A Novel Cost-Effective Simulation Model for Continuous Curvilinear Capsulorhexis.

Introduction: We describe and validate a low-cost simulation model for practicing anterior lens capsule continuous curvilinear capsulorhexis (CCC). Methods: A simulation model for CCC was developed from widely available low-cost materials. Ophthalmologists attending the annual scientific meeting of the Research Institute of Ophthalmology, Giza, Egypt, were asked to perform a five CCC model task and then anonymously answer a questionnaire that assessed the realism and training utility of the model using a five-point Likert scale (1 = unacceptable, 2 = poor, 3 = acceptable, 4 = favorable and 5 = excellent). Results: Twenty-seven ophthalmologists completed the task and the anonymous questionnaire. Overall, participants felt that the model simulated CCC step in cataract surgery well (mean: 3.5) and was comparable to other kinds of CCC simulation models (mean: 3.3). The model scored highly for its overall educational value (mean: 4.00) and for enlarging a small CCC (mean:3.7), while the feasibility of this model in practicing the management of a runaway leading edge of CCC scored 2.9. Conclusion: This model may provide an alternative method for training for CCC and other anterior lens capsule-related maneuvers. This option may be particularly helpful for residency training programs with limited access to virtual reality simulators or commercially available synthetic eye models.

Microbial (viruses, bacteria and fungi) protective personal clothing

This chapter highlights the new approaches to producing personal protective clothing (PPC) as antimicrobial fabrics such as gloves, gowns and face masks. Antimicrobial colorants, either natural or synthetic dyes, are widely employed in textile applications as bifunctional agents. This chapter also focuses on the potent nanometals (metal nanoparticles, MNPs) in the finishing process and their finishing techniques. Furthermore, many studies have reported on the antimicrobial activities of metal nanoparticles and dyes, however their antiviral activity has not been adequately investigated. The COVID-19 pandemic has increased the urgency of studying the antiviral potentiality of those agents in addition to their cytotoxicity and applicability. Moreover, there are many kinds of PPC according to their application that require different finishing techniques. This chapter provides a review of the applicability of antimicrobial and antiviral agents and the modern techniques used in textile finishing processes to achieve the highest antimicrobial and antiviral activities. © 2022 Elsevier Ltd. All rights reserved.

International Society of Blood Transfusion survey of experiences of blood banks and transfusion services during the COVID-19 pandemic.

BACKGROUND AND OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has impacted blood systems worldwide. Challenges included maintaining blood supplies and initiating the collection and use of COVID-19 convalescent plasma (CCP). Sharing information on the challenges can help improve blood collection and utilization. MATERIALS AND METHODS: A survey questionnaire was distributed to International Society of Blood Transfusion members in 95 countries. We recorded respondents' demographic information, impacts on the blood supply, CCP collection and use, transfusion demands and operational challenges. RESULTS: Eighty-two responses from 42 countries, including 24 low- and middle-income countries, were analysed. Participants worked in national (26.8%) and regional (26.8%) blood establishments and hospital-based (42.7%) institutions. CCP collection and transfusion were reported by 63% and 36.6% of respondents, respectively. Decreases in blood donations occurred in 70.6% of collecting facilities. Despite safety measures and recruitment strategies, donor fear and refusal of institutions to host blood drives were major contributing factors. Almost half of respondents working at transfusion medicine services were from large hospitals with over 10,000 red cell transfusions per year, and 76.8% of those hospitals experienced blood shortages. Practices varied in accepting donors for blood or CCP donations after a history of COVID-19 infection, CCP transfusion, or vaccination. Operational challenges included loss of staff, increased workloads and delays in reagent supplies. Almost half of the institutions modified their disaster plans during the pandemic. CONCLUSION: The challenges faced by blood systems during the COVID-19 pandemic highlight the need for guidance, harmonization, and strengthening of the preparedness and the capacity of blood systems against future infectious threats.

Novel Antiviral and Antibacterial Durable Polyester Fabrics Printed with Selenium Nanoparticles (SeNPs).

