Search Results (1,350)

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterised by persistent joint inflammation and systemic immune dysregulation. While bone marrow activation has been linked to RA pathogenesis, direct access to bone marrow tissue for progenitor analysis remains limited by ethical and technical constraints. Analysis of progenitor cells in peripheral blood can serve as a surrogate reflecting bone marrow activation. In this study, we analysed peripheral blood cells from 12 RA patients and 9 healthy controls using high-dimensional spectral flow cytometry with a nine-marker panel (CD45, CD31, CD235, CD133, CD34, CD105, CD271, CD90, PDPN). Flow Self-Organizing Map (FlowSOM) clustering identified 20 distinct cell populations. Additionally, a complementary flow cytometry panel was used to assess CD31 expression on immune subsets in peripheral mononuclear cells (PBMCs) from 9 RA and 9 healthy donors of this cohort. RA patients showed increased CD45⁺CD31⁻ immune cells, but not their putative progenitors. Conversely, putative CD45⁺CD31^int progenitors and CD45⁺CD31^int mature cells were reduced, along with CD31 expression on T cells. Levels of CD235a⁺ putative erythroid precursors and CD45⁺CD31⁺ progenitors were significantly increased in RA patients. Three putative stromal cell populations were detected in circulation. Together, these findings reveal expanded erythroid precursor populations and reduced CD31 expression on T cells in RA. Our data underscore broad systemic alterations in cellular homeostasis in RA patients. In conclusion, our results suggest that the loss of CD31 expression on immune cell precursors plays a role in age-associated immune remodelling and immune activation in RA and provides the rationale for further studies on erythroblast differentiation and the functional role of erythroblasts in chronic inflammation. 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: Papillary thyroid cancer (PTC) is the most common form of thyroid malignancy, with an incidence that has been steadily rising globally. Early and accurate diagnosis remains crucial for effective treatment and improved outcomes. MicroRNAs (miRNAs), small non-coding RNA molecules that regulate gene expression, have emerged as promising biomarkers in cancer research due to their stability and accessibility in serum. In this pilot study we compared the expression of 84 consistently reported, malignancy-associated serum miRNAs in patients with PTC (PTC group) and benign thyroid disease (Control group) as potential PTC markers. Methods: A focused panel containing primer assays for 84 human miRNAs that are consistently reported in the literature as being detectable and differentially expressed in serum in various organ-specific cancers was used to measure miRNA levels in serum samples from PTC (n = 8) and benign thyroid disease (n = 6) patients prior to thyroidectomy. Results: Among the 84 miRNAs analyzed, a panel of ten miRNAs showed numerical trends of differential expression between the two groups, including three upregulated (hsa-miR-150-5p, hsa-miR-21-5p, hsa-miR-23a-3p) and seven downregulated miRNAs (hsa-miR-17-5p, hsa-miR-17-3p, hsa-miR-200c-3p, hsa-miR-296-5p, hsa-miR-574-3p, hsa-miR-885-5p, hsa-miR-130-3p). The serum expression levels of hsa-miR-23a-3p were markedly elevated in patients with malignant nodules compared with those with benign lesions, while hsa-miR-574-3p was significantly downregulated in the PTC group. Conclusions: These findings warrant further investigation of hsa-miR-23a-3p and hsa-miR-574-3p in larger cohorts of patients with PTC to validate their potential clinical relevance. Full article

