Automated, High-Resolution Micropipet Aspiration Reveals New Insight into the Physical Properties of Fluid Membranes
Bibliographic record
Abstract
We describe recent advances in our experimental approach to examine the physical properties of biological and artificial membranes by automated micropipet aspiration. New instrumentation allows us to apply fast yet precise tension protocols to membranes while continuously recording the membrane deformation with high-speed videomicroscopy. Robust algorithms for subpixel geometric measurements track the displacements of membrane edges with resolution of a few nanometers and enable us to determine changes of the membrane area and enclosed volume of pipet-aspirated cells or vesicles with exceptional accuracy. Experimentation and data analysis are greatly facilitated by custom-written software whose basic design is described here as well. Example measurements demonstrate how this technique has significantly improved the amount and reliability of data obtained by various types of micropipet-aspiration experiments, allowing us to study interesting aspects of membrane behavior that have eluded earlier techniques.
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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 | 0.000 |
| 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".