Maria-Raluca Gogu 1, 2 *, Ivona Costachescu 1, Gabriela-Dumitrita Stanciu 1, Bogdan-Ionel Tamba 1, Dragos-Lucian Gorgan 2
1 Prof. Ostin C. Mungiu Advanced Research and Development Center for Experimental Medicine – CEMEX, Grigore T. Popa University of Medicine and Pharmacy, Iasi, Romania
2 Faculty of Biology, Alexandru Ioan Cuza University, Iasi, Romania
* Correspondence to: Gogu Maria-Raluca, Prof. Ostin C. Mungiu Advanced Research and Development Center for Experimental Medicine (CEMEX), Grigore T. Popa University of Medicine and Pharmacy, University Street No. 16, 700115 Iasi, Romania. E-mail: raluca.gogu@umfiasi.ro
Abstract
Alzheimer’s disease (AD) is characterized by amyloid-β (Aβ) plaques, tau pathology, synaptic degeneration and neuroinflammation and its growing global prevalence underscores the need for precise tools to evaluate therapeutic strategies. Immunohistochemistry (IHC) remains essential in preclinical AD research because it enables direct visualization and quantification of pathological changes: Aβ deposition, tau aggregation, neuronal loss and glial activation, within intact brain tissue, offering mechanistic insight beyond behavioral or biochemical assays. Recent advances such as whole-slide imaging (WSI), digital pathology and machine-learning-based image analysis have transformed IHC into a high-throughput, reproducible platform capable of generating objective and spatially resolved metrics across large cohorts. Multiplex IHC and spatial proteomic methods further expand the capacity to map complex cellular states and microenvironmental interactions relevant to AD progression. Together, these innovations establish IHC-driven digital neuropathology as a powerful framework for evaluating disease-modifying therapies and improving translation between animal models and human pathology.