Use of Fluorescent Probes to Detect Lipid Signaling Intermediates in Macrophages
Bibliographic record
Abstract
To fulfill their function in host defense, professional phagocytes such as neutrophils and macrophages exhibit the ability to ingest (phagocytose), kill, and dispose of pathogenic microorganisms. Recent studies have provided strong evidence for the importance of membrane lipids such as polyphosphoinositides in these processes. In turn, reversible phosphorylation events, involving protein and lipid kinases and phosphatases, regulate signaling pathways involving metabolism of membrane lipids. Our ability to study lipid signaling events has been greatly facilitated by the development of fluorescent molecular imaging techniques. In particular, the expression of recombinant fusions of derivatives of the jellyfish-derived green fluorescent proteins (GFP) coupled to reporter molecules enables real-time monitoring of signaling events in live cells. Here, we discuss methods to monitor alterations in membrane polyphosphoinositides involved in signaling events regulating phagocytosis. To illustrate the use of this technology, we will focus on the role of protein tyrosine phosphatase MEG2 in phagocytosis and its modulation by phosphatidylinositol-3,4,5-triphosphate (PIP3). This approach enables investigators to ascertain the involvement of lipid intermediates in diverse signaling pathways.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".