Proteomic Profiling of Lipopolysaccharide-Activated Macrophages by Isotope Coded Affinity Tagging
Bibliographic record
Abstract
Lipopolysaccharide (LPS), a glycolipid component of the outer membranes of Gram-negative bacteria, initiates proinflammatory, proapoptotic, and antiapoptotic pathways upon binding to macrophage TLR4. Macrophages that are exposed to LPS become activated and exhibit altered morphology and response to infection. We performed isotope coded affinity tagging (ICAT), multidimensional liquid chromatography, and mass spectrometry to identify proteins that are differently expressed between naive and LPS-activated macrophages. We performed replicate ICAT analyses on RAW 264.7 cultured mouse macrophages as well as C57BL/6 bone marrow derived mouse macrophages. We identified and obtained relative abundances for 1064 proteins, of which we identified 36 as having significantly different expression levels upon activation by LPS. We also compared our results with a two color microarray gene expression assay performed by the Institute for Systems Biology and observed approximately 75% agreement between mRNA transcription and protein expression regarding up- or down-regulation of gene products. We used Western blot analysis to confirm the findings of ICAT and mRNA for one protein, sequestosome 1, the cellular concentration of which was observed to increase upon activation by LPS.
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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 | 0.000 |
| 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 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".