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Record W2057508448 · doi:10.1159/000099111

Examining Potential Therapies Targeting Myocardial Fibrosis through the Inhibition of Transforming Growth Factor-Beta 1

2007· article· en· W2057508448 on OpenAlex
Razi Khan

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCardiology · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsMcGill University
Fundersnot available
KeywordsFibrosisBlockadeAngiotensin IITransforming growth factor betaCardiac fibrosisMedicineBETA (programming language)Transforming growth factorMyocardial fibrosisIn vivoTGF beta signaling pathwayInternal medicineEndocrinologyCancer researchReceptorBiology

Abstract

fetched live from OpenAlex

After injury, the heart undergoes a remodeling process consisting primarily of myocyte hypertrophy, apoptosis and interstitial fibrosis. Although initially beneficial, excess fibrosis gradually results in alteration of left ventricular properties and cardiac dysfunction. Transforming growth factor-beta 1 (TGF-beta(1)) is thought to be a primary mediator of fibrosis within the heart after injury. Currently, angiotensin II blockade is used to inhibit the actions of TGF-beta(1). However, recent studies indicate that angiotensin II blockade alone may not be sufficient to prevent TGF-beta(1)-induced fibrosis. Thus far, both in vivo and in vitro models have shown that direct TGF-beta(1) inhibition, NAPDH oxidase inhibitors, growth factors and hormonal treatment regimens targeting TGF-beta(1) may significantly reduce cardiac fibrosis after injury. This study attempts to underline these alternatives to angiotensin II blockade in combating TGF-beta(1)-induced cardiac dysfunction.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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