Search Results (2,711)

Exosomes and small extracellular vesicles are promising liquid-biopsy biomarkers because they carry molecular information from their cells of origin and can be accessed from minimally invasive biofluids. Reliable separation and detection are made more difficult by their small size, low abundance, diverse composition, and co-occurrence with lipoproteins, protein aggregates, and other extracellular particles. To improve exosome enrichment, capture, and sensing, nanomaterial-assisted techniques have become crucial. Using a mechanism-based approach that differentiates between non-gravimetric signal amplification and genuine physical mass loading, this study offers an organized comparison of nanomaterial-enabled exosome sensing techniques. This distinction is helpful because different transducers measure different physical quantities: while optical, electrochemical, fluorescent, catalytic, and nucleic acid-based platforms typically benefit from enhanced signal generation rather than increased mass, resonant and gravimetric sensors benefit from increased inertial or surface-bound mass. In terms of amplification mechanism, transducer compatibility, sample-matrix tolerance, workflow complexity, and translational maturity, the review contrasts metallic nanoparticles, magnetic systems, metal–organic frameworks, carbon and two-dimensional materials, quantum dots, upconversion nanomaterials, DNA nanostructures, and polymer-based platforms. The gap between analytical sensitivity and clinical utility, including separation purity, recovery, biological heterogeneity, pre-analytical variability, interference from complex biofluids, and the need for uniform validation, is given special focus. The review concludes that no single nanomaterial or amplification method is universally optimal; instead, platform-aware, application-specific integration of isolation, amplification, and validation techniques is necessary for clinically meaningful exosome sensing. Full article

The development of sustainable and climate-resilient food systems increasingly relies on robust analytical methodologies capable of integrating environmental, biochemical, and management-related signals. In this study, a multi-isotope framework based on δ²H, δ¹⁸O, δ¹³C, and δ¹⁵N was applied to assess its capacity to discriminate between contrasting raspberry production systems and to provide chemically grounded indicators of agroecosystem functioning. Raspberry fruits (Rubus idaeus L.; cultivars Opal and Delniwa) were collected during the 2024–2025 growing seasons from two distinct systems in Romania: an organic open-field system and a rainfed agroforestry system. Stable isotope ratio analysis revealed system-dependent isotopic patterns, with the strongest differentiation observed for δ¹⁵N. Nitrogen isotope composition (δ¹⁵N) provided the strongest discrimination, with enriched values in organic fruits (2.73–9.77‰) and depleted values in agroforestry fruits (−3.01 to 0.62‰), reflecting differences in nitrogen sources and cycling pathways. Hydrogen and oxygen isotopes (δ²H: −60.46 to −4.62‰; δ¹⁸O: −6.19 to 10.41‰) were consistent with hydroclimatic variability and evaporative fractionation processes associated with soil–plant–atmosphere interactions. Carbon isotopes (δ¹³C: −28.14 to −22.62‰) provided complementary insights into plant water-use conditions. Multivariate statistical analysis supported the separation between production systems, while short-term fertilisation effects were secondary to system-level controls. The results suggest that raspberry fruits preserve an integrated isotopic fingerprint of production environment and management practices. From an analytical chemistry perspective, this work highlights the relevance of multi-isotope approaches as transferable tools for food authentication, traceability, and sustainability assessment, contributing to the broader application of stable isotope techniques across complex biological systems. Full article

Nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H₂S) were once regarded solely as toxic environmental gases. However, accumulating evidence over the past several decades has established them as the three principal endogenous gasotransmitters that regulate a wide spectrum of physiological and pathological processes. Unlike conventional signaling molecules, gasotransmitters diffuse freely across biological membranes and exert potent biological effects through receptor-independent mechanisms, including redox-sensitive post-translational modifications and modulation of heme-containing proteins. Although the individual functions of NO, CO, and H₂S have been extensively reviewed, emerging studies indicate that these gaseous mediators rarely operate in isolation. Instead, they form a highly integrated signaling network characterized by direct chemical interactions, reciprocal enzymatic regulation, and convergence upon common downstream pathways. In this mini-review, we propose the concept of a “Gasotransmitter Trio Network,” emphasizing the molecular crosstalk among NO, CO, and H₂S as a fundamental determinant of cellular homeostasis. We first summarize the biosynthetic pathways and major signaling mechanisms of the gasotransmitter trio, including S-nitrosylation, persulfidation, and heme-dependent regulation. We then discuss recent advances revealing how interactions among these gases generate novel bioactive intermediates and coordinate redox signaling. Particular attention is given to the emerging roles of gasotransmitters in regulating ferroptosis, autophagy, and mitophagy by modulating iron metabolism, lipid peroxidation, mitochondrial quality control, and antioxidant defense systems. These findings support a unified framework in which gasotransmitters function as master regulators of cellular fate under conditions of physiological and pathological stress. Finally, we highlight recent progress in stimuli-responsive donors, CO-releasing molecules (CORMs), NO-releasing materials (NORMs), H₂S donors, and advanced nanoplatforms that enable spatiotemporally controlled gas delivery. We propose that future therapeutic strategies will increasingly rely on programmable multi-gas systems that recapitulate endogenous gasotransmitter networks. Collectively, this review provides a systems-level perspective on gasotransmitter biology and outlines emerging opportunities for the development of precision gas medicine in cardiovascular, neurodegenerative, inflammatory, metabolic, and malignant diseases. Full article

