Objective To investigate chromosome abnormality rate and related factors of spontaneous abortion in early pregnancy. Methods A total of 831 tissue samples of spontaneous abortion in early pregnancy were collected from June 2015 to August 2018 in the First Affiliated Hospital of Nanjing Medical University. Chromosomal copy number was analyzed by next generation sequencing (NGS). The relationships between chromosome abnormality and maternal age, in vitro fertilization?embryo transfer (IVF?ET) pregnancy, number of previous spontaneous abortions, history of live birth were analyzed by statistical methods. Results Among 831 tissue samples of spontaneous abortion in early pregnancy, 461 (55.5%, 461/831) were found to have chromosome abnormalities. Maternal age (OR=1.107, 95%CI: 1.070-1.145) and history of live birth ( OR=1.909, 95%CI : 1.182-3.083) were the positive correlative factors of chromosome abnormality. Times of previous spontaneous abortion (OR=0.807, 95%CI: 0.702-0.928) and IVF?ET pregnancy ( OR=0.554, 95%CI : 0.404-0.760) were the negative correlative factors of chromosome abnormality. Conclusions Chromosome abnormality is an important cause of spontaneous abortion in early pregnancy. The rate of chromosome abnormality increases with the increase of maternal age and the history of live birth, and decreases with the increase of number of previous spontaneous abortion and IVF?ET pregnancy.

Objective: To investigate chromosome abnormality rate and related factors of spontaneous abortion in early pregnancy. Methods: A total of 831 tissue samples of spontaneous abortion in early pregnancy were collected from June 2015 to August 2018 in the First Affiliated Hospital of Nanjing Medical University. Chromosomal copy number was analyzed by next generation sequencing (NGS). The relationships between chromosome abnormality and maternal age, in vitro fertilization-embryo transfer (IVF-ET) pregnancy, number of previous spontaneous abortions, history of live birth were analyzed by statistical methods. Results: Among 831 tissue samples of spontaneous abortion in early pregnancy, 461 (55.5%, 461/831) were found to have chromosome abnormalities. Maternal age (OR=1.107, 95%CI: 1.070- 1.145) and history of live birth (OR=1.909, 95%CI: 1.182-3.083) were the positive correlative factors of chromosome abnormality. Times of previous spontaneous abortion (OR=0.807, 95%CI: 0.702-0.928) and IVF-ET pregnancy (OR=0.554, 95%CI: 0.404-0.760) were the negative correlative factors of chromosome abnormality. Conclusions Chromosome abnormality is an important cause of spontaneous abortion in early pregnancy. The rate of chromosome abnormality increases with the increase of maternal age and the history of live birth, and decreases with the increase of number of previous spontaneous abortion and IVF-ET pregnancy.

Objective:To construct a machine-learning model for predicting the progression of pancreatic cystic lesions (PCLs) based on clinical and CT features, and to evaluate its predictive performance in internal/external testing cohorts.Methods:Baseline clinical and radiological data of 200 PCLs in 177 patients undergoing abdominal thin slice enhanced CT examination at Peking Union Medical College Hospital from July 2014 to December 2022 were retrospectively collected. PCLs were divided into progressive and non-progressive groups according to whether the signs indicated for surgery by the guidelines of the European study group on PCLs were present during three-year follow-up. 200 PCLs were randomly divided into training (150 PCLs) and internal testing cohorts (50 PCLs) at the ratio of 1∶3. 15 PCLs in 14 patients at Jinling Affiliated Hospital of Medical School of Nanjing University from October 2011 to May 2020 were enrolled as external testing cohort. The clinical and CT radiological features were recorded. Multiple feature selection methods and machine-learning models were implemented and combined to identify the optimal machine-learning model based on the 10-fold cross-validation method. Receiver operating characteristics (ROC) curve was drawn and area under curve (AUC) was calculated. The model with the highest AUC was determined as the optimal model. The optimal model's predictive performance was evaluated on testing cohort by calculating AUC, sensitivity, specificity and accuracy. Permutation importance was used to assess the importance of optimal model features. Calibration curves of the optimal model were established to evaluate the model's clinical applicability by Hosmer-Lemeshow test.Results:In training and internal testing cohorts, the progressive and non-progressive groups were significantly different on history of pancreatitis, lesions size, main pancreatic duct diameter and dilation, thick cyst wall, presence of septation and thick septation (all P value <0.05) In internal testing cohort, the two groups were significantly different on gender, lesion calcification and pancreatic atrophy (all P value <0.05). In external testing cohort, the two groups were significantly different on lesions size and pancreatic duct dilation (both P<0.05). The support vector machine (SVM) model based on five features selected by F test (lesion size, thick cyst wall, history of pancreatitis, main pancreatic duct diameter and dilation) achieved the highest AUC of 0.899 during cross-validation. SVM model for predicting the progression of PCLs demonstrated an AUC of 0.909, sensitivity of 82.4%, specificity of 72.7%, and accuracy of 76.0% in the internal testing cohort, and 0.944, 100%, 77.8%, and 86.7% in the external testing cohort. Calibration curved showed that the predicted probability by the model was comparable to the real progression of PCLs. Hosmer-Lemeshow goodness-of-fit test affirmed the model's consistency with actual PCLs progression in testing cohorts. Conclusions:The SVM model based on clinical and CT features can help doctors predict the PCLs progression within three-year follow-up, thus achieving efficient patient management and rational allocation of medical resource.

