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Record W2033549658 · doi:10.1139/y10-113

Changes in adiponectin expression in acute myocardial infarction rats and the significance of bisoprolol intervention

2011· article· en· W2033549658 on OpenAlexvenueno aff
Song Zhang, Ben He, Steven A. Goldstein, Junbo Ge, George Ruiz

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2011
Typearticle
Languageen
FieldMedicine
TopicAdipokines, Inflammation, and Metabolic Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMyocardial infarctionAdiponectinInternal medicineBisoprololCardiologyEndocrinologyHeart failure

Abstract

fetched live from OpenAlex

The aims of this study were to explore the changes in expression of myocardial adiponectin (APN), changes in serum APN, and the significance of bisoprolol intervention in acute myocardial infarction (AMI) rats. An AMI rat model was established for the purposes of this study and was used for analysis of serum APN as determined by ELISA. Changes in expression of myocardial APN mRNA and APN protein in AMI rats were determined via reverse transcriptase (RT)-PCR and immunohistochemistry. Serum APN concentration and APN protein expression of the myocardium decreased significantly in the AMI groups compared with the sham operation group, with the lowest serum APN and APN protein expression on day 7 after AMI. On days 7 and 10 after AMI, the expression of myocardial APN mRNA in the AMI groups decreased significantly compared with the sham operation group. However, the APN mRNA increased on day 10 compared with that on day 7. Notably, there was an increase in levels of serum APN and myocardial APN expression after bisoprolol intervention. The expression of myocardial APN and serum APN decreased in AMI rats. APN may be an important protective factor against AMI. Bisoprolol can also protect against AMI because it increases APN expression.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 integrity0.0000.001
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 head0.019
GPT teacher head0.279
Teacher spread0.260 · 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 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

Citations5
Published2011
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Physiology and PharmacologySame topicAdipokines, Inflammation, and Metabolic DiseasesFrench-language works237,207