DYT1 MUTATIONS AMONGST EARLY ONSET PRIMARY DYSTONIA PATIENTS IN CHINA

Objective To investigate the frequency of GAG deletion in the DYT1 gene among early onset primary dystonia patients in China. Methods Thirteen patients with early onset primary torsion dystonia were screened for mutation in exon 5 of the DYT1 gene using denaturing high-performance liquid chromatography （DHPLC） and DNA sequencing, and the results were confirmed with polymerase chain reaction-restriction fragment length polymorphism （PCR-RFLP）. Results The GAG deletion mutation which results in Glu302del in exon 5 of the DYT1 gene was found in 5 patients. The detecting results were consistent between with DHPLC and PCR-RFLP. We did not find any other mutations in the DYT1 gene. Conel^iotm The GAG deletion in the DYT1 gene is common amongst early onset primary torsion dystonia patients in Chin＆ The frequency of DYT1 mutation is not significantly different between European and Asian patients with early onset primary dystonia.

Effect of neoadjuvant chemotherapy on immune function, vascular endothelial function and LEP in patients with rectal cancer

Objective:To investigate the effect of neoadjuvant chemotherapy on immune function, vascular endothelial function and LEP in patients with rectal cancer.Methods: The clinical data of 110 patients undergoing laparoscopic rectal cancer radical resection in our hospital were retrospectively analyzed. They were divided into control group (n=55) and study group (n=55) according to the surgical procedure. The control group was treated with laparoscopic surgery, and the study group was treated with laparoscopic surgery combined with neoadjuvant chemotherapy. The tumor markers CA242 and CA19-9, immunological function indicators C3, C4, IgA, IgG, vascular endothelial function VEGF and VEGFR-2, LEP and IGF-1 were detected at 1 day before treatment and 1 day after treatment.Results:Before treatment, serum CA242, CA19-9, C3, C4, IgA, IgG, VEGF, VEGFR-2, LEP and IGF-1 levels were not significantly different between the two groups (P<0.05). After treatment, serum CA242 and CA19-9 levels were significantly lower in the two groups (P<0.05). The levels of CA242 and CA19-9 in the study group were (15.23±1.53) IU/mL and (20.13±2.01) U/mL, which were significantly lower than the control group (P<0.05). After treatment, serum IgA and IgG levels were significantly higher in both groups, and C3 and C4 levels were significantly increased in the study group (P<0.05). The levels of C3, C4, IgA and IgG in the study group were significantly higher (1.31±0.13) g/L, (0.34±0.03) g/L, (1.78±0.18) g/L and (11.02±1.13) g/L, which were higher those in the control group (P<0.05). After treatment, serum VEGF and VEGFR-2 levels were significantly lower in the two groups (P<0.05). The levels of VEGF and VEGFR-2 in the study group were (118.15±11.86) ng/L and (92.44±9.26) ng/L, which were significantly lower than those in the control group (P<0.05). After treatment, LEP levels were significantly increased in both groups, and IGF-1 levels were significantly lower in both groups (P<0.05). The LEP of the study group was (7.51±0.71) ng/mL, which were significantly higher than that of the control group, and the level of IGF-1 was (281.47±28.86) μg/L in the study group, which were significantly lower than the control group (bothP<0.05).Conclusion:Laparoscopic rectal cancer surgery combined with neoadjuvant chemotherapy can significantly improve the vascular endothelial function of patients with rectal cancer and improve the immune function of the body. It is worthy of clinical application.

Graph attention convolutional neural network model for chemical poisoning of honey bees’ prediction

The impact of pesticides on insect pollinators has caused worldwide concern. Both global bee decline and stopping the use of pesticides may have serious consequences for food security. Automated and accurate prediction of chemical poisoning of honey bees is a challenging task owing to a lack of understanding of chemical toxicity and introspection. Deep learning(DL) shows potential utility for general and highly variable tasks across fields. Here, we developed a new DL model of deep graph attention convolutional neural networks(GACNN) with the combination of undirected graph(UG) and attention convolutional neural networks(ACNN) to accurately classify chemical poisoning of honey bees. We used a training dataset of 720 pesticides and an external validation dataset of 90 pesticides, which is one order of magnitude larger than the previous datasets. We tested its performance in two ways: poisonous versus nonpoisonous and GACNN versus other frequently-used machine learning models. The first case represents the accuracy in identifying bee poisonous chemicals. The second represents performance advantages. The GACNN achieved ~6% higher performance for predicting toxic samples and more stable with ~7%Matthews Correlation Coefficient(MCC) higher compared to all tested models, demonstrating GACNN is capable of accurately classifying chemicals and has considerable potential in practical applications.In addition, we also summarized and evaluated the mechanisms underlying the response of honey bees to chemical exposure based on the mapping of molecular similarity. Moreover, our cloud platform(http://beetox.cn) of this model provides low-cost universal access to information, which could vitally enhance environmental risk assessment.