Bladder cancer (BC) is one of the most common urinary tract malignancies. In recent years, increasing attention has been paid to the role of pyroptosis—an inflammatory form of programmed cell death—in cancer development. Gasdermin B (GSDM B), a member of the gasdermin protein family, is involved in the regulation of inflammatory processes and the immune response, and its expression may be associated with cancer development and progression. The aim of the study was to assess GSDM B concentrations in the serum of patients with bladder cancer and to determine its potential diagnostic value in comparison with the tumor markers carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9). This study included patients with bladder cancer hospitalized at the Department of Urology, Medical University of Białystok, and a healthy control group. GSDM B concentrations were determined by Enzyme-Linked Immunosorbent Assay (ELISA), while CEA and CA19-9 concentrations were determined by chemiluminescent microparticle immunoassay (CMIA). Concentrations in the serum of patients with bladder cancer were significantly higher than in the control group. A positive correlation was found between GSDM B and CEA and CA19-9 concentrations, as well as the age of the subjects. Receiver-operating characteristic (ROC) analysis demonstrated moderate but significant diagnostic value of GSDM B in differentiating patients with BC from healthy controls. No significant differences in GSDM B concentrations were observed between low- and high-grade tumors. These findings suggest that GSDM B may serve as a potential diagnostic marker for bladder cancer, particularly when used as part of a multimarker panel. Full article

Satellite DNA (satDNA) is a family of tandemly repeated non-coding sequences in eukaryotic genomes involved in shaping genome architecture and regulation of various biological functions. Within a species, all satDNA families collectively form the satellitome. Satellitomes of Allium species has been explored only superficially, largely due to enormous genome sizes, high transposable element content, and a general lack of reference genomic resources. The emergence of reference genome assemblies now makes it possible to conduct a more in-depth study. Here, we applied a comprehensive bioinformatics approach to study the satellitomes of Allium cepa and Allium fistulosum. Using two complementary bioinformatics pipelines along with available reference genome assemblies, we have created the most complete collection of consensus satDNA sequences of A. cepa and A. fistulosum so far, consisting of 83 and 97 consensus sequences, respectively. The in silico analysis of the genomic distribution allowed the identification of 11 novel candidates for cytogenetic marker panels, including chromosome-specific satDNA families. Validation of satDNA using PCR and FISH confirmed the reliability of the created satellitomes. Furthermore, comparative analysis of satDNA genomic organization and abundance provided insights into the evolution of these species satellitomes. These findings provide a foundational resource that will help illuminate the evolutionary dynamics of Allium satellitomes and pave the way for future cytogenetic studies of Allium species. Full article

This Data Descriptor presents an anonymized, shuffled dataset of creatinine-normalized urinary metabolite measurements from 73 Bulgarian children with autism spectrum disorder (ASD), released to support reuse in secondary analyses and cross-cohort comparisons. The public release represents a pathway-oriented 24-marker subset from a broader urinary diagnostic panel, assembled as a self-contained resource for investigators working in these metabolic domains. Spot urine results are provided as individual-level values after creatinine normalization; for trimethylamine, values below the limit of quantification (LOQ) were replaced with LOQ/2. The deposit contains measurements for 24 urinary markers grouped into three functional classes (neurotransmitters and aromatic amino acid precursors; one-carbon/methylation and vitamin-related metabolites; and energy metabolism/organic acids with microbiome-related amines). The underlying cohort comprised children aged 3–13 years, and no contemporaneous neurotypical control group was enrolled. Second-morning, midstream, acid-stabilized spot urine samples were collected within the provider’s workflow; metabolites were measured by LC–MS/MS, and spot urinary creatinine was measured enzymatically for normalization. The release includes the results table in both XLSX and CSV formats, a reference limits and units file for contextual interpretation, a data dictionary, a README, a changelog, and SHA-256 checksums for integrity verification. The public files contain de-identified analytical variables only and omit individual-level demographics, dates, standalone urinary creatinine, and richer clinical metadata to preserve anonymity. Full article

