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Understanding the role of transforming growth factor-β1 in intimal thickening after vascular injury

2007· review· en· W2091931082 on OpenAlexaff
Raja B. Khan, Alex Agrotis, Alex Bobik

Bibliographic record

VenueCardiovascular Research · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTGF-β signaling in diseases
Canadian institutionsWestern University
Fundersnot available
KeywordsThickeningCardiologyMedicineTransforming growth factorInternal medicinePathologyChemistry

Abstract

fetched live from OpenAlex

Intimal thickening is the most important cause of in-stent restenosis. The pathology of intimal thickening is attributable to a local inflammatory response after vascular injury which results in the production of cytokines. Transforming growth factor-beta1 (TGF-beta1) is a profibrotic cytokine that is involved in the induction of intimal thickening. Up-regulation of TGF-beta1 after arterial injury results in the activation of various downstream pathways which stimulate the proliferation and migration of vascular smooth muscle cells, as well as the production of local extracellular matrix proteins. Recent evidence suggests that antagonizing TGF-beta1 activity with direct or indirect inhibitors may attenuate or prevent intimal thickening. Additionally, TGF-beta1 synthesis, activation and downstream regulation may also serve as significant sources of treatment. This review attempts to show the role of TGF-beta1 in the pathology of intimal thickening and underlines the importance of TGF-beta1 as a target for therapy.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.155
GPT teacher head0.386
Teacher spread0.231 · 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

Citations108
Published2007
Admission routes1
Has abstractyes

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