MétaCan
Menu
Back to cohort
Record W2087791466 · doi:10.1139/h07-183

A pediatric perspective on inflammation and oxidative stress in response to exercise

2008· article· en· W2087791466 on OpenAlexaffvenue
Brian W. Timmons, Sandeep Raha

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2008
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsMcMaster UniversityMcMaster Children's Hospital
Fundersnot available
KeywordsOxidative stressMedicineInflammationCytokineContext (archaeology)Perspective (graphical)Physical exerciseImmunologyPhysical therapyInternal medicineBiology

Abstract

fetched live from OpenAlex

Dr. Oded Bar-Or was a giant in the area of pediatric exercise science and made numerous contributions to the health of children around the world. He also had a significant impact on a relatively new area of pediatric exercise science -- pediatric exercise immunology. Under his supervision, some aspects of the immunobiology of exercise have been unravelled from a pediatric perspective. In general, healthy children experience less inflammatory stress in response to standardized exercise, while demonstrating an exercise-induced elevation in the anabolic cytokine IL-8. Mechanisms for the maturity- and age-dependent changes in cytokine responses to exercise are unknown, but may involve oxidative stress. Studies of oxidative stress and exercise in children are scant, but preliminary data suggests that, like the inflammatory cytokine response to exercise, children may experience less oxidative stress in response to intense exercise. We propose that the links between exercise, inflammatory and oxidative stress, and growth factors will be important to understand in the context of how exercise contributes to optimal growth and development during childhood. This understanding will be particularly relevant for childhood diseases that restrict growth.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.281
Teacher spread0.264 · 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

Citations11
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueApplied Physiology Nutrition and MetabolismSame topicExercise and Physiological ResponsesFrench-language works237,207