Maximal Aerobic Effort Increases Genetic Expression of HSP90AA1, HSP90AB1, and PTGES3 in Elite Taekwondo Athletes
Bibliographic record
Abstract
Heat shock proteins (HSPs) work in response to a variety of external and internal stresses to maintain homeostasis and are upregulated upon cellular damage. This study aimed to determine the effect of maximal aerobic effort test ( $${{\dot {V}}}{{{\text{O}}}_{2}}$$ max test) on the expression of genes related to heat shock proteins’ (HSPs) cycle (HSP90AA1, HSP90AB1, PTGES3). Eleven black-belt taekwondo male athletes participated in this study and performed a $${{\dot {V}}}{{{\text{O}}}_{2}}$$ max test on a treadmill connected to the Cortex gas analyzer till the point of physical exhaustion. Gene expression was analyzed by real-time PCR, while the physiological parameters were measured spectrophotometrically or by immune assays using serum form the blood Before the test (Bf), Immediately After (IA), and Two Hours After (2HA) the $${{\dot {V}}}{{{\text{O}}}_{2}}$$ max test. The levels of fold change expression were affected by the VO2max test. HSP90AA1, HSP90AB1 and PTGES3 mRNA levels were significantly higher IA the test (P ≤ 0.05). HSPs surpassed the cut-off value (1.5-fold) IA showed (M = 2.29 times for HSP90AA1), (M = 1.68 times for HSP90AB1), while PTGES3 did not reach the cut-off value (M = 1.12 times). The expression levels of the three genes were significantly decreased 2HA and returned to the baseline values. Moreover, physiological parameters including growth hormone, creatinine kinase, white blood cells, platelets count, and blood lactate showed a peak in their levels IA the test and then dropped 2HA (P ≤ 0.05). Our findings demonstrate that genetic expressions of HSP90AA1 and HSP90AB1 genes were significantly elevated IA the test and decreased 2HA. The same applied on most of the physiological parameters; strongly suggesting the possible utility of using those parameters as a reference to confirm evidence of exercise-induced cell stress.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".