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Abstract Background Ultra‐high‐field 7 Tesla (7T) magnetic resonance imaging (MRI) provides improved resolution and signal‐to‐noise ratio (SNR) over standard clinical field strengths (1.5T, 3T). However, 7T scanners are costly, scarce, and introduce additional challenges such as susceptibility artifacts. Purpose We propose an efficient transformer‐based model (7T‐Restormer) to synthesize 7T‐like MRI (quantitative T1 MP2RAGE maps) from routine 1.5T or 3T T1‐weighted (T1W) images. Methods The proposed method leverages an efficient restoration transformer backbone and spatial attention layers to capture long‐range dependencies and generate high‐quality 7T‐like images. Our model was validated on an institutional dataset, comprised of 35 1.5T and 108 3T T1w MRI paired with corresponding 7T T1 maps of patients with confirmed multiple sclerosis (MS). A total of 141 patient cases (32 128 slices) were randomly divided into 105 (25 1.5T and 80 3T) training cases (19 204 slices), 19 (5 1.5T and 14 3T) validation cases (3476 slices), and 17 (5 1.5T and 12 3T) test cases (3145 slices). The synthetic 7T T1 maps were evaluated by comparing their similarity to the ground truth volumes using peak signal‐to‐noise ratio (PSNR), structural similarity index measure (SSIM), and normalized mean squared error (NMSE), and were compared against ResViT and ResShift. In addition, a blinded reader study was performed in which three clinicians scored the diagnostic image quality of each method on a 5‐point Likert scale (1 = non‐acceptable, 5 = excellent). Statistical significance ( α = 0.05) was assessed using two‐sided paired t ‐tests with Holm correction for multiple comparisons and Wilcoxon signed‐rank tests with Holm correction for reader scores. Effect sizes (Cohen's for paired data) were also computed to quantify practical significance. We interpreted and as small, medium, and large effects. Results For 1.5T inputs, 7T‐Restormer achieved an NMSE of 0.018 ± 0.003, PSNR of 25.0 ± 0.6 dB, and SSIM of 0.870 ± 0.019; for 3T inputs, the corresponding values were 0.019 ± 0.006, 24.5 ± 1.2 dB, and 0.874 ± 0.027. Across both field strengths, 7T‐Restormer provided the lowest NMSE and highest PSNR and SSIM among the three methods, reducing NMSE by approximately 5% and 25% relative to ResShift and ResViT at 1.5T and by 14% and 24% at 3T, respectively, and increasing PSNR by 0.5–1.5 dB (Holm‐adjusted p < 0.05, paired Cohen's = 1.37–6.84). Training on mixed 1.5T+3T data improved performance for 1.5T inputs compared with 1.5T‐only training (e.g., NMSE 0.018 vs. 0.019; p = 0.001, ), without degrading performance for 3T inputs ( p = 0.630, for NMSE). In the blinded reader study, 7T‐Restormer received higher diagnostic quality scores (3.50 ± 0.28) than ResShift (3.00 ± 0.27) and ResViT (2.33 ± 0.27), corresponding to mean improvements of 0.5–1.2 points on the 5‐point scale (Holm‐adjusted p = 0.014 and 0.004; paired Cohen's and 3.24, respectively). Conclusion We propose a novel method for predicting quantitative 7T MP2RAGE maps from 1.5T and 3T T1W scans with higher quality than existing state‐of‐the‐art methods. Future development and application of our approach may enhance diagnostic accuracy, treatment planning, and facilitate downstream tasks by making the benefits of 7T MRI more accessible to standard clinical workflows.

Abstract INTRODUCTION Research into cognitive dispersion – a cognitive process score measuring the intra‐individual variability (IIV) across a single testing session – suggests utility in neurodegenerative populations. Given widespread deficits observed in sporadic early‐onset Alzheimer's disease (EOAD), however, it is unclear if examining cognitive dispersion shows benefit in this condition. METHODS A total of 309 participants (188 amyloid‐positive EOAD, 43 amyloid‐negative early‐onset dementia [EOnonAD], 78 cognitively normal [CN]) completed neuropsychological testing twice over 12 months. Dispersion‐related differences among groups were assessed, as was cognitive dispersion's capacity to predict domain‐specific cognitive trajectories, and its convergence with imaging biomarkers. RESULTS EOAD participants displayed higher cognitive dispersion than EOnonAD participants, and associations with EOAD‐specific biomarkers. Additionally, cognitive dispersion was associated with 12‐month reliable change across several cognitive domains. DISCUSSION These preliminary results examine cognitive dispersion in sporadic EOAD. When used with baseline cognitive performance, cognitive dispersion measures may enrich future clinical trials in EOAD by enhancing treatment monitoring over time.

