Objective　By exploring the function of sulfakinin (SK) and sulfakinin receptor (SKR) of Aedes aegypti, it laid a certain experimental basis and theoretical basis for the research and development of new insecticides targeting neuropeptides and their receptors. Methods　This study investigated the roles of SK and its receptor gene in Ae. aegypti using bioinformatics analysis and Clustered Regularly Interspaced Short Palindromic Repeats(CRISPR)/Cas9 knockout technology. Subsequently, RNA interference technology was employed to suppress the expression of SK or its receptor in adult mosquitoes. Lastly, transcriptome sequencing technology was utilized to identify and analyze differentially expressed genes between the interference group and the control group in order to gain insights into their functions. Results　It was found that there is only one SK receptor in Ae. aegypti. In addition, during the construction of mutant strains of Ae. aegypti SK and its receptor gene, it was found that only 2% of the G0 generation mutant strains mutated to form chimeras, with a large number of male chimeras dying, and only 14% of female chimeras being able to lay eggs, ultimately resulting in no effective G1 generation mutants. Transcriptome data showed, compared to the control group, 181 genes were significantly differentially expressed after interfering with the SK gene, with 62 genes significantly upregulated and 119 genes significantly downregulated. In addition, after interference with the sulfakinin receptor, 110 genes exhibited significant differential expression, including 20 upregulated and 90 downregulated genes. Cross-analysis of the two datasets identified 46 genes with significant expression changes after interference with sulfakinin or its receptor, with only 4 genes upregulated and the remaining 42 genes significantly downregulated, and the differentially expressed genes were mainly enriched in the metabolic pathway, endocrine system, and digestive system. Conclusions　The SK and its receptor gene are highly conserved and may primarily play roles in regulating the energy metabolism and digestion functions in Ae. aegypti, thus playing an important role in regulating insect growth and development.

Objective: To explore the risk factors of long-term treatment outcomes and establish predicting model for laparoscopic left hepatectomy in hepatolithiasis. Methods: Clinical data of 108 patients with hepatolithiasis who underwent laparoscopic left sided hepatectomy and with complete follow-up data were retrospectively collected from June 2011 to June 2016 at the Second Affiliated Hospital of Nanchang University. Twenty-six males and 82 females were enrolled. The age was (52.4±11.7) years (range:20-80 years) , and the median follow-up time was 36 months (range: 24-83 months) . Patients were randomly divided into training group (79 cases) and validation group (29 cases) with a ratio of about 3∶1. Twenty-five preoperative and intraoperative clinical factors were selected for potential factors that might affect long-term outcomes, and quality of life was used as an surrogate evaluation index. Univariate analysis and multivariate logistic regression analysis were used to investigate the potential risk factors, and to construct and validate the predictive nomogram for surgical outcomes. Results: Among 108 patients, 10 patients (9.3%) had residual stones, 8 patients (7.4%) had recurrent stones, 12 patients (11.1%) had recurrent cholangitis and 3 patients (2.8%) died. Univariate analysis showed that history of hepatobiliary surgery, gender, activation of partial thromboplastin time, alkaline phosphatase, use of choledochoscopy, postoperative stone residual, serum creatinine, postoperative biliary drainage and operation time were risk factors that may affect long-term outcomes (all P<0.15) . Multivariate analysis showed that the history of previous hepatobiliary surgery (OR=2.305, 95% CI: 0.383-4.227, P=0.019) , postoperative biliary drainage (OR=2.043, 95% CI: 0.182-4.209, P=0.048) , operation time ≥262.5 minutes (OR=1.971, 95% CI: 0.154-4.023, P=0.045) were independent risk factor affecting long-term outcomes. Based on the above factors, the predictive nomogram model was constructed. Internal and external validations showed good discrimination (area under the curve of receiver operating curve>0.7) and calibration (Hosmer-Lemeshow test: P>0.05) performance, which indicated that the prediction effect was favorable. Conclusions History of previous hepatobiliary surgery, postoperative biliary drainage and operation time ≥262.5 minutes are independent risk factors for long-term outcome. The predictive nomogram model based on risk factors relates to surgical outcomes presented good clinical predictive effects, which might contribute to the prediction of the long-term outcomes of laparoscopic left sided hepatectomy for hepatolithiasis.

Artificial intelligence (AI) has important significance and great promise in the pathological diagnosis,imaging diagnosis,prognosis prediction,and molecular subtyping of prostate cancer (PCa). This review focuses on the progress of AI for the diagnosis and molecular classification of PCa,and briefly introduces the application of AI in the pathological diagnosis of needle biopsy and Gleason grading,pathological diagnosis and grading after prostatectomy,and prognosis prediction of PCa patients based on pathological sections. For the pathological diagnosis of needle biopsy and Gleason grading,AI has already comparable to general pathologists;for the pathological diagnosis and grading after prostatectomy,AI can accurately grade and classify tumors;and for the prognosis prediction of PCa patients,AI can directly extract relevant prognostic information from pathological tissue sections for prognosis prediction. In addition,AI can also predict gene mutations in PCa patients and suggest the probability of gene mutation by analyzing the pathological sections.