UV-C irradiation-based inactivation of SARS-CoV-2 in contaminated porous and non-porous surfaces.

The SARS-CoV-2 pandemic emphasized effective cleaning and disinfection of common spaces as an essential tool to mitigate viral transmission. To address this problem, decontamination technologies based on UV-C light are being used. Our aim was to generate coherent and translational datasets of effective UV-C-based SARS-CoV-2 inactivation protocols for the application on surfaces with different compositions. Virus infectivity after UV-C exposure of several porous (bed linen, various types of upholstery, synthetic leather, clothing) and non-porous (types of plastic, stainless steel, glass, ceramics, wood, vinyl) materials was assessed through plaque assay using a SARS-CoV-2 clinical isolate. Studies were conducted under controlled environmental conditions with a 254-nm UV-C lamp and irradiance values quantified using a 254 nm-calibrated sensor. From each material type (porous/non-porous), a product was selected as a reference to assess the decrease of infectious virus particles as a function of UV-C dose, before testing the remaining surfaces with selected critical doses. Our data show that UV-C irradiation is effectively inactivating SARS-CoV-2 on both material types. However, an efficient reduction in the number of infectious viral particles was achieved much faster and at lower doses on non-porous surfaces. The treatment effectiveness on porous surfaces was demonstrated to be highly variable and composition-dependent. Our findings will support the optimization of UV-C-based technologies, enabling the adoption of effective customizable protocols that will help to ensure higher antiviral efficiencies.

Barthel's Index: A Better Predictor for COVID-19 Mortality Than Comorbidities.

BACKGROUND: The most consistently identified mortality determinants for the new coronavirus 2019 (COVID-19) infection are aging, male sex, cardiovascular/respiratory diseases, and cancer. They were determined from heterogeneous cohorts that included patients with different disease severity and previous conditions. The main goal of this study was to determine if activities of daily living (ADL) dependence measured by Barthel's index could be a predictor for COVID-19 mortality. METHODS: A prospective cohort study was performed with a consecutive sample of 340 COVID-19 patients representing patients from all over the northern region of Portugal from October 2020 to March 2021. Mortality risk factors were determined after controlling for demographics, ADL dependence, admission time, comorbidities, clinical manifestations, and delay-time for diagnosis. Central tendency measures were used to analyze continuous variables and absolute numbers (proportions) for categorical variables. For univariable analysis, we used t test, chi-square test, or Fisher exact test as appropriate (α=0.05). Multivariable analysis was performed using logistic regression. IBM SPSS version 27 statistical software was used for data analysis. RESULTS: The cohort included 340 patients (55.3% females) with a mean age of 80.6±11.0 years. The mortality rate was 19.7%. Univariate analysis revealed that aging, ADL dependence, pneumonia, and dementia were associated with mortality and that dyslipidemia and obesity were associated with survival. In multivariable analysis, dyslipidemia (odds ratio [OR], 0.35; 95% confidence interval [CI], 0.17-0.71) was independently associated with survival. Age ≥86 years (pooled OR, 2.239; 95% CI, 1.100-4.559), pneumonia (pooled OR, 3.00; 95% CI, 1.362-6.606), and ADL dependence (pooled OR, 6.296; 95% CI, 1.795-22.088) were significantly related to mortality (receiver operating characteristic area under the curve, 82.1%; p<0.001). CONCLUSION: ADL dependence, aging, and pneumonia are three main predictors for COVID-19 mortality in an elderly population.

Vitamin D-related polymorphisms and vitamin D levels as risk biomarkers of COVID-19 disease severity.

Vitamin D is a fundamental regulator of host defences by activating genes related to innate and adaptive immunity. Previous research shows a correlation between the levels of vitamin D in patients infected with SARS-CoV-2 and the degree of disease severity. This work investigates the impact of the genetic background related to vitamin D pathways on COVID-19 severity. For the first time, the Portuguese population was characterized regarding the prevalence of high impact variants in genes associated with the vitamin D pathways. This study enrolled 517 patients admitted to two tertiary Portuguese hospitals. The serum concentration of 25 (OH)D, was measured in the hospital at the time of patient admission. Genetic variants, 18 variants, in the genes AMDHD1, CYP2R1, CYP24A1, DHCR7, GC, SEC23A, and VDR were analysed. The results show that polymorphisms in the vitamin D binding protein encoded by the GC gene are related to the infection severity (p = 0.005). There is an association between vitamin D polygenic risk score and the serum concentration of 25 (OH)D (p = 0.04). There is an association between 25 (OH)D levels and the survival and fatal outcomes (p = 1.5e-4). The Portuguese population has a higher prevalence of the DHCR7 RS12785878 variant when compared with its prevalence in the European population (19% versus 10%). This study shows a genetic susceptibility for vitamin D deficiency that might explain higher severity degrees in COVID-19 patients. These results reinforce the relevance of personalized strategies in the context of viral diseases.Trial registration: NCT04370808.

The Challenge of Dental Education After COVID-19 Pandemic - Present and Future Innovation Study Design.

The present work suggests research and innovation on the topic of dental education after the COVID-19 pandemic, is highly justified and could lead to a step change in dental practice. The challenge for the future in dentistry education should be revised with the COVID-19 and the possibility for future pandemics, since in most countries dental students stopped attending the dental faculties as there was a general lockdown of the population. The dental teaching has an important curriculum in the clinic where patients attend general dentistry practice. However, with SARS-CoV-2 virus, people may be reluctant having a dental treatment were airborne transmission can occur in some dental procedures. In preclinical dental education, the acquisition of clinical, technical skills, and the transfer of these skills to the clinic are extremely important. Therefore, dental education has to adapt the curriculum to embrace new technology devices, instrumentations systems, haptic systems, simulation based training, 3D printer machines, to permit validation and calibration of the technical skills of dental students.

Polymer Selection for Hot-Melt Extrusion Coupled to Fused Deposition Modelling in Pharmaceutics.

Three-dimensional (3D) printing offers the greatest potential to revolutionize the future of pharmaceutical manufacturing by overcoming challenges of conventional pharmaceutical operations and focusing design and production of dosage forms on the patient's needs. Of the many technologies available, fusion deposition modelling (FDM) is considered of the lowest cost and higher reproducibility and accessibility, offering clear advantages in drug delivery. FDM requires in-house production of filaments of drug-containing thermoplastic polymers by hot-melt extrusion (HME), and the prospect of connecting the two technologies has been under investigation. The ability to integrate HME and FDM and predict and tailor the filaments' properties will extend the range of printable polymers/formulations. Hence, this work revises the properties of the most common pharmaceutical-grade polymers used and their effect on extrudability, printability, and printing outcome, providing suitable processing windows for different raw materials. As a result, formulation selection will be more straightforward (considering the characteristics of drug and desired dosage form or release profile) and the processes setup will be more expedite (avoiding or mitigating typical processing issues), thus guaranteeing the success of both HME and FDM. Relevant techniques used to characterize filaments and 3D-printed dosage forms as an essential component for the evaluation of the quality output are also presented.