The functional response of U937 macrophage-like cells is modulated by extracellular matrix proteins and mechanical strain
Bibliographic record
Abstract
Extracellular matrix proteins (ECMs) play a significant role in the transfer of mechanical strain to monocyte-derived macrophages (MDMs) affecting morphological changes in a foreign body reaction. This study investigated how the functional responses of U937 macrophage-like cells differed when subjected to 2 dynamic strain types (nonuniform biaxial or uniform uniaxial strain) while cultured on siloxane membranes coated with either collagen type I or RGD peptide repeats (ProNectin). Biaxial strain caused an increase in intracellular esterase and acid phosphatase (AP) activities, as well as monocyte-specific esterase (MSE) protein levels in cells that were seeded on either uncoated surfaces (shown previously) or collagen, but not ProNectin. Released AP activity, but not released esterase activity, was increased on all surfaces. Biaxial strain increased IL-6, but not IL-8 on all surfaces. When cells were subjected to uniaxial strain, intracellular esterase increased on coated surfaces only, whereas intracellular AP activity was unaffected. Both esterase and AP released activities increased on all surfaces. Uniaxial strain increased the release of IL-6 on all surfaces, but IL-8 on coated surfaces only. This study demonstrated for the first time that ECM proteins could specifically modulate cellular responses to different types of strain. Using this approach with an in vitro cell system may help to unravel the complex function of MDMs in the foreign-body reaction.
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) | 0.001 | 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".