DNA mixture interpretation remains one of the most technically demanding challenges in forensic genetics. While probabilistic genotyping (PG) systems have substantially advanced likelihood ratio (LR) evaluation, comparatively less attention has been devoted to the systematic reconstruction of contributor genotypes, particularly in no-suspect and database-search contexts. This review synthesizes recent developments in DNA mixture deconvolution through a four-strategy framework: (i) physical and biological separation, (ii) high-information genetic markers, (iii) continuous probabilistic algorithms, and (iv) integration with database searching infrastructures. Upstream approaches, including single-cell isolation and sequencing, reduce mixture complexity at the molecular level. Marker innovations such as microhaplotypes, MiniHaps and DIP-STRs increase per-locus information content and enhance resistance to degradation. Downstream probabilistic models—extended from STRs to SNPs and microhaplotypes—leverage quantitative signal data to infer contributor genotypes, with recent advances in Hamiltonian Monte Carlo, variational inference, and deep learning improving inferential stability and reconstruction accuracy. Importantly, genotype deconvolution and LR evaluation represent mathematically distinct objectives, requiring different validation metrics and potentially separate architectural optimization. The convergence of molecular innovation, algorithmic refinement, and LR-based database searching is progressively transforming mixture interpretation from a purely evidential assessment into an integrated investigative framework. Future progress will depend on standardized marker panels, deconvolution-specific performance metrics, and scalable LR-enabled database infrastructures. Full article

Fibromyalgia (FM) is a complex chronic syndrome marked by widespread musculoskeletal pain, neurocognitive dysfunction (“fibro-fog”), and autonomic disturbances. Clinical management remains challenging due to subjective symptom reporting and the lack of definitive diagnostics. Emerging evidence points to a multifactorial origin involving central sensitization, neuroendocrine imbalance, and systemic immune-inflammatory alterations. A wide array of candidate biomarkers has been reported in FM, encompassing neurotransmitters (serotonin, norepinephrine), excitatory and inhibitory amino acids, metabolic and glycolytic enzymes, stress-related proteins, autoantibodies, oxidative stress markers and pro-inflammatory cytokines. This molecular heterogeneity reflects the systemic and multidimensional nature of FM. However, most of these biomarkers have been primarily investigated in serum or plasma, where analytical validation and reference ranges are more established. In contrast, the exploration of salivary biomarkers—although highly attractive due to its non-invasive, stress-free, and repeatable collection—remains comparatively limited. Saliva contains a reduced concentration range of many systemic markers and is strongly influenced by circadian rhythms, stress, flow rate, and oral health conditions. While promising candidates such as α-amylase, cortisol, calgranulins, and selected metabolic enzymes have shown potential in saliva, many proposed FM-related biomarkers lack full analytical validation, standardized protocols, and clinically defined reference intervals in this matrix. In this context, non-invasive electrochemical biosensors represent a transformative technological approach. Advanced electrode architectures incorporating nucleic acid probes, redox reporters, and nanostructured materials offer high sensitivity in low-volume and low-concentration biofluids such as saliva. The integration of multiplexed biomarker panels into portable platforms could enable real-time, longitudinal monitoring of FM pathophysiology, supporting phenotype stratification, personalized therapeutic adjustment, and objective disease activity tracking. Full article

Chronic kidney disease (CKD) is associated with persistent inflammation and increased oxidative stress. Trace elements play an important role in these processes as modulators of redox balance, acting either as cofactors of antioxidant systems or as potential inducers of pro-oxidant mechanisms. In this study, the serum profile of trace elements with antioxidant and pro-oxidant relevance was characterized by inductively coupled plasma mass spectrometry (ICP-MS) in hemodialysis patients. Results were compared with those from a healthy control group, and associations with biochemical and hematological parameters were explored. A cross-sectional observational study was conducted including 117 hemodialysis patients and 82 healthy controls, determining a panel of eight trace elements (Zn, Se, Cu, Mn, As, Cr, Co, and Ni). The method showed adequate sensitivity, satisfactory precision for most elements, and acceptable trueness. Hemodialysis patients exhibited significantly lower serum concentrations of Zn and Se, together with greater interindividual variability, as well as higher concentrations of elements with potential pro-oxidant effects, including As, Cr, Co, and Ni. Within this group, Zn and Se were mainly associated with markers of the protein compartment, Cu with ceruloplasmin and inflammatory markers, and Cr and Ni with parameters of renal function and vitamin D status. Full article

