Influence of intramuscular nerve growth factor injection on the response properties of rat masseter muscle afferent fibers.
Bibliographic record
Abstract
AIMS: To investigate whether local administration of nerve growth factor (NGF) decreases the mechanical threshold (MT) of putative nociceptive masseter afferent fibers as part of its mechanism of mechanical sensitization. METHODS: Electrophysiologic recordings were made from masseter afferents and a randomized, blinded approach was used to test the effects of intramuscular injection of NGF (2.5 or 25 microg/mL) into the rat masseter muscle on the MT of masseter afferents (n=65) and plasma protein extravasation. RESULTS: The plasma protein extravasation data and electrophysiological recordings indicated that rat NGF injection was not inflammatory and did not evoke afferent discharge or induce mechanical sensitization (as reflected in a decreased MT) in masseter afferents in either male or female rats. To investigate whether the lack of effect of NGF injection might be due to differences between human and rat NGF, additional experiments with human NGF injection (25 microg/mL) were undertaken. Intramuscular injection of human NGF into the rat masseter muscle also failed to evoke afferent discharges; however, it did decrease the MT of masseter afferent fibers. CONCLUSION: The finding that neither rat nor human NGF excited putative nociceptive masseter afferent fibers is consistent with a previous report that intramuscular NGF injections are not acutely painful in human subjects. The ability of human NGF injection into the rat masseter muscle to induce afferent mechanical sensitization suggests that this experimental approach may be useful for the study of peripheral mechanisms of myofascial pain and tenderness associated with temporomandibular disorders.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".