A comparison of pain responses, hemodynamic reactivity and fibre type composition between Bergström and microbiopsy skeletal muscle biopsies
Bibliographic record
Abstract
This study tested the hypotheses that 1) skeletal muscle biopsies performed with the Bergström needle evoke larger perceptions of pain and greater hemodynamic reactivity compared to biopsies performed with the microbiopsy needle, and 2) both needles yield samples with similar fibre type compositions when samples are collected at similar skeletal muscle depths. Fourteen healthy (age: 21.6 ± 3.2 years; VO2peak: 41.5 ± 5.8 mL/kg/min) males (n = 7) and females (n = 7) provided two resting skeletal muscle biopsies, one with each needle type, following a randomized crossover design. Participants completed the short-form McGill Pain Questionnaire and the Brief Pain Inventory before, during, and after the skeletal muscle biopsies. Hemodynamic reactivity was assessed by measuring heart rate (HR) and mean arterial pressure (MAP) at rest and during the biopsy procedures. Immunofluorescence analysis was used to assess fibre type composition in vastus lateralis samples. Compared to the microbiopsy needle, the Bergström needle elicited a larger perception of pain but similar hemodynamic reactivity during the biopsy. Both needles yielded skeletal muscle samples with similar fibre type composition and resulted in similar perceptions of pain and pain-related interference during the post-biopsy recovery period. Collectively, these findings suggest that studies should consider using the microbiopsy needle rather than the Bergström needle unless large amounts of muscle tissue or certain muscle fibre lengths are required. However, future work should determine whether our findings are generalizable to biopsies performed with different procedures and/or types of Bergström/microbiopsy needles.
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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 | 0.001 | 0.002 |
| 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".