Relationships of root conductivity and aquaporin gene expression in Pisum sativum: diurnal patterns and the response to HgCl2 and ABA
Bibliographic record
Abstract
Experiments were undertaken to test how aquaporins (AQPs) facilitate the uptake of water by roots of Pisum sativum. Changes in PsPIP2-1 gene expression and root hydraulic conductivity (Lpr) were measured in response to the time of day as well as treatment of the roots with a compound that reduced Lpr [i.e. mercuric chloride (HgCl2)] and one that was intended to increase Lpr [abscisic acid (ABA)]. There was a diurnal rhythm in PsPIP2-1 expression in lateral roots that was strongly correlated with diurnal changes in Lpr. Taproots also displayed a rhythm in PsPIP2-1 expression, but this was offset from that of Lpr. This suggested that changes in Lpr were mediated by changes in PsPIP2-1 mRNA transcript abundance. Reduction of Lpr by HgCl2 treatment was accompanied by an increase in PsPIP2-1 expression, implying that PsPIP2-1 expression may have increased to compensate for AQPs blocked by mercury. ABA usually increased Lpr, but changes in PsPIP2-1 were variable and the direction of the response was strongly dependent on the dose of ABA that was applied. Overall, the coincident rhythms in Lpr and PIP2 expression and response to AQP blockage are consistent with the hypothesis that Lpr changes are mediated, at least in part, by changes in PsPIP2-1 expression. Inconsistencies with ABA data may have been due to more complex interactions of ABA with AQP channels.
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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 | 0.001 |
| 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".