Transcriptomic response of immune signalling pathways in intestinal epithelial cells exposed to lipopolysaccharides, Gram-negative bacteria or potentially probiotic microbes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In order to understand the appropriate use of potentially probiotic Gram-positive microbes through their introduction in the gut microbiome, it is necessary to understand the influence of individual bacteria on the host-response system at a cellular level. In the present study, we have shown that lipopolysaccharides, flagellated Gram-negative bacteria, potentially probiotic Gram-positive bacteria and yeast interact differently with human intestinal epithelial cells with a custom-designed expression microarray evaluating 17 specific host-response pathways. Only lipopolysaccharides and flagellated Gram-negative bacteria induced inflammatory response, while a subset of Gram-positive microbes had anti-inflammatory potential. The main outcome from the study was the differential regulation of the central mitogen-activated protein kinase signalling pathway by these Gram-positive microbes versus commensal/pathogenic Gram-negative bacteria. The microarray was efficient to highlight the impact of individual bacteria on the response of intestinal epithelial cells, but quantitative real-time polymerase chain reaction validation demonstrated some underestimation for down-regulated genes by the microarray. This immune array will allow us to better understand the mechanisms underlying microbe-induced host immune responses.
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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 | 0.001 | 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 | 0.000 |
| 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