SERUM MYOKINE LEVELS DURING THE 430 MILE YUKON ARCTIC ULTRA
Bibliographic record
Abstract
A. N. Weaver1, M. S. Coker1, M. Steinach2, R. H. Coker1 1Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK, 2Center for Space Medicine and Extreme Environments Berlin, Berlin, Germany This research was presented by representatives from the Alaska chapter of the American College of Sports Medicine. PURPOSE: The Yukon Arctic Ultra is considered the longest and coldest ultraendurance event in the world. Recently, cold exposure and exercise have been reported to influence circulating levels of certain myokines and proteins that may influence the “browning” of white adipose tissue. The purpose of the study was to evaluate the influence of the Yukon Arctic Ultra (430 mile participants) on serum irisin, meteorin, IL-6, and FGF21 in healthy individuals. METHODS: Eight male and female participants (mean±SEM; age = 44±3 yr; BMI = 23.3±0.9) were recruited for participation. Blood samples were collected at pre-event, mid event (200 mile) and post-event checkpoints. RESULTS: The average temperature during the event ranged from -45ºC to -8ºC. Due to the challenging conditions, only 50% of the participants finished the event and they lost 2.2±0.3 kg of body weight. Serum irisin was 307±63 ug/ml (pre-event), rose to 496±17 ug/ml (mid-event), and remained elevated at 513±18 (post-event) but the lack of significance was likely due to attrition. Serum meteorin remained stable at 3.1±0.1 ng/ml (pre-event), 3.1±0.0 (mid-event), and 3.0±0.1 ng/ml (post-event). Serum IL-6 fell from 183±51 ug/ml (pre-event), to 118±55 ug/ml (mid-event), to 90±39 ug/ml (post-event). Serum FGF21 was 30±3 ug/ml (pre-event), 34±8 ug/ml (mid-event), and 62±21 ug/ml (post-event). CONCLUSION: The combined influence of cold exposure and extreme levels of prolonged ultraendurance exercise may promote elevations in serum irisin and FGF21, while IL-6 may decline under these circumstances. Despite previous reports in pre-clinical studies of cold exposure induced increments in serum meteorin, these responses were not evident in a limited number of humans undergoing substantially greater metabolic stress. Utilizing participants competing in all distances of Yukon Arctic Ultra 2016 and hot-weather marathons, future studies are planned to gather more data on serum myokines, and examine potential changes in FNDC5 and PGC-1α in muscle and UCP-1 gene expression in white adipose tissue.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".