Search Results (16,488)

Background/Objectives: Multiple sclerosis (MS) often leads to gait impairments, even in early stages, and can affect autonomy and quality of life. Traditional assessment methods, while widely used, have been criticized because they lack sensitivity to subtle gait changes. This scoping review aims to map the landscape of advanced gait analysis technologies—both wearable and non-wearable—and evaluate their application in detecting, characterizing, and monitoring possible gait dysfunction in individuals with MS. Methods: A systematic search was conducted across PubMed and Scopus databases for peer-reviewed studies published in the last decade. Inclusion criteria focused on original human research using technological tools for gait assessment in individuals with MS. Data from 113 eligible studies were extracted and categorized based on gait parameters, technologies used, study design, and clinical relevance. Results: Findings highlight a growing integration of advanced technologies such as inertial measurement units, 3D motion capture, pressure insoles, and smartphone-based tools. Studies primarily focused on spatiotemporal parameters, joint kinematics, gait variability, and coordination, with many reporting strong correlations to MS subtype, disability level, fatigue, fall risk, and cognitive load. Real-world and dual-task assessments emerged as key methodologies for detecting subtle motor and cognitive-motor impairments. Digital gait biomarkers, such as stride regularity, asymmetry, and dynamic stability demonstrated high potential for early detection and monitoring. Conclusions: Advanced gait analysis technologies can provide a multidimensional, sensitive, and ecologically valid approach to evaluating and detecting motor function in MS. Their clinical integration supports personalized rehabilitation, early diagnosis, and long-term disease monitoring. Future research should focus on standardizing metrics, validating digital biomarkers, and leveraging AI-driven analytics for real-time, patient-centered care. Full article

Dysregulation contributes to Alzheimer’s disease (AD) pathophysiology. Zinc therapy promotes enterocyte copper sequestration, potentially reducing systemic copper. Individual biological responses may vary. Methods: ZINCAiD was a 24-week, randomized, double-blind, placebo-controlled phase II trial assessing zinc therapy in individuals with mild cognitive impairment (MCI) due to AD (EudraCT No.: 2019-000604-15; registered on 26 March 2020). Participants were randomized 2:1 to receive elemental zinc (135 mg/day for 12 weeks, then 65 mg/day) or placebo. Ceruloplasmin was measured at predefined intervals for safety monitoring, blinded to the investigators. Post hoc, “Zinc Responders” were defined by ≥20% reduction in ceruloplasmin at week 12. The primary cognitive endpoint was the Cognitive Composite 2 scale (CC2); secondary endpoints included MMSE and CDR-Sob. Findings: Of the 48 participants randomized, 9 discontinued, primarily due to unrelated clinical deterioration; 39 had complete ceruloplasmin data. Two serious adverse events occurred in the Placebo group. Mild gastrointestinal symptoms occurred in eight participants, with only four leading to dropout. In the primary zinc vs. placebo analysis, no significant differences emerged in cognitive outcomes. A post hoc exploratory analysis stratified participants by pharmacodynamic response: 12 individuals with MCI due to AD (31%) met the criteria for “Zinc Responder,” defined by ≥20% reduction in serum ceruloplasmin at week 12. Only Zinc Responders maintained cognitive stability over 24 weeks, whereas the combined group of Zinc Non-Responders and placebo-treated participants showed a significant decline. For the composite cognitive score (CC2), the interaction between visit and response group was significant (p = 0.030), with deterioration observed only in the Non-Responder + Placebo group (Δ = –2.72, p < 0.0001 vs. –0.71, p = 0.35 in Responders). Similar patterns were observed for CDR-Sob (interaction p = 0.017) and MMSE (trend p = 0.09). Interpretation: Zinc therapy stabilized cognition in a pharmacodynamically defined MCI subgroup. These exploratory findings suggest serum ceruloplasmin as a feasible biomarker of target engagement. Larger trials are needed for confirmation. Full article

Surface-enhanced Raman scattering (SERS) has emerged as a powerful signal amplification strategy to address the inherent limitations of conventional flow-based diagnostic methods such as lateral flow analysis (LFA) and vertical flow analysis (VFA). By incorporating SERS-active nanostructures into these platforms, SERS-integrated LFA and VFA systems have significantly improved sensitivity, specificity, and multiplexing performance while maintaining the simplicity and portability of conventional approaches. In this review, we summarize recent advances in SERS-enhanced flow-based diagnostics with a focus on exogenous and endogenous disease detection. Exogenous targets include viral antigens, bacterial pathogens, and foodborne contaminants such as mycotoxins and antibiotic residues. Endogenous applications include therapeutic drug monitoring, inflammation profiling, cancer biomarker detection, and exosome-based molecular subtyping. We highlight the structural differences between LFA and VFA approaches and their impact on analytical performance, and explore the advantages of SERS-integrated platforms for rapid and multiplexed detection in complex biological matrices. Finally, we provide an overview of key technical challenges, such as signal reproducibility, matrix interference, and device integration, and discuss future directions for clinical implementation of SERS-based flow diagnostics in point-of-care settings. Full article

