Search Results (738)

Magnetic resonance imaging (MRI) and hyperspectral imaging (HSI) provide complementary information for image-guided neurosurgery, combining high-resolution anatomical detail with tissue-specific optical characterization. This work presents a novel multimodal phantom dataset specifically designed for MRI–HSI integration. The phantoms reproduce a three-layer tissue structure comprising white matter, gray matter, tumor, and superficial blood vessels, using agar-based compositions that mimic MRI contrasts of the rat brain while providing consistent hyperspectral signatures. The dataset includes two designs of phantoms with MRI, HSI, RGB-D, and tracking acquisitions, along with pixel-wise labels and corresponding 3D models, comprising 13 phantoms in total. The dataset facilitates the evaluation of registration, segmentation, and classification algorithms, as well as depth estimation, multimodal fusion, and tracking-to-camera calibration procedures. By providing reproducible, labeled multimodal data, these phantoms reduce the need for animal experiments in preclinical imaging research and serve as a versatile benchmark for MRI–HSI integration and other multimodal imaging studies. Full article

Background: Small-cell lung cancer (SCLC) is an aggressive type of lung cancer, and several factors are currently used to predict poor outcomes, including performance status (PS), extensive-stage disease, male sex, advanced age, and elevated lactate dehydrogenase (LDH) levels. In this study, we aimed to explore the role of Tegs and inflammatory indices, such as CRP and NLR, in predicting response to immunotherapy. Methods: Fifty-one therapy-naïve ES-SCLC patients and ten healthy donors were enrolled. Peripheral blood mononuclear cells (PBMCs) were isolated and stained with fluorochrome-conjugated monoclonal antibodies. Multicolor flow cytometry was performed to determine the levels of CD8⁺ T cells and CD4⁺ Tregs, as well as their correlation with inflammatory indices and clinical outcomes. Results: ES-SCLC patients harbored higher percentages of CD8⁺ Teffs (p = 0.005) and FOXP3⁺ Tregs (p < 0.0001) in circulation before therapy compared with healthy donors. In addition, high levels of CD3⁺CD8⁺ T effectors were associated with longer PFS (p = 0.018) and longer OS (p = 0.012) compared with patients bearing low levels, while Tregs were not found to be predictive. More importantly, a survival benefit was observed in ES-SCLC patients with a low Treg/Teff ratio, as longer OS was observed in those with high percentages of CD8⁺ Teffs and low FOXP3⁺CTLA-4⁺ Tregs (p = 0.014) compared with those bearing low CD8⁺ Teffs and high FOXP3⁺CTLA-4⁺ Tregs. A low Treg/Teff ratio was further associated with low eosinophil levels and a low NLR before treatment initiation. Conclusions: These findings suggest a novel, easily obtainable blood-based signature that may help predict response to ICIs in ES-SCLC patients. Full article

Repeated exposure to low-level blast overpressure (BOP) during controlled detonations is an emerging occupational health concern for military breachers and Special Operations Forces personnel, given accumulating evidence that chronic exposure may produce subtle, subclinical neurotrauma. This study derived a latent neuroinjury construct integrating three complementary domains of brain health—post-concussive symptoms, working-memory performance, and circulating biomarkers—to determine whether breachers exhibit coherent patterns of neurobiological alteration. Symptom severity was assessed using the Rivermead Post-Concussion Questionnaire (RPQ), and working memory was assessed with the N-Back task and a panel of thirteen neuroproteomic biomarkers was measured reflecting astroglial activation, neuronal and axonal injury, oxidative stress, inflammatory signaling, and neurotrophic regulation. Experienced Canadian Armed Forces breachers with extensive occupational BOP exposure were compared with unexposed controls. Bayesian latent-variable modeling provided probabilistic evidence for a chronic, subclinical neurobiological signal, with the strongest contributions arising from self-reported symptoms and smaller but consistent contributions from the biomarker domain. Working-memory performance did not load substantively on the latent factor. Several RPQ items and circulating biomarkers showed robust loadings, and the latent neuroinjury factor was elevated in breachers relative to controls (97% posterior probability). The pattern is broadly consistent with subclinical neurobiological stress in the absence of measurable cognitive impairment, suggesting early or compensated physiological alterations rather than overt dysfunction. This multidomain, biomarker-informed framework provides a mechanistically grounded and scalable approach for identifying subtle neurobiological strain in military personnel routinely exposed to repetitive low-level blast. It may offer value for risk stratification, operational health surveillance, and the longitudinal monitoring of neurobiological change in high-risk occupations. Full article