Background: Ischemic stroke has been reported rarely after coronavirus disease 2019 (COVID-19) vaccination, most clearly in association with vaccine-induced immune thrombotic thrombocytopenia (VITT). Nevertheless, temporal proximity alone cannot establish causality, particularly when conventional vascular risk factors are present. We report a case of posterior circulation ischemic stroke occurring 36–48 h after first-dose ChAdOx1 nCoV-19/AZD1222 vaccination without VITT and provide a focused narrative review of the clinical, epidemiological, and mechanistic evidence regarding post-vaccination stroke. Methods: Clinical, laboratory, and neuroimaging data were reviewed retrospectively. A focused narrative literature review was performed to contextualize VITT-related and non-VITT ischemic stroke after COVID-19 vaccination, pharmacovigilance signals, population-based evidence, and proposed biological mechanisms. Results: A 63-year-old man with well-controlled hypertension and a remote history of smoking developed systemic symptoms within 24 h of first-dose ChAdOx1 nCoV-19/AZD1222 vaccination, followed by severe hypertension and acute posterior circulation neurological symptoms 36–48 h after vaccination. Neuroimaging showed an acute left cerebellar infarct extending into the middle cerebellar peduncle, with approximately 50% stenosis of the intradural left vertebral artery. Platelet counts remained normal, D-dimer and anti-PF4 antibody testing were normal, SARS-CoV-2 polymerase chain reaction (PCR) testing was negative, and routine cardiac evaluation did not identify a definite cardioembolic source. Conclusions: This case highlights an early posterior circulation ischemic stroke temporally associated with ChAdOx1 nCoV-19/AZD1222 vaccination in the absence of VITT. Although individual causality cannot be established from a single case, careful reporting of such presentations may improve clinical recognition, etiological evaluation, and pharmacovigilance. Full article

Genomic instability is a defining feature of cancer progression and therapeutic resistance, yet contemporary oncology interprets it largely through tumor-intrinsic genetic alterations, with less attention to the evolving host physiological context in which DNA damage accumulates and genome maintenance operates. In this perspective, we propose a longitudinal host-transfer-state framework that treats host physiology not as a static background but as a continuously evolving adaptive system. Gut microbial ecology, micronutrient physiology, inflammatory signaling, circadian organization, hydration, environmental exposures, and chronic stress are framed as interacting biologic transfer systems that shape DNA repair fidelity, oxidative buffering, immune coordination, and adaptive tumor behavior over time. These influences are proposed to vary by tumor type, treatment context, and individual physiologic reserve, and clinically observable disease may lag behind deeper latent biologic dynamics. We further outline how longitudinal multi-omic integration and constrained, bounded artificial intelligence—used for longitudinal data integration, normalization, contextualization, and bounded analytical support rather than autonomous decision-making—could identify patient-specific constraints on genome maintenance and treatment tolerance. Host-directed strategies are presented as complementary to, not replacements for, established tumor-directed therapies. Full article

