Search Results (406)

Background/Objectives: Mild cognitive impairment (MCI), the prodromal stage of Alzheimer’s disease, may be influenced by nutritional status and genetic susceptibility. This systematic review synthesised evidence on how nutritional biomarkers interact with genetic variants, particularly APOE ε4, to influence cognitive outcomes in individuals with MCI. Methods: Following PRISMA 2020 guidelines, seven studies were included (three longitudinal, two randomised controlled trials, and two cross-sectional) involving adults aged ≥55 years with MCI. Nutritional exposures comprised plasma or serum concentrations of vitamins A, D, E, the vitamin B group, lipids, selenium, and ketogenic medium-chain triglycerides. Genetic risk was assessed primarily through APOE ε4 status. Risk of bias was assessed using RoB 2 and ROBINS-I, and certainty of evidence using GRADE. Due to heterogeneity in biomarkers, cognitive tools, and study designs, findings were synthesised narratively. Results: Across nutrient categories, higher concentrations of vitamin D, selenium, and antioxidants were associated with better cognitive outcomes. kMCT supplementation improved episodic memory and brain energy metabolism. Evidence for nutrient–gene interactions was mixed: APOE ε4 modified responses to vitamin B group and selenium but showed limited influence on vitamin D, lipids, or kMCT effects. Heterogeneity in biomarker assays, cognitive tools, and genetic stratification limited comparability across studies. Conclusions: Nutritional biomarkers appear to influence cognitive trajectories in MCI, and some associations may differ by APOE ε4 status. However, small samples and limited genetic stratification constrain interpretation. Future research should prioritise standardised biomarker measurement, genetically stratified cohorts, and individual participant data meta-analyses to clarify nutrient–gene interactions in MCI. Full article

Alzheimer’s disease is a complex neurodegenerative condition characterized by progressive cognitive decline, neuroinflammation, metabolic dysregulation, and abnormal protein deposition. While genetic factors and amyloid-beta-focused hypotheses have been extensively investigated, they fail to fully account for the prolonged prodromal phase or the early susceptibility of olfactory and limbic regions. Emerging evidence suggests chronic peripheral and mucosal infections may influence disease risk; however, mechanisms by which microbial activity outside the central nervous system contributes to persistent neuropathology remain poorly understood. This review explores the emerging concept that bacterial outer membrane vesicles act as mobile, lipid-rich vectors linking peripheral microbial reservoirs to neuroimmune and metabolic dysfunction in the aging brain. We discuss evidence suggesting vesicles originating from oral, olfactory, and upper airway niches can access the central nervous system via vascular routes and direct neural pathways, including olfactory and trigeminal nerves, where they influence glial and endothelial cell function. We also propose the Accumulative Vesicle Load Hypothesis, which describes how cumulative lifetime exposure to bacterial vesicles shapes disease onset, anatomical vulnerability, and progression, and incorporates components of other hypotheses proposed for Alzheimer’s disease. This offers a system-level perspective for early diagnosis and upstream therapeutic strategies, including minimally invasive vesicle profiling in nasal fluid, saliva, blood, and cerebrospinal fluid. This work is a conceptual review that summarizes current evidence in a hierarchically organized manner and proposes a testable model; it does not assert causality where direct human evidence is currently limited. Full article

