Effects of Nanoparticles on Double-Stranded RNA Stability in Moth Hemolymph

RNA interference (RNAi) is an immune response in which double-stranded RNA (dsRNA) suppresses a target gene. By designing dsRNA to target genes that are necessary for life, dsRNA can potentially be used as an insecticide. RNAi-based insecticides are badly needed because they are more specific than conventional pesticides and because many insects have developed resistance to pesticides. Unfortunately, some insects produce enzymes that degrade dsRNA and prevent the RNAi response (Cooperet al., 2018). Therefore, RNAi-based insecticides currently cannot be used to control all insects. Here we investigate dsRNA stability when incubated in hemolymph ex vivoto determine if degradation of dsRNA is contributing to the inadequate RNAi response exhibited by lepidopterans, such as the European corn borer (ECB, Ostrinia nubilalis). Our findings indicate that dsRNA is significantly degraded in ECB hemolymph, but encapsulation of dsRNA in chitosan-based nanoparticles (CB-NPs) enhances stability. These findings provide insight into RNAi efficiency limitations in insects, and may provide a method to enhance RNAi efficiency in lepidopterans and other RNAi-refractory pests

Consumers' Willingness to Pay for Treatment-Induced Quality Attributes in Anjou Pears

Ethylene treatments provide an effective method for shortening post-harvest ripening periods for winter Anjou pears and allow market availability throughout the year. However, pear quality may vary under different treatments. A sensory experiment and a consumer survey including questions that address valuation, assessments of sensory characteristics, purchasing habits, and demographics were conducted. Analyses indicate that treatment-induced quality losses significantly affect consumers’ willingness to pay (WTP). Mean WTP for each treatment reveals that consumers prefer pears with a six-day ethylene treatment and are willing to pay a premium of $0.25/pound compared to the market price.pears, sensory, willingness to pay, Consumer/Household Economics, Crop Production/Industries, Resource /Energy Economics and Policy,

Effects of Nanoparticles on Double-Stranded RNA Stability in Corn Soil

Double-stranded RNA (dsRNA) can potentially be used as a pesticide because these molecules trigger an immune response called RNA interference (RNAi). If the expression of essential genes matching the dsRNA sequence are silenced, then the pest dies. New classes of pesticides, including RNAi-based pesticides, are needed to overcome pesticide resistance and reduce the environmental impacts of pesticides. Unfortunately, dsRNA is easily degraded by enzymes in the environment, particularly those produced by microbes in the soil (Dubelmanet al., 2014),severely limiting delivery of dsRNA to cryptic (soil dwelling) species unless transgenic plants are used. Here we investigate dsRNA stability when incubated in corn soil supernatant ex situ to determine if encapsulation of dsRNA in chitosan-basednanoparticles (CB-NPs) enhances stability in corn soil. Interestingly, dsRNA stability was not affected by soil supernatant, possibly due to the time of year when sampling was performed (Icozet al., 2008). Nonetheless, these findings provide insight into dsRNA stability in soil, and in the future may lead to a method for protecting dsRNA from environmental degradation using CB-NPs

Effects of Nanoparticles on Double-Stranded RNA Stability in Corn Soil

Double-stranded RNA (dsRNA) can potentially be used as a pesticide because these molecules trigger an immune response called RNA interference (RNAi). If the expression of essential genes matching the dsRNA sequence are silenced, then the pest dies. New classes of pesticides, including RNAi-based pesticides, are needed to overcome pesticide resistance and reduce the environmental impacts of pesticides. Unfortunately, dsRNA is easily degraded by enzymes in the environment, particularly those produced by microbes in the soil (Dubelmanet al., 2014),severely limiting delivery of dsRNA to cryptic (soil dwelling) species unless transgenic plants are used. Here we investigate dsRNA stability when incubated in corn soil supernatant ex situ to determine if encapsulation of dsRNA in chitosan-basednanoparticles (CB-NPs) enhances stability in corn soil. Interestingly, dsRNA stability was not affected by soil supernatant, possibly due to the time of year when sampling was performed (Icozet al., 2008). Nonetheless, these findings provide insight into dsRNA stability in soil, and in the future may lead to a method for protecting dsRNA from environmental degradation using CB-NPs

Jing Tong Yu Shu, a traditional Chinese medicine, suppresses IL-1β and IL-6 gene expressions in macrophages, and alleviates endometriosis

Purpose: To evaluate the effect of a traditional Chinese medicine, Jing Tong Yu Shu (JTYS) on endometriosis in a rat surgical model. Methods: Endometriosis was induced in 40 female rats. The rats were randomly divided into 4 groups: three JTYS groups given different doses of the drug, and a saline group. After four weeks of treatment with JTYS, the volume of the endometriotic explants was measured, and the levels of IL-1β and IL-6 in peritoneal fluid and serum were determined by enzyme-linked immunosorbent assay (ELISA). The production of cytokine IL-1β and IL-6 by peritoneal macrophages was also measured for each group. Results: JTYS treatment brought about regression of implants and inhibition of IL-1β and IL-6 production in a dose-dependent manner, with high-dose JTYS eliciting 66.76 % reduction in mean endometriotic explant volume. Plasma and peritoneal fluid levels of IL-1β and IL-6 were significantly lower in the high-dose JTYS group than in the saline group (p < 0.05). However, JTYS treatment significantly inhibited IL-1β and IL-6 production in peritoneal macrophages (p < 0.05). Conclusion: These results suggest that JTYS treatment leads to regression of endometriotic lesions in rat. Thus, JTYS has the potential to be developed into a new drug for the treatment of endometriosis. Keywords: Endometriosis, Interleukins, Traditional Chinese medicine, Jing Tong Yu Shu Macrophage

