Epilepsia

Rationale: Reliable electroencephalography (EEG) biomarkers of cortical excitability could improve diagnosis and longitudinal monitoring in epilepsy, yet it remains unclear which metrics best balance sensitivity across individuals with intra-individual stability over time. Methods: We analyzed scalp EEG recordings from the open-access Temple University Hospital EEG Epilepsy Corpus, comprising 1,404 recordings from 96 individuals with neurologist-confirmed epilepsy and 85 healthy controls across multiple sessions. Eight global measures were computed: aperiodic exponent and offset, sample entropy, detrended fluctuation analysis exponent and derived index, spatial gamma-band phase consistency, and absolute and relative alpha power. Group differences were assessed by permutation tests with false discovery rate correction at recording, session, and subject levels. Associations with antiseizure medication burden, temporal stability, and cross-metric correlation structure were evaluated as secondary analyses. Results: Aperiodic parameters showed the most robust case-control separation, remaining significant after subject-level averaging (exponent: median difference = 0.20, q = 0.010; offset: median difference = 0.25, q = 0.011). Entropy and alpha power distinguished groups at the recording and session levels, while gamma-band phase consistency was significant at the session level only; none of these survived subject-level averaging, suggesting greater state-dependency. Higher medication burden was associated with reductions in alpha power and detrended fluctuation analysis, and adjusting for it substantially attenuated group differences, though residual effects in the aperiodic exponent persisted. Cross-metric correlation structure was preserved between groups but modestly reorganized by medication burden. Conclusions: Aperiodic spectral parameters are the most robust EEG markers of epilepsy, reflecting stable trait-like network properties. Complexity and synchrony measures capture complementary, state-sensitive dimensions. Medication burden substantially influences multiple metrics, underscoring the need to account for pharmacological effects when interpreting EEG biomarkers in epilepsy.

Mild malformation of cortical development with oligodendroglial hyperplasia and epilepsy (MOGHE) is a recently recognized cause of drug-resistant focal epilepsy. It is often MRI-negative or shows imaging features mimicking focal cortical dysplasias, which makes recognition difficult and limits presurgical counseling. We aimed to identify an intracranial EEG (iEEG) biomarker that distinguishes MOGHE from other developmental brain lesions encountered in epilepsy surgery. In a retrospective multicenter test cohort of 38 patients (18 MOGHE, 20 non-MOGHE), we analyzed long-term stereo-EEG and subdural recordings. Only MOGHE patients showed highly stereotyped clusters of very brief low-voltage fast activity (LVFA) events, organized into status-like 3 to 12-minute episodes that often lacked clear clinical symptoms. LVFA clusters were present in 16/18 MOGHE and 0/22 non-MOGHE patients. We then tested diagnostic performance in an independent, blinded single-center validation cohort of 22 patients (11 MOGHE, 11 non-MOGHE), in which visual identification of LVFA clusters correctly classified 10/11 MOGHE and 10/11 non-MOGHE cases (Cohens kappa=0.82). Penalized logistic regression further confirmed MOGHE histology as the strongest predictor of LVFA clusters, independent of age and lobe localization. Because LVFA clusters can be recognized visually on routine intracranial EEG recordings without specialized software, this biomarker is readily applicable in clinical practice and may improve presurgical identification of MOGHE. Future prospective studies should determine whether its recognition influences surgical planning, improves outcome prediction, or facilitates selection of patients for mechanism-based therapies.

Normal emotional experience depends on dynamic modulation of neural excitability across limbic and prefrontal circuits, yet the spectral markers that reflect these shifts in humans remain incompletely understood. In this study, we combined a validated video-based emotion induction paradigm with stereotactic electroencephalography (SEEG) in 31 patients with drug-resistant epilepsy to investigate how positive and negative affective states modulate oscillatory and aperiodic (asynchronous) neural activity. Using spectral parameterization to dissociate oscillatory power from the aperiodic 1/f component, we found that emotional valence robustly altered the aperiodic slope in a regionally specific manner: negative valence flattened the slope in thalamus, posterior insula, and posterior cingulate cortex, whereas positive valence produced flattening in dorsolateral prefrontal cortex. Simultaneous oscillatory changes included increased high-frequency activity and decreased alpha/beta power during negative affect, and reduced alpha power during positive affect, which were elucidated after adjusting for broadband aperiodic spectral shifts. These effects persisted after controlling for audiovisual stimulus or physiological features and were not evident in simultaneously recorded scalp EEG, underscoring their localization to intracranial sites. Together, these results provide the first direct evidence that active induction of emotional states modulates the aperiodic slope of human intracranial field potentials, reflecting valence-dependent shifts in local circuit excitability. The findings highlight the 1/f slope as a sensitive neural marker of affective brain states and for mood dysregulation.