Herpes simplex virus (HSV) infection is highly prevalent worldwide and poses important risks during pregnancy due to the potential for vertical transmission and severe neonatal disease. HSV-1 is traditionally associated with orofacial lesions and HSV-2 with genital infection; however, HSV-1 has emerged as a significant cause of genital and neonatal herpes. Physiological immunomodulation during pregnancy may facilitate viral reactivation and replication. Vertical transmission may occur intrauterinely, intrapartum, or postnatally, with approximately 85% of neonatal infections acquired during delivery through contact with infected genital secretions. The risk is highest when primary maternal infection occurs in the third trimester, before adequate transplacental transfer of protective antibodies. Neonatal infection may present as disease limited to the skin, eyes, and mouth; central nervous system involvement; or disseminated multiorgan disease, the latter associated with high morbidity and mortality. Maternal infection ranges from asymptomatic viral shedding to painful vesiculoulcerative lesions and, rarely, disseminated disease. Because asymptomatic shedding is common, diagnosis relies on laboratory confirmation using polymerase chain reaction (PCR) or viral culture, with type-specific serology aiding in distinguishing primary from recurrent infection. Management aims to reduce symptoms, viral shedding, recurrences near delivery, and vertical transmission. Acyclovir and valacyclovir are safe and effective in pregnancy. Suppressive therapy from 36 weeks’ gestation reduces recurrences and viral shedding at delivery and decreases the need for cesarean delivery, which is recommended when active lesions or prodromal symptoms are present at labor. Neonatal herpes requires prompt recognition and intravenous acyclovir therapy to reduce mortality and neurological sequelae. Preventive strategies include counseling, behavioral risk reduction, suppressive antiviral therapy, and avoidance of neonatal exposure to active lesions. Full article

Mild behavioral impairment (MBI) is a clinical syndrome characterized by the late-life onset and persistence of neuropsychiatric symptoms (NPSs), representing a change from longstanding behavior or personality and considered a potential prodrome of neurodegenerative disease. MBI is classified into five domains: decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, and psychotic symptoms. In this narrative review, we synthesize clinical, neuroanatomical, and molecular evidence linking MBI to the spectrum of tauopathies, including Alzheimer’s disease (AD), frontotemporal spectrum disorders (FTSDs), and primary four-repeat tauopathies such as progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD). Emerging evidence suggests that early behavioral symptoms associated with MBI may reflect the selective vulnerability of frontolimbic, salience, default mode, and frontostriatal networks to tau-mediated neurodegeneration. Mechanistically, converging findings support roles for tau-related synaptic dysfunction, including synaptotoxic soluble tau species, cytoskeletal and axonal transport disruption, monoaminergic neurotransmitter imbalance in brainstem systems, and neuroinflammatory and glial pathways. We also highlight genotype-related behavioral profiles in genetic frontotemporal lobar degeneration and discuss how scalable blood-based biomarkers, including neurofilament light chain, glial fibrillary acidic protein, and plasma phospho-tau species, may complement MBI-based phenotyping for differential diagnosis and prognostic stratification in clinical research. Full article

Alzheimer’s disease (AD) is the most common form of dementia marked by cognitive decline and memory loss. Early detection is essential for timely intervention; however, traditional biomarkers, including cerebrospinal fluid (CSF) assays, neuroimaging, and cognitive assessments, are limited by cost, invasiveness, and accessibility. Digital biomarkers, obtained from wearable sensors, smartphone applications, speech analysis, and other passive monitoring technologies, represent a promising alternative for scalable, non-invasive, and continuous assessment of early cognitive decline. This paper provides a comprehensive review of the current landscape of digital biomarkers for AD diagnosis, emphasizing their potential application in the preclinical and prodromal stages of the disease. In addition, a bibliometric analysis demonstrates the rapid expansion of digital biomarker research, highlighting key trends in publication volume, influential authors, institutions, and interdisciplinary collaborations. Despite the significant promise of digital biomarkers, challenges remain regarding validation, regulatory approval, data privacy, and integration into clinical practice. The results indicate that future research should prioritize standardization, multimodal biomarker integration, and large-scale longitudinal studies to fully realize the potential of digital technologies in AD detection. Full article

