Citations

Background/Objectives: Speech and motor control share overlapping neural mechanisms, yet their quantitative relationships in Parkinson’s disease (PD) remain underexplored. This study investigated bidirectional associations between acoustic voice features and objective motor metrics to better understand how vocal and motor systems relate in PD. Methods: Cross-sectional baseline data from participants in a randomized neuromodulation trial were analyzed (n = 13). Motor performance was captured using an Integrated Motion Analysis Suite (IMAS), which enabled quantitative, objective characterization of motor performance during balance, gait, and upper- and lower-limb tasks. Acoustic analyses included harmonic-to-noise ratio (HNR), smoothed cepstral peak prominence (CPPS), jitter, shimmer, median fundamental frequency (F0), F0 standard deviation (SD F0), and voice intensity. Univariate linear regressions were conducted in both directions (voice ↔ motor), as well as partial correlations controlling for PD motor symptom severity. Results: When modeling voice outcomes, faster motor performance and shorter movement durations were associated with acoustically clearer voice features (e.g., higher elbow flexion-extension peak speed with higher voice HNR, β = 8.5, R2 = 0.56, p = 0.01). Similarly, when modeling motor outcomes, clearer voice measures were linked with faster movement speed and shorter movement durations (e.g., higher voice HNR with higher peak movement speed in elbow flexion/extension, β = 0.07, R2 = 0.56, p = 0.01). Conclusions: Voice and motor measures in PD showed significant bidirectional associations, suggesting shared sensorimotor control. These exploratory findings, while limited by sample size, support the feasibility of integrated multimodal assessment for future longitudinal studies.

Abstract High‐titer glutamic acid decarboxylase 65 (GAD65) antibodies (>20 nmol/L) are linked to chronic focal epilepsy, usually of temporal regional onset. Identification of these antibodies has treatment and prognostic implications. We compared patients with drug‐resistant epilepsy and high‐titer GAD65 antibodies to an age‐ and sex‐matched control group with drug‐resistant GAD65 antibody–negative temporal lobe epilepsy. From 1432 patients presented at a single‐center surgical epilepsy conference (2007–2024), we identified 15 patients (1% from surgical epilepsy conference: 13 female, 86.7%) with high‐titer serum GAD65 antibodies (median serum titer = 960 nmol/L; range 34–4678). The median age at epilepsy onset was 25 years (range 4–44). All had temporal regional‐onset epilepsy; 53% had bitemporal seizures. Three patients had limbic encephalitis, and three developed mesial temporal sclerosis. Those with GAD65 antibody–associated epilepsy were more likely to have depression and/or anxiety and less likely to undergo resection after evaluation than those in the control group. Although seizure types, electroencephalography (EEG), imaging, and autoimmune history were not statistically significantly different from the control group, we found that musicogenic seizures, limbic encephalitis, and type 1 diabetes occurred only in GAD65‐positive patients. These features, when present, may suggest an autoimmune etiology and warrant antibody testing. Identifying patients with GAD65 antibody–associated epilepsy is important due to its drug resistance, lower rate of satisfactory surgical outcomes, and potential responsiveness to immunotherapy. Further research is needed to define the optimal treatment and distinguish this subgroup from other causes of drug‐resistant epilepsy.

