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Record W1567631042 · doi:10.1002/iub.1274

Regulation of apoptosis by heat shock proteins

2014· review· en· W1567631042 on OpenAlexaff
Donna Kennedy, Richard Jäger, Dick D. Mosser, Afshin Samali

Bibliographic record

VenueIUBMB Life · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsApoptosisHeat shock proteinCell biologyBiologyProgrammed cell deathHomeostasisImmune systemImmunologyBiochemistryGene

Abstract

fetched live from OpenAlex

Thermotolerance, the acquired resistance of cells to stress, is a well-established phenomenon. Studies of the key mediators of this response, the heat shock proteins (HSPs), have led to the discovery of the important roles played by these proteins in the regulation of apoptotic cell death. Apoptosis is critical for normal tissue homeostasis and is involved in diverse processes including development and immune clearance. Apoptosis is tightly regulated by both proapoptotic and antiapoptotic factors, and dysregulation of apoptosis plays a significant role in the pathophysiology of many diseases. In the recent years, HSPs have been identified as key determinants of cell survival, which can modulate apoptosis by directly interacting with components of the apoptotic machinery. Therefore, manipulation of the HSPs could represent a viable strategy for the treatment of diseases. Here, we review the current knowledge with regard to the mechanisms of HSP-mediated regulation of apoptosis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.030
GPT teacher head0.337
Teacher spread0.307 · 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

Citations149
Published2014
Admission routes1
Has abstractyes

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