Objective To evaluate the association between the single-nucleotide polymorphism (SNP) of the 5-59A/G (rs2241027) of Htra2 gene and Parkinson's disease in Han population of the western GuangDong province. MethodsThe restriction fragment length polymorphism (PCR-RFLP) was used to determine the 5-59A/G polymorphism in the intron region of Htra2 gene in the case group (n=56) and healthy control group (n=109). ResultsA allele frequency of 5-59 A/G in cases (46.4%) was trended to more than that in controls (36.7%) (P=0.073), as well as the AA genotyping frequency (21.4% vs 11.0%, P=0.072). For the male, the frequency of AA genotype was significantly more in cases (25.7%) than that in controls (10.3%） (P=0.041), and the frequency of A allele was trended to more in cases (48.6%) than in controls (34.6%) (P=0.051). ConclusionA allele and AA genotype of the 5-59A/G (rs2241027) of Htra2 gene may increase the risk of suffering from Parkinson's disease, especially for males.

Objective:To establish a prediction model using the random forest (RF) and support vector machine (SVM) algorithms to achieve the numerical and classification predictions of the gamma passing rate (GPR) for volumetric arc intensity modulation (VMAT) validation.Methods:A total of 258 patients who received VMAT radiotherapy in the 1 st Affiliated Hospital of Wenzhou Medical University from April 2019 to August 2020 were retrospectively selected for patient-specific QA measurements, including 38 patients who received VMAT radiotherapy for head and neck, and 220 patients who received VMAT radiotherapy for chest and abdomen. Thirteen complexity parameters were extracted from the patient′s VMAT plans and the GPRs for VMAT validation under the analysis criteria of 3%/3 mm and 2%/2 mm were collected. The patients were randomly divided into a training cohort (70%) and a validation cohort (30%) , and the complexity parameters for the numerical and classification predictions were screened using the RF and minimum redundancy maximum correlation (mRMR) method, respectively. Complexity models and mixed models were established using PTV volume, subfield width, and smoothness factors based on the RF and SVM algorithms individually. The prediction performance of the established models was analyzed and compared. Results:For the validation cohort, the GPR numerical prediction errors of the complexity models based on RF and SVM under the two analysis criteria are as follows. The root-mean-square errors (RMSEs) under the analysis criterion of 3%/3 mm were 1.788% and 1.753%, respectively; the RMSEs under the analysis criterion of 2%/2 mm were 5.895% and 5.444%, respectively; the mean absolute errors (MAEs) under the analysis criterion of 3%/3 mm were 1.415% and 1.334%, respectively, and the MAEs under the analysis criteria of 2%/2 mm were 4.644% and 4.255%, respectively. For the validation cohort, the GPR numerical prediction errors of the mixed models based on RF and SVM under the two analysis criteria were as follows. The RMSEs under the analysis criterion of 3%/3 mm were 1.760% and 1.815%, respectively; the RMSEs under the analysis criterion of 2%/2 mm were 5.693% and 5.590%, respectively; the MAEs under the analysis criterion of 3%/3 mm were 1.386% and 1.319%, respectively, and the MAEs under the analysis criteria of 2%/2 mm were 4.523% and 4.310, respectively. For the validation cohort, the AUC result of the GPR classification prediction of the complexity models based on RF and SVM were 0.790 and 0.793, respectively under the analysis criterion of 3%/3 mm and were 0.763 and 0.754, respectively under the analysis criterion of 2%/2 mm. For the validation cohort, the AUC result of the GPR classification prediction of the mixed models based on RF and SVM were 0.806 and 0.859, respectively under the analysis criterion of 3%/3 mm and were 0.796 and 0.796, respectively under the analysis criterion of 2%/2 mm cohort.Conclusions:Complexity models and mixed models were developed based on the RF and SVM method. Both types of models allow for the numerical and classification predictions of the GPRs of VMAT radiotherapy plans under analysis criteria of 3%/3 mm and 2%/2 mm. The mixed models have higher prediction accuracy than the complexity models.

Objective:To explore the correlation between prenatal clinical data with etiological diagnosis and neonatal outcome in isolated fetal ascites.Methods:Totally, 36 pregnancy cases diagnosed as isolated fetal ascites by ultrasound in Provincial Hospital Affiliated to Shandong University from June 22nd, 2016 to September 28th, 2018 were collected. Invasive prenatal diagnosis was performed by taking fetal cord blood, amniotic fluid, and fetal ascites respectively for cytogenetics, molecular genetics and biochemical examination and the impact of intrauterine therapeutic procedures on neonatal outcomes was evaluated as well. The correlation among prenatal examination, pathogeny and prognosis was analyzed by Fisher′s exact test.Results:(1) The prognosis of isolated fetal ascites initially presenting ≥28 weeks was better than that before 28 weeks, survival rate of 1-year-old were 13/15 and 9/17,respectively, the difference was statistically significant ( P<0.05). (2) The etiologic diagnosis rate of ascites before delivery was 31%(11/36), which increased to 53%(19/36) totally after birth. Characteristics of cases which were defined prenatally were as follows: 8 cases of digestive tract diseases showed ultrasonic abnormalities, including echogenic bowel, bowel dilatation and polyhydramnios; platelet level in umbilical cord blood of fetuses infected with cytomegalovirus were below 100 × 10 9/L in 2 cases; 1 case of urinary system malformation showed megalocystis and hydronephrosis. Cases which were defined causes after birth included: 3 fetuses with chyloperitonium presented persistent fetal ascites; 3 cases of digestive-related causes were rectal duplication with infection, mesentery stenosis, and intestinal atresia; other causes included Pierre-Robin syndrome and Budd-Chiari syndrome. (3) The live birth rate was 72% (26/36) and survival rate of 1-year-old was 61% (22/36). And 9/10 of infants who underwent surgeries got good outcomes. Fetal ascites due to abdominal or pelvic factors turned well in 13/16 of cases. Conclusions:The pregnancy outcome of fetal isolated ascites depends mainly on primary causes. Gastrointestinal abnormality is one of the most common causes. Excluded intrauterine infection, chromosomal abnormality and abnormal systemic ultrasonic findings, fetus with reduced ascites as the pregnancy progresses will get good outcome.