Winter and summer leaves of <i>Cistus incanus</i>: differences in leaf morphofunctional traits, photosynthetic energy partitioning, and poly(ADP-ribose) polymerase (PARP) activity
Bibliographic record
Abstract
Leaf anatomy, photosynthetic performance, and the role of poly(ADP-ribosyl)ation in maintaining genomic stability in winter and summer leaves of Cistus incanus L. were investigated to evaluate the strategies allowing this species to grow in a Mediterranean climate. Measurements on summer leaves (SL) were conducted at midday and on the following morning to assess the reversibility of changes induced by high temperatures and irradiances reached at midday. Winter leaves (WL) were thicker with a lower leaf density and higher intercellular spaces compared with SL, which showed reduced net photosynthesis (Pn) and a decrease in Rubisco activity. Compared with WL, SL showed a higher thermal dissipation (ΦNPQ) in compensating for the reduced Pn. This allowed minimization of ROS production (low ΦNO) and hence prevented photo-oxidative damage. In SL, poly(ADP-ribose) polymerase (PARP) activity was down-regulated, probably allowing leaves to become tolerant to high temperatures and irradiances. SL are also characterised by chloroplasts occupying larger cell volume and well exposed to intercellular spaces. This may well favour better liquid-phase CO2 diffusion towards carboxylation sites, contributing to reducing the negative influence of high leaf density and the low percentage of intercellular spaces on photosynthesis.
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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".