LC–ESI–QTOF–MS, MS/MS Analysis of Glycerophospholipid Species in Three Tunisian <i>Pistacia lentiscus</i> Fruit Populations
Bibliographic record
Abstract
Abstract Three populations of Pistacia lentiscus fruits were analyzed for their contents, classes and different molecular species of glycerophospholipids (PL) in order to promote their production and marketability. The LC–ESI–TOF–MS and MS/MS were used to accomplish this analysis. Only four classes of PL were detected at different retention times—phosphatidic acid (PA), phosphatidylethanolamine (PE), phosphatidylglycerol (PG) and phosphatidylinositol (PI). There was a significant difference in the relative observed abundance of various glycerophospholipid classes. PI was found to be the dominant class in the all provenances of lentisc fruit, followed by the PG class in the KO and RM populations. Within the TB population, the PA class is more abundant than PG and PE. The major molecular specie in the PA class is PA‐C16:0/18:2 followed by PA‐C18:1/18:2; and the minor species were determined to be PA‐C16:0/18:3, and PA‐C18:3/18:2. In the PE class of phospholipids PE‐C18:1/18:1 and PE‐C18:2/18:2 are the major species identified. The phospholipids PG‐C18:2/18:2, PG‐18:2/18:1, PI‐C16:0/18:2 and PI‐C16:0/18:1 are the most abundant species within the PG and PI classes. PG‐C18:1/18:1, PI‐C18:0/18:1 and PI‐C16:0/18:3 are found to be only relatively minor chemical species. In conclusion, it is clear that the predominant molecular species of PL are those containing C16:0, C18;1, C18:2 fatty acids and the minor species are those containing C18:0 and C18:3.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".