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Record W2084534013 · doi:10.1139/h08-068

Heat shock proteins 27 and 70 regulating angiotensin II-induced NF-κB: a possible connection to blood pressure control?

2008· review· en· W2084534013 on OpenAlexaffvenue
Tracy S. Voegeli, Amanda J. Wintink, Yu Chen, R. William Currie

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsDalhousie UniversityWestern University
Fundersnot available
KeywordsHeat shock proteinHsp27Angiotensin IINF-κBHsp70Transcription factorHeat shock factorApoptosisBlood pressureCell biologyHeat shockBiologyEndocrinologyInternal medicineChemistrySignal transductionMedicineGeneBiochemistry

Abstract

fetched live from OpenAlex

Heat shock proteins (HSPs) are critical for cell survival and have several mechanisms of action. HSPs regulate protein folding, suppress apoptosis, and regulate anti-oxidative activity. In addition, HSPs are involved in the regulation of the pro-inflammatory transcription factor nuclear factor (NF)-kappaB. When angiotensin (Ang) II is infused into rats, there is a significant increase in systolic blood pressure, and NF-kappaB is activated in the heart. If rats are heat shocked to induce the heat shock response and HSPs before Ang II infusion, there is a significant suppression of both the Ang II-induced increase in blood pressure and NF-kappaB activation in the heart. Although the role of specific HSPs in the regulation of NF-kappaB is unclear, several HSPs, including Hsp27 and Hsp70, are thought to be involved in the regulation of Ang II-induced NF-kappaB. The role of Hsp27 and Hsp70 in NF-kappaB activation is reviewed here, along with evidence suggesting that HSPs regulate Ang II-induced blood pressure through the regulation of NF-kappaB.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.021
GPT teacher head0.290
Teacher spread0.268 · 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

Citations20
Published2008
Admission routes2
Has abstractyes

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