Perinatal brain injury (PBI) is a major predictor of neurological disability. Commonly associated with prematurity, infection, stroke, hypoxia-ischemia, hemorrhage, and/or toxin exposure, PBI triggers acute and persistent systemic inflammation. There are many stages of vulnerability to PBI during development including pregnancy, birth - term and preterm, and neonatal age. The vulnerable stages can compound inflammation through injury to the placental-fetal-brain axis, adaptive and innate immune system development, neural-immune communication, and central nervous system maturation. Neonates exhibit unique inflammatory signatures and lasting neural-immune responses to various etiologies. Chronic immune dysregulation and priming to a secondary, later-in-life immune challenge defines different forms of PBI while shaping the neonatal and adult immune response with long-term changes. Immunomodulated changes impact regulatory, helper and innate T cells, neutrophils, natural killer cells and immune responsiveness. The major routes of persistent and compounding inflammation in PBI are perinatal neural-immune interactions, cytokine influx, and glial crosstalk. Most treatments are not administered long enough or in the optimal time window to combat sustained inflammation in tertiary and quaternary phases of PBI pathophysiology and are ineffective in reducing neonatal mortality and morbidity and promoting functional recovery. Indeed, persistent systemic and central inflammation is a likely explanation for failed recovery of PBI after the resolution of acute insults. We propose attenuating persistent inflammation and normalizing systemic immune reactivity as key to reducing the functional impact of PBI throughout the lifespan through various avenues including therapeutic treatment, gut microbiome modulation, and novel immunomodulation from preclinical research.

We aimed to examine the prevalence of frailty in older adults with hypertension and its association with suboptimal blood pressure (BP), with a particular focus on differences by sex. The study was conducted at two major hospitals in Vietnam from 2023 to 2024. Frailty was defined by a Clinical Frailty Scale of ≥ 4. Suboptimal BP was defined as systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg. There were 1038 participants (326 female, mean age 73 years). The prevalence of frailty was 28.6%, higher in female (35.3%) than male participants (25.6%). The overall rate of suboptimal BP was 26.7%. In female participants, the frail had a significantly higher rate of suboptimal BP (33.9%) compared to the non-frail (20.9%), but no significant differences among male. In the logistic model adjusted for age, education, marital status, physical exercise, falls, coronary heart disease, diabetes, chronic kidney disease, osteoarthritis, heart failure, stroke, atrial fibrillation, osteoporosis, chronic obstructive pulmonary disease, duration of hypertension, monotherapy/combination therapy, and medication adherence score, the odds ratios of frailty on suboptimal BP were 2.01 (95% CI 1.08-3.76) in female participants, 0.92 (95% CI 0.59-1.44) in male, female-to-male ratio of odds ratios 2.18 (95% CI 1.01-4.70). These findings highlight the need for sex-specific approaches in managing hypertension in older populations.

Obstructive sleep apnea (OSA) is a frequent complication of childhood obesity associated with neurocognitive impairment. Subtle brain injury caused by intermittent hypoxia and sleep fragmentation has been implicated, yet cannot be detected by structural MRI. This study investigated whether three-dimensional texture analysis (3D TA) of T2-weighted MRI could detect subtle microstructural alterations in brain regions affected by cognitive impairment in obese children with moderate to severe OSA compared to healthy age-matched controls. Texture features were extracted, ranked using the Fisher Criterion, and classified with k-nearest neighbors across regions of interest. Among 23 children with OSA and 26 healthy controls, classification accuracy was highest in the left amygdala (87%), right hippocampus (82%), and left insula (82%), with intensity-based features proving most discriminative. In two patients treated with continuous positive airway pressure (CPAP), follow-up scans indicated normalization of brain texture features. These results highlight 3D TA as a sensitive, clinically accessible method for detecting subtle brain changes in pediatric obesity related OSA. Incorporating this approach into clinical practice may improve treatment monitoring and outcomes, though validation in larger cohorts is needed to confirm its validity and to further assess how these markers change with therapies such as CPAP.