Introduction. Psoriasis is a chronic inflammatory disease histologically characterized by epidermal hyperproliferation, altered keratinocyte differentiation and dermal vascular remodeling. Although the diagnosis is mainly clinical, non-invasive imaging methods, such as high-frequency skin ultrasound, allow an objective assessment of skin changes and disease activity. Material and Methods. We conducted a pilot, observational, cross-sectional and comparative study, conducted within the Dermatovenerology Department of the Central Military Emergency Hospital “Dr. Carol Davila”, Bucharest, which included 40 patients diagnosed with psoriasis vulgaris, of whom 22 received conventional systemic treatment (methotrexate 15 mg/week), and 18 received biological therapy. For each patient, a representative, clinically active and recently appeared psoriatic plaque was evaluated with ultrasound, and the thickness of the epidermis, the thickness of the dermis, the thickness of the hypoechoic subepidermal band (SLEB) and the Doppler signal were analyzed. Statistical analysis was performed using SPSS v26. Results. Patients under biologic therapy had significantly lower ultrasound parameters compared to those under conventional systemic therapy, especially regarding epidermis thickness, hypoechoic subepidermal band thickness and Doppler signal. The PASI score was significantly higher in the conventionally treated group. Also, significant positive correlations were found between the PASI score and the hypoechoic subepidermal band thickness and the Doppler signal, Conclusions. Ultrasound parameters represent useful objective markers in the evaluation of psoriasis, reflecting disease activity. Patients under biologic therapy presented, at the time of evaluation, imaging parameters suggestive of reduced skin inflammation compared to those treated conventionally. Full article

Chikungunya virus (CHIKV), traditionally recognized as a mosquito-borne alphavirus that causes febrile illness and debilitating arthralgia, has increasingly been associated with atypical organ involvement, including respiratory manifestations. These observations raise important questions regarding whether respiratory symptoms reflect severe systemic disease or signal previously underappreciated respiratory exposure routes. This review aimed to synthesize current evidence on respiratory complications of CHIKV infection and to evaluate the plausibility of respiratory or aerosol-associated transmission. A systematic literature search of PubMed, EMBASE, and MEDLINE (Ovid) identified five eligible studies spanning clinical virology, outbreak surveillance, epidemiology, and experimental aerosol models. Across human studies conducted in India, Réunion Island, Puerto Rico, and Brazil, respiratory presentations—including pneumonia, dyspnea, and respiratory failure—were uncommon but consistently associated with increased hospitalization and mortality risk. Respiratory symptoms generally arose in the context of respiratory viral coinfections, systemic inflammation, or cardiopulmonary decompensation rather than primary viral tropism for the respiratory tract. Only one non-human primate study directly evaluated aerosol exposure, demonstrating that cynomolgus macaques could be infected via inhaled CHIKV, confirming biological plausibility but showing no evidence of enhanced respiratory pathology. Importantly, no epidemiologic data support human-to-human airborne or droplet transmission. Collectively, available evidence indicates that respiratory involvement serves as a marker of disease severity rather than a transmission route. Nonetheless, rare aerosol-acquisition events in laboratory settings underscore the need for continued vigilance, strengthened surveillance, and re-evaluation of respiratory risks as climate change and viral evolution expand CHIKV’s global footprint. Full article

Early-onset colorectal cancer (EOCRC) is increasing disproportionately among Hispanic/Latino (H/L) populations and demonstrates substantial molecular and clinical heterogeneity. Although Wingless/Integrated (WNT) pathway alterations are among the most common genomic events in colorectal cancer, their prognostic significance in the context of contemporary systemic therapies, including Bevacizumab, remains incompletely understood. We conducted an integrative clinical–genomic analysis of colorectal cancer cohorts stratified by age at diagnosis, ancestry, and Bevacizumab exposure, interrogating somatic alterations across curated WNT signaling pathway genes. Conversational artificial intelligence agents (AI-HOPE and AI-HOPE-WNT) enabled dynamic cohort construction, treatment-specific subgroup analyses, and pathway-level interrogation through natural language-driven clinical–genomic integration. WNT pathway alterations, predominantly involving APC, were highly prevalent across all cohorts; however, their distribution and clinical associations demonstrated strong treatment-, ancestry-, and age-dependent variability. Bevacizumab-treated tumors exhibited lower mutation frequencies in several WNT regulators, including RNF43, AXIN1/2, TCF7L2, and AMER1, suggesting potential biologic interaction or treatment-related selective pressure. Importantly, WNT pathway alterations were associated with improved overall survival in H/L EOCRC and Non-Hispanic White (NHW) late-onset colorectal cancer, but with worse survival in NHW EOCRC, highlighting distinct ancestry- and age-specific prognostic effects. These findings support the role of the WNT pathway dysregulation as a disparity-aware biomarker framework in colorectal cancer and demonstrate the utility of conversational AI systems for scalable multidimensional clinical–genomic integration in precision oncology. Full article

