Regular physical exercise promotes overall and brain health and can improve cognition and mood. Similar effects on brain health have been observed after well-controlled intermittent exposures to low ambient oxygen (hypoxia), termed hypoxia conditioning, in several pilot studies. This raises the question of how exercising in hypoxia affects the brain. Among hypoxic exercise training forms are altitude training camps, which have been used systematically by athletes to improve physical performance for many decades, or exposure to simulated altitude/inspiratory hypoxia in laboratory settings, combined or not with exercise. Here, we explore the theoretical basis of overlaps and differences in brain health-related physiological responses to exercise and hypoxia. We present different types of altitude training undertaken by athletes, as well as hypoxia conditioning methods used to enhance physical performance and brain health and to reduce symptoms of neuropsychiatric diseases. We attempt to evaluate the potential of different altitude/hypoxia training types for brain health and indicate potential links to selected clinical applications of combined exercise and hypoxia. In conclusion, the effects of traditional types of altitude training on brain health and function have been poorly investigated, but various benefits of intermittent hypoxia conditioning have been demonstrated, indicating its potential for clinical applications in improving cognition and mental health. Remaining challenges include reducing the stigma surrounding the negative effects of severe hypoxia on the brain, standardizing terminology and approaches to therapeutic hypoxia, and selecting optimized protocols of therapeutic hypoxia exposures and combinations with exercise for specific general health-promoting or clinical applications.
Alzheimer's disease (AD) is the most common cause of dementia, representing a major global public health challenge as populations age. It accounts for roughly 60%-80% of all dementia and is characterized by progressive cognitive decline, memory impairment, and eventual loss of independence in daily functioning. The disease unfolds over decades, with neuropathological alterations preceding the onset of clinical symptoms by many years. Alzheimer's disease is closely linked to the accumulation and deposition of cerebral amyloid-β (Aβ) and represents the most common cerebral amyloid deposition disorder. Recent advances in molecular biology, neuroimaging, and biomarker science have revealed a complex, multifactorial pathogenesis involving protein misfolding, neuroinflammation, synaptic dysfunction, vascular factors, and network-level propagation of pathology. This review synthesizes current knowledge on AD terminology, epidemiology and risk factors, clinical phenotypes and natural history, pathophysiological mechanisms, diagnostic approaches (including imaging and fluid biomarkers), and established as well as emerging therapeutic strategies, while also outlining key challenges and future directions.
Parkinson's disease (PD) is a significant mental health condition, and patients greatly benefit from prompt diagnosis and treatment if the disease is identified early. One powerful method for diagnosing PD at an early stage is the analysis of hand-drawing and handwriting samples from individuals with PD. The novelty of this research lies in developing a handwriting and hand-drawing Parkinson's Disease (HwdPD) framework for detecting PD. This framework utilizes hand-drawing and Arabic handwriting samples, which have been observed to be effective in detecting PD. Based on VGG19 and transformer, the proposed framework was tested using a real standard dataset containing 63 hand-drawn images, namely spiral, wave, and ellipse samples, with 30 samples from PD and 33 from healthy patients. The dataset also contains Arabic handwriting samples, namely "eight" and hello ("لو"). These images were processed by using augmentation to enhance the performance of the HwdPD framework. This enhancement of the image area was fed to the classification algorithm (transformer ViT-B16 and VGG19). ViT-B16 scored high accuracy, with 100% in spiral, wave, and ellipse images. In handwriting samples ("eight"), the system successfully achieved a high percentage of 100%. This system emphasizes the potential to improve diagnostic accuracy and assist clinical decision-making by evaluating its performance on these datasets. The HwdPD framework demonstrates potential for identifying PD biomarkers, which may lead to improved diagnostics.
