A rheometer-confocal platform for the study of cell deformation in three-dimensional environments
Bibliographic record
Abstract
In vivo, cells undergo various external mechanical loadings. Mechanical forces have effects on cellular behavior and activities, including aspects such as cell morphology, migration, and protein expression. Such interactions between cells and their surroundings are essential, but not clearly understood. An in-depth understanding of external mechanical forces' impacts on cells requires advanced experimental approaches. Here I present a customized platform that combines two instruments: a rheometer and a confocal microscope. I then tested the platform with sub-micron sized fluorescent beads embedded in a homogeneous gel, by comparing optically measured strain with applied strain values. This rheometer-confocal platform is ideal for studying cellular interactions with surroundings, and cell activities specifically under shear load. With the calibrated system, I studied the relations between externally applied strain and internal cell strain. Cells were cultured within the three-dimensional hydrogel matrices and sheared by the rheometer. The internal strain was indicated by the fluorescent intensity ratio of a recombinant protein construct measured by the confocal microscope. The platform enables simultaneous observation and mechanical manipulation of the sample, providing a powerful tool to investigate the mechanical interactions between cells and their surroundings.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".