Background/Objectives: Active surveillance (AS) has become the standard of care for many men with localised prostate cancer, aiming to avoid the overtreatment of indolent disease while maintaining oncological safety. Despite improvements in diagnostic techniques, misclassification at diagnosis and the limited ability to predict disease progression remain major challenges in AS. Novel molecular and genetic biomarkers, assessed through liquid biopsy approaches, offer the potential to refine patient selection and support risk-adapted monitoring in AS. Methods: We conducted a narrative review of biomarkers in the context of AS for prostate cancer, framing the discussion in terms of the challenges in AS and how biomarkers may address these. PubMed and Embase were searched for English-language peer-reviewed studies published between 2000 and 2025. International guidelines (AUA, EAU, NCCN, NICE) and reference lists were reviewed manually. Priority was given to large prospective cohorts, meta-analyses, and high-impact publications. Results: Blood-based assays such as PHI and the 4K score, urinary tests including ExoDx and SelectMDx, and the Prostate Urine Risk (PUR) signatures have all shown associations with disease progression or decisions to undergo earlier treatment. However, studies are often small, use surrogate endpoints, and lack validation in MRI-integrated cohorts. Biomarkers appear most informative in men with Gleason Grade 1 (GG1) disease, while evidence in GG2 cohorts is limited. Cost-effectiveness, heterogeneity of endpoints, and uncertainty in managing discordant biomarker and MRI results remain barriers to clinical adoption. Conclusions: Molecular and genetic biomarkers show promise for improving AS by reducing diagnostic misclassification and enhancing prediction of progression. Future research should define clinically relevant cut-offs, clarify integration with MRI, and evaluate longitudinal use. Demonstrating utility in contemporary cohorts could enable the development of biomarker-guided, personalised AS that maintains safety while minimising harm. Full article

Plasma cell-free RNA (cfRNA) metagenomics is increasingly explored for blood-based pathogen detection, but the structure of the shared background “blood microbiome”, the reproducibility of reported signals, and the practical limits of this approach remain unclear. We performed a critical re-analysis and benchmarking (“stress test”) of host-filtered blood RNA sequencing data from two cohorts: a bacteriologically confirmed tuberculosis (TB) cohort (n = 51) previously used only to derive host cfRNA signatures, and a coronary artery disease (CAD) cohort (n = 16) previously reported to show a CAD-shifted “blood microbiome” enriched for periodontal taxa. Both datasets were processed with a unified pipeline combining stringent human read removal and taxonomic profiling using the latest versions of specialized tools Kraken2 and MetaPhlAn4. Across both cohorts, only a minority of non-host reads were classifiable; under strict host filtering, classified non-host reads comprised 7.3% (5.0–12.0%) in CAD and 21.8% (5.4–31.5%) in TB, still representing only a small fraction of total cfRNA. Classified non-host communities were dominated by recurrent, low-abundance taxa from skin, oral, and environmental lineages, forming a largely shared, low-complexity background in both TB and CAD. Background-derived bacterial signatures showed only modest separation between disease and control groups, with wide intra-group variability. Mycobacterium tuberculosis-assigned reads were detectable in many TB-positive samples but accounted for ≤0.001% of total cfRNA and occurred at similar orders of magnitude in a subset of TB-negative samples, precluding robust discrimination. Phylogeny-aware visualization confirmed that visually “enriched” taxa in TB-positive plasma arose mainly from background-associated clades rather than a distinct pathogen-specific cluster. Collectively, these findings provide a quantitative benchmark of the background-dominated regime and practical limits of plasma cfRNA metagenomics for pathogen detection, highlighting that practical performance is constrained more by a shared, low-complexity background and sparse pathogen-derived fragments than by large disease-specific shifts, underscoring the need for transparent host filtering, explicit background modeling, and integration with targeted or orthogonal assays. Full article

Creutzfeldt–Jakob disease (CJD) is a rare but devastating neurodegenerative disorder characterized by the pathological misfolding of the cellular prion protein (PrP^C) into the pathogenic isoform-scrapie prion protein (PrP^Sc), ultimately leading to fatal outcomes. Cerebrospinal fluid (CSF) biomarkers play a pivotal role in early diagnosis, longitudinal monitoring, and prognostic assessment, thereby enhancing the clinical management of this challenging disease. This review summarizes the established CSF biomarkers, 14-3-3 protein, tau protein (total tau), phosphorylated tau isoforms, α-synuclein, neurofilament light chain (Nfl), S100B, neuron-specific enolase (NSE), and phosphorylated neurofilament heavy chain (pNFH), highlighting typical sensitivity ranges (14-3-3 ~70–85%; RT-QuIC > 90%) and subtype-dependent performance variation. We further dissect limitations related to assay variability, inter-laboratory cut-off inconsistencies, and reduced specificity in non-prion dementias. Looking ahead, we discuss emerging multi-omics discovery, integration of CSF with blood-based biomarkers and imaging signatures, and AI-enabled diagnostic modeling. We propose a three-tier biomarker framework combining Real-Time Quaking-Induced Conversion (RT-QuIC) as a confirmatory assay, tau/NfL/pNFH as injury-severity indicators, and multi-omics-derived signatures for early detection and prognosis stratification. Full article

