The single-use plastic pandemic in the covid-19 era

Single-use plastic (SUP) products are designed to be used only once or for a short time before being discarded. This research focused on personal protective equipment (PPE) made of SUP-based products (face masks, gloves, etc.) and SUP packaging during the COVID-19 era. One of the most obvious effects of the pandemic has been the increase in the use of PPE not only by healthcare professionals but also by the general public. As part of the fight against the pandemic, quarantines were started in many countries;people had to work from home, and shops were closed. Online shopping became more common. The increase in e-commerce also increased the use of SUP packaging. Here, we present an estimation of the number of daily single-use face masks and the amount of medical waste, considering the current COVID-19 cases and population. As a result of our calculations, we show that while the daily amount of medical waste is greatest in the European region, the number of single-use face masks used each day is highest in Asia. These results are associated with the number of COVID-19 cases and population data in the regions. Medical waste and number of patients were directly proportional, as were population and face mask waste. We are faced with plastic pollution that is becoming more difficult to control each day. In the current circumstances, within the scope of combating the possible plastic pandemic, we should prevent the shift of beneficial plastic from a preservative to a pollutant by prioritizing individual, societal, and institutional reforms to minimize plastic pollution. © 2023 John Wiley & Sons Ltd.

Assessment of the safety and feasibility of local anaesthetic cystodiathermy for indeterminate bladder lesions in the COVID-19 era

Introduction: Patients presenting with bladder lesions identified during cystoscopy require histological diagnosis, routinely obtained by biopsy under general anaesthetic (GA). GA biopsies are resource intensive as they require the use of an operating theatre and surgical staff. Local anaesthetic cystodiathermy (LAC) is an alternative method for obtaining biopsies, suitable for bladder lesions <5mm in size. LAC can be performed in the outpatient setting thus reducing the need for theatre resources. The aim of our audit was to assess the safety and feasibility LAC bladder biopsies for indeterminate bladder lesions. Method(s): LAC were carried out at our peripheral London outpatient clinic. The main inclusion criteria was the presence of sub 5mm indeterminate lesions identified during routine and surveillance flexible cystoscopy. Patients notes were reviewed for follow up 2 months after their procedure. Result(s): 10 patients underwent LAC between July and September 2021, with an age range of 36-83 years old and ASA grade between 1 and 3. 6 patients were invited following positive findings at routine surveillance cystoscopy, 3 following cystoscopy for new haematuria, and 1 was investigated for routine UTIs. Only one patient had a malignant histology, with 90% reporting a benign biopsy. No patient required admission or subsequent GA biopsy, and no complications were reported. Conclusion(s): LAC is a resource-effective procedure eliminates the exposure of patient to GA. It avoids the need for preassessment and inpatient admission, thus freeing up theatre resources for other patients. This project supports the use of LAC for small indeterminate bladder lesions.

A review on the effect of micro- and nano-plastics pollution on the emergence of antimicrobial resistance

The recent upsurge in the studies on micro/nano plastics and antimicrobial resistance genes has proven their deleterious effects on the environmental and human health. Till-date, there is a scarcity of studies on the in-teractions of these two factors and their combined influence. The interaction of microplastics has led to the formation of new plastics namely plastiglomerates, pyroplastics. and anthropoquinas. It has long been ignored that the occurrence of microplastics has become a breeding ground for the emergence of antimicrobial resistance genes. Evidently microplastics are also associated with the occurrence of other pollutants such as polyaromatic hydrocarbons and pesticides. The increased use of antibiotics (after Covid breakout) has further elevated the detrimental effects on human health. Therefore, this study highlights the relation of microplastics with antibiotic resistance generation. The factors such as uncontrolled use of antibiotics and negligent plastic consumption has been evaluated. Furthermore, the future research prospective was provided that can be helpful in correctly identifying the seriousness of the environmental occurrence of these pollutants.

