Search Results (2,805)

Raynaud’s Phenomenon (RP) serves as the clinical sentinel for systemic autoimmunity, frequently predating connective tissue disease diagnosis by years. While RP is a largely benign functional vasospasm in the general population, its prevalence in Systemic Sclerosis (SSc) approaches 99%. A fundamental mystery in Rheumatology is the divergent fate of the microvasculature across connective tissue diseases. RP can occur in other autoimmune diseases; it is usually not associated with the relentless transition to obliterative vasculopathy. In SSc, the vessel lumen is physically occluded by intimal proliferation and perivascular fibrosis, yet the mechanism triggering this ischemia remains poorly understood. Beyond the classic tri-phasic color change, SSc patients frequently report other early distressing sensory symptoms, specifically intense pruritus, neuropathic burning, and profound edema. Historically dismissed as secondary to ischemia, we propose that these sensations are primary markers of the underlying pathological driver. We challenge the traditional B-cell/T-cell-centric view of SSc by introducing the concept of autoallergy. We hypothesize that these sensory symptoms represent chronic, IgE-mediated activation of resident mast cells. This mast cell-driven circuit, triggered by SSc-specific autoantigens, acts as a persistent secretory pump for pro-fibrotic cytokines, fundamentally distinguishing SSc vasculopathy from the purely inflammatory vascular patterns seen in other connective tissue diseases. Targeting the IgE–mast cell axis early in the course of the disease may offer a novel therapeutic window to halt the transition from functional vasospasm to permanent structural obliteration. Full article

Background: Multiple sclerosis (MS) is a chronic inflammatory, autoimmune, and neurodegenerative disease of the central nervous system. Our study aimed to examine the relationship between serum iron levels and the following clinical parameters: depression, anxiety, fatigue, neuropathic pain, and disease activity on magnetic resonance imaging in patients with relapsing-remitting multiple sclerosis (RRMS). Material and methods: This study was designed as a clinical observational, cross-sectional study. This study was conducted at the Clinic of Neurology of the University Clinical Center Kragujevac, from 2022 to 2024, according to the ethical code of the Declaration of Helsinki. Demographic and clinical data on patients were obtained from the medical history. All MS patients were diagnosed according to the McDonald criteria (2017). This study included 65 patients in the experimental group and 11 healthy individuals in the control group, with an average age of 39.68 years. Serum iron levels were biochemically analyzed from venous blood. The following standardized tests were used to collect data on depression, anxiety, fatigue, and neuropathic pain: Beck Depression Inventory (BDI), Hamilton Anxiety Rating Scale (HAM-A), Modified Fatigue Impact Scale (MFIS), PainDETECT Questionnaire (PD-Q), and Visual Analogue Scale (VAS). Results: Serum iron level significantly correlates with disease activity on magnetic resonance imaging in patients with multiple sclerosis. Serum iron showed a moderate positive correlation with hemoglobin, hematocrit, total and direct bilirubin, and a weak positive correlation with uric acid, while a moderate negative correlation was observed with erythrocyte sedimentation rate. No statistically significant difference was found between serum iron levels and depression, anxiety, fatigue, and severity of neuropathic pain. The ROC curves show the diagnostic potential of the combined parameters in differentiating RRMS from controls, as well as the potential of iron in differentiating active from inactive MS. The presence of disease, hemoglobin and total bilirubin were recorded as significant independent predictors. Conclusion: This study is a descriptive attempt to present the potential role of iron in the radiological activity of the disease. High serum iron level may be associated with radiological disease activity in patients with multiple sclerosis. Full article

