Bibliographic record
Abstract
Abstract Biological membranes consist of a complex array of proteins and lipids that create selective permeability barriers in cells. Another function of membrane lipids is their degradation to generate ‘lipid second messengers’ that can regulate important cellular functions such as cell division and cell death. The major membrane lipids of eukaryotic cells are the glycerophospholipids, the sterols and the sphingolipids. The most abundant glycerophospholipids in eukaryotic cells are phosphatidylcholine and phosphatidylethanolamine, each of which is synthesised by two independent pathways. The glycosphingolipids consist of structures in which ceramide is attached to a variety of oligosaccharide chains to create an enormously diverse class of lipids that are highly enriched on the cell surface. In mammalian cells, cholesterol is the most abundant sterol in membranes, whereas plants and fungi do not contain cholesterol per se but instead contain sterols that are related to cholesterol; prokaryotic membranes do not contain sterols. Key Concepts: Lipid bilayers provide the fundamental architecture of biological membranes. Cellular phospholipid levels are tightly regulated. Major classes of phospholipids are made by more than one pathway. Acyl chain composition of phospholipids can be modified by deacylation. The cholesterol‐lowering statin drugs regulate cholesterol biosynthesis at the step catalysed by 3‐hydroxy‐3‐methylglutaryl‐CoA reductase.
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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 0.042 |
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".