RSTV: SCIENCE MONITOR 22.05.2021 – INSIGHTSIAS



Scientists at DRDO-INMAS develop the first anti-COVID therapeutic application of 2DG:

• An anti-COVID-19 therapeutic application of the drug 2-deoxy-D-glucose (2-DG) has been developed by Institute of Nuclear Medicine and Allied Sciences (INMAS), a lab of DRDO.
• Clinical trial results have shown that this molecule helps in faster recovery of hospitalised patients and reduces supplemental oxygen dependence.
• Higher proportion of patients treated with 2-DG showed RT-PCR negative conversion in COVID patients. The drug will be of immense benefit to the people suffering from COVID-19.
• Scientists conducted laboratory experiments with the help of Centre for Cellular and Molecular Biology (CCMB), Hyderabad and found that this molecule works effectively against SARS-CoV-2 virus and inhibits the viral growth.
• Based on these results, Drugs Controller General of India’s (DCGI) Central Drugs Standard Control Organization (CDSCO) permitted Phase-II clinical trial of 2-DG in COVID-19 patients in May 2020.
• In Phase-II trials (including dose ranging) conducted during May to October 2020, the drug was found to be safe in COVID-19 patients and showed significant improvement in their recovery.
• In efficacy trends, the patients treated with 2-DG showed faster symptomatic cure than Standard of Care (SoC) on various endpoints. A significantly favourable trend (2.5 days difference) was seen in terms of the median time to achieving normalisation of specific vital signs parameters when compared to SoC.
• In 2-DG arm, significantly higher proportion of patients improved symptomatically and became free from supplemental oxygen dependence (42% vs 31%) by Day-3 in comparison to SoC, indicating an early relief from Oxygen therapy/dependence.
• The similar trend was observed in patients aged more than 65 years.
• The drug comes in powder form in sachet, which is taken orally by dissolving it in water. It accumulates in the virus infected cells and prevents virus growth by stopping viral synthesis and energy production. Its selective accumulation in virally infected cells makes this drug unique.

Pune based startup develops Cov-Tech Ventilation System for PPE kit user:

• Health workers may soon be relieved of sweating out long hours in heavy suffocating PPE kits to meet their busy duty schedules.
• A compact, economical ventilation system for PPE kits developed by a Pune based startup can prevent excessive sweating while wearing such kits.
• The ventilation system when attached with the conventional PPE kits with one simple modification, keeps the health workers’ well ventilated preventing not only bodily discomforts but also possible fungal diseases in the body.
• The ‘Cov-Tech Ventilation System’ can be fastened over the waist just like a simple belt over which the traditional PPE is worn and can provide comfort to the doctors and medical practitioners working in the hospitals to treat Covid infected patients.
• The design of the ventilation system ensures a complete air seal from the PPE kit. It provides a breeze of fresh air to the user in a gap of just 100 seconds.
• The result was a compact, portable, and user-friendly device to provide a ventilation system for PPE suits. The Covtech Ventilation system is being used in Sai Sneh hospital, Pune and Lotus Multi- Specialty hospital, Pune and the company plans to scale up the uses by May/June.

Inexpensive COVID 19 test kits develop by startup supported by DST:

• Mumbai-based startup is ready with its affordable Rapid Antigen Test that offers COVID 19 diagnosis & surveillance at the cost of Rs 100 per test.
• The test developed will complement the gold standard RTPCR & Rapid antigen tests and make it one of the most affordable ones available in the market.
• The Centre for Augmenting WAR with COVID-19 Health Crisis (CAWACH), an initiative by the Department of Science and Technology (DST), supported the startup in July 2020 to develop Rapid Covid 19 diagnostics (both Rapid antibody and antigen tests for surveillance and early diagnosis of Covid- 19, respectively).
• The startup plans to launch the rapid Covid-19 antigen tests in 2021.
• The Rapid covid-19 tests (~10-15 minutes) would be helpful for early diagnosis of Covid-19 in rural areas, doctor’s clinics, and resource constraint areas where pathology and diagnostic labs are not available. The test is affordable and would be helpful to control the pandemic.

Indian astronomers develop AI-ML based algorithm to identify stars among clusters:

• Indian Astronomers have developed a new method based on Machine Learning that can identify cluster stars assembly of stars physically related through common origin, with much greater certainty. The method can be used on clusters of all ages, distances, and densities.
• The method has been used to identify hundreds of additional stars for six different clusters up to 18000 light-years away and uncover peculiar stars.
• Studying stars and how they evolve is the cornerstone of astronomy. But understanding them is difficult since they are observed at different ages. A star cluster is, therefore, a great place to study stars.
• All stars in a star cluster have approximately the same age and chemistry, so any differences seen can be attributed to the peculiarities in individual stars with certainty. As the clusters are part of the Milky Way, there are many stars between us and the cluster, so it isn’t easy to identify and select the stars of a particular cluster.
• IIA team identified the crucial measurements for this task and understood the complex relationship between these parameters, using a machine learning technique called Probabilistic Random Forest.
• This uses a combination of parallax, proper motion, temperature, brightness and other parameters to classify each star as a cluster member or a non-member. The IIA team trained their algorithm using the most likely members from a model called the Gaussian Mixture Model, which can identify clumps of co-moving stars.
• The Probabilistic Random Forest algorithm then learns how to identify a typical cluster member star and efficiently takes out stars that share only similar proper motions or only similar velocities as the cluster itself. They used 10 parameters to identify members, after performing a trade study of all available parameters in the catalogue.
• The newly developed method can now identify cluster stars with much greater certainty and pinpoint individual stars that behave differently from their siblings. The team will apply the algorithms to more clusters in the future.
• Manual identification of stars belonging to a star-cluster is a daunting task owing to an armload of data to be analyzed. The new Artificial Intelligence based algorithm is very promising in automating and greatly speeding this process and may also find uses in other areas of analysis of patterns in biology and materials science.