Arrangement of sympathetic fibers within the human common peroneal nerve: implications for microneurography
Bibliographic record
Abstract
Recently, interest has grown in the firing patterns of individual or multiunit action potential firing patterns in human muscle sympathetic nerve recordings using microneurography. Little is known, however, about sympathetic fiber distribution in human lower limb nerves that will affect the multiunit recordings. Therefore, the purpose of this study was to examine the sympathetic fiber distribution within the human common peroneal nerve using immunohistochemical techniques (tyrosine hydroxylase, avidin-biotin complex technique). Five-micrometer transverse and 10-μm longitudinal sections, fixed in formaldehyde, were obtained from the peroneal nerve that had been harvested from three human cadavers (83 ± 11 yr) within 24 h of death. Samples of rat adrenal gland and brain served as controls. Sympathetic fiber arrangement varied between left and right nerves of the same donor, and between donors. However, in general, sympathetic fibers were dispersed throughout ∼25-38 fascicles of the peroneal nerve. The fibers were grouped in bundles of ∼2-44 axons or expressed individually throughout the fascicles, and the distribution was skewed toward smaller bundles with median and interquartile ratio values of 5 and 1 axons/bundle, respectively. These findings confirm the bundled organization of sympathetic axons within the peroneal nerve and provide the anatomical basis for outcomes in microneurographic studies.
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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 | 0.001 |
| 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 | 0.001 |
| 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".