2,4-Dichlorophenoxyacetic acid (2,4-D), originally developed as a synthetic auxinic herbicide, is the most widely used chemical inducer of somatic embryogenesis (SE) in plants. Despite extensive use of 2,4-D in plant regeneration, the systems-level regulatory mechanisms connecting hormonal signaling, metabolic reprogramming, translational control, and embryogenic competence remain poorly resolved. Here, we hypothesize that TOR signaling functions as an integrative molecular hub coordinating transcriptional, metabolic, and developmental reprogramming during somatic embryogenesis induction. To investigate the molecular regulatory landscape associated with 2,4-D-induced SE, we performed a systems-level analysis integrating publicly available transcriptomic data from Arabidopsis thaliana with high-confidence protein–protein interaction (PPI) network analyses using STRING v12.0 (confidence score ≥ 0.900). Using a previously published transcriptomic dataset, we identified 1927 upregulated genes associated with SE induction, which were organized into 34 functional modules related to transcriptional regulation, translation metabolism, hormone signaling and cellular homeostasis. Within this interactome, TARGET OF RAPAMYCIN (TOR) kinase emerged as an integrative regulatory hub associated with multiple pathways involved in embryogenic reprogramming. Network analyses revealed three major TOR-associated regulatory axes: (1) the TOR–FKBP12–RPS6A axis, associated with ribosome biogenesis and translational regulation; (2) the TOR–CBP20 axis, connected with transcriptional reprogramming; SE master regulators (LEC1, LEC2, and FUS3); and lipid, sterol, brassinosteroid (BR), and auxin-associated pathways; and (3) the TOR–TAP46 axis, linked with one-carbon metabolism, nucleotide biosynthesis, DNA replication and repair, and genome-stability pathways. Additionally, the network contained 411 embryo-lethal (EMBL) genes distributed across multiple regulatory modules, reinforcing the biological relevance of the identified interactome and highlighting the importance of coordinated developmental, metabolic, and transcriptional regulation during embryogenesis induction. These findings support a systems-level TOR-associated regulatory framework involved in the integration of transcriptional, translational, metabolic, hormonal, and genome-maintenance pathways during embryogenesis. This interactome model provides a foundation for functional studies aimed at dissecting the molecular mechanisms underlying SE and identifying candidate targets to improve regeneration and biotechnological application and crop genetic engineering. Collectively, this study proposes a mechanistic framework in which TOR signaling integrates developmental, metabolic, translational, and genome-stability pathways to orchestrate embryogenic competence, providing candidate molecular targets for improving plant regeneration and genome engineering platforms. Full article

Postbiotics are defined as preparations of inanimate microorganisms and/or their components that confer a health benefit on the host. Although interest in postbiotics has increased substantially, their translational use in functional foods remains insufficiently characterized with respect to preparation identity, production methodology, food-matrix compatibility, mechanistic specificity, and regulatory positioning. This PRISMA-guided structured review aims to synthesize current evidence on postbiotics in functional food and nutraceutical contexts, with particular emphasis on preparation-based characterization, gut–brain axis-related mechanisms and clinical findings, food matrix applicability, and regulatory and health-claim considerations. Unlike broader postbiotic reviews that mainly address definitions, general health effects, or technological stability, this review integrates preparation identity, production process, gut–brain axis-related evidence, food matrix compatibility, and regulatory/health-claim translation within a single functional food framework. A structured literature search was conducted in Scopus and Web of Science Core Collection and was completed on 16 February 2026. The search strategy included three conceptual blocks: postbiotic and inactivation-based preparation terms, functional food/nutraceutical and food matrix terms, and gut–brain axis-related clinical and mechanistic terms. Cosmetic, topical, veterinary, animal feed, and aquaculture-focused publications were excluded. The export files contained 131 records from Scopus and 136 from the Web of Science Core Collection, yielding 267 records after applying document-type and language filters. After manually removing duplicates, 237 unique records were screened. Following title/abstract screening, 176 records were excluded as outside the scope of the review, and 61 publications were retained for full-text assessment and final thematic synthesis. The review was reported according to applicable PRISMA 2020 items. The evidence was organized into three thematic domains: gut–brain axis-related clinical findings, mechanistic evidence, and food matrix/product development applications. Heat-inactivated preparations, including Lactobacillus gasseri CP2305 and Lactiplantibacillus plantarum SNK12, have shown preliminary effects on stress-related symptoms, sleep quality, and selected neuroendocrine or inflammatory biomarkers in human studies. Mechanistic pathways include gut barrier integrity, immunomodulation, short-chain fatty acid signaling, tryptophan–kynurenine–serotonin metabolism, vagal communication, and regulation of the hypothalamic–pituitary–adrenal axis. Food matrix studies support the potential application of postbiotics in fermented dairy products, cereal-based systems, plant-based matrices, powders, concentrates, and bioactive packaging; however, matrix-dependent effects on bioavailability, sensory quality, and biological activity remain incompletely defined. Postbiotics provide a stable translational platform for functional-food development, but their scientific and commercial use requires clear characterization of the microbial source, production process, inactivation method, retained active fractions, dose metric, delivery matrix, and clinically meaningful endpoint. Future studies should avoid broad category-level claims and prioritize preparation- and matrix-defined human evidence with standardized safety reporting. Full article

