Potential Influence of Follistatin and Myostatin on Body Composition during the Yukon Arctic Ultra
Bibliographic record
Abstract
Objective The objective of this study was to determine the potential roles of follistatin and myostatin on body composition under conditions of prolonged physical activity, chronic cold exposure and remote isolation. Methods Participants traveling on foot in the 2017 Yukon Arctic Ultra 692‐km (430‐mile) were recruited for the study. Measurements and samples were obtained at pre‐event, mile 173 at Carmacks checkpoint 1 (C1), mile 239 at Pelly Crossing (C2) and post‐event. Body composition measurements were obtained using bioelectrical impedance analysis. Wrist worn accelerometer devices were utilized to provide an estimation of caloric expenditure and dietary recall provided an assessment of caloric intake. Blood serum samples were collected, centrifuged on‐site, frozen and later analyzed using enzyme linked immunosorbent assays to determine myostatin and follistatin concentrations. Results were analyzed using one‐way ANOVA, presented as means±SEM and considered significant at P<0.05 . Results Ten participants (37±10 yr, body mass index: 24.4±2.6 kg/m 2 ; 8 males, 2 females) were recruited, and five male participants completed the entire event in 260±9 hours. Caloric intake/expenditure was 4,244±471 kcal/day and 6,669±427 kcal/day, respectively, indicating a caloric deficit of 2,425±653 kcal/day. Total mass, body mass index and fat mass were reduced at each time point of the event. Fat free mass was unchanged throughout the event (Pre‐event: 60±3 kg, C1: 60±3 kg, C2: 60±3 kg, Post‐event: 59±1 kg). Follistatin was increased at C1 (1,715±310 pg/mL) in comparison to all other time points. Myostatin trended towards an increased level at C1 (20,494±5,531 pg/mL). Conclusions Despite a remarkable caloric deficit and extreme cold conditions, fat free mass was preserved in participants traveling on foot in the event. Transient alterations in follistatin and myostatin may occur during chronic exercise and may potentially influence the regulation of lean tissue retention under these conditions. Future studies will be directed at the role of nutrient strategies and sleep deprivation on cytokines and physiological resilience under these conditions. Support or Funding Information Research reported in this publication was primarily supported by the DLR grant 50WB1330. Additional support was also provided by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Numbers UL1GM118991, TL4GM118992, or RL5GM118990. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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".