Neuroinflammation is a complex process involved in the pathogenesis of several neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, Huntington’s disease, and amyotrophic lateral sclerosis. Neutrophils, although traditionally considered peripheral immune cells, have emerged as active participants in the immunopathology of the central nervous system (CNS) through the release of neutrophil extracellular traps (NETs), structures composed of decondensed chromatin embedded with pro-inflammatory proteins. Evidence suggests that NETs play a dual role: they are protective against pathogens but can also induce tissue damage when produced in excess. Several pathways are involved in their formation, including vesicle-mediated release (vital NETs), the lytic NADPH oxidase (NOX)-dependent pathway, and the mitochondrial pathway. Targeting NETs therapeutically, through the use of NETosis inhibitors, NET-degrading strategies, or blockade of neutrophil migration, has shown promise in reducing neuroinflammation/neurodegeneration and improving neurological outcomes in experimental models. This review aims to investigate both the protective and deleterious roles of NETs and how this knowledge may reveal new therapeutic strategies to modulate neurodegenerative diseases and preserve neural integrity, offering valuable insights for potential applications in clinical practice. Full article

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by immune-mediated demyelination and neurodegeneration. Although the exact cause of MS remains unclear, accumulating epidemiological and immunological evidence strongly implicates Epstein–Barr virus (EBV) infection as a major environmental factor associated with disease development. Nearly all individuals with MS are EBV seropositive, and longitudinal studies have demonstrated that EBV infection precedes MS onset, supporting a causal relationship. EBV establishes lifelong latency in B cells and can profoundly influence host immune responses, providing several potential mechanisms through which it may contribute to autoimmunity. In this review, we summarize current knowledge of EBV biology and discuss epidemiological findings linking EBV infection with MS risk. We then examine alterations in EBV-specific immune responses observed in MS, including dysregulated humoral and cellular immunity. Particular attention is given to molecular mimicry involving the Epstein–Barr nuclear antigen 1 (EBNA1) and central nervous system proteins, which may promote cross-reactive autoimmune responses. Finally, we discuss evidence for the presence and potential role of EBV-infected immune cells within the MS brain and highlight key unanswered questions that remain critical for understanding EBV-driven neuroinflammation. Full article

Cannabis sativa contains more than 120 phytocannabinoids, with Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD) being the best characterized. This review synthesizes preclinical and clinical evidence on hemp-derived extracts, cannabinoids, and active compounds. THC primarily acts as a partial agonist at cannabinoid receptor type 1 (CB1) and type 2 (CB2), producing psychoactive, appetite-stimulating, antiemetic, and analgesic effects. CBD is non-intoxicating and has a multimodal profile involving CB1 negative allosteric modulation, CB2 inverse agonism or antagonism, inhibition of anandamide inactivation, and activity at 5-HT1A receptors, transient receptor potential channels, GPR55, and peroxisome proliferator-activated receptor gamma. Preclinical models of Parkinson’s disease, Alzheimer’s disease, Huntington’s disease, epilepsy, and pain support anti-inflammatory, antioxidant, anti-excitotoxic, and glial-modulating mechanisms, but clinical translation remains uneven. The strongest evidence supports FDA-approved cannabidiol for Lennox–Gastaut syndrome, Dravet syndrome, and tuberous sclerosis complex, and THC-based agents for refractory chemotherapy-induced nausea and vomiting and AIDS-related anorexia. Moderate-certainty evidence supports nabiximols for multiple sclerosis spasticity and small benefits in selected chronic neuropathic pain populations. Evidence remains insufficient or negative for acute pain, insomnia, most psychiatric disorders, and many promoted indications. Key risks include cannabis use disorder, cognitive and psychiatric effects, cardiovascular events, sedation, high-dose CBD hepatotoxicity, and drug interactions. Rigorous, long-term, product-standardized trials are needed. Full article