Abstract The growing availability of large-scale biomarker datasets has allowed data-driven methods to characterize Alzheimer’s disease biological heterogeneity. However, most prior studies have focused on cohorts of late-onset amnestic cases, leaving early-onset Alzheimer’s disease underexplored. We aimed to characterize tau-PET-based subtypes through a robust data-driven approach in the Longitudinal Early-Onset Alzheimer’s Disease Study. Baseline [18F]Flortaucipir PET scans from 365 amyloid-PET-positive participants with sporadic early-onset Alzheimer’s disease were quantified in the left and right medial temporal, lateral temporal, occipital, parietal, and frontal cortices. Tau PET values were z-scored against 85 amyloid-PET-negative cognitively normal age-matched participants and fitted into Subtype and Stage Inference (SuStaIn)—an unsupervised clustering algorithm that simultaneously models subtypes and progression from cross-sectional data. The derived subtypes were subsequently characterized by baseline and longitudinal clinical, cognitive, MRI, tau and amyloid PET features. We identified three tau-PET-based subtypes: on average, Subtype 1/Typical (n = 144, 40%) showed a predominant bilateral temporoparietal pattern typical of Alzheimer’s disease. Subtype 2/Left temporal (n = 111, 31%) showed predominant left temporal binding. Subtype 3/Posterior (n = 104, 29%) showed early and permeating occipitoparietal involvement. Subtypes did not differ in demographics or global amyloid burden, but were relatively more enriched for specific clinical presentations: S1/Typical for amnestic presentations, S2/Left Temporal for primary progressive aphasia, and S3/Posterior for posterior cortical atrophy. Baseline tau PET subtypes aligned with cortical atrophy patterns and domain-specific cognitive impairment. When follow-up tau PET scans were fitted to SuStaIn trained on baseline data, 85.6% (n = 172/201) of participants retained the same subtype classification, indicating subtype temporal stability, and progressed within subtypes by 0.56 ± 0.70 SuStaIn stage/year. Longitudinal voxel-wise linear mixed-effects modelling revealed tau accumulation patterns for each subtype in regions relatively spared at baseline: occipital lobe accumulation predominated in S1/Typical, bilateral frontal and right temporal in S2/Left Temporal, and bilateral frontotemporal lobes in S3/Posterior. All subtypes showed longitudinal increases in Clinical Dementia Rating-Sum of Boxes, but with slower worsening in S3/Posterior compared with the other subtypes. Our findings reveal robust subtypes in sporadic early-onset Alzheimer’s disease characterized by distinct spatiotemporal tau patterns that parallel differences in clinical presentations and trajectories of neurodegeneration. These subtypes extend beyond traditional clinical syndromes and support a more nuanced framework for individualized prognosis and care. Incorporating tau PET subtyping into clinical trial design could enable more targeted therapeutic approaches for this younger population.

Augmented cardiovascular responses to spontaneous nocturnal arousals were previously shown in chronic short-sleeping adults, without known sex differences. Sustained 4-h sleep restriction produced a sex-dependent alteration in heart rate responses to arousals and resulted in a prolonged reduction in postarousal pulse transit time in females only. These findings yield the first sex-specific characterization of nocturnal cardiovascular responses to spontaneous arousals following sleep restriction, and may place females at greater sleep truncation-related cardiovascular disease risk.

