Targeted lipidomics – advances in profiling lysophosphocholine and platelet‐activating factor second messengers
Bibliographic record
Abstract
Glycerophosphocholines are the major building blocks of biological membranes. They are also precursors of low-molecular-weight second messengers with mass to charge ratios of 450-600. These messengers include lysophosphatidylcholines (LPCs) and lyso-platelet activating factors (PAFs) that may be further processed into PAFs. Often considered as a single species, LPCs, PAFs and lyso-PAFs are, in fact, families of glycerophosphocholine-derived lipids distinguished by the linkage of their sn-1 carbon chains to the phosphoglyceride backbone (ester or ether), their sn-1 carbon chain length and degree of unsaturation, and the identity of their sn-2 constituents (a hydroxyl or acetyl group). Each LPC and PAF species exhibits a different affinity for its cognate G-protein-coupled receptors, and each species elicits receptor-independent actions that play critical signalling roles. Targeted mass spectrometry-based lipidomic approaches are enabling the molecular identification and quantification of these low-abundance second messengers. Variations between datasets map the temporal landscape of second messengers available for signalling, and provide snapshots of the state of structural membrane compositional remodelling at the time of extraction. Here, we review a number of advances in lipidomic methodologies used to identify LPCs, lyso-PAFs and PAFs, and highlight how these targeted approaches are providing valuable insight into the roles played by the cellular lipidome in cell function and disease susceptibility.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".