Expanding the UTAUT2 framework to determine the drivers of mobile shopping behaviour among older adults.

In the current severe aging of the population, the problem of "digital divide" of the elderly has become increasingly prominent, and the elderly market represents a vast demographic that is increasingly becoming an important customer segment for mobile shopping in the future. However, there is currently insufficient attention given to the research on mobile shopping behavior among older adults. This study tries to answer what are the driving factors of mobile phone shopping behavior among the elderly? The purpose of this study is to analyze the factors that drive the elderly's mobile phone shopping behavior, and to establish a mobile phone shopping acceptance model for the elderly to predict the factors of the elderly's behavioral intention of using smart phones. Based on the second edition of Unified Theory of Acceptance and Use of Technology theory (UTAUT 2), this study proposed a mobile phone shopping acceptance model for the elderly. The study collected valid data from 389 Chinese elderly people through questionnaires and analyzed them using structural equation models. The results showed that utilitarian, anxiety, trust, performance expectancy, effort expectancy, social influence, facilitating conditions and habit directly impact the older adults' intention to engage in mobile shopping. Additionally, facilitating conditions, habit and the older adults' intention to engage in mobile shopping act as driving factors for actual use behavior. This study further expands the UTAUT theoretical model, provides a theoretical basis for the research of mobile shopping behavior of the elderly, and enricues the application groups and fields of the UTAUT theoretical model. The results of this study provide inspiration for the development, design and marketing of age-appropriate mobile shopping products, and contribute to the realization and further adoption of age-appropriate mobile shopping, and also contribute to promoting the active aging of the elderly.

Factors affecting students' online courses learning behaviors.

Online course learning is an important part of higher education curriculum. However, the factors influencing college students' online course learning behavior are poorly understood. The purpose of this study is to analyze the factors affecting college students' online course learning behavior. This study integrated the Information System Success Model, the Technology Acceptance Model, and Self-efficacy Theory to construct an online course learning acceptance model. A total of 308 college students participated from China filled out the questionnaire, and 18 of them also participated in a semi-structured interview. The structural equation model was used to analyze the research data. The empirical analysis showed that self-efficacy has a positive impact on perceived usefulness and perceived ease-of-use; Perceived usefulness, attitude, system quality, and information quality affect users' behavioral intentions positively; Perceived ease of use has a positive effect on users' attitudes and perceived usefulness; and perceived usefulness has a direct effect on users' attitudes; Furthermore, behavioral intention can predict the actual use of online courses by college students. In addition, we will discuss these results and provide recommendations. This study provides a theoretical basis for the study of online course learning acceptance and extends the technology acceptance model. The research can provide inspiration for the design of online course learning and the decision-making of management institutions, and contribute to the sustainable development of education.

Psychological factors affecting potential users' intention to use autonomous vehicles.

As a currently emerging technology and an emerging intelligent mode of transport, autonomous vehicles (AVs) with lots of potential advantages need attention in terms of acceptability of their users. This research incorporates three psychological factors of perceived trust, perceived value, and perceived enjoyment into the technology acceptance model, and explores the influence of these factors on the potential use intention of AVs users. In this study, the questionnaire data from 232 participants were analysed, and the structural equation model test study model was adopted, and nine hypotheses proposed in this study were verified. The results show that perceived enjoyment, perceived trust, perceived usefulness, and attitude have a direct positive impact on users' usage intentions. Perceived value, perceived usefulness, and perceived ease of use have a direct positive impact on user attitudes. In addition, perceived ease of use has also been shown to directly affect perceived usefulness. This study constructs and demonstrates a model of autonomous vehicle acceptance. This model can be used for user acceptance research of unmanned vehicles. The research expands the theory of technology acceptance model and its applicable fields, and enriches the theory of user research on unmanned vehicles. This study provides predictors of AVs acceptance for AVs designers, automakers, automotive policy makers, and related practitioners. Help them make actionable autonomous vehicle-related decisions to promote high-acceptance autonomous vehicle design and user intent for autonomous vehicles.

Exploring the Chemical Space of CYP17A1 Inhibitors Using Cheminformatics and Machine Learning.

Cytochrome P450 17A1 (CYP17A1) is one of the key enzymes in steroidogenesis that produces dehydroepiandrosterone (DHEA) from cholesterol. Abnormal DHEA production may lead to the progression of severe diseases, such as prostatic and breast cancers. Thus, CYP17A1 is a druggable target for anti-cancer molecule development. In this study, cheminformatic analyses and quantitative structure-activity relationship (QSAR) modeling were applied on a set of 962 CYP17A1 inhibitors (i.e., consisting of 279 steroidal and 683 nonsteroidal inhibitors) compiled from the ChEMBL database. For steroidal inhibitors, a QSAR classification model built using the PubChem fingerprint along with the extra trees algorithm achieved the best performance, reflected by the accuracy values of 0.933, 0.818, and 0.833 for the training, cross-validation, and test sets, respectively. For nonsteroidal inhibitors, a systematic cheminformatic analysis was applied for exploring the chemical space, Murcko scaffolds, and structure-activity relationships (SARs) for visualizing distributions, patterns, and representative scaffolds for drug discoveries. Furthermore, seven total QSAR classification models were established based on the nonsteroidal scaffolds, and two activity cliff (AC) generators were identified. The best performing model out of these seven was model VIII, which is built upon the PubChem fingerprint along with the random forest algorithm. It achieved a robust accuracy across the training set, the cross-validation set, and the test set, i.e., 0.96, 0.92, and 0.913, respectively. It is anticipated that the results presented herein would be instrumental for further CYP17A1 inhibitor drug discovery efforts.

