Plastid protein delivery: coping with diversityThis review is one of a selection of papers published in the Special Issue on Plant Cell Biology.
Bibliographic record
Abstract
Plastids play a central role in a variety of biosynthetic activities such as photosynthesis, amino acid synthesis, and oil production. Many of these activities depend on the compartment’s ability to adapt appropriately to the ever-changing environment of a plant cell. The pressure to adapt can arise from both internal and external sources. The complex nature of these adaptation activities is likely to be mirrored in the diversity of proteins being transported in a given situation. This diversity can be manifested at all molecular levels of the proteins, from different transit signal-bearing preproteins to different structural versions of the same preprotein. Unanticipated changes can also arise spontaneously upon exposing the population of translocating proteins to environmental stress, for example heat or cold. It is therefore important for plastids to maintain a responsive and efficient protein transport process to accommodate all situations, immediately or for the longer-term. By drawing on existing evidence, this review explores specific structural features or schemes for adapting the plastid protein delivery process and speculates on other adaptation possibilities for future consideration.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".