A transcriptomic study reveals differentially expressed genes and pathways respond to simulated acid rain in <i>Arabidopsis thaliana</i>
Bibliographic record
Abstract
Acid rain, as a worldwide environmental issue, can cause serious damage to plants. In this study, we provided the first case study on the systematic responses of arabidopsis (Arabidopsis thaliana (L.) Heynh.) to simulated acid rain (SiAR) by transcriptome approach. Transcriptomic analysis revealed that the expression of a set of genes related to primary metabolisms, including nitrogen, sulfur, amino acid, photosynthesis, and reactive oxygen species metabolism, were altered under SiAR. In addition, transport and signal transduction related pathways, especially calcium-related signaling pathways, were found to play important roles in the response of arabidopsis to SiAR stress. Further, we compared our data set with previously published data sets on arabidopsis transcriptome subjected to various stresses, including wound, salt, light, heavy metal, karrikin, temperature, osmosis, etc. The results showed that many genes were overlapped in several stresses, suggesting that plant response to SiAR is a complex process, which may require the participation of multiple defense-signaling pathways. The results of this study will help us gain further insights into the response mechanisms of plants to acid rain stress.
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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".