Sarcodia suieae acetyl-xylogalactan regulate RAW 264.7 macrophage NF-kappa B activation and IL-1 beta cytokine production in macrophage polarization
Bibliographic record
Abstract
In this study, the effects of acetyl-xylogalactan extracted from Sarcodia suieae on RAW 264.7 macrophage polarisation were evaluated. This extracted acetyl-xylogalactan had a monosaccharide composition of 91% galactose and 9% xylose, with polysaccharide and acetyl contents of 80.6% and 19.3%, respectively. MALDI-TOF mass spectrometry and NMR spectroscopy revealed the molecular weight of the acetyl-xylogalactan to be 88.5 kDa. After acetyl-xylogalactan treatment, RAW 264.7 macrophage polarisation was noted, along with enhanced phagocytic ability. Furthermore, the Cell Counting Kit-8 (CCK-8) assay was performed and the results demonstrated non-significant alteration in lactate dehydrogenase levels in the treated cells. Next, interleukin (IL) 1β, TNF, and Malt-1 expression in RAW 264.7 macrophages treated with the S. suieae acetyl-xylogalactan was investigated through real-time quantitative polymerase chain reaction, and the results demonstrated that S. suieae acetyl-xylogalactan induced IL-1β and Malt-1 expression. RNA sequencing analysis results indicated the S. suieae acetyl-xylogalactan positively regulated cytokine production and secretion, protein secretion, and response to IL-1 activation, based on the observed GO terms. The predicted target genes in the GO enrichment analysis were found to upregulate NF-κB signalling and M0 to M1 macrophage conversion through the observed cytokine production. Thus, acetyl-xylogalactan can positively regulate RAW 264.7 macrophage polarisation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".