Abstract Introduction Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia strongly associated with α-synucleinopathies, most commonly Parkinson’s disease (PD). Among Veterans, posttraumatic stress disorder (PTSD) is common and may influence RBD presentation and outcomes. The extent to which PTSD modifies demographic, medical, and mortality profiles in Veterans with RBD, and how these differ from those with RBD and Parkinson’s disease (PD), remains poorly characterized. Methods We conducted a retrospective cohort study using the Veterans Health Administration Corporate Data Warehouse. Veterans with at least one ICD-9 or ICD-10 diagnostic code for RBD were identified between 1999 - 2020 and categorized into three, mutually-exclusive groups based on the presence or absence of co-occurring ICD codes: RBD-only, RBD+PTSD, or RBD+PD. Demographics, comorbidities (Charlson Comorbidity Index [CCI]), and mortality outcomes were compared using logistic regression models adjusted for age, sex, race/ethnicity, BMI, and CCI. Results The cohort included 11,283 Veterans with RBD only, 17,527 with RBD+PTSD, and 5,675 with RBD+PD. Veterans with RBD+PTSD were younger (mean 58.9 ± 14.9 y) and had higher psychiatric comorbidity (94.2%) compared to RBD only (54.2%) or RBD+PD (46.5%). Those with RBD+PD were older (73.6 ± 8.1 y), predominantly male (98.9%), and had the highest neurological comorbidity (92.6%). Unadjusted mortality was lowest in RBD+PTSD (15.3%) and highest in RBD+PD (53.6%). Adjusted models showed reduced mortality risk for RBD+PTSD (aOR 0.73, 95% CI 0.70–0.80, p &lt; 0.001) and increased risk for RBD+PD (aOR 2.43, 95% CI 2.3–2.6, p &lt; 0.001) vs. RBD alone. Higher age, male sex, and greater comorbidity independently predicted mortality. Conclusion In this large national VA cohort, comorbid PTSD and Parkinson’s disease were associated with distinct demographic and clinical profiles among Veterans with RBD. RBD+PTSD was linked to younger age, greater psychiatric burden, and lower mortality. These findings underscore the heterogeneity of RBD in Veterans and support stratified approaches to surveillance for synucleinopathy and trauma-related sleep disturbances. Support (if any) VA CDA # IK2CX002363-01A1 (MJ); NHLBI K25 #1K25HL152006-01 (JR)

Abstract Introduction Isolated REM sleep behavior disorder (iRBD) is characterized by loss of normal REM sleep atonia and dream enactment behavior. iRBD is strongly associated with α-synucleinopathies and risk for developing Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA), yet phenoconversion risk for long-term outcomes of younger women and men remains undefined. We aimed to ascertain longitudinal outcomes and phenoconversion risk in the Mayo Clinic iRBD cohort. Methods Eighty-nine of 165 registry participants with at least one-year follow-up were included. Retrospective chart review attained baseline demographics, age at presentation, baseline Timed Up and Go (TUG) and Montreal Cognitive Assessment (MoCA) scores, and phenoconversion status (iRBD, PD, DLB, mild cognitive impairment [MCI], MSA, or other). Kaplan–Meier survival analysis and Cox proportional hazards modeling were analyzed with alpha at p &lt; 0.05. Results 68 men and 21 women had a mean age of 63 years at polysomnographic diagnosis. At follow-up, 64 (71.9%) remained iRBD; 7 (7.9%) developed PD, 11 (12.4%) developed DLB, 3 (3.4%) developed MCI, 1 (1.1%) developed MSA, and 3 (3.4%) developed another dementia. Abnormal TUG (&gt;12 seconds) occurred in 5.9% and abnormal MoCA (&lt; 24) in 23.3%. Phenoconversion rates were similar in women and men (p = 0.44). Older age at PSG predicted phenoconversion, corresponding to a two-fold increase in risk with each 10-year increase (HR 2.00, 95% CI 1.15–3.52). Neither abnormal TUG nor MoCA predicted conversion. Cumulative phenoconversion was approximately 1% at 1 year, 7% at 3 years, 10% at 5 years, 30% at 10 years, 34% at 12 years, and 49% at 15 years. Mean and median time to phenoconversion was 7 years (range, 1-18 years). Conclusion We found that iRBD phenoconversion rates were lower than historically reported. Only age at presentation predicted phenoconversion, with risk doubling per decade. At 12 years, cumulative phenoconversion rate was approximately 34%. Support (if any)