Background/Objectives: This aim of this study was to describe the demographic, clinical, and laboratory characteristics of hospitalized children with benign acute childhood myositis (BACM) and to evaluate seasonal patterns, including changes observed during the COVID-19 pandemic. Methods: We conducted a retrospective single-center review of pediatric patients hospitalized with a diagnosis of BACM between January 2016 and December 2024. Clinical, laboratory, and epidemiological data were analyzed, including seasonal distribution before and after the COVID-19 pandemic. Results: We identified 47 cases of BACM, with a male predominance (66%) and a median age of 7 years. Most cases (72%) occurred during autumn and spring. The most common prodromal symptoms were fever, cough and rhinorrhea. Bilateral calf pain was the most frequent presenting symptom. The median creatine phosphokinase (CPK) level was 4986 U/L, with higher values in boys (p = 0.040). Higher CPK levels were associated with longer hospital stays in our cohort (p = 0.030). Influenza B was the most frequently identified pathogen (63%). No BACM cases were recorded during the COVID-19 pandemic period (2020–2022), followed by an increase in 2024. All patients fully recovered, with a median hospital stay of 3.2 days. Conclusions: BACM is a self-limiting condition with a characteristic clinical and laboratory profile. The absence of cases during the COVID-19 pandemic suggests a possible association between reduced viral circulation and BACM incidence. Awareness of its typical presentation may support early diagnosis, reduce unnecessary investigations, and facilitate appropriate clinical management. Full article

Background: Youth mental health services increasingly encounter adolescents and young adults with complex affective presentations and trauma histories. Dissociation has been proposed as a clinically relevant marker within bipolar vulnerability pathways but remains underrecognized in early-intervention settings. This pilot study investigated the prevalence and clinical correlates of bipolar at-risk (BAR) status in a help-seeking youth sample, with specific focus on dissociative symptoms in this vulnerable population. Methods: A pilot study with a cross-sectional design was conducted in a specialized outpatient clinic for 14–25-year-olds. Seventy-six participants without Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision bipolar disorder completed a multidimensional assessment, including dissociative (Dissociative Experiences Scale version 2 [DES-II], Adolescent-DES [A-DES], Structured Clinical Interview for DSM Dissociative Disorders [SCID-D]), affective, anxiety, impulsivity, and prodromal symptom measures. BAR status (BAR+) was determined via clinical interview according to Bechdolf criteria. Clinically significant dissociation (DES+) was defined by established cut-offs at the DES-II and A-DES scales. Group comparisons, binary logistic regression and exploratory mediation analysis were performed. Results: In our sample, 44.7% of the participants met BAR+ criteria and 42.9% displayed clinically significant dissociation. Patients with BAR+ status more frequently reported familiar history of affective disorders, previous antidepressant use, loneliness, and non-suicidal self-injury. They displayed more severe depressive symptoms and impulsivity, as well as higher scores at all the affective temperament subscale except for hyperthymic. BAR+ patients displayed higher prevalence of dissociative symptoms than BAR− (51.6% vs. 24.2%; p = 0.045). Among the BAR+ subgroup, DES+ youths showed greater traumatic burden, depressive symptoms, and anxious temperament scores. Dissociation was associated with BAR+ status (OR 3.2) after adjusting for age, gender, and loneliness, while attentional impulsivity did not mediate this relationship. Conclusions: Dissociative symptomatology is highly prevalent among help-seeking youths and is directly associated with subthreshold bipolar-spectrum vulnerability. A dissociative BAR phenotype, marked by emotional instability and trauma exposure, may delineate a clinically complex subgroup, supporting the integration of dissociation-focused assessment into youth bipolar-risk staging and early-intervention protocols. Full article

Background: Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is an autoimmune disorder frequently associated with ovarian teratomas in young women. Although infectious triggers have been proposed to contribute to immune activation, direct evidence linking viral presence within tumor tissue to disease pathogenesis remains limited. Case Presentation: An 18-year-old woman presented with acute neuropsychiatric symptoms, fever, gastrointestinal prodrome, and rapidly progressive behavioral disturbance progressing to encephalopathy. Cerebrospinal fluid and blood test results, together with clinical features, supported the diagnosis of anti-NMDAR encephalitis. Imaging identified an ovarian mass, and surgical resection was performed. Histopathology confirmed a mature teratoma containing neuroglial elements. Molecular analysis detected parvovirus B19 DNA within the resected teratomatous tissue. No systemic viremia or active central nervous system viral infection was identified. The patient received immunotherapy combined with tumor removal, with subsequent clinical improvement. Discussion: Ovarian teratomas remain a critical etiologic factor in anti-NMDAR encephalitis and mandate prompt surgical management. Detection of B19 viral DNA within teratomatous neuroglial tissue raises the hypothesis that viral persistence could enhance local immune activation and autoantibody generation. However, in this case polymerase chain reaction positivity does not indicate active infection, and the biological significance of this finding remains uncertain. Conclusions: This case documents rare detection of B19V DNA within an ovarian teratomatous tissue in anti-NMDAR encephalitis. The observation is hypothesis-generating rather than causal; established management priorities remain immunotherapy and tumor resection, and viral nucleic acid detection should be interpreted within the broader clinical context. Full article

