Evidence map›Paper›PMID 40962875›Full record

ArticleScientific reports2025

AI-assisted phenotyping in a zebrafish hypophosphatasia model enables early and precise detection of skeletal alterations.

Regina Hark, Simon Zürlein, Viet T Nguyen, Gunther Gust, Lukas Hekel, Daniel Liedtke

Abstract read
In one paragraph

Article in Scientific reports, 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

6 authors.

Regina Hark *Institute of Human Genetics, Am Hubland, Biocenter, Julius-Maximilians-University Würzburg, 97074, Würzburg, Germany. regina.hark@uni-wuerzburg.de.ORCID https://orcid.org/0009-0001-9211-5870
Simon Zürlein *Chair for Enterprise Artificial Intelligence, Center for Artificial Intelligence and Data Science (CAIDAS), Sanderring 2, Würzburg, Germany.
Viet T NguyenChair for Enterprise Artificial Intelligence, Center for Artificial Intelligence and Data Science (CAIDAS), Sanderring 2, Würzburg, Germany.ORCID https://orcid.org/0009-0003-3746-0123
Gunther GustChair for Enterprise Artificial Intelligence, Center for Artificial Intelligence and Data Science (CAIDAS), Sanderring 2, Würzburg, Germany.ORCID https://orcid.org/0000-0001-6671-1380
Lukas HekelInstitute of Human Genetics, Am Hubland, Biocenter, Julius-Maximilians-University Würzburg, 97074, Würzburg, Germany.
Daniel LiedtkeInstitute of Human Genetics, Am Hubland, Biocenter, Julius-Maximilians-University Würzburg, 97074, Würzburg, Germany. daniel.liedtke@uni-wuerzburg.de.ORCID https://orcid.org/0000-0003-0934-7169

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypophosphatasia (HPP) is a rare genetic disorder mainly affecting bone and tooth mineralization in patients due to ALPL gene mutations. Understanding genotype-phenotype correlations in HPP remains challenging due to different severities and the disease's heterogeneity. To address this, we established a novel zebrafish animal model (alpl

Indexed as

Artificial IntelligenceBone and BonesHypophosphatasiaZebrafishAnimalsAnimals, Genetically ModifiedDisease Models, AnimalPhenotypeALPLDeep learningExplainable AIHypophosphatasiaPhenotype classificationVision TransformersZebrafish

Identifiers

PMID40962875
PMCPMC12443964

What OpenQuestion 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 OpenQuestion graph.