Toward the promotion of One Health - Part II: Interdisciplinary research cooperation between digital transformation and exposome.

Takeshi Yoneshiro, Yoshito Kumagai, Keiko Nohara, Shingo Iwami, Naoki Honda, Nobuhiko Ohno, Motohiro Nishida

Abstract readReview

In one paragraph

Review in The journal of physiological sciences : JPS, 2026. 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

7 authors.

Takeshi YoneshiroDivision of Molecular Physiology and Metabolism, Tohoku University Graduate School of Medicine, Sendai, Miyagi 980-8575, Japan; Division of Metabolic Medicine, Research Center for Advanced Science and Technology (RCAST), The University of Tokyo, Meguro-ku, Tokyo 153-8904, Japan.

Yoshito KumagaiDepartment of Physiology, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka 812-8582, Japan.

Keiko NoharaHealth and Environmental Risk Division, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan.

Shingo IwamiGraduate School of Life Science, Nagoya University, Nagoya, Aichi 464-8602. Japan.

Naoki HondaNagoya University Graduate School of Medicine, Nagoya, Aichi 466-8550, Japan; Center for One Medicine Innovative Translational Research (COMIT), Nagoya University, Nagoya 466-8550, Japan; Graduate School of Integrated Sciences for Life, Hiroshima University, Higashihiroshima, Hiroshima 739-8526, Japan.

Nobuhiko OhnoNational Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Aichi 444-8787, Japan; Department of Anatomy, Division of Histology and Cell Biology, Jichi Medical University, Tochigi 329-0498, Japan. Electronic address: ohno@nips.ac.jp.

Motohiro NishidaDepartment of Physiology, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka 812-8582, Japan; National Institute for Physiological Sciences, National Institutes of Natural Sciences, Okazaki, Aichi 444-8787, Japan; Exploratory Research Center on Life and Living Systems, National Institutes of Natural Sciences, Okazaki, Aichi 444-8787, Japan. Electronic address: nishida@phar.kyushu-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human activities increasingly disrupt global ecosystems, contributing to climate change, biodiversity loss, and emerging health threats. In response, the One Health framework has gained attention as an integrative approach encompassing human, animal, and environmental health. In a symposium at APPW2025, experts in Exposome science and Digital Transformation discussed how interdisciplinary integration can advance predictive and preventive medicine. This review summarizes five key topics: Exposome as a determinant of disease risk, epigenetic mechanisms encoding environmental memory, environmental programming of brown adipose tissue, adaptive prioritization of environmental signals, and simulation-based drug repurposing. Collectively, these studies highlight a paradigm shift from conventional linear exposure-disease models toward a systems-level understanding integrating cumulative exposures, biological memory, and predictive modeling. The convergence of Exposome science and Digital Transformation provides a foundation for advancing One Health into a predictive and actionable scientific framework.

Indexed as

ExposomeInterdisciplinary ResearchAnimalsHumansDigital transformationDrug repurposingEpigeneticsExposomePredictive modeling

Identifiers

PMID42061101

DOI10.1016/j.jphyss.2026.100078

PMCPMC13141750

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

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.