Recent evidence links lens epithelial cell (LEC) dysfunction and cellular senescence—an irreversible cell cycle arrest with a pro-inflammatory secretory phenotype—to age-related cataract (ARC) progression. This systematic review synthesizes current knowledge on LEC senescence, its molecular features, and laboratory methods for senescence assessment in the ARC. Following PRISMA guidelines, a comprehensive search of PubMed, Scopus and Cochrane databases retrieved 3417 records from inception to 9 February 2025, with 14 studies ultimately included (821 patients and multiple in vitro LEC models). The following multiple senescence expression pathways were identified: SA-β-gal activity, p53/p21 and p16INK4A pathway activation, mitochondrial dysfunction, oxidative stress, and secretion of senescence-associated secretory phenotype (SASP) factors. Notably, cortical cataract demonstrated direct association with local senescent cell accumulation, while nuclear cataract reflected cumulative oxidative damage from impaired LEC-mediated antioxidant defense. Senescence markers correlated positively with cataract severity across multiple studies. Several potential therapeutic targets emerged, including metformin (AMPK activation/autophagic restoration), circMRE11A silencing, NLRP3 inflammasome inhibition, and modulation of FYCO1/PAK1 and MMP2 pathways. This review establishes LEC senescence as a central process in ARC pathogenesis and highlights promising senotherapeutic approaches. Future research should prioritize human surgical samples, develop standardized senescence detection panels (SA-β-gal + p21/p16 + SASP factors), and conduct longitudinal studies to establish causal relationships between senescence accumulation and cataract progression. Full article

Background: A major technical challenge in single-cell transcriptomics is the absence of an integrative analytic pipeline that can simultaneously leverage gene regulatory network (GRN) architecture, AI-assisted gene panel discovery, and functional relevance analyses to generate coherent biological insights. Existing approaches often treat these components independently, focusing on clusters, marker genes, or predictive features without integrating them into a mechanistically grounded framework. Consequently, comprehensive screening that links regulatory association, gene signature screening, and functional interpretation within single-cell datasets remains limited, underscoring the need for an integrated strategy. Methods: We developed an integrative bioinformatics pipeline based on Gene regulatory network–AI–Functional Analysis (GAFA), combining latent-space integration, unsupervised clustering, diffusion pseudotime analysis, lineage-resolved generalized additive modeling, GRN inference, and machine learning-based gene panel discovery. This framework enables systematic mapping of cell-state structure, reconstruction of differentiation and effector trajectories, and identification of transcriptional and regulatory features strongly associated with clinical outcomes. As a case study, we applied the pipeline to NK cell transcriptomes from six CML patients (two early relapse, two late relapse, two durable treatment-free remission—TFR; 15 samples) collected at TKI discontinuation and 6–12 months after therapy cessation. Results: We reanalyzed publicly available scRNA-seq data from a previously published CML cohort to evaluate NK-cell transcriptional programs associated with treatment-free remission and relapse. We resolved six transcriptionally distinct NK cell states spanning CD56^bright-like cytokine-responsive, early activated, terminally mature, cytotoxic, lymphoid trafficking, and HLA-DR⁺ immunoregulatory populations, each exhibiting outcome-specific compositional differences. Pseudotime analysis revealed two major NK cell lineages—a maturation trajectory and a cytotoxic effector trajectory. TFR samples displayed balanced occupancy of both lineages, whereas early relapse samples showed marked depletion of the maturation branch and preferential accumulation in cytotoxic end states. AI-guided feature selection and random forest modeling identified an 18-gene panel that distinguished NK cells from TFR and relapse samples in an exploratory manner. Among them, CST7, FCER1G, GNLY, GZMA, and HLA-C were conventional NK-associated genes, whereas ACTB, CYBA, IFITM2, IFITM3, LYZ, MALAT1, MT2A, MYOM2, NFKBIA, PIM1, S100A8, S100B, and TSC22D3 were novel. The GRN inference further uncovered outcome-specific regulatory modules, with RUNX3, EOMES, ELK4, and REL regulons enriched in TFR, whereas FOSL2 and MAF regulons were enriched in relapse, and their downstream targets linked to IFN-γ signaling, metabolic reprogramming, and immunoregulatory feedback circuits. Conclusions: This AI-enabled single-cell analysis demonstrates how NK cell state composition, differentiation trajectories, and regulatory network rewiring collectively shape TFR versus relapse following TKI discontinuation in CML. The integrative pipeline provides a modular framework that could be extended to additional datasets for data-driven biomarker discovery and mechanistic stratification, and highlights candidate transcriptional regulators and NK cell programs that may be leveraged to improve remission durability, pending validation in larger patient cohorts. Full article

