Post-Transcriptional Regulation by microRNAs during Drought in Rye
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rye ( Secale cereale L.) is renowned for its strong adaptability in marginal environments and is of great significance for ensuring food security and achieving sustainable agriculture in areas with frequent droughts. This study systematically explored the miRNA expression dynamics of rye under drought stress and its mechanism of action in gene silencing, signal integration and stress adaptation. Through high-throughput sequencing technology, multiple differentially expressed mirnas under drought conditions were identified, and their potential target genes were predicted. The results of functional annotation and network analysis indicated that these mirnas were mainly involved in regulating key pathways such as reactive oxygen species (ROS) clearance, abscisic acid (ABA) signaling, and transcriptional regulation related to stress responses. In the case studies of miR398, miR159 and miR166, the research revealed how specific mirNA-target gene interactions affect the physiological characteristics of rye under drought stress, including ROS clearance efficiency, hormone signal regulation and leaf morphology changes, etc. This study not only deepens the understanding of the molecular response mechanism of rye to drought, but also provides new ideas and technical support for mirNa-based functional genomics research and the improvement of stress-resistant crops in the context of climate change.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it