Artificial intelligence (AI) is revolutionizing interventional pulmonology (IP) by enhancing diagnostics, procedural precision, and patient outcomes. AI-powered tools improve lung nodule detection, radiomics-based risk stratification, and bronchoscopic navigation. Machine learning (ML) algorithms aid in lung cancer screening by analyzing imaging data, reducing false positives, and improving early diagnosis. AI-driven robotic-assisted bronchoscopy enhances navigation and biopsy accuracy, particularly for peripheral lung lesions. Endobronchial ultrasound (EBUS) and cytopathology benefit from AI’s ability to assess lymph node malignancy and optimize rapid on-site evaluation (ROSE). AI applications extend to phenotyping chronic obstructive pulmonary disease (COPD) and identifying candidates for bronchoscopic lung volume reduction (BLVR). Deep learning (DL) models analyze computed tomography (CT) imaging and spirometry data to optimize patient selection. AI-driven algorithms are also advancing pleural effusion detection, differentiation, and classification, supporting clinical decision-making. Education and research in IP are also transforming with AI-driven simulation, virtual reality, and automated assessment tools that enhance procedural training and competency evaluation. The integration of AI into clinical work and procedural training accelerates advancements while presenting challenges in ethical AI implementation, data security, and bias mitigation. As AI continues to evolve, its role in IP will expand, improving procedural efficiency, personalizing treatment plans, and optimizing patient selection for interventions. Future developments will focus on refining AI-driven predictive analytics, enhancing robotic-assisted procedures, and integrating AI seamlessly into clinical workflows. The responsible implementation of AI in IP holds the potential to transform patient care, reduce complications, and advance precision medicine.

ABSTRACT Photogrammetry has emerged as a powerful tool in medical education, offering precise and cost‐effective 3D anatomical models that enhance spatial learning and accessibility. This systematic review synthesizes evidence from forty‐eight (48) peer‐reviewed studies (2000–2025) to evaluate photogrammetry's applications, technical workflows, and educational outcomes in anatomy and surgical training. Findings demonstrate its effectiveness across training levels, with high learner satisfaction (e.g., 96.4% preference over traditional methods) and sub‐millimeter accuracy in rendering complex structures like neuroanatomy and musculoskeletal systems. Photogrammetry's adaptability for remote learning and specimen preservation addresses critical gaps in resource‐limited settings. However, challenges persist, including the lack of tactile feedback and difficulties in visualizing deep anatomical relationships. Future directions should focus on integrating artificial intelligence (AI)‐assisted processing, hybrid digital–physical models, and immersive technologies like virtual reality (VR)/augmented reality (AR) to bridge these gaps. By balancing innovation with evidence‐based implementation, photogrammetry can further solidify its role as a transformative adjunct in modern medical curricula.

Abstract Background Alzheimer's disease (AD) exhibits significant genetic heterogeneity, with no single model fully explaining its inheritance pattern. Structural variants (SVs) may contribute to the missing heritability of AD, particularly in disease pathology and familial AD, which remain largely unexplored. Method Structural variants (SVs) were analyzed in unrelated 1,162 individuals from the ROSMAP study (687 cognitively normal (CN), 475 AD patients), as well as 197 Non‐Hispanic White (NHW) families (926 individuals, 58.5% with AD) and 214 Caribbean Hispanic (CH) families (1,340 individuals, 59.17% with AD). Large insertions and deletions were identified using Manta, Absinthe, and MELT from whole‐genome sequencing, supplemented by Sniffles2 and external SV call sets. This approach generated a unified VCF file containing 45,251 insertions and 76,566 deletions. After filtering for missingness rate and allele counts, a total of 9,290 insertions and 9,529 deletions were retained for analysis. Genome‐wide SV analyses were performed with AD‐related metrics in ROSMAP, adjusting for age, sex, and principal components, and validated in an independent ADSP replication cohort comprising 29,055 unrelated individuals (17,110 CN and 11,945 AD patients). Result We identified nine SVs (one insertion and eight deletions) segregating in AD families. An insertion near PDCD10 in NHW families reached genome‐wide significance ( p <5×10 ‐8 ) for AD risk in the replication cohort. Two deletions in KIF26B and SPHKAP were found in both CH and NHW families, while five appeared only in NHW and one in CH. All eight deletions showed genome‐wide significance for AD risk. SV GWAS on AD pathologies in ROSMAP revealed an insertion in INPP4B with the strongest association to global brain pathology (β=0.19; p = 2.32×10 ‐5 ), also linked to pathological AD, diffuse plaques, and Braak staging. A deletion near ADGRB1 (β=1.53; p = 5.05×10 ‐6 ) was associated with neuritic plaques, and another near ARMC2 (β=1.66; p = 2.17×10 ‐6 ) was linked to diffuse plaques. All three SVs associated with AD ( p <5×10 ‐6 ) in replication. Conclusion Our findings reveal numerous SVs segregating in familial AD across both CH and NHW families, as well as additional SVs linked to sporadic AD. Prioritizing these SVs based on their potential effects on gene function and expression will provide deeper insight into their contributions to both familial and sporadic AD.