Background and Objectives: Older adults with epilepsy are at increased risk for Alzheimer's disease (AD), yet the mechanisms underlying this association remain poorly understood. We applied a validated AD neuroimaging signature to older adults with epilepsy to examine 1) whether older adults with epilepsy mirror AD-related changes, 2) associations with clinical, cognitive, and plasma biomarker outcomes, and 3) utility for identifying subgroups at heightened risk for cognitive decline. Our multicenter, prospectively enrolled cohort allowed for direct examination of differences in AD signatures between those with early-onset and late-onset unexplained epilepsy. Methods: Participants included 449 older adults: 87 with focal epilepsy from the multicenter Brain Aging and Cognition in Epilepsy (BrACE) cohort (age=66.10 [SD=6.86], including early-onset (<55 years at seizure onset) and late-onset ([&ge;]55 years at seizure onset) epilepsy); 362 from the Alzheimer's Disease Neuroimaging Initiative (ADNI), including cognitively unimpaired (CU) healthy controls and individuals with mild cognitive impairment (MCI) or AD dementia. An AD signature was derived from regional cortical thickness and hippocampal volume weighted by their sensitivity to AD-related neurodegeneration in prior work. Associations between the AD signature, epilepsy characteristics, plasma biomarkers ({beta}-amyloid 42/40, phosphorylated tau [pTau217, pTau181], neurofilament light chain [NfL]), and cognition were evaluated in BrACE. Results: Participants with epilepsy demonstrated more AD-like signatures compared to ADNI CU controls ({beta}= -0.43, p<0.001), reflecting reduced thickness/volume in AD-vulnerable regions. This effect was stronger among early-onset ({beta}= -0.57) versus late-onset ({beta}= -0.26) epilepsy. In BrACE, the AD signature correlated with NfL ({beta}= -0.30, p=0.050), memory performance ({beta}= 0.30, p=0.006), and predicted greater odds of cognitive impairment specifically among those with early-onset, but not late-onset, epilepsy (interaction p=0.043). Further, among those with early-onset epilepsy, the AD signature significantly improved identification of cognitive impairment over and beyond the effects of plasma AD biomarkers (p=0.041). Findings were similar when examining the effects of epilepsy duration rather than epilepsy onset age. Discussion: AD neuroimaging signatures may help identify clinically meaningful subgroups among older adults with epilepsy, particularly when integrated with AD biomarkers. Findings support a multimodal framework for assessing AD-related risk in epilepsy and highlight interactive effects of epilepsy chronicity and AD-related processes that can influence cognitive outcomes.

The objective assessment of patients with disorders of consciousness (DOC) remains a significant clinical challenge. Behavioral scales like the Coma Recovery Scale-Revised (CRS-R) are susceptible to rater subjectivity and have difficulty in detecting patients with cognitive-motor dissociation (CMD), while existing electrophysiological paradigms typically evaluate isolated processing levels, especially in visual functions. To address these limitations, we developed a novel, hierarchical visual EEG framework that evaluates three progressive tiers of visual processing--sensory input, selective attention, and object discrimination--within a single, unified paradigm. This framework uses steady-state and event-related potentials, analyzed with statistical testing and machine learning, to provide objective detection. In a cohort of 85 participants, the framework demonstrated a robust alignment with behavioral CRS-R levels and successfully identified CMD patients missed by bedside behavioral examinations. Notably, model predictions derived from this framework showed a significant correlation with 3-month clinical outcomes. This prognostic utility generalized effectively and remained consistent across distinct EEG acquisition systems in an independent validation cohort of 17 patients. In summary, this work offers electrophysiological validation for the hierarchical design of the CRS-R and provides a practical tool for bedside objective assessment of DOC.