Oral Manifestations In Mucormycosis Report Of 6 Cases The Starring Disease Of 2020

With the emergence of the pandemic disease covid 19 in the year 2019, disease had a devastating and life-threatening impression in the second wave that has calamitously ascended the number of cases of the disease called Mucormycosis all over the world and including our country, India. Being the most infrequent fungal infection, it was seen as the most rapidly occurring fulminating disease among the patients who were recovering from recent SARS-CoV-2 infection. The most common form of this infection is seen in the rhinomaxillary region and in patients who were immunocompromised such as diabetes. This article will highlight the various characteristic oral features of Mucormycosis with the CBCT characteristic features that have been observed in 6 different cases of recovered COVID-19 patients, with few patients having a history of diabetes.

PeerConnect: Live Virtual Event Platform by using Web Server

Peerconnect is a great solution for virtual event management. Peerconnect is an all-in-one event management platform for promoting and conducting online events on the same platform. The point of virtual event management software is to allow users to create hosts and manage the events at ease without having to depend on many software to accomplish different tasks. So, the event management software Peerconnect has established the pipeline for people who want to promote, manage and conduct virtual events. Organizers can create the events on the platform and can promote and sell the tickets to other users on the same platform. Organizers can host live chat rooms and live discussions with video calling capabilities as well. Peerconnect is a web application using which the user can get to know about the events which are conducted virtually. Once the user selects the event, then he has to register for it. Once the registration is successful, user can attend the event on the same platform. Once the registration is successful, users can successfully login and they can search for an event that they are interested in and filter them according to their interests. Once the user selects the event then they have to register for it. Once registration for the event is successful, user can join the event in just one click and attend the event on the same platform and can download the participation certificate as well. If a registered user misses an event, he can still watch the recorded session of that event anytime after its completion. The event organizer can create an organization and later post the event. During the event, the organizer can send files and use the chat feature to engage and clear doubts of the attendees. They can also share their screen so that it is visible to all the attendees. Organizers can also capture the attendance of those who are attending, based on which the attendees can be able to download their participation certificates. © 2022 IEEE.

Computed tomography severity scoring of COVID 19 infected young patients: Is the second wave affecting the young lungs more than the first wave in India?

We evaluated the High Resolution Computed Tomography (HRCT) findings in young patients (< 40 years) infected with the COVID 19 virus and tried to find out any difference in the severity of lung involvement between the first and second wave of the pandemic and whether the notion of young population being more severely affected by the second wave holds true. Two-hundred (200) young patients (<40 years) with RT PCR documented COVID infections undergoing HRCT chest at our institute were included. Group A included young patients infected in the first wave (up to 28 February 2021) while Group B included patients beyond this date. Demographic and clinical data was obtained from the medical records department. HRCT scans were retrieved from the archive and were assessed by two radiologists or CT severity scoring. The mean severity scores were calculated and any statistical difference between Group A and B was sought. CT scans of four fully vaccinated patients were also evaluated.The age and gender distribution among the two groups was comparable. A greater number of patients in group B required hospital admission compared to group A (74% VS 53%). In group A, the mean severity score was 10.1 +/- 2.1 with 34 patients (34%) in mild category, 46 patients (46%) in moderate group and 20 patients (20%) in the severe group. In group B, the mean CT severity score was 12.6 +/- 2.3 with 20 patients (20%) in mild category, 42 patients (42%) in moderate group and 38 patients (38%) in the severe group.Lung involvement in young patients in the second wave is more severe requiring more hospital admissions. Vaccinated population may well have a milder form of the disease.

