Early life environmental exposures have a minor impact on the gut ecosystem following a natural birth
Bibliographic record
Abstract
A growing body of evidence suggests that the environment is an important source of colonizing bacteria for the gastrointestinal tract of C-section delivered infants, who undergo multiple birth-related interventions; however, the extent to which environmental microbes impact vaginally delivered infants remains unclear. Here we investigated the impact of rural and urban environmental exposures on microbial establishment and immunity in vaginally delivered mice. We simulated rural and urban home environments by adding soil types to cages from breeding to weaning. Our aims were to determine the impact of rural and urban soil exposures on the gut microbiome in young mice and to understand whether these changes persisted into adulthood. Host immune cytokines and microbial short-chain fatty acids were quantified to understand the impact on immunity. We found that early-life soil exposure had a minor effect on the richness of the neonatal gut microbiota contributing 5% and 9% variation in the bacterial community structure between mice during early-life and adulthood, respectively. Exposure to urban soil increased Clostridiaceae and propionic acid which persisted into adulthood. While soil exposure had a limited effect on the gut taxa, systemic cytokine and chemokine profiles were altered in adulthood. The findings presented here show that unlike in C-section deliveries previously reported, environmental exposures following a natural birth have a limited impact on the gut microbial taxa but potentially play an important role in immune-mediated disease susceptibility later in life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".