Search Results (1,028)

Background and Objectives: Neutrophil extracellular traps (NETs) have been linked to hypercoagulability, immunothrombosis, and organ injury in COVID-19. Digital morphology of peripheral blood smears enables the identification of NET-compatible appearances (NET-like) in circulation, and associations between NET-like derived indices and clinical outcomes have been reported. However, evidence at hospital admission that relates smear NET-like burden to systemic inflammation and clinical severity remains limited. We therefore aimed to compare the burden of NET-like structures on admission smears according to disease severity and systemic inflammatory markers. Materials and Methods: We included 50 consecutively enrolled adults hospitalized for COVID-19; samples were obtained within 24 h of admission. Severity was defined by the World Health Organization Clinical Progression Scale and grouped as moderate or severe. C-reactive protein (CRP), ferritin, and complete blood counts were measured; the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were calculated. Digital morphology assessed 200 leukocytes per patient; the presence of morphological abnormalities, including NET-like events per patient, was recorded. We additionally quantified NET-like events per 100 white blood cells (NET-like/100 WBC) and the neutrophil extracellular trap–segmented neutrophil ratio (NNSR). Results: At admission, CRP, ferritin, NLR, and PLR of patients were above method-specific reference intervals. NET-like events were identified in 66% of patients. NET-like/100 WBC correlated positively with NLR (r = 0.312; p < 0.05). Patients with severe COVID-19 had higher NET-like/100 WBC than those with moderate disease (5.8 ± 7.34 vs. 14.14 ± 15.12; p = 0.0294). Conclusions: Digital morphological identification of NET-like structures on peripheral blood smears is frequent at admission and is associated with systemic inflammatory burden and with greater COVID-19 severity. These findings support the potential complementary value of reporting NET-like events for initial risk stratification in the clinical laboratory. Full article

Background/Objectives: Hepatocellular carcinoma (HCC) is one of the most common causes of cancer and cancer-related death worldwide. Beyond the well-known factors influencing the risk of HCC, experimental data from animal models and observational human studies support a significant role of the gut microbiota (GM) in HCC initiation and progression. Dysbiosis and increased intestinal permeability synergistically disrupt the ‘gut–liver axis,’ exposing the liver to bacterial metabolites and microbial-associated molecular patterns, thereby contributing to hepatocarcinogenesis. While these findings have expanded our understanding of HCC pathogenesis, a critical translational gap persists as most data derive from preclinical settings, with limited validation in large-scale clinical studies. Methods: This narrative review aimed to contextualise the current evidence on the GM-HCC axis and its clinical translatability. A literature search was conducted in PubMed/MEDLINE, Scopus, and Web of Science up to July 2025 using Medical Subject Headings and related keywords, including HCC, GM, dysbiosis, intestinal permeability, gut–liver axis, microbial metabolites, inflammation/immune modulation, and microbiota-targeted interventions (probiotics, antibiotics, and faecal microbiota transplantation). Reference lists of relevant articles were also screened to identify additional studies. Results: Preclinical models consistently indicate that dysbiosis and impaired gut barrier function can promote hepatic inflammation, immune dysregulation, and pro-tumorigenic signalling through microbe-derived products and metabolite perturbations, supporting a contributory role of the GM in hepatocarcinogenesis. In humans, HCC and advanced chronic liver disease are associated with altered microbial composition and function, increased markers of intestinal permeability, and changes in bile acid and other metabolite profiles; however, reported signatures are heterogeneous across cohorts and analytical platforms. Conclusions: The GM is a biologically plausible and experimentally supported contributor to HCC initiation and progression, with potential for biomarker development and therapeutic targeting. However, clinical translation is limited by predominantly preclinical/associative evidence, interindividual variability, and non-standardised microbiome methods. Large longitudinal studies and adequately powered randomised trials are needed to establish causality, validate biomarkers, and determine whether GM modulation improves HCC prevention, detection, stratification, or outcomes. Full article

