Evidence map›Paper›PMID 39140525›Full record

ArticleActa cirurgica brasileira2024

A neural cell automated analysis system based on pathological specimens in a gerbil brain ischemia model.

Eri Katsumata, Abhishek Kumar Ranjan, Yoshihiko Tashima, Takayuki Takahata, Toshiyuki Sato, Motoaki Kobayashi, Masami Ishii, Toyomi Takahashi, Asahi Oda, Momoko Hirano and 3 more

Abstract read
In one paragraph

Article in Acta cirurgica brasileira, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

13 authors.

Eri KatsumataSysmex Co. - Hyogo, Japan.ORCID http://orcid.org/0009-0001-9015-4083
Abhishek Kumar RanjanSysmex Co. - Hyogo, Japan.ORCID http://orcid.org/0009-0000-5925-2526
Yoshihiko TashimaSysmex Co. - Hyogo, Japan.ORCID http://orcid.org/0009-0002-1753-6293
Takayuki TakahataSysmex Co. - Hyogo, Japan.ORCID http://orcid.org/0009-0001-6214-9500
Toshiyuki SatoSysmex Co. - Hyogo, Japan.ORCID http://orcid.org/0000-0003-0127-3521
Motoaki KobayashiSept.Sapie Co. - Tokyo, Japan.ORCID http://orcid.org/0009-0009-1200-9348
Masami IshiiSept.Sapie Co. - Tokyo, Japan.ORCID http://orcid.org/0009-0004-5574-5170
Toyomi TakahashiSept.Sapie Co. - Tokyo, Japan.ORCID http://orcid.org/0009-0009-8309-325X
Asahi OdaNippon Veterinary and Life Science University - School of Veterinary Nursing and Technology - Department of Basic Science - Tokyo, Japan.ORCID http://orcid.org/0009-0001-2083-7372
Momoko HiranoNippon Veterinary and Life Science University - School of Veterinary Nursing and Technology - Department of Basic Science - Tokyo, Japan.ORCID http://orcid.org/0009-0007-4347-9372
Yoji HakamataNippon Veterinary and Life Science University - School of Veterinary Nursing and Technology - Department of Basic Science - Tokyo, Japan.ORCID http://orcid.org/0000-0002-0138-6692
Kazuhisa SugaiNippon Veterinary and Life Science University - School of Veterinary Nursing and Technology - Department of Basic Science - Tokyo, Japan.ORCID http://orcid.org/0000-0003-2152-5394
Eiji KobayashiNippon Veterinary and Life Science University - School of Veterinary Nursing and Technology - Department of Basic Science - Tokyo, Japan.ORCID http://orcid.org/0000-0001-8617-3778

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAmid rising health awareness, natural products which has milder effects than medical drugs are becoming popular. However, only few systems can quantitatively assess their impact on living organisms. Therefore, we developed a deep-learning system to automate the counting of cells in a gerbil model, aiming to assess a natural product's effectiveness against ischemia.

methodsThe image acquired from paraffin blocks containing gerbil brains was analyzed by a deep-learning model (fine-tuned Detectron2).

resultsThe counting system achieved a 79%-positive predictive value and 85%-sensitivity when visual judgment by an expert was used as ground truth.

conclusionsOur system evaluated hydrogen water's potential against ischemia and found it potentially useful, which is consistent with expert assessment. Due to natural product's milder effects, large data sets are needed for evaluation, making manual measurement labor-intensive. Hence, our system offers a promising new approach for evaluating natural products.

Indexed as

Brain IschemiaDisease Models, AnimalGerbillinaeAnimalsBrainDeep LearningImage Processing, Computer-Assisted

Identifiers

PMID39140525
PMCPMC11321503

What OpenQuestion holds

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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.