Behaviors of Microtubules (MTs) Driven by Biological Motors (Dynein c) at Collisions Against Micro-Fabricated Tracks and MTs for Potential Nano-Bio-Machines
Bibliographic record
Abstract
In vitro motility assays, where protein motors (attached to a surface) move protein filaments, have been used for investigating protein motors' functions. In recent decades, these assays are extended to explore potential applications of motor proteins as biological motors in nano-bio-machine development. Recent attempts include fabricating micrometer-scale tracks on the surface to confine and guide the flow of bio-filaments as a power transfer medium driven by the motor proteins. Understanding the interaction between bio-filaments and fabricated tracks as well as the mutual interaction between bio-filaments is of importance to the design of potential nano-bio-machines. In this study, we investigate the behaviors of a microtubule driven by axonemal dynein at the collision against another microtubule and micro-fabricated walls, respectively. Based on experimental observations, we propose a model to study possible mechanisms for the microtubule-microtubule and microtubule-wall interactions, which involve bumping force, bending moment and torque generation.
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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 | 0.000 | 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 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".