Background/Objectives: Syncope remains a common problem in the elderly, adversely affecting quality of life, morbidity and mortality. Diagnosis is challenging due to the atypical presentation, multifactorial aetiology, overlap with non-syncoptic falls and increased prevalence of cardiac disease. This study aims to investigate the impact of cardiac syncope in this high-risk population. Methods: A retrospective single-centre observational cohort study, including 171 patients ≥65 years old with syncope of unknown origin or other falls, was conducted. Different diagnostic tests and strategies were utilised during the investigational process, based on clinical judgement and the latest guidelines. Patients were classified either in the ‘high risk’ (‘cardiac’) or ‘low-risk’ (‘autonomic’) pathway. Results: Mean age was 76.4 ± 6.6 years (range: 65–92 years old) and the mean follow-up period was 40.5 months. Our study population was characterised by a high incidence of comorbidities and underlying heart disease, and polypharmacy. One third of the patients did not report prodromals, 81.9% had no recognisable trigger and 43.3% had various 12-lead ECG abnormalities. Overall, 67.8% of the patients were stratified in the ‘cardiac pathway’. Eventually, a final diagnosis was established in 126 patients (73.7%). The cause was cardiac syncope in 56.4%, reflex syncope in 26.2%, orthostatic hypotension in 7.9% and non-syncopal falls in 9.5%. An ILR was implanted in 90.1% with a diagnostic yield of 43%. ECG-based diagnosis occurred in 53.2% whereas time to diagnosis was 4.8 ± 3.3 months. Conclusions: Cardiac disease, mostly arrythmias, represent a common and possibly underestimated cause of unexplained syncope in the elderly. A structured approach including a targeted use of ILRs improves investigational process. Full article

Introduction: Psychotic symptoms (PS) in Alzheimer’s disease (AD) are associated with unfavorable prognosis, including accelerated functional decline and reduced survival. Multiple neurotransmitter systems have been implicated in the pathophysiology of PS, with the serotonergic system emerging as particularly relevant. Materials and Methods: Between 2010 and 2020, 120 patients with prodromal AD and 26 cognitively healthy controls underwent comprehensive evaluation, including clinical history, neurological and neuropsychological assessment, neuroimaging, and lumbar puncture. All participants underwent longitudinal clinical monitoring for a minimum of five years or until the emergence of PS. In February 2024, baseline cerebrospinal fluid (CSF) serotonin (5-HT) concentrations were quantified using competitive ELISA (FineTest, Wuhan, China). Results: CSF 5-HT levels were significantly elevated (p < 0.003) in patients who subsequently developed psychosis (n = 49) compared with those who remained free of PS during the 8-year follow-up (n = 19). A threshold of 4.89 ng/mL yielded 80% sensitivity for identifying individuals at risk. Baseline Neuropsychiatric Inventory (NPI; p < 0.001) and Unified Parkinson’s Disease Rating Scale part III (UPDRS III; p < 0.009) scores also demonstrated strong discriminative capacity. Conclusions: Measurement of CSF 5-HT and detailed clinical profiling in prodromal AD may provide predictive value for psychosis onset within 8 years of diagnosis. To our knowledge, this is the first study to report CSF 5-HT findings in AD patients. Full article