Role of big geospatial data in the COVID-19 crisis

The outbreak of the 2019 novel coronavirus disease (COVID-19) has infected 4 million people worldwide and has caused more than 300, 000 deaths worldwide. With infection and death rates on rise, COVID-19 poses a serious threat to social functioning, human health, economies, and geopolitics. Geographic information systems and big geospatial technologies have come to the forefront in this fight against COVID-19 by playing an important role by integrating multisourced data, enhanced and rapid analytics of mapping services, location analytics, and spatial tracking of confirmed, forecasting transmission trajectories, spatial clustering of risk on epidemiologic levels, public awareness on the elimination of panic spread and decision-making support for the government and research institutions for effective prevention and control of COVID-19 cases. Big geospatial data has turned itself as the major support system for governments in dealing with this global healthcare crisis because of its advanced and innovative technological capabilities from preparation of data to modeling the results with quick and large accessibility to every spatial scale. This robust data-driven system using the accurate and prediction geoanalysis is being widely used by governments and public health institutions interfaced with both health and nonhealth digital data repositories for mining the individual and regional datasets for breaking the transmission chain. Profiling of confirmed cases on the basis of location and temporality and then visualizing them effectively coupled with behavioral and critical geographic variables such as mobility patterns, demographic data, and population density enhance the predictive analytics of big geospatial data. With the intersection of artificial intelligence, geospatial data enables real-time visualization and syndromic surveillance of epidemic data based on spatiotemporal dynamics and the data are then accurately geopositioned. This chapter aims to reflect on the relevance of big geospatial data and health geoinformatics in containing and preventing the further spread of COVID-19 and how countries and research organizations around the world have used it as accurate, fast, and comprehensive dataset in their containing strategy and management of this public health crisis. China and Taiwan are used as case studies as in how these countries have applied the computational architecture of big geospatial data and location analytics surveillance techniques for prediction and monitoring of COVID-19-positive cases. © 2022 Elsevier Inc.

Advantages of Allometric Scaling Methods for Predicting Human Pharmacokinetics of Novel JAK Inhibitor -Baricitinib and Dose Extrapolation

The primary motive of this study was to examine advantages of allometry scaling strategies for correct prediction of pharmacokinetics of Baricitinib in human from preclinical species. Baricitinib is basically Janus kinase (JAK) inhibitor used for the treatment of rheumatoid arthritis. Currently approved by FDA in combination with remdesivir for treatment of COVID-19 hospitalized patient. The literature published pharmacokinetic parameters (Cl and Vd) of preclinical species (Rat, Dog and monkey) were utilized for the allometry scaling of Baricitinib. The connection among the primary pharmacokinetic parameters [Volume of distribution (Vd) and clearance (Cl)] and body weight (BW) were studied across three preclinical species, we used the double logarithmic plots for prediction of the human pharmacokinetic parameters i.e. Cl and Vd with use of simple allometry and with additional correction factors for better prediction. The dose extrapolation of baricitinib was carried out by FDA guidelines. By application of the allometric scaling methods and principles correlation was found to be satisfactory for the prediction of intravenous human Cl and Vd for baricitinib. The volume of distribution (Vd) predicted by simple allometry (65.3 L) was found to be in agreement with the reported value (75.5 L);clearance (Cl) prediction by simple allometry was found to be at least 1.06 -closer to the reported value (245 mL/min);CF were used to predict the clearance. Both brain weight (B.W) and maximum life span potential (MLP) predicted the Cl with 0.52- and 0.61 -fold difference. The application of monkey liver blood flow predicted Cl with 0.81 fold which was also in close agreement with reported value. The Cl prediction was also extrapolated using LBF (Liver blood flow) method and observed that the higher species (Dog and Monkey) have predicted Cl with better accuracy than rat. Overall, the simple allometry (SA), monkey liver blood flow (MLBF) and application of liver blood flow (LBF) methods showed excellent correlation with human. The time vs. plasma concentration simulated graph also showed the similar closeness with human profile. The inclusion of plasma protein binding factor didn't improve the prediction accuracy. The FIH dose extrapolation were showed that PK guided approach and exponent for BSA based approach was found closer to actual human dose of 4.0 mg/Kg. Oriental Scientific Publishing Company