Migraine is a multifactorial disorder influenced by both genetic and environmental factors. In this study, we aimed to explore the association of tumor necrosis factor alpha (TNFa) rs1800629 with migraine susceptibility. A case-control study design was employed to assess this association in individuals of Greek ancestry. Subsequently, a meta-analysis of published studies was conducted, thereby incorporating the findings of the present study to further evaluate the relationship between rs1800629 and a migraine. A total of 123 patients with migraines (44.4 ± 10.3 years, 105 women) and an even number of healthy controls (HC) (58.7 ± 12.0 years, 76 women) were recruited. TNFa rs1800629 was in Hardy-Weinberg equilibrium among the HC (P = 1.00). No association was observed between TNFa rs1800629 and migraines under any genetic model. Additional, subgroup analyses stratified by sex and migraine subtype showed no associations. The meta-analysis, comprised of 14,742 participants with migraines and 46,384 HC, indicated a trend towards a risk-conferring effect of rs1800629 [Odds ratio (OR) = 1.26, 95% confidence interval (95% CI) = (0.97-1.64), P = 0.09]. Subgroup analyses revealed a significant association in individuals of Asian ancestry [OR = 1.64, 95% CI = (1.08-2.48), P = 0.02]. Additionally, the over-dominant model was related to migraines with aura [OR = 1.21, 95% CI = (1.08-1.35), P = 0.001]. Subgroup analyses for men and women, as well as for migraines without aura, were insignificant. This case-control study provides evidence that the TNFa rs1800629 polymorphism is not associated with migraine susceptibility in the Greek population. The updated meta-analysis showed that rs1800629 increases migraine risk in individuals of Asian ancestry. These findings support a population-specific genetic effect. Finally, the observed association with migraine with aura under the over-dominant model may indicate a heterozygote-driven effect. Given the extremely low frequency of homozygosity for the minor allele, this result should be interpreted with caution.
Electroencephalography (EEG) based cognitive state classification has been widely explored with deep-learning models demonstrating remarkable performance. Deep-learning models need high computational resources and large datasets, creating a need for an alternative methodology. Graph signal processing (GSP) techniques provide an effective lightweight alternative by capturing spatial dependencies across the channels. This study investigates the effectiveness of GSP-based graph Fourier transform (GFT) features on a publicly available EEG mental arithmetic task (EEGMAT) dataset. A strict 5-fold cross-validation has been used as an evaluation technique. GFT is applied to extract spatial-spectral features by modeling EEG-channels as graph nodes. The extracted features have been evaluated using multiple classifiers including Random Forest (RF), Extreme Gradient Boosting (XGB), Decision Tree (DT), and Logistic Regression (LR). Statistical analysis confirms the significance of GFT features compared to raw signals. RF gave the highest accuracy of approximately 99 percent. Model interpretability based on Shapley additive explanations (SHAP) revealed that the frontal and central regions contributed to the classification aligning with the findings of cognitive neuroscientists.
Schizophrenia spectrum disorders (SCZ) are a group of psychiatric disorders that can severely impact social and occupational functioning. Social cognition plays a key role in social functioning, with deficits in social cognition potentially revealing social deficits. However, existing tests of social cognition are lengthy to administer and only measure one or two aspects of social cognition. The Edinburgh Social Cognition Test (ESCoT) is a newly developed brief assessment that evaluates multiple domains of social cognition, including cognitive Theory of Mind (ToM), affective ToM, and interpersonal and intrapersonal understandings of social norms. However, the ESCoT has not been utilized before to examine social cognition in SCZ. This observational study analyzed 18 individuals with SCZ and 19 healthy controls (HC), all of whom completed the ESCoT and several social functioning scales, including the Lubben Social Network Scale (LSNS), the Pinkham Social Skill Rating (PSSR), the Role Function Scale (RFS), and the Social Disconnectedness Scale (SDS). Between-group comparisons revealed significantly reduced scores in the participants with SCZ on cognitive and affective ToM but comparable scores on interpersonal and intrapersonal understandings of social norms, compared to HC. Additionally, the participants with SCZ showed reduced scores on the LSNS, PSSR, RFS, and SDS. Furthermore, ESCoT-derived cognitive ToM scores were positively correlated with scores on the LSNS, PSSR, and SDS, whereas affective ToM scores were positively correlated with the LSNS and PSSR. Interpersonal understanding of social norms was positively correlated with the LSNS and RFS score. The current study showed deficits in cognitive and affective ToM alongside other aspects of social functioning in SCZ compared to HC participants. The ESCoT sub-scores were correlated with scores from validated questionnaires of social functioning, thus validating the utility of the ESCoT to study social cognition in SCZ. Further investigation is recommended to replicate these findings in larger and more heterogeneous samples of SCZ individuals for a better generalization of these findings.