Background: Multiple sclerosis (MS) is an immune-mediated neuroinflammatory disorder with a multifactorial etiology involving genetic susceptibility, environmental triggers, and vascular contributions. Carotid intima–media thickness (CIMT) is a significant marker of endothelial dysfunction. Endothelial cell-specific molecule-1 (endocan) and hyaluronic acid, key components implicated in endothelial and vascular remodeling, may significantly contribute to the inflammatory and vascular pathologies observed in MS. We aimed to investigate the relationship between CIMT and endothelial biomarkers, such as endocan and hyaluronic acid, in patients with MS. Methods: In this cross-sectional study, 100 patients with relapsing–remitting MS and 56 healthy controls were included. Demographic, clinical, laboratory, and imaging data were documented. CIMT was measured bilaterally using high-resolution B-mode ultrasonography. Serum endocan and hyaluronic acid levels were quantified via enzyme-linked immunosorbent assays. Results: MS patients exhibited significantly higher CIMT and serum endocan levels compared with controls (p < 0.001). CIMT values were significantly elevated in MS patients, with longer disease duration, higher expanded disability status scale scores, and an older diagnosis age (p < 0.05). However, serum endocan and hyaluronic acid levels did not significantly differ between MS subgroups based on disease duration, disability severity, and diagnosis age. Additionally, there was no correlation between CIMT and serum endocan and hyaluronic acid levels in MS patients (p > 0.05). Conclusions: Increased CIMT and serum endocan levels in MS patients may indicate endothelial dysfunction suggesting vascular involvement in MS. The lack of a correlation between CIMT and endocan and hyaluronic acid levels reveals the complexity of vascular and immune interactions in MS, which needs further research. Full article

The X-linked TLR7 rs179008 T allele has been associated with altered antiviral immunity. Given their shared inflammatory pathways and higher pediatric mortality rates in Brazil during the pandemic, we investigated their association with multisystem inflammatory syndrome in children (MIS-C) together with Kawasaki disease (KS) following SARS-CoV-2 infection. A cross-sectional study (2021–2022) analyzed 73 hospitalized children (<13 years) with confirmed COVID-19. Genotyping for TLR7 rs179008, TLR8 (rs3764879, rs2407992), and TLR3 rs3775291 was performed via PCR and Sanger sequencing. MIS-C/KS cases were identified using CDC criteria, with severity classified by the need for ICU care. Statistical analysis included Fisher’s exact test and relative risk (RR) calculations. Hemizygous boys carrying the TLR7 T allele had a 1.87-fold higher risk of MIS-C/KS (p = 0.007) and a 1.75-fold increased risk of severe or critical outcomes. The T allele frequency was 2.6× higher in MIS-C/KS cases versus other COVID-19 presentations. All fatalities occurred in boys (3/8 MIS-C cases) with one T-allele carrier. No associations were found for TLR8 or TLR3 variants. The TLR7 rs179008 T allele is a potential genetic risk factor for severe post-COVID-19 inflammatory syndromes in boys, likely due to impaired immune signaling. These findings highlight its utility as a biomarker for risk stratification in pediatric populations. Full article

The integration of deep learning (DL) and nanozyme-based biosensing has emerged as a transformative strategy for next-generation medical diagnostics. This review explores how DL architectures enhance nanozyme design, functional optimization, and predictive modeling by elucidating catalytic mechanisms such as dual-atom active sites and substrate-surface interactions. Key applications include disease biomarker detection, medical imaging enhancement, and point-of-care diagnostics aligned with the ASSURED criteria. In clinical contexts, advances such as wearable biosensors and smart diagnostic platforms leverage DL for real-time signal processing, pattern recognition, and adaptive decision-making. Despite significant progress, challenges remain—particularly the need for standardized biomedical datasets, improved model robustness across diverse populations, and the clinical translation of artificial intelligence (AI)-enhanced nanozyme systems. Future directions include integration with the Internet of Medical Things, personalized medicine frameworks, and sustainable sensor development. The convergence of nanozymes and DL offers unprecedented opportunities to advance intelligent biosensing and reshape precision diagnostics in healthcare. Full article

