1.Association between preconception oral microbiome and fetal overgrowth
Qiuli XIAO ; Xushan CAI ; Lifeng ZHANG ; Fengyun YANG ; Xingying LI ; An CHEN ; Huajun ZHENG ; Hong JIANG
Chinese Journal of Perinatal Medicine 2024;27(6):457-467
Objective:To analyze the association between the pre-pregnancy oral microbiota of women and fetal overgrowth, and the possible mechanisms involved.Methods:A nested case-control study design based on a pre-pregnancy cohort was used to select 51 mothers who delivered macrosomia and/or large-for-gestational-age (LGA) infants from the population recruited at the Maternal and Child Health Care Hospital of Jiading District in Shanghai from October 2016 to December 2021 as the case group. A control group was formed by selecting 204 mothers who delivered infants with normal birth weight and appropriate for gestational age during the same period, in a 1:4 ratio. The LGA subgroup consisted of 48 mothers who delivered LGA infants from the total population, and a corresponding control group of 192 was randomly selected from the remaining mothers who delivered non-LGA infants in a 1∶4 ratio for the LGA subgroup analysis. The 16S rRNA gene sequencing technique was utilized to detect pre-pregnancy saliva samples to compare the characteristics of the oral microbiota, differential microorganisms, and differential functional pathways between groups. Nonparametric Wilcoxon rank-sum tests, two independent samples t-tests, or Chi-square (or Fisher's exact) tests were used for statistical analysis. Factor analysis was conducted on the pre-pregnancy diet data of women, and the primary dietary pattern of each study subject was identified based on the highest score of the dietary pattern factors. For microbiota count data, α and β diversity indices were calculated using R and QIIME2 software, and the corresponding microbiota functional count data were acquired through PICRUSt2. Results:(1) General data: There was no significant difference in the time interval from pre-pregnancy sampling to pregnancy and from sampling to delivery between the two groups. In the case group, there were three cases of macrosomia and 48 cases (94.1%) of LGA. The corresponding control group for the LGA subgroup consisted of 192 cases. There were no significant differences in dietary patterns between the case group and the control group. (2) α diversity analysis: The species richness index of the case group was lower than that of the control group [(367.27±84.57) vs. (408.71±93.08), multivariate analysis, P=0.009], while no significant differences were found between the two groups in the Shannon and Simpson indices; the species richness index of the LGA subgroup was also lower than that of the corresponding control group [(371.04±83.92) vs. (408.04±94.21), multivariate analysis, P=0.033], with no significant differences in the Shannon and Simpson indices. (3) β diversity analysis: There was a statistically significant difference in the unweighted UniFrac distance of the oral microbiota between the case group and the control group ( R2=0.006, F=1.479, P=0.048). No significant differences were found in the β diversity indices of the oral microbiota between the LGA subgroup and the corresponding control group. (4) Differential microbiota analysis: There were 14 differential microbiotas from phylum to genus between the case group and the control group. At the genus level, members of the G1 genus of the Streptococcaceae were enriched in the case group, while the Lautropia, Dialister, Leptotrichia, and Rothia were enriched in the control group. In the LGA subgroup and its corresponding control group, there were 14 differential microbiota from phylum to genus; at the genus level, Leptotrichia, Rothia, G6 genus of the Saccharibacteria, and Selenomonas were enriched in the control group (all LDA value>2, and all P<0.05). (5) Differential functional analysis: In the case group, metabolic pathways such as nicotinate degradation [log 2 fold change ( FC)=3.510, q=0.005], de novo synthesis of pyrimidine nucleotides (log 2FC=0.078, q=0.005), and L-tyrosine degradation pathway (log 2FC=0.710, q=0.034) were enriched in the oral microbiota of women. In the LGA subgroup, compared to the corresponding control group, metabolic pathways related to nicotinate degradation were enriched in the oral microbiota (log 2FC=3.660, q=0.012). Conclusions:There are differences in the structure of the pre-pregnancy oral microbiota of mothers with overgrown fetuses compared to those with normally grown fetuses, and mothers of normally grown fetuses show higher diversity in their pre-pregnancy oral microbiota. The enrichment of certain pathogenic bacteria and the reduction of symbiotic bacteria in the pre-pregnancy oral microbiota are associated with fetal overgrowth, and this association may be mediated by functional pathways such as nicotinate degradation.
2.Pediatric reference intervals for plasma and whole blood procalcitonin of in China: a multicenter research
Zhan MA ; Fangzhen WU ; Jiangtao MA ; Yunsheng CHEN ; Guixia LI ; Jinbo LIU ; Hongbing CHEN ; Huiming YE ; Xingyan BIAN ; Dapeng CHEN ; Jiangwei KE ; Haiou YANG ; Lijuan MA ; Qiuhui PAN ; Hongquan LUO ; Xushan CAI ; Yun XIE ; Wenqi SONG ; Lei ZHANG ; Hong ZHANG
Chinese Journal of Laboratory Medicine 2022;45(6):581-588
Objective:To establish the biology reference interval (RI) of peripheral blood procalcitonin (PCT) for children between 3 days and 6 years old in China.Methods:Totally 3 353 reference individuals with apparent health or no specific diseases were recruited in 18 hospitals throughout the country during October 2020 to May 2021. Reference individuals were divided into four groups: 3-28 days, 29 days - 1 year, 1-3 years and 4-6 years. Vein blood or capillary blood were collected by percutaneous puncture from every reference individual. The PCT level in serum and the capillary whole blood were assayed by Roche Cobas e601 and Norman NRM411-S7 immunoanalyzer. Outliers were deleted and 95th percentiles of every group were provided as RIs. Man-Whitney U test or Kruskal-Wallis test were used performed to assess the difference among different gender, age or method groups. Results:The difference of PCT distribution between male and female is not statistically significant, but the difference between serum and capillary whole blood is statistically significant. The differences between age groups are significant too. For Roche e601, serum PCT RI of 3-28 days group is <0.23 μg/L, 29 days - 6 years are <0.11 μg/L. For NRM411, Serum PCT RI of 3-28 days group is <0.21 μg/L, 29 days - 1 year: <0.09 μg/L, 1 - 6 years: <0.10 μg/L. For whole blood PCT, RI of 3-28 days group is <0.26 μg/L, 29 days - 6 years is <0.15 μg/L.Conclusions:Serum and capillary whole blood PCT have different RIs, however, capillary whole blood PCT testing is valuable in pediatric application. Children in 3-28 days show higher PCT levels than other age group. To establish the RIs and understand the differences among different groups are essential for the interpretation and clinical application of peripheral blood PCT testing results.
3.Role of lipophagy in the regulation of lipid metabolism and the molecular mechanism.
Linna SHI ; Ke WANG ; Yudi DENG ; Yingna WANG ; Shuangling ZHU ; Xushan YANG ; Wenzhen LIAO
Journal of Southern Medical University 2019;39(7):867-874
Recent studies have discovered a selective autophagy-lipophagy, which can selectively identify and degrade lipids and plays an important role in regulating cellular lipid metabolism and maintaining intracellular lipid homeostasis. The process of lipophagy can be directly or indirectly regulated by genes, enzymes, transcriptional regulators and other factors. This review examines the role of lipophagy in reducing liver lipid content, regulating pancreatic lipid metabolism, and regulating adipose tissue differentiation, and summarizes the findings of the molecules (Rab GTPase, enzymes, ion channels, transcription factors, small molecular substances) involved in the regulation of lipophagy, which points to new directions for the treatment of diseases caused by lipid accumulation.
Adipose Tissue
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Autophagy
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Homeostasis
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Lipid Metabolism
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Liver