Rhino-orbito-cerebral infection is a rare but potentially life-threatening condition that usually occurs in immunocompromised patients. Identification of the causative organism is often challenging. A 71-year-old man without overt immunosuppression, such as corticosteroid use or chemotherapy, presented with visual loss in the left eye and was found to have internal carotid artery occlusion complicated by ischemic stroke. Despite extensive investigations, including surgical biopsy, a definitive diagnosis could not be established for nearly 4 months. Fungal infection was eventually confirmed by culturing a large volume (10 mL) of cerebrospinal fluid (CSF), which revealed a mixed infection with Cladosporium halotolerans and Penicillium corylophilum by Internal Transcribed Spacer rDNA sequencing and β-tubulin gene sequencing. The patient was treated with liposomal amphotericin B followed by voriconazole, resulting in gradual clinical and radiologic improvement. Clinicians should consider fungal infection in patients with unexplained carotid artery occlusion and stroke. Submitting an adequate volume of CSF may improve the diagnostic yield for identifying the causative fungi.

Artificial Intelligence (AI) has become integral to the research of neurological diseases due to the rapid expansion of neuroimaging, clinical, physiological, and wearable data. However, the concise synthesis of recent machine learning (ML) and deep learning (DL) remains limited. This systematic review analyzes studies published between January 2021 and March 2026 on five major conditions- Alzheimer's disease, stroke, Parkinson's disease, brain tumors, and traumatic brain injury (TBI)-following the PRISMA 2020 guidelines and a structured search of PubMed, Scopus, and Web of Science, yielding 206 eligible articles. The results show that convolutional and encoder-decoder architectures dominate imaging tasks, whereas hybrid and multimodal approaches increasingly combine imaging with clinical and sensor data. Emerging paradigms, including federated learning, self-supervised learning, and foundation models, address data scarcity, privacy, and cross-institutional variability. Key advances include high-performing transformer-based models for Alzheimer's diagnosis, real-time stroke detection by CT/MRI, improved Parkinson's detection by multimodal fusion, hybrid models for brain tumor classification, and outcome prediction in TBI. Despite these gains, challenges in generalizability, interpretability, and clinical translation persist, underscoring the need for more robust and clinically reliable AI systems to address these issues.

The United States has not produced a national noise health burden estimate using disability-adjusted life year methodology. We quantified the population health burden of transportation noise across the contiguous United States and examined its distribution across states and socially vulnerable communities. We applied comparative risk assessment to census-tract noise exposure data from the National Transportation Noise Exposure Map for 324.4 million residents. We estimated attributable ischemic heart disease, ischemic stroke, cardiomyopathy, type 2 diabetes, cardiovascular mortality, high annoyance, and high sleep disturbance using exposure-response functions from WHO systematic reviews. We calculated disability-adjusted life years with WHO 2024 noise-specific disability weights, stratified by state and CDC Social Vulnerability Index quintile, with 12-parameter Monte Carlo uncertainty analysis. An estimated 94.5 million people were exposed to transportation noise at or above 45 dB LAeq. We attributed 272,600 DALYs annually (84 per 100,000; 95% UI: 45-121), including 6,330 premature cardiovascular deaths, 11,400 ischemic heart disease cases, 13,600 type 2 diabetes cases, 12.3 million highly annoyed, and 3.3 million with high sleep disturbance. State burden varied six-fold, from 25 to 149 DALYs per 100,000. Communities in the highest social vulnerability quintile bore 2.29 times the burden of the least vulnerable. This is the first US noise burden estimate using WHO DALY methodology with social vulnerability stratification. The equity disparity identifies target populations for noise reduction. Disability weights for annoyance (30%) and road noise fraction (32%) are the two largest contributors to DALY variance, followed by sleep disturbance disability weight (14%) and the LAeq-to-Lden offset (11%), pointing to source-specific noise mapping, larger valuation studies, and standardized metric conversion as priorities.