School of Medicine

While the apolipoprotein E (APOE) ε4 allele promotes blood–brain barrier (BBB) permeability and microstructural disruption, its specific contribution to white matter hyperintensity (WMH) pathological heterogeneity remains unknown. We measured BBB permeability (Ktrans) in 31 and microstructure in 59 cognitively normal older adults with WMHs and normal‐appearing white matter (NAWM) using dynamic contrast‐enhanced magnetic resonance imaging and restriction spectrum imaging (RSI). Linear mixed‐effects models (LMMs) examined differences between WMHs and NAWM by APOE ε4 status. In APOE ε4 carriers, Ktrans was elevated and restricted isotropic diffusion (RI) was reduced within WMHs compared to NAWM. This effect was absent in non‐carriers. In contrast, reduced restricted directional diffusion and elevated isotropic free water within WMHs was observed in both genotypes. Ktrans did not correlate with brain microstructure. Our data suggest that WMHs comprise both APOE ε4‐related and APOE ε4‐independent pathological components. These findings implicate neurovascular and non‐vascular mechanisms through which APOE ε4 may contribute to WMH pathological heterogeneity. Apolipoprotein E (APOE) white matter hyperintensities (WMHs) show higher blood–brain barrier permeability and lower restricted isotropic diffusion. Additional microstructure abnormalities in WMHs are APOE ε4 independent. Permeability and microstructure are independent features of WMH pathology. APOE ε4 contributes to WMH burden through a distinct vascular phenotype.

BackgroundParity history influences dementia risk and cognitive aging, and recent evidence suggests it may also influence the association between physical activity and cognition in later life.ObjectiveTo examine associations between total lifetime and life-stage-specific physical activity and later life cognition in postmenopausal females with differing parity histories.MethodsThis cross-sectional analysis using data from the Rancho Bernardo Study included 867 postmenopausal females with complete data, categorized into three parity groups (number of pregnancies >6-months): nulliparous, 1-2 pregnancies, and grand-multiparous (≥3 pregnancies). Cognitive outcomes included executive functions and memory. Physical activity was assessed using a self-report questionnaire capturing retrospective activity during adolescence, age 30, age 50, and current activity in later life. Covariates included age, education, health composite score, body mass index, and hysterectomy status. Linear models examined associations between physical activity and domain-specific later life cognitive outcomes stratified by parity.ResultsGreater total lifetime physical activity was associated with higher executive functions in nulliparous and grand-multiparous females. Moderate activity in nulliparous females and high activity in grand-multiparous females during adolescence and at age 30 were associated with higher executive functions. High physical activity at age 50 and currently was associated with higher executive functions in nulliparous females.ConclusionsThe findings suggest the relationship between self-reported physical activity and cognition was strongest in the two groups at greater risk for cognitive decline and Alzheimer's disease, the nulliparous and grand-multiparous groups. Further research is needed to understand the mechanisms driving parity differences.

Precision management of Parkinson's disease (PD) requires frequent levodopa (L-dopa) dose adjustments, yet current monitoring relies on subjective symptom reporting and infrequent blood testing. Here, we present a soft, fingertip-mounted wearable platform for continuous, noninvasive L-dopa monitoring. By combining osmotically harvested passive sweat with soft hydrogels, a potentiometric sensing strategy, and individualized calibration, the platform estimates blood L-dopa information from sweat without external power or iontophoresis. Strong correlations between sweat and high-performance liquid chromatography (HPLC)-measured blood L-dopa concentrations were observed in healthy ([Formula: see text]) and PD subjects ([Formula: see text]) following a single immediate-release L-dopa/carbidopa dose. Low motor symptom scores aligned with peak L-dopa levels, confirming pharmacodynamic relevance. L-dopa cleared faster in PD patients despite similar bioavailability to healthy subjects, while recorded hemodynamic responses showed short hypotensive trends for both groups. Machine learning identified sweat and blood pressure as key contributors toward accurate estimation of blood L-dopa levels (mean absolute error = 2.02 µM vs. ground truth). Overall, our easy-to-use, energy-efficient wearable supports real-time, stimulation-free monitoring, potentially enabling at-home dosage adjustments and paving the way for future autonomous closed-loop L-dopa therapeutic system development.

Optimal levodopa (L-Dopa) dosing for the personal management of Parkinson’s disease represents a major clinical challenge due to L-Dopa’s narrow therapeutic window and inter- and intra-patient absorption variability. Current methods for measuring L-Dopa, relying on repeated blood draws for centralized laboratory measurements, fall short of capturing dynamic L-Dopa fluctuations that are relevant for timely interventions. Here, we present a minimally invasive microneedle (MN)-based wearable biosensor for continuous monitoring of L-Dopa (CDM) in human subjects. The MN biosensor platform relies on a tyrosinase-functionalized working electrode for detecting L-Dopa in interstitial fluid (ISF) through enzymatic electrochemical detection. The device was evaluated in healthy volunteers and participants with Parkinson’s disease in clinical settings, illustrating its ability to provide actionable temporal insights. Critical validation of the MN biosensor was carried out by comparing the ISF L-Dopa signals with plasma L-Dopa concentrations measured by high-performance liquid chromatography (HPLC). Using subject-specific calibration and lag-time correction, the ISF-derived drug profiles showed a close correlation with plasma L-Dopa pharmacokinetics, with a mean absolute relative difference (MARD) of 9.64%. An inverse correlation between the L-Dopa pharmacokinetics and the corresponding motor performance was observed. Such pioneering demonstration of the clinical feasibility of MN-based CDM in humans highlights its considerable potential for supporting the management of Parkinson’s disease.

