Substrate viscoelasticity affects human macrophage morphology and phagocytosis
Bibliographic record
Abstract
Viscoelasticity is an inherent characteristic of many living tissues and, in an attempt to better recapitulate this aspect in cell culture, hydrogel biomaterials have been engineered to exhibit time-dependent energy-dissipative mechanical behavior. Viscoelastic hydrogel culture platforms have been instrumental in understanding the biological effects of viscoelasticity. Although viscoelasticity has been shown to regulate fundamental cell processes such as spreading and differentiation in adherent cells, the influence of viscoelasticity on macrophage behavior has not been explored. Here, we use a tunable viscoelastic polyacrylamide hydrogel culture system to demonstrate that viscoelasticity is an important biophysical regulator of macrophage function. After biologically validating our system with HS-5 fibroblasts to show behavior consistent with existing reports, we seed human THP-1 monocytes on these viscoelastic substrates and differentiate them into macrophages. THP-1 macrophages become smaller and rounder, and less efficient at phagocytosis on more viscous polyacrylamide hydrogel substrates. Since macrophages play key roles in mounting responses such as inflammation and fibrosis, these results indicate that viscoelasticity is an important parameter in the design of immunomodulatory biomaterials.
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".