Background and Objectives: Converging evidence hints at neurodevelopmental effects in genetic frontotemporal degeneration (FTD). In cross-sectional studies, for some genes, young adult FTD variant carriers show differences in brain volumes and cognition compared to familial non-carriers. However, longitudinal trajectories may more sensitively capture FTD-related neurodevelopmental vs. neurodegenerative changes than cross-sectional approaches. This study examined longitudinal trajectories of brain volumes, executive function, and plasma biomarkers in young adult carriers compared to familial non-carriers, as measures of neurodevelopmental and neurodegenerative outcomes of FTD-causing variants. Methods: This longitudinal cohort study comprised participants, aged 18-30 years, from the FTD Prevention Initiative across Europe, Canada, and the USA. Genetic groups included C9orf72 (47%), MAPT (30%), and GRN (23%). Linear mixed-effects models were computed to assess longitudinal outcomes across age between groups, controlling for sex, scanner (for brain volumes), and education (for executive function); random effects accounted for between-subject variability nested within family membership. Results: Variant carriers (n=147) and familial non-carriers (n=113) did not differ in age (mean{+/-}SD, 25.9{+/-}3.2 years), sex (53% female), or number of visits (2.1{+/-}1.7). Young adult C9orf72 repeat expansion carriers exhibited smaller thalamic volumes than non-carriers at the reference age of 26 years (b=-982.8mm3, SE=317.0, p=0.0046, f2=0.32), with relatively stable trajectories across ages 18-30 (i.e., no change over time). Trajectories of rostral anterior cingulate volumes differed in C9orf72 carriers and non-carriers across age, where carriers showed relatively stable trajectories and non-carriers showed age-appropriate declines (b=64.4mm3, SE=29.9, p=0.035, f2=0.07). For MAPT and GRN, there were little to no differences in total brain, cortical, or subcortical volumes between groups and over time. No longitudinal differences were observed between carriers and non-carriers in executive function, or plasma NfL or GFAP for any genetic group. Discussion: C9orf72 repeat expansions were linked to smaller average thalamic volumes and stable trajectories between ages 18 to 30, supporting potential neurodevelopmental origins. The modest evidence supporting an absence of difference in neurodegenerative biomarkers and executive function suggests minimal early neurodegeneration and functional preservation in young adulthood.

Although language acquisition delays are frequently observed in children with autism spectrum disorder (autism), our current understanding of the neurobiological mechanisms underlying language development in autism is sparse. Previous studies have found resting-state electroencephalography (EEG) power to be associated with language abilities in autistic children. However, longitudinal studies examining resting-state EEG phase coherence in relation to language development in preschool-aged children with autism are limited. This study aimed to characterize age- and group-related changes in whole-brain coherence in neurotypical children and in autistic children with and without language delay. Resting-state EEG and language data were collected at 2, 3, and 4 years of age. Peak phase coherence within the alpha band (6-11 Hz) was calculated at each timepoint and differences in the developmental trajectory of peak alpha coherence (PAC) were analyzed. In neurotypical children, PAC increased between 2 and 4 years of age. In contrast, PAC did not significantly change with age in children with autism. However, when examining autistic children based on language delay status, PAC increased with age in autistic children without language delay, but not in children with language delay. Exploratory analysis revealed evidence for an interaction between PAC and age, suggesting that the direction of the association between PAC and VDQ varied across age. Overall, these results support previous findings of altered oscillatory connectivity in autism and suggest that differences become apparent early in development. Importantly, phase coherence may not only differentiate diagnostic groups but also capture meaningful variability within the autism group. Future research should further investigate the use of EEG coherence as a biomarker of language development in autism.