Housing market price movements under tech industry expansion during COVID-19

Purpose This study aims to analyze the impact of technology-based corporation relocation on housing price indices during COVID-19 within the metropolitan areas of Austin, Texas and Seattle/Bellevue, Washington.The corporations under observation were Tesla and Amazon, respectively. The analysis intends to understand economic drivers behind the housing market and the radius of its effect while including fixed and random effects. Design/methodology/approach This study used a difference-in-difference (DID) method to evaluate changes in housing price index near and further away from Tesla's and Amazon's new corporate locations. The DID method allows for the capture of unique regional characteristics, as it requires a treatment and control group: housing price index and 5-mile and 10-mile search radii centered from the new corporate location. Findings The results indicated that corporate relocation announcements had a positive effect on housing price index post-pandemic. Specifically, the effect of Tesla's relocation in Austin on the housing price index was not concentrated near the relocation site, but beyond the 5- and 10-mile radii. For Seattle/Bellevue, the effect of Amazon's relocation announcement on housing price index was concentrated near the relocation site as well as beyond a 10-mile radius. Interestingly, these findings suggest housing markets incorporate speculation of prospective economic expansion linked with a corporate relocation. Originality/value Previous literature assessed COVID-19 housing market conditions and the economic effects of corporate relocation separately, whereas this study analyzed the housing price effects of corporate relocation during COVID-19. The DID method includes spatial and temporal analyses that allow for the impact of housing price to be observed across specified radii rather than a city-wide impact analysis.

Synthesis of novel 2,5-bis(substituted thio)-1,3,4-thiadiazoles by acid catalyzed intermolecular cyclization reactions of substituted dithiocarbazates as a possible 2019-nCoV main protease inhibitor

A convenient and facile synthesis of a privileged pharmaceutical scaffolds, 2,5-bis(substituted thio)-1,3,4-thiadiazoles is accomplished. The reaction of hydrazine hydrate with carbon disulfide and substituted alkyl/aryl chloride in basic medium yielded S-substituted alkyl/aryl dithiocarbazates in high yield. These dithiocarbazates on reaction with tetrafluoro acetic acid underwent a unique acid catalyzed intermolecular cyclization reaction to afford a novel 2,5-bis(substituted thio)-1,3,4-thiadiazoles. A simple procedure and high yields are the characteristic features of these reactions. These compounds are characterized on the basis of physico-chemical and spectral (FT-IR, ESI Mass, 1H, 13C and DEPT 135° 13C {1H} NMR) studies. Compound 2b crystallizes in orthorhombic system with point group P bca. Using the DFT/B3LYP/6–311 G (d,p) level of theory, HOMO-LUMO energy gap and molecular electrostatic potential (MEP) analyses were carried out. The HOMO-LUMO energy gap allowed the calculation of chemical hardness, chemical inertness, electronegativity and the electrophilicity index of the molecule, which depicted their potential kinetic stability and reactivity. The molecular docking studies of 2b-2e with 2019-nCoV main protease(7BRO) revealed binding free energies of (ΔGb) = -6.22, -5.38, -4.43 and -4.25 kcal mol−1 respectively. Docking study revealed that the aromatic congeners exhibit appreciable therapeutic efficiency to be used as 2019-nCoV main protease inhibitors. © 2021 Elsevier B.V.

The impact of COVID-19 on home value in major Texas cities

Purpose: This study aims to analyze the impact of COVID-19 on housing price within four major metropolitan areas in Texas: Austin, Dallas, Houston and San Antonio. The analysis intends to understand economic and mobility drivers behind the housing market under the inclusion of fixed and random effects. Design/methodology/approach: This study used a linear mixed effects model to assess the socioeconomic and housing and transport-related factors contributing to median home prices in four major cities in Texas and to capture unobserved factors operating at spatial and temporal level during the COVID-19 pandemic. Findings: The regression results indicated that an increase in new COVID-19 cases resulted in an increase in housing price. Additionally, housing price had a significant and negative relationship with the following variables: business cycle index, mortgage rate, percent of single-family homes, population density and foot traffic. Interestingly, unemployment claims did not have a significant impact on housing price, contrary to previous COVID-19 housing market related literature. Originality/value: Previous literature analyzed the housing market within the first phase of COVID-19, whereas this study analyzed the effects of the COVID-19 throughout the entirety of 2020. The mixed model includes spatial and temporal analyses as well as provides insight into how quantitative-based mobility behavior impacted housing price, rather than relying on qualitative indicators such as shutdown order implementation. © 2021, Emerald Publishing Limited.

