Data-driven risk assessment of the incursion of African swine fever virus via pig products brought illegally into South Korea by travelers based on the temporal relationship between outbreaks in China

Since 2018, Asian countries have been affected by the African swine fever (ASF) virus, with major socioeconomic consequences. Moreover, the number of people traveling in Asian countries has been increasing, leading to an inevitable increase in the risk of ASF spread through livestock products carried by travelers. China and South Korea have close geo-economic ties and numerous international travelers. After the ASF outbreak in China in 2018, many illegally imported pig products (IIPPs) that were confiscated from travelers from China at the port of entry in South Korea tested positive for ASF. The detection of ASF virus (ASFV)-positive IIPPs highlights the need to further assess the risk of incursion by travelers and review the existing prevention strategies. Here, we investigated the temporal relationship between ASF outbreaks in China and the detection of ASFV-positive IIPPs in randomly confiscated samples from all ports of entry, such as flights and ships to South Korea, from 2018 to 2019 using a cross-correlation analysis. Based on the significantly correlated temporal lags between the bivariate time-series data, a risk assessment model, using the Bayesian framework, was built to estimate the distribution of the parameters for the risk assessment model and the monthly probability of ASF being introduced via IIPPs from China to South Korea. ASF outbreaks in China were significantly associated with the detection of ASFV-positive IIPPs in South Korea 5 months later. Hence, the monthly probability of ASFV-infected pig products imported from China via a traveler to South Korea was estimated to be 2.00 × 10−5, corresponding to a 0.98 mean monthly probability of at least one ASF-infected pig product arriving at ports of entry via travelers, from 2018 to 2019. To our knowledge, this study is the first attempt to estimate the risk of ASF introduction via pig products carried by international travelers to all ports from neighboring countries in the Asian region using commonly exchanged observed data. The data presented in this study can be used to refine the intervention strategies to combat the spread of transboundary animal diseases

Generation of high concentration nanobubbles based on friction tubes

Nanobubble-related technologies have been confirmed to be useful in various fields such as climate change and the environment as well as water-based industries such as water purification, crops, horticulture, medical care, bio, and sterilization. However, a method of mass production in real time enough to apply nano-bubbles to the industry has not yet been developed. We explored the mechanism of nano-bubble water generation by friction between water and walls and developed a tube device applying the shape of the flow path to maximize the friction in the fluid passing through the flow path. It also describes the case of real-time and low-power mass production of nanobubbles and its technical utility. We found that the friction of nanotubes alone can easily and quickly improve the production of nanobubbles with small particle size in real time; by increasing the shearing pressure while increasing the effective friction constant value, the particle size of nanobubbles can be smaller while increasing the particle concentration.Comment: 24 pages, 24 figures, 6 table

Sleep state classification using power spectral density and residual neural network with multichannel EEG signals.

This paper proposes a classification framework for automatic sleep stage detection in both male and female human subjects by analyzing the electroencephalogram (EEG) data of polysomnography (PSG) recorded for three regions of the human brain, i.e., the pre-frontal, central, and occipital lobes. Without considering any artifact removal approach, the residual neural network (ResNet) architecture is used to automatically learn the distinctive features of different sleep stages from the power spectral density (PSD) of the raw EEG data. The residual block of the ResNet learns the intrinsic features of different sleep stages from the EEG data while avoiding the vanishing gradient problem. The proposed approach is validated using the sleep dataset of the Dreams database, which comprises of EEG signals for 20 healthy human subjects, 16 female and 4 male. Our experimental results demonstrate the effectiveness of the ResNet based approach in identifying different sleep stages in both female and male subjects compared to state-of-the-art methods with classification accuracies of 87.8% and 83.7%, respectively

Friction Tubes to Generate Nanobubble Ozone Water with an Increased Half-Life for Virucidal Activity

Nanobubbles and related technologies are expected to be highly utilized in water resource-based industries such as water purification, crops, horticulture, medicine, bio, and sterilization. Ozone, a chemical with high sterilizing power, is known as a natural substance that is reduced to oxygen and water after reacting with pollutants. Ozone water, which is generated by dissolving ozone in water, has been used in various industrial sectors such as medical care, food, and environment. Due to the unstable molecular state of ozone, however, it is difficult to produce, use, and supply ozone at industrial sites in a stable manner. This study proposed a method for constructing a system that can generate high-concentration ozone water in large quantities using low power in real time and maintaining the concentration of the generated ozone water over the long term. Friction tubes (called 'nanotube') played a key role to generate nanobubble ozone water with an increased half-life for virus killing activity. In addition, the safety of ozone water during its spray into the air was explained, and virucidal activity test cases for the influenza A (H1N1/A/PR8) and COVID-19 (SARS-CoV-2) virus using high-concentration ozone water as well as its technical efficacy were described

Effect of 5-aminolevulinic acid-based photodynamic therapy via reactive oxygen species in human cholangiocarcinoma cells

Cancer cells have been reported to exhibit an enhanced capacity for protoporphyrin IX (PpIX) synthesis facilitated by the administration of 5-aminolevulinic acid (ALA). We investigated the effect of ALA-based photodynamic therapy (PDT) on human cholangiocarcinoma cells (HuCC-T1). Since protoporphyrin IX (PpIX), a metabolite of ALA, can produce reactive oxygen species (ROS) under irradiation and then induce phototoxicity, ALA-based PDT is a promising candidate for the treatment of cholangiocarcinoma. When various concentrations of ALA (0.05–2 mM) were used to treat HuCC-T1 cells for 6 or 24 hours, the intracellular PpIX level increased according to the ALA concentration and treatment time. Furthermore, an increased amount of PpIX in HuCC-T1 cells induced increased production of ROS by irradiation, resulting in increased phototoxicity

Cordycepin inhibits human ovarian cancer by inducing autophagy and apoptosis through Dickkopf-related protein 1/β-catenin signaling

Cordycepin, the major active component from Cordyceps militaris, has been reported to significantly inhibit some types of cancer; however, its effects on ovarian cancer are still not well understood. In this study, we treated human ovarian cancer cells with different doses of cordycepin and found that it dose-dependently reduced ovarian cancer cell viability, based on Cell counting kit-8 reagent. Immunoblotting showed that cordycepin increased Dickkopf-related protein 1 (Dkk1) levels and inhibited β-catenin signaling. Atg7 knockdown in ovarian cancer cells significantly inhibited cordycepin-induced apoptosis, whereas β-catenin overexpression abolished the effects of cordycepin on cell death and proliferation. Furthermore, we found that Dkk1 overexpression by transfection downregulated the expression of c-Myc and cyclin D1. siRNA-mediated Dkk1 silencing downregulated the expression of Atg8, beclin, and LC3 and promoted β-catenin translocation from the cytoplasm into the nucleus. These results suggest that cordycepin inhibits ovarian cancer cell growth, possibly through coordinated autophagy and Dkk1/β-catenin signaling. Taken together, our findings provide new insights into the treatment of ovarian cancer using cordycepin