0.05).Conclusion: Lamiophlomis rotata capsule showed the similar curative effect and safety as Radix Notoginseng capsule did on dysmenorrhea.

OBJECTIVETo identify the biomarkers of renal cell cancer (RCC) through urine metabolic analysis.

METHODSUrine samples of 27 RCC patients, 26 patients with other urinary cancers and 26 healthy volunteers were examined with gas chromatography-mass spectrometry (GC-MS). SIMCA-P+12.0.1.0 software was used for principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) to screen for the differential metabolites.

RESULTSPCA (R2X=0.846, Q2=0.575) and OPLS-DA (R2X=0.736, R2Y=0.974, Q2Y=0.897) model were established for the RCC patients and control subjects. Fourteen metabolites were selected as the characteristic metabolites, including pentanoic acid, malonic acid, glutaric acid, adipic acid, amino quinoline, quinoline, indole acetic acid, and tryptophan, whose levels in the urine were significantly higher in the RCC patients than in the normal subjects (P<0.01); the RCC patients showed significantly higher urine contents of pentanoic acid, phenylalanine, and 6-methoxy-nitro quinoline than those with other urinary tumors (P<0.01).

CONCLUSIONThe urine metabolites identified based on GC-MS analysis can distinguish RCC patients from patients with other urinary cancers and healthy subjects, suggesting their potential as diagnostic markers for RCC.

Biomarkers ; urine ; Carcinoma, Renal Cell ; urine ; Discriminant Analysis ; Gas Chromatography-Mass Spectrometry ; Humans ; Least-Squares Analysis ; Metabolome ; Metabolomics ; Principal Component Analysis ; Software

Objective To analyze the echocardiographic findings , associated anomalies and chromosomal characteristics in fetuses with pulmonary atresia with ventricular septal defect ( PA/VSD ) . Methods T he echocardiographic data and follow‐up materials were retrospectively reviewed in 30 256 fetuses from December 2012 to M arch 2018 in the consultation center of fetal heart disease in maternal‐fetal medicine in Anzhen hospital . Of all the fetuses ,59 cases ( 0 .19% ) had PA/VSD . T he echocardiographic findings ,associated anomalies and chromosomal characteristics were retrospectively analyzed in all the 59 fetuses with PA/VSD . Based on w hether the presence of the native pulmonary arteries and the major aortopulmonary collateral arteries ( M APCAs) or not ,the PA‐VSD was classified into type A ,type B ,and type C . Results A large ventricular defect was demonstrated in five‐chamber view with 61 .7% of the mean ratio of the aortic overriding . O ther fetal echocardiographic features of all the 59 fetuses with PA/VSD included :the right aortic arch ( n ＝19 ) ,reversal flow in the ductus arteriosus ( n ＝40 ) ,M APCAs ( n ＝24) . T he classification of the PA/VSD included :type A ( n ＝35) ,type B ( n ＝5) and type C ( n ＝19) . Associated anomalies :persistent left superior vena cava ( n ＝ 13 ) ,anomalous pulmonary vein connection ( n＝5 ) ,complete atrioventricular septal defect ( n ＝ 5 ) ; single umbilical artery ( n ＝ 3 ) ,right atrial isomerism ( n ＝3) . Of all the 30 cases performed chromosomal test ,3 cases had aneuploidy and 7 cases had microdeletion of chromosome . Conclusions The fetal echocardiographic findings of the PA/VSD are characteristic . For prenatal diagnosis of PA/VSD ,the type of PA/VSD should be defined and chromosomal test should be performed ,w hich can be helpful for prenatal consulting .

OBJECTIVE: To summarize the clinical features and spectrum of genetic variants in 12 patients with Loeys-Dietz syndrome (LDS), and to explore the correlation between the type of genetic variants and clinical phenotypes. METHODS: Twelve patients suspected for LDS at Beijing Anzhen Hospital Affiliated to Capital Medical University from January 2015 to January 2022 were selected as the study subjects. Clinical data of the patients were collected. Genomic DNA was extracted from peripheral blood samples and subjected to genetic testing. Pathogenicity of candidate variants was analyzed. RESULTS: The clinical phenotypes of the 12 patients have mainly included cardiovascular, musculoskeletal, craniofacial, skin, ocular and other systemic signs. Four patients (patients 5-1, 5-2, 6, 7) have carried heterozygous missense variants of the TGFBR1 gene, 5 patients (patients 1-1, 1-2, 2, 3, 4) have carried heterozygous variants of the TGFBR2 gene, and 2 patients (patients 8-1, 8-2) had carried heterozygous frameshift variants of the TGFB3 gene. One patient (patient 9) had carried a heterozygous missense variant of the SMAD3 gene. Among these, TGFBR1 c.603T>G (p.1201M) and TGFB3 c.536delA (p.H179FS35) had not been reported previously. CONCLUSION Variants of the TGFBR1, TGFBR2, SMAD3, TGFB2, TGFB3 and SMAD2 genes are mainly associated with LDS. The severity of the disease phenotype caused by the same variant may vary, whilst the clinical phenotype caused by different variant sites may be specific.
Humans ; Loeys-Dietz Syndrome/genetics* ; Receptor, Transforming Growth Factor-beta Type I/genetics* ; Receptor, Transforming Growth Factor-beta Type II/genetics* ; Transforming Growth Factor beta3 ; Face