Intercropping in Rice Farming under the System of Rice Intensification—An Agroecological Strategy for Weed Control, Better Yield, Increased Returns, and Social–Ecological Sustainability

Rice is the staple food for more than half of the world’s population. In South Asia, rice farming systems provide food to the majority of the population, and agriculture is a primary source of livelihood. With the demand for nutritious food increasing, introducing innovative strategies in farming systems is imperative. In this regard, intensification of rice farming is intricately linked with the challenges of water scarcity, soil degradation, and the vagaries of climate change. Agroecological farming systems like the System of Rice Intensification (SRI) have been proposed as water-saving and sustainable ways of food production. This study examines the effect of intercropping beans with rice under SRI management on the growth of weeds and on the different plant growth parameters. Intercropping led to a 65% decrease in weed infestation on average, which is important given that weed infestation is stated as a criticism of SRI in some circles and is a major factor in limiting yield in rice-producing regions. In addition to the water savings of about 40% due to the SRI methodology, the innovation led to an increase in rice yield by 33% and an increase in the net income of farmers by 57% compared to the conventional rice farming method. The results indicate that intercropping can be a positive addition to the rice farming system, hence contributing to social–ecological sustainability.

Technofunctional, rheological, thermal and structural properties of gorgon nut (Eurayle ferox) as affected by drying temperature

The effect of drying at different temperatures viz;60, 70, 80, and 90 degrees C on gorgon nut flour (GNF) was envisaged by the hot air oven method. The resultant flours were known as GNF-60, GNF-70, GNF-80, and GNF-90, respectively. The effect of drying on rheology and technofunctional properties was studied. The drying at different temperatures resulted in significant changes in technofunctional and pasting properties of GNF. The water and oil absorption capacities increased with the increase in drying temperature from 0.45 to 0.70 g/g and 0.35 to 0.46 g/g, respectively. The viscosity of the GNF decreased with the increase in drying temperature from 1592 to 990 cP. The increase in the drying temperature resulted in an increase in the swelling power and solubility from 7 to 11 g/g and 29% to 117%, respectively. The rise in temperature increased the gelatinisation peak temperature and reduced the gelatinization enthalpy.. The shear rate dependency on study shear stress and study shear viscosity showed a nonNewtonian behavior for all the samples. The storage modulus, G ' was found greater than the loss modulus, G '' and increased with the rise in temperature from 60 to 90 degrees C indicating the dominance of elastic behavior. The FTIR and XRD spectra revealed structural characteristic peaks with increased intensities at a higher temperature. The drying of the GNF at different temperatures is being reported for the first time and resulted in a significant alteration of the technofunctional and rheological properties. The study will serve a basis for the exploration of the GNF in industrial-related processing operations. Practical implications According to the report jointly published by the World Health Organization, Food and Agricultural Organization and the State of Food Security and Nutrition in the World, about 650 million of the total world's population went hungry in 2019, with the expected 120 million addition to this figure due to Covid-19 pandemic by the end of 2020. The economically lower class people are mainly involved in hunger and malnutrition due to either unavailability or higher costs of the nutritionally rich food resources. Exploration of underutilized and nutritionally rich sources becomes the need of the hour in this type of situation. Gorgon nut being a nutritionally rich and underutilized crop of mainly Asian continent, can serve as an affordable food source to fight this hunger and malnutrition problem.

Retrospective observational RT-PCR analyses on 688 babies born to 843 SARS-CoV-2 positive mothers, placental analyses and diagnostic analyses limitations suggest vertical transmission is possible.

