Two dominant timescales of cytoskeletal crosslinking in the viscoelastic response of the cytoplasm
Bibliographic record
Abstract
Cells precisely regulate their frequency-dependent viscoelastic properties in response to chemical and mechanical cues. We use optical trap-based active microrheology using intracellular probes to measure the cytoplasmic mechanical response of fibroblast and macrophage cells over a broad frequency range ($\ensuremath{\sim}0.02--350$ Hz). Both cell types show similar frequency-dependent behavior, suggesting that the mechanisms that control the cell's mechanical response are general to many cell types. At frequencies above 1 Hz, the cytoplasmic mechanical behavior shows a broad distribution of relaxation timescales consistent with power-law mechanics. At low frequencies ($<1$ Hz), cells exhibit fluidlike behavior with distinct relaxation timescales, similar to that observed in reconstituted networks of transiently crosslinked actin filaments. The response across all frequencies can be captured by a mathematical model combining a power-law term with two crosslinker-unbinding terms. The two unbinding rates required to describe the low-frequency response suggest that the viscoelastic relaxation of the cytoplasm is governed either by multiple dominant crosslinkers or by a single crosslinker with multiple states.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".