Activity gradients measured with neuroimaging play a fundamental role in brain function, yet their relationship to the brain's internal predictive models during rest remains poorly understood. Clarifying this relationship can reveal how the brain processes information efficiently and adapts to a changing environment. Here, I discussed how energy flows may give rise to gradients of activity between voxels and to spatial coding in fMRI, and I described computational algorithms that can be applied directly to brain-activity images. I proposed that the brain continuously maintains and updates predictions about its environment through internal models, and that these models are embedded in the dynamic activity flows observed at rest and during cognitive tasks. This perspective emphasizes the role of energy turnover in supporting cognition: Neural circuits reflect predictions and adjustments shaped by past experience. I argue that the interplay between predictive processing and energy dynamics offers a richer account of cognitive mechanisms and points to new research directions in psychology and physiology. Together, these insights underscore the importance of energetic principles in brain physiology.
Background: The influence of moral identity on smoking behaviors remains an open question, particularly among youth prone to risk-taking and moral challenges. This study examined whether moral identity modulates late positive potential (LPP) responses during emotional-cognitive processing of smoking-related and non-smoking stimuli, while hypothesizing that attentional bias operates independently of individual moral identity differences. Methods: Seventy-eight participants (M = 22 years, SD = 2.1) completed an event-related potential (ERP) session in which the LPP activity was recorded while they viewed target stimuli (1 = smoking and 2 = non-smoking) and non-target stimuli (neutral images). Prior to the ERP task, the participants completed the Moral Identity Scale (validated Malay language version) and provided sociodemographic information. The LPP components were extracted and subsequently analyzed using a mixed-design analysis of variance (ANOVA) with stimulus type (target 1 and 2, non-target) as a within-subject factor and moral identity (internalization, symbolization) as a between-subject factor. Results: Strong main effects of visual stimuli on both the LPP amplitude and latency were revealed, thus indicating robust attentional engagement with emotionally and behaviorally relevant stimuli. No interaction effects with moral identity were observed, thus suggesting that attentional mechanisms function independently of moral self-construal. Post hoc comparisons showed a consistent attentional bias toward target versus neutral stimuli, with smoking versus non-smoking differences varying across cortical regions: amplitude effects in central and temporal areas, and latency effects in parietal and occipital areas. Conclusion: Smoking-related stimuli automatically capture attention irrespective of moral identity, thus highlighting the dissociation between moral self-construal and neural markers of emotional attention.
Berberine (BBR) possesses varied pharmacological properties, including anti-apoptotic and potent neuroprotective effects, and can ameliorate cognitive impairments associated with diverse diseases. Despite the noted potential of BBR in mitigating cognitive deficits associated with chronic cerebral hypoperfusion (CCH), the precise mechanisms underlying its therapeutic effects remain inadequately defined. To explore these mechanisms, a CCH rat model was developed using a refined micro-spring method for bilateral common carotid artery stenosis (BCAS). For the experimental setup, rats were systematically divided into six groups: a Sham group (n = 15), a Sham + BBR group (n = 15), a BCAS group (n = 15), a BCAS + BBR group (n = 15), a BCAS + BBR + Colivelin group (with Colivelin serving as a STAT3 activator, n = 15), and a BCAS + AG490 group (AG490 acting as a JAK2 inhibitor, n = 15). Cognitive performance was evaluated through the Morris water maze and novel object recognition (NOR) tests. Additionally, neuronal integrity was assessed by Nissl and TUNEL staining within the hippocampal region. The study further examined the protein expressions of JAK2, STAT3, phosphorylated JAK2, phosphorylated STAT3, and cleaved caspase-3 using western blot analysis. Interaction targets of BBR were predicted through the STITCH database, and its binding affinity to STAT3 was confirmed using molecular docking and surface plasmon resonance (SPR) techniques. The findings indicated an increase in apoptosis and a decline in cognitive abilities among the hippocampal neurons of the BCAS model rats. These deleterious effects, however, were substantially alleviated following treatment with BBR. The study posits that BBR primarily exerts its neuroprotective effects through the inhibition of the JAK2/STAT3 pathway. Notably, while the activation of this pathway by Colivelin exacerbated neuronal damage and cognitive decline, its inhibition via AG490 markedly decreased apoptosis and improved cognitive outcomes. Therefore, this research suggests that BBR enhances cognitive functions in BCAS rats predominantly by reducing apoptosis in hippocampal neurons through the modulation of the JAK2/STAT3 pathway.