OBJECTIVE: To explore the genetic etiology of recurrent hydatidiform mole (RHM) and provide accurate guidance for reproduction. METHODS: Peripheral venous blood samples of the probands with RHM and members from 5 unrelated pedigrees were collected. Genomic DNA was extracted by using routine method, and whole exome sequencing was carried out to detect variants of RHM-associated genes including NLRP7 and KHDC3L. Sanger sequencing and real-time quantitative PCR (RT-qPCR) were used to validate the candidate variants and delineate their parental origin. RESULTS: Homozygous or compound heterozygous variants of the NLRP7 gene were identified in four patients from three pedigrees, which included a homozygous deletion of exon 1 to 4 of NLRP7 in patient P1 and her elder sister, compound heterozygous variants of NLRP7 c.939delG (p.Q314Sfs*6) pat and c.1533delG (p.N512Tfs*4) mat in patient P2, and compound heterozygous variants of NLRP7 c.2389_2390delTC (p.A798Qfs*6) pat and c.2165A>G (p.D722G) mat in patient P4. All variants were interpreted as pathogenic or likely pathogenic according to the American College of Medical and Genomics (ACMG) guidelines. Among these, NLRP7 exons 1 to 4 deletion, c.939delG (p.Q314Sfs*6), c.1533delG (p.N512Tfs*4) and c.2389_2390delTC (p.A798Qfs*6) were unreported previously. CONCLUSION Variants of the NLRP7 gene probably underlay autosomal recessive RHM in the three pedigrees, and definitive molecular diagnosis is beneficial for accurate genetic counseling. Above finding has also enriched the spectrum of the NLRP7 variants underlying RHM.
Adaptor Proteins, Signal Transducing/genetics* ; Aged ; China ; Female ; Homozygote ; Humans ; Hydatidiform Mole/pathology* ; Mutation ; Pedigree ; Pregnancy ; Sequence Deletion

Autoimmune hepatitis (AIH) is a severe globally distributed liver disease that could occur at any age. Human menstrual blood-derived stem cells (MenSCs) have shown therapeutic effect in acute lung injury and liver failure. However, their role in the curative effect of AIH remains unclear. Here, a classic AIH mouse model was constructed through intravenous injection with concanavalin A (Con A). MenSCs were intravenously injected while Con A injection in the treatment groups. The results showed that the mortality by Con A injection was significantly decreased by MenSCs treatment and liver function tests and histological analysis were also ameliorated. The results of phosphoproteomic analysis and RNA-seq revealed that MenSCs improved AIH, mainly by apoptosis and c-Jun N-terminal kinase/mitogen-activated protein signaling pathways. Apoptosis analysis demonstrated that the protein expression of cleaved caspase 3 was increased by Con A injection and reduced by MenSCs transplantation, consistent with the TUNEL staining results. An AML12 co-culture system and JNK inhibitor (SP600125) were used to verify the JNK/MAPK and apoptosis signaling pathways. These findings suggested that MenSCs could be a promising strategy for AIH.
Mice ; Animals ; Humans ; Hepatitis, Autoimmune/pathology* ; Signal Transduction ; Disease Models, Animal ; Stem Cells