Abstract Background Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy associated with repetitive head impacts (RHI). Autopsy studies show that RHI influences risk for other later‐life neuropathologies, particularly white matter and vascular injury. We have observed a unique pattern of white matter hyperintensities (WMH) on FLAIR MRI in people exposed to RHI (RHI‐WMH) characterized by small, discrete lesions near the depths of sulci (Figure 1a). The objective of this study was to characterize this pattern empirically in former American football players and to investigate neuropathology co‐localizing with the WMH. Method The sample included 164 male former football players ( n = 111 professional, n = 53 college) and 55 asymptomatic males without RHI from the DIAGNOSE CTE Project (Table 1). Visual ratings of WMH blind to the participant's RHI and clinical status were conducted to count lesions that were a.) within 1.0cm of the gray/white matter boundary, b.) as bright as the cortex, c.) spherical and d.) <1.0cm in size. ANCOVA compared groups on total number of WMH adjusted for age and vascular risk factors. We selected one individual (former professional player) with the typical RHI‐WMH pattern and who donated their brain for neuropathological examination. Guided by in vivo MRI, ex vivo MRI was done to locate the WMH near the depths of the sulci in the tissue. Tissue sections were tested for phosphorylated tau immunoreactivity and reactive astrocytes and microglia in areas surrounding the lesion seen on MRI. Result Number of RHI‐WMH was greater in football players compared to controls ( p = 0.007) (Figure 1b). Number of RHI‐WMH was greater in former professional players compared to controls ( p = 0.001) but not compared to the college players ( p = 0.983). In the neuropathology case study, we located the punctate RHI‐WMH on ex vivo MRI. Immunostaining revealed that the RHI‐WMH was adjacent to a sulcus with the pathognomonic CTE p ‐tau lesion and was characterized by myelin pallor, dense GFAP‐positive glial scarring, and increased total and activated microglia (Figure 2). Conclusion We provide empirical support for exposure to RHI as potentially leading to a unique pattern of WMH. Importantly, histopathological evidence showed that the RHI‐WMH co‐localized with RHI and CTE‐related neuropathologies at the depths of the sulci.

Abstract Background Individuals living in socioeconomically disadvantaged areas are disproportionately affected by dementia. However, the pathway leading from neighbourhood deprivation to cognitive symptoms is not well understood. To test our hypothesis that this relationship is associated with cerebral small vessel disease (SVD), we examined (1) whether neighbourhood deprivation related to midlife SVD burden and cognition, and (2) whether these links can be explained by modifiable lifestyle risk factors. Method In this multi‐centre cross‐sectional study, 514 cognitively healthy midlife participants aged 40‐59 years (median 52 years, 64.6% female) underwent clinical assessment and 3T MRI. Postcode data were used to obtain national indices of neighbourhood deprivation. To quantify SVD, we assessed white matter hyperintensities (WMH), perivascular spaces, cerebral microbleeds, and lacunes. Cognition was assessed using the Computerized Assessment of Information Processing (COGNITO) battery. Lifestyle risk factors were evaluated based on clinical data. Using multivariate statistics like structural equation modelling (SEM) and canonical correlation analysis (CCA), we examined associations between these constructs both globally and at the item‐level (i.e., distinction between domains of cognition/deprivation), to shed light on specific domains that could inform targeted prevention strategies. Result Neighbourhood deprivation related to greater prevalence of lifestyle risk factors ( r = 0.36, p < .001), greater SVD burden (b=0.18, p = .01; Figure 1), and greater cognitive impairment ( r = 0.36, p < .001), independent of educational attainment, sex, and age. These links with neighbourhood deprivation were largely driven by lifestyle factors relating to vascular health (sleep, physical activity, obesity, hypertension) (Figure 2), and cognitive deficits consistent with SVD (processing speed, visuospatial) (Figure 3). Residents of deprived neighbourhoods displayed greater prevalence of lifestyle risk factors, except alcohol consumption. Lower cognitive scores were most closely associated with deprivation domains of Crime and Living Environment (Figure 3). The DEPRIVATION→SVD path was mediated by lifestyle risk factors (z=2.57, p = .010), and the DEPRIVATION→COGNITION path was mediated by SVD (z=‐2.14, p = .032) (global SVD & hypertensive subtype, but not CAA‐SVD). Conclusion The pathway linking neighbourhood disadvantage to cognitive impairment at midlife is influenced by vascular risk factors and cerebrovascular burden. Tailored strategies could promote resilience against dementia by promoting health behaviours aligned with the community's unique needs.

