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Exercise-induced elevation of HSP70 is intensity dependent

2002· article· en· W2327020352 on OpenAlexaff
Kevin Milne, Earl G. Noble

Bibliographic record

VenueJournal of Applied Physiology · 2002
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsLawson Health Research InstituteWestern University
Fundersnot available
KeywordsHsp70TreadmillInternal medicineSoleus muscleEndocrinologySkeletal muscleVastus lateralis muscleIntensity (physics)Exercise intensityAnimal scienceChemistryHeat shock proteinBiologyMedicineAnatomyHeart rateBlood pressureBiochemistry

Abstract

fetched live from OpenAlex

Exercise induces expression of the protective heat shock protein, HSP70, in striated muscle. To characterize the relationship between induction of this protein and exercise intensity in muscles exhibiting different recruitment patterns, male Sprague-Dawley rats were assigned to a sedentary control or one of seven exercise groups for which treadmill running speed varied between 15 and 33 m/min (n = 8/group). Twenty-four hours after a single 60-min exercise bout, hearts, red and white portions of the vastus (RV and WV, respectively) muscles, and soleus (Sol) muscles were harvested and analyzed for both relative and absolute HSP70 content. Cardiac HSP70 was significantly elevated only when animals were exercised at 24 m/min and beyond. Similarly, HSP70 was elevated in RV at running speeds above 24 m/min but did not increase in WV until 27 m/min. In contrast, HSP70 content was initially elevated in the Sol but subsequently declined at the highest running speeds. The observed patterns of HSP70 expression in skeletal muscle were in general accordance with known muscle recruitment patterns and suggest that alterations in muscle loading, resulting from changes in exercise intensity, are an important component of exercise-induced increases in HSP70 content.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.039
GPT teacher head0.283
Teacher spread0.244 · 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

Citations196
Published2002
Admission routes1
Has abstractyes

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