Bibliographic record
Abstract
Membranes of mammalian subcellular organelles contain defined amounts of specific phospholipids that are required for normal functioning of proteins in the membrane. Despite the wide distribution of most phospholipid classes throughout organelle membranes, the site of synthesis of each phospholipid class is usually restricted to one organelle, commonly the endoplasmic reticulum (ER). Thus, phospholipids must be transported from their sites of synthesis to the membranes of other organelles. In this article, pathways and subcellular sites of phospholipid synthesis in mammalian cells are summarized. A single, unifying mechanism does not explain the inter-organelle transport of all phospholipids. Thus, mechanisms of phospholipid transport between organelles of mammalian cells via spontaneous membrane diffusion, via cytosolic phospholipid transfer proteins, via vesicles and via membrane contact sites are discussed. As an example of the latter mechanism, phosphatidylserine (PS) is synthesized on a region of the ER (mitochondria-associated membranes, MAM) and decarboxylated to phosphatidylethanolamine in mitochondria. Some evidence is presented suggesting that PS import into mitochondria occurs via membrane contact sites between MAM and mitochondria. Recent studies suggest that protein complexes can form tethers that link two types of organelles thereby promoting lipid transfer. However, many questions remain about mechanisms of inter-organelle phospholipid transport in mammalian cells.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".