Repellency Assessment of Nepeta cataria Essential Oils and Isolated Nepetalactones on Aedes aegypti.

There is an increased need for improved and affordable insect repellents to reduce transmission of rapidly spreading diseases with high mortality rates. Natural products are often used when DEET cannot be afforded or accessed and when consumers choose not to use a synthetic repellent. The essential oils from two newly bred Nepeta cataria (catnip) plants representing two different chemotypes and their respective isolated nepetalactone isomers were evaluated as mosquito repellents against Aedes aegypti mosquitoes that transmit the Zika and Dengue virus in a one choice landing rate inhibition assay. A dose response curve was generated for each treatment and a time course analysis of repellency was performed over 24 hours with a N. cataria essential oil sample. The results indicate that all essential oil samples and their respective purified nepetalactone isomers were able to achieve greater than 95% repellency. Between two and four hours, the ability to repel more than 95% of the mosquitoes diminished. At the lowest concentrations tested, the nepetalactones and crude essential oil samples were more effective than DEET at reducing the number of mosquito landings

A sensitive electrochemical sensor based on polypyrrole/electrochemically reduced graphene oxide for the determination of imidacloprid

The glassy carbon electrode (GCE) was modified by electrochemically reduced graphene oxide (ERGO) and polypyrrole (PPy) prepared by simple cyclic voltammetry (CV) electropoly­merization. The PPy/ERGO modified electrode (PPy/ERGO/GCE) was used as a platform of electrochemical sensor to detect imidacloprid (IMI) insecticide. CV and differential pulse voltammetry (DPV) were chosen as the methods to investigate of the electrochemical behavior of IMI on PPy/ERGO/GCE surface. Scanning electron microscopy (SEM) and Raman spectra were utilized to describe the morphology and structure of the modified electrode. Experimental parameters were optimized, such as the number of polymerization cycles, scan rate and the pH value of electrolyte. Under the optimized conditions, when the concentration of IMI was in the range of 1-10 μM and 10-60 μM, the increase of reduction peak current was linear with the concentration of IMI, and the low detection limit was found to be 0.18 μM (S/N = 3). Results showed that PPy/ERGO/GCE demonstrated satisfactory reproducibility and stability, and has great potential in actual sample testing

Endoplasmic Reticulum Stress Mediated MDRV p10.8 Protein-Induced Cell Cycle Arrest and Apoptosis Through the PERK/eIF2α Pathway

In this study, the mechanism of Muscovy duck reovirus (MDRV) p10.8 protein-induced pathogenesis was investigated, with a focus on endoplasmic reticulum (ER) stress. In chicken embryo fibroblasts cell lines (DF1), pCI-neo-flg-p10.8 protein transfection increased the phosphorylation (p-) levels of PERK and eIF2α as shown by Western blotting analysis and led to the dissociation of BiP from PERK as shown by co-immunoprecipitation (Co-IP) analysis. Results of treatment with both ER stress activator and inhibitor further confirmed that p10.8 protein induced ER stress. Subsequently, using flow cytometry analysis, it was also found that p10.8 protein induced cell cycle arrest during the G0/G1 phase. Furthermore, p10.8 transfection increased the phosphorylation levels of PERK and eIF2α, and reduced the expression levels of CDK2, CDK4, and Cyclin E according to Western blotting analysis. Treatment with ER stress activator and ER stress inhibitor after p10.8 protein transfection in DF1 cells further indicated that p10.8 protein induced ER stress, which resulted in cell cycle arrest. The results of knockdown of either PERK or eIF2α genes further confirmed that p10.8 protein-induced ER stress led to cell cycle arrest through the PERK/eIF2α pathway. Further results showed that p10.8 protein induced ER stress and apoptosis in DF1 cells. The expression levels of p-PERK, p-eIF2α, CHOP, cleaved-Caspase12, and cleaved-Caspase3 were increased by p10.8 protein. Test results of treatment with each of Tunicamycin, TUDCA and knockdown of PERK, and eIF2α, confirmed that p10.8 protein induced ER stress involving apoptosis via the PERK/eIF2α pathway. In conclusion, MDRV p10.8 protein induced ER stress that caused cell cycle arrest and apoptosis through the PERK/eIF2α pathway

Overexpression of Smad2 Reveals Its Concerted Action with Smad4 in Regulating TGF- β-Mediated Epidermal Homeostasis

AbstractMembers of the transforming growth factor-β (TGF-β) superfamily are critical regulators for epithelial growth and can alter the differentiation of keratinocytes. Transduction of TGF-β signaling depends on the phosphorylation and activation of Smad proteins by heteromeric complexes of ligand-specific type I and II receptors. To understand the function of TGF-β and activin-specific Smad, we generated transgenic mice that overexpress Smad2 in epidermis under the control of keratin 14 promoter. Overexpression of Smad2 increases endogenous Smad4 and TGF-β1 expression while heterozygous loss of Smad2 reduces their expression levels, suggesting a concerted action of Smad2 and -4 in regulating TGF-β signaling during skin development. These transgenic mice have delayed hair growth, underdeveloped ears, and shorter tails. In their skin, there is severe thickening of the epidermis with disorganized epidermal architecture, indistinguishable basement membrane, and dermal fibrosis. These abnormal phenotypes are due to increased proliferation of the basal epidermal cells and abnormalities in the program of keratinocyte differentiation. The ectodermally derived enamel structure is also abnormal. Collectively, our study presents the first in vivo evidence that, by providing an auto-feedback in TGF-β signaling, Smad2 plays a pivotal role in regulating TGF-β-mediated epidermal homeostasis

A peanut and weed detection model used in fields based on BEM-YOLOv7-tiny

Due to the different weed characteristics in peanut fields at different weeding periods, there is an urgent need to study a general model of peanut and weed detection and identification applicable to different weeding periods in order to adapt to the development of mechanical intelligent weeding in fields. To this end, we propose a BEM-YOLOv7-tiny target detection model for peanuts and weeds identification and localization at different weeding periods to achieve mechanical intelligent weeding in peanut fields at different weeding periods. The ECA and MHSA modules were used to enhance the extraction of target features and the focus on predicted targets, respectively, the BiFPN module was used to enhance the feature transfer between network layers, and the SIoU loss function was used to increase the convergence speed and efficiency of model training and to improve the detection performance of the model in the field. The experimental results showed that the precision, recall, mAP and F1 values of the BEM-YOLOv7-tiny model were improved by 1.6%, 4.9%, 4.4% and 3.2% for weed targets and 1.0%, 2.4%, 2.2% and 1.7% for all targets compared with the original YOLOv7-tiny. The experimental results of positioning error show that the peanut positioning offset error detected by BEM-YOLOv7-tiny is less than 16 pixels, and the detection speed is 33.8 f/s, which meets the requirements of real-time seedling grass detection and positioning in the field. It provides preliminary technical support for intelligent mechanical weeding in peanut fields at different stages