Oral manifestations in young adults infected with COVID-19 and impact of smoking:a multi-country cross-sectional study

Background: Oral manifestations and lesions could adversely impact the quality of people's lives. COVID-19 infection may interact with smoking and the impact on oral manifestations is yet to be discovered. Objectives: The aim of this study was to assess the self-reported presence of oral lesions by COVID-19-infected young adults and the differences in the association between oral lesions and COVID-19 infection in smokers and non-smokers. Methods: This cross-sectional multi-country study recruited 18-to-23-year-old adults. A validated questionnaire was used to collect data on COVID-19-infection status, smoking and the presence of oral lesions (dry mouth, change in taste, and others) using an online platform. Multi-level logistic regression was used to assess the associations between the oral lesions and COVID-19 infection; the modifying effect of smoking on the associations. Results: Data was available from 5,342 respondents from 43 countries. Of these, 8.1% reported COVID-19-infection, 42.7% had oral manifestations and 12.3% were smokers. A significantly greater percentage of participants with COVID-19-infection reported dry mouth and change in taste than non-infected participants. Dry mouth (AOR=, 9=xxx) and changed taste (AOR=, 9=xxx) were associated with COVID-19-infection. The association between COVID-19-infection and dry mouth was stronger among smokers than non-smokers (AOR = 1.26 and 1.03, p = 0.09) while the association with change in taste was stronger among non-smokers (AOR = 1.22 and 1.13, p = 0.86). Conclusion: Dry mouth and changed taste may be used as an indicator for COVID-19 infection in low COVID-19-testing environments. Smoking may modify the association between some oral lesions and COVID-19-infection

Cigarettes' use and capabilities-opportunities-motivation-for-behavior model:a multi-country survey of adolescents and young adults

The use of cigarettes among adolescents and young adults (AYA) is an important issue. This study assessed the association between regular and electronic-cigarettes use among AYA and factors of the Capability-Motivation-Opportunity-for-Behavior-change (COM-B) model. A multi-country survey was conducted between August-2020 and January-2021, Data was collected using the Global-Youth-Tobacco-Survey and Generalized-Anxiety-Disorder-7-item-scale. Multi-level logistic-regression-models were used. Use of regular and electronic-cigarettes were dependent variables. The explanatory variables were capability-factors (COVID-19 status, general anxiety), motivation-factors (attitude score) and opportunity-factors (country-level affordability scores, tobacco promotion-bans, and smoke free-zones) controlling for age and sex. Responses of 6,989-participants from 25-countries were used. Those who reported that they were infected with COVID-19 had significantly higher odds of electronic-cigarettes use (AOR = 1.81, P = 0.02). Normal or mild levels of general anxiety and negative attitudes toward smoking were associated with significantly lower odds of using regular-cigarettes (AOR = 0.34, 0.52, and 0.75, P < 0.001) and electronic-cigarettes (AOR = 0.28, 0.45, and 0.78, P < 0.001). Higher affordability-score was associated with lower odds of using electronic-cigarettes (AOR = 0.90, P = 0.004). Country-level-smoking-control policies and regulations need to focus on reducing cigarette affordability. Capability, motivation and opportunity factors of the COM-B model were associated with using regular or electronic cigarettes

Anxiety among adolescents and young adults during COVID-19 pandemic: A multi-country survey

(1) Background: Adolescents-and-young-adults (AYA) are prone to anxiety. This study assessed AYA's level of anxiety during the COVID-19 pandemic; and determined if anxiety levels were associated with country-income and region, socio-demographic profile and medical history of individuals. (2) Methods: A survey collected data from participants in 25 countries. Dependent-variables included general-anxiety level, and independent-variables included medical problems, COVID-19 infection, age, sex, education, and country-income-level and region. A multilevel-multinomial-logistic regression analysis was conducted to determine the association between dependent, and independent-variables. (3) Results: Of the 6989 respondents, 2964 (42.4%) had normal-anxiety, and 2621 (37.5%), 900 (12.9%) and 504 (7.2%) had mild, moderate and severe-anxiety, respectively. Participants from the African region (AFR) had lower odds of mild, moderate and severe than normal-anxiety compared to those from the Eastern-Mediterranean-region (EMR). Also, participants from lower-middle-income-countries (LMICs) had higher odds of mild and moderate than normal-anxiety compared to those from low-income-countries (LICs). Females, older-adolescents, with medical-problems, suspected-but-not-tested-for-COVID-19, and those with friends/family-infected with COVID-19 had significantly greater odds of different anxiety-levels. (4) Conclusions: One-in-five AYA had moderate to severe-anxiety during the COVID-19-pandemic. There were differences in anxiety-levels among AYAs by region and income-level, emphasizing the need for targeted public health interventions based on nationally-identified priorities