Stingless bee honey (SBH), widely consumed in Southeast Asia, is traditionally valued for its medicinal and nutritional properties, particularly in promoting brain health. However, its neuroprotective potential against Alzheimer's disease (AD) remains underexplored. In this study, we investigated the therapeutic effects and safety of SBH in a rat model of AD. A total of sixty-three adult male Sprague-Dawley rats (180-200 g) were used: Fifteen were assigned to three toxicity groups (500, 750, 1000 mg/kg; n = 5) and forty-eight to six therapeutic groups (n = 8): Normal control, AD (AlCl₃ + D-gal), AD + Donepezil (1.5 mg/kg), and three SBH-treated groups (500, 750, 1000 mg/kg). Alzheimer-like pathology was induced by aluminium chloride (150 mg/kg) and D-galactose (300 mg/kg), followed by 14 days of treatment. Toxicity was evaluated through liver and kidney histopathology, while behavioural performance was assessed using the Open Field Test and Morris Water Maze. Serum dopamine, serotonin, corticosterone, and acetylcholinesterase activity were quantified via ELISA, and hippocampal morphology was examined histologically. SBH administration produced no signs of systemic toxicity and significantly improved exploratory activity and spatial learning, with the most pronounced effects at 750 mg/kg. Biochemical assays showed reduced acetylcholinesterase and corticosterone levels alongside increased dopamine and serotonin concentrations. Histological analysis confirmed neuronal preservation and reduced hippocampal damage. Inclusion of Donepezil as a positive control enabled comparison with a standard pharmacological treatment. These findings demonstrated that SBH is a safe and promising natural therapeutic capable of alleviating cognitive deficits associated with AD.
Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social interaction and repetitive behaviors. Increasing evidence suggests that endoplasmic reticulum (ER) stress contributes to abnormal brain development in ASD; however, whether prenatal modulation of ER stress can prevent ASD-like phenotypes remains unclear. In this study, we investigated the effects of prenatal administration of the chemical chaperone 4-phenylbutyric acid (4-PBA) in two etiologically distinct ASD mouse models: valproic acid (VPA)-exposed Jcl:ICR (ICR) mice and BTBR T+ Itpr3tf/J (BTBR) mice. Social behaviors were evaluated using the three-chamber test, and repetitive behaviors were assessed by self-grooming duration. 4-PBA was administered to mid-gestation mice, and behavioral changes in the male offspring derived-two type ASD model (VPA and BTBR mice) were evaluated. 4-PBA reduced ER stress in the cerebral cortex of the offspring male VPA and BTBR mice. In particular, 4-PBA strongly inhibited the expression of 94-kDa glucose-regulated protein, an ER stress marker, in BTBR male mice. In addition, 4-PBA improved synaptic organizer expression and neuronal maturation, which are diminished in ASD, specifically in the cerebral cortex of VPA mice. Furthermore, 4-PBA improved social reciprocity, a behavior specific to ASD in male VPA and BTBR mice. In conclusion, ER stress during mid-pregnancy is strongly associated with the development of ASD symptoms. Furthermore, the reduction in ER stress by 4-PBA leads to the suppression of ASD symptoms. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by a lack of sociality, and the difficulty in forming social relationships often leads to various social problems. Prenatal administration of 4-PBA to mothers may reduce the risk of developing ASD, and we believe this could be a new approach to prevention.
Applying transcranial alternating current stimulation (tACS) at the gamma range to the frontal and parietal regions can improve cognitive dysfunctions. This study aimed to explore the neural changes following tACS. Electroencephalography (EEG) recordings were obtained from a cohort of 34 participants with various cognitive impairments before and after 11 sessions of 40 Hz tACS treatment. Alternating currents at 2.0 mA were administered to the electrode positions F3 and P3 for 25 min of each session, following the 10-20 EEG convention. Using eLORETA, scalp-recorded signals were reconstructed into cortical current source density (CSD). We then assessed the differences in power and connectivity strength across multiple spectra. We observed a consistent trend of decreased CSD at the stimulating sites across different spectra, most prominent at beta and gamma bands (P < 0.01). On the contrary, the right hemisphere showed a trend of increased CSD, which was likely mediated by inter-hemispheric rivalry. In addition, the connectivity strength between the left frontal and parietal regions increased significantly (P = 0.017). Application of tACS would desynchronize regional oscillation and enhance inter-regional crosstalk. The pattern of neural changes was concordant with our previous tACS reports (5 Hz), suggesting common neural mechanisms driving the neurophysiological effects of tACS.
