α-Galactosidase A (α-Gal A ) activities in plasma and peripheral blood granulocytes of 100healthy subjects and one patient with Fabry disease was determined by means of fluorogenic substrate.The results showed that the enzymatic activities of peripheral blood granulocytes and plasma in 100 subjects were (51.97 ± 15.24)and(148.08±26.30) nmol · h-1 · ml-1 respectively.The α-Gal A activities in plasma and granulocytes were positively correlated( r=0.533,P＜0.01 ).The enzymatic activities in peripheral blood granulocytes and plasma of the patients with Fabry disease were 1.05 and 10.06 nmol · h-1 · ml-1 respectively,both much lower than those of 100healthy subjects.These results suggest that α-Gal A activity in plasma and peripheral blood granulocytes can be used for diagnosis and screening of Fabry disease.

Objective To evaluate the role of real-time three-dimensional transesophageal echocardiography(RT3D-TEE) in non-valvular atrial fibrillation with left atrial appendage(LAA) stunning after catheter ablation.Methods Clinical and echocardiographic variables were analyzed by univariate regression in order to investigate the relationship between the group of LAA stunning and others in 28 patients after catheter ablation.Results Univariate analysis revealed difference in persisting time of atrial fibrillation[(16.4 ± 11.6)weeks vs (21.3 ± 18.6) weeks,P ＜0.05],left atrial diameter[(43.4 ± 8.3) mm vs (47.6 ± 5.9) mm,P ＜0.05 ],left atrial emptying fraction (0.38 ± 0.04 vs 0.30 ± 0.09,P ＜0.05).LAA emptying fraction based on three-dimensional volume measurements had significant difference (0.20 ± 0.03 vs 0.12 ± 0.02,P ＜ 0.001) between the group of LAA stunning and other cases.Conclusions LAA ejection fraction calculation by RT3D-TEE is feasible and more accurate than by clinical and other echocardiographic in LAA stunning after ablaton of atrial fibrillation.

Objective To compare proprotein convertase subtilisin/kexin type 9 (PCSK9) levels between premenopausal and postmenopausal women,and to investigate the relationship between serum PCSK9 and metabolic factors.Methods Totally 515 women were enrolled from the study on diabetes of prediction,prevention,and intervention in Nanjing in 2009.Survey,physical examinations,and determination of related metabolic indexes were performed.Serum PCSK9 level was measured by sandwich ELISA.Results Serum PCSK9 level was positively correlated with low density lipoprotein-cholesterol (LDL-C),total cholesterol (TC),triglyceride,fasting plasma glucose,body mass index,waist-hip ratio,and age in women (all P＜0.01).PCSK9 level was significantly lower in premenopausal women than that in postmenopausal women [(58.18 ± 25.44 vs 80.91 ± 33.74) ng/ml,P ＜0.01].Conclusion Higher level of PCSK9 exists in postmenopausal women compared with premenopausal women.The level of PCSK9 is closely correlated with age,TC,and LDL-C.

Algorithms ; Case-Control Studies ; Genome-Wide Association Study ; Humans ; Internet ; Phenotype ; Polymorphism, Single Nucleotide ; genetics ; Schizophrenia ; genetics ; Signal Transduction ; Software ; User-Computer Interface

The large amount of repeats, especially high copy repeats, in the genomes of higher animals and plants makes whole genome assembly (WGA) quite difficult. In order to solve this problem, we tried to identify repeats and mask them prior to assembly even at the stage of genome survey. It is known that repeats of different copy number have different probabilities of appearance in shotgun data, so based on this principle, we constructed a statistical model and inferred criteria for mathematically defined repeats (MDRs) at different shotgun coverages. According to these criteria, we developed software MDRmasker to identify and mask MDRs in shotgun data. With repeats masked prior to assembly, the speed of assembly was increased with lower error probability. In addition, clone-insert size affect the accuracy of repeat assembly and scaffold construction, we also designed length distribution of clone-inserts using our model. In our simulated genomes of human and rice, the length distribution of repeats is different, so their optimal length distributions of clone-inserts were not the same. Thus with optimal length distribution of clone-inserts, a given genome could be assembled better at lower coverage.
Animals ; Cloning, Molecular ; Genome ; Genome, Human ; Genomics ; methods ; Humans ; Models, Genetic ; Models, Statistical ; Models, Theoretical ; Oryza ; genetics ; Sequence Analysis, DNA

