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Record W2418230026 · doi:10.14712/18059694.2019.28

Cardiac Troponins Following Repeated Administration of an Iron Chelator – Salicylaldehyd Isonicotinoyl Hydrazone (SIH) – in Rabbits

2003· article· en· W2418230026 on OpenAlexaff
Michaela Adamcová, Martin Štěrba, Ivona Klimtová, Tomáš Šimůnek, Radomír Hrdina, Vladimír Geršl, Přemysl Poňka

Bibliographic record

VenueActa Medica (Hradec Kralove Czech Republic) · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPesticide Residue Analysis and Safety
Canadian institutionsMcGill University
FundersGrantová Agentura České RepublikyMinisterstvo Školství, Mládeže a Tělovýchovy
KeywordsTroponin complexTroponin IMedicineTroponinInternal medicineAnesthesiaCardiologyMyocardial infarction

Abstract

fetched live from OpenAlex

Both cardiac troponin T (cTnT) and cardiac troponin I (cTnI) are considered to be reliable biomarkers with sufficient sensitivity and specificity for cardiac injury in the majority of laboratory animals. The aim of our study was to compare the diagnostic performance of cTnT and cTnI in three groups of rabbits: 1) control (saline 1 ml/kg i.v.); 2) Salicylaldehyde Isonicotinoyl Hydrazone--SIH (50 mg/kg, once weekly, i.p.; partially dissolved in 10% Cremophor solution); 3) 10% Cremophor solution in water (2 ml/kg i.v.). The drugs were given once a week, 10 administrations. The concentration of cTnT was measured using Elecsys Troponin T STAT Immunoassay (Roche). The concentration of cTnI was measured using AxSYM Troponin I (Abbott). The linear regression model was applied to see if there is a dependence between cTnT and cTnI. The coefficient of determination was not acceptable in all groups. The highest value of R2 was found in the control group (R2 = 0.424). We may conclude that in rabbits meaningful dependence between cTnT and cTnI was not found. According to our long-term experiences cTnT seems to be more suitable cardiomarker in rabbits in comparison with cTnI where the data are characterized by the large scatter.

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)0.002
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 score0.787
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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 designBench or experimental
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

Citations4
Published2003
Admission routes1
Has abstractyes

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