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Basic Science and Pathogenesis.

Alzheimers Dement

December 2024

University of California San Diego, La Jolla, CA, USA.

Background: Our data from several clinical trials of individuals with asymptomatic AD demonstrates that plasma Aβ42/40 quantification by mass spectrometry can serve as a reliable biomarker for predicting elevated brain amyloid as detected by PET. We investigated how adding plasma p-tau measures to our plasma Aβ42/40 algorithm to streamline identification of eligible participants and reduce burden and trial cost. To determine if the addition of plasma p-tau181 and/or p-tau217 concentrations can improve plasma Aβ42/40 algorithms to correctly identify participants with amyloid burden of >20 centiloids with the NAV4694 tracer among individuals screening for participation in the AHEAD preclinical AD trial.

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Purpose: To quantify outer retina structural changes and define novel biomarkers of inherited retinal degeneration associated with biallelic mutations in RPE65 (RPE65-IRD) in patients before and after subretinal gene augmentation therapy with voretigene neparvovec (Luxturna).

Methods: Application of advanced deep learning for automated retinal layer segmentation, specifically tailored for RPE65-IRD. Quantification of five novel biomarkers for the ellipsoid zone (EZ): thickness, granularity, reflectivity, and intensity.

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Understanding the spatial and temporal dynamics of gene expression is crucial for unraveling molecular mechanisms underlying various biological processes. While traditional methods have offered insights into gene expression patterns, they primarily focus on mature mRNA transcripts, lacking real-time visualization of newly synthesized or nascent transcription events. Recent advancements in monitoring nascent transcription in live cells provide valuable insights into transcriptional dynamics.

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To evaluate the combined relationship between ischemia, retinal fluid, and layer thickness measurements with visual acuity (VA) outcomes in patients with retinal vein occlusion (RVO). Swept-source optical coherence tomography (OCT) data were used to assess retinal layer thickness and quantify intraretinal fluid (IRF) and subretinal fluid (SRF) using a deep learning-based, macular fluid segmentation algorithm for treatment-naïve eyes diagnosed with visual impairment resulting from central RVO (CRVO) or branch RVO (BRVO). Patients received 3 loading doses of 2 mg intravitreal aflibercept injections and were then put on a treat-and-extend regimen.

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This retrospective study developed an automated algorithm for 3D segmentation of adipose tissue and paravertebral muscle on chest CT using artificial intelligence (AI) and assessed its feasibility. The study included patients from the Boston Lung Cancer Study (2000-2011). For adipose tissue quantification, 77 patients were included, while 245 were used for muscle quantification.

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