Transcriptional responses to low temperature and their regulation in <i>Arabidopsis</i>
Bibliographic record
Abstract
Recent studies have used a transcriptional profiling approach to identify genes in Arabidopsis that respond at the level of transcript abundance to cold (4 °C) or chilling (13 °C) temperatures. Results have shown that plants respond to low temperatures by altering mRNA levels of a large number of genes belonging to different independent pathways. Early transcriptional response to low temperatures frequently involves signaling pathways used to respond to other environmental stresses, indicating the existence and involvement of a complex genetic network. Genes with functions specific to low-temperature signaling pathways, and those with functions in multiple signaling pathways, especially those encoding transcription factors and other signaling molecules, have been identified based on their transcriptional responses to different environmental stresses. The qualitative and quantitative difference in transcriptional response to chilling and cold suggests that plants might have different molecular mechanisms to acclimate to different types of low-temperature stresses. The regulation and interactions of genes involved in low-temperature response at the transcriptional level has been further explored by computational methods, and preliminary results have identified motifs that are known to be important for cold response, raising the possibility of a better understanding of the processes involved.Key words: Arabidopsis, low-temperature stress, gene expression, transcriptional regulation, microarray.
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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".