Introduction: Rare diseases disperse expertise across institutions and borders, making structured second-opinion systems a pragmatic way to concentrate subspecialty knowledge and reduce diagnostic delays. This scoping review mapped the design, governance, adoption, and impacts of such services across implementation scales. Objectives: To describe how second-opinion services for rare diseases are organized and governed, to characterize technological and workflow models, to summarize benefits and barriers, and to identify priority evidence gaps for implementation. Methods: Using a population–concept–context approach, we included peer-reviewed studies describing implemented second-opinion systems for rare diseases and excluded isolated case reports, purely conceptual proposals, and work outside this focus. Searches in August 2025 covered PubMed/MEDLINE, Scopus, Web of Science Core Collection, Cochrane Library, IEEE Xplore, ACM Digital Library, and LILACS without date limits and were restricted to English, Portuguese, or Spanish. Two reviewers screened independently, and the data were charted with a standardized, piloted form. No formal critical appraisal was undertaken, and the synthesis was descriptive. Results: Initiatives were clustered by scale (European networks, national programs, regional systems, international collaborations) and favored hybrid models over asynchronous and synchronous ones. Across settings, services shared reproducible workflows and provided faster access to expertise, quicker decision-making, and more frequent clarification of care plans. These improvements were enabled by transparent governance and dedicated support but were constrained by platform complexity, the effort required to assemble panels, uneven incentives, interoperability gaps, and medico-legal uncertainty. Conclusions: Systematized second-opinion services for rare diseases are feasible and clinically relevant. Progress hinges on usability, aligned incentives, and pragmatic interoperability, advancing from registries toward bidirectional electronic health record connections, alongside prospective evaluations of outcomes, equity, experience, effectiveness, and costs. Full article

Background: Periodontitis is a multifactorial, chronic inflammatory disease that leads to progressive destruction of the periodontal apparatus. Despite the effectiveness of scaling and root planing (SRP), residual inflammation and limited regenerative potential justify the search for adjunctive biologic therapies. Platelet-derived concentrates, including platelet-rich plasma (PRP), platelet-rich fibrin (PRF), concentrated growth factors (CGF), and platelet-poor plasma (PPP), have gained attention as autologous sources of growth factors enhancing periodontal regeneration. Aim: This narrative review provides a comparative analysis of the biological mechanisms, preparation protocols, and clinical outcomes associated with the adjunctive use of platelet-derived concentrates in non-surgical periodontal therapy. Methods: A narrative literature review was conducted using English-language publications retrieved from PubMed and Google Scholar, covering studies published from 2012 onward. The search strategy was based on combinations of keywords related to platelet-derived concentrates and non-surgical periodontal therapy. In vitro, in vivo, and clinical studies, as well as relevant narrative, systematic, and umbrella reviews evaluating the adjunctive use of platelet-derived concentrates (PRP, PRF, CGF, and PPP) were considered. Studies focusing on biological mechanisms, preparation protocols, and clinical periodontal outcomes were included, whereas case reports, studies unrelated to periodontal therapy, and publications lacking relevant clinical or biological outcome data were excluded. Results: Most clinical studies reported improvements in probing depth reduction, clinical attachment level gain, and bleeding indices following adjunctive use of platelet-derived concentrates with SRP. PRF tended to demonstrate more consistent clinical outcomes compared to PRP, potentially related to its simplified preparation and sustained release of bioactive molecules. CGF showed promising osteogenic and angiogenic properties in preclinical and early clinical studies. PPP, although less extensively investigated, exhibited regenerative and antimicrobial potential in preliminary reports. Conclusions: Platelet-derived concentrates may serve as valuable adjuncts in non-surgical periodontal therapy; however, the current evidence is characterized by methodological heterogeneity and variable study quality. While PRF appears to yield more consistent clinical results, definitive conclusions regarding superiority among different platelet concentrates cannot be drawn. Further well-designed randomized controlled trials are required, particularly for CGF and PPP. Full article