Background/Objectives: Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by lung scarring, impaired function, and high mortality. Effective therapies to reverse fibrosis are lacking. This study aims to uncover the molecular mechanisms of IPF, explore diagnostic biomarkers, and identify therapeutic targets. Methods: Multi-omics data were integrated to identify biomarkers with causal associations to IPF using Mendelian randomization and transcriptomic analysis. Machine learning was employed to construct a diagnostic model, and single-cell transcriptomic analysis determined gene expression patterns in fibrotic lung tissue. Results: Seven core genes (GREM1, UGT1A6, CDH2, TDO2, HS3ST1, ADGRF5, and MPO) were identified, showing strong diagnostic potential (AUC = 0.987, 95% CI: 0.972–0.987). These genes exhibited distinct distribution patterns in fibroblasts, endothelial cells, epithelial cells, macrophages, and dendritic cells. Conclusions: This study highlights key genes driving IPF, involved in pathways related to metabolism, immunity, and inflammation. However, their utility as fluid-based biomarkers remains unproven and requires protein-level validation in prospective cohorts. By integrating genomic, immunological, and cellular insights, it provides a framework for targeted therapies and advances mechanism-based precision medicine for IPF. Full article

As aquaculture expands globally, understanding immune responses in non-traditional farmed species like Octopus vulgaris under varying environmental conditions is increasingly important. This study investigated lysozyme activity, a key innate immune marker, in cell-free hemolymph of O. vulgaris following experimental challenge with four Gram-negative fish pathogens (Photobacterium damselae subsp. piscicida, P. damselae subsp. damselae, Vibrio alginolyticus, and V. anguillarum O1) at two temperatures (21 ± 0.5 °C and 24 ± 0.5 °C). These pathogens were selected because octopus farming frequently occurs near fish aquaculture facilities, raising the potential for pathogen crossover. A total of 216 wild octopuses were injected intramuscularly or intravenously and sampled on days 0, 3, and 7 post-challenge. Lysozyme activity varied by pathogen, injection route, sampling time, and temperature. A significant time- and temperature-dependent increase was observed, especially in IM-challenged groups exposed to Photobacterium species. Elevated temperatures supported a more prolonged immune response. These results highlight lysozyme as a responsive biomarker of innate immunity in O. vulgaris and emphasize the role of environmental factors in immune modulation. This work provides a foundation for disease monitoring and health management in cephalopod aquaculture. Future research should examine long-term lysozyme dynamics, broader pathogen exposure, molecular mechanisms, and additional environmental stressors such as salinity and pollution. Full article

Objectives: The FibroScan–aspartate transaminase (AST) score (FAST score) is a hybrid biomarker combining ultrasound and blood test data for identifying nonalcoholic steatohepatitis (NASH). This study aimed to assess the feasibility of using quantitative ultrasound (QUS) biomarkers related to hepatic steatosis for NASH detection and to compare their diagnostic performance with the FAST score. Methods: A total of 137 participants, comprising 71 individuals with NASH and 66 with non-NASH (including 49 normal controls), underwent FibroScan and ultrasound exams. QUS imaging features (Nakagami parameter m, homodyned-K parameter μ, entropy H, and attenuation coefficient α) were extracted from backscattered radiofrequency data. A weighted QUS parameter based on m, μ, H, and α was derived via linear discriminant analysis. NASH was diagnosed based on liver biopsy findings using the nonalcoholic fatty liver disease activity score (NAS). Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and compared with the FAST score using the DeLong test. Separation metrics, including the complement of overlap coefficient, Bhattacharyya distance, Kullback–Leibler divergence, and silhouette score, were used to assess inter-group separability. Results: All QUS parameters were significantly elevated in NASH patients (p < 0.05). AUROC values for individual QUS features ranged from 0.82 to 0.91, with the weighted QUS parameter achieving 0.91. The FAST score had the highest AUROC (0.96), though differences with the weighted QUS and homodyned-K parameters were not statistically significant (p > 0.05). Separation metrics ranked the FAST score highest, closely followed by the weighted QUS parameter. Conclusions: QUS biomarkers can be repurposed for NASH detection, with the weighted QUS parameter offering diagnostic accuracy comparable to the FAST score and serving as a promising, blood-free alternative. Full article

