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Record W4400488282 · doi:10.1073/pnas.2313370121

An HSF1–JMJD6–HSP feedback circuit promotes cell adaptation to proteotoxic stress

2024· article· en· W4400488282 on OpenAlexaff
Milad J. Alasady, Martina Koeva, Seesha Takagishi, Dmitri Segal, David R. Amici, Roger S. Smith, Daniel J. Ansel, Susan Lindquist, Luke Whitesell, Elizabeth T. Bartom, Mikko Taipale, Marc L. Mendillo

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Institutes of HealthNorthwestern UniversitySusan G. Komen for the CureFoundation for the National Institutes of Health
KeywordsHSF1Cell biologyCellular adaptationAdaptation (eye)BiologyHeat shock proteinHsp70NeuroscienceGenetics

Abstract

fetched live from OpenAlex

Heat Shock Factor 1 (HSF1) is best known as the master transcriptional regulator of the heat-shock response (HSR), a conserved adaptive mechanism critical for protein homeostasis (proteostasis). Combining a genome-wide RNAi library with an HSR reporter, we identified Jumonji domain-containing protein 6 (JMJD6) as an essential mediator of HSF1 activity. In follow-up studies, we found that JMJD6 is itself a noncanonical transcriptional target of HSF1 which acts as a critical regulator of proteostasis. In a positive feedback circuit, HSF1 binds and promotes JMJD6 expression, which in turn reduces heat shock protein 70 (HSP70) R469 monomethylation to disrupt HSP70-HSF1 repressive complexes resulting in enhanced HSF1 activation. Thus, JMJD6 is intricately wired into the proteostasis network where it plays a critical role in cellular adaptation to proteotoxic stress.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.047
GPT teacher head0.336
Teacher spread0.289 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations9
Published2024
Admission routes1
Has abstractyes

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