Sphingolipids as cell fate regulators in lung development and disease
Bibliographic record
Abstract
Sphingolipids are a diverse class of signaling molecules implicated in many important aspects of cellular biology, including growth, differentiation, apoptosis, and autophagy. Autophagy and apoptosis are fundamental physiological processes essential for the maintenance of cellular and tissue homeostasis. There is great interest into the investigation of sphingolipids and their roles in regulating these key physiological processes as well as the manifestation of several disease states. With what is known to date, the entire scope of sphingolipid signaling is too broad, and a single review would hardly scratch the surface. Therefore, this review attempts to highlight the significance of sphingolipids in determining cell fate (e.g. apoptosis, autophagy, cell survival) in the context of the healthy lung, as well as various respiratory diseases including acute lung injury, acute respiratory distress syndrome, bronchopulmonary dysplasia, asthma, chronic obstructive pulmonary disease, emphysema, and cystic fibrosis. We present an overview of the latest findings related to sphingolipids and their metabolites, provide a short introduction to autophagy and apoptosis, and then briefly highlight the regulatory roles of sphingolipid metabolites in switching between cell survival and cell death. Finally, we describe functions of sphingolipids in autophagy and apoptosis in lung homeostasis, especially in the context of the aforementioned diseases.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".