How fast and how well the Omicron epidemic was curtailed. A Guangzhou experience to share.

Introduction: SARS-CoV-2 has ravaged the world and undergone multiple mutations during the course of the COVID-19 pandemic. On 7 April 2022, an epidemic caused by SARS-CoV-2 Omicron (BA.2) variant broke out in Guangzhou, China, one of the largest transportation and logistical hubs of the country. Methods: To fast curtained the Omicron epidemic, based on the routine surveillance on the risk population of SARS-CoV-2 infection, we identify key places of the epidemic and implement enhanced control measures against Omicron. Results: Transmission characteristics of the Omicron variant were analyzed for 273 confirmed cases, and key places involved in this epidemic were fully presented. The median incubation time and the generation time were 3 days, and the reproduction number Rt was sharply increased with a peak of 4.20 within 2 days. We tried an all-out effort to tackle the epidemic in key places, and the proportion of confirmed cases increased from 61.17% at Stage 2 to 88.89% at Stage 4. Through delimited risk area management, 99 cases were found, and the cases were isolated in advance for 2.61 ± 2.76 days in a lockdown zone, 0.44 ± 1.08 days in a controlled zone, and 0.27 ± 0.62 days in a precautionary zone. People assigned with yellow code accounted for 30.32% (84/277) of confirmed COVID-19 cases, and 83.33% of them were detected positive over 3 days since code assignment. For the districts outside the epicenter, the implementation duration of NPIs was much shorter compared with the Delta epidemic last year. Conclusion: By blocking out transmission risks and adjusting measures to local epidemic conditions through the all-out effort to tackle the epidemic in key places, by delimiting risk area management, and by conducting health code management of the at-risk population, the Omicron epidemic could be contained quickly.

Everestmab, a novel long-acting GLP-1/anti GLP-1R nanobody fusion protein, exerts potent anti-diabetic effects.

In the present study, a novel single domain antibody (sdAb) fusion protein, named everestmab, composing of a mutated GLP-1(A8G) fused to the tandem bispecific humanized GLP-1R-targeting and albumin-binding nanobodies was designed and characterized for the therapies for type 2 diabetes mellitus (T2DM). Surface plasmon resonance (SPR) measurements demonstrated everestmab associates with serum albumins of rat and monkey species with high affinity, and tends to be cross-reactive with rat and monkey species. In vitro GLP-1R binding and activation assays revealed that everestmab can specifically activate the GLP-1R, and the antagonist exendin-4 (9-39) did not inhibit the activation yet. In vivo multiple oral glucose tolerance tests (OGTTs) and hypoglycaemic efficacy tests proved that a single injection of everestmab reduced the blood glucose for at least 144 h in Goto-Kakizaki (GK) rats. The plasma half-lives of 4.1 and 7.8 days were observed after a single s.c. administration of everestmab in SD rats and cynomolgus monkeys, respectively. Chronic treatment of everestmab to GK and diet induced obese (DIO) rats achieved beneficial effects on weight reducing, HbA1c lowering, glucose tolerance, liver and pancreas islet function impairment. In summary, everestmab is a unique G-protein-coupled receptor-targeted nanobody fusion protein and exerts potential as a therapeutic treatment for T2DM.

Applying analytic hierarchy process to assess healthcare-oriented cloud computing service systems.

Numerous differences exist between the healthcare industry and other industries. Difficulties in the business operation of the healthcare industry have continually increased because of the volatility and importance of health care, changes to and requirements of health insurance policies, and the statuses of healthcare providers, which are typically considered not-for-profit organizations. Moreover, because of the financial risks associated with constant changes in healthcare payment methods and constantly evolving information technology, healthcare organizations must continually adjust their business operation objectives; therefore, cloud computing presents both a challenge and an opportunity. As a response to aging populations and the prevalence of the Internet in fast-paced contemporary societies, cloud computing can be used to facilitate the task of balancing the quality and costs of health care. To evaluate cloud computing service systems for use in health care, providing decision makers with a comprehensive assessment method for prioritizing decision-making factors is highly beneficial. Hence, this study applied the analytic hierarchy process, compared items related to cloud computing and health care, executed a questionnaire survey, and then classified the critical factors influencing healthcare cloud computing service systems on the basis of statistical analyses of the questionnaire results. The results indicate that the primary factor affecting the design or implementation of optimal cloud computing healthcare service systems is cost effectiveness, with the secondary factors being practical considerations such as software design and system architecture.