Chronic obstructive pulmonary disease (COPD) is often diagnosed after significant lung damage has already occurred, highlighting a need for minimally invasive biomarkers for early detection of COPD development. This study aims to identify transcriptional biomarkers in peripheral blood mononuclear cells (PBMCs). A Weighted Gene Co-Expression Network Analysis (WGCNA) was performed on the GSE146560 transcriptomic dataset. Hub genes were cross-validated using independent transcriptomic data (GSE94916), topology analysis of a COPD-related protein–protein interaction (PPI) network, and a text-mining approach. The top candidate genes were validated using RT-qPCR in a clinical cohort, consisting of 28 COPD patients and 13 healthy volunteers, and their diagnostic value was evaluated using receiver operating characteristic (ROC) analysis. WGCNA identified four gene modules significantly correlated with COPD, the functional annotation of which revealed their enrichment in immune and tissue remodeling pathways. Further analysis of the PPI network topology structure and gene expression revealed a hub gene signature that was significantly upregulated in PBMCs of COPD patients, including MDM2 (6.3-fold, p < 0.001), FKBP5 (7.0-fold, p < 0.001), and CTNNA1 (10.0-fold, p < 0.001). ROC analysis demonstrated high diagnostic accuracy for these genes, with AUC values of 0.849, p < 0.001, for MDM2, 0.957, p < 0.001, for FKBP5, and 0.958, p < 0.001, for CTNNA1. MDM2, FKBP5, and CTNNA1 represent promising, readily accessible PBMC biomarkers for COPD diagnosis. Full article

Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the expansion of hematopoietic stem cells harboring leukemogenic mutations in the absence of overt malignancy. Strongly associated with advancing age, CHIP is detected by next-generation sequencing of peripheral blood in more than 20% of individuals over 80, most commonly through mutations in DNMT3A, TET2, ASXL1, and PPM1D. While CHIP confers over a four-fold increased risk of hematologic malignancy, it has recently emerged as a key determinant of cardiometabolic health. Epidemiological data indicated a 40% higher cardiovascular disease (CVD) risk events and a 34% increase in all-cause mortality among CHIP carriers, with specific mutations and larger clone sizes conferring greater cardiovascular burden. Preclinical studies have shown that macrophages deficient in TET2 or DNMT3A drive interleukin (IL)-1β/IL-6 inflammasome activation, thereby promoting atherosclerosis and metabolic dysfunction, whereas the JAK2V617F mutation accelerates thrombosis. CHIP integrates into a broader network of dysregulation encompassing adiposity and inflammaging, which underlies its association with diverse comorbidities, including type 2 diabetes (T2D), chronic kidney disease (CKD), and chronic obstructive pulmonary disease (COPD). Multi-omics approaches have identified epigenetic and proteomic signatures correlated with CHIP expansion, providing potential biomarkers for risk stratification. Despite growing evidence of its systemic impact, CHIP screening remains limited to research settings. Emerging therapeutic strategies, including inflammasome inhibition, STING modulation, and epigenetic restoration, highlight its potential as a modifiable risk factor. This narrative review synthesizes current epidemiological, mechanistic, and translational insights, framing CHIP as an emerging causal factor in cardiometabolic disease and as a promising target for precision medicine in aging populations. Full article

Inflammatory bowel disease (IBD) remains difficult to manage in patients who fail multiple therapeutic lines, and growing evidence suggests that alterations in the gut microbiome contribute to persistent symptoms and inflammatory activity. This study evaluated a three-month, AI-guided, multi-omic personalized microbiome modulation program in adults with treatment-refractory IBD. Baseline stool metagenomic sequencing, blood biomarkers, micronutrient panels, and clinical data were integrated through an artificial intelligence platform to generate individualized plans combining dietary adjustments, targeted synbiotics, selective antimicrobials, and micronutrient correction. Clinical outcomes, inflammatory markers, and microbial signatures were reassessed after three months. Across 358 participants, stool frequency decreased substantially, urgency and rectal bleeding resolved in most patients, and over 70% reported a “much improved” overall condition. Inflammatory biomarkers showed marked normalization, with reductions in hs-CRP and fecal calprotectin observed in over 85% of cases. Micronutrient deficiencies, particularly iron and zinc, also improved, and beneficial microbial taxa such as Faecalibacterium prausnitzii, Bifidobacterium longum, and Akkermansia muciniphila increased significantly. These findings suggest that personalized, multi-omic microbiome modulation may support clinically meaningful improvements by targeting microbial, metabolic, and immune imbalances rather than symptoms alone. While encouraging, these results require confirmation in randomized controlled studies. Full article

