Nano-positioning and tubulin conformation contribute to axonal transport regulation of mitochondria along microtubules
Bibliographic record
Abstract
Correct spatiotemporal distribution of organelles and vesicles is crucial for healthy cell functioning and is regulated by intracellular transport mechanisms. Controlled transport of bulky mitochondria is especially important in polarized cells such as neurons that rely on these organelles to locally produce energy and buffer calcium. Mitochondrial transport requires and depends on microtubules that fill much of the available axonal space. How mitochondrial transport is affected by their position within the microtubule bundles is not known. Here, we found that anterograde transport, driven by kinesin motors, is susceptible to the molecular conformation of tubulin in neurons both in vitro and in vivo. Anterograde velocities negatively correlate with the density of elongated tubulin dimers like guanosine triphosphate (GTP)-tubulin. The impact of the tubulin conformation depends primarily on where a mitochondrion is positioned, either within or at the rim of microtubule bundle. Increasing elongated tubulin levels lowers the number of motile anterograde mitochondria within the microtubule bundle and increases anterograde transport speed at the microtubule bundle rim. We demonstrate that the increased kinesin velocity and density on microtubules consisting of elongated dimers add to the increased mitochondrial dynamics. Our work indicates that the molecular conformation of tubulin contributes to the regulation of mitochondrial motility and as such to the local distribution of mitochondria along axons.
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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".