Background: Obsessive-compulsive disorder (OCD) is characterized by disturbing thoughts (obsessions) that initiate anxiety-reducing thoughts or behaviors (compulsions). For patients with treatment-resistant OCD (tr-OCD), neuromodulation techniques, like capsulotomy (a lesion in the anterior limb of the internal capsule) and deep brain stimulation (DBS), have emerged as interventions that likely regulate connectivity between the prefrontal cortex (PFC) and subcortical targets. Three patients (Cap-DBS1-3) underwent a failed capsulotomy followed by successful DBS. Here, we aimed to understand the brain connections disrupted by failed capsulotomy vs modulated by successful DBS. Methods: We used diffusion-weighted magnetic resonance imaging (dMRI) tractography in a control cohort with tr-OCD (n=12) and in two of the Cap-DBS patients themselves to determine connectivity profiles of the capsulotomy, volume of tissue activated (VTA), and potentially necessary tracts (VTA minus capsulotomy tracts). We used whole-brain, PFC-focused, and subcortically-focused tractography algorithms to fully explore the space of possible connections. Results: Capsulotomy regions-of-interest (ROIs) connected with a variety of PFC and subcortical regions. VTA ROIs and potentially necessary tracts had limited and inconsistent PFC connectivity but substantial subcortical connectivity. While correlated to the average OCD connectome (r = 0.214, 95% CI [0.177, 0.251]; r = 0.756, 95% CI [0.739, 0.772]), the Cap-DBS connectomes had many edges that were stronger (z-score > 3). Conclusions: The connectivity profile of potentially necessary tracts for successful DBS treatment after failed capsulotomy revealed a surprising proportion of subcortical regions and inconsistent PFC involvement, highlighting an often-ignored set of connections that may be critical to effective DBS.

Background: Mono-allelic Dehydrodolichyl Diphosphate Synthase (DHDDS) variants are associated with juvenile Parkinsonism, developmental delay and seizures. Symptoms are progressive, and various mechanisms, such as defective glycosylation, lysosomal dysfunction and cholesterol accumulation have been hypothesized to underlie disease symptoms. There is no treatment for DHDDS-related disease. Methods: Patient-derived cortical forebrain organoids were created to elucidate disease mechanisms and evaluate potential treatments. In these neuronal models, glycosylation, lipidomics, proteomics, cholesterol/ganglioside accumulation, mitochondrial function and electrophysiological activity were assessed. Finally, we investigated the effects of nicotinamide mononucleotide (NMN), identified through a yeast-based drug screen, in neuronal cell models and in six patients in an off-label, N-of-1, observational series. Results: DHDDS-patient derived organoids showed visual signs of degeneration after four months of culturing. This was accompanied by significant cholesterol accumulation in astrocytes, decreased mitochondrial respiration and loss of deep-layer neurons. In addition, we identified glycosylation abnormalities, showing for the first time that glycosylation in human tissue is affected by monoallelic DHDDS variants. Proteomic analysis revealed altered protein expression of proteins involved in lipid metabolism, cytoskeletal organization and neuronal development. We found that oral Nicotinamide Mononucleotide supplementation led to significant improvement in mitochondrial respiration and electrophysiological parameters in organoids, concurring with clinical improvements in all of the treated patients, particularly regarding their ataxia and tremor. Conclusion: Our findings reveal a progressive phenotype in DHDDS-patient-derived brain organoids, with mitochondrial dysfunction and astrocyte-specific metabolic alterations contributing to disease pathology. Notably, NMN treatment led to clinical improvements in patients with heterozygous DHDDS variants, highlighting its potential as a therapeutic strategy.

Background: Mucopolysaccharidosis type IIIB (MPS IIIB) is a devastating neurodegenerative lysosomal storage disorder caused by alpha-N-acetylglucosaminidase (NAGLU) deficiency. There is currently no approved therapy. We report the 3-month outcomes of a novel intracerebroventricular (ICV) gene therapy in a child with MPS IIIB. Methods: In an open-label, single-center, investigator-initiated trial (ChiCTR2600121466), a single dose of RDGT-101 (2.0E14; vg of an AAV9 vector encoding human NAGLU) was administered via ICV infusion. Primary outcomes were safety and tolerability. Secondary outcomes included serum NAGLU activity, urinary heparan sulfate (HS) excretion, and neurocognitive function. Exploratory analyses included hematological parameters. Results: The patient achieved serum NAGLU activity (17.06 nmol/mL/hour) approaching that of healthy controls (17.75 {+/-} 1.37 nmol/mL/hour) by Month 3, accompanied by a 58.4% reduction in urinary HS. Clinically, previously severe hand and toe contractures resolved, allowing for full extension. Neurocognitive improvements were observed, including clear articulation, logical conversation, and sustained eye contact. Hematological analyses revealed normalized red blood cell indices and improved iron utilization. No dose-limiting toxicities, serious adverse events, or clinically significant laboratory abnormalities were observed. Conclusions: A single ICV infusion of RDGT-101 was safe and well-tolerated in this patient with MPS IIIB. Early biochemical correction was accompanied by marked improvements in somatic, neurocognitive, and hematological parameters. These findings support further investigation of ICV AAV9 gene therapy for MPS IIIB.

