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Heat shock proteins (Abstract Nos. 69-73)

2003· article· es· W4249693320 on OpenAlexaff
S Busteed, Michael Bennett, Catherine B. Molloy, James Stone, J. William O’Connell, Fergus Shanahan, Michael Molloy, Valerie Corrigall

Bibliographic record

VenueLara D. Veeken · 2003
Typearticle
Languagees
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineShock (circulatory)Heat shock proteinInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Poster Session 1. Heat shock proteins 43pression of IκBα was without effect on hypoxia-or cytokine (IL-1, TGFb)induced VEGF production, showing that in these cells VEGF is not under the control of NFκB.Spontaneous VEGF release by RA synovial membrane cultures was significantly inhibited (70%) following infection with AdvIκBα.Complete inhibition of VEGF was not observed, most likely due to the FLS population in the cell mixture.Conclusions: Our results show that the transcription factor NFκB plays an important role in the regulation of VEGF in RA.Nevertheless the signalling mechanisms leading to VEGF production in RA are complex, and cell-as well as stimuli-specific.Understanding those mechanisms may provide new therapeutic strategies for the treatment of RA. 68.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.585
Threshold uncertainty score0.592

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.5850.241

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 head0.018
GPT teacher head0.295
Teacher spread0.277 · 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.

Study designNot applicable
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

Citations0
Published2003
Admission routes1
Has abstractyes

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