The TRIPS Waiver Decision at the World Trade Organization: Too Little Too Late!

The recently adopted Trade-Related Aspects of Intellectual Property Rights (TRIPS) waiver decision at the World Trade Organization is a grossly inadequate and insincere response to the COVID-19 pandemic. This paper criticizes the TRIPS waiver for being faulty on several fronts such as: excluding COVID-19 diagnostics and therapeutics from its fold and focusing only on COVID-19 vaccines;restricting its coverage to only patents and leaving out other intellectual property rights;excluding developed countries that possess manufacturing and technological capability from being eligible exporters of COVID-19 vaccines;and its perplexing silence on the transfer of technology. It will have negligible impact on fighting the pandemic, sets an enfeebled example for the future, and is a classic case of too little too late. Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of the Asian Society of International Law.

Computational study of some potential inhibitors of COVID-19: A DFT analysis

Background: There is an urgent demand of drug or therapy to control the COVID-19. Until July 22, 2021 the worldwide total number of cases reported is more than 192 million and the total number of deaths reported is more than 4.12 million. Several countries have given emergency permission for use of repurposed drugs for the treatment of COVID-19 patients. This report presents a computational analysis on repurposing drugs-tenofovir, bepotastine, epirubicin, epoprostenol, tirazavirin, aprepitant and valrubicin, which can be potential inhibitors of the COVID-19.Method: Density functional theory (DFT) technique is applied for computation of these repurposed drug. For geometry optimization, functional B3LYP/6-311G (d, p) is selected within DFT framework.Results: DFT based descriptors-highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap, molecular hardness, softness, electronegativity, electrophilicity index, nucleophilicity index and dipole moment of these species are computed. IR and Raman activities are also analysed and studied. The result shows that the HOMO-LUMO gap of these species varies from 1.061 eV to 5.327 eV. Compound aprepitant with a HOMO-LUMO gap of 1.419 eV shows the maximum intensity of IR (786.176 km mol-1) and Raman spectra (15036.702 a.u.).Conclusion: Some potential inhibitors of COVID-19 are studied by using DFT technique. This study shows that epirubicin is the most reactive compound whereas tenofovir is found to be the most stable. Further analysis and clinical trials of these compounds will provide more insight.

Utility of nasal swabs as samples for the diagnosis of Mucormycosis using molecular methods for detection

Objectives: Mucormycosis is an aggressive, life-threatening infection caused by fungi in the order Mucorales. There was an explosion of new cases of rhino-sino-orbital mucormycosis following the COVID pandemic in India, and the need for easy and rapid diagnostics was felt. The current diagnosis of mucormycosis relies on mycological cultures, radiology, and histopathology. These methods lack sensitivity and are most definitive later in the course of infection, resulting in the failure of timely intervention. A real-time multiplex PCR platform is commercially available for the detection of Rhizopus spp., Mucor spp.Rhizomucor spp., Lichtheimia spp., and Cunninghamella spp. (PN-700, MucorGenius , PathoNostics , Maastricht, The Netherlands) This real-time PCR has been validated to identify these fungal pathogens from bronchoalveolar lavage, tissue, and serum samples. This study aimed to validate this PCR-based system to detect Mucorales from nasal swab samples and evaluate its utility in the detection of Mucorales from nasal cavities of high-risk patients developing signs and symptoms of mucormycosis. Method(s): A single-center cross-sectional observational study was conducted on 50 hospitalized adult patients with signs and symptoms of mucormycosis. Nasal swabs were taken for PCR analysis once there was a clinical suspicion and were com-pared with the results of the gold standard.The gold standard for the diagnosis of mucormycosis was the conventional method (KOHmountedmicroscopy/HPE).Demographicdetails andrisk factorsfor thesepatients wererecorded, andthe RTPCR-based test was run on the nasal swab samples of all these 50 patients. The workflow is depicted graphically in Fig. 1 (Created with BioRender.com). Result(s): The study population mean (SD) age was 50 (16) years and consisted of 32 (64%) males. A total of 39 (78%) patients were known cases of diabetes mellitus, 48 (96%) patients had amphotericin B intake, and 20 (40%) had posaconazole intake. In all, 21 (42%) patients had a past history of COVID-19 infection;14 patients had received steroids and 10 patients received oxygen support. PCR for Mucorales was positive in 15 (30%) patients while the KOH mount was positive in 4 (8%) patients. Conclusion(s): These results are not encouraging for the use of nasal swabs as the sample for diagnosis of mucormyco-sis. Though the PCR performed better on the swab samples than KOH preparation and culture techniques, it highlights the importance of using standard sampling methods.

A review: Machine learning approaches in the diagnosis of infectious diseases

Infectious diseases are a group of medical conditions caused by infectious agents such as parasites, bacteria, viruses, or fungus. Patients who are undiagnosed may unwittingly spread the disease to others. Because of the transmission of these agents, epidemics, if not pandemics, are possible. Early detection can help to prevent the spread of an outbreak or put an end to it. Infectious disease prevention, early identification, and management can be aided by machine learning (ML) methods. The implementation of ML algorithms such as logistic regression, support vector machine, Naive Bayes, decision tree, random forest, K-nearest neighbor, artificial neural network, convolutional neural network, and ensemble techniques to automate the process of infectious disease diagnosis is investigated in this study. We examined a number of ML models for tuberculosis (TB), influenza, human immunodeficiency virus (HIV), dengue fever, COVID-19, cystitis, and nonspecific urethritis. Existing models have constraints in data handling concerns such data types, amount, quality, temporality, and availability. Based on the research, ensemble approaches, rather than a typical ML classifier, can be used to improve the overall performance of diagnosis. We highlight the need of having enough diverse data in the database to create a model or representation that closely mimics reality. © 2022, Institute of Advanced Engineering and Science. All rights reserved.

