Peptide YY (PYY) Is Expressed in Human Skeletal Muscle Tissue and Expanding Human Muscle Progenitor Cells
Bibliographic record
Abstract
Peptide YY (PYY) is considered a gut peptide with roles in post-prandial appetite and glucose regulation. Circulating PYY protein levels increase during aerobic exercise. Furthermore, people who have greater increases in muscle progenitor cells (hMPCs), the adult stem cell population responsible for skeletal muscle (SkM) repair, after resistance training have higher PYY transcript levels in SkM prior to training. Currently, examination of PYY expression patterns in SkM and/or hMPCs is lacking. Our objective was to identify the expression patterns of PYY in SkM and hMPCs. PYY and the associated Y receptors were analyzed in SkM biopsy tissue and cultured hMPCs from young and old human participants. Additional experiments to assess the role and regulation of PYY in hMPCs were performed. In SkM, PYY and one of the three Y receptors (Y1r) were detectable, but expression patterns were not affected by age. In expanding hMPCs, PYY and all three Y receptor (Y1r, Y2r, and Y5r) proteins were expressed in a temporal fashion with young hMPCs having greater levels of Y receptors at various time points. Exogenous PYY did not affect hMPC population expansion. hMPC PYY levels increased following the metabolic stimulus, 5-Aminoimidazole-4-carboxamide ribonucleotide (AICAR), but were not affected by the inflammatory stimulus, tumor necrosis factor alpha (TNF). In conclusion, PYY and Y receptor expression are not impacted by age in SkM tissue but are reduced in old vs. young expanding hMPCs. Furthermore, PYY production is stimulated by low energy states potentially as a compensatory mechanism to maintain hMPC population expansion.
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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) | 0.002 | 0.001 |
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".