Alzheimer’s disease (AD), the most common form of dementia, is a progressive and irreversible neurodegenerative disorder. Structural MRI is widely used for diagnosis, revealing brain changes associated with AD. However, these alterations are often subtle and difficult to detect manually, particularly at early stages. Early intervention during prodromal stages, such as mild cognitive impairment (MCI), can help slow disease progression, highlighting the need for reliable automated methods. In this work, we introduce a dual-level evaluation framework comparing fifteen deep learning architectures, including convolutional neural networks (CNNs), Transformers, and hybrid models, for classifying AD, MCI, and cognitively normal (CN) subjects using the ADNI dataset. A central focus of our work is the impact of robust and standardized preprocessing pipelines, which we identified as a critical yet underexplored factor influencing model reliability. By evaluating performance at both slice-level and scan-level, we reveal that multi-slice aggregation affects architectures asymmetrically. By systematically optimizing preprocessing steps to reduce data variability and enhance feature consistency, we established preprocessing quality as an essential determinant of deep learning performance in neuroimaging. Experimental results show that CNNs and hybrid pre-trained models outperform Transformer-based models in both slice-level and scan-level classification. ConvNeXtV2-L achieved the best scan-level performance (91.07%), EfficientNetV2-L the highest slice-level accuracy (86.84%), and VGG19 balanced results (86.07%/88.52%). ConvNeXtV2-L and SwinV1-L exhibited scan-level improvements of 7.60% and 9.04% respectively, while EfficientNetV2-L experienced degradation of 2.66%, demonstrating that architectural selection and aggregation strategy are interdependent factors. These findings suggest that carefully designed preprocessing not only improves classification accuracy but may also serve as a foundation for more reproducible and interpretable Alzheimer’s disease detection pipelines. Full article

Parkinson’s disease (PD) and associated synucleinopathies are preceded by a prolonged prodromal phase during which neurodegenerative processes evolve years before the onset of motor or cognitive symptoms. Identifying biologically specific and accessible biomarkers during this window is critical for early diagnosis, risk stratification, and the development of disease-modifying therapies. Increasing evidence supports the skin as a key peripheral tissue involved in synucleinopathy, offering a minimally invasive source for in vivo detection of pathological α-synuclein. This review summarizes current evidence on skin-derived biomarkers across the prodromal continuum of PD, with particular emphasis on skin biopsy-based detection of phosphorylated α-synuclein and α-synuclein seed amplification assays (SAAs). Findings in high-risk prodromal phenotypes, including idiopathic REM sleep behavior disorder (iRBD) and pure autonomic failure (PAF), are critically reviewed. Emerging data suggest that cutaneous α-synuclein pathology may precede nigrostriatal dopaminergic degeneration and may predict phenoconversion to overt synucleinopathies. Important knowledge gaps are highlighted, including the lack of data in other prodromal phenotypes such as hyposmia. Overall, skin-based biomarkers appear to represent promising, scalable tools for biological diagnosis, prognostication, and enrichment of prodromal PD cohorts in clinical trials. Full article

