Glycerophospholipids: Roles in Cell Trafficking and Associated Inborn Errors
Bibliographic record
Abstract
Glycerophospholipids (GPLs) are the main lipid components of cellular membranes. They are implicated in membrane structure, vesicle trafficking, neurotransmission, and cell signalling. GPL molecules are amphiphilic, organized around the three carbons of glycerol. Positions sn-1 and sn-2 are each esterified to a fatty acid (FA). At position sn-3, a phosphate group is linked, which in turn can bind a polar head group, the most prevalent classes being phosphatidic acid (PA, phosphate alone as head group), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylinositol (PI), and cardiolipin (CL). Pathways of GPL biosynthesis span several cell compartments (endoplasmic reticulum (ER), Golgi mitochondria). Particularly important are mitochondria-associated membranes (MAMs), where the ER and mitochondrial outer membrane are in proximity. After synthesis, GPLs continuously undergo remodelling by FA hydrolysis and re-esterification. Esterification with different FAs alters membrane properties. Many steps in GPL synthesis and remodelling can be mediated by more than one enzyme, suggesting complexity that requires further exploration. The 38 known GPL-related inborn errors are clinically diverse. 23 (61%) have neurologic features, sometimes progressive and severe, particularly developmental delay/encephalopathy in 16 (42%) and spastic paraplegia in 12 (32%). Photoreceptor/neuroretinal disease occurs in 14 (37%). Three present skeletal dysplasias (8%). Most GPL inborn errors have been diagnosed by broad molecular testing. Lipidomics holds promise for diagnostic testing and for the discovery of functionally relevant metabolite profiles for monitoring natural history and treatment response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".