Glaucoma is a leading cause of irreversible blindness worldwide, with its asymptomatic progression highlighting the urgent need for early, minimally invasive biomarkers. Exosomes derived from the aqueous humor (AH) have emerged as promising candidates, as they carry proteins, nucleic acids, and lipids that reflect the physiological and pathological state of ocular tissues such as the trabecular meshwork and ciliary body. However, their low abundance, nanoscale size, and the limited volume of AH complicate detection and characterization. Conventional methods, including Western blotting, PCR or mass spectrometry, are labor-intensive, time-consuming, and often incompatible with microliter-scale samples. Electrochemical biosensors offer a highly sensitive, rapid, and low-volume alternative, enabling the detection of exosomal surface markers and internal cargos such as microRNAs, proteins, and lipids. Recent advances in nanomaterial-enhanced electrodes, microfluidic integration, enzyme- and nanozyme-mediated signal amplification, and ratiometric detection strategies have significantly improved sensitivity, selectivity, and multiplexing capabilities. While most studies focus on blood or serum, these platforms hold great potential for AH-derived exosome analysis, supporting early-stage glaucoma diagnosis, monitoring of disease progression, and evaluation of therapeutic responses. Continued development of miniaturized, point-of-care electrochemical biosensors could facilitate clinically viable, noninvasive exosome-based diagnostics for glaucoma. Full article

Background/Objectives: Periodontal disease is a prevalent chronic inflammatory condition that often progresses to irreversible tissue destruction. This study aimed to evaluate the clinical efficacy of a combined minimally invasive periodontal therapeutic protocol scaling and root planing (SRP) with injectable platelet-rich fibrin (i-PRF) and microneedling (MN) compared to conventional SRP with i-PRF alone in patients with stage II–III periodontitis. Methods: A prospective split-mouth clinical study was conducted on 54 patients diagnosed according to the 2018 EFP/AAP classification. Each participant received SRP + i-PRF in the upper arch (control) and SRP + i-PRF + MN in the lower arch (test). Periodontal parameters clinical attachment level (CAL), bleeding on probing (BOP), and plaque index (PI) were measured at baseline, 1, 3, and 6 months. Data were analyzed using Friedman and Wilcoxon tests with Bonferroni correction. Results: Both treatment protocols produced significant longitudinal improvements in CAL, BOP, and PI (p < 0.001). The most pronounced BOP reduction occurred within the first month, while CAL improvement was progressive and stabilized after six months. The Combined protocol achieved slightly greater CAL gain at 6 months (mean difference ≈ 0.46 mm; p = 0.0013), indicating a modest yet statistically significant advantage in attachment recovery. Correlation analyses confirmed a coherent healing trajectory characterized by early inflammation resolution, plaque control, and later tissue stabilization. Conclusions: Both i-PRF-based regenerative approaches significantly improved periodontal parameters. The addition of MN enhanced CAL recovery and may favor early vascularization and collagen remodeling. Although the clinical difference was limited, the biological plausibility and sustained improvement suggest that MN could represent a valuable adjunct to non-surgical regenerative periodontal therapy. Longer-term studies are warranted to assess the durability of these effects. Full article

Recently, extracellular vesicles (EVs) have emerged as pivotal mediators of intercellular communication that reflect physiological homeostasis and pathological alterations. By encapsulating diverse biomolecules, including proteins, nucleic acids, and lipids, EVs mirror the molecular signatures of their parent cells, thereby positioning EV-based biosensing as a transformative platform for noninvasive diagnostics, prognostic prediction, and therapeutic monitoring. This review provides a comprehensive overview of the current state and clinical translation of EV biosensing technologies. Herein, we have discussed ongoing efforts toward standardization and analytical validation (e.g., MISEV2023 and EV-TRACK) and evaluated advances in sensing modalities such as surface plasmon resonance (SPR), electrochemical, fluorescence, and magnetic detection systems, which have significantly improved analytical performance in terms of sensitivity and specificity. Furthermore, we highlight recent developments in multiplexed and multiomics integration at the single-EV level and the application of machine learning to enhance diagnostic accuracy and interpret biological heterogeneity. The clinical relevance of EV biosensing has been explored across multiple disease domains, including oncology, neurology, and cardiometabolic and infectious diseases, with an emphasis on translational progress toward standardized, regulatory-compliant, and scalable platforms. Finally, this review identifies key challenges in manufacturing scale-up, quality control, and point-of-care deployment and proposes a unified framework to accelerate the adoption of EV biosensing as a cornerstone of next-generation precision diagnostics and personalized medicine. Full article