Camellia oil (Camellia oleifera Abel.) treatment improves high-fat diet-induced atherosclerosis in apolipoprotein E (ApoE)-/- mice.

Atherosclerosis is the main cause of cardiovascular diseases, and healthy dietary habits are a feasible strategy to prevent atherosclerosis development. Camellia oil, an edible plant oil, exhibits multiple beneficial cardiovascular effects. Our previous study showed that oral administration of camellia oil attenuated hyperglycemia, fat deposits in the liver, and the atherosclerosis index in high-fat diet (HFD)-induced obese mice. Here, an atherosclerosis model of apolipoprotein E (ApoE)-/- mice induced by HFD was used to study the effect of camellia oil on atherosclerosis, and 16S rRNA gene sequencing was used to analyze the changes in gut microbiota composition. The results showed that camellia oil significantly inhibited the formation of atherosclerotic plaques in ApoE-/- mice, which were characterized by significantly reduced levels of serum total cholesterol and enhanced levels of serum high-density lipoprotein cholesterol. The aortic levels of interleukin-6 and tumor necrosis factor were decreased. The results of the 16S rRNA analysis showed that after camellia oil interventions, the intestinal flora of ApoE-/- mice changed significantly, with the diversity of intestinal flora especially increasing, the relative abundances of Bacteroides, Faecalibaculum, Bilophila, and Leuconostoc increasing, and the Firmicutes/Bacteroidetes ratio and Firmicutes abundance decreasing. Collectively, our findings confirmed the promising value of camellia oil in preventing the development of atherosclerosis in ApoE-/- mice. Mechanistically, this preventive effect of camellia oil was probably due to its lipid-lowering activity, anti-inflammatory effects, and alteration of the gut microbiota composition in the mice.

On the force field optimisation of [Formula: see text]-lactam cores using the force field Toolkit.

When employing molecular dynamics (MD) simulations for computer-aided drug design, the quality of the used force fields is highly important. Here we present reparametrisations of the force fields for the core molecules from 9 different [Formula: see text]-lactam classes, for which we utilized the force field Toolkit and Gaussian calculations. We focus on the parametrisation of the dihedral angles, with the goal of reproducing the optimised quantum geometry in MD simulations. Parameters taken from CGenFF turn out to be a good initial guess for the multiplicity of each dihedral angle, but the key to a successful parametrisation is found to lie in the phase shifts. Based on the optimised quantum geometry, we come up with a strategy for predicting the phase shifts prior to the dihedral potential fitting. This allows us to successfully parameterise 8 out of the 11 molecules studied here, while the remaining 3 molecules can also be parameterised with small adjustments. Our work highlights the importance of predicting the dihedral phase shifts in the ligand parametrisation protocol, and provides a simple yet valuable strategy for improving the process of parameterising force fields of drug-like molecules.

Research on the use intention of potential designers of unmanned cars based on technology acceptance model.

The success of unmanned car, an emerging tool of transportation with so many advantages, depends to a large extent on its user acceptability. Potential designers are both the decision makers of driverless car design and the users of driverless cars. This study aims to explore the influencing factors of the potential designers' intention to use unmanned cars. Based on the theory of Technology Acceptance Model (TAM), this study further expanded the TAM by incorporating perceived trust, perceived enjoyment and self-efficacy, so as to explain and predict potential designers' intention to use unmanned cars. The questionnaire is determined through theoretical literature, pre-tests, etc., and the Structural Equation Model is used to analyze the data of 202 valid survey samples to investigate the influencing factors of the willingness to use unmanned vehicles. The results show that potential designers' intention to use unmanned cars is positively affected by perceived trust, perceived enjoyment, perceived usefulness and perceived ease of use, and perceived trust has a positive effect on perceived ease of use, self-efficacy and perceived ease of use also have a positive effect on perceived usefulness. The findings of this study can provide designers and developers of unmanned cars, policy makers and implementers with guidance in the follow-up design, policy formulation and advertising of unmanned cars.

Oral administration of camellia oil ameliorates obesity and modifies the gut microbiota composition in mice fed a high-fat diet.

