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Record W4412001437 · doi:10.1093/jmcb/mjaf017

The disruption of COPII vesicles activates HSF-1 through SEC-23

2025· article· en· W4412001437 on OpenAlexaff
Zhidong He, Na Tang, Hao Liu, Xueqing Wang, Yue Yin, Chao Peng, Yidong Shen

Bibliographic record

VenueJournal of Molecular Cell Biology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsInstitute of Infection and Immunity
FundersChinese Academy of Sciences
KeywordsCOPIICell biologyEndoplasmic reticulumCOPIBiologyVesicleGolgi apparatusProteostasisCaenorhabditis elegansSecretionTransport proteinSecretory pathwayBiochemistryGeneMembrane

Abstract

fetched live from OpenAlex

HSF-1 is a highly conserved transcription factor that plays a central role in protecting organisms from diverse cellular stresses. However, the mechanisms by which HSF-1 senses and responds to different types of stress remain incompletely understood. COPII-coated vesicles, responsible for transporting cargo from the endoplasmic reticulum to the Golgi apparatus, are essential for protein secretion and cellular homeostasis. Disruption of these vesicles impairs protein secretion and triggers severe proteotoxic stress. Here, we show that HSF-1 directly monitors COPII vesicle dysfunction through interactions with the core COPII component SEC-23, in both Caenorhabditis elegans and NIH3T3 cells. Inhibition of SEC-23 or SAR-1 disrupts COPII vesicle formation, leading to the release of HSF-1 from the COPII complex. This release induces a specific transcriptomic change to restore protein homeostasis. Our findings reveal a conserved mechanism by which HSF-1 responds to COPII vesicle dysregulation, providing new insights into the HSF-1-centered proteostasis network.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.005
GPT teacher head0.261
Teacher spread0.256 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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