Background: Older adults face increased risks of influenza infection and related complications due to declining immunity and reduced vaccine responsiveness. Despite widespread vaccination, only 30–40% mount immune response due to immunosenescence. However, no biomarkers exist to identify potential non-responders, limiting the ability to target vaccine strategies, like high-dose or adjuvanted formulations, to those unlikely to benefit from standard options. Methods: We analysed publicly available baseline bulk RNA sequencing data from peripheral blood mononuclear cells of individuals aged ≥65 years to determine baseline transcriptomic signatures predictive of influenza vaccine response. Using two independent cohorts (discovery and validation), we classified individuals as triple responders (TRs) or triple non-responders (TNRs) based on hemagglutination inhibition assay titers at Day 0 and Day 28 for three components: A/H1N1, A/H3N2, and B/Yamagata. Results: We identified 1152 differentially expressed genes between TRs and TNRs at baseline. TRs exhibited enrichment of genes involved in B cell activation and protein synthesis, while TNRs showed enrichment of genes associated with innate immune responses and platelet activation. A response score derived from gene expression achieved high predictive accuracy in the discovery cohort (area under the curve [AUC] = 0.98). However, performance declined in the validation cohort (AUC = 0.69), and did not outperform clinical predictors, such as baseline titers, sex and vaccine dose. Conclusions: While baseline transcriptomic profiles may reveal mechanistic insights into vaccine responsiveness in the elderly, they offer limited predictive utility. Future work should prioritise higher-resolution or combined cell-specific approaches, such as single-cell RNA-sequencing or flow cytometry. Full article

Colorectal cancer (CRC) remains a major cause of morbidity and mortality worldwide, with its incidence and biological behavior influenced by both genetic and environmental factors. Emerging evidence highlights notable sex differences in CRC, with men generally exhibiting higher incidence rates and poorer prognoses, while women often display stronger immune responses and distinct molecular profiles. Traditional screening tools, such as colonoscopy and fecal-based tests, have improved survival through early detection but are limited by invasiveness, cost, and adherence issues. In this context, biosensors have emerged as innovative diagnostic platforms capable of rapid, sensitive, and non-invasive detection of CRC-associated biomarkers, including genetic, epigenetic, and metabolic alterations. These technologies integrate biological recognition elements with nanomaterials, microfluidics, and digital systems, enabling the analysis of biomarkers such as proteins, nucleic acids, autoantibodies, epigenetic marks, and metabolic or VOC signatures from blood, stool, or breath and supporting point-of-care applications. Electrochemical, optical, piezoelectric, and FET platforms enable label-free or ultrasensitive multiplexed readouts and align with liquid biopsy workflows. Despite challenges related to standardization, robustness in complex matrices, and clinical validation, advances in nanotechnology, multi-analyte biosensing with artificial intelligence are enhancing biosensor performance. Integrating biosensor-based diagnostics with knowledge of sex-specific molecular and hormonal pathways may lead to more precise and equitable approaches in CRC detection, selection of therapeutic regimes and management. Full article

Bovine ketosis represents a critical metabolic challenge in modern dairy production, primarily affecting high-yielding cows during the periparturient period. The disorder arises from severe negative energy balance (NEB), where energy demands exceed supply, triggering substantial mobilization of adipose tissue and hepatic accumulation of non-esterified fatty acids (NEFAs). This stress overwhelms hepatic oxidative capacity, leading to incomplete fatty acid oxidation and excessive ketone body production—primarily β-hydroxybutyrate (BHB), acetoacetate, and acetone. While genomics enables the identification of candidate genes and genetic variations influencing ketosis susceptibility, metabolomics provides comprehensive, multi-matrix metabolic signatures across blood, milk, urine, and tissues, often revealing predictive biomarkers in the dry period and pre-clinical stage. This review provides a comprehensive overview of ketosis etiology, emphasizing the roles of NEB, fat mobilization, hormonal dysregulation, and oxidative stress. We systematically examine candidate genes, signaling pathways, and the diverse metabolomic profiles underlying disease pathogenesis, and discuss current prevention strategies focusing on periparturient nutritional management and therapeutic interventions. Understanding these integrated molecular and metabolic mechanisms offers valuable insights for developing targeted breeding programs and precision management approaches to enhance metabolic health and economic efficiency in dairy cattle. Full article