RESEARCH QUESTION: Is there vertical transmission (from mother to baby antenatally or intrapartum) after SARS-CoV-2 (COVID-19) infected pregnancy? STUDY DESIGN: A systematic search related to SARS-CoV-2 (COVID-19), pregnancy, neonatal complications, viral and vertical transmission. The duration was from December 2019 to May 2020. RESULTS: A total of 84 studies with 862 COVID positive women were included. Two studies had ongoing pregnancies while 82 studies included 705 babies, 1 miscarriage and 1 medical termination of pregnancy (MTOP). Most publications (50/84, 59.5%), reported small numbers (<5) of positive babies. From 75 studies, 18 babies were COVID-19 positive. The first reverse transcription polymerase chain reaction (RT-PCR) diagnostic test was done in 449 babies and 2 losses, 2nd RT-PCR was done in 82 babies, IgM tests were done in 28 babies, and IgG tests were done in 28 babies. On the first RT-PCR, 47 studies reported time of testing while 28 studies did not. Positive results in the first RT-PCR were seen in 14 babies. Earliest tested at birth and the average time of the result was 22 hours. Three babies with negative first RT-PCR became positive on the second RT-PCR at day 6, day 7 and at 24 hours which continued to be positive at 1 week.Four studies with a total of 4 placental swabs were positive demonstrating SARS-CoV-2 localised in the placenta. In 2 studies, 10 tests for amniotic fluid were positive for SARS-CoV-2. These 2 babies were found to be positive on RT-PCR on serial testing. CONCLUSION: Diagnostic testing combined with incubation period and placental pathology indicate a strong likelihood that intrapartum vertical transmission of SARS-CoV-2 (COVID-19) from mother to baby is possible.

Burden of H1N1 influenza related mortality in a tertiary care centre

BACKGROUND: Influenza or the common flu is a commonly recognized cause of respiratory tract infection. A high level of clinical suspicion is required before a sample can be sent and often the diagnosis is established posthumously. In developing countries like India, data on disease burden of Influenza is severely lacking. It is a consequence of an under-estimation of Influenza as an important cause of illness and its natural course under-simplified to be a mild self-limiting illness. India was affected with a moderate severity compared to the other countries, although there was an insufficiency of epidemiological data from India during 2009 - 2010. Post-pandemic period, India was affected by major outbreaks in 2015 and 2017. We wanted to analyse the rate of positivity in a tertiary care centre amongst the total number of oropharyngeal swabs sent for Influenza virus testing. We also wanted to assess the mortality rate in Influenza positive cases in a tertiary care centre. METHODS: Data of oropharyngeal swabs sent for influenza virus testing through Real-Time Reverse Transcription Polymerase Chain Reaction from K.S. Hegde Medical Academy, Deralakatte was reviewed through a retrospective search of official influenza virus reports of Karnataka State along with the reports in Medical Records Department of K.S. Hegde Medical Academy in the time period of January 1^st 2016 to November 22^nd 2018. This study was done as a cross sectional retrospective study. RESULTS: Out of 127 oropharyngeal swabs that were sent during the study time period, 24 (18.9%) were positive for influenza virus. 18 (75%) cases were found to be H1N1 positive, 3 were H3N2 positive (seasonal strain) and remaining 3 were positive for Influenza B virus. 9 (37.5%) out of 24 cases of influenza succumbed to the disease, of which all were H1N1 positive (50% of the total H1N1 cases). CONCLUSIONS: H1N1 related mortality is a cause for concern for every healthcare providing institution. Influenza virus should be actively tested in patients with respiratory symptoms. During this COVID 19 related pandemic situation, there is a higher possibility of underdiagnosing H1N1. Lessons learnt from the past should be remembered and Influenza should not be neglected.

Support vector regression for predicting COVID-19 cases

This study uses the Machine Learning models to forecast the number of upcoming cases affected by COVID-19. Particularly two models for forecasting such as Support Vector Regression and Linear regression (LR)are used in this study to predict future number of cases of COVID-19. Number of upcoming covid-19 cases is going to be happen and deaths are predicted by using these two models for the next 365 days. The predictions are done for India and the worldwide. Between these two SVR is performing well compared with Linear Regression. © 2020 Ubiquity Press. All rights reserved.