Search

Nitenpyram, taking the place of imidacloprid, is a widely used neonicotinoid insecticide to control Nilaparvata lugensin Asia. Two P450s, CYP4CE1 and CYP6ER1, are key factors in the metabolic resistance against nitenpyram and imidacloprid. In this study, we found that CYP4CE1expression was strongly associated with nitenpyram resistance in 8 field-collected populations, whereas CYP6ER1expression correlated with imidacloprid resistance. Hence, we focused on nitenpyram metabolism by CYP4CE1, due to that imidacloprid metabolism by CYP6ER1 has intensively investigated. Mass spectrometry analysis revealed that recombinant CYP4CE1 metabolized nitenpyram into three products, N-desmethyl nitenpyram, hydroxy-nitenpyram, and N-desmethyl hydroxy-nitenpyram, with a preference for hydroxylation. In contrast, CYP6ER1 metabolized nitenpyram into a single product, N-desmethyl nitenpyram. These results provide new insights into the specific catalytic mechanisms of P450 enzymes in neonicotinoid metabolism and underscore the importance of different catalytic reactions in neonicotinoid insecticide resistance.

In order to improve the accuracy of user consumption behaviour prediction, mining accuracy of behaviour data, and reduce the long prediction time, this paper designs a user consumption behaviour prediction method in the context of social media marketing. Firstly, research on social media marketing platforms is conducted, and then the impact model between social media marketing and user consumption behaviour is analysed, in order to analyse the impact of social media marketing on user consumption behaviour. Then the user consumption behaviour data is obtained and deeply mined. With the help of integrated weak learning classifier, the behaviour data is classified, and the information entropy of different behaviour data is calculated. Finally, a prediction model based on random forest is constructed to achieve the final prediction analysis. The test results show that the proposed prediction method reduces the prediction error, has high mining accuracy and short prediction time cost for behavioural data, and has good application value.

The importance of glutathione S-transferases (GSTs) in imidacloprid resistance in Nilaparvata lugens, a major rice pest, and other insects was often excluded, mostly due to the slight effects of diethyl maleate (DEM) on synergizing imidacloprid in resistant populations. Here, we found that the synergistic effects of DEM were time-dependent. At 24 or 48 h, the time often selected to record mortalities in imidacloprid bioassay, DEM really did not cause an obvious increase in imidacloprid toxicity. However, significant effects were observed after 72 h. The results revealed that GSTs, as phase II detoxification enzymes to metabolize secondary products generated from phase I detoxification enzymes, were also important in imidacloprid resistance in N. lugens, but might have occurred a little later than that of P450s and CarEs as phase I enzymes. The constitutive overexpression in the imidacloprid-resistant strain G25 and expression induction by imidacloprid in the susceptible strain S25 indicated that four GST genes, NlGSTs1, NlGSTs2, NlGSTe1, and NlGSTm1, were important in imidacloprid resistance, which was confirmed by RNAi test. The higher expression levels and more expression induction by imidacloprid in the midgut and fat body compared to the whole insect supported the important roles of these four GSTs, which was also supported by the more overexpression times in the midgut and fat body versus the whole insect between G25 and S25 strains. Taking the data together, the study ascertained the roles of GSTs in imidacloprid resistance in N. lugens.

Supplemental Digital Content is available in the text.

Background To evaluate the diagnostic value of combinations of tumor markers carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 125, CA153, and CA19-9 in identifying malignant pleural effusion (MPE) from non-malignant pleural effusion (non-MPE) using machine learning, and compare the performance of popular machine learning methods.Methods A total of 319 samples were collected from patients with pleural effusion in Beijing and Wuhan, China, from January 2018 to June 2020. Five machine learning methods including Logistic regression, extreme gradient boosting (XGBoost), Bayesian additive regression tree, random forest, and support vector machine were applied to evaluate the diagnostic performance. Sensitivity, specificity, Youden's index, and the area under the receiver operating characteristic curve (AUC) were used to evaluate the performance of different diagnostic models.Results For diagnostic models with a single tumor marker, the model using CEA, constructed by XGBoost, performed best (AUC = 0.895, sensitivity = 0.80), and the model with CA153, also by XGBoost, showed the largest specificity 0.98. Among all combinations of tumor markers, the combination of CEA and CA153 achieved the best performance (AUC = 0.921, sensitivity = 0.85) in identifying MPE under the diagnostic model constructed by XGBoost.Conclusions Diagnostic models for MPE with a combination of multiple tumor markers outperformed the models with a single tumor marker, particularly in sensitivity. Using machine learning methods, especially XGBoost, could comprehensively improve the diagnostic accuracy of MPE.

