Evidence map›Paper›PMID 42722756›Full record

ArticleScientific reports2026

DeepLabCut-based automated system reveals diverse temperature tolerance among medaka strains and related Oryzias species.

Yoshiya Matsuo, Takuya Kato, Kiyoshi Naruse, Takashi Yoshimura, Tatsuhito Hasegawa, Tomoya Nakayama

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Yoshiya Matsuo *Laboratory of Animal Integrative Physiology, Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan.
Takuya Kato *Graduate School of Engineering, University of Fukui, Fukui, 910-8507, Japan.
Kiyoshi NaruseDepartment of Basic Biology, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Okazaki, 444-8787, Japan.
Takashi YoshimuraLaboratory of Animal Integrative Physiology, Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan.
Tatsuhito HasegawaGraduate School of Engineering, University of Fukui, Fukui, 910-8507, Japan. t-hase@u-fukui.ac.jp.
Tomoya NakayamaLaboratory of Animal Integrative Physiology, Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan. nakayama.tomoya.r8@f.mail.nagoya-u.ac.jp.

Funding

ACT-X JPMJAX21BIFusion Oriented REsearch for disruptive Science and Technology JPMJFR2438Japan Society for the Promotion of Science JP24H02008
6 · The paper itself

Abstract

Temperature is a critical environmental factor influencing the physiology and behavior of ectothermic animals, yet conventional methods for evaluating thermal tolerance in fish rely on subjective manual observation of loss of equilibrium (LOE), limiting experimental throughput and introducing observer bias. Here, we developed an automated temperature tolerance evaluation system integrating DeepLabCut-based pose estimation with custom image processing algorithms to objectively quantify the timing of LOE during thermal stress tests. Our system incorporated region partitioning and color transformation preprocessing to improve keypoint detection accuracy, followed by a classification model combining ResNet34-based frame features with keypoint coordinates to objectively determine the timing of LOE without manual observation. Validation against manual annotation showed that the automated system achieved an accuracy comparable to the natural variability between trained investigators, and outperformed naive human observers, supporting its validity as an objective and reproducible alternative to manual scoring. Using this system, we characterized cold and heat tolerance across six medaka strains (Oryzias latipes: d-rR/TOKYO, HB11A, OK-Cab, HO5 and HdrR-II1; O. sakaizumii: HNI-II). Cold and heat tolerance assessment revealed inter-strain variation, with HdrR-II1 among the most cold- and heat-tolerant strains and HNI-II the least tolerant of both cold and heat stress. We further evaluated cold tolerance in medaka-related species (O. sinensis, O. cabaranensis, O. curvinotus, O. luzonensis, O. celebensis, and O. javanicus) and zebrafish (Danio rerio), revealing substantial interspecific variation that broadly corresponded with latitudinal distribution. O. latipes, distributed at the highest latitudes among the tested species, exhibited the greatest cold tolerance, whereas O. celebensis, O. javanicus, and other tropical or low-latitude species showed comparatively low cold tolerance. Our automated system provides a robust, high-throughput platform for thermal tolerance evaluation and, combined with the genetic and genomic resources available in medaka, establishes a foundation for elucidating the molecular mechanisms underlying temperature adaptation in fish.

Indexed as

OryziasThermotoleranceAlgorithmsAnimalsHot TemperatureImage Processing, Computer-AssistedTemperatureAutomated phenotypingDeepLabCutLoss of equilibriumMedakaThermal tolerance

Identifiers

PMID42722756
PMCPMC13562581

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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.