Enhanced collagen type I synthesis by human tenocytes subjected to periodic in vitro mechanical stimulation
Bibliographic record
Abstract
BACKGROUND: Mechanical stimulation (e.g. slow heavy loading) has proven beneficial in the rehabilitation of chronic tendinopathy, however the optimal parameters of stimulation have not been experimentally determined. In this study of mechanically stimulated human tenocytes, the influence of rest insertion and cycle number on (1) the protein and mRNA levels of type I and III collagen; (2) the mRNA levels of transforming growth factor beta (TGFB1) and scleraxis (SCXA); and (3) tenocyte morphology, were assessed. METHODS: Human hamstring tenocytes were mechanically stimulated using a Flexcell® system. The stimulation regimens were 1) continuous and 2) rest-inserted cyclic equiaxial strain at a frequency of 0.1 Hz for 100 or 1000 cycles. Data were normalized to unstimulated (non-stretched) control groups for every experimental condition. qPCR was performed to determine relative mRNA levels and quantitative immunocytochemistry image analysis was used to assess protein levels and cell morphology. RESULTS: Collagen type I mRNA level and pro-collagen protein levels were higher in tenocytes that were subjected to rest-inserted mechanical stimulation, compared to continuous stretching (p<0.05). Rest insertion and increased cycle number also had significant positive effects on the levels of mRNA for TGFB1 and SCXA (p<0.05). There was no direct relation between cell morphology and gene expression, however mechanical stimulation, overall, induced a metabolically active tenocyte phenotype as evidenced by cells that on average demonstrated a decreased major-minor axis ratio (p<0.05) with greater branching (p<0.01). CONCLUSIONS: The incorporation of rest periods in a mechanical stretching regimen results in greater collagen type I synthesis. This knowledge may be beneficial in refining rehabilitation protocols for tendon injury.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".