Lipophilic natural compounds (n‐3 polyunsaturated fatty acids) modulate plasma membrane organization in mouse CD4 <sup>+</sup> T cells (975.1)
Bibliographic record
Abstract
We have previously shown that n‐3 polyunsaturated fatty acids (PUFA) increase plasma membrane lipid order in mouse CD4 + T cells, blocking T cell activation. Since lipid rafts are important for T cell activation, we hypothesized that n‐3 PUFA perturb CD4 + T cell plasma membrane lipid rafts. To probe the mechanism for n‐3 PUFA action, CD4 + T cells from Fat‐1 transgenic mice (enriched in n‐3 PUFA), were transduced with fluorescence energy resonance transfer (FRET) lipid raft probes Lck(N10) and LAT(ΔCP), and non‐raft probe Src(N15). Co‐clustering of Lck(N10) and LAT(ΔCP) in CD4 + T cells increased in the presence of n‐3 PUFA as assessed by FRET; conversely n‐3 PUFA did not alter the co‐clustering between Lck(N10) and Src(N15). These data demonstrate that n‐3 PUFA modulate membrane nano‐organization in CD4 + T cells. We have also previously demonstrated that n‐3 PUFA decrease the mass of phosphatidylinositol‐(4,5)‐bisphosphate [PI(4,5)P 2 ] in CD4 + T cells. Since discrete pools of PI(4,5)P 2 may exist in the plasma membrane, we also determined whether n‐3 PUFA modulate spatial organization of PI(4,5)P 2 relative to raft and non‐raft domains. Co‐clustering of PH(PLC‐δ1), a PI(4,5)P 2 probe, and Lck(N10) or LAT(∆CP) was not affected by n‐3 PUFA; however, co‐clustering of PH(PLC‐δ1) and Src(N15) showed a decrease in the presence of n‐3 PUFA, suggesting that n‐3 PUFA alter the spatial organization of PI(4,5)P 2 . Grant Funding Source : Supported by NSERC and NIH
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".