Neonatal gut microbiota succession in mice mapped over time, site, injury and single immunoglobulin interleukin-1 related receptor genotype
Bibliographic record
Abstract
Summary Microbial succession during postnatal gut development in mice is likely impacted by site of sampling, time, intestinal injury, and host genetics. We investigated this in wild-type and Sigirr transgenic mice that encode the p.Y168X mutation identified in a neonate with necrotizing enterocolitis (NEC). Temporal profiling of the ileal and colonic microbiome after birth to weaning revealed a clear pattern of progression from a less diverse, Proteobacteria/Escherichia_Shigella dominant community to a more diverse, Firmicutes/Bacteroidetes dominant community. Formula milk feeding, a risk factor for necrotizing enterocolitis, decreased Firmicutes and increased Proteobacteria leading to enrichment of bacterial genes denoting exaggerated glycolysis and increased production of acetate and lactate. Sigirr transgenic mice exhibited modest baseline differences in microbiota composition but exaggerated formula feeding-induced dysbiosis, mucosal inflammation, and villus injury. Postnatal intestinal microbiota succession in mice resembles human neonates and is shaped by developmental maturity, ileal vs. colonic sampling, formula feeding, and Sigirr genotype.
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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 | 0.001 | 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 | 0.001 |
| 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".