Molecular Characterization of Severe Acute Respiratory Syndrome Coronavirus 2 Isolates From Central Inner Sardinia

BackgroundThe SARS-CoV-2 pandemic stimulated an outstanding global sequencing effort, which allowed to monitor viral circulation and evolution. Nuoro province (Sardinia, Italy), characterized by a relatively isolated geographical location and a low population density, was severely hit and displayed a high incidence of infection.MethodsAmplicon approach Next Generation Sequencing and subsequent variant calling in 92 respiratory samples from SARS-CoV-2 infected patients involved in infection clusters from March 2020 to May 2021.ResultsPhylogenetic analysis displayed a coherent distribution of sequences in terms of lineage and temporal evolution of pandemic. Circulating lineage/clade characterization highlighted a growing diversity over time, with an increasingly growing number of mutations and variability of spike and nucleocapsid proteins, while viral RdRp appeared to be more conserved. A total of 384 different mutations were detected, of which 196 were missense and 147 synonymous ones. Mapping mutations along the viral genome showed an irregular distribution in key genes. S gene was the most mutated gene with missense and synonymous variants frequencies of 58.8 and 23.5%, respectively. Mutation rates were similar for the S and N genes with one mutation every ∼788 nucleotides and every ∼712 nucleotides, respectively. Nsp12 gene appeared to be more conserved, with one mutation every ∼1,270 nucleotides. The frequency of variant Y144F in the spike protein deviated from global values with higher prevalence of this mutation in the island.ConclusionThe analysis of the 92 viral genome highlighted evolution over time and identified which mutations are more widespread than others. The high number of sequences also permits the identification of subclusters that are characterized by subtle differences, not only in terms of lineage, which may be used to reconstruct transmission clusters. The disclosure of viral genetic diversity and timely identification of new variants is a useful tool to guide public health intervention measures.

The impact of invisible-spreaders on COVID-19 transmission and work resumption

The global impact of coronavirus disease 2019 (COVID-19) is unprecedented, and many control and prevention measures have been implemented to test for and trace COVID-19. However, invisible-spreaders, who are associated with nucleic acid detection and asymptomatic infections, have received insufficient attention in the current COVID-19 control efforts. In this paper, we analyze the time series infection data for Italy, Germany, Brazil, India and Sweden since the first wave outbreak to address the following issues through a series of experiments. We conclude that: 1) As of June 1, 2020, the proportion of invisible-spreaders is close to 0.4% in Sweden, 0.8% in early Italy and Germany, and 0.4% in the middle and late stages. However, in Brazil and India, the proportion still shows a gradual upward trend; 2) During the spread of this pandemic, even a slight increase in the proportion of invisible-spreaders could have large implications for the health of the community; and 3) On resuming work, the pandemic intervention measures will be relaxed, and invisible-spreaders will cause a new round of outbreaks.

Integration of fuzzy logic in the SEIRD compartmental model for the analysis of intervention and transmission heterogeneity on SARS-CoV-2 transmission dynamics

Different epidemiological compartmental models have been presented to predict the transmission dynamics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we have proposed a fuzzy rule-based Susceptible-Exposed-Infectious-Recovered-Death ([Formula: see text]) compartmental model considering a new dynamic transmission possibility variable as a function of time and three different fuzzy linguistic intervention variables to delineate the intervention and transmission heterogeneity on SARS-CoV-2 viral infection. We have analyzed the datasets of active cases and total death cases of China and Bangladesh. Using our model, we have predicted active cases and total death cases for China and Bangladesh. We further presented the correspondence of different intervention measures in relaxing the transmission possibility. The proposed model delineates the correspondence between the intervention measures as fuzzy subsets and the predicted active cases and total death cases. The prediction made by our system fitted the collected dataset very well while considering different fuzzy intervention measures. The integration of fuzzy logic in the classical compartmental model also produces more realistic results as it generates a dynamic transmission possibility variable. The proposed model could be used to control the transmission of SARS-CoV-2 as it deals with the intervention and transmission heterogeneity on SARS-CoV-2 transmission dynamics.

Shaoyao Gancao Decoction for limb dysfunction after fractures around the knee: A protocol for systematic review

Review question / Objective: This study aimed to evaluate the effects of SGD on patients with limb dysfunction from the perspectives of pain, limb edema, stiffness, as well as physical dysfunction. Study designs to be included: This review only includes the intervention measures of SGD, including trials comparing SGD with standard treatment and/ or placebo. Trials of SGD combined with other therapies will be included.