Opioid-related iatrogenic harms, including opioid use disorder, overdose, and opioid-induced respiratory depression, constitute a major patient safety challenge. Although clinicians document key safety signals in unstructured clinical narratives, many of these indicators are not readily captured by conventional surveillance approaches that rely on structured administrative data. This clinically focused narrative review synthesizes 47 empirical studies published between 2009 and 2025 that applied artificial intelligence (AI) methods to identify opioid-related harms from clinical text and to address the resulting ascertainment gap. Across studies, administrative coding systems, including ICD-10, often under-ascertain opioid-related events, whereas text-based AI can identify additional cases and contextual details often documented primarily in narrative records, such as fluctuating mental status, suspected drug causality, and responses to naloxone. Methodologically, the literature has progressed from interpretable rule-based lexicons to machine learning and deep learning models and, more recently, to transformer-based approaches, including large language models (LLMs) for classification and schema-driven extraction. Rule-based systems established the feasibility of transparent surveillance and frequently recovered clinically documented cases missed by billing codes. Subsequent supervised and deep learning approaches expanded scalability and, in a smaller subset of studies, were integrated into electronic health record workflows with operational metrics reported. More recent transformer- and LLM-based studies emphasize richer extraction schemas and benchmark development, including characterization of overdose context and intentionality and identification of potential prodromal neurocognitive signals, although external validation, calibration, and prospective outcome evaluation remain inconsistently reported. Given that the evidence base is predominantly retrospective and that clinical workflow studies remain comparatively few, a pragmatic near-term clinical role is to provide detection-to-triage decision support rather than autonomous diagnosis, in which systems surface candidate cases with reviewable evidence for clinician adjudication. Future progress will require greater standardization of phenotype definitions, routine equity auditing and subgroup reporting, stronger external validation and calibration at operational thresholds, and a shift from retrospective discrimination metrics toward prospective assessments of the clinical workflow impact, clinical utility, and patient-centered outcomes. Full article

Parkinson disease (PD) and mood disorders represent two substantial global health burdens that increasingly co-occur as both conditions rise in prevalence worldwide. Diagnosing Parkinson disease in patients with pre-existing mood disorders is clinically challenging due to overlapping symptoms, medication effects, and shared neurobiological mechanisms. Apathy, psychomotor slowing, and fatigue may mimic depressive symptoms, leading to delayed recognition of early parkinsonism. Development of an underlying neurodegenerative disorder could account for some treatment-resistant symptoms or treatment failures if not recognized. Therefore, the identification of PD will change the treatment and management plan significantly. Accurate diagnosis of PD requires a detailed neurologic examination focusing on bradykinesia, rigidity, and resting tremor, supported when appropriate by dopamine transporter imaging (DaT scan) or other emerging biomarkers. Understanding the temporal relationship between psychiatric and motor features helps differentiate prodromal PD from primary mood disorders. Management of patients with both mood disorders and PD integrates dopaminergic replacement therapy for motor symptoms with individualized treatment of psychiatric comorbidities. Levodopa remains the cornerstone for motor control, while dopamine agonists, MAO-B inhibitors, and COMT inhibitors can be added as needed. For depression and anxiety, SSRIs and SNRIs are first-line choices; quetiapine or clozapine are preferred when treatment for psychosis is necessary. Intentional, thoughtful polypharmacy is frequently required. Non-pharmacologic interventions—including cognitive behavioral therapy, structured exercise, and patient–caregiver education—enhance mood, function, and quality of life. Multidisciplinary collaboration between neurology, psychiatry, and allied health professionals is essential for optimal outcomes. This review offers guidance to healthcare providers as well as other interested parties involved in patients with mood disorders who may also be developing or have PD, especially to those who may have limited access to neurologic resources. Full article

Migraine is a common neurological condition characterized by recurrent headache attacks, frequently associated with prodromal, aura, and postdrome phases. Increasing evidence suggests that metabolic and mitochondrial dysfunction play a central role in migraine pathophysiology, contributing to cortical hyperexcitability and increased oxidative stress. Additionally, the gut microbiota has emerged as an important modulator of migraine susceptibility via the gut–brain axis, influencing inflammation, neurotransmitter production, and neuronal excitability. Specific dietary interventions, including ketogenic diets, low-carbohydrate diets, DASH, omega-3 supplementation, and elimination diets, may modulate these metabolic and inflammatory pathways, as well as the microbiota composition, ultimately reducing the frequency and severity of migraine attacks. This review provides an overview of current evidence on the interplay between metabolism, microbiota, and diet in migraine pathophysiology and management. Overall, the available data support a biologically plausible role for diet as an adjunctive strategy in migraine prevention; however, the current evidence remains highly heterogeneous and is often limited by small sample sizes in sample size, a lack of protocol standardization, suboptimal adherence assessment, and insufficient long-term follow-up. Future studies should focus on adequately powered trials with standardized outcome measures, objective biomarkers and precision medicine approaches. Full article