Theoretical description of a four-level system for luminescent thermometry was proposed. Based on this description, the sensitivity was proved not to exceed Sr =|E23 – E12|/T2, where T is the temperature and |E23 – E12| is the absolute energy difference between the excited state energy gaps. The analysis was verified for the terbium-europium coordination compounds, the most studied class of four-level thermometry systems, which revealed that most of the examples fall within either this theory or represent three-level systems, where the ligand is not involved in the thermally-activated processes. From this description, it follows that the highest Sr can be reached either when the triplet state is not involved or when the ligand triplet state is very high, which in the case of terbium-europium coordination compounds means exceeding 26 800 cm-1.Correction for ‘X-ray pair distribution function analysis and electrical and electrochemical properties of cerium doped Li5La3Nb2O12 garnet solid-state electrolyte’ by Bo Dong et al., Dalton Trans., 2020, 49, 11727-11735, DOI 10.1039/d0dt02112a.

RNA viruses exhibit an extraordinary ability to evolve in a changing environment and to switch from animal hosts to humans. The ongoing COVID-19 pandemic, recognized as a respiratory disease, is an example of zoonotic transmission of the RNA virus known as SARS-CoV-2. CORT125134 The development and regulatory approval of a vaccine against SARS-CoV-2 pose multiple preventive and therapeutic challenges, especially during an ongoing pandemic.

The review intended to examine the challenges and recent achievements in the development of vaccine candidates against COVID-19.

The research team performed a literature review, searching relevant and up to date information from the literature. The sources of data included Google Scholar, PubMed, NCBI, and Yahoo. The search terms used were COVID-19 challenges, SARS-CoV-2 prospective challenges, RNA viruses adoptability, host switching by RNA viruses, COVID-19 vaccines.

The study took place at the digital libraries of contributing institutions. The data was combined, selected fvelopment and approval of efficacious and safe vaccines is key to the effort to provide preventive measures against COVID-19 and future viruses. However, the development and availability of a vaccine candidate is a time-consuming process and often can’t be completed during an epidemic. Currently, several types of vaccines are under development, and most of them won’t realistically be available in time for the present COVID-19 pandemic.In contrast with medical imaging diagnostics powered by artificial intelligence (AI), in which deep learning has led to breakthroughs in recent years, patient outcome prediction poses an inherently challenging problem because it focuses on events that have not yet occurred. Interestingly, the performance of machine learning-based patient outcome prediction models has rarely been compared with that of human clinicians in the literature. Human intuition and insight may be sources of underused predictive information that AI will not be able to identify in electronic data. Both human and AI predictions should be investigated together with the aim of achieving a human-AI symbiosis that synergistically and complementarily combines AI with the predictive abilities of clinicians.

With the dramatic development of Web 2.0, increasing numbers of patients and physicians are actively involved in online health communities. Despite extensive research on online health communities, the conversion rate from visitor to customer and its driving factors have not been discussed.

The aim of this study was to analyze the conversion rate of online health communities and to explore the effects of multisource online health community information, including physician-generated information, patient-generated information, and system-generated information.

An empirical study was conducted to examine the effects of physician-generated, patient-generated, and system-generated information on the conversion rate of physicians’ personal websites by analyzing short panel data from 2112 physicians over five time periods in a Chinese online health community.

Multisource online health community information (ie, physician-generated, patient-generated, and system-generated information) positively affected the cf online health communities.

Most children and adolescents diagnosed with cancer become long-term survivors. For most of them, regular follow-up examinations to detect and treat late effects are necessary, especially in adulthood. The transition from pediatric to adult-focused follow-up care is a critical moment for childhood cancer survivors (CCSs); a substantial proportion of CCSs are lost to follow-up in this transition process and do not attend follow-up care in adulthood. This can have serious effects on survivors’ health if late effects are not discovered in a timely fashion.

In this study, we primarily assess the current follow-up situation, related needs, and knowledge of adolescent and young adult CCSs who have transitioned from pediatric to adult-focused follow-up care. As secondary objectives, we evaluate transition readiness, identify facilitating factors of transition and adherence to long-term follow-up (LTFU) care, and compare three different transition models.

The Aftercare of Childhood Cancer Survivors (ACCS) Switzerland study is a prospective, multicenter, observational study that was approved by the ethics committee in February 2019. We are recruiting CCSs from three pediatric oncology centers and using questionnaires to answer the study questions.

To date, we have recruited 58 participants. The study is ongoing, and recruitment of participants will continue until January 2021.

The ACCS study will provide information on CCSs’ preferences and expectations for follow-up care and their transition into the adult setting. The results will help improve the LTFU care and cancer knowledge of CCSs and subsequently enhance adherence to follow-up care and reduce loss to follow-up in adulthood.

ClinicalTrials.gov NCT04284189; https//clinicaltrials.gov/ct2/show/NCT04284189?id=NCT04284189.

PRR1-10.2196/18898.

PRR1-10.2196/18898.