Increased Prevalence of Methanosphaera stadtmanae in Inflammatory Bowel Diseases
Bibliographic record
Abstract
BACKGROUND: The gut microbiota is associated with the modulation of mucosal immunity and the etiology of inflammatory bowel diseases (IBD). Previous studies focused on the impact of bacterial species on IBD but seldom suspected archaea, which can be a major constituent of intestinal microbiota, to be implicated in the diseases. Recent evidence supports that two main archaeal species found in the digestive system of humans, Methanobrevibacter smithii (MBS) and Methanosphaera stadtmanae (MSS) can have differential immunogenic properties in lungs of mice; with MSS but not MBS being a strong inducer of the inflammatory response. We thus aimed at documenting the immunogenic potential of MBS and MSS in humans and to explore their association with IBD. METHODS: To validate the immunogenicity of MBS and MSS in humans, peripheral blood mononuclear cells from healthy subjects were stimulated with these two microorganisms and the production of inflammatory cytokine TNF was measured by ELISA. To verify MBS and MSS prevalence in IBD, stool samples from 29 healthy control subjects and 29 patients suffering from IBD were collected for DNA extraction. Plasma was also collected from these subjects to measure antigen-specific IgGs by ELISA. Quantitative PCR was used for bacteria, methanogens, MBS and MSS quantification. RESULTS: Mononuclear cells stimulated with MSS produced higher concentrations of TNF (39.5 ng/ml) compared to MBS stimulation (9.1 ng/ml). Bacterial concentrations and frequency of MBS-containing stools were similar in both groups. However, the number of stool samples positive for the inflammatory archaea MSS was higher in patients than in controls (47% vs 20%). Importantly, only IBD patients developed a significant anti-MSS IgG response. CONCLUSION: The prevalence of MSS is increased in IBD patients and is associated with an antigen-specific IgG response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".