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Influence Of Slow Versus Fast Increases In Core Temperature On Prolactin And TNF-alpha

2011· article· en· W2334081762 on OpenAlexaffabout
Heather E. Wright, Brian J. Friesen, Glen P. Kenny

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2011
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsProlactinEndocrinologyInternal medicineHyperthermiaCore temperatureTumor necrosis factor alphaMedicineTreadmillCore (optical fiber)Rectal temperatureHypothalamusVenous bloodChemistryHormoneMaterials science

Abstract

fetched live from OpenAlex

Prolactin (PRL), a pituitary hormone regulated by neurons in the hypothalamus, has been suggested as an indicator of fatigue during exercise-induced hyperthermia (EIH) given its strong relationship with body core temperature (Tco). However, the strength of this relationship during different rates of Tco increase and subsequent recovery are unknown. In addition, given the influence that systemic inflammatory cytokines, such as Tumor necrosis factor (TNF)-α, have on the pituitary gland; it would be of interest to determine the relationship between PRL and TNF-α during EIH. PURPOSE: To examine the PRL and TNF-α heat stress responses during low (slow heating) and moderate (fast heating) exercise intensities and subsequent resting or cold water immersion recovery. METHODS: Seven trained individuals (5 males, 2 females, mean ± SE: 27.0 ± 3.3 yrs, 57.9 ± 2.2 mL·kg-1nim·-1, 18.5 ± 2.4 % fat) underwent 4 EIH sessions (40°C, 30% R.H.) on a treadmill to a rectal temperature (Tre), measured continuously, of 39.5°C while wearing an impermeable rain suit followed by upright seated resting or 2°C ice-water immersion recovery. Venous blood was obtained at rest (PRE; prior to exercise), during exercise (Tre 38, 39, 39.5°C), the start of recovery (5 min post 39.5°C), and subsequent recovery (Tre 39, 38°C). PRL and TNF-α (high sensitivity) were measured by an ELISA and corrected for changes in plasma volume. RESULTS: PRL exhibited a strong relationship with Tre during exercise (r >0.75), where no differences were observed between the slow and fast trials at a given Tre. During recovery, PRL remained elevated at 39°C (46 ng·mL-1) and 38°C (37 ng·mL-1) during the cooling compared to resting (28 and 16 ng·mL-1, respectively). TNF-α was elevated throughout cooling compared to resting recovery (0.76-0.82 vs. 0.58-0.69 pg·mL-1), the fast but not the slow EIH. CONCLUSION: PRL remained elevated during the cooling compared to resting recovery, likely due to the shorter recovery and reduced clearance from a decrease in blood flow via cutaneous vasoconstriction. It appears that the influence of TNF-α on the pituitary gland does not interfere with the Tre, or stronger, stimulus for the secretion of PRL. Support: Natural Sciences and Research Council of Canada and Canada Foundation for Innovation (held by G.P. Kenny).

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
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 head0.032
GPT teacher head0.304
Teacher spread0.272 · 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 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".

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Citations0
Published2011
Admission routes2
Has abstractyes

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