Hearing loss is a highly prevalent disease state affecting almost 1 in 5 individuals globally. Growing research shows that untreated or undertreated hearing loss carries significant long-term sequelae, including increased risk of social isolation, depression, and cognitive decline, among other ramifications. Limited awareness and common misperceptions among the general US adult population and primary care providers contribute to low rates of referral to hearing specialty clinics and underutilization of hearing aids, cochlear implants, and other rehabilitative devices. Comprised of diverse membership, the Hearing Health Collaborative (HHC) was formed in May 2021 to identify and overcome challenges impacting good health care practices and public policy on hearing care in connection with healthy aging. This editorial documents a recent outcome of the HHC derived from a structured A3 process. Specifically, initiative 2, a proposal to develop a simple, clinically anchored staging system primarily for use by frontline providers and patients, is presented. Unlike other common disorders that harbor long-term health sequelae, a corresponding pragmatic clinical staging system—leveraging precedent disease staging convention, based on clinically meaningful outcomes and prognosis for acquired hearing loss—does not exist. The development of this staging system will potentially allow for improved communication across providers and patients, facilitate referral pathways, and ultimately enable patient access to timely and appropriate care.

Background and Objectives: Autosomal dominant polycystic kidney disease (ADPKD) is characterized by multisystem involvement, including renal cysts, hepatic cysts, intracranial aneurysms, and aortic root dilatation and dissection. Though exceedingly rare, cervical artery dissections (CeAD) have been reported in association with ADPKD. The aim of this retrospective observational study is to investigate clinical features in patients with ADPKD that increase the probability of an associated CeAD diagnosis. Materials and Methods: The National Inpatient Sample from 2016 to 2020 was utilized to compare clinical features for patients with an ICD-10 code diagnosis of ADPKD, CeAD, and both ADPKD and CeAD. The Cochran–Armitage test and Chi-square test were utilized to assess clinical features or trends in ADPKD patients associated with a concurrent CeAD diagnosis. Results: Between 2016 and 2020, there were 224,065 people with ADPKD, 86,135 with CeAD and 155 with both (0.05%). The total cohort had a mean age of 56.74 years, with 47.26% female participants (p = 0.70), and was predominantly white (66.15%, p < 0.001). In patients with ADPKD, comorbid acute ischemic stroke (p < 0.001), transient ischemic attack (p < 0.001), aortic dissection (p < 0.001), coronary artery dissection (p < 0.001), subarachnoid hemorrhage (p < 0.001), coagulation defects (p = 0.002), and hypertension (p < 0.001) are risk factors associated with an increased probability of concomitant CeAD. Conclusions: CeAD in ADPKD patients is rare. In ADPKD patients, acute ischemic stroke, transient ischemic attack, aortic dissection, coronary artery dissection, subarachnoid hemorrhage, coagulation defects, and hypertension are risk factors of concomitant CeAD. Recognizing these factors can aid in the decision to screen for concomitant CeAD in patients with ADPKD.