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Record W2051841458 · doi:10.1007/s12192-009-0126-9

The mechanism whereby heat shock induces apoptosis depends on the innate sensitivity of cells to stress

2009· article· en· W2051841458 on OpenAlexafffund
Kerstin Bellmann, Steve J. Charette, Philippe J. Nadeau, Dominic Poirier, Anne Loranger, Jacques Landry

Bibliographic record

VenueCell Stress and Chaperones · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecHôtel-Dieu de QuébecUniversité Laval
FundersCanadian Institutes of Health Research
KeywordsApoptosisCell biologyHeat shock proteinProteasomeProgrammed cell deathBiologySignal transductionHeat shockAggresomeUnfolded protein responseChemistryBiochemistryAutophagy

Abstract

fetched live from OpenAlex

The cellular response to heat shock (HS) is a paradigm for many human diseases collectively known as "protein conformation diseases" in which the accumulation of misfolded proteins induces cell death. Here, we analyzed how cells having a different apoptotic threshold die subsequent to a treatment with HS. Cells with a low apoptotic threshold mainly induced apoptosis through activation of conventional stress kinase signaling pathways. By contrast, cells with a high apoptotic threshold also died by apoptosis but likely after the accumulation of heat-aggregated proteins as revealed by the formation of aggresomes in these cells, which were associated with the generation of atypical nuclear deformations. Inhibition of the proteasome or expression of an aggregation prone protein produced similar nuclear alterations. Furthermore, elevated levels of chaperones markedly suppressed both HS-induced nuclear deformations and apoptosis induced upon protein aggregation whereas they had little effect on stress kinase-mediated apoptosis. We conclude that the relative contribution of stress signaling pathways and the accumulation of protein aggregates to cell death by apoptosis is related to the innate sensitivity of cells to deadly insults.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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 teacher head, 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

Citations29
Published2009
Admission routes2
Has abstractyes

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