Convolutional neural network-derived neurofibrillary tangle classifiers: Investigative tools to identify maturation levels and explore post-translational modifications using laser capture microdissection coupled mass spectrometry.

ABSTRACT: Post-translational modifications (PTM) of tau are implicated in Alzheimer disease (AD) progression and are established biomarkers in cerebrospinal fluid and plasma; however, the labor-intensive nature of conventional proteomics limits their investigation in histology-specific contexts. We describe the findings of an artificial intelligence-guided laser capture microdissection (LCM) pipeline for harvesting neurofibrillary tangles (NFTs) by maturation level into pretangles (pre-NFTs), mature tangles (iNFTs), and ghost tangles (eNFTs) using 38 cases obtained from 2 independent biobanks. We evaluated the performance characteristics of proprietary machine learning algorithms for the subclassification of these NFT categories in anti-pTau217-stained whole slide images of entorhinal cortex, hippoc

SUBMITTER: Jimenez Jaramillo C 

PROVIDER: S-EPMC12852951 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature