Evidence map›Paper›PMID 40587002›Full record

ArticleAnatomical science international2025

Combination method of macroscopic imaging with MRI and microscopic imaging with super resolution microscopy for brain microstructure analysis.

Yuka Nakano, Kenji F Tanaka, Yoshifumi Abe

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

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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.

Yuka NakanoDivision of Brain Sciences, Institute for Advanced Medical Research, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, 160-8582, Japan.
Kenji F TanakaDivision of Brain Sciences, Institute for Advanced Medical Research, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, 160-8582, Japan.
Yoshifumi AbeDivision of Brain Sciences, Institute for Advanced Medical Research, Keio University School of Medicine, 35 Shinanomachi, Shinjuku, Tokyo, 160-8582, Japan. yoshifumi.abe@keio.jp.ORCID http://orcid.org/0000-0002-5903-8308

Funding

Japan Agency for Medical Research and Development JP24wm0625308
6 · The paper itself

Abstract

Identifying disease-relevant and therapy-related brain regions remains a major challenge in studies using animal models of psychiatric disorders. Conventional hypothesis-driven approaches often result in limited or subjective identification of brain regions. In this study, we propose an integrative method combining unbiased whole-brain structural magnetic resonance imaging (MRI) screening and detailed histological analysis. Our methodology uses structural MRI to systematically detect volumetric changes across the entire brain, enabling the identification of target regions without relying on predefined hypotheses. Once brain regions are identified, super-resolution microscopy (SRM) is employed to determine microstructural alterations at the cellular level, focusing on neurons and glial cells within those regions. To exemplify the utility of this method, we applied it to a mouse model treated with electroconvulsive therapy (ECT), an intervention which is known to increase hippocampal volume. Our demonstration highlights the potential of this approach to systematically search for brain regions of interest, providing valuable insights and guiding future studies toward a more focused exploration of key aspects of psychiatric disorder research, both in terms of pathophysiology and therapeutic action.

Indexed as

BrainMagnetic Resonance ImagingMicroscopyAnimalsElectroconvulsive TherapyMaleMiceMice, Inbred C57BLNeuronsBrain volumePsychiatric disease animal modelsStructural MRISuper-resolution microscopyVoxel-based morphometry

Identifiers

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Registered trials

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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.