Introduction dental procedures produce bio-aerosols that can carry the highly contagious COVID-19 virus. Hence, the entire dental care team has to follow the current COVID-19 related infection control protocols. The study aims to assess the knowledge, attitude, and practices associated with infection control methods during dental procedures among dental practitioners during the COVID-19 pandemic in India. Methods the online questionnaire consisted of four sections namely, demographic details, eight questions on knowledge, four questions on attitude and eight questions on the practice of dentists during COVID-19 pandemic. One point was attributed for a correct response and zero point for an incorrect response. The study used descriptive statistics and binary logistic regression models in Jamovi 1.8.1 to establish relationships between knowledge, attitude, and practices among dental professionals and their demographic characteristics. Results among 384 dentists, 294 (76.6%) were aware of the hand hygiene methods, 372 dentists (96.9%) were aware of the Personal Protective Equipment (PPE), 343 dentists (89.3%) recorded the body temperature of the patients. One hundred and thirty eight (138) dentists (35.9%) did not use rubber dam and 158 dentists (41.1%) were not aware of the four-handed dentistry. Among the study participants, 57.8% displayed adequate knowledge, 63.8% possessed good attitude and 93.5% followed good practices on COVID-19 appropriate infection control measures during dental procedures. The mean knowledge, attitude, and practice scores were found to be 6.61, 2.04, and 3.38 respectively. Based on multivariable binary logistic regression analysis, it is observed that males (aOR: 0.55, 95% CI 0.35-0.87; p=0.011) have a lower likelihood of having a good knowledge when compared with females after adjusting for the other independent variables in the model. Also, individuals with higher qualifications (aOR: 0.57, 95% CI 0.36-0.92; p=0.022) appear to have lower likelihood of having good knowledge on COVID-19 infection control methods during dental procedure. Conclusion the study concludes that participants possess sound knowledge, attitude and practice on hand hygiene, PPE, patient triage and waiting area modifications at the workplace. However, poor response was noted on the use of rubber dam, remote telephonic screening and four-handed dentistry practice.

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Hemoglobinopathies are inherited disorders of red blood cells that poses significant cause of morbidity and mortality, impose a heavy burden on family. The study aims to assess the awareness of Thalassemia, and its willingness to screen among young women from Udupi district. Methods: A descriptive cross-sectional survey design was employed to assess the awareness on Thalassemia among young women belonging to the age group of 18-24 years from selected undergraduate institutions of the Udupi district. The study used descriptive statistics, data visualization methods and chi-square tests. Results: Among the 389 participants, 3(0.8%) of the participants reported Thalassemia in their families. Also, 28 (7.2%) of the participants have a history of consanguineous marriage. 273 (70%) participants reported Thalassemia is a lifetime condition, whereas 284(73%) believed that consanguinity does not increase the Thalassemia incidence. According to 275(70%) respondents, premarital screening is not essential to rule out Thalassemia. The readiness of young women to screen for carrier status was estimated to be 57(15%), While 101(27%) were unwilling to screen, While 221 (58%) were unsure about screening for carrier status. Based on Pearson's Chi-Squared test, there was association between following variables: Age and Thalassemia awearness, (χ 2 (4) = 13.749, p < 0.008), Education and Thalassemia awearness (χ 2 (4) = 10.864, p < 0.028), knowledge score and family income (χ 2 (8) = 21.100, p < 0.007). Conclusion:The premise suggests a lack of awareness of Thalassemia disorder among young women, this calls for an urgent need to revise the Thalassemia control programme.

Concern about fertility impairment after vaccination is one of the reasons for vaccine hesitancy in the population. This retrospective observational study aims to understand the impact of CovishieldTM (ChAdOx1 nCoV- 19 Corona Virus Vaccine, Recombinant) COVID-19 vaccination on ejaculate quality in fifty-three patients undergoing semen analysis between 2018 to 2021. A baseline semen profile was recorded from the subjects during their visit before the vaccination for fertility work-up. Follow-up ejaculates were provided approximately 82 (Q1:37, Q3:124) days after the second dose of vaccination. Semen characteristics such as volume, sperm concentration, sperm motility, and morphological abnormalities were recorded. Of the 53 subjects, 33 (62%) had semen characteristics above the WHO reference. In general, no significant variations in the semen parameters were observed except for a moderate decline in sperm morphology (p< 0.05). The baseline semen characteristics in 20 (38%) subjects were below the WHO reference range; however, no significant decline in the ejaculate quality was observed in their follow-up samples. Further, none of the ejaculates in both study groups were azoospermic during the follow-up evaluation. Our results affirm that CovishieldTM vaccine is not detrimental to male fertility.

This study investigated whether combining metabolomic and embryologic data with machine learning (ML) models improve the prediction of embryo implantation potential. In this prospective cohort study, infertile couples (n=56) undergoing day-5 single blastocyst transfer between February 2019 and August 2021 were included. After day-5 single blastocyst transfer, spent culture medium (SCM) was subjected to metabolite analysis using nuclear magnetic resonance (NMR) spectroscopy. Derived metabolite levels and embryologic parameters between successfully implanted and failed groups were incorporated into ML models to explore their predictive potential regarding embryo implantation. The SCM of blastocysts that resulted in successful embryo implantation had significantly lower pyruvate (p<0.05) and threonine (p<0.05) levels compared to medium control but not compared to SCM related to embryos that failed to implant. Notably, the prediction accuracy increased when classical ML algorithms were combined with metabolomic and embryologic data. Specifically, the custom artificial neural network (ANN) model with regularized parameters for metabolomic data provided 100% accuracy, indicating the efficiency in predicting implantation potential. Hence, combining ML models (specifically, custom ANN) with metabolomic and embryologic data improves the prediction of embryo implantation potential. The approach could potentially be used to derive clinical benefits for patients in real-time.