Author response: Aurora kinase A localises to mitochondria to control organelle dynamics and energy production
Bibliographic record
Abstract
Structures called mitochondria power cells by turning oxygen and sugar into chemical energy. Each cell can have thousands of mitochondria, which work together to supply changing energy demands. They can fuse together or break apart, forming networks that change size and produce different amounts of energy. Getting the balance right is crucial; if energy levels are too low, the cell will not be able to grow and divide. If energy levels are too high, the cell can grow at a faster rate, which can contribute to the cell becoming cancerous. Although we know that mitochondria provide energy, it is not clear how they communicate to fine-tune the supply. Some clues come from cancer cells that seem dependent on their mitochondria for survival. In these cells, levels of a protein called AURKA are higher than normal. AURKA helps cells to divide, and it interacts with many different proteins. This complexity makes it difficult to work out exactly what AURKA does, but it is possible that it plays a role in energy supply. Bertolin et al. have now investigated whether mitochondria use AURKA to communicate inside human breast cancer cells. Tagging AURKA proteins with a fluorescent marker revealed that it accumulates inside mitochondria. Once it gets there, AURKA changes the shape of the mitochondria, which has dramatic effects on their capacity to produce energy. At normal levels, AURKA causes the mitochondria to fragment, breaking apart into smaller pieces. This maintains their energy output at a normal level. If AURKA levels are too high, the mitochondria fuse together and produce more energy. This means AURKA could help to fuel fast-growing cancer cells. Current drugs that aim to treat cancer by blocking the activity of AURKA show poor results. This is partly due to the fact that the protein has so many different roles in the cell. Finding that AURKA affects mitochondria is the first step in understanding one of its unknown roles. It also suggests the possibility of developing new drugs to change how mitochondria make energy in cancer cells that contain high levels of AURKA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.214 | 0.102 |
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".