Are phloem sieve tubes leaky conduits supported by numerous aquaporins?
Bibliographic record
Abstract
PREMISE OF THE STUDY: Aquaporin membrane water channels have been previously identified in the phloem of angiosperms, but currently their cellular characterization is lacking, especially in tree species. Pinpointing the cellular location will help generate new hypotheses of how membrane water exchange facilitates sugar transport in plants. METHODS: L.) in leaf, petiole, and stem organs. Immuno-labeling techniques were used to characterize the distribution of PIP1 and PIP2 subfamilies of aquaporins along the phloem pathway. Confocal and super resolution microscopy (3D-SIM) was used to identify the localization of aquaporins at the cellular level. KEY RESULTS: Sieve tubes of the leaf lamina, petiole, and stem were labeled with antibodies directed at PIP1s and PIP2s. While PIP2s were mostly observed in the plasma membrane, PIP1s showed both an internal membrane and plasma membrane labeling pattern. CONCLUSIONS: The specificity and consistency of PIP2 labeling in sieve element plasma membranes points to high water exchange rates between sieve tubes and adjacent cells. The PIP1s may relocate between internal membranes and the plasma membrane to facilitate dynamic changes in membrane permeability of sieve elements in response to changing internal or environmental conditions. Aquaporin-mediated changes in membrane permeability of sieve tubes would also allow for some control of radial exchange of water between xylem and phloem.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".