The COVID-19 pandemic accelerated vaccine innovation but also exposed weaknesses in global access and manufacturing. Yeast-based platforms, particularly Saccharomyces cerevisiae and Pichia pastoris, also known as Komagataella phaffii, offer a practical complement to vector systems. These eukaryotic microorganisms combine safety, scalability, and cost-effectiveness with the ability to express complex antigens and assemble virus-like particles. Building on the success of the recombinant hepatitis B vaccine, recent advances in glycoengineering, CRISPR-based host optimization, and surface display technologies have expanded the utility of yeast-based platforms for the rapid development of vaccines. Yeast-derived SARS-CoV-2 receptor-binding domain (RBD) subunit vaccines, such as Corbevax and Abdala (CIGB-66), demonstrate that affordable, immunogenic, and thermostable products are feasible at scale. Emerging innovations in glycan humanization, thermostable formulations, and oral or mucosal delivery highlight the potential of yeast-based vaccines for decentralized manufacturing and equitable pandemic preparedness. This review summarizes recent technical and clinical progress in yeast-based vaccine research, positioning these platforms as accessible and adaptable tools for future outbreak responses and global immunization strategies. Full article

Background: Early diagnosis of Alzheimer’s disease (AD) is essential for slowing disease progression and mitigating cognitive decline. However, conventional diagnostic methods are often invasive, time-consuming, and costly, limiting their utility in large-scale screening. There is an urgent need for scalable, non-invasive, and accessible screening tools. Methods: We propose a novel screening framework combining a pre-trained multimodal large language model with structured MMSE speech tasks. An artificial intelligence-assisted multilingual Mini-Mental State Examination system (AAM-MMSE) was utilized to collect voice data from 1098 participants in Sichuan and Chongqing. CosyVoice2 was used to extract speaker embeddings, speech labels, and acoustic features, which were converted into statistical representations. Fourteen machine learning models were developed for subject classification into three diagnostic categories: Healthy Control (HC), Mild Cognitive Impairment (MCI), and Alzheimer’s Disease (AD). SHAP analysis was employed to assess the importance of the extracted speech features. Results: Among the evaluated models, LightGBM and Gradient Boosting classifiers exhibited the highest performance, achieving an average AUC of 0.9501 across classification tasks. SHAP-based analysis revealed that spectral complexity, energy dynamics, and temporal features were the most influential in distinguishing cognitive states, aligning with known speech impairments in early-stage AD. Conclusions: This framework offers a non-invasive, interpretable, and scalable solution for cognitive screening. It is suitable for both clinical and telemedicine applications, demonstrating the potential of speech-based AI models in early AD detection. Full article

Objective: This was a longitudinal study of TCF4 CTG18.1 trinucleotide repeat lengths in 17 patients (27 eyes) diagnosed with Fuchs’ endothelial corneal dystrophy (FECD), and it aimed to correlate the repeat expansion status with disease severity and progression. Design: This was a prospective cohort study looking at FECD clinical progression and TCF4 CTG18.1 repeat length expansion status over time. Methods: A total of 27 eyes from 17 patients diagnosed with FECD were recruited. Only eyes with FECD disease severity of at least Grade 4 on the modified Krachmer clinical grading scale were included; eyes that had previously undergone any form of ocular surgery prior to the first genotyping or during the duration of follow-up were excluded. CTG trinucleotide repeat genotyping was performed on peripheral blood leukocytes at two time points over an average follow-up of 10 years. Over the follow-up period, the FECD progression of each subject was examined using pachymetry, Scheimpflug imaging (Pentacam), and endothelial cell density (ECD) readings, during the baseline visit, yearly thereafter, at the time of repeat CTG18.1 genotyping, and at their latest visit. Main Outcome Measures: The clinical progression of FECD patients was assessed using central corneal thickness (CCT), ECD, and any keratoplasty performed. CTG repeat length was assessed twice over the entire follow-up period. Results: The non-expanded alleles were shown to be stable over the period of follow-up and did not develop any expanded repeats. Repeat expansion did not influence the risk of attaining Threshold Disease, although more patients in the L ≥ 40 group (CTG18.1 repeat sequence of more than or equal to 40 repeats) underwent keratoplasty. Conclusions: Through this study, we found that the CTG18.1 allele lengths of <40 repeats in peripheral blood leukocytes showed minimal change over a 10-year period, and none became an expanded repeat. Hence, a single CTG expansion assessment, performed at any point in a patient’s lifetime, is likely a good representation of genetic risk. Clinicians may use this information to better advise patients on the risk of clinical progression and the best therapeutic strategy. Full article

