Improved reproductive growth of euhalophyte Suaeda salsa under salinity is correlated with altered phytohormone biosynthesis and signal transduction
Bibliographic record
Abstract
Phytohormones are essential for plant reproductive growth. Salinity limits crop reproductive growth and yield, but improves reproductive growth of euhalophytes. However, little is known about the mechanisms underlying salinity's effects on plant reproductive growth. To elucidate the role of plant hormones in flower development of the euhalophyte Suaeda salsa under saline conditions, we analysed endogenous gibberellic acid (GA3,4), indoleacetic acid (IAA), zeatin riboside (ZR), abscisic acid (ABA), and brassinosteroids (BRs) during flowering in control (0 mM) and NaCl-treated (200 mM) plants. At the end of vegetative growth, endogenous GA3, GA4, ABA and BR contents in stems of NaCl-treated plants were significantly higher than those in controls. During flowering, GA3, GA4, IAA and ZR contents showed the most significant enhancement in flower organs of plants treated with NaCl when compared with controls. Additionally, genes related to ZR, IAA, GA, BR and ABA biosynthesis and plant hormone signal transduction, such as those encoding CYP735A, CYP85A, GID1, NCED, PIF4, AHP, TCH4, SnRK2 and ABF, were upregulated in S. salsa flowers from NaCl-treated plants. These results suggest that coordinated upregulation of genes involved in phytohormone biosynthesis and signal transduction contributes to the enhanced reproductive growth of S. salsa under salinity.
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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".