ABSTRACT
IntroductionDemand for digital mental health tools has risen since the start of the COVID-19 pandemic;however, their evolving use in mental health care is not well understood. We surveyed mental health care professionals (HCPs) before and after the onset of the pandemic and assessed how use of and attitudes about digital technology changed.MethodsWe distributed a digital health survey to HCPs in the United States in 2019 (pre-pandemic;N = 141) and in 2021 (during the pandemic;N = 151). Both surveys recorded the respondents' perceived barriers to integrating new digital health technologies and the tools they currently used in their practice.ResultsHCP use of telemedicine increased from 47% of respondents in 2019 to 81% in 2021, as did the use of mHealth sensors (2% vs 10%). Patient comfort with technology remained one of the biggest barriers to implementing new digital tools (40% vs 43%), while difficulty integrating digital tools into clinical practice became less common (40% vs 32%). Data management (19% vs 10%) and patient acceptability (19% vs 13%) were cited less often as barriers in 2021. Respondents' thoughts on what can be most improved by digital technology shifted substantially, with increased access to care rising from 27% of responses in 2019 to 46% in 2021.ConclusionsThe pandemic has changed how HCPs perceive digital health technologies and how they implement these tools in clinical practice. A growing number of HCPs believe increased access to care is the outcome that technology can most improve.FundingOtsuka Pharmaceutical Development & Commercialization, Inc., Princeton, NJ, USA
ABSTRACT
This research identifies the optimum supervised classification algorithm based on modeling Covid 19 lockdown situations all around the World. As the deadly Covid 19 viruses suddenly stopped the fast-moving World. All the commercial and noncommercial activities suddenly stop for an uncertain period during 2020-2021. In this work, object-based image classification approaches have been used to compare pre-Covid and post-Covid (at the time lockdown) images of the study area. These study areas are Washington DC, USA, Sao Paulo, Brazil, Cairo, Egypt, Afghanistan/Iran border, and Beijing, China. All the study areas possess different geographical conditions but have a similar situation of Covid 19 lockdowns. Six supervised image classification techniques are known as Parallelepiped classification (PPC), Minimum distance classification (MDC), Mahalanobis distance classification (MaDC), Maximum likelihood classification (MLC), Spectral angle mapper classification (SAMC) and Spectral information divergence classification (SIDC) are used to classify the satellite data of the study area. Thus based on classification results and statistical features, it has been observed that PPChas obtained the least significant results. In contrast, the most reliable results and highest classification accuracies are obtained through MDC, MaDC, and MLCclassification algorithms.
ABSTRACT
Periodontal diseases are caused mainly by inflammation of the gums and bones surrounding the teeth or by dysbiosis of the oral microbiome, and the Global Burden of Disease study (2019) reported that periodontal disease affects 20–50% of the global population. In recent years, more preference has been given to natural therapies compared to synthetic drugs in the treatment of periodontal disease, and several oral care products, such as toothpaste, mouthwash, and dentifrices, have been developed comprising honeybee products, such as propolis, honey, royal jelly, and purified bee venom. In this study, we systematically reviewed the literature on the treatment of periodontitis using honeybee products. A literature search was performed using various databases, including PubMed, Web of Science, ScienceDirect, Scopus, clinicaltrials.gov, and Google Scholar. A total of 31 studies were reviewed using eligibility criteria published between January 2016 and December 2021. In vitro, in vivo, and clinical studies (randomized clinical trials) were included. Based on the results of these studies, honeybee products, such as propolis and purified bee venom, were concluded to be effective and safe for use in the treatment of periodontitis mainly due to their antimicrobial and anti-inflammatory activities. However, to obtain reliable results from randomized clinical trials assessing the effectiveness of honeybee products in periodontal treatment with long-term follow-up, a broader sample size and assessment of various clinical parameters are needed.
ABSTRACT
COVID-19 pandemic has accounted for ~ 4.3 million confirmed cases and ~ 292,000 deaths (till 12th May, 2020) across the globe since its outbreak. Several anti-viral drugs such as RNA dependent RNA polymerase inhibitors (remdesivir, favipiravir, ribavirin), protease inhibitors (lopinavir, ritonavir) and drugs targeting endocytic pathway (hydroxychloroquine) are being evaluated for COVID-19 but standard therapeutics yet not available. Severe health deterioration in critically ill patients is characterized by pulmonary edema, severe respiratory distress, cytokine storm and septic shock. To combat cytokine storm, immune-therapy targeting IL-1, IL-2, IL-6 and TNFα are being evaluated and one of the promising immune-modulator is the mesenchymal stem cells (MSCs) that can surmount the severity of COVID-19 infections. Recent studies have shown that MSC-therapy significantly dampens the cytokine storm in critically ill COVID-19 patients. This communication endows with the insight of stem cell therapy and summarizes the recent studies on COVID-19 patients.