Chimeric antigen receptor (CAR)-γδ T cells are promising in immunotherapy owing to the dual recognition system of γδ T cells, which is potential to exhibit stronger anti-tumor effect. Up to date, established CAR-γδ T cells exhibit poor anti-tumor efficiency and are commonly generated using lentiviral (LV) or gamma-retroviral (γRV) vectors, which may increase the risk of insertional mutagenesis. Nowadays, clustered regularly interspaced palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) has been widely used to cleave the genomic sequence precisely, as well as Adeno-associated Virus (AAV) being used to deliver DNA templates for target sequence knock-in (KI) mediated by homology-directed repair, which could contribute to achieve the accurate insertion of CAR at a specific site. Furthermore, the endogenous promoter of TCR has been used to express CAR molecules with stable expression and better antitumor function in the production of CAR-αβ T cells. In the present study, we established and optimized the strategy to generate CAR-γδ T cells, combining the site-specific knock-out (KO) targeting the TCR delta chain constant region (TRDC) site of γδ T cells using CRISPR/Cas9 and site-specific CAR knock-in using AAV.

CYP6ER1overexpression is a prevalent mechanism for neonicotinoid resistance in Nilaparvata lugens. Except for imidacloprid, the metabolism of other neonicotinoids by CYP6ER1 lacked direct evidence. In this study, a CYP6ER1knockout strain (CYP6ER1–/–) was constructed using the CRISPR/Cas9 strategy. The CYP6ER1–/–strain showed much higher susceptibility to imidacloprid and thiacloprid with an SI (sensitivity index, LC50of WT/LC50of CYP6ER1–/–) of over 100, which was 10–30 for four neonicotinoids (acetamiprid, nitenpyram, clothianidin, and dinotefuran) and less than 5 for flupyradifurone and sulfoxaflor. Recombinant CYP6ER1 showed the highest activity to metabolize imidacloprid and thiacloprid and moderate activity for the other four neonicotinoids. Main metabolite identification and oxidation site prediction revealed that CYP6ER1 activities were insecticide structure-dependent. The most potential oxidation site of imidacloprid and thiacloprid was located in the five-membered heterocycle with hydroxylation activity. For the other four neonicotinoids, the potential site was within the ring opening of a five-membered heterocycle, indicating N-desmethyl activity.

Cytochrome P450 enzymes metabolize various xenobiotics in insects. Compared to numerous P450s associated with insecticide detoxification and resistance, fewer have been identified to bioactivate proinsecticides in insects. Here we reported that two P450s, CYP4C62 and CYP6BD12, in Nilaparvata lugenscould bioactivate chlorpyrifos, an organophosphorus insecticide, into its active ingredient chlorpyrifos-oxon in vivoand in vitro. RNAi knockdown of these two genes significantly reduced the sensitivity to chlorpyrifos and the formation of chlorpyrifos-oxon in N. lugens. Chlorpyrifos-oxon was generated when chlorpyrifos was incubated with the crude P450 enzyme prepared from N. lugensor recombinant CYP4C62 and CYP6BD12 enzymes. The expression reduction of CYP4C62 and CYP6BD12 and alternative splicing in CYP4C62 reduced the oxidation of chlorpyrifos into chlorpyrifos-oxon, which contributed importantly to chlorpyrifos resistance in N. lugens. This study revealed a novel mechanism of insecticide resistance due to the bioactivation reduction, which would be common for all currently used proinsecticides.

Nonlinear concentration-dependent electronic and optical properties of the Si1–xGexsubstitutional alloy nanowires are investigated using first-principles calculations. The nonuniform distribution of Ge (or Si) atoms is found, and the resulting orbital hybridization of the inner Ge or Si atoms results in the nonlinear Ge concentration dependence of electronic properties in the Si1–xGexalloy NWs, which suggests an effective approach to modulate band-gap properties of the NWs along all three directions. Moreover, a strong adsorption of solar radiation and a high quantum yield is predicted in (110)-oriented alloy NWs, which implies a great potential of Si1–xGexalloy NWs in the optical electronics applications on nanoscale.

Background Ischaemia-reperfusion injury is considered an inevitable component of organ transplantation, compromising organ quality and outcomes. Although several treatments have been proposed, none has avoided graft ischaemia and its detrimental consequences.