The Association Between Gestational Diabetes and Microbiota in Placenta and Cord Blood
Bibliographic record
Abstract
Objective: Early life is a critical period for gut microbial development. It is still controversial whether there is microbiota during a healthy pregnancy. Gestational diabetes mellitus (GDM) is associated with increased risk of metabolic syndrome in the offspring and the mechanisms are unclear. We sought to explore whether microbiota in placenta and cord blood may be altered in GDM. Methods: Placenta and cord blood samples were collected from 8 GDM and 7 euglycemic (control) term pregnancies in caesarean deliveries without evidence of clinical infections. The Illumina MiSeq Sequencing System was used to detect the microbiota based on the V3-V4 hypervariable regions of the 16S ribosomal RNA gene. Results: The microbiota were detectable in all placental samples. Compared GDM vs. controls, there were more operational taxonomic units (OTUs) (Mean±SE: 373.63±14.61 versus 332.43±9.92, P=0.024), higher Ace indice (395.15±10.56 versus 356.27±8.47, P=0.029) and Chao indice (397.67±10.24 versus 361.32±8.87, P=0.04). The placental microbiota was mainly composed of four phyla: Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria at the phylum level and 10 dominant genus at the genus level in both GDM and controls. Despite of the dominant similarity in microbiota composition, at the OTU level, the abundance of Ruminococcus, Coprococcus, Paraprevotella, and Lactobacillus were higher, while Veillonella was lower in the placentas of GDM vs. controls. The microbiota was detected in one of the 15 cord blood samples, and its components were similar as to the corresponding placental microbiota at both phylum and genus levels suggesting placental microbiota as the potential source. Conclusions: The most abundant phyla and genus of placental microbiota were similar in GDM and euglycemic pregnancies, but GDM was associated with higher diversity of placental microbiota. Further study is needed to confirm the existence of microbiota in cord blood in pregnancies without clinical infection.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".