Background: Electrolyte replacement is ubiquitous in the acute care setting, but its familiarity cannot belie that even small dosing errors with potassium can cause lethal cardiac arrhythmias. Recently, MedAgentBench offered a benchmark for agentic artificial intelligence (AI) including the ability to correctly dose potassium based on a single rule; however, this does not adequately reflect the clinical complexity or safety concerns of an agent that has been used as the lethal injection. The purpose of this analysis was to a probe leaderboard large language model (LLM) capabilities to follow basic dosing rules to safely replace potassium in a series of clinician-annotated cases. Methods: Using a clinician panel, we developed a series of dosing principles and 20 clinical cases reflective of the complexity of potassium replacement. External clinicians were surveyed to assess practice variability and agreement to clinician panel answers. We tested GPT-5-chat with each case in triplicate, with and without the clinician curated dosing principles, and prompted the model to answer six questions involving potassium goals, dosing, route, lab frequency, concurrent interventions, and the model's perceived level of confidence for the output and complexity of the case. The primary outcome was the rate of appropriate recommendations in comparison to clinician answers. Results: A total of 54 clinicians reviewed the 20 hypokalemia cases and hypokalemia dosing guideline. Clinicians expressed "highly agree" or "somewhat agree" for 66.8% of the cases evaluated when asked if they agree with the guideline-recommended management. When given the potassium dosing guideline, total errors dropped from 165 to 104, and average accuracy improved from 45% to 65% with GPT-5-Chat. GPT-5-Chat conveyed a high level of confidence for 100% of responses, while labeling 80% and 76% of cases as highly complex with and without the criteria, respectively. Potential harm scores were considerable in both groups, however, a notable reduction in severity scores occurred with the dosing guidance document. Recommendations on concurrent interventions and dosing had the highest rate of errors in both groups. Conclusions: Benchmarks must appropriately reflect clinical complexity to be considered valuable for the deployment of agentic artificial intelligence tools in the healthcare domain. GPT-5-Chat assessment on a comprehensive medication management task for potassium replacement showed improvement with dosing guidance, yet unfit benchmarking performance.

Brain-derived tau (BD-tau) is an emerging blood-based biomarker for neurodegeneration, yet there are currently limited well validated BD-tau assays available for research and clinical use. To enhance access to this vital biomarker for neurological disorders including traumatic brain injury (TBI), we developed a novel blood-based immunoassay for BD-tau on the ultra-sensitive Quanterix HD-X platform using Single Molecule Array technology. Analytical validation assessed dilution linearity, specificity, precision, detection limits, and spike recovery, each recording robust metrics in agreement with international expert recommendations. The assay demonstrated robust validation metrics, achieving between-run stability of 95% when analyzing aliquots from six independent plasma and serum samples across five analytical runs. It also showed strong dilution linearity when diluted four-fold and achieved over 90% recovery when spiked with cerebrospinal fluid. Next, we evaluated the clinical utility of the assay in cohorts of individuals with traumatic brain injury (TBI), where strong performances were recorded whether using the 2-step or 3-step assay formats ({rho}= 0.94; p < 0.0001). Furthermore, plasma BD-tau distinguished samples from TBI patients based on time from injury and severity (AUC=0.93). Plasma BD-tau differentiated between favorable and unfavorable functional outcomes in the acute-severe group. Our findings underscore the significant potential of the BD-tau assay as a biomarker for TBI in the severe phase.

