Search

BackgroundThe high prevalence of COVID-19 has resulted in 200,000 deaths as of early 2020. The corresponding mortality rate among different countries and times varies. ObjectiveThis study aims to investigate the relationship between the mortality rate and prevalence of COVID-19 within a country. MethodsWe collected data from the Johns Hopkins Coronavirus Resource Center. These data included the daily cumulative death count, recovered count, and confirmed count for each country. This study focused on a total of 36 countries with over 10,000 confirmed COVID-19 cases. Mortality was the main outcome and dependent variable, and it was computed by dividing the number of COVID-19 deaths by the number of confirmed cases. ResultsThe results of our global panel regression analysis showed that there was a highly significant correlation between prevalence and mortality (ρ=0.8304; P

BackgroundA mobile app generates passive data, such as GPS data traces, without any direct involvement from the user. These passive data have transformed the manner of traditional assessments that require active participation from the user. Passive data collection is one of the most important core techniques for mobile health development because it may promote user retention, which is a unique characteristic of a software medical device. ObjectiveThe primary aim of this study was to quantify user retention for the “Staff Hours” app using survival analysis. The secondary aim was to compare user retention between passive data and active data, as well as factors associated with the survival rates of user retention. MethodsWe developed an app called “Staff Hours” to automatically calculate users’ work hours through GPS data (passive data). “Staff Hours” not only continuously collects these passive data but also sends an 11-item mental health survey to users monthly (active data). We applied survival analysis to compare user retention in the collection of passive and active data among 342 office workers from the “Staff Hours” database. We also compared user retention on Android and iOS platforms and examined the moderators of user retention. ResultsA total of 342 volunteers (224 men; mean age 33.8 years, SD 7.0 years) were included in this study. Passive data had higher user retention than active data (P=.011). In addition, user retention for passive data collected via Android devices was higher than that for iOS devices (P=.015). Trainee physicians had higher user retention for the collection of active data than trainees from other occupations, whereas no significant differences between these two groups were observed for the collection of passive data (P=.700). ConclusionsOur findings demonstrated that passive data collected via Android devices had the best user retention for this app that records GPS-based work hours.

BackgroundAssessing human behaviors via smartphone for monitoring the pattern of daily behaviors has become a crucial issue in this century. Thus, a more accurate and structured methodology is needed for smartphone use research. ObjectiveThe study aimed to investigate the duration of data collection needed to establish a reliable pattern of use, how long a smartphone use cycle could perpetuate by assessing maximum time intervals between 2 smartphone periods, and to validate smartphone use and use/nonuse reciprocity parameters. MethodsUsing the Know Addiction database, we selected 33 participants and passively recorded their smartphone usage patterns for at least 8 weeks. We generated 4 parameters on the basis of smartphone use episodes, including total use frequency, total use duration, proactive use frequency, and proactive use duration. A total of 3 additional parameters (root mean square of successive differences, Control Index, and Similarity Index) were calculated to reflect impaired control and compulsive use. ResultsOur findings included (1) proactive use duration correlated with subjective smartphone addiction scores, (2) a 2-week period of data collection is required to infer a 2-month period of smartphone use, and (3) smartphone use cycles with a time gap of 4 weeks between them are highly likely independent cycles. ConclusionsThis study validated temporal stability for smartphone use patterns recorded by a mobile app. The results may provide researchers an opportunity to investigate human behaviors with more structured methods.

Abstract Background Gastric precancerous lesions are a critical stage in the development of gastric cancer or gastric adenocarcinoma, and their outcome plays an important role in the malignant progression of gastric cancer. Coptidis Rhizoma has a good effect on Gastric precancerous lesions. However, the specific mechanisms of its action remain incompletely elucidated. Methods Network pharmacology and molecular docking techniques were used to explore the active ingredients and molecular mechanism of Coptidis Rhizoma in treating gastric precancerous lesions. The active compounds of Coptidis Rhizoma and their potential gastric precancerous lesions related targets were obtained from TCMSP, GeneCards, and OMIM databases. An interaction network based on protein–protein interactions (PPIs) was constructed to visualize the interactions between hub genes. Analysis of GO enrichment and KEGG pathway were conducted using the DAVID database. An investigation of interactions between active compounds and potential targets was carried out by molecular docking. Finally, animal experiments were conducted to verify the effect and mechanism of Coptidis Rhizoma in treating precancerous lesions of gastric cancer. Results A total of 11 active compounds and 95 anti-gastric precancerous lesions targets of Coptidis Rhizoma were screened for analysis. GO enrichment analysis showed that the mechanism of Coptidis Rhizoma acting on gastric precancerous lesions involves gene expression regulation and apoptosis regulation. KEGG pathway enrichment analysis showed that Coptidis Rhizoma against gastric precancerous lesions involving the AKT /HIF-1α/VEGF signalling pathway. Molecular docking simulations indicated potential interactions between these compounds and core targets involved in anti-gastric precancerous lesions activity. In addition, it was confirmed in vivo that Berberine and Coptidis Rhizoma may reverse atrophy and potential intestinal metaplasia by inhibiting the expression of p-AKT, HIFA, and VEGF. Conclusion Bioactive compounds in Coptidis Rhizoma have the potential to prevent atrophy and intestinal metaplasia. These compounds function by regulating the proteins implicated in AKT /HIF-1α/VEGF signalling pathways that are crucial in gastric epithelial cell differentiation, proliferation and maturation.

Abstract The oxidative dehydrogenation of propane, primarily sourced from shale gas, holds promise in meeting the surging global demand for propylene. However, this process necessitates high operating temperatures, which amplifies safety concerns in its application due to the use of mixed propane and oxygen. Moreover, these elevated temperatures may heighten the risk of overoxidation, leading to carbon dioxide formation. Here we introduce a microchannel reaction system designed for the oxidative dehydrogenation of propane within an aqueous environment, enabling highly selective and active propylene production at room temperature and ambient pressure with mitigated safety risks. A propylene selectivity of over 92% and production rate of 19.57 mmol mCu −2 h−1 are simultaneously achieved. This exceptional performance stems from the in situ creation of a highly active, oxygen-containing Cu catalytic surface for propane activation, and the enhanced propane transfer via an enlarged gas-liquid interfacial area and a reduced diffusion path by establishing a gas-liquid Taylor flow using a custom-made T-junction microdevice. This microchannel reaction system offers an appealing approach to accelerate gas-liquid-solid reactions limited by the solubility of gaseous reactant.