The Function of Autophagy in Lace Plant Programmed Cell Death
Bibliographic record
Abstract
The lace plant (Aponogeton madagascariensis) is an aquatic monocot that utilizes programmed cell death (PCD) to form perforations throughout its mature leaves as part of normal development. The lace plant is an emerging model system representing a unique form of developmental PCD. The role of autophagy in lace plant PCD was investigated using live cell imaging, transmission electron microscopy (TEM), immunolocalization, and in vivo pharmacological experimentation. ATG8 immunostaining and acridine orange staining revealed that autophagy occurs in both healthy and dying cells. Autophagosome-like vesicles were also found in healthy and dying cells through ultrastructural analysis with TEM. Following autophagy modulation, there was a noticeable increase in vesicles and vacuolar aggregates. A novel cell death assay utilizing lace plant leaves revealed that autophagy enhancement with rapamycin significantly decreased cell death rates compared to the control, whereas inhibition of autophagosome formation with wortmannin or blocking the degradation of cargoes with concanamycin A had an opposite effect. Although autophagy modulation significantly affected cell death rates in cells that are destined to die, neither the promotion nor inhibition of autophagy in whole plants had a significant effect on the number of perforations formed in lace plant leaves. Our data indicate that autophagy predominantly contributes to cell survival and we found no clear evidence for its direct involvement in the induction of developmental PCD during perforation formation in lace plant leaves.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".