In February 2026, the FDA announced that a single pivotal phase 3 (P3) trial would become the new default standard for drug approval - a regulatory direction that had been legally enabled since the FDA Modernization Act of 1997. This announcement has strategic, scientific, and economic implications for drug developers, contract research organizations (CROs), and biotech investors. We argue that the expansion of this framework, originally reserved for various niche submissions, represents a paradigm change, dramatically increasing the value of rigorous early phase (P1 and P2) trial design, requiring sponsors to establish both statistical efficacy signals and mechanistic biological understanding before entering phase 3. Using a CNS indication cost model, we show that single P3 approval can reduce total development expenditure from approximately $447 million over 14 years to $297 million over 12 years - a savings of $150 million and providing two years of additional commercial runway for a modeled CNS drug. Case examples including lecanemab, omaveloxolone, and tofersen illustrate how biomarker-informed early phase strategies can establish the confirmatory evidence necessary for single-trial approval. We provide practical guidance for maximizing the value of P1 and P2 under this evolving framework.

Background: Artemisinin-based combination therapies remain the mainstay of malaria control strategies; nevertheless, the advent of genetic markers linked to partial artemisinin resistance in Plasmodium falciparum has elicited substantial concern across African settings. To assess the prevalence, geographic distribution, and clinical associations of these molecular markers, we undertook a systematic review and meta-analysis of observational cohort studies.Methods: We conducted a search of cohort studies published between January 2015 and June 2025, following PRISMA 2020 guidelines. We queried databases including PubMed/MEDLINE, Scopus, Web of Science, and CINAHL. Eligibility required prospective enrollment of patients, longitudinal monitoring (therapeutic efficacy studies), and pfkelch13 propeller domain genotyping.Results: A meta-analytical synthesis of 888 isolates from six core prospective cohorts revealed a pooled prevalence of 6% (95% CI: 2.1%-11.8%) for validated pfkelch13 mutations. A profound geographic dichotomy was identified: while West and Central African cohorts maintained a 0% prevalence, East African hotspots showed significant expansion, with prevalence reaching 12.8% in Rwanda and up to 25.5% in Northern Uganda; high statistical heterogeneity (, ) reflects this biological divergence. Conclusions: These findings highlight the established and expanding presence of artemisinin partial resistance in East Africa. Standardized surveillance is essential to adapt malaria control policies across the continent. Keywords: Africa; artemisinin resistance; clinical indicators; pfkelch13 gene; molecular markers; partial resistance; Plasmodium falciparum.

Background: This study aimed to evaluate real-world adverse event (AE) signals of EV to provide evidence-based guidance for its safe clinical application. Methods: Data from the FDA Adverse Event Reporting System (FAERS) database from the period of 2019 Q1-2025 Q3 were analyzed. Disproportionality analysis algorithms, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM), were utilized to mine safety signals.The time to onset (TTO) was evaluated using the Weibull distribution model. Results: Among 11,697,906 reports, 4,177 EV-treated patients experienced 14,511 AEs. The most common System Organ Classes (SOCs) were skin and subcutaneous tissue disorders (18.23%), general disorders and administration site conditions (13.17%).Multi-algorithm consensus identified 179 positive signals. Alongside known toxicities (rash, peripheral neuropathy, hyperglycemia), potential new signals emerged, including dysgeusia, atypical skin lesions, and myelosuppression. Median TTO was 14 days, with the Weibull {beta} of 0.736, confirming an "early failure" profile. Subgroup analysis revealed toxicity heterogeneity: patients aged [&ge;]65 and females exhibited stronger signals for fatal severe cutaneous adverse reactions, while patients aged < 65 and males showed higher susceptibility to neurological and metabolic toxicities. Conclusions: The real-world safety profile of EV confirms known toxicities, reveals new risks (e.g., dysgeusia), and shows toxicity concentrated in the first treatment cycle. Clinical practice requires proactive monitoring during the first two weeks using demographic-specific strategies: vigilance for fatal skin toxicity in elderly and female patients, and close follow-up of neurological and metabolic indicators in younger and male populations.