Interstitial lung diseases (ILDs) comprise a heterogeneous group of pulmonary disorders associated with substantial morbidity and mortality. We examined mortality attributed to selected J84-coded ILDs in the United States from 1999 to 2024 using CDC WONDER underlying-cause-of-death data. Age-adjusted mortality rates (AAMRs) per 100,000 population were standardized to the 2000 U.S. population and stratified by sex and race. Joinpoint regression was used to identify changes in temporal slope and estimate annual percent change (APC), average annual percent change (AAPC), 95% confidence intervals (CIs), and p-values. After the removal of overlapping years between the CDC WONDER database series, 444,573 unique deaths occurred. Annual deaths increased from 11,358 in 1999 to 22,849 in 2024, while AAMR increased from 4.2 to 5.1 per 100,000. Overall, AAMR increased during 1999–2004 (APC 2.32%, 95% CI 1.39–3.26; p < 0.001) and more slowly during 2004–2024 (APC 0.36%, 95% CI 0.16–0.56; p = 0.001), with an overall AAPC of 0.75% (95% CI 0.60–0.90; p < 0.001). Male AAMRs remained higher than female AAMRs, while race-specific trends were heterogeneous. No temporal reduction in population mortality coincided with the introduction of antifibrotic therapies; however, this ecological analysis cannot evaluate treatment effectiveness or individual treatment exposure. Full article

Background: Multiple sclerosis and periodontal disease are chronic inflammatory conditions that may share immune-mediated mechanisms, including cytokine activation, oral dysbiosis, oxidative stress, and systemic inflammatory burden. This systematic review aimed to synthesize recent evidence on common inflammatory pathways linking periodontal disease and multiple sclerosis. Methods: The review was conducted according to PRISMA 2020 guidelines. PubMed/MEDLINE, Cochrane Library, and Scopus were searched for English-language studies published between June 2020 and June 2026. Eligible studies addressed multiple sclerosis, periodontal disease, oral microbiome alterations, systemic inflammation, or neuroinflammatory outcomes. Study selection and data extraction were performed independently by three reviewers. Risk of bias was assessed using AMSTAR 2, the Newcastle–Ottawa Scale, and the Joanna Briggs Institute checklist, according to study design. Results: Seventeen studies were included in the qualitative synthesis. The main shared mechanisms were cytokine-mediated inflammation involving TNF-α, IL-1β, IL-6, and IL-17; NF-κB signaling; Th17/Treg imbalance; blood–brain barrier disruption; oxidative stress; matrix metalloproteinase activity; complement activation; and oral–gut–brain axis dysregulation. The evidence suggests that periodontal inflammation may contribute to systemic immune activation and may amplify neuroinflammatory processes in multiple sclerosis. Conclusions: Current evidence supports a biologically possible association between periodontal disease and multiple sclerosis through shared inflammatory and microbial pathways. However, causality remains unproven, and further longitudinal and interventional studies are needed. Full article

Autoimmune diseases substantially increase the risk of atrial and ventricular arrhythmias and sudden cardiac death through shared immune-mediated mechanisms. Pro-inflammatory cytokines, autoantibodies, and progressive myocardial fibrosis disrupt ion channel function, impair conduction, and create re-entrant substrates. Across systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and systemic sclerosis (SSc), these pathways manifest as atrial fibrillation, ventricular arrhythmias, conduction disease, and heightened arrhythmic mortality. Anti Ro/SSA antibodies, in particular, contribute to QT prolongation and atrioventricular (AV) block, while cytokines such as TNF α, IL 1β, and IL 6 remodel electrophysiological properties and promote fibrosis. Advanced cardiac imaging, especially cardiac magnetic resonance (CMR), detects inflammation and fibrosis even when ejection fraction is preserved, enabling earlier intervention. Management requires a dual approach: standard arrhythmia therapies alongside aggressive control of systemic inflammation with disease-specific immunosuppression. Despite growing evidence, major gaps remain, including the absence of randomized trials targeting immune-driven arrhythmias and the need for integrated risk models incorporating inflammatory biomarkers. Full article

