Correlation of placental microbiota with fetal macrosomia and clinical characteristics in mothers and newborns
Bibliographic record
Abstract
// Jia Zheng 1 , Xin-Hua Xiao 1 , Qian Zhang 1 , Li-Li Mao 1 , Miao Yu 1 , Jian-Ping Xu 1 and Tong Wang 1 1 Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Diabetes Research Center of Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China Correspondence to: Xin-Hua Xiao, email: xiaoxh2014@vip.163.com Keywords: fetal macrosomia, placenta, microbiota, 16S rRNA gene, clinical characteristics Received: April 18, 2017 Accepted: June 24, 2017 Published: July 18, 2017 ABSTRACT Substantial studies indicated that fetal macrosomia was associated with detrimental pregnancy outcomes, and increased susceptibility to metabolic diseases in later life. However, investigations into the association between placental microbiota and fetal macrosomia are limited. We aimed to profile the placental microbiota of fetal macrosomia and study whether they relate to clinical characteristics. Placenta samples were collected from fetal macrosomias and newborns with normal birth weight. The clinical characteristics, umbilical cord blood parameters were measured, and placental microbiota were sequenced and further analysed. The clinical characteristics of infants and mothers and umbilical cord blood parameters were significantly different between macrosomias and controls. The relative abundance of microbiota sequences revealed that microbial structures of the placenta differed significantly between macrosomia and controls. Regression analysis showed a cluster of key operational taxonomic unit (OTUs), phyla and genera were significantly correlated with body length, ponderal index and placenta weight, body weight increase during pregnancy of mothers, and cord blood IGF-1 and leptin concentrations. In conclusion, our study for the first time explored the relationship between placental microbiota profile and fetal macrosomia. It is novel in showing that a distinct placental microbiota profile is present in fetal macrosomia, and is associated with clinical characteristics of mothers and newborns.
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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 | 0.001 |
| 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".