Nitric oxide (NO) is a small, highly reactive gaseous signaling molecule that plays diverse and context-dependent roles in microbial physiology and host–microbe interactions. Over the past decade, increasing evidence has revealed the dual nature of NO as both an antimicrobial effector and a signaling mediator involved in microbial stress responses, metabolism, biofilm dynamics, quorum sensing, virulence regulation, and symbiotic interactions. In microbial systems, NO influences adaptation to environmental stress and contributes to mechanisms associated with persistence and antimicrobial resistance. In host organisms, NO functions as a key component of innate immunity while also participating in beneficial interactions involving rhizobia, mycorrhizal fungi, and probiotic microorganisms. Despite its biological significance, accurate detection and quantification of NO remain challenging because of its transient nature, high reactivity, low physiological concentrations, and interference from related reactive oxygen and nitrogen species. Recent advances in biosensing technologies have substantially improved NO detection capabilities through the development of electrochemical, optical, enzyme-based, microfluidic, wearable, and implantable sensing platforms. These innovations are complemented by analytical techniques including electron paramagnetic resonance spectroscopy, mass spectrometry, fluorescence-based imaging, and advanced microscopy, which enhance sensitivity, specificity, and spatiotemporal resolution in complex biological environments. Concurrently, statistical and computational approaches—including sensor calibration models, multivariate analyses, machine learning algorithms, and bioinformatics pipelines—have become increasingly important for extracting biologically meaningful information from NO-related datasets. Unlike previous reviews that primarily focus on either NO biology or sensing technologies, this review integrates current knowledge of NO-mediated microbial physiology and host–microbe interactions with recent developments in biosensor engineering, analytical methodologies, statistical frameworks, and emerging artificial intelligence (AI)-driven data interpretation. We further highlight applications of NO detection in infectious disease diagnostics, antimicrobial screening, probiotic and biofertilizer evaluation, environmental microbiome monitoring, and real-time studies of symbiosis and infection. Finally, future directions including miniaturized sensing platforms, multi-omics integration, AI-assisted analytics, and sensor standardization are discussed. By unifying molecular, analytical, and computational perspectives, this review provides a multidisciplinary framework and roadmap for advancing NO-based research and translational applications across microbial, environmental, and host-associated systems. Full article

Polycyclic aromatic hydrocarbons (PAHs) and their halogenated derivatives are important targets in environmental monitoring and pollution control because of their persistence, bioaccumulation, and potential carcinogenicity. Reliable strategies for detecting these pollutants remain essential for environmental risk assessment. In recent years, microbial whole-cell biosensors have attracted increasing attention as analytical tools for pollutant detection and toxicity evaluation. These biosensors employ living cells to recognize target compounds and generate measurable signals through endogenous metabolic pathways and transcriptional regulatory networks. As a result, they can reflect biologically relevant responses and operate in complex environmental matrices, making them suitable for in situ monitoring. This review summarises recent advances in whole-cell biosensors for detecting PAHs and their halogenated derivatives. We discuss the design strategies for constructing these whole-cell biosensors and outline their technological development. Recent efforts to improve biosensor performance are also highlighted. Current research trends indicate a shift from optimizing individual genetic components to improving overall system robustness, standardized evaluation, and practical field deployment. These developments provide important insights for designing reliable and engineerable whole-cell biosensing platforms for monitoring PAHs and related pollutants. Full article