Background Children in low- and middle-income countries (LMICs) face an elevated risk of developmental delay, yet scalable neuroimaging tools to study early brain development in these contexts remain limited. Children who are HIV-exposed but uninfected (CHEU) represent a growing population with evidence of language and motor delays and altered brain development compared with children who are HIV-unexposed (CHU). Ultra-low-field (ULF) MRI offers a more affordable alternative to conventional high-field (HF) MRI, but its application in early childhood remains underexplored. Methods We compared brain volumes derived from ULF (64mT) and HF (3T) MRI in South African CHEU and CHU as part of the DolPHIN-2 PLUS study. Volumetric segmentation was performed using FreeSurfer v7.4.1 and SynthSeg on the Flywheel platform. Agreement between modalities was assessed using Pearsons and Lins concordance correlation coefficients across global and subcortical regions. Associations between ULF-derived brain volumes and developmental outcomes, measured by the Bayley Scales of Infant Development, Third Edition, were evaluated using partial correlations adjusted for sex and age. Results Forty-five children (9 CHEU, 36 CHU; mean age 45.6 months) had paired ULF and HF scans of usable quality. Strong correlations were observed between ULF and HF volumes for global white and grey matter regions (r > 0.92) and larger subcortical grey matter structures such as the thalamus, caudate, and putamen (r = 0.86-0.89). Moderate-to-weak correlations were evident in smaller structures (hippocampus, pallidum, amygdala). ULF underestimated most grey matter volumes, and overestimated total white matter volume relative to HF. ULF-derived global and subcortical volumes were associated with receptive and expressive communication (r = 0.34-0.59, all p < 0.05). Conclusions ULF MRI produces brain volume estimates comparable to HF MRI and captures meaningful associations with early language development. These findings support ULF MRI as a feasible and scalable tool for studying neurodevelopment in vulnerable paediatric populations in LMICs.

Introduction: Myalgic Encephalomyelitis (ME)/Chronic Fatigue Syndrome (CFS) is a debilitating condition characterised by severe fatigue and post-exertional malaise (PEM). Reported neuropsychophysiological abnormalities suggest ME/CFS is multifactorial, but current knowledge remains fragmented. This study protocol outlines a multimodal investigation designed to (1) compare neuropsychophysiological mechanisms between ME/CFS patients and healthy participants, (2) test an integrative model of ME/CFS, (3) identify neuropsychophysiological subgroups within the patient population, and (4) identify predictors of symptom response during rehabilitation. Methods and analysis: This study will enroll 115 ME/CFS patients and 55 healthy participants. Groups will be comparable in age, sex, and education level, with a larger patient sample enabling subgroup and longitudinal analyses. A cross-sectional assessment at baseline will be carried out in both groups. Patients will then be evaluated longitudinally throughout a standardized cognitive-behavioral therapy rehabilitation program delivered as routine care. Baseline measures include systemic inflammation and general health biomarkers, measures of autonomic and central nervous system function, neuroinflammation (magnetic resonance spectroscopy, [18F]DPA714 PET in a subsample), serum short-chain fatty acid levels, gut microbiota composition and function, and neuroendocrine and self-reported responses to psychosocial stress. Fatigue severity (physical and cognitive) and PEM will be assessed through validated questionnaires, ecological momentary assessment, and laboratory tasks. These will be re-evaluated during therapy, and all non-neuroimaging measures will be repeated after the rehabilitation program. Statistical analyses will comprise multivariate analysis of variance, general linear models, classification algorithms, structural equation models, least absolute shrinkage selection operator principal component regression (LASSO-PCR), cluster analysis and latent class growth analysis (LCGA).