Abstract Introduction Hypoglossal nerve stimulators (HGNS) are used in patients with moderate-to-severe obstructive sleep apnea (OSA) who are unable to tolerate or do not respond to continuous positive airway pressure (CPAP) therapy. However, a subgroup of patients fail to achieve resolution of OSA with HGNS alone. Previous studies have shown that lower BMI, lower nadir oxygenation, decreased sleep latency, and higher VOTE score on drug-induced sleep endoscopy (DISE) predict better treatment outcome. We hypothesize that baseline diagnostic polysomnography (PSG) may further predict which patients will achieve successful therapeutic outcome with HGNS therapy. Methods We conducted a retrospective analysis of all adult patients who underwent HGNS implantation at Mayo Clinic Arizona between 2019-2025 and had a pre-implantation diagnostic PSG available for review. Treatment success was defined by Sher Criteria: &gt;50% reduction in post-treatment apnea hypopnea index (AHI) to a final AHI of &lt; 20/hr. Responders met Sher criteria and non-responders did not meet Sher criteria. Demographics, sleep questionnaire results, PSG variables, and VOTE score on DISE were collected and analyzed using Spearman’s rank correlation of reduction in AHI. Results Twenty-three patients (11M/12F, median age: 69[IQR:64,75] years) met inclusion criteria. Median baseline AHI was 24[IQR:19,37]/hr. Median post-implant AHI was 8 [IQR:3, 14]/hr. Responders (n=15, 65%) and non-responders (n=8, 35%) demonstrated median post-implant AHI of 4.5[IQR:2.3,7.3]/hr and 15.7[IQR:12.3,28.5]/hr, respectively. Treatment response was associated with less time with SpO2 &lt; 88% (T88%) (21min [IQR:3,64] vs. 73[IQR:36,105mins]; p=0.023) and higher central apnea index (CAI) (1[IQR:0.1,3] vs. 0[IQR:0,1], p=0.03) on pre-implantation PSG. Conclusion In this small cohort of OSA patients, less nocturnal hypoxemia as defined by T88% and higher baseline central apnea index were predictors of better treatment response to HGNS therapy as measured by Sher criteria. We hypothesize that greater nocturnal hypoxemia likely reflects more severe airway obstruction during sleep. Our analysis also showed that responders had higher baseline CAI than non-responders, however we believe this association is not clinically significant and likely driven by one outlier (CAI 13/hr). Further analysis in a larger HGNS cohort is needed to confirm these findings. Data enrichment efforts and more sophisticated analyses are underway. Support (if any)

Abstract Introduction The relationship between sleep and brain metabolism remains unclear. This study aimed to examine whether overnight sleep features, using a home sleep apnea system based on peripheral arterial tonometry, are associated with regional FDG-PET changes in older adults. Methods We analyzed cognitively unimpaired adults (≥60 years) from the Mayo Clinic Study of Aging (MCSA) cohort who were not receiving sleep apnea treatment. Participants underwent overnight sleep assessment with the WatchPAT system, followed by FDG-PET imaging the next morning. FDG-PET data were co-registered to 3T MRI and automatically segmented into 122 anatomical regions. PET signal was referenced to the pons (SUVR). We computed voxel-weighted median FDG signal across 47 bilateral cortical and subcortical regions of interest (ROIs), excluding brainstem and cerebellum. Associations between sleep architecture and sleep apnea/hypoxemia burden and regional metabolism were assessed using partial Spearman’s rank correlation, adjusting for age. Results Thirty-seven participants were included (70.3% female; median [IQR] age: 72.0 [68.0–78.0] years). Wake after sleep onset (WASO) showed widespread negative associations with FDG uptake in cortical regions (p&lt; 0.05), particularly the ventromedial/ventrolateral (rs=–0.47 to –0.33) prefrontal cortex, lateral temporal (rs=–0.38 to –0.33), and occipital (rs=–0.47 to –0.37) cortices. Total sleep time (TST) was positively associated with medial structures (p&lt; 0.05), including the posterior cingulate (rs=0.39), retrosplenial cortex (rs=0.48), hippocampus/parahippocampal (rs=0.34 to 0.36), calcarine cortex (ρ=0.38), thalamus (rs=0.37), and caudate (rs=0.43). Hypoxic burden was positively associated with medial occipital regions (rs=0.35 to 0.39) and AHI-4% with cuneus (rs=0.33). Regional gray matter volume did not mediate these associations. WASO correlated with Insomnia Severity Index (rs=0.43, p=0.008) and self-reported refreshing sleep (rs=0.046). Conclusion Overnight sleep macrostructure features (WASO and TST) and hypoxic burden are significantly associated with brain metabolism, potentially underlying symptoms of sleep disturbance and cognitive aging. Support (if any) Mayo Clinic Alzheimer’s Disease Research Center Development Award (P30 AG062677), R01 AG056366, U01 AG006786, R01 AG056366, R01 AG034676, R37 AG011378, R01 AG041851, R01 NS097495, R01 AG068206, P30 AG062677, R01 HL065176. CLARA project work with funding from the European Union’s HORIZON EUROPE research and innovation programme (No 101136607).

