler–Bernoulli beam assumption, displacement fields and kinematic relations are formulated for both configurations. An energy-based approach is employed to decompose the total energy into stretching and bending contributions, while an added-mass block is incorporated into the kinetic energy as a lumped mass. The governing equations of motion are derived using the Lagrange equations and the Hamiltonian function. Based on these results, the influence of the added mass on displacement signatures is examined, and the mode-dependent observability in the flat versus buckled states is compared, providing an analytical basis for mass sensor evaluation. Full article