Substance P enhances collagen remodeling and MMP‐3 expression by human tenocytes
Bibliographic record
Abstract
The loss of collagen organization is considered a hallmark histopathologic feature of tendinosis. At the cellular level, tenocytes have been shown to produce signal substances that were once thought to be restricted to neurons. One of the main neuropeptides implicated in tendinosis, substance P (SP), is known to influence collagen organization, particularly after injury. The aim of this study was to examine the influence of SP on collagen remodeling by primary human tendon cells cultured in vitro in three-dimensional collagen lattices. We found that SP stimulation led to an increased rate of collagen remodeling mediated via the neurokinin-1 receptor (NK-1 R), the preferred cell receptor for SP. Gene expression analysis showed that SP stimulation resulted in significant increases in MMP3, COL3A1 and ACTA2 mRNA levels in the collagen lattices. Furthermore, cyclic tensile loading of tendon cell cultures along with the administration of exogenous SP had an additive effect on MMP3 expression. Immunoblotting confirmed that SP increased MMP3 protein levels via the NK-1 R. This study indicates that SP, mediated via NK-1 R, increases collagen remodeling and leads to increased MMP3 mRNA and protein expression that is further enhanced by cyclic mechanical loading.
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 | 0.000 | 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 | 0.000 |
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".