The COVID-19 pandemic has clearly shown the importance of developing advanced protective equipment, and new antiviral fabrics for the protection and prevention of life-threatening viral diseases are needed. In this study, selenium nanoparticles (SeNPs) were combined with polyester fabrics using printing technique to obtain multifunctional properties, including combined antiviral and antibacterial activities as well as coloring. The properties of the printed polyester fabrics with SeNPs were estimated, including tensile strength and color fastness. Characterization of the SeNPs was carried out using TEM and SEM. The results of the analysis showed good uniformity and stability of the particles with sizes range from 40-60 nm and 40-80 nm for SeNPs 25 mM and 50 mM, respectively, as well as uniform coating of the SeNPs on the fabric. In addition, the SeNPs-printed polyester fabric exhibited high disinfection activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with an inhibition percentage of 87.5%. Moreover, a toxicity test of the resulting printed fabric revealed low cytotoxicity against the HFB4 cell line. In contrast, the treated fabric under study showed excellent killing potentiality against Gram-positive bacteria (Bacillus cereus) and Gram-negative bacteria (Pseudomonas aeruginosa, Salmonella typhi, and Escherichia coli). This multifunctional fabric has high potential for use in protective clothing applications by providing passive and active protection pathways.

Latent Growth Curve Modeling for COVID-19 Cases in Presence of Time-Variant Covariate.

For the past two years, the entire world has been fighting against the COVID-19 pandemic. The rapid increase in COVID-19 cases can be attributed to several factors. Recent studies have revealed that changes in environmental temperature are associated with the growth of cases. In this study, we modeled the monthly growth rate of COVID-19 cases per million infected in 126 countries using various growth curves under structural equation modeling. Moreover, the environmental temperature has been introduced as a time-varying covariate to enhance the performance of the models. The parameters of growth curve models have been estimated, and accordingly, the results are discussed for the affected countries from August 2020 to July 2021.

The New Novel Discrete Distribution with Application on COVID-19 Mortality Numbers in Kingdom of Saudi Arabia and Latvia

This paper aims to introduce a superior discrete statistical model for the coronavirus disease 2019 (COVID-19) mortality numbers in Saudi Arabia and Latvia. We introduced an optimal and superior statistical model to provide optimal modeling for the death numbers due to the COVID-19 infections. This new statistical model possesses three parameters. This model is formulated by combining both the exponential distribution and extended odd Weibull family to formulate the discrete extended odd Weibull exponential (DEOWE) distribution. We introduced some of statistical properties for the new distribution, such as linear representation and quantile function. The maximum likelihood estimation (MLE) method is applied to estimate the unknown parameters of the DEOWE distribution. Also, we have used three datasets as an application on the COVID-19 mortality data in Saudi Arabia and Latvia. These three real data examples were used for introducing the importance of our distribution for fitting and modeling this kind of discrete data. Also, we provide a graphical plot for the data to ensure our results.

The new discrete distribution with application to COVID-19 Data.

This research aims to model the COVID-19 in different countries, including Italy, Puerto Rico, and Singapore. Due to the great applicability of the discrete distributions in analyzing count data, we model a new novel discrete distribution by using the survival discretization method. Because of importance Marshall-Olkin family and the inverse Toppe-Leone distribution, both of them were used to introduce a new discrete distribution called Marshall-Olkin inverse Toppe-Leone distribution, this new distribution namely the new discrete distribution called discrete Marshall-Olkin Inverse Toppe-Leone (DMOITL). This new model possesses only two parameters, also many properties have been obtained such as reliability measures and moment functions. The classical method as likelihood method and Bayesian estimation methods are applied to estimate the unknown parameters of DMOITL distributions. The Monte-Carlo simulation procedure is carried out to compare the maximum likelihood and Bayesian estimation methods. The highest posterior density (HPD) confidence intervals are used to discuss credible confidence intervals of parameters of new discrete distribution for the results of the Markov Chain Monte Carlo technique (MCMC).

Upregulation of FOXP3 is associated with severity of hypoxia and poor outcomes in COVID-19 patients.