Background: Physical activity plays a vital role in caring for people with multiple sclerosis (MS). Yet, challenges like fatigue, mobility impairment, fall risk, symptom fluctuation, and poor access to rehabilitation often make sustained participation difficult. Adhering to physical activity programmes is tough. Artificial intelligence (AI) may transform wearable, smartphone, clinical, and patient-reported data into interpretable information for monitoring, prediction and individualized support. Objective: Building on the identified need for individualized support, this scoping review mapped original AI-based studies relevant to physical activity, gait, mobility, ambulation, fatigue, fall risk, and real-world functioning in people with MS. Methods: The review followed PRISMA-ScR principles. Search covered records published from 1 January 2016 to 14 May 2026 across biomedical, rehabilitation, technology-oriented, trial registry, and citation-searching sources. Eligible studies included MS or MS-specific data, an explicit AI/ML or model-derived predictive analytics component, and an activity-related clinical domain. Results: The search identified 332 records/reports. After removing 127 duplicates, 205 records were screened, 45 full texts were assessed, and 21 original AI studies met the eligibility criteria. These addressed inertial sensor deep learning, wearable gait speed estimation, postural sway fall risk prediction, connected device prediction of fatigue and health state, smartphone-based ambulation characterization, treadmill or walkway gait classification, chair stand fall status prediction, daily life gait/turning fall prediction, fear-of-falling detection, sensor-derived fatigue prediction, mobile/wearable modelling of MS, and physical activity prediction. Conclusions: AI can extract clinically relevant patterns from gait, wearable, smartphone, connected device, clinical, and patient-reported data in MS. However, evidence does not yet show that AI-supported systems improve physical activity, adherence, fatigue burden, fall risk, quality of life, or functional independence. AI is therefore promising but early, and prospective, externally validated, human-supervised, fatigue-aware, safety-sensitive studies are needed to support clinically meaningful, patient-centred MS rehabilitation and activity planning. Full article

Access to neurological care remains profoundly unequal worldwide, driven by the increasing burden of chronic and neurodegenerative disorders and a persistent shortage of specialist neurologists. Tele-neurology has emerged as a promising strategy to improve access to neurological expertise, while recent advances in artificial intelligence (AI) have expanded its capabilities beyond remote consultation toward data-driven diagnosis, monitoring, and clinical decision support. This narrative review critically synthesizes current evidence on the evolution of tele-neurology and the emerging role of AI across multiple domains of neurological care. The review examines AI-enhanced diagnostic applications, including neuroimaging, electroencephalography, and digital biomarkers, as well as AI-assisted remote monitoring, patient engagement, and predictive analytics in disorders such as stroke, epilepsy, Parkinson’s disease, multiple sclerosis, dementia, headache disorders, and neuromuscular diseases. Available evidence suggests that tele-neurology can achieve clinical outcomes comparable to in-person care in selected settings while improving accessibility, continuity of care, and patient satisfaction. AI applications have shown promising early results in image interpretation, automated EEG analysis, remote disease monitoring, and individualized risk prediction. Despite these advances, important challenges remain. Limitations include constraints in remote neurological examination, evidence gaps regarding clinical validation, unequal access to digital infrastructure, data governance and cybersecurity concerns, fragmented regulatory frameworks, and difficulties integrating AI into routine clinical workflows. Furthermore, the clinical maturity of AI applications varies substantially, with many systems remaining at the proof-of-concept or early validation stage. To make this variation explicit, we introduce a transparent, criteria-based three-tier classification of the clinical practicability of AI applications, graded by strength of evidence, degree of validation, and real-world integration. Tele-neurology is increasingly evolving toward hybrid models that combine in-person neurological assessment with digitally enabled longitudinal monitoring and AI-supported decision tools. Future progress will depend on rigorous clinical validation, equitable implementation strategies, integration into healthcare systems, and the development of multimodal AI approaches that combine clinical, imaging, electrophysiological, and digital biomarker data to support personalized neurological care. Full article

