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Recognition of Early Myocardial Infarction by Immunohistochemical Staining with Cardiac Troponin‐I and Complement C9*

2012· article· en· W1496816974 on OpenAlexaff
Shashi K. Jasra, Cherryl Badian, Iain Macri, Paul Ra

Bibliographic record

VenueJournal of Forensic Sciences · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsWindsor Regional HospitalUniversity of Windsor
Fundersnot available
KeywordsMyocardial infarctionImmunohistochemistryTroponinMedicineCardiologyInternal medicineTroponin IComplement (music)Forensic pathologyPathologyAutopsyBiologyBiochemistry

Abstract

fetched live from OpenAlex

The diagnosis of early myocardial infarction (MI) after death, especially in the first few hours (c. 6 h) after the onset of MI, poses a challenge to the forensic pathologists. During this time, the damaged myocardium does not show grossly identifiable morphological changes and may not be recognized even with routine histological microscopic examination. However, the infarcted cardiac tissue releases certain chemicals that can be detected microscopically, two of these being cardiac troponin-I (CT-I) and complement C9 (C9). This study utilizes the importance of these two biomarkers immunohistochemically in an attempt to identify this early phase of MI. This study reveals that the early phase of MI of <6 h duration may be detected through immunohistochemical staining with CT-I and C9. The ischemic/infarcted cardiac myofibers in the <6 h group display reduced/absent CT-I staining as well as positive C9 staining.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.020
GPT teacher head0.270
Teacher spread0.250 · 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 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

Citations29
Published2012
Admission routes1
Has abstractyes

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