Coastal lagoons are key wintering habitats for waders, yet long-term changes in their community structure remain poorly understood in Mediterranean systems. We analyzed a 30-year dataset (1993–2022, excluding 2021) of wintering waders in the Venice Lagoon to assess trends in abundance, community structure, thermal composition and spatial patterns. Total abundance increased significantly (+3.5% yr⁻¹), while species richness ranged between 12 and 21 species per winter and increased over time. Community structure changed markedly, but the assemblage remained highly dominated by Dunlin Calidris alpina without evidence of increasing dominance or declining evenness. Instead, richness, Shannon diversity and Pielou’s evenness increased, whereas Berger–Parker dominance declined slightly but significantly. Species-level analyses showed a prevalence of increasing trends: ten of the 19 species analyzed increased significantly, three declined, one was stable, and five showed uncertain trends. Multivariate analyses based on Bray–Curtis dissimilarities showed significant compositional differences among approximately decadal periods, both including and excluding Dunlin, indicating that long-term assemblage reorganization was not solely attributable to the dominant species. The Community Temperature Index (CTI) increased significantly (p = 0.001), but this abundance-weighted signal was weak in biological magnitude and contrasted with a declining presence–absence CTI; moreover, this pattern was not robust to the exclusion of Dunlin, indicating dominance-driven dynamics. Spatial analyses revealed a strong increase in the proportion of counted birds recorded in the open lagoon (p < 0.001) and a decline in fish farms (p < 0.001), but this pattern disappeared after excluding Dunlin, suggesting that the apparent spatial redistribution was largely driven by this species. Overall, the assemblage is increasing and compositionally reorganized, while remaining strongly influenced by Dunlin dominance, highlighting the need to integrate species- and community-level approaches when interpreting ecological indicators. Full article

Circadian rhythms synchronize physiological processes with the light–dark cycle and regulate biological functions relevant to cancer, including cell-cycle control, metabolism, DNA repair, immunity, and tissue homeostasis. Growing evidence indicates that disruption of these temporal mechanisms contributes to tumor initiation, progression, metastasis, and treatment response. In colorectal cancer (CRC), circadian clock dysregulation has emerged as an important component of tumor biology. A systematic search identified 1338 records, of which 43 studies met the eligibility criteria (20 human, 19 experimental, and 4 chronotherapy studies). Across the included studies, statistically significant associations were consistently reported between dysregulation of clock genes such as PER1, PER3, CLOCK, BMAL1, CRY1, TIMELESS, and ARNTL2 and alterations in proliferation, metabolism, epithelial plasticity, immune regulation, metastatic potential, and treatment responsiveness. Experimental evidence also supported interactions with Wnt signaling, ferroptosis, oxidative-stress adaptation, epithelial–mesenchymal remodeling, and a proposed clock–microbiota–immune axis. Overall, the available evidence indicates that circadian dysregulation represents a systems-level disturbance that gives rise to a multidimensional biological condition, here referred to as the Tumor Temporal State, integrating the metabolic, immune, invasive, and therapeutic dimensions of colorectal cancer biology. Full article

Physiological signals, such as electroencephalograms (EEG), electrocardiograms (ECG), and electromyograms (EMG) play a critical role in modern clinical diagnosis, monitoring, and rehabilitation. While deep artificial neural networks (ANNs) have achieved strong performance in analyzing these signals, their high computational cost and energy demands limit deployment in real-time, wearable, and edge-based healthcare systems. Spiking Neural Networks (SNNs), inspired by biological neural computation, offer an event-driven alternative that naturally captures temporal dynamics and enables energy-efficient inference. This article provides a comprehensive review of SNN-based methods for physiological signal analysis across EEG, ECG, and EMG modalities. We survey neuron models, network architectures, encoding schemes, and training methodologies, and systematically review recent state-of-the-art applications in medical diagnosis and rehabilitation. Through analysis, we identify recurring architectural and methodological trends that indicate the dominance of convolution-based spiking architectures, the critical role of encoding strategies in determining energy efficiency, and the task-dependent nature of SNN training approaches. Despite demonstrating performance comparable to conventional deep learning models, often at significantly reduced computational cost, SNN research remains challenged by inconsistent evaluation protocols, limited benchmark standardization, and restricted clinical validation. We conclude by outlining key open challenges and future research directions, emphasizing the need for standardized benchmarks, encoding-aware training, and hybrid ANN–SNN systems. As neuromorphic hardware and event-driven learning methods continue to mature, SNNs are well-positioned to introduce scalable, low-power physiological signal processing for next-generation intelligent healthcare systems. Full article