Quantification of fast molecular adhesion by fluorescence footprinting
Bibliographic record
Abstract
Rolling adhesion is a unique process in which the adhesion events are short-lived and operate under highly nonequilibrium conditions. These characteristics pose a challenge in molecular force quantification, where in situ measurement of these forces cannot be achieved with molecular force sensors that probe near equilibrium. Here, we demonstrated a quantitative adhesion footprint assay combining DNA-based nonequilibrium force probes and modeling to measure the molecular force involved in fast rolling adhesion. We were able to directly profile the ensemble molecular force distribution in our system during rolling adhesion with a dynamic range between 0 and 18 pN. Our results showed that the shear stress driving bead rolling motility directly controls the molecular tension on the probe-conjugated adhesion complex. Furthermore, the shear stress can steer the dissociation bias of components within the molecular force probe complex, favoring either DNA probe dissociation or receptor-ligand dissociation.
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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 | 0.001 |
| 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".