Assessment of Respiratory Viral Co-infections Among SARS-CoV-2-Infected Patients

Introduction: Emerging evidence suggests that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients are at an increased risk for co-infections. The aim of this study was to assess the prevalence of respiratory viral co-infections among SARS-CoV-2 patients via molecular testing. Materials and Methods: Nasopharyngeal swabs of 68 SARS-CoV-2 positive cases detected between December 1, 2020 and December 20, 2021 were subjected to nucleic acid isolation and screening using molecular techniques. Real-time-qPCR analysis was performed using the FTD Respiratory Pathogens 21 Panel Kit. Positive results were further confirmed by QIAstat-Dx™ Respiratory Panel. Results: Co-infections were detected in 7.4% (n= 5/68) of SARS-CoV-2-infected patients. Commonly observed co-infecting pathogens were rhinovirus, parainfluenza virus 4, influenza A H3N2, bocavirus, respiratory syncytial virus, and adenovirus. Overall, co-infections were observed in the ≤35 age group. Patients with co-infections did not require hospitalization. Conclusion: Simultaneous identification of respiratory co-infections in SARS-CoV-2 positive patients offers the possibility of implementing optimized treatment regimens preventing morbidity and mortality

Nanoscale charging hysteresis measurement by multifrequency electrostatic force spectroscopy

We report a scanning probe technique that can be used to measure charging of localized states on conducting or partially insulating substrates at room temperature under ambient conditions. Electrostatic interactions in the presence of a charged particle between the tip and the sample is monitored by the second order flexural mode, while the fundamental mode is used for stabilizing the tip-sample separation. Cycling the bias voltage between two limits, it is possible to observe hysteresis of the second order mode amplitude due to charging. Results are presented on silicon nitride films containing silicon nanocrystals. (c) 2008 American Institute of Physics

Research on GIS-aided housing satisfaction using fuzzy decision-making techniques

In housing satisfaction research, studies that focus on the evaluation of surveying and its results draw much attention. However, a guiding contribution cannot be made to the decision-making processes in planning due to the lack of modelling for the spatial provisions of these survey-based studies. This study was conducted using two multi-criteria decision-making methods (Fuzzy DEMATEL+Fuzzy TOPSIS), and a model was created for the evaluation of housing satisfaction in two different TOKI housing estates. A fuzzy examination was carried out on the factors that affect satisfaction with the housing estates and their spatial provisions. A comparable housing satisfaction map based on a geostatistical analysis and supported with Geographic Information System was created for both housing estates using the obtained results. The planning, typology and design approaches of both TOKI housing estates are the same, but the level of the satisfaction with the houses in the Yenidogan TOKI housing estate was found to be as high as 60%, while the level of satisfaction with the Ildem TOKI housing estate was found to be extremely low. The study concluded that this difference derived from site selection, and that relationships with the city centre and transportation corridors were determinant factors

GIS Based Urban Renewal Area Awareness and Expectation Analysis Using Fuzzy Modeling

It is necessary to establish a new urban renewal approach, prioritizing the participation of the local society with the capability to resolve problems with the contributions of government, private sectors, and society

Long-COVID-19 in Asymptomatic, Non-Hospitalized, and Hospitalized Populations: A Cross-Sectional Study

A substantial proportion of coronavirus disease 2019 (COVID-19) survivors continue to suffer from long-COVID-19 (LC) symptoms. Our study aimed to determine the risk factors for LC by using a patient population from Northern Cyprus. Subjects who were diagnosed with severe acute respiratory syndrome-2 (SARS-CoV-2) infection in our university hospital were invited and asked to fill in an online questionnaire. Data from 296 survivors who had recovered from COVID-19 infection at least 28 days prior the study was used in the statistical analysis. For determination of risk factors for “ongoing symptomatic COVID-19 (OSC)” and “Post-COVID-19 (PSC)” syndromes, the patient population was further divided into group 1 (Gr1) and group 2 (Gr2), that included survivors who were diagnosed with COVID-19 within 4-12 weeks and at least three months prior the study, respectively. The number of people with post-vaccination SARS-CoV-2 infection was 266 (89.9%). B.1.617.2 (Delta) (41.9%) was the most common SARS-CoV-2 variant responsible for the infections, followed by BA.1 (Omicron) (34.8%), B.1.1.7 (Alpha) (15.5%), and wild-type SARS-CoV-2 (7.8%). One-hundred-and-nineteen volunteers (40.2%) stated an increased frequency of COVID-19-related symptoms and experienced the symptoms in the week prior to the study. Of those, 81 (38.8%) and 38 (43.7%) were from Gr1 and Gr2 groups, respectively. Female gender, chronic illness, and symptomatic status at PCR testing were identified as risk factors for developing OSC syndrome, while only the latter showed a similar association with PSC symptoms. Our results also suggested that ongoing and persistent COVID-19-related symptoms are not influenced by the initial viral cycle threshold (Ct) values of the SARS-CoV-2, SARS-CoV-2 variant as well as vaccination status and type prior to COVID-19. Therefore, strategies other than vaccination are needed to combat the long-term effect of COVID-19, especially after symptomatic SARS-CoV-2 infection, and their possible economic burden on healthcare settings