A multi-country study on the impact of sex and age on oral features of COVID-19 infection in adolescents and young adults

Background: Oral diseases are features of COVID-19 infection. There is, however, little known about oral diseases associated with COVID-19 in adolescents and young adults (AYA). Therefore, the aim of this study was to assess oral lesions’ association with COVID-19 infection in AYA; and to identify if sex and age will modify these associations. Methodology: Data was collected for this cross-sectional study between August 2020 and January 2021 from 11-to-23 years old participants in 43-countries using an electronic validated questionnaire developed in five languages. Data collected included information on the dependent variables (the presence of oral conditions- gingival inflammation, dry mouth, change in taste and oral ulcers), independent variable (COVID-19 infection) and confounders (age, sex, history of medical problems and parents’ educational level). Multilevel binary logistic regression was used for analysis. Results: Complete data were available for 7164 AYA, with 7.5% reporting a history of COVID-19 infection. A significantly higher percentage of participants with a history of COVID-19 infection than those without COVID-19 infection reported having dry mouth (10.6% vs 7.3%, AOR = 1.31) and taste changes (11.1% vs 2.7%, AOR = 4.11). There was a significant effect modification in the association between COVID-19 infection and the presence of dry mouth and change in taste by age and sex (P = 0.02 and < 0.001). Conclusion: COVID-19 infection was associated with dry mouth and change in taste among AYA and the strength of this association differed by age and sex. These oral conditions may help serve as an index for suspicion of COVID-19 infection in AYA

Machine learning for survival analysis in cancer research: A comparative study

Overview: Survival analysis is at the basis of every study in the field of cancer research. As every endeavor in this field aims primarily and eventually to improve patients’ survival time or reduce the potential for recurrence. This article presents a summary of some cancer survival analysis techniques and an up-to-date overview of different implementations of Machine Learning in this area of research. This paper also presents an empirical comparison of selected statistical and Machine Learning approaches on different types of cancer medical datasets. Methods: In this paper we explore a selection of recent articles that: review the use of Machine Learning in cancer research and/or benchmark the different Machine Learning techniques used in cancer survival analysis. This search resulted in 12 papers that were selected following certain criteria. Our aim is to assess the importance of the use of Machine Learning for survival analysis in cancer research, compared to the statistical methods, and how different Machine Learning techniques may perform in different settings in the context of cancer survival analysis. The techniques were selected based on their popularity. Cox Proportional Hazards with Ridge penalty, Random Survival Forests, Gradient Boosting for Survival Analysis with a CoxPh loss function, linear and kernel Support Vector Machines were applied to 10 different cancer survival datasets. The mean Concordance Index and standard deviation were used to compare the performances of these techniques and the results of these implementations were summarized and analyzed for noticeable patterns or trends. Kaplan-Meier plots were used for the non-parametric survival analysis of the different datasets. Results: Cox Proportional Hazards delivers comparable results with Machine Learning techniques thanks to the Ridge penalty and the different methods for dealing with tied events but fails to produce results in higher dimensional datasets. All techniques benchmarked in the study had comparable performances. The use of prognostic tools when there is a mismatch between the patients and the populations used to train the models may not be advisable since each dataset provides a differently shaped survival curve even when presenting a similar cancer type

Chemical Composition and Biological Activities of the Aqueous Fraction of Parkinsonea aculeata L. Growing in Saudi Arabia

Polyphenolic constituents and chromatographic fingerprint of the aqueous fraction obtained from the ethanolic extract of the aerial parts of Parkinsonea aculeata L. growing in Saudi Arabia were investigated for the first time using UPLC-ESI/MS/MS in negative mode. Forty compounds were tentatively identified including sixteen C-flavone glycosides, twenty-two O-flavone glycosides, and two polymethoxylated flavonoids. Compounds identification was based on the MS/MS fragmentation and literature comparison. The aqueous fraction fingerprint is rich in C- and O-flavone glycosides, like apigenin-8-C-β-D-glucopyranoside (vitexin), vitexin 2″-O-rhamnoside, luteolin-8-C-glucoside (orientin), luteolin-8-C-β-D-glucopyranoside-7-O-rhamnoside and luteolin-7-O-rutinoside. These compounds were identified for the first time in the aqueous fraction of Saudi P. aculeata L. plant. Additionally, the antioxidant and anticancer activities were investigated. The aqueous fraction showed a strong DPPH scavenging activity with IC50 48.3 ± 1.5 μg/mL compared to ascorbic acid 14.2 ± 0.5 μg/mL. However, this fraction showed a very weak cytotoxic activity against HepG-2 (Hepatocellular carcinoma) and MCF-7 (Breast carcinoma) with IC50 222 ± 1.8 and 304 ± 9.2 µg/ml respectively compared to cisplatin IC50 3.67 ± 8.1 and 5.71 ± 3.8 µg/ml respectively. Keywords: Parkinsonea aculeata, C and O-flavone glycosides, Antioxidant, Anticancer, UPLC-ESI-MS/M