Obesity, which is often caused by adipocyte metabolism dysfunction, is rapidly becoming a serious global health issue. Studies in the literature have shown that camellia oil (Camellia oleifera Abel) exerted potential lipid regulation and other multiple biological activities. Here, we aimed to investigate the effects of camellia oil on obese mice induced by a high-fat diet and to explore gut microbiota alterations after camellia oil intervention. The results showed that oral administration of camellia oil dramatically attenuated the fat deposits, serum levels of the total cholesterol, triacylglycerol, low-density lipoprotein cholesterol, fasting plasma glucose, the atherosclerosis index, the hepatic steatosis and inflammation in high-fat diet-induced obese mice. Meanwhile, the high-density lipoprotein cholesterol level in obese mice was enhanced after the camellia oil treatment. Furthermore, 16S rRNA analysis showed that certain aspects of the gut microbiota, especially the gut microbiota diversity and the relative abundance of Actinobacteria, Coriobacteriaceae, Lactobacillus and Anoxybacillus, were significantly increased by camellia oil treatment while the ratio of Firmicutes to Bacteroidetes was decreased. Taken together, our finding suggested that camellia oil was a potential dietary supplement and functional food for ameliorating fat deposits, hyperglycemia and fatty liver, probably by modifying the gut microbiota composition.

Attitudes of the elderly living independently towards the use of robots to assist with activities of daily living.

BACKGROUND: Robots are gaining attention as a potential solution to aging. OBJECTIVE: The purpose of this study is to explore the attitude of robot assistance in Activities of Daily Living (ADLs) among elderly people living independently. METHODS: The one-on-one interview, buddy robot video and questionnaire survey were used to analyze mean, median, range, and the test results of non-parametric statistical methods such as Wilcoxon sign-rank test statistic and one-sample Wilcoxon sign-rank test statistic, so as to explore the attitude of the elderly living independently towards robot-assisted ADLs and the acceptance of the use of robots in 32 ADLs. RESULTS: The results showed that there were significant differences in the attitudes, usability and ease of use of elderly people towards robot assistance before and after watching the Buddy Robot video and they had a more positive attitude after watching the video. According to the results, the elderly was more receptive to the use of robots in activities such as "reminding to carry objects" and "reminding to take medicine", while they were less receptive to the use of robots in the group or private activities such as "playing mahjong" and "taking a bath". CONCLUSIONS: The results showed that the elderly had a positive attitude towards the use of robot-assisted ADLs, and there were differences in the acceptance of robot-assisted ADLs. The results are helpful to understand the assistance needs and attitudes of the elderly, and provide a reference for the design of assistive robots that meet user needs, and ultimately improve the ability of the elderly to live independently at home.

ß-Glucan ameliorates nonalcoholic steatohepatitis induced by methionine and choline-deficient diet in mice.

Nonalcoholic steatohepatitis (NASH) is becoming a huge global health problem. Studies showed that ß-glucan displayed potent anti-inflammatory and other multi-beneficial pharmacological properties. Thus, the objective of this study was to investigate the effects of ß-glucan on NASH mice induced by the MCD diet. After 8 weeks of ß-glucan treatments, results showed that ß-glucan effectively decreased the serum ALT and AST levels compared with the MCD model. Besides, histopathological results demonstrated that ß-glucan significantly attenuated the fat accumulation, steatosis, and inflammation in the liver compared with that of the MCD group. Furthermore, the ER stress-responsive proteins, including GRP78, p-eiF-2α, and p-JNK, were markedly restrained by ß-glucan, while ERp57, p-MAPK, and p-Akt were significantly increased after ß-glucan treatment. Collectively, our results suggested that ß-glucan beneficially resisted NASH induced by the MCD diet. The ER stress response may be involved in the mechanisms of action of ß-glucan. PRACTICAL APPLICATIONS: This study is the first to report the hepatoprotective activity of ß-glucan against MCD diet-induced NASH in mice, mainly reflecting its ability to ameliorate hepatic lipid accumulation and inflammation, with the mechanism possibly involving mediating the ER stress signaling pathway. Our results suggest that the ß-glucan has good application prospects to be used as a raw material in functional foods for the clinical treatment of NASH.

Potential targets for intervention against doxorubicin-induced cardiotoxicity based on genetic studies: a systematic review of the literature.

Cardiotoxicity is a well-known adverse effect of doxorubicin (Dox) administration, but the underlying molecular mechanism of this effect is not fully understood. Over the past two decades, considerable efforts have focused on the potential molecular targets of cardiotoxicity in the hope that novel targeted therapies will be generated to attenuate Dox-induced cardiotoxicity. Here, we provide a comprehensive overview of genetically modified animals that show enhanced or reduced susceptibility to the cardiotoxic effects of Dox. We focused on the process by which the molecules involved in DNA damage, oxidative stress, apoptosis, autophagy and necrosis are affected in the presence of Dox. We also present a protein-protein interaction network and explain the contribution of the components to the process of Dox-induced cardiotoxicity. More importantly, data from the literature have indicated that PI3Kγ and Rac1 are potential targets with therapeutic advantages in cancer therapy; molecules that target these proteins can simultaneously attenuate Dox-induced cardiotoxicity and enhance its anticancer activity. This review highlights the potential molecular targets that are critical regulators involved in Dox-mediated cardiotoxicity, thus providing further insight into the development of potential treatment strategies to prevent the cardiotoxic effects and enhance the anticancer efficiency of Dox in cancer patients.