Objective To explore the predictive efficacy of three machine learning algorithms for carotid plaque stability in patients with cerebral infarction.Methods The clinical data of 500 pa-tients with cerebral infarction were retrospectively analyzed.Univariate analysis and multivariate anal-ysis were used to determine the predictive factors entering the model.The prediction model of carotid plaque stability in patients with cerebral infarction was constructed based on nomogram,decision tree and random forest respectively.The enrolled patients were randomly divided into training set and test set according to the ratio of 7∶3.Sensitivity,specificity,accuracy,recall,accuracy and area under the curve(AUC)were used to compare the application efficiency of the model.Results The AUC of the nomogram model for evaluating the stability of carotid plaque in patients with cerebral infarction in the training set was 0.910(95％CI,0.950 to 0.983),the sensitivity was 0.910,the specificity was 0.917,the accuracy was 0.886,the recall rate was 0.910,and the accuracy rate was 0.914.The AUC of the decision tree model for evaluating the stability of carotid plaque in patients with cerebral infarction in the training set was 0.932(95％CI,0.903 to 0.961),the sensitivity was 0.903,the specificity was 0.922,the accuracy was 0.891,the recall rate was 0.903,and the accuracy rate was 0.914.The AUC of the random forest model for evaluating the stability of carotid plaque in patients with cerebral infarction in the training set was 0.984(95％CI,0.970 to 0.998),the sensitivity was 0.972,the specificity was 0.995,the accuracy was 0.993,the recall rate was 0.972,and the ac-curacy was 0.986.Conclusion The model based on the random forest algorithm has a better pre-diction effect and stability in evaluating the stability of carotid plaque in patients with cerebral infarc-tion,and its prediction efficiency is better than that of the Nomogram and decision tree.

Objective To explore the predictive efficacy of three machine learning algorithms for carotid plaque stability in patients with cerebral infarction.Methods The clinical data of 500 pa-tients with cerebral infarction were retrospectively analyzed.Univariate analysis and multivariate anal-ysis were used to determine the predictive factors entering the model.The prediction model of carotid plaque stability in patients with cerebral infarction was constructed based on nomogram,decision tree and random forest respectively.The enrolled patients were randomly divided into training set and test set according to the ratio of 7∶3.Sensitivity,specificity,accuracy,recall,accuracy and area under the curve(AUC)were used to compare the application efficiency of the model.Results The AUC of the nomogram model for evaluating the stability of carotid plaque in patients with cerebral infarction in the training set was 0.910(95％CI,0.950 to 0.983),the sensitivity was 0.910,the specificity was 0.917,the accuracy was 0.886,the recall rate was 0.910,and the accuracy rate was 0.914.The AUC of the decision tree model for evaluating the stability of carotid plaque in patients with cerebral infarction in the training set was 0.932(95％CI,0.903 to 0.961),the sensitivity was 0.903,the specificity was 0.922,the accuracy was 0.891,the recall rate was 0.903,and the accuracy rate was 0.914.The AUC of the random forest model for evaluating the stability of carotid plaque in patients with cerebral infarction in the training set was 0.984(95％CI,0.970 to 0.998),the sensitivity was 0.972,the specificity was 0.995,the accuracy was 0.993,the recall rate was 0.972,and the ac-curacy was 0.986.Conclusion The model based on the random forest algorithm has a better pre-diction effect and stability in evaluating the stability of carotid plaque in patients with cerebral infarc-tion,and its prediction efficiency is better than that of the Nomogram and decision tree.

Objective:To evaluate the safety and effectiveness of Kangduo endoscopic surgical robot system for partial nephrectomy.Methods:Consecutive patients with stage T 1 renal tumor meeting the inclusion criteria from the Department of Urology, Peking University First Hospital from December 2020 to February 2021 were prospectively enrolled. All patients underwent partial nephrectomy with the Kangduo endoscopic surgical robot system after signing the informed consent. Clinical data including preoperative, perioperative and postoperative pathology and follow-up were collected. Results:Among the 26 patients, there were 16 males and 10 females, with a median age of 53(33-74) years, and a median body mass index of 25.99(20.90-32.91) kg/m 2. There were 12 cases of left kidney tumor and 14 cases of right kidney tumor. The median tumor diameter was 2.2(1.0-3.5) cm. The median time of warm ischemia was 17.7(7.1-29.2) minutes, and all of them were less than 30 minutes. The median docking time was 4.7(2.3-9.9) minutes, and the median time of robotic arm operation was 65.0 (37.0-155.0) minutes. The median National Aeronautics and Space Administration Task Load Index (NASA-TLX) score was 5.3 (2.0-28.0), and no instrument-related adverse events occurred intraoperatively. The median postoperative hospital stay was 4 (4-5) days. All tumor margins were negative on pathologic reports. No Clavien Ⅱ stage operative complications occurred in all patients during perioperative period and 1 month after the surgery. Conclusions:The partial nephrectomy using the kangduo endoscopic surgical robot system were completed successfully, and no instrument-related adverse events and complications occurred, showing that this surgical system used for partial nephrectomy is safe and effective.

Thyroid cancer is the most common malignant tumor of the endocrine system, and its incidence is increasing year by year showing younger trend. The pathological types of thyroid cancer are papillary carcinoma, follicular carcinoma, medullary carcinoma and undifferentiated carcinoma. Medullary thyroid carcinoma (MTC) and papillary thyroid carcinoma (PTC) are the two common types of thyroid cancer. Since MTC and PTC have different biological origins, invasiveness and prognosis. Therefore, the occurrence of both medullary carcinoma and papillary carcinoma is very rare and rarely reported in China and abroad and the treatment is challenging. In this paper, we review the pathogenesis, ancillary tests, diagnosis and treatment of this disease, with the aim of providing reference for clinical treatment of patients with medullary thyroid carcinoma complicated by papillary carcinoma.

Bipolar Disorder ; genetics ; Genome-Wide Association Study ; Genomics ; methods ; Humans