目的 分析妊娠中期血清25(OH)D₃水平对妊娠期糖尿病(gestational diabetes mellitus,GDM)的预测价值。方法 选取2019年7月—2020年3月在广州市妇女儿童医疗中心及广东省计划生育专科医院进行产前检查的孕中期妇女,根据孕妇的空腹血糖(FBG)水平和口服糖耐量试验(OGTT)结果分为GDM组(100例)和对照组(320例)。分别测定两组孕妇的年龄、孕前BMI、空腹血糖、服糖后l h血糖、服糖后2 h血糖、空腹胰岛素及25(OH)D₃等指标,进行统计分析与比较。结果 GDM组维生素D不足及缺乏的发病率高于对照组(P＜0.05)。年龄、空腹胰岛素在两组之间无统计学差异(P＞0.05);GDM组25(OH)D₃水平低于对照组(P＜0.05);GDM组空腹血糖、服糖后1 h、2 h血糖及孕前BMI均高于对照组(P＜0.05)。血清25(OH)D₃水平与空腹血糖、服糖后1 h、2 h血糖呈负相关(P＜0.05),而与年龄、BMI及空腹胰岛素无显著相关性(P＞0.05)。25(OH)D₃水平与妊娠期糖尿病发生风险呈负相关。结论 妊娠中期血清25(OH)D₃水平降低可能增加GDM的发生风险,联合检测妊娠中期血清25(OH)D₃水平有助于GDM的早期预测。

Objective To analyze the predictive value of serum 25(OH)D₃ level in the second trimester of pregnancy for gestational diabetes mellitus. Methods From July 2019 to March 2020, pregnant women who had prenatal examinations in Guangzhou Women and Children's Medical Center and Guangdong Family Planning Hospital were selected and divided into GDM group (100 cases) and control group (320 cases) according to FBG level and oral glucose tolerance test (OGTT) results.The age, pre-pregnancy BMI, fasting blood glucose, l h blood glucose after taking sugar, 2 h blood glucose after taking sugar, fasting insulin, 25(OH)D₃ and other indicators of the two groups of pregnant women were measured, respectively, for statistical analysis and comparison. Results The incidence of vitamin D deficiency and deficiency in GDM group was higher than that in control group (P<0.05).There was no significant difference in age and fasting insulin between the two groups (P>0.05).The level of 25(OH)D₃ in the GDM group was lower than that in the control group (P<0.05).Fasting blood glucose, blood glucose at 1 h and 2 h after taking sugar and BMI before pregnancy were all higher in the GDM group than in the control group (P<0.05).Serum 25(OH)D₃ level was negatively correlated with fasting blood glucose and blood glucose at 1 h and 2 h after taking sugar (P<0.05), but not significantly correlated with age, BMI and fasting insulin (P>0.05).The level of 25(OH)D₃ was negatively correlated with the risk of gestational diabetes. Conclusion Reduced serum 25(OH)D₃ levels in the second trimester may increase the risk of GDM, and combined detection of serum 25(OH)D₃ levels in the second trimester is helpful for early prediction of GDM.

目的 探讨两种不同机器学习算法在妊娠期糖尿病(gestational diabetes mellitus,GDM)风险预测中的应用。方法 选取2019年7月—2020年8月在广州市妇女儿童医疗中心及广东省计划生育专科医院进行产前检查的孕早期妇女520例,其中妊娠期糖尿病孕妇200例,随机抽取同期正常孕妇320例,收集孕妇的一般资料和孕早期(8～12周)的生化指标、血常规和凝血功能等检测资料。利用这些分析变量建立支持向量机(SVM)和Logistic回归(LR)预测模型。根据模型预测能力和模型实用性,如准确率、精确率、真阳性(TP)率、假阳性(FP)率、召回率、F测度、受试者工作特征曲线(ROC)进行效果评价。结果 两种预测模型的分类准确率总体为86%。SVM模型在真阳性(TP)率、假阳性(FP)率、召回率、F测度、受试者工作特征曲线(ROC)方面优于LR模型。结论 在分类与预测方面,支持向量机算法比Logistic回归模型更具有实用价值。

Objective To explore the application of two different machine learning algorithms in the risk prediction of gestational diabetes mellitus (GDM). Methods A total of 520 pregnant women with gestational diabetes mellitus were selected from Women and Children's Medical Center and Guangdong Family Planning Hospital from July 2019 to August 2020, including 200 cases of gestational diabetes mellitus, and 320 normal pregnant women in the same period. The general information of pregnant women and the detection data of biochemical indexes, blood routine test and coagulation function in early pregnancy (8～12 weeks) were collected. Support vector machine (SVM) and logistic regression (LR) prediction models were established by using these analysis variables. According to the predictive ability and practicability of the model, something like accuracy rate, precision ratio, true positive (TP) rate, false positive (FP) rate, recall rate, F-measure and receiver operating characteristic curve (ROC) were evaluated. Results The classification accuracy of the two models was 86%. SVM model is better than LR model in TPrate, FPrate, recall rate, F measure and ROC. Conclusion Support vector machine is more practical than logistic regression model in classification and prediction.

目的 通过对不同受孕能力精子外显子的分析,寻找并验证特异性外显子作为精子受孕能力的生物标记物。 方法 基于二代测序数据进行生物信息学分析,寻找特异性外显子并设计引物。各取8份高、低受孕能力精液标本,提取精子RNA反转录后进行real time q-PCR验证外显子的表达效率,筛选表达差异恒定的精子外显子作为生物标记物。各取10份高、低受孕能力精子标本,用筛选后的外显子引物进行real time q-PCR验证。 结果 生物信息学分析得到31个候选精子外显子,从31个候选外显子中筛选出9个表达差异恒定的精子外显子GAPDHS、HSF2BP、HSPA1L、ADAM21、SPEM1、WBP2NL、DDX20、TSGA10、PGK2;real time q-PCR验证结果显示,在高、低受孕能力精液标本中这9种精子外显子表达差异明显。 结论 初步确定,差异表达恒定的九种外显子可作为评估精子质量的生物标记物。

Objective To find and verify specific exons as biomarkers of sperm fertility by analyzing sperm exons with different fertility ability.Methods Based on the second generation sequencing data, bioinformatics analysis was conducted to find specific exons and design primers. We obtained 16 semen samples, 8 of high and the other 8 of low fertilizing ability, after the sperm RNAs were extracted and reverse-transcribed, real time q-PCR was performed to verify the expression efficiency of exons, and the sperm exons with constant expression difference were selected as biomarkers. 10 high and 10 lowfertility ability sperm samples were taken for real time q-PCR verification with screened exon primers. Results Thirty-one sperm exons were obtained by bioinformatics analysis, and 9 sperm exons with constant expression differences were selected from the 31 candidate exons, including GAPDHS, HSF2BP, HSPA1L, ADAM21, SPEM1, WBP2NL, DDX20, TSGA10 and PGK2. The results of real time q-PCR verification showed that the exons of these 9 sperm were significantly different in the semen samples with high and low fertility ability. Conclusion Nine exons with constant differential expression can be used as biomarkers to evaluate sperm quality.