Objective:To summarize the etiological mechanism, echocardiographic and clinical features of fetal cardiomyopathies (FCMs).Methods:According to the data of echocardiography in Maternal-Fetal Medicine Center in Fetal Heart Disease of Beijing Anzhen Hospital during 2015 January to 2020 December, 70 cases with FCMs were retrospectively reviewed, and the clinical, ultrasonic, pathological and clinical outcome data were collected. Whole exome sequencing and whole genome sequencing were used to identify the genetic changes.Results:Primary FCMs were diagnosed in 55 cases (78.6%, 55/70), including 39 fetuses with non-compaction of the ventricular myocardium (NVM), 10 with dilated cardiomyopathy (DCM), 5 with hypertrophic cardiomyopathy (HCM), and 1 with restricted cardiomyopathy (RCM). Secondary FCMs were diagnosed in 15 cases (21.4%, 15/70), including 7 fetuses with maternal anti-Ro/La antibodies (presenting with DCM), 4 with twin-twin transfusion syndrome (2 with DCM and 2 with HCM), 2 with fetal anemia (presenting with DCM), 1 with maternal diabetes (presenting with HCM) and 1 with chorioangioma of the placenta (presenting with DCM). In all cases, 9 cases were born, 3 cases died in perinatal period, and 58 pregnancies were terminated due to ineffective treatment or the decisions of pregnant women. Thirty cases with primary FCMs were performed with genetic tests, and 13 of them were identified with positive genetic changes related to FCMs, including 12 cases with NVM and 1 with HCM.Conclusions:Primary FCMs are more common than secondary FCMs in fetal period. The genetic disorders have a high proportion in fetal NVM. Fetal DCM and HCM have a large spectrum of intrinsic and extrinsic causes.

Objective:To evaluate artificial intelligence constructed by deep convolutional neural network (DCNN) for the site identification in upper gastrointestinal endoscopy.Methods:A total of 21 310 images of esophagogastroduodenoscopy from the Cancer Hospital of Chinese Academy of Medical Sciences from January 2019 to June 2021 were collected. A total of 19 191 images of them were used to construct site identification model, and the remaining 2 119 images were used for verification. The performance differences of two models constructed by DCCN in the identification of 30 sites of the upper digestive tract were compared. One model was the traditional ResNetV2 model constructed by Inception-ResNetV2 (ResNetV2), the other was a hybrid neural network RESENet model constructed by Inception-ResNetV2 and Squeeze-Excitation Networks (RESENet). The main indices were the accuracy, the sensitivity, the specificity, positive predictive value (PPV) and negative predictive value (NPV).Results:The accuracy, the sensitivity, the specificity, PPV and NPV of ResNetV2 model in the identification of 30 sites of the upper digestive tract were 94.62%-99.10%, 30.61%-100.00%, 96.07%-99.56%, 42.26%-86.44% and 97.13%-99.75%, respectively. The corresponding values of RESENet model were 98.08%-99.95%, 92.86%-100.00%, 98.51%-100.00%, 74.51%-100.00% and 98.85%-100.00%, respectively. The mean accuracy, mean sensitivity, mean specificity, mean PPV and mean NPV of ResNetV2 model were 97.60%, 75.58%, 98.75%, 63.44% and 98.76%, respectively. The corresponding values of RESENet model were 99.34% ( P<0.001), 99.57% ( P<0.001), 99.66% ( P<0.001), 90.20% ( P<0.001) and 99.66% ( P<0.001). Conclusion:Compared with the traditional ResNetV2 model, the artificial intelligence-assisted site identification model constructed by RESENNet, a hybrid neural network, shows significantly improved performance. This model can be used to monitor the integrity of the esophagogastroduodenoscopic procedures and is expected to become an important assistant for standardizing and improving quality of the procedures, as well as an significant tool for quality control of esophagogastroduodenoscopy.