Programmed cell death: genes involved in signaling, regulation, and execution in plants and animals
Bibliographic record
Abstract
Programmed cell death (PCD) is a suicide mechanism adopted by multicellular organisms that is essential for development and resistance to different forms of stress. In plants, PCD is involved from embryogenesis to death of the whole plant. PCD is genetically regulated and the molecular pathways involved in different forms of this process in animals are relatively more understood than in plants. At the morphological level, apoptosis, one of the forms of PCD in animals, and plant PCD have some similarities such as cell shrinkage, shrinkage of the nucleus, and DNA fragmentation. Because morphological characteristics are a product of the genetically encoded PCD mechanism, it is of interest to figure out how much of the apoptotic pathway is shared with plant PCD in terms of the genes involved. Evidence of some level of similarities has been gathered in the last decade, supporting conservation during signaling, regulation, and execution of apoptosis and plant PCD. A continued search into the genomes of plants has provided insights about homologues of apoptosis genes present in plants, and functional analysis provides evidence about which genes are carrying out similar roles during apoptosis and plant PCD. This review is aimed at updating on the progress of plant PCD mechanism research and highlighting some of the similarities and differences between plant and mammalian PCD mechanisms, with special focus on the commonalities.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".