Background/Objectives: Canine visceral leishmaniasis (CVL) is one of the main neglected protozoan diseases in the world. Dogs play a fundamental role in the maintenance of Leishmania infantum in the Americas, and we have already encountered resistance problems with drugs currently used in these animals. Methods: In view of this, two new immunotherapeutic protocols were tested in 48 dogs, using L. amazonensis antigens plus saponin (LaSap) and only L. amazonensis antigens (La) as a control group. Dogs naturally infected with L. infantum were divided into four groups, according to clinical staging. A total of 24 dogs (stages 1 and 2) received a four-dose protocol, and another 24 dogs (stages 3 to 5) received six doses. All animals received a booster dose every three months until they were one year old. Results: Our results showed that dogs in the early stages of the disease respond better and are able to remain stable for longer, maintaining baseline laboratory biomarkers, in addition to having a lower parasite load. Conclusions: On the other hand, dogs in more advanced stages have a poor response, with stage 3 being a key point in clinical progression or regression. Full article

Objective: This study aims to develop and validate an interpretable deep learning framework that leverages self-supervised time reversal (TR) pretraining to identify consistent, biologically plausible functional network biomarkers across multiple neurological and psychiatric disorders. Methods: We pretrained a hierarchical LSTM model using a TR pretext task on the Human Connectome Project (HCP) dataset. The pretrained weights were transferred to downstream classification tasks on five clinical datasets (FBIRN, BSNIP, ADNI, OASIS, and ABIDE) spanning schizophrenia, Alzheimer’s disease, and autism spectrum disorder. After fine-tuning, we extracted latent features and employed a logistic regression probing analysis to decode class-specific functional network contributions. Models trained from scratch without pretraining served as a baseline. Statistical tests (one-sample and two-sample t-tests) were performed on the latent features to assess their discriminative power and consistency. Results: TR pretraining consistently improved classification performance in four out of five datasets, with AUC gains of up to 5.3%, particularly in data-scarce settings. Probing analyses revealed biologically meaningful and consistent patterns: schizophrenia was associated with reduced auditory network activity, Alzheimer’s with disrupted default mode and cerebellar networks, and autism with sensorimotor anomalies. TR-pretrained models produced more statistically significant latent features and demonstrated higher consistency across datasets (e.g., Pearson correlation = 0.9003 for schizophrenia probing vs. −0.67 for non-pretrained). In contrast, non-pretrained models showed unstable performance and inconsistent feature importance. Conclusions: Time Reversal pretraining enhances both the performance and interpretability of deep learning models for fMRI classification. By enabling more stable and biologically plausible representations, TR pretraining supports clinically relevant insights into disorder-specific network disruptions. This study demonstrates the utility of interpretable self-supervised models in neuroimaging, offering a promising step toward transparent and trustworthy AI applications in psychiatry. Full article

Environmental pollutants such as heavy metals, endocrine-disrupting chemicals, microplastics, and airborne particulates are increasingly recognized for their potential to influence immune function through epigenetic mechanisms. This review examines conserved pollutant-associated pathways at interfaces of immunity and epigenetics, with particular attention to Toll-like receptor–NF-κB signalling, NLRP3 inflammasome activity, and reactive oxygen species-driven cascades. Evidence from cellular, animal, and epidemiological studies indicates that these pathways may converge on chromatin regulators such as DNA methyltransferases, histone deacetylases, and EZH2, leading to DNA methylation shifts, histone modifications, and altered chromatin accessibility. Pollutants are also reported to modulate non-coding RNAs, including miR-21, miR-155, and several lncRNAs, which can act as intermediaries between cytokine signalling and epigenetic remodelling. Findings from transgenerational models suggest that pollutant-linked immune–epigenetic alterations might persist across generations, raising the possibility of long-term consequences for immune and neurodevelopmental health. Comparative analyses further indicate convergence across diverse pollutant classes, pointing to a shared mechanistic axis of immune–epigenetic disruption. Overall, these insights suggest that pollutant-induced immune–epigenetic signatures may contribute to inflammation, altered immune responses, and heritable disease risks, and their clarification could inform biomarker discovery and future precision approaches in immunotoxicology. Full article

Background/Objectives: Glioblastomas are a part of adult-type diffuse gliomas, the most common and most aggressive primary brain tumors in adults (glioblastoma, IDH-wildtype). The identification of the genetic factors associated with glioblastoma could be an important contribution to the diagnosis and early prevention of this disease. We compiled data from the global literature and analyzed clinically relevant variants implicated in glioblastoma risk. Methods: PubMed, Web of Science, and Scopus were used as databases. Associations between the SNPs and glioblastoma risk were calculated as a measure of pooled odds ratios (ORs) and 95% confidence intervals. Pearson’s analysis was used for epidemiological correlation (only p-values less than 0.05 were statistically significant), and data were obtained from the World Health Organization platform and the 1000 Genomes Project. Statistical analysis was performed using Review Manager (RevMan) 5.4 and BioEstat 5.0. Results: CCDC26 rs891835 G/T, G/G, and G/T-G/G genotypes were analyzed and determined to increase glioblastoma risk (G/T OR = 1.96, 95% CI: 1.38–2.77, p = 0.0002, I² = 0%; G/G OR = 1.33, 95% CI: 0.46–3.85, p = 0.60, I² = 0%; G/T − G/G OR = 1.96, 95% CI: 1.39–2.76, p = 0.0001, I² = 0%). Epidemiological correlation also demonstrated that the higher the frequency of the CCDC26 rs891835 variant, the higher the incidence of that variant in the European population. Conclusions: CCDC26 rs891835 may serve as a predictive biomarker for glioblastoma, IDH-wildtype risk and may influence higher glioblastoma incidence rates in the European population. Full article

