The influence of chromosome flexibility on chromosome transport during anaphase A
Bibliographic record
Abstract
The role of protein flexibility in molecular motor function has previously been studied by considering a Brownian ratchet motor that is connected to its cargo by an elastic spring, with the result that the average velocity of the motor/cargo system is increased by reducing the stiffness of the linkage. Here, we extend this investigation to the case of chromosome transport during anaphase A, in which the relevant flexibility is not primarily in the motor/cargo linkage but rather in the cargo itself, i.e., in the chromosome. We model the motor mechanism as an imperfect Brownian ratchet with a built-in opposing load and the chromosome as a collection of discrete segments linked by an elastic energy function that discretizes the potential energy of an elastic rod. Thermal fluctuations are produced in the model by random forces, as in Brownian dynamics. All of the parameters that characterize the chromosome are known or can be estimated from experimental data, as can all but one of the motor parameters, which is adjusted to give the correct transport velocity of normal-length chromosomes. With the parameters so determined, we then reproduce the experimental finding of Nicklas [Nicklas, R. B. (1965) J. Cell Biol. 25, 119-135] that chromosome speed is essentially independent of chromosome length, even though our model contains no "velocity governor." We find instead that this effect is a consequence of chromosome flexibility, as it disappears when stiffer than normal chromosomes are considered.
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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 | 0.001 |
| 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 | 0.001 | 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".