The Effect of Artemisinin-Based Drugs vs Non-artemisinin-based Drugs on Gametophyte Carrying in the Body After the Treatment of Uncomplicated Falciparum Malaria: A Systematic Review and Meta-analysis

The WHO recommends Artemisinin-based combination therapy (ACTs) as the first-line treatment for malaria. This meta-analysis aims to analyze the effects of artemisinin and its derivatives as well as non-artemisinin drugs on the gametophytes in the host during the treatment of falciparum malaria. Fourteen studies were included in this analysis, and the artemisinin combination drugs involved were: artemether-lumefantrine (AL), artemisinin (AST), artemether-benflumetol (AB), dihydroartemisinin-piperaquine + trimethoprim + primaquine (CV8), amodiaquine + sulfadoxine-pyrimethamine (ASP), pyronaridine-phosphate + dihydroartemisinin (PP-DHA), dihydroartemisinin (DHA), and mefloquine + artesunate (MA), with 1702 patients. The control intervention measures involved the following: sulfadoxine-pyrimethamine (SP), mefloquine (MQ), atovaquone-proguanil (AT-PG), chloroquine + sulfadoxine-pyrimethamine (C-SP), quinine (Q), pyronaridine-phosphate (PP), pyronaridine (PN), and mefloquine + primaquine (MP), with 833 patients. The effect of ACTs was more obvious (OR = 0.37, 95%CI: 0.22–0.62, p < 0.05). In the control group of second malaria attacks, the difference between the two groups was not statistically significant (RD = 1.16, 95%CI: 0.81–1.66, p < 0.05); there was no significant difference in treatment failure during follow-up (RD = -0.01, 95%CI: 0.04–0.03, p < 0.05). There were also very few serious adverse events in both groups. ACTs showed good therapeutic effects in preventing gametocythemia but did not control the recrudescence rate and overall cure, which indicated the effectiveness of the combination of antimalarial drugs. Further research is required to explore which compatibility method is most conducive to the development of clinical malaria control.

Study on the correlation between PPARγ, Aβ1-42, miR-155 and the occurrence and development of diabetes

The objective of this research was to study the correlation between PPARγ, Aβ1-42, miR-155 and the occurrence and development of diabetes. For this purpose, 52 patients with diabetes who were hospitalized from September 2019 to May 2021 were selected as the research objects. They were grouped according to the severity of the disease, which was pre-diabetes (n=16), mild (n=25), and moderate (n=16). =11), another 20 healthy subjects were taken as the control group, and the levels of PPARγ, Aβ1-42, miR-155 in each group were measured, and the correlation between changes in the levels of various indicators and the occurrence and development of diabetes was explored. Results showed that comparison of age, gender, course of disease, BMI, living habits, comorbidities, and high-density lipoprotein among the groups of diabetic patients (P>0.05); the levels of total cholesterol, triglycerides and low-density cholesterol decreased with the development of diabetes (P<0.05) ); Compared with the healthy group, the levels of PPARγ and miR-155 were significantly reduced, and the levels of Aβ1-42 were significantly increased (P<0.05); compared with the prediabetes, the levels of mild and moderate PPARγ and miR-155 showed a downward trend, and Aβ1 -42 level showed an upward trend (P<0.05); PPARγ and miR-155 levels were negatively correlated with pre-diabetes, mild, and moderate; Aβ1-42 was positively correlated with pre-diabetes, mild, and moderate (P<0.05) ; PPARγ, Aβ1-42, miR-155 levels can effectively predict the occurrence and development of diabetes, and the sensitivity, specificity and accuracy of the detection of diabetes by various indicators, positive predictive value and negative predictive value are significantly higher. It is concluded that PPARγ, Aβ1-42, miR-155 are closely related to the occurrence and development of diabetes, and there are many influencing factors of diabetes. Clinical intervention measures can be taken according to specific conditions.

A Comprehensive Analysis of E-Health Literacy Research Focuses and Trends

Objective: To sort out the research focuses in the field of e-health literacy, analyze its research topics and development trends, and provide a reference for relevant research in this field in the future. Methods: The literature search yielded a total of 431 articles retrieved from the core dataset of Web of Science using the keywords “ehealth literacy”, “E-health literacy” and “electronic health literacy”. A bibliometric analysis was performed by using CiteSpace to explore the development history, hot themes, and trends of future research in the field of e-health literacy. Results: The thematic evolution path in e-health literacy was divided into three stages. The research focuses were inspected from four aspects: evaluation, correlation with health-promotion behaviors, influencing factors, and intervention measures for improvement. Conclusion: E-health literacy research faces challenges such as the development of the connotation of the term, the objectivity of evaluation methods, and the long-term impact of interventions. Future research themes in e-health literacy will include the standardization of evaluation instruments and the individualization of therapeutic strategies.