Development and acceptability of behavioral interventions promoting mothers’ brushing of pre-school children’s teeth: The preparation phase of the multi-phase optimization strategy framework

Abstract Background Early childhood caries can be prevented through regular parental-supported toothbrushing, indicating the importance of behavior modification interventions targeting parents. Mobile oral health (m-oral health) interventions are gaining increased popularity although their production is not always based on solid theoretical frameworks and evidence about the efficacy of individual intervention components is not available. The Multiphase Optimization Strategy (MOST) offers a framework to develop complex m-oral health interventions and assessing the efficacy of individual components. Aim This study describes the development and assesses the acceptability of 3 intervention components using MOST to promote mothers’ brushing of their preschool children’s teeth. Methods The Theory of Planned Behavior guided the development of 3 components: motivational interviewing (MI), storytelling videos (STVs), and oral health promotion messages (OHPMs). A researcher received training to conduct MI. Twenty-four OHPMs were developed, and 14 STVs scripts were developed based on the “And, But, Therefore” framework. A feasibility pilot study was conducted to determine the optimization objective and assess mothers’ preferences regarding the frequency and timing of receiving the intervention components. The mothers participated in a semi-structured interview to assess the acceptability of the components using 7 open-ended questions based on the framework of acceptability and thematic analysis was used to analyze the qualitative data. The mothers also responded to questions assessing the perceived and experienced acceptability of the components using close-ended questions. Descriptive statistics were presented as means and standard deviations for continuous variables and median and interquartile range for categorical variables. Results Sixteen mothers were included. The mothers expressed positive affective attitude towards the interventions. They felt the components served as “good reminders” to brush their children’s teeth. However, “time” was a burden for the mothers. 80% of the mothers preferred receiving the OHPMs and STVs once per week, from 8 pm to 2 am (50%), and 60% indicated they can set 15–30 min to receiving the interventions. Conclusion The 3 components were acceptable to the mothers. The OHPMs and STVs will be sent to the mothers once per week, between 8 pm to 2 am. The MI and follow-up phone calls will be limited to 15 min

Influence of Si4+ and Ga3+ doped in the BiSiGaVOx system on the structure and ionic conductivity

In the present work, the Si and Ga co-doped the Bi4V2O11 compound, i.e., the Bi4V2-xGax/2Six/2O11-3x/4 system (0.1 ≤ x ≤ 0.9) was studied. Structural analysis by XRD reveals that the ordered α-monoclinic phase is synthesized for x ≤ 0.1. The less ordered β-orthorhombic phase was observed in the compositional range of 0.2 ≤ x ≤ 0.3, while the disordered γ-tetragonal phase was obtained over a wide compositional range of 0.4 ≤ x ≤ 0.8. The conductivity of the solid solution Bi4V2-xGax/2Six/2O11-3x/4, with x = 0.2, is promising at 500°C, reaching 1.1 × 10–1 S.cm−1

Design and Mathematical Modeling of CMOS Compatible - MEMS Microhotplate

Current Microhotplates have large power consumptions, temperature uniformity problems, and are highly priced; additionally, special stages are required to be integrated with ICs. The modeling and design of a MEMS Microhotplate (MHP) using standard 0.18 μm IP4M CMOS process technology is discussed in this paper. The designed MHP is intended to achieve good temperature uniformity while dissipating little power. The MHP microbridges lengths are varied from 80 μm to 120 μm whereas the MHP microbridges widths are varied from 5 μm to 25 μm. The effect of the length and width are studied and three different lengths of micro heater 15560 μm, 24360 μm, 35160 μm, and 5 μm width were studied. The optimized design with microbridges of 100 μm length and 25 μm width and a heater length of 15560 μm is selected. The power dissipation and operating temperature were measured using mathematical modeling and actuation voltages ranging from 0.2 V to 1 V. The modeling estimates MHP power dissipation ranging from 0.264 mW to 3.181 mW at operating temperatures ranging from 11.12 oC to 277.92 oC