Background/Objectives: Polymyalgia rheumatica (PMR) is a relatively common inflammatory rheumatic disease of the elderly. The role of vitamin D remains unclear in this condition. The endpoints of this study were to assess 25-hydroxyvitamin D [25(OH)D] serum concentrations in PMR patients with active disease compared to elderly controls and to determine if baseline levels or changes following supplementation [delta 25-hydroxyvitamin D, Δ25(OH)D] were associated with improved clinical outcomes. Methods: In this retrospective, case–control study, 29 PMR patients (55% males, 75.24 ± 9.6 years old, disease duration of 3.8 ± 3 months) were included, meeting the 2012 EULAR/ACR classification criteria, with 29 age- and sex-matched controls without systemic inflammatory rheumatic diseases. We assessed demographic, clinical and laboratory features for PMR patients, including baseline 25(OH)D serum concentrations, disease activity (polymyalgia rheumatica activity score), and serum inflammatory biomarkers. A subgroup of them (n = 25) was followed longitudinally, for an average period of 21.1 ± 17.7 months, to evaluate the association between Δ25(OH)D and clinical outcomes at follow-up using multivariate logistic regression. Results: Although lower than the normal reference values, baseline 25(OH)D concentrations did not differ significantly between PMR patients and controls (21.6 ± 9.2 vs. 22.7 ± 11.3 ng/mL, p = 0.66) and did not predict long-term clinical outcomes. However, after only 3 months of supplementation, the increase in 25(OH)D concentrations was significantly associated with a remission status, and patients in remission showed a significant increase in 25(OH)D compared to those with persistent disease activity (+22.02 vs. +1.33 ng/mL, respectively; p = 0.044). Notably, in the multivariate model, this Δ25(OH)D was the strongest independent predictor of remission (OR = 2.89; 95% CI [1.60–4.11]), an effect independent of prednisone dosage prescribed at first visit (p = 0.32) and glucocorticoid exposure at third month (p = 0.12). Conclusions: Individual’s response of PMR patients to supplementation of vitamin D seems to be a robust independent predictor of early clinical remission achievement. Interestingly, optimizing vitamin D supplementation based on individual responsiveness may represent a valuable adjunctive strategy in PMR management. Full article

Mitochondria, as the metabolic hubs of cells, play a pivotal role in maintaining cardiovascular homeostasis through dynamic regulation of energy metabolism, redox balance, and calcium signaling. Cardiovascular diseases (CVDs), including heart failure, ischemic heart disease, cardiomyopathies, and myocardial infarction, remain the leading cause of global mortality, with mitochondrial dysfunction emerging as a unifying pathological mechanism across these conditions. Emerging evidence suggests that impaired mitochondrial transport systems—critical gatekeepers of metabolite flux, ion exchange, and organelle communication—drive disease progression by disrupting bioenergetic efficiency and exacerbating oxidative stress. This review synthesizes current knowledge on mitochondrial transport proteins, such as the voltage-dependent anion channels, transient receptor potential channels, mitochondrial calcium uniporter, and adenine nucleotide translocator, focusing on their structural–functional relationships and dysregulation in CVD pathogenesis. We highlight how aberrant activity of these transporters contributes to hallmark features of cardiac pathology, including metabolic inflexibility, mitochondrial permeability transition pore destabilization, and programmed cell death. Furthermore, we critically evaluate preclinical advances in targeting mitochondrial transport systems through pharmacological modulation, gene editing, and nanoparticle-based delivery strategies. By elucidating the mechanistic interplay between transport protein dysfunction and cardiac metabolic reprogramming, we address a critical knowledge gap in cardiovascular biology and provide a roadmap for developing precision therapies. Our insights underscore the translational potential of mitochondrial transport machinery as both diagnostic biomarkers and therapeutic targets, offering new avenues to combat the growing burden of CVDs in aging populations. Full article