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Record W7116098732 · doi:10.1016/j.cstres.2025.100142

J-domain proteins: from molecular mechanisms to diseases

2025· article· en· W7116098732 on OpenAlexafffund

Bibliographic record

VenueCell Stress and Chaperones · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of TorontoUniversity of Calgary
FundersNational Institute of General Medical SciencesRheinische Friedrich-Wilhelms-Universität BonnUniversity of TorontoMarquette UniversityNational Institute of Diabetes and Digestive and Kidney DiseasesStowers Institute for Medical Research
KeywordsChaperone (clinical)Human proteins

Abstract

fetched live from OpenAlex

J-domain proteins (JDPs) are known to drive the functional specificity of Hsp70 chaperone machines. Here we report on the latest findings presented at the third international JDP workshop held in 2025 in Gdansk, Poland. Investigators from many different disciplines, including structural biology, genetics, chemical biology, translational research, computational sciences, and biophysics, took part in the meeting. This article includes short summaries of the seminars presented by many of the speakers, which provided exciting new insights into the chaperone-dependent and chaperone-independent functions of JDPs, some of which go beyond Hsp70-dependent functions. We also provide a revised classification of members of the (human) JDP family that emerged from open discussion at the meeting. This workshop continues to serve as the premier venue for discussions of JDP evolution, structure, function, and roles in health, aging, and disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.243
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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