Quantitative analysis of corticospinal tract (CST) sprouting after injury requires reliable labeling of long-range axons and fine collateral branches. Conventional biotinylated dextran amine (BDA) tracing has limited sensitivity and requires additional surgeries, while some viral-based approaches, although robust, rely on extensive tissue processing and signal amplification. Here, we describe a streamlined adeno-associated virus (AAV)-based workflow for CST sprouting analysis using TurboRFP that enables robust labeling of descending CST axons, including sprouting fibers after unilateral pyramidotomy. This approach allows direct visualization of fine CST axons without immunostaining or signal amplification, simplifying tissue processing and reducing experimental variability. Using a standardized workflow, we enable consistent CST labeling and reproducible quantification of CST remodeling. In addition, compatibility with co-delivery of other AAVs enables simultaneous circuit tracing and genetic manipulation within the same neuronal population. This workflow provides a practical platform that lowers technical barriers to axon repair research and potentially improves reproducibility across laboratories.

Autonomic dysfunction (AD) is present in nearly all people with Parkinson disease (PD), contributing to tremendous morbidity and mortality. Highly variable presentations including cardiovascular, gastrointestinal, urogenital, and thermoregulatory dysfunction can substantially affect daily function, safety, medication tolerance, and quality of life. Although autonomic symptoms are frequently encountered in neurologic practice, their management frequently extends beyond the traditional scope of neurologic care and may require input from multiple disciplines. Despite the increasing complexity of PD care and the need for coordinated multidisciplinary involvement, there are currently limited practical frameworks to guide specialist collaboration. Consequently, people with PD and their caregivers are often left to navigate fragmented care systems, conflicting recommendations, and uncertainty regarding which clinician should guide management. To help address these gaps, we provide a framework for the possible indications for specialist referrals and the potential roles of different healthcare practitioners in evaluating and treating AD. The manuscript also discusses the intersection between autonomic and neuropsychiatric manifestations in PD and offers practical clinical guidance for addressing this overlap. By providing a framework informed by coauthors in movement disorders, autonomic disorders, cardiology, nephrology, gastroenterology, physical therapy, and psychiatry, we hope to encourage neurologists – who often serve as the central point of contact – to collaborate closely and actively engage multidisciplinary team members in the management of these complex patients.

Following spinal cord injury (SCI), a complex lesion scar forms at the injury site that matures and remodels over weeks, profoundly influencing neural repair and functional recovery. This lesion consists of a fibrotic scar at its core surrounded by an astrocytic scar (or border). While the astrocytic scar has been extensively studied for decades, the fibrotic scar has only recently emerged as a critical player in post-injury pathophysiology. Fibrotic scarring plays a dual role: it contributes to tissue stabilization and limits secondary damage, yet its persistence can pose a barrier that inhibits axonal regeneration and hinders recovery. Despite growing interest, key aspects of fibrotic scar formation and function remain poorly understood. This review synthesizes the current knowledge of fibrotic scarring after SCI, including its temporal progression, cellular composition, molecular mechanisms, and interactions with other cell types at the injury site, and we discuss emerging therapeutic strategies targeting fibrosis. We further highlight critical knowledge gaps and outline future directions to define how fibrotic scarring shapes the injury microenvironment and influences neural repair.

Machine learning enables scalable quantification of neuropathology, offering deeper phenotyping of Alzheimer's disease (AD). In this validation study, we quantified amyloid-beta (Aβ) deposits, evaluating multiple brain regions across institutions, and evaluated associations with clinical, demographic, and genetic factors in persons pathologically diagnosed with AD. All linear models were adjusted for sex, age of death, ethnicity, and center. We analyzed densities (#/mm2) of cored plaques, diffuse plaques, and cerebral amyloid angiopathy (CAA) in 273 individuals from 3 Alzheimer's Disease Research Centers. Formalin-fixed paraffin-embedded sections of frontal, temporal, and parietal cortices were immunostained and digitized, generating 799 whole-slide images (WSIs). Following log transformation, mixed-effects modeling revealed the parietal cortex had the highest cored plaque densities (P < .001); the temporal cortex had the highest diffuse plaque (P < .001); CAA showed no regional differences. Wilcoxon rank-sum test, and covariates adjusted linear models showed ApoE ε4- status was associated with higher cored plaque densities in the temporal lobe (P = .04). ApoE ε4+ status was associated with diffuse plaques in the temporal lobe (P = .001), and CAA in the frontal lobe (P = .004). These findings provide further validation and provide exploratory associations advancing deeper phenotyping of AD.

Characterizing neural connectivity at transcriptomic cell-type resolution is essential for understanding neural mechanisms of circuit function. Here, we present single transcriptome assisted rabies tracing (START), a protocol combining monosynaptic rabies tracing with single-nucleus RNA sequencing to identify transcriptomic cell types providing inputs to defined neuronal populations in the mouse cortex. We describe steps for Cre-dependent helper virus injection, EnvA-pseudotyped rabies infection, tissue microdissection, and fluorescence-activated nuclei sorting. We then detail procedures for library preparation and computational annotation of nuclei. For complete details on the use and execution of this protocol, please refer to Patiño et al.¹.