Background and Objectives: Immunohistochemistry (IHC) is a keystone in gastric cancer (GC) management, allowing treatment customization, including for advanced or metastatic diseases. This review aims to evaluate the critical role of IHC markers, analyzing their efficiency in molecular subclassification and prediction of response to gastric cancer-targeted therapies, while also describing state-of-the-art IHC techniques and perspectives. Results: The major challenges for the GC management were structured in two main sections, as follows: (i) the current paradigm of gastric neoplasia diagnosis, which includes subsections related to the methodological and morphological foundations, the epidemiological dynamics, and risk factors, as well as differential diagnosis of poorly differentiated tumors; and (ii) the progress in 3,3′-diaminobenzidine (DAB) application and advanced reagents in gastric cancer immunohistochemistry. Discussion: Considering the role of IHC and DAB, the following topics were successively addressed in seven sections: GC key biomarkers, such as human epidermal growth factor receptor 2 (HER2), programmed death-ligand 1 (PD-L1), and DNA replication mismatch repair (MMR) system, allow direct correlation between tissue morphology and protein expression; intestinal and gastrointestinal differentiation markers; emerging and aggressive histological subtypes; epithelial–mesenchymal transition, E-cadherin, and the process of tumor budding; implementation of innovative procedures in gastric cancer immunohistochemistry; and automation, quality control, and sustainability in the pathology laboratory. Perspectives: The main directions were focused on the integration of artificial intelligence (AI) algorithms for digital quantification of the IHC signal and also on the expansion of panels to new targets, such as Claudin 18.2 (CLDN 18.2), which redefines treatment approaches in advanced stages. Conclusions: Although faced with technical and biological limitations, immunohistochemistry remains indispensable in modern gastric oncology. The evolution towards digital pathology and the refinement of scoring criteria will transform IHC from a complementary test into a visual tool that is essential for personalizing oncological treatment. Full article

Bladder cancer (BC) is one of the most commonly diagnosed cancers of the genitourinary system and ranks ninth in terms of incidence worldwide. Due to the varied clinical course of the disease and the frequent tendency for tumor recurrence, diagnostic studies are being conducted to find non-invasive and prognostic markers that could be helpful in diagnosing BC. The aim of this review was to present the current state of knowledge on the role of extracellular matrix metalloproteinases (MMPs) and pro-inflammatory cytokines in the pathogenesis of bladder cancer, as well as to assess their potential as biomarkers measured in body fluids. The study reviewed the literature published in English between 2012 and 2025. The studies included clinical and experimental research analysing the expression and activity of selected metalloproteinases, including MMP-2, MMP-9, MMP-7 and MMP-1, and pro-inflammatory cytokines such as interleukins (ILs): IL-6, IL-8, IL-17, and IFN-γ in serum, urine, and tumor tissues of patients with BC, using immunochemical methods and genetic analyses. The collected data indicate that MMPs play a key role in the degradation of the extracellular matrix, facilitating invasion, angiogenesis, and metastasis. Elevated concentrations of MMP-2 and MMP-9, especially in urine, correlate with the clinical stage and histopathological malignancy of the tumor. MMP-7 may be important in the early stages of carcinogenesis, while MMP-1 shows promising potential in multi-marker panels. At the same time, chronic inflammation and increased pro-inflammatory cytokine activity play a key role in modulating the tumor microenvironment. IL-6 and IL-8 have high diagnostic value in urine tests, with IL-6 also serving as a prognostic marker. IL-17 is associated with more aggressive forms of the disease, while IFN-γ may reflect the immune response to BC treatment. There is also evidence of positive feedback between cytokines and MMPs, which intensifies the process of tumor invasion and progression. Therefore, both extracellular matrix metalloproteinases and pro-inflammatory cytokines may be promising non-invasive biomarkers of bladder cancer. Their combined assessment can increase the diagnostic and prognostic value compared to the analysis of individual parameters. However, further multicentre prospective studies are needed for clinical validation and standardisation of the methods of determination. Full article

