Lipopolysaccharide-stimulated, NF-kB-, miRNA-146a- and miRNA-155-mediated molecular-genetic communication between the human gastrointestinal tract microbiome and the brain
Bibliographic record
Abstract
Through the use of RNA sequencing, microRNA (miRNA) and messenger RNA (mRNA) microfluidic array analysis, LED Northern, Western and ELISA analysis and multiple bioinformatics algorithms we have discovered a novel route for pathogenic communication between the human gastrointestinal (GI)-tract microbiome and the brain. The evidence suggests that this pathogenic gut-brain circuit involves: (i) lipopolysaccharide (LPS) from the GI-tract resident enterotoxigenic Gram-negative bacteria Bacteroides fragilis (BF-LPS); (ii) LPS transit across the GI-tract barrier into the systemic circulation; (iii) transport of a highly pro-inflammatory systemic BF-LPS across the blood-brain barrier (BBB) into the brain-parenchyma and neuronal-cytoplasm; (iv) activation and signaling via the pro-inflammatory NF-kB (p50/p65) transcription-factor complex; (v) NF-kB-coupling and significant up-regulation of the inducible pro-inflammatory microRNA-146a (miRNA-146a) and microRNA-155 (miRNA-155); each containing multiple NF-kB DNA-binding and activation sites in their immediate promoters; and (vi) subsequent down-regulation of miRNA-146a-miRNA-155 regulated mRNA targets such as that encoding complement factor H (CFH), a soluble complement control glycoprotein and key repressor of the innate-immune response. Down-regulated CFH expression activates the complement-system, the major non-cellular component of the innate-immune system while propagating neuro-inflammation. Other GI-tract microbes and their highly complex pro-inflammatory exudates may contribute to this pathogenic GI-tract-brain pathway. We speculate that it may be significant that the first Gram-negative anaerobic bacterial species intensively studied as a potential contributor to the onset of Alzheimer's disease (AD), that being the bacillus Bacteroides fragilis appears to utilize damaged or leaky physiological barriers and an activated NF-kB (p50-p65) - pro-inflammatory miRNA-146a-miRNA-155 signaling circuit to convey microbiome-derived pathogenic signals into the brain.
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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) | 0.001 | 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".