Behavior of α, β tubulin in DMSO-containing electrolytes
Bibliographic record
Abstract
α, β-tubulin is a cytoskeletal protein that forms cylindrical structures termed microtubules, which are crucial to the cell for a variety of roles. Microtubules are frequently modelled as one-dimensional bionanowires that act as ion transporters in the cell. In this work, we used dynamic light scattering (DLS) to measure the hydrodynamic diameter of tubulin in the presence of a polar aprotic co-solvent. We found that the hydrodynamic diameter increased with increasing DMSO volume fraction, almost doubling at 20% DMSO. To evaluate if this was due to an enlarged solvation shell, we performed reference interaction site model (RISM) simulations and found that the extent of solvation was unchanged. Using fluorescence microscopy, we then showed that tubulin was polymerization competent in the presence of colchicine, and thus inferred the presence of oligomers in the presence of DMSO, which points to its mechanism of action as a microtubule polymerization enhancing agent. Tubulin oligomers are known to form when microtubules depolymerize and are controversially implicated in microtubule polymerization. We show that DLS may be used to monitor early-state microtubule polymerization and is a viable alternative to fluorescence and electron microscopy-based methods. Our findings showing that DMSO causes tubulin oligomerization are thus of critical importance, both for creating bio-inspired nanotechnology and determining its biophysical roles in the cell.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".