Spatio‐Temporal Control of Dynamic Topographic Patterns on Azopolymers for Cell Culture Applications
Bibliographic record
Abstract
Cell response to exogenous cues is the result of a complex integration of multiple biochemical/biophysical signals, which might occur simultaneously and might be characterized by specific spatial and temporal patterns. Among these signals, surface topography plays an important role in affecting cell functions and fate. However, the current understanding of the interplay between cells and topography relies on static environment. Here the intrinsic light‐responsive properties of azopolymers and the versatility of laser‐based confocal microscope technique is exploited, aiming to induce spatio‐temporal dynamic topographic changes in situ during cell culture. Diverse patterns can be designed on cell‐populated azopolymer films with high control on time, space, and on‐off signal modification. The technique proposed in this study enables the development of synthetic platforms that finely control cell orientation and migration both in time and space. The results may pave the way to unravel complex processes involved in cell‐topography interactions, thus allowing to define the spatio‐temporal features that most effectively influence cell functions.
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) | 0.001 | 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 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".