Quantitative Super‐Resolution Imaging of Molecular Tension
Bibliographic record
Abstract
DNA-based molecular tension probes have revolutionized the localization of mechanical events in live cells with super-resolution. However, imaging the magnitude of these forces at super-resolution has been challenging. Here, qtPAINT (quantitative tension points accumulation for imaging in nanoscale topography) is introduced as a strategy to image the magnitude of molecular tension with super-resolution accuracy. By leveraging the force-dependent dissociation kinetics of short DNA oligonucleotides on their complementary strands, tension is encoded on individual molecules through their binding kinetics. This method allowed for a quantitative analysis of these kinetics, providing a detailed reconstruction of the force magnitudes acting on each tension probe. The technique integrates a molecular-beacon PAINT imager with a hairpin molecular tension probe, achieving a force quantification range of 9-30 pN and maintaining a spatial resolution of 30-120 nm in low and high-density regions. Additionally, qtPAINT offers a temporal resolution on the order of a minute, enhancing its applicability for studying dynamic cellular processes.
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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 | 0.001 |
| 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".