Analyzing and predicting of the effect of Lactobacillus peptidoglycan on gene expression in immune cells of BALB/c mice immune cells using GO database
Why this work is in the frame
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Bibliographic record
Abstract
Objective:To explore the effect of Lactobacillus peptidoglycan (PGN) on gene expressing profile of murine immune cells.Methods:BALB/c mice were administrated (i.p.) with Lactobacillus peptidoglycan once or three times.Total RNA was extracted from pooled peritoneal macrophages and splenic lymphocytes.Affymetrix MOE430A genechip was used to analyze gene expression.Expression data was further analyzed using tools based on GO database (GoSufer,DAVID cluster analysis tool and GenMAPP).Significantly changed genes for their expressing amount was termed as PGN responsive genes.Results:1 dose of WPG administration triggered a rapid and widespread response in the expressing prifile.When treated thrice,a slow but more specific response was induced which was focused on immune response.PGN responsive genes were analyzed using GenMAPP,the results showd that PGN-representative biological process GO terms were related to macrophage phagocytic activity,lymphocyte activation functionation and positive regulation of inflammatory response.The GO terms related to molecule function were related to metabolism and signal transduction.The GO terms of cellular components were related to immunological synapse and T cell receptor complex.Conclusion:WPG mainly induceds the activations of innate immune response and enhanced antigen presentation.
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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 | 0.000 | 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 it