Inhibitor studies of leaf lamina hydraulic conductance in trembling aspen (Populus tremuloides Michx.) leaves
Bibliographic record
Abstract
The present study investigated leaf water transport properties in trembling aspen (Populus tremuloides) leaves. Leaf lamina hydraulic conductance (K(lam)) and stomatal conductance (g(s)) were drastically suppressed by NaF (a general metabolic inhibitor). In leaves treated with 0.2 mM HgCl(2) (an aquaporin blocker), K(lam) declined by 22% when the leaves were sampled in June but the decline was not significant when the leaves were sampled in August. The leaves sampled in June that transpired 30 mM beta-mercaptoethanol following mercury application showed similar K(lam) as those in control leaves transpiring distilled water. When leaves were pressure-infiltrated with 0.1 mM HgCl(2), K(lam) significantly declined by 25%. Atrazine (a photosystem II inhibitor) drastically reduced leaf net CO(2) uptake by the leaves from seedlings and mature trees but did not have any effect on K(lam) regardless of the irradiance at the leaf level during the K(lam) measurements. When PTS(3) (trisodium 3-hydroxy-5,8,10-pyrenetrisulphonate) apoplastic tracer was pressure-infiltrated inside the leaves, its concentration in the leaf exudates did not change from ambient light to high irradiance treatment and declined in the presence of HgCl(2) in the treatment solution. Trembling aspen K(lam) appears to be linked to leaf metabolism and is uncoupled from the short-term variations in photosynthesis. Aquaporin-mediated water transport does not appear to constitute the dominant pathway for the pressure-driven water flow in the leaves of trembling aspen trees.
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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) | 0.000 | 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 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".