Importance Hospital-based shootings represent an extreme form of workplace violence, with notable consequences for staff, patients, and visitors. Despite growing concern, these events remain poorly understood. Objective To categorize hospital-based shootings from 2012 to 2024 and incorporate prior published events between 2000 and 2011 to examine trends in shootings over a 25-year span. Evidence Review Events in this systematic review of acute care hospital–based shootings in the US from January 1, 2012, through December 31, 2024, with subgroup analysis of previously published data trending shootings over 25 years (January 1, 2000, through December 31, 2024), were identified using EBSCO Regional Business News, ProQuest US Newsstream Collection, Gun Violence Archive, and Google News Search. Selected shooting events involved at least 1 injured person (a nonperpetrator or perpetrator) that occurred within or on the immediate property of the hospital. Findings A total of 327 news articles of unique hospital-based shooting events (5.2 per year per 1000 hospitals) were included from a review of 6658 articles, spanning 47 US states (94.0%). There was an overall incidence of 25.2 hospital-based shootings per year. Between 2012 and 2024, shootings increased by a mean (SD) of 1.7 (0.5) events per year, from 14 to 34 events (8.4% increase per year). Large hospitals accounted for the highest rate of shootings (258.1 events per 1000 hospitals). Events primarily occurred in urban settings (314 [96.0%]), and 161 (49.2%) occurred in the US South. Nearly one-third (105 [32.1%]) were potentially preventable by weapons screening. From 2000 to 2024, shootings increased by a mean (SD) of 1.1 (0.2) events per year, from 6 to 34 events (6.4% increase per year). A positive correlation was found in annual firearm fatalities in hospital settings and US firearms fatalities overall between 2012 and 2023 ( r = 0.42). Conclusions and Relevance This systematic review found that hospital-based shootings in the US have increased steadily over the past 25 years, representing an intersection between broader national trends in workplace and firearm violence. Large hospitals, those in the US South, and hospitals in urban communities are particularly at-risk settings. These findings underscore the need for hospital-specific prevention strategies, including consideration of weapons screening technology, alongside broader societal efforts to address rising firearm violence.

Abstract INTRODUCTION : Despite expanding use of plasma biomarkers for Alzheimer's disease (AD), minimal examination has been undertaken in early‐onset AD (EOAD). Prior analyses assessed criterion and convergent validity of common plasma biomarkers in a well‐characterized sample with sporadic EOAD. METHODS : Plasma amyloid beta (Aβ) 42/40, tau phosphorylated at threonine 231 (p‐tau231), glial fibrillary acidic protein (GFAP), and neurofilament light change (NfL) levels were obtained for 189 EOAD, 52 early‐onset non‐AD (EOnonAD), and 83 cognitively normal (CN) participants. Diagnostic group differences, convergence with imaging biomarkers, and the capacity to predict specific cognitive domains were investigated. RESULTS : After controlling for cognitive status, EOAD participants exhibited more pathologic levels of Aβ42/40, p‐tau231, and GFAP relative to EOnonAD participants. However, NfL displayed the greatest sensitivity to non‐amnestic cognitive impairment across the sample. DISCUSSION : These results establish criterion and convergent validity of plasma biomarkers in sporadic EOAD and highlight complementary roles that AD‐specific and non‐specific plasma markers may play across the course of AD care.