Carnosine (β-alanyl-L-histidine) is an endogenous dipeptide widely distributed in mammalian tissues, especially skeletal and cardiac muscle cells, and, to a lesser extent, in the brain. While early interest in carnosine was given because of its role in muscle cell metabolism and athletic performance, it has more recently gained attention for its potential application in several chronic diseases. Specifically, brain aging and neurodegenerative disorders have received particular attention, as a marked reduction in carnosine levels has been described in these conditions. Carnosine exerts a wide range of biological activities, including antioxidant, anti-inflammatory, anti-glycation, metal-chelating, and neuroprotective properties. Mechanistically, it acts by inhibiting the production of advanced glycation end products (AGEs), buffering cellular pH, and regulating intracellular nitric oxide signaling and mitochondrial function. Its safety profile, the lack of toxicity, and significant side effects support its application for long-term therapeutic use. In this review, we aim to recapitulate and discuss the effects, dosages, and administration routes of carnosine in preclinical in vivo models, with a particular focus on neurodegenerative disorders where it has been shown to reduce oxidative stress, suppress neuroinflammation, modulate protein aggregation, and preserve cognitive function, all key features of neurodegeneration. Despite promising findings, there are gaps in the knowledge on how carnosine affects synaptic plasticity, neuronal remodeling, and other processes that play a central role in the pathophysiology of neurodegenerative disorders. Additionally, clinical translation remains challenging due to inconsistencies across in vivo studies in terms of dosage, treatment duration, routes of administration, and disease models, which affect reproducibility and cross-study comparability. Therefore, while carnosine emerges as a multifunctional and well-tolerated molecule, further research is needed to clarify its therapeutic relevance in human diseases. In this review, we also address future perspectives and key methodological challenges that must be overcome to effectively translate carnosine's biological potential into clinical practice.
Multiple sclerosis (MS) is a chronic disease of the central nervous system (CNS) affecting young adults, particularly in North America and Europe, with nearly 2.5 million individuals impacted globally. Characterized by demyelination and neuronal damage, MS involves complex immune-mediated mechanisms. In this review, we focused on the pathophysiological processes of MS, highlighting the roles of T cells, B cells, and proinflammatory cytokines in driving demyelination, which are often the main focus of treatments in the form of immunotherapy. We emphasized remyelination as a key therapeutic target that is necessary for protecting axons and restoring neural function to solve the root problem. Emerging therapies, such as high-dose supplementation with vitamin D and glutathione, appear effective in regulating immune activity and lowering oxidative burden, thus supporting remyelination and neuroprotection. Preclinical models using toxin-induced demyelination have provided valuable insights into the mechanisms of remyelination and identified potential therapeutic targets like LINGO-1 antagonists. Clinical trials, particularly those involving the anti-LINGO-1 monoclonal antibody BIIB033, have demonstrated encouraging results in enhancing remyelination and improving clinical outcomes. LINGO-1 is an inhibitory protein that impairs OPC differentiation. Integrating these innovative approaches into clinical practice could revolutionize MS management by shifting the focus from managing symptoms to promoting CNS repair and long-term recovery. Continued research into the molecular mechanisms of remyelination and the development of targeted therapies is essential for advancing MS treatment and improving the quality of life for patients.
Background:Alzheimer's disease (AD) and mild cognitive impairment (MCI) are widely recognized for their hallmark cognitive deficits, typically characterized by progressive cognitive deterioration. However, neuropsychiatric symptoms (NPS), including depression, apathy, anxiety, irritability, and sleep disturbances, are increasingly prevalent in the early stages of these conditions and significantly influence the disease trajectory and patient outcomes. Importantly, neuropsychiatric symptoms often precede overt memory loss by several years, with subtle mood and behavioral disturbances serving as early pre-diagnostic markers of an underlying Alzheimer's pathology. Their presence complicates the diagnosis, accelerates the disease progression, and intensifies the caregiver burden. However, distinguishing NPS arising from neurodegeneration and primary psychiatric disorders remains a profound diagnostic challenge, thus delaying timely intervention and obscuring early disease recognition. Objective:This structured narrative review examines the diagnostic complexities, clinical impact, and current management of NPS in early-stage Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI), alongside the biological underpinnings, clinical relevance, diagnostic challenges, and treatment perspectives. We argue that understanding and managing NPS is essential to improve the clinical outcomes, reduce the caregiver burden, and guide therapeutic innovation. Methods:A structured narrative review of peer-reviewed studies published between 2012 and 2025 was conducted using PubMed, MEDLINE, Scopus, PsycINFO, Google Scholar, and CINAHL. The included studies investigated NPS prevalence, neurobiological correlations, and management strategies in individuals with AD or MCI. Findings:NPS affects up to 80% of individuals with early AD or MCI, often preceding cognitive decline. The current management strategies heavily rely on non-pharmacological interventions such as caregiver support, behavioral activation, and structured routines, while pharmacological options remain limited by modest efficacy and safety concerns. Discussion:Advancing knowledge of NPS and their association with cognitive decline is critical to establish more precise diagnostic criteria and to inform personalized therapeutic approaches. Future research should emphasize biomarker-driven diagnostics and the development of novel, targeted interventions that simultaneously address cognitive and neuropsychiatric domains to optimize outcomes for patients and caregivers. This study contributes to the field by reframing NPS as potential early biomarkers in the trajectory of MCI and dementia progression.