Correlations between IGF-IR Expression and Clinicopathological Factors and Prognosis in Patients with Lung Adenocarcinoma

Background and objective The incidence of lung adenocarcinoma increases rapidly, and IGF-IR is the key mediator of several growth factors signal transduction, therefore it plays an important role in the proliferation and differentiation of cancer cell. The aim of this study is to detect the expression of IGF-IR in lung adenocarcinoma and to evaluate its implication for the clinicopathological factors and prognosis of patients with this disease. Methods The IGF-IR expression was detected by immunohistochemical staining. Correlations between IGF-IR expression with clinicopathological factors were analyzed using the Chi-squared test. The Kaplan-Meier method was used to calculate the overall patient survival rate, and the difference in survival curves was evaluated using a Log-rank test. Univariate and multivariate analysis was carried out using the Cox proportional-hazard model. Results In 126 cases of tumor sections tested, IGF-IR were detected in 89 cases. Statistical analysis revealed that the IGF-IR expression was related to tumor size and T stage, while there were no relations between IGFIR expression and age, gender, smoking, pathological stages, and differentiation. Cox analysis indicated that metastasis and chemotherapy efficacy were the prognostic factors in these patients, while IGF-IR expression was not the independent prognostic factor. Conclusion The IGF-IR expression is related to tumor size and T stage, while there is no relation between IGF-IR expression and prognosis

Stock Trading Optimization through Model-based Reinforcement Learning with Normalizing Fl

With the fast development of quantitative portfolio optimization in financial engineering, lots of promising algorithmic trading strategies have shown competitive advantages in recent years. However, the environment from real financial markets is complex and hard to be fully simulated, considering non-stationarity of the stock data, unpredictable hidden causal factors and so on. Fortunately, difference of stock prices is often stationary series, and the internal relationship between difference of stocks can be linked to the decision-making process, then the portfolio should be able to achieve better performance. In this paper, we demonstrate normalizing flows is adopted to simulated high-dimensional joint probability of the complex trading environment, and develop a novel model based reinforcement learning framework to better understand the intrinsic mechanisms of quantitative online trading. Second, we experiment various stocks from three different financial markets (Dow, NASDAQ and S&P 500) and show that among these three financial markets, Dow gets the best performance results on various evaluation metrics under our back-testing system. Especially, our proposed method even resists big drop (less maximum drawdown) during COVID-19 pandemic period when the financial market got unpredictable crisis. All these results are comparatively better than modeling the state transition dynamics with independent Gaussian Processes. Third, we utilize a causal analysis method to study the causal relationship among different stocks of the environment. Further, by visualizing high dimensional state transition data comparisons from real and virtual buffer with t-SNE, we uncover some effective patterns of betComment: arXiv admin note: text overlap with arXiv:2205.1505

All-optical active THz metasurfaces for ultrafast polarization switching and dynamic beam splitting.

Miniaturized ultrafast switchable optical components with an extremely compact size and a high-speed response will be the core of next-generation all-optical devices instead of traditional integrated circuits, which are approaching the bottleneck of Moore's Law. Metasurfaces have emerged as fascinating subwavelength flat optical components and devices for light focusing and holography applications. However, these devices exhibit a severe limitation due to their natural passive response. Here we introduce an active hybrid metasurface integrated with patterned semiconductor inclusions for all-optical active control of terahertz waves. Ultrafast modulation of polarization states and the beam splitting ratio are experimentally demonstrated on a time scale of 667 ps. This scheme of hybrid metasurfaces could also be extended to the design of various free-space all-optical active devices, such as varifocal planar lenses, switchable vector beam generators, and components for holography in ultrafast imaging, display, and high-fidelity terahertz wireless communication systems

All-optical active THz metasurfaces for ultrafast polarization switching and dynamic beam splitting.

Miniaturized ultrafast switchable optical components with an extremely compact size and a high-speed response will be the core of next-generation all-optical devices instead of traditional integrated circuits, which are approaching the bottleneck of Moore's Law. Metasurfaces have emerged as fascinating subwavelength flat optical components and devices for light focusing and holography applications. However, these devices exhibit a severe limitation due to their natural passive response. Here we introduce an active hybrid metasurface integrated with patterned semiconductor inclusions for all-optical active control of terahertz waves. Ultrafast modulation of polarization states and the beam splitting ratio are experimentally demonstrated on a time scale of 667 ps. This scheme of hybrid metasurfaces could also be extended to the design of various free-space all-optical active devices, such as varifocal planar lenses, switchable vector beam generators, and components for holography in ultrafast imaging, display, and high-fidelity terahertz wireless communication systems