Evidence map›Paper›PMID 37542080›Full record

ArticleScientific reports2023

Machine learning discriminates P2X7-mediated intracellular calcium sparks in human-induced pluripotent stem cell-derived neural stem cells.

Yuki Hanafusa, Akira Shiraishi, Fumiyuki Hattori

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.8field-weighted citation impact, top 28% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. 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

3 authors at 2 institutions in 1 country.

Yuki Hanafusa *Innovative Regenerative Medicine, Graduate School of Medicine, Kansai Medical University, Osaka, Japan.
Akira ShiraishiDivision of Integrative Biomolecular Function, Bioorganic Research Institute, Suntory Foundation for Life Sciences, Kyoto, Japan.
Fumiyuki Hattori *Innovative Regenerative Medicine, Graduate School of Medicine, Kansai Medical University, Osaka, Japan. hattorif@hirakata.kmu.ac.jp.
Kansai Medical University · JPSuntory Foundation for Life Sciences · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adenosine triphosphate (ATP) is an extracellular signaling molecule that mainly affects the pathophysiological situation in the body and can be sensed by purinergic receptors, including ionotropic P2X7. Neuronal stem cells (NSCs) remain in adult neuronal tissues and can contribute to physiological processes via activation by evoked pathophysiological situations. In this study, we revealed that human-induced pluripotent stem cell-derived NSCs (iNSCs) have ATP-sensing ability primarily via the purinergic and ionotropic receptor P2X7. Next, to develop a machine learning (ML)-based screening system for food-derived neuronal effective substances and their effective doses, we collected ATP-triggered calcium responses of iNSCs pretreated with several substances and doses. Finally, we discovered that ML was performed using composite images, each containing nine waveform images, to achieve a better ML model (MLM) with higher precision. Our MLM can correctly sort subtle unidentified changes in waveforms produced by pretreated iNSCs with each substance and/or dose into the positive group, with common mRNA expression changes belonging to the gene ontology signatures.

Indexed as

Induced Pluripotent Stem CellsNeural Stem CellsAdenosine TriphosphateAdultCalciumCalcium SignalingHumansReceptors, Purinergic P2X7Adenosine TriphosphateCalciumReceptors, Purinergic P2X7

Identifiers

PMID37542080
PMCPMC10403609
OpenAlexW4385579379

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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 Socratic graph.