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Inflammation and Apoptosis in the Myocardium in rats following Myocardial Infarction

2011· article· en· W3174796932 on OpenAlexafffundabout
Katherine V. Westcott, Monir Ahmad, John P. Veinot, Balwant S. Tuana, Frans H. H. Leenen

Bibliographic record

VenueThe FASEB Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineMyocardial infarctionVentricleInternal medicineTUNEL assayCardiologyPreloadInflammationInfarctionFibrosisMyocardial fibrosisApoptosisImmunohistochemistryHemodynamics

Abstract

fetched live from OpenAlex

Following myocardial infarction (MI) a variety of mechanisms contribute to progressive cardiac remodelling and dysfunction. The objective of this study is to assess changes in inflammation and apoptosis in the myocardium of the left ventricle (LV) after MI. Rats were subjected to left anterior descending coronary artery occlusion, and studied 10 days, 4 weeks and 16 weeks after surgery. MI size was ~40% of LV. LVEDP increased to ~15mmHg. TNF-α, IL-6, IL-1β and IL-10 showed no significant changes in the non-infarcted LV. Macrophages were not found in the non-infarcted LV in either MI or sham rats. Apoptosis was absent in sham rats. Macrophage Immunohistochemistry: (macrophages/field 515x1158 μm) Peri-Infarcted Infarct 10 days MI n=7 127±16 144±12 4 weeks MI n=13 13±2.5 53±4.7 16 weeks MI n=10 2±0.6 28±5.7 Apoptotic Index: (% TUNEL stained cardiac nuclei in 2x2mm field) Non-Infarcted Peri-Infarcted Infarct 10 days MI n=6 0.5±0.3 1.3±0.7 2.6±0.5 4 weeks MI n=3 0±0 0±0 0±0 16 weeks MI n=2 0.6±0.6 0±0 0±0 After MI there is a rapid increase in macrophages and TUNEL staining in the infarct and peri-infarcted myocardium which both decrease over subsequent weeks. There is no inflammation in the non-infarcted myocardium up to 16 weeks post MI. Funding for this project provided by the Canadian Institutes of Health Research.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.199

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.000
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 head0.252
Teacher spread0.226 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2011
Admission routes3
Has abstractyes

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