A Comprehensive Mobile Tele-consultation Solution for Tertiary Hospitals in India

The recent outbreak of the COVID-19 pandemic resulted in the suspension of outpatient services in various hospitals and healthcare facilities, including tertiary hospitals. This has elicited interest in development of novel, low-cost solutions with a quick turnaround time for tele-consultation that patients can use to consult with doctors using mobile devices. This paper presents the design, development and implementation perspectives for such a tele-consultation system developed for tertiary care hospitals in India. The comprehensive application includes workflows for patients, doctors and healthcare workers on both web and mobile devices. Patients or healthcare workers can raise tele-consultation requests that can be approved by doctors. Consultation through video-calling and Electronic Health Record (EHR) compliant clinical prescriptions can be generated from the solution using clinician's speech. It has been deployed at various tertiary hospitals in India on a pilot basis and the deployment outcomes indicate positive acceptance and adoption of the solution. The paper also focuses on emerging technologies that can be integrated with such solutions, including blockchain based Electronic Health Records (EHR) management and cloud-based deployments that leverage advances in communication networks such as enhanced Mobile Broadband (eMBB) and low-latency provisions in 5G for improving Quality of Service (QoS) and user experience. © 2022 IEEE.

Impact of COVID-19 lockdown on real-time DO-BOD variation of river Ganga

A comparative assessment of dissolved oxygen (DO) and biochemical oxygen demand (BOD) of river Ganga during prelockdown and lockdown periods was made through analysis of data generated from real-time water quality motoring systems. The concentration data for DO and BOD are examined for (i) prelockdown period (March 15-21, 2020) and (ii) lockdown period (March 22-April 15, 2020). The analysis results show 3%-20% decrease in DO concentration. The slight decrease in DO observed at all locations during the first week after lockdown which may be due to the increased levels of suspended solids and turbidity in the river water because of heavy rains. DO during fourth week of lockdown has shown a decreased value as compared to the prelockdown period at most of the locations. However, in West Bengal the DO has increased in lockdown. BOD value ranged between 1.13 mg/L and 5.56 mg/L during lockdown period, more or less similar to prelockdown range of 1.37-5.58 mg/L. This chapter further discusses the cause of water quality changes during the period of lockdown as compare to prelockdown period. © 2021 Elsevier Inc.

Kloman Metre: An EMD-Based Tool for Triaging Diseases Leading to Lung Infections Including COVID-19

The digital revolution can help developing countries to overcome the problem of limited healthcare infrastructure in developing nations such as India. The COVID-19 pandemic has shown the urgency of integration of digital technologies into healthcare infrastructure. In order to solve the issue of lack of trained healthcare professionals at public health centres (PHCs), researchers are trying to build tools which can help to tag pulmonary ailment within a fraction of second. Such tagging will help the medical community to utilize their time more efficiently. In this work, we have tried to assess the “lung health” of patients suffering from a variety of pulmonary diseases including COVID-19, tuberculosis and pneumonia by applying Earth Mover’s Distance algorithm to the X-ray images of the patients. The lung X-ray images of patients suffering from pneumonia, TB and COVID-19 and healthy persons are pooled together from various datasets. Our preliminary data based upon 100 random images depicting each type of lung disease such as COVID-19, tuberculosis and pneumonia revealed that patients suffering from tuberculosis have the highest severity as per the values obtained from the EMD scale. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Is blended learning better than online learning for b.Ed students?

Blended learning is a newly emerging area of research and practice in educational institutions. It is defined as a useful and reasonable combination of online and face-to-face learning and is acclaimed as a successful mode of teaching. The recent growth of online education, which is without classroom interaction, in a developing country like India therefore presents a reason to verify the relative effectiveness of these teaching modes. This study was an experimental study spread over two years, to compare the effectiveness of the blended learning mode and the online learning modes (including their specific teaching-learning strategies) for a B.Ed curriculum. A randomly selected sample of students with a comparable level of intelligence quotient (IQ) was subjected to both controlled (face-to-face) and experimental treatments (online and blended learning). The participants were the students of a predominantly face-to-face mode of a B.Ed Course. The researcher found that the average achievement scores of the blended learning mode were higher than the online learning mode. It appears that the interaction of the instructor and the learners was a critical factor for the better performance of blended learning. This research also suggests that blended learning resulted in better learning attainment and motivation. Blended learning has potential to support learner-centric teaching-learning endeavours. It is an important finding for the emerging trend towards online learning in India. It is also relevant in the context of the conditions created by the COVID-19 pandemic, which has put constraints on the face-to-face mode of teaching. © 2020, Commonwealth of Learning. All rights reserved.