Background: A patient’s lung condition can be estimated using mechanical ventilation waveform data. These procedures are often labour-intensive and error-prone, especially during large-scale health crises, leading to infrequent executions. Automated diagnostic techniques in healthcare are currently limited by the lack of large, labelled datasets required for effective machine learning applications. Analytical modelling of the mechanical ventilator-patient (MV-P) system is complex, and existing models fail to fully integrate adjustable parameters for patient, ventilation, and disease conditions. Methods: This article presents an expanded system model developed in MATLAB^® Simulink^®. The model accommodates adjustments to anthropometric parameters, ventilator settings for the three most common modes in ICU sedation, and disease progression simulations. Other uniquely combined aspects include the ability to perform an end-inspiratory hold manoeuvre and per-breath optimisation of PI control parameters. Results: The system has been validated against clinical techniques, compared to real-world data, and verified with accuracy within 3% and average normalised standard deviation of 3.4% for all adjustable parameters. Conclusions: Based on this model, which introduces high-fidelity disease progression modelling, a fully labelled synthetic dataset of nearly 2M breaths over a range of health conditions was generated. This addresses the critical shortage of labelled data needed for developing early proof-of-concept, resource-efficient diagnostic tools for automatically estimating lung conditions. Full article

Background: Cirrhosis represents the final common pathway of chronic liver injury, arising from diverse etiologies such as metabolic, viral, autoimmune, and alcohol-related liver diseases. Despite similar exposures, disease progression varies considerably among individuals, suggesting a genetic contribution to susceptibility and outcome. Objective: This narrative review examines how specific genetic variants influence the risk, progression, and phenotypic expression of cirrhosis. It provides a structured synthesis of established and emerging gene associations, emphasizing their biological mechanisms and potential clinical relevance. Methods: This narrative review synthesizes evidence from all major biomedical and scientific databases, including PubMed, Scopus, Web of Science, and Google Scholar, as well as reference lists of relevant articles, covering literature published between 2005 and 2025 on genetic polymorphisms associated with cirrhosis and its etiological subtypes. Content: Variants are categorized into four mechanistic domains—metabolic regulation, immune modulation, liver enzyme activity, and ancestry-linked expression patterns—representing a novel integrative framework for understanding genetic risk in cirrhosis. Well-characterized variants such as PNPLA3, TM6SF2, HSD17B13, and MBOAT7, along with less commonly studied loci and chromosomal alterations, are discussed in relation to major etiologies, including MASLD/MASH, viral hepatitis, alcohol-related liver disease, and autoimmune conditions. Conclusions: Genetic insights into cirrhosis offer pathways toward early risk stratification and personalized disease management. While polygenic risk scores and multi-omic integration show promise, their clinical translation remains exploratory and requires further validation through large-scale prospective studies. Full article

