A custom microarray analysis of gene expression during programmed cell death in <i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
Programmed cell death (PCD) is a form of cellular suicide requiring active gene expression, and occurs in both animals and plants. While the cascade of events and the genes that control PCD have been extensively studied in animals, we remain largely ignorant about the similar process in plant cells. Many of the key proteins of animal cell death such as the Bcl-2 family and the caspase family of proteases do not appear to be conserved in plants, suggesting that plants may employ unique mechanisms to execute PCD. To identify genetic elements of PCD in plants, we monitored changes in transcript levels of approximately 100 selected genes during cell death in an Arabidopsis cell suspension culture using a cDNA microarray. PCD was induced in the cell cultures by two independent means (heat treatment or by allowing the cultures to senesce) to allow the distinction to be drawn between changes in gene expression that are related to PCD and those that are specific to a particular treatment. We argue that genes whose expression is altered during PCD induced by two different means may be generally involved in all types of PCD. We show that certain oxidative stress-related genes, including CSD1, CSD3, and GPX, in addition to cysteine proteinases, some transcription factors, and HR-related genes may serve as markers of a core plant cell death programme. Additionally we observe a down-regulation of the mitochondrial adenine nucleotide transporter and suggest that this may be an early event in the execution of plant PCD.
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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 | 0.001 |
| 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) | 0.002 | 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".