Citations

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.

Combined histopathological and metabolomic analysis of the same tissue specimen can reduce biological variability compared to independent analyses of similar samples. However, conventional workflows are incompatible: tissue fixation leads to metabolite loss through dilution and chemical reactions with fixative, while metabolomic extraction typically destroys the specimen. We propose a method that reconciles these conflicting requirements by enabling metabolite recovery from fixative while preserving tissue for histopathology. In this approach, tissue is initially fixed in a small volume of fixative; an aliquot of the fixative is then collected for nuclear magnetic resonance-based metabolomic analysis before additional fixative is added for standard processing. As a proof-of-concept, mouse kidneys from the same subject were analyzed using two protocols: standard perchloric acid extraction (ensuring complete metabolite recovery but destroying tissue) and metabolite extraction from fixative. Several metabolites were fully recoverable from the fixative, others partially, while some were lost due to chemical reactions. Despite some limitations, this strategy may be useful for analyzing precious specimens, such as human biopsies, that must remain intact for further studies. Moreover, using the same specimen for dual analyses reduces the number of animals required and enhances statistical robustness.

Abstract INTRODUCTION Sleep and circadian rest–activity rhythm (RAR) disruption may bidirectionally relate to Alzheimer's disease (AD). Down syndrome (DS), the most common genetic cause of AD, presents sleep disorders, yet RAR patterns across the DS‐associated AD continuum remain uncharacterized. METHODS We analyzed 7‐day wrist actigraphy in 140 adults with DS (108 asymptomatic; 32 AD dementia) and 41 unimpaired controls. General linear models, adjusted for age, sex, sleep efficiency, and obstructive sleep apnea (OSA) severity, tested group differences, with interaction terms included to evaluate group‐specific associations. RESULTS DS showed lower relative amplitude and higher nocturnal activity, already in asymptomatic individuals. Rhythm strength declined further with AD progression, while regularity and phase timing remained preserved until dementia. Findings were independent of sleep duration and OSA. DISCUSSION Adults with DS showed early RAR disturbance that progressed across the AD continuum, paralleling sporadic AD. Circadian RAR features may be scalable biomarkers of AD progression.

Abstract Background Knowing the prevalence of patent foramen ovale (PFO) and the increasing number of people who inject drugs (PWID) with right-sided infective endocarditis (RSIE), we aimed to better characterize the syndrome of injection drug use, RSIE, and PFO with systemic embolic events. Method A systematic search across multiple databases was independently screened using predefined criteria (from inception until September 2025). Published cases of adult PWID diagnosed with RSIE and ischemic stroke or other systemic embolic event were included, provided they had PFO assessment. Individuals were excluded if they had cardiac implantable electronic device (CIED) infections or any other conditions associated with systemic or paradoxical embolism. Results The review identified 13 studies with 14 young patients, mostly without comorbidities, predominantly infected with Staphylococcus aureus. In most cases, echocardiography revealed large tricuspid valve vegetations. Neuroimaging confirmed multiple ischemic infarcts, while 5 patients showed emboli outside the central nervous system (4 of them as the only systemic embolism). At least 11 (79%) patients had echocardiographic evidence of right-to-left shunting. Management included cardiac surgery in 6 cases that involved valve replacement or repair, percutaneous PFO closure in 2 cases, and percutaneous mechanical aspiration in 1 case. Three patients (21%) died during hospitalization, and only 27.3% patients had outpatient follow-up. Conclusions RSIE with systemic embolism in PWID with PFO has rarely been reported, affects younger patients without sex predominance, and was usually due to S. aureus with large tricuspid vegetations. Right-to-left shunting was characteristic, and outcomes were poor despite combined medical, surgical, and interventional therapies.

Background/Objectives: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluation. However, current automated approaches for lesion detection and segmentation are typically designed for specific MRI contrasts or acquisition sites, limiting their generalizability in real-world clinical settings where imaging protocols vary widely. This work proposes a robust multi-site, multi-contrast segmentation framework for spinal cord lesions. Methods: The segmentation model was trained and evaluated on a large-scale dataset comprising 4428 annotated images from 1849 persons with MS across 23 imaging centers, encompassing six MRI contrasts (T1w, T2w, T2*w, PSIR, STIR, and UNIT1) acquired at 1.5 tesla (T), 3 T, and 7 T. Results: Likert-type assessment performed by neuroradiologist ratings demonstrated superior generalization of the model compared to existing contrast-specific pipelines ( p < 0.01). Additional experiments evaluated robustness across spinal levels, acquisition resolutions, binarization thresholds, and quantitative evaluation on external labeled datasets. Conclusions: The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barrier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher. Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast

Abstract Context Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, and consequences remain undefined. Objective To develop, validate, and deploy a natural language processing (NLP) pipeline to identify ITFs in radiology reports and assess their prevalence, features, and clinical outcomes. Design Retrospective cohort study. Setting Mayo Clinic sites (Rochester, Arizona, Florida, Mayo Clinic Health System). Participants Adults without prior thyroid disease undergoing thyroid-capturing imaging from July 1, 2017, to September 30, 2023. A transformer-based NLP pipeline identified ITFs and extracted nodule characteristics from image reports from multiple modalities and body regions. Outcomes ITF prevalence, downstream thyroid ultrasound, biopsy, thyroidectomy, and cancer diagnosis. Logistic regression identified demographic and imaging-related factors. Results Among 115 683 patients (mean age, 56.8 [SD 17.2]; 52.9% women), 9077 (7.8%) had an ITF (92.9% nodular). ITFs were more likely in women, older adults, higher BMI, and in imaging ordered by specialties different from Emergency Medicine. Compared with chest CT, ITFs were more likely via neck CT, PET, and nuclear medicine scans. Nodule characteristics were poorly documented, with size reported in 44% and other features in fewer than 15%. Compared with patients without ITFs, those with ITFs had higher odds of thyroid nodule diagnosis (OR 45, 95%CI 41.1-49.3), biopsy (OR 46.8, 95%CI 39.0-56.2) thyroidectomy (OR 55.8, 95%CI 31.3-99.3), and thyroid cancer diagnosis (OR 61.7, 95%CI 38.6-98.5). Most cancers were papillary (88.5%) and larger when detected after ITFs (2 cm SD 1.4) vs no ITF (1.3 cm SD 0.8). Conclusion ITFs were common and strongly associated with cascades leading to the detection of small, low-risk cancers, highlighting their role in overdiagnosis and the need for standardized reporting and more selective follow-up.

Abstract In 2011, a workgroup of the Alzheimer's Association Research Roundtable introduced recommendations for detecting and monitoring amyloid‐related imaging abnormalities (ARIA) in Alzheimer's disease (AD) clinical trials. Since then, anti‐amyloid immunotherapies have received regulatory approval for AD treatment and are beginning to enter clinical practice, underscoring the importance of informing healthcare providers, researchers, and patients about ARIA's implications in real‐world settings. In response, the Alzheimer's Association convened a new workgroup to review current knowledge of ARIA, including underlying mechanisms, clinical presentations, associated risk factors, mitigation strategies, radiologic detection methods, patients’ perspectives in treatment decision‐making, and outstanding challenges. Here, we outline key insights from this workgroup, highlighting that effective ARIA detection and monitoring in clinical practice requires adherence to robust protocols to mitigate risks and enhance patient safety. Limited availability of clinical and pathologic data on predictors of symptomatic and severe ARIA underscores the importance of continued real‐world data collection.