Delivery mode, birth order, and sex impact neonatal microbial colonization
Bibliographic record
Abstract
The initial microbial colonization of the infant gut during birth plays a critical role in shaping both immediate and long-term health outcomes. While mode of delivery is a known determinant of this colonization process, the potential impacts of infant sex and birth order remain underexplored. This study investigates the influence of delivery mode, infant sex, and birth order (maternal parity) on the microbial communities in first-pass meconium samples from neonates, using 16S rRNA gene sequencing. We found that delivery mode impacted the presence of detectable microbial communities. Specifically, only 17% of samples from neonates delivered by elective Cesarean section showed any microbial presence, compared to approximately two-thirds of samples from neonates exposed to maternal vaginal microbes (emergency C-section or vaginal delivery). Among vaginally delivered neonates without antibiotic exposure, birth order was associated with taxonomic shifts. Neonates born to primiparous mothers had a lower abundance of Bifidobacterium, a keystone species in the infant gut microbiome. Unexpectedly, the gut microbiota differed by infant sex, with males having lower alpha diversity and shifts in microbial community composition (PERMANOVA p = 0.008), characterized by elevated levels of Enterobacteriales, which was both less prevalent and less abundant in female neonates. These findings highlight the intricate interplay between delivery mode, infant sex, and birth order in shaping the early gut microbiome.
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 | 0.003 |
| 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) | 0.002 | 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".