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Record W2768614538 · doi:10.1186/s11658-017-0056-y

Heat shock protein 27 plays a protective role in thoracic aortic dissection by promoting cell proliferation and inhibiting apoptosis

2017· article· en· W2768614538 on OpenAlexaff
Sili Zou, Mingfang Liao, Junlin Yang, Tong Huang, Mark Green, Jianjin Wu, Lefeng Qu

Bibliographic record

VenueCellular & Molecular Biology Letters · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsArthritis Research Centre of Canada
FundersScience and Technology Commission of Shanghai MunicipalityNational Natural Science Foundation of China
KeywordsHsp27Oxidative stressHeat shock proteinApoptosisCell growthCell biologyCellHsp70ImmunologyBiologyCancer researchChemistryEndocrinologyBiochemistryGene

Abstract

fetched live from OpenAlex

Thoracic aortic dissection (TAD) is one of the most severe aortic diseases. The study aimed to explore the potential role of heat shock protein 27 (HSP27) in the pathogenesis of TAD using an in vitro model of oxidative stress in vascular smooth muscle cells (VSMCs). HSP27 was analyzed in aortic surgical specimens from 12 patients with TAD and 8 healthy controls. A lentiviral vector was used to overexpress HSP27 in rat aortic VSMCs. Cell proliferation and apoptosis were measured under oxidative stress induced by H 2 O 2 . HSP27 expression was significantly higher in aortic tissue from patients with TAD and VSMCs in the aortic media were the main cell type producing HSP27. Elevated oxidative stress was also detected in the TAD samples. Overexpression of HSP27 significantly attenuated H 2 O 2 -induced inhibition of cell proliferation. Furthermore, HSP27 was found to decrease H 2 O 2 -induced cell apoptosis and oxidative stress. These results suggest that HSP27 expression promotes VSMC viability, suppresses cell apoptosis, and confers protection against oxidative stress in TAD.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.007
GPT teacher head0.271
Teacher spread0.264 · 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.

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

Citations11
Published2017
Admission routes1
Has abstractyes

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