Polyunsaturated fatty acid metabolism in human Mono Mac‐1 cells
Bibliographic record
Abstract
The human monocyte‐like Mono Mac‐1 (MM‐1) cell line is a good model to study the differentiation of monocytes toward a macrophage‐like phenotype. In this study, polyunsaturated fatty acid (PUFA) metabolism in untreated and LPS‐differentiated MM‐1 cells was investigated. When MM‐1 cells were incubated with various n‐3 and n‐6 PUFA, they were efficiently elongated and desaturated through the delta‐6 and delta‐5 desaturase steps with some capacity to convert 22:4n‐6 and 22:5n‐3 to 22:5n‐6 and 22:6n‐3, respectively. The cells could also retroconvert 22:4n‐6 and 22:5n‐3 to 20:4n‐6 and 20:5 n‐3, respectively. When cells were differentiated to a macrophage phenotype, they were more enriched in 20:4n‐6 and 20:5n‐3. Additionally, differentiated cells accumulated 2‐fold more 20:4n‐6 and 6‐fold more 20:5n‐3 compared to undifferentiated cells when incubated with their 18‐carbon precursors. Similarly, retroconversion to 20:4n‐6 and 20:5n‐3 from their 22‐carbon counterparts was also more efficient in differentiated cells. Since 20:4n‐6 and 20:5n‐3 are substrates for the 5‐lipoxygenase (5‐LO), its expression was also investigated. 5‐LO mRNA was increased 10‐fold following differentiation as determined by qPCR, and protein content increased from undetectable levels as assessed by Western blots. Differentiated cells also acquired the capacity to synthesize leukotriene B 4 following ionophore stimulation. In conclusion, PUFA metabolism of MM‐1 cells is modified following differentiation and these cells may represent a good model to investigate changes in PUFA and eicosanoid metabolism that accompany human monocyte‐macrophage differentiation. (Supported by the Canadian Institutes of Health Research and the Canada Research Chairs).
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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) | 0.002 | 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".