Background: Cognitive impairment in Parkinson's disease (PD) is linked to degeneration of the cholinergic basal forebrain, particularly cholinergic nucleus 4 (Ch4) in the nucleus basalis of Meynert. Structural and diffusion MRI separately detect this degeneration, but few studies have combined these modalities across the PD cognitive spectrum. Methods: We analyzed 92 participants: 14 healthy controls (HC), 35 PD with normal cognition (PD-NC), 33 with mild cognitive impairment (PD-MCI), and 10 with dementia (PDD). For Ch4 and cholinergic nuclei 1, 2, and 3 (Ch1-3) in the medial septal/diagonal band complex, we determined TIV-normalized gray matter density (GMD) and free-water (FW) fraction. We evaluated group differences, cognitive correlations, adjusted multivariable regression, and exploratory ROC discrimination. Results: Ch4 GMD was significantly lower in PDD compared to PD-MCI (p=0.007), PD-NC (p<0.001), and HC (p<0.001). Ch4 GMD was also lower in PD-MCI versus HC (p=0.028); the PD-MCI versus PD-NC difference was not significant after correction (p=0.074). Ch1-3 GMD was lower in PDD versus PD-NC (p=0.008) and HC (p=0.009). Ch4 and Ch1-3 FW were elevated in PDD versus all other groups (all p<0.01). Among PD patients (n=78), MoCA was positively correlated with Ch4 GMD ({rho}=0.49) and Ch1-3 GMD ({rho}=0.42) and negatively correlated with Ch4 FW ({rho}=-0.51) and Ch1-3 FW ({rho}=-0.40; all p<0.001). In the full four-metric model, Ch4 GMD and Ch4 FW were the only independent basal forebrain predictors (Ch4 GMD {beta}=+2.04, p<0.001; Ch4 FW {beta}=-1.46, p=0.005) of MoCA score. The combined Ch4 GMD + Ch4 FW model showed high discrimination for PDD versus non-demented PD (AUC=0.934; optimism-corrected AUC=0.925). Conclusions: Structural and free-water diffusion MRI provide complementary information about Ch4 degeneration in PD. The combined Ch4 model showed promising exploratory discrimination of PDD; validation in larger independent samples is needed.

Objective To map national Parkinsons disease (PD) research capability to inform an inclusive delivery strategy for a large-scale clinical trial. Background Few people with PD participate in clinical trials, particularly from under-served populations. The Edmond J Safra Accelerating Clinical Trials in PD initiative (EJS ACT-PD) aims to deliver an inclusive multi-arm multi-stage (MAMS) disease modification PD trial. Methods A survey disseminated to National Health Service (NHS) hospitals assessed PD research capability regarding trial experience, rater expertise, trial facilities and specialist investigations. A process was developed to categorise sites into 3 tiers, with tier 1 having the least PD-research capability or experience, and tier 3 being experienced specialist centres. We mapped tiers to PD prevalence, social deprivation and ethnic diversity to identify infrastructure gaps. We developed trial delivery strategies to facilitate rapid and inclusive recruitment. Results Out of 97 survey responses, 43 sites were categorised as tier 1, 33 as tier 2 and 21 as tier 3. Diversity and social deprivation index were higher for tier 3 sites (predominantly urban). A greater proportion of tier 1 and 2 sites were situated in areas of higher PD prevalence (predominantly rural). Ninety one percent of sites reported experience with remote trial delivery methods. Our delivery strategy included: initial trial set-up at tier 3 sites to enable rapid and ethnically diverse recruitment; core funded staff within strategic sites to develop regional solutions for inclusive trial participation and to enable research opportunity provision in areas where currently very little exists, and a hybrid delivery model of in-person and remote study visits, ensuring maximal acceptability and deliverability. Conclusions The mapping of current PD research delivery capability has allowed us to develop a trial delivery strategy that will broaden the provision of research participation opportunity to under-served groups. It has also enabled existing infrastructure to be maximised while mitigating identified gaps.

INTRODUCTION Severe acute brain injury (stroke, traumatic brain injury or hypoxic-ischemic encephalopathy; SABI) is increasingly recognized as a chronic condition with care and communication needs beyond the initial hospitalization. This study aimed to characterize post-acute care patterns among SABI survivors, focusing on healthcare utilization and outpatient communication. METHODS Data were collected from a prospective cohort of hospitalized SABI patients using surveys, chart reviews, and the ED Information Exchange database. Socioeconomic disadvantage was assessed using the Area Deprivation Index (ADI), and qualitative analysis of outpatient notes examined conversations around palliative care needs and goals-of-care. RESULTS Two-thirds of patients (140/222) survived until discharge, primarily to nursing facilities (39%) or inpatient rehabilitation (38%). Among 109 with one-year follow-up, there were 89 hospitalizations, 104 ED visits, and 28 deaths. Patients from the most disadvantaged neighborhoods had significantly higher odds of rehospitalization or ED use within 30 days (OR 3.37, p=0.036). ADI was not linked to one-year utilization. seen outpatient by primary care (40%), neurology/neurosurgery (57%), and palliative care (1%), but conversations rarely revisited prognosis or goals-of-care. CONCLUSIONS Our findings highlight the need for improved long-term care planning and communication, particularly for socioeconomically disadvantaged survivors of SABI.