When becoming a parent, caregivers undergo complex, and sometimes permanent, neurobiological alterations, and this area of neurobiology has been extensively studied for decades. Due to ethical concerns and experimental limitations, the first parental neurobiology experiments were exclusively performed using rodent animal model systems, such as mice, rats, and voles. More recent technological advancements, such as the functional MRI (fMRI) scan, have become widely adopted and led to great insight into the impact of parenting on human neurobiology. In this thematic literature review, we present key studies that provide insight into the relationship of pregnancy and parturition on maternal caregiving behavior and the relationship of postpartum on all parents. First, we examine the relationship of endocrine hormones such as estrogen, progesterone, oxytocin, and testosterone with the neurobiological development of a parent. Next, we describe the significant transformation of subcortical maternal circuit components that occur during pregnancy, and the changes in the volume of grey and white matter generated during the postpartum. These brain structure alterations contribute to the development of parental nurturing behaviors.
Computational modeling of excitatory/inhibitory (E/I) balance offers transformative insights into the neurobiological underpinnings of autism spectrum disorder (ASD). In this review, we examined the integration of neurotransmitter dynamics and genetic factors into multiscale computational frameworks to elucidate the mechanisms driving E/I dysregulation in ASD. We explored the pivotal roles of glutamate and GABA, the primary excitatory and inhibitory neurotransmitters, and the modulatory impact of serotonin and dopamine (DA), in shaping neural circuit stability, behavioral outcomes, and ASD core symptoms. Genetic mutations affecting synaptic proteins such as SHANK3, GRIN2A, and GABRB3 were highlighted for their capacity to disturb synaptic scaffolding and glutamatergic and GABAergic signaling, thereby shifting the E/I ratio. Computational approaches, ranging from detailed neuronal simulations to neural mass and spiking network models, captured the heterogeneous manifestations of E/I imbalance and aligned with molecular, neuroimaging, and electrophysiological findings in ASD. We discussed how these models informed individualized diagnostic strategies, enabled prediction of treatment responses, and offered targets for precision medicine. Major challenges included methodological inconsistencies, neurochemical measurement discrepancies, polygenic interactions, and the translation of model predictions into clinical practice. We concluded that the integration of neurotransmitter and genetic data within advanced computational models represents a significant advance toward unraveling ASD pathophysiology, with the promise of developing dynamic, personalized interventions. Ongoing efforts should emphasize longitudinal data, multiomic integration, sex-specific trajectories, and cross-disciplinary collaboration to further the clinical applicability and translational potential of computational E/I balance modeling in autism research.
Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammation, demyelination, and neurodegeneration within the central nervous system (CNS). It predominantly affects women and young adults, with environmental and genetic factors contributing to its onset. MS presents a wide range of neurological symptoms due to the scattering of lesions in the CNS, often leading to vision, sensorimotor, and cognitive impairments. The clinical course of MS varies, with relapsing-remitting MS (RRMS) being the most common, followed by secondary progressive MS (SPMS) and primary progressive MS (PPMS). Diagnosis is based on clinical evaluation, MRI findings, and cerebrospinal fluid analysis, with the McDonald criteria playing a key role in confirming dissemination in time and space. Current treatments, such as disease-modifying therapies (DMTs) and steroids, focus on managing relapses and reducing long-term disability. Novel therapies, including remyelination and neuroprotective agents, are showing promise in advancing care. While these medications can slow progression and improve quality of life, MS remains an incurable disease that requires ongoing research to find more effective therapies. Surgical interventions are rare but can address severe symptoms like spasticity and bladder dysfunction, contributing to an overall personalized management approach.