Accurate radiation biodosimetry is urgently needed for medical management after large-scale radiation exposure. Partial-body irradiation with 5% bone marrow sparing (PBI/BM5) provides a realistic radiation model. The current study specifically focused on the high-dose lethality window (12–16 Gy), where survival transitioned from 100% to 0%, representing a clinically distinct and underserved scenario requiring dedicated biodosimetry tools. We defined the survival profile of male C57BL/6 mice after PBI/BM5 and found that doses of 13.5–14.0 Gy were nonlethal within 12 days, whereas 15.0–15.5 Gy caused 100% mortality within 12 days, with a calculated LD_50/12 of 14.68 Gy. A separate cohort of 14.0 Gy showed 100% survival up to 90 days post-radiation. To develop serum cytokine-based biodosimetry in high-dose radiation exposure, mice were exposed to 12.0–16.0 Gy PBI/BM5, and serum was collected on days 1, 3, and 7. A multiplex cytokine assay was used to quantify 70 total cytokines/chemokines. After the exclusion of 4 targets outside detection limits, 66 markers were utilized for downstream analysis. PCA, clustering and heatmaps, and LASSO classification revealed that cytokine signatures can classify radiation groups/status/doses. A 4-cytokine panel (IL-7, GDF-15, IL-16 and FLT3L) could distinguish naïve vs. irradiated mice on all study days. A 24-cytokine signature panel distinguished radiation survivors vs. non-survivors, and another 34-cytokine panel separated radiation doses (12–16 Gy); the prediction was better on day 7 compared to earlier time points. This exploratory study was specifically designed to define the systemic inflammatory response in a high-dose window where survival transitions from 100% to 0% (the ‘lethality threshold’) in a clinically relevant partial-body irradiation model. These findings show that serum cytokines have strong potential for high-dose triage, survival prediction, and dose discrimination within the near-lethal exposure range in a clinically relevant PBI/BM5 model. Extension to lower dose ranges is an important direction for future work. Full article

Background/Objectives: In Puerto Rico (PR), lung cancer mortality remains high because diagnoses frequently occur at advanced stages. Although low-dose computed tomography (LDCT) lowers lung cancer–specific mortality, this screening is difficult to operationalize locally due to high false-positive rates, radiology capacity constraints, payer limitations, and geographic barriers affecting rural populations. Methods: We performed a narrative review on the literature from 2001–2026 of established and emerging detection strategies—LDCT; serum biomarkers (CEA, CYFRA-21-1, NSE, ProGRP, SCC-Ag, HE4, Hp, TAAb); breath analysis (FeNO and VOCs); and liquid biopsy (ctDNAs/CTCs/miRNAs). We assessed technical performance, feasibility, and health-system fit in PR and then synthesized these findings into an implementable biomarker-first triage workflow for are. Results: Multiplex serum panels analyzed with machine learning outperform single markers and TAAb provide high specificity with biological lead time, supporting their use as a triage gateway before LDCT. Breathomics is also feasible at the point of care. Liquid biopsy has modest sensitivity in very-early disease yet provides molecular adjudication for indeterminate nodules. A stepwise pathway—expanded risk assessment, integrated multi-panel testing in primary care, LDCT reserved for biomarker-positive individuals, and liquid biopsy when imaging is inconclusive—can enrich pre-test probability, reduce unnecessary scans, align with capitation, and protect limited radiology capacity. Conclusions: An integrated, non-invasive, biomarker-first triage model offers a pragmatic, equitable route to earlier lung cancer detection in PR and resource stewardship, while reducing disparities. Full article