Background: Multiple sclerosis (MS) is a neurodegenerative and chronic inflammatory disease, often associated with psychiatric comorbidities, particularly depression and anxiety, which play a major role in disability, cognitive dysfunction, and quality of life. Growing evidence suggests that affective symptoms in MS are not only related to psychosocial burden but also to structural and functional abnormalities in the brain that can be identified using magnetic resonance imaging (MRI). Methods: A systematic database search was performed to identify studies for a structured narrative review. Original articles that examined MRI correlates of depression and anxiety in adult MS patients were included. Structural MRI, diffusion imaging, and functional MRI studies evaluating lesion distribution, cortical and subcortical atrophy, white matter microstructure, and network connectivity were analyzed alongside psychometric instruments used to assess affective symptoms. Results: Depression in MS was consistently associated with fronto-limbic and subcortical abnormalities including cortical thinning, hippocampal and thalamic atrophy, white matter disconnection and altered connectivity within the default mode, salience and executive control networks. Diffusion MRI studies have shown microstructural damage in associative white matter tracts, and functional MRI studies have supported a model of network-level dysfunction. In contrast, anxiety had less robust and reproducible associations with conventional MRI findings, indicating a more complex interaction between inflammatory, neurobiological and psychosocial mechanisms. Conclusions: Multimodal MRI approaches may increase our knowledge of the neurobiological substrates of depression and anxiety in MS and may contribute to more personalized diagnostic and therapeutic strategies. Full article

Neurodegenerative diseases represent a major and growing global health burden. Although these disorders are often clinically defined by symptoms and affected brain regions, many are mechanistically linked to abnormal protein accumulation, misfolding, impaired proteostasis, RNA dysregulation, mitochondrial dysfunction, and neuroinflammation. In this Perspective article, I discuss major neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, multiple system atrophy, amyotrophic lateral sclerosis, frontotemporal dementia, Huntington’s disease, prion diseases, spinocerebellar ataxias, and spinal muscular atrophy, through the lens of disease-associated proteins and experimental modeling. I argue that a protein-centered framework provides a useful approach for understanding disease mechanisms and selecting transgenic mouse models, while recognizing that aging, cellular context, neuroinflammation, mitochondrial dysfunction, vascular dysfunction, and other disease modifiers also shape neurodegeneration. Transgenic and genetically engineered mouse models have been essential for dissecting the pathogenic roles of amyloid-β, tau, α-synuclein, TDP-43, SOD1, FUS, C9ORF72-associated dipeptide repeat proteins, mutant huntingtin, prion protein, ataxins, and SMN deficiency. However, these models have important limitations, including artificial overexpression, familial mutation bias, species differences, and incomplete representation of aging-related sporadic diseases. Rather than seeking a single “best” model, a more productive strategy is to adopt model portfolios tailored to specific biological questions and to integrate mouse studies with human cellular models, postmortem tissue, omics approaches, and biomarker-based validation. Such an approach may improve mechanistic insight, strengthen translational relevance, and enhance the predictive value of preclinical neurodegenerative disease research. Full article

Background/Objectives: Pulmonary arterial hypertension (PAH) occurs in >12% of systemic sclerosis (SSc) patients and has a high mortality. Annual screening for all SSc patients is the standard of care and can include spirometry (RFT), serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) and echocardiography (TTE). We sought to evaluate the accuracy of NT-proBNP alone to screen for SSc-PAH. Methods: We defined groups as low, intermediate and high risk of PAH according to RFT, TTE and RHC (right heart catheter) parameters. NT-proBNP thresholds predictive of risk group were defined, and ROC curves were used to evaluate the predictive accuracy of the calculated cut-points to diagnose SSc-PAH within the following 12 months. Results: A total of 820 SSc patients had NT-proBNP recorded 12 months prior to RHC, or if no RHC had been performed, within 12 months of the most recently recorded annual visit. The majority (335, 40.85%) were assigned to low risk of PAH, 189 (23.05%) to intermediate risk and 176 (21.46%) to high risk. NT-proBNP level < 122.9 ng/L defined the low-risk group, 122.9–186.6 ng/L defined the intermediate risk and >186.6 ng/L defined the high risk. NT-proBNP ≥210 ng/L with RFT (the ‘ASIG algorithm’) had the highest predictive accuracy, with sensitivity of 86.75% (77.52–93.19%), specificity of 60.71% (58.52–62.87%), PPV of 8.47% (6.69–10.55%), NPV of 99.09% (98.38–99.55%) and AUC of 0.74 (0.70–0.78). NT-proBNP ≥ 210 ng/L alone had sensitivity of 67.05% (56.21–76.70), specificity of 71.91% (70.03–73.72), PPV of 8.25% (6.34–10.52), NPV of 98.30% (97.57–98.86) and AUC of 0.69 (0.64–0.74). NT-proBNP thresholds associated with the three defined risk groups performed similarly overall. Conclusions: NT-proBNP alone, compared to the ASIG algorithm, had a slight reduction in NPV and AUC to predict PAH within 12 months. When NT-proBNP is ≥210 ng/L, the NPV remains high (98.0%). Full article

