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Record W2037950072 · doi:10.1155/2012/210852

Exercise and the Cardiovascular System

2012· article· en· W2037950072 on OpenAlexaff
Saeid Golbidi, Ismail Laher

Bibliographic record

VenueCardiology Research and Practice · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineCardioprotectionDiseaseInsulin resistanceDiabetes mellitusPhysical exerciseBioinformaticsObesityHeat shock proteinEndoplasmic reticulumCardiologyInternal medicineEndocrinologyMyocardial infarctionCell biologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

There are alarming increases in the incidence of obesity, insulin resistance, type II diabetes, and cardiovascular disease. The risk of these diseases is significantly reduced by appropriate lifestyle modifications such as increased physical activity. However, the exact mechanisms by which exercise influences the development and progression of cardiovascular disease are unclear. In this paper we review some important exercise-induced changes in cardiac, vascular, and blood tissues and discuss recent clinical trials related to the benefits of exercise. We also discuss the roles of boosting antioxidant levels, consequences of epicardial fat reduction, increases in expression of heat shock proteins and endoplasmic reticulum stress proteins, mitochondrial adaptation, and the role of sarcolemmal and mitochondrial potassium channels in the contributing to the cardioprotection offered by exercise. In terms of vascular benefits, the main effects discussed are changes in exercise-induced vascular remodeling and endothelial function. Exercise-induced fibrinolytic and rheological changes also underlie the hematological benefits of exercise.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.068
GPT teacher head0.363
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations71
Published2012
Admission routes1
Has abstractyes

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