Evidence map›Paper›PMID 41128826›Full record

ArticleNeurochemical research2025

Advancing Cell Therapy to Enhance Passive Avoidance Memory: Integrative Approaches Combining Neural-Like Cells and Rosmarinic Acid Through Behavioral, Molecular, and Histological Analyses.

Elham Hoveizi, Golamreza Bijavi, Hoda Parsa

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Article in Neurochemical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Elham HoveiziDepartment of Biology, Faculty of Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran. e.hoveizi@scu.ac.ir.ORCID http://orcid.org/0000-0002-3285-5682
Golamreza BijaviDepartment of Biology, Faculty of Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran.
Hoda ParsaDepartment of Biology, Faculty of Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is characterized by progressive neurodegeneration, synaptic dysfunction, and cognitive decline. Regenerative strategies aim to replace lost neurons and modulate the inflammatory milieu to restore neural networks. This study examined the effects of neural-like cells (NLCs) derived from dental pulp mesenchymal stem cells (DPSCs) on a chitosan scaffold using rosmarinic acid (RA) in AD rats. In this study, DPSCs were extracted from teeth, characterized and differentiated, induced an AD model by destroying the Meynert nucleus, conducted passive avoidance tests, analyzed histology and immunohistochemistry, and measured inflammatory and oxidative stress markers. The extraction and differentiation of DPSCs were successful. Differentiated DPSCs into neural progenitors showed increased expression of Tuj-1, Map2, Nestin, and NF (RT-PCR, p < 0.001). Behavioral tests confirmed the AD model after seven days, and histology showed neuronal loss and gliosis following Meynert destruction. Histomorphology revealed improved brain tissue and significantly increased choline acetyltransferase (ChAT) expression in the treatment groups. Notable behavioral improvements were observed in the Y‑maze and shuttle box for treated rats compared with the AD group. Biochemical analyses showed a significant decrease in inflammatory markers IL‑1β, IL‑6, and TNF‑α, along with increases in superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPX) in the RA-treated groups. The results provide reliable evidence that DPSCs, in combination with RA, exert a promising therapeutic effect and represent a meaningful advance toward the clinical application of combination therapies for patients with AD.

Indexed as

Alzheimer DiseaseAvoidance LearningCell- and Tissue-Based TherapyCinnamatesDepsidesMemoryNeuronsAnimalsCell DifferentiationDental PulpMaleMesenchymal Stem CellsOxidative StressRatsRats, Sprague-DawleyRosmarinic AcidCinnamatesDepsidesRosmarinic AcidAlzheimerRegenerative medicineRosmarinic acidStem cell therapy

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.