Neurotrophic Factor Changes in the Rat Thick Skin following Chronic Constriction Injury of the Sciatic Nerve
Bibliographic record
Abstract
BACKGROUND: Cutaneous peripheral neuropathies have been associated with changes of the sensory fiber innervation in the dermis and epidermis. These changes are mediated in part by the increase in local expression of trophic factors. Increase in target tissue nerve growth factor has been implicated in the promotion of peptidergic afferent and sympathetic efferent sprouting following nerve injury. The primary source of nerve growth factor is cells found in the target tissue, namely the skin. Recent evidence regarding the release and extracellular maturation of nerve growth factor indicate that it is produced in its precursor form and matured in the extracellular space. It is our hypothesis that the precursor form of nerve growth factor should be detectable in those cell types producing it. To date, limitations in available immunohistochemical tools have restricted efforts in obtaining an accurate distribution of nerve growth factor in the skin of naïve animals and those with neuropathic pain lesions. It is the objective of this study to delineate the distribution of the precursor form of nerve growth factor to those cell types expressing it, as well as to describe its distribution with respect to those nerve fibers responsive to it. RESULTS: We observed a decrease in peptidergic fiber innervation at 1 week after the application of a chronic constriction injury (CCI) to the sciatic nerve, followed by a recovery, correlating with TrkA protein levels. ProNGF expression in CCI animals was significantly higher than in sham-operated controls from 1-4 weeks post-CCI. ProNGF immunoreactivity was increased in mast cells at 1 week post-CCI and, at later time points, in keratinocytes. P75 expression within the dermis and epidermis was significantly higher in CCI-operated animals than in controls and these changes were localized to neuronal and non-neuronal cell populations using specific markers for each. CONCLUSIONS: We describe proNGF expression by non-neuronal cells over time after nerve injury as well as the association of NGF-responsive fibers to proNGF-expressing target tissues. ProNGF expression increases following nerve injury in those cell types previously suggested to express it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".