Background and Clinical Significance: Wartenberg’s syndrome (cheiralgia paresthetica) is classically described as a pure sensory neuropathy of the superficial branch of the radial nerve (SBRN). However, in rare circumstances, dynamic mechanical irritation around the radial styloid may produce an atypical clinical phenotype with concurrent motor impairment, broadening the clinical significance of recognizing motion-related compression mechanisms. Case Presentation: A 35-year-old woman presented with persistent dorsoradial wrist pain and numbness, accompanied by progressive weakness of thumb extension, five years after a conservatively treated nondisplaced scaphoid fracture. Neurological examination demonstrated sensory loss in the SBRN distribution and Medical Research Council (MRC) grade 3/5 strength of the extensor pollicis longus (EPL). Nerve conduction studies revealed a markedly prolonged EPL motor latency (4.5 ms; normal ≤ 2.5 ms) with preserved sensory conduction. High-resolution ultrasound showed focal enlargement of the SBRN (cross-sectional area 0.13 cm²) and, critically, dynamic snapping of the nerve over the radial styloid that reproduced the patient’s symptoms. The patient underwent ten weekly sessions of ultrasound-guided hydrodissection with 5% dextrose. After treatment, the pain Visual Analog Scale improved from 8/10 to 0/10 and EPL strength recovered to MRC 5/5. Follow-up nerve conduction studies demonstrated normalization of EPL motor latency (2.1 ms), and repeat ultrasound confirmed resolution of SBRN enlargement and snapping. Conclusions: This case expands the phenotype of Wartenberg’s syndrome to include mixed sensory–motor involvement associated with dynamic SBRN snapping at the radial styloid. Dynamic ultrasound was pivotal for identifying the motion-dependent mechanism, and ultrasound-guided 5% dextrose hydrodissection achieved complete sensory and motor recovery as a minimally invasive and effective treatment option. Full article

Background: Essential tremor (ET) is among the most common neurological disorders, requiring precise diagnosis and severity assessment for personalized and effective management. Methods: This study explores an innovative approach to evaluate ET severity using the gold-standard Archimedes spiral test. The family-based dataset covers the entire range of tremor severity, from very mild (level 1) to advanced stages, offering a valuable resource for studying early diagnosis and tracking disease progression. The proposed method introduces a machine learning pipeline that combines Principal Component Analysis (PCA), linear discriminant analysis (LDA), and support vector machines (SVMs) to classify ET severity based on Archimedean spiral radius data. Results: By incorporating the Fahn–Tolosa–Marin Tremor Rating Scale (FMT-TRS), the pipeline effectively distinguishes between tremor presence and severity. Its robustness was demonstrated through rigorous cross-validation and tests involving Gaussian noise perturbations. Conclusions: These results underscore the machine learning-based pipeline’s potential as a non-invasive and trustworthy diagnostic tool for clinical use and telemedicine applications. Moreover, the combination of geometric features, FMT-TRS scores, clinically oriented evaluation metrics, and classical statistical and machine learning models offers a robust, interpretable, explainable, and clinically meaningful analytical framework. Full article

This narrative review explores the impact of diet and physical exercise both as a risk factor of central nervous system inflammatory diseases, but more importantly as potential adjunctive disease modifiers in Multiple Sclerosis (MS), Neuromyelitis Optica Spectrum Disorders (NMOSD), and Myelin Oligodendrocyte Glycoprotein (MOG) antibody-associated disease (MOGAD). The majority of evidence relies on MS preclinical and clinical studies, but preclinical studies also support the benefit of lifestyle intervention in NMOSD and MOGAD. In MS, adherence to healthy diets (particularly Mediterranean and MIND diets) could lead to a milder disease course with reduced relapse rates, while structured exercise from early disease stages promotes neuroprotection by upregulating neurotrophic factors and preserving brain volume, possibly impacting disease progression. The ketogenic diet and intermittent caloric restriction also showed promising results. Physical activity, including both aerobic training and resistance training, emerges as a potential disease-modifying strategy by promoting neuroprotection, reducing inflammation, and supporting functional and cognitive outcomes, particularly when implemented early in the disease course. A synergistic approach alongside disease-modifying treatments (DMTs) would further positively modulate core pathological processes. Evidence for NMOSD and MOGAD warrants further investigation. We highlight that integrating personalized lifestyle strategies would be beneficial from the early stages. However, future large-scale, standardized trials are required to fully confirm the neuroprotective potential of diet and exercise across the entire spectrum of CNS disorders. Full article