The levels of messenger RNA (mRNA) transcription of FOXP3, IFN-γ, TNF, IL-6 and COX-2 from both COVID-19 infected and control subjects were evaluated using SYBRTM green real-time polymerase chain reaction (RT-PCR). Severe/critical cases showed significantly lower lymphocyte counts and higher neutrophil counts than the mild or moderate cases. There were significantly lower levels of mRNA expressions of IFN-γ, TNFα and FOXP3 in COVID-19 patients than in the control group. On the other hand, IL-6 and COX-2 expressions were significantly higher in patients suffering from severe disease. FOXP3 expressions were correlated with the severities of hypoxia and were excellent in predicting the disease severity. This was followed by the IL-6, COX-2 and TNFα expressions. FOXP3 expression was the only biomarker to show a significant correlation with patient mortality. It was concluded that SARS-CoV-2 infection is associated with the downregulation of FOXP3 and upregulations of IL-6 and COX-2.

Artificial neural networks and statistical models for optimization studying COVID-19.

The biggest challenge facing the world in 2020 was the pandemic of the coronavirus disease (COVID-19). Since the start of 2020, COVID-19 has invaded the world, causing death to people and economic damage, which is cause for sadness and anxiety. Since the world has passed from the first peak with relative success, this should be evaluated by statistical analysis in preparation for potential further waves. Artificial neural networks and logistic regression models were used in this study, and some statistical indicators were extracted to shed light on this pandemic. WHO website data for 32 European countries from 11th of January 2020 to 29th of May 2020 was utilized. The rationale for choosing the stated methodological tools is that the classification accuracy rate of artificial neural networks is 85.6% while the classification accuracy rate of logistic regression models 80.8%.

Knowledge, attitude and practice regarding COVID-19 among Sudanese population during the early days of the pandemic: Online cross-sectional survey.

BACKGROUND: Coronavirus disease (COVID-19) is an infectious disease caused by a new coronavirus strain. The first case of the disease was reported as pneumonia of unknown cause in late December 2019, in Wuhan, China, and then the disease started to spread to other countries. This study aimed to assess the knowledge attitude and practice of the Sudanese population toward COVID-19. METHODS: This cross-sectional online study was conducted among the Sudanese population. The Data was collected by using a self-administered online survey, the survey was in Arabic language and we tested it before sthe distribution. The data collection period was started from 31 March to 3 April 2020. We used an appropriate statistical test and a p-value of <0.05 was considered as statistically significant. RESULT: About 62% of the respondents were females, and 55.1% aged 12-24 years. Our study determined that 68.3% of the study participants had a good knowledge toward COVID-19, and the majority (96.4%) knew that the COVID-19 is transmitted through droplets, while 89.9% of the participants had a positive attitude toward the COVID-19 pandemic. On the other hand, only 48.5% of the participants had a good practice toward COVID-19 pandemic. We also found that good knowledge is significantly associated with good practice. CONCLUSION: Our participants had good knowledge, and positive attitude toward the COVID-19. Our findings revealed that education is positively associated with knowledge, and good level of knowledge is associated with good practice toward COVID-19. Efforts should focus more to raise the awareness among the less educated people.

Coronavirus disease (COVID-19) and decrease in blood donation: a cross-sectional study from sudan

Abstract Background and objectives The COVID-19 pandemic has a negatively impact on the blood donation process, whole the world nowadays is struggling to maintain a sufficient safe blood supply. The aim of this study was to identify the reasons for lapsing from blood donation during the COVID-19 pandemic among the Sudanese blood donors, and also to determine the motives for returning to blood donation. Materials and methods This was a cross-sectional study. Our population was all lapsing Sudanese blood donors who received an invitation from the national central laboratory and did not respond. We used an interviewing questionnaire, interviews were done through phone calls. Result 674 blood donors had participated in our study. About 94.6% of the participants were males and the majority was younger than 36 years. The most common reason for lapsing from blood donation was staying at home to avoid the COVID-19 infection (60.6%). About 63.4% of the participants said that they would return to donate if there were regular invitations. And 52.4% of our participants said they would return if the COVID-19 pandemic was controlled. The altruistic factor was the most common motivation for first time donation. Conclusion We have to find strategies to overcome this reduction in the blood donors. We have to raise the awareness of people about the importance of maintaining adequate blood supply;also we have to provide mobile donation sites and to send regular invitations to the donors.