ThermalProGAN: A sequence-based thermally stable protein generator trained using unpaired data.

MOTIVATION: The synthesis of proteins with novel desired properties is challenging but sought after by the industry and academia. The dominating approach is based on trial-and-error inducing point mutations, assisted by structural information or predictive models built with paired data that are difficult to collect. This study proposes a sequence-based unpaired-sample of novel protein inventor (SUNI) to build ThermalProGAN for generating thermally stable proteins based on sequence information. RESULTS: The ThermalProGAN can strongly mutate the input sequence with a median number of 32 residues. A known normal protein, 1RG0, was used to generate a thermally stable form by mutating 51 residues. After superimposing the two structures, high similarity is shown, indicating that the basic function would be conserved. Eighty four molecular dynamics simulation results of 1RG0 and the COVID-19 vaccine candidates with a total simulation time of 840[Formula: see text]ns indicate that the thermal stability increased. CONCLUSION: This proof of concept demonstrated that transfer of a desired protein property from one set of proteins is feasible. Availability and implementation: The source code of ThermalProGAN can be freely accessed at https://github.com/markliou/ThermalProGAN/ with an MIT license. The website is https://thermalprogan.markliou.tw:433. Supplementary information: Supplementary data are available on Github.

Conceptualizing the Internet Compulsive-Buying Tendency: What We Know and Need to Know in the Context of the COVID-19 Pandemic

Over the past decade, new innovative products and services have been introduced into the marketplace using advanced technology. The enticement of new products lures consumers to buy compulsively. Because of the convenience and the characteristics of online shopping, it will increase the incidence of compulsive-buying behavior. Meanwhile, due to the fact that the COVID-19 pandemic is continuing to spread around the world, consumers may change their decision-making and behavior to shop online more frequently and intensively. The repetitive shopping online means more cardboard, delivery transportations, and vehicles and that more goods will be produced. It will result in an unfriendly result for the environment. Given the critical role of compulsive buying in the emerging Internet retail environment, it is necessary to develop and validate an instrument to measure the Internet compulsive-buying tendency (ICBT). Therefore, a rigorous measurement-scale-development procedure was applied to evaluate the initial 31 items. After two rounds of data collection and assessment, the final instrument contained 18 items that fall into four subconstructs: the tendency to spend online, feelings about online shopping and spending, dysfunctional online spending, and online post-purchase guilt. These factors can provide a basis for predicting tendencies toward Internet compulsive shopping and can be used to evaluate consumers’abnormal behavior in online-shopping circumstances.

Rapid detection of SARS-CoV-2 with CRISPR-Cas12a.

The recent outbreak of betacoronavirus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which is responsible for the Coronavirus Disease 2019 (COVID-19) global pandemic, has created great challenges in viral diagnosis. The existing methods for nucleic acid detection are of high sensitivity and specificity, but the need for complex sample manipulation and expensive machinery slow down the disease detection. Thus, there is an urgent demand to develop a rapid, inexpensive, and sensitive diagnostic test to aid point-of-care viral detection for disease monitoring. In this study, we developed a clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated proteins (Cas) 12a-based diagnostic method that allows the results to be visualized by the naked eye. We also introduced a rapid sample processing method, and when combined with recombinase polymerase amplification (RPA), the sample to result can be achieved in 50 minutes with high sensitivity (1-10 copies per reaction). This accurate and portable detection method holds a great potential for COVID-19 control, especially in areas where specialized equipment is not available.

Characteristics of COVID-2019 in areas epidemic from imported cases.

OBJECTIVES: The outbreak of the 2019 novel coronaviruses disease (COVID-2019) in areas with epidemics due to imported cases is a cause of concern in China; however, few studies have reported on the prevalence of COVID-19 in these areas. METHODS: The number of diagnosed cases in Fujian Province was collected, and the time distribution of these cases was analyzed. RESULTS: The results showed that the COVID-19 prevalence in areas with epidemics due to imported cases could be divided into two stages. The first stage was an outbreak dominated by imported cases, with the data showing an obviously skewed distribution. The second stage was dominated by nonimported cases with sporadic and low-level fluctuations. Moreover, the data demonstrated that the ratio of unexplained infections to nonimported cases was increasing. CONCLUSIONS: A two-stage outbreak in areas with epidemics due to imported cases, effective control of the "source of infection" and blocking of the transmission route can significantly minimize the peak height in the first stage and the spread of the epidemic in the second stage. Control of the epidemic in the second stage requires prevention and control of the aggregation of cases caused by unexplained infections.