Background and Objectives: Type I interferon (IFN-I) transcriptional signatures are widely utilised as readouts of innate immunity. We evaluated whether age and sex affect single interferon-stimulated genes (ISGs) and the composite IFN-I score, with implications for control selection and assay calibration. Materials and Methods: Ninety-five healthy individuals (53 males, 42 females; 18 days to 89 years) were studied. Whole-blood expressions of IFI27, IFI44L, IFIT1, ISG15, RSAD2 and SIGLEC1 was quantified by RT-qPCR, normalised to GAPDH and calibrated to a paediatric reference. Age associations used Spearman’s rho; sex differences, two-sided Mann–Whitney U tests. Results: Age effects were modest and gene-specific: IFI44L declined and IFI27 increased with age (significant overall and in females), whereas in males only IFI44L decreased; other ISGs were null (|r| ≤ 0.36). The composite IFN-I score showed no association with age or sex, indicating that aggregation mitigates small gene-level variation and that demographic influences on baseline IFN-I readouts appear minimal within this six-gene whole-blood qPCR panel in our cohort. Conclusions: Methodologically, a single primary cut-off within homogeneous pipelines is appropriate. Although best practice favours age-, sex- and matrix-matched healthy controls, our data show no significant age- or sex-related differences in the composite IFN-I score; matching therefore primarily supports comparability and clinical governance rather than correction of demographic shifts. Full article

Background/Objectives: The accumulation of specific amyloid proteins and peptides in the human brain is a hallmark of neurodegenerative disorders such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). Beyond the central nervous system, circulating peripheral blood cells are also exposed to these pathological proteins, which may contribute to the systemic disease manifestation. Human platelets (PLTs) were used as an in vitro model to investigate the impacts of amyloid Aβ1-42 peptide oligomers (Aβ42) and on-pathway α-synuclein (α-syn), two key amyloids implicated in AD and PD, on platelet biophysical properties. Methods: Using atomic force microscopy, imaging and force–distance modes, we analyzed changes in surface nanostructure, morphometric and nanomechanical signatures of PLTs, derived from healthy donors, following exposure to increasing concentrations of Aβ42 and α-syn. Results: Our findings show that platelet activation progresses with increasing amyloid concentration, characterized by cytoskeletal remodeling (filopodia-to-pseudopodia and lamellipodia transformation). While Aβ42 causes progressive decrease in the platelet membrane roughness, α-syn exhibits a biphasic effect—initial smoothing followed by a pronounced increase in the roughness at high concentrations. Both amyloids induce substantial increase in membrane stiffness (Young’s modulus). Conclusions: The changes in PLTs’ biophysical properties closely resemble the previously observed modification in PLTs derived from AD and PD patients, suggesting that amyloid proteins’ interactions with PLTs may contribute to their dysfunction. Our results underscore the potential of platelets as peripheral indicators of neurodegeneration and point to their role in the systemic pathology of amyloid-associated diseases. Full article

Dysregulated T-cell-mediated immune responses are a hallmark of inflammatory bowel diseases (IBD), including Crohn’s disease (CD) and ulcerative colitis (UC). MicroRNAs (miRNAs) regulate various biological processes and play a significant role in the pathophysiology of numerous diseases. In this study, we aim to clarify the relationship between dysregulated immune response and altered miRNA signatures in patients with IBD. Our goal is to identify differentially expressed miRNAs that could potentially serve as diagnostic markers to differentiate between CD and UC. To quantify circulating miRNAs, we employed small RNA sequencing. To describe immune dysregulation, we determined the levels of circulating T-cell-related cytokines and the distribution of T-cell subpopulations in both circulation and in tissue samples. Our analysis revealed that 14 miRNAs exhibited significant expression differences between IBD patients and control subjects. These miRNAs may also implicate pathways associated with colitis-related colorectal carcinogenesis, suggesting their value in early risk assessment. Furthermore, we found that five miRNAs demonstrated a strong ability to discriminate between CD and UC patients. Additionally, levels of IL-22 and IFN-γ were significantly elevated in individuals with IBD. Notably, miRNA levels showed strong correlations with cytokine levels and T-cell subset distribution in both blood and tissue samples, exhibiting disease-specific patterns. In conclusion, we identified differentially expressed miRNAs in IBD patient groups, and a subset of these miRNAs might exhibit diagnostic potential to distinguish between CD and UC. Analyzing miRNAs in the blood of IBD patients may provide valuable insights into the underlying immune dysfunction. Full article