Background: The latest revision of the McDonald criteria for diagnosis of multiple sclerosis (MS) establishes that the optic nerve can serve as a fifth anatomical location within the central nervous system for diagnosis. Optical coherence tomography (OCT) images can serve as evidence for this purpose. Objective: To assess the accuracy of automated artificial-intelligence-based classification of MS patients using OCT data obtained from two different centers. Methods: OCT data were collected from two centers using standardized APOSTEL-based protocols and similar equipment. Retinal layer thicknesses—mean and standard deviation (STD) values—were analyzed in four layers and in six regions per layer per eye. A support vector machine classifier with recursive feature elimination and Shapley additive explanations value analysis was applied to identify the most relevant features and maximize classification accuracy between control subject and MS patient eyes. Results: The database drawn from two hospitals comprised 112 eyes with MS without prior history of optic neuritis and 193 eyes of control subjects. The classifier achieved maximum accuracy (0.8459) using 20 input features. The mean and STD metrics had similar importance, with the most influential layers being the ganglion cell layer, inner plexiform layer, and the inner retinal layer complex. Key regions included the papillomacular bundle and the superior temporal perimacular area. Conclusions: OCT data facilitates highly accurate MS diagnosis across different centers. Artificial intelligence assessment could facilitate automated classification. These findings provide evidence of the important role of the optic nerve in MS diagnosis. Full article

Background: Amyotrophic lateral sclerosis (ALS) is increasingly recognized as a multisystem disorder involving neurovascular dysfunction. The retina allows in vivo assessment of neurovascular changes. This study evaluated retinal structural and microvascular alterations in ALS using optical coherence tomography (OCT) and optical coherence tomography angiography (OCT-A). Methods: This cross-sectional study included 46 participants with ALS and 19 healthy controls. Retinal thickness and vascular density in the superficial and deep retinal capillary plexuses and the choriocapillaris were quantified using OCT and OCT-A. Group comparisons and logistic regression analyses were performed to assess associations with ALS. Subgroup analyses were conducted according to clinical phenotype. Results: In total, 124 eyes were analyzed. ALS was associated with increased average retinal thickness (p = 0.023) and reduced vascular density in the superficial retinal capillary plexus (p = 0.005), deep retinal capillary plexus (p < 0.001), and choriocapillaris (p = 0.004). In logistic regression analyses, retinal thickness was positively associated with ALS status (OR = 1.42, p = 0.023), whereas higher vascular density in the superficial plexus, deep plexus, and choriocapillaris was associated with lower odds of ALS. No significant differences were observed between bulbar- and spinal-onset ALS phenotypes. Conclusions: ALS is associated with structural and microvascular retinal alterations detectable by OCT and OCT-A. These findings support the presence of systemic neurovascular dysfunction and highlight retinal imaging as a promising, non-invasive approach for investigating disease mechanisms and developing potential biomarkers. Full article