Let’s Catch Up- Jan’21
COVID-19 UPDATE: From where we left
B.1.1.7, a new variant that is believed to be more contagious (increasing the reproduction number by 0.4-0.7) was detected in UK in September, and
eventually spread drastically in the country. There is yet no evidence of it having a more severe effect, however the variant has also been prevalent in USA, Canada, India and numerous other countries. Two more variants have been detected in South Africa and Brazil respectively, however have not entered the majorly affected countries yet.
UK regulators approved the Oxford-AstraZeneca’s Covishield vaccine, a cheaper and simpler alternative to its competitors, supposedly opening doors for middle-income countries to plan vaccine administration. Thereafter, India started planning the logistics of mega vaccine distribution of Covishield and Covaxin (Bharat Biotech) after their emergency approval was granted. However, as vaccination drives began, almost 50 countries with an estimated population of 7.8 billion people were left behind. Vaccines and drug development take years for a reason, and Pfizer vaccines’ adverse effects reported globally reiterated the need to distinguish between haste and urgency.
Simple, consistent and revolutionary
Hydrogels are used to maintain cells. 3-D models can provide physiological details and help study cell viability, proliferation and differentiation in a more descriptive and reliable manner.
Jellagel (Trademarked): A jellyfish derived collagen hydrogel was launched by JellaGen® Limited this month. This gel is consistent, naturally derived (non mammalian), easy to use and is all set to revolutionize research. Its biochemically simple property makes it almost inert when used to culture cells. Moreover, the gel’s storage is straightforward, removing the need of preserving it at low temperatures.
MIT RESEARCHERS STUDY VIRAL EVOLUTION AND ESCAPE
Viral escape, the ability for viruses to escape the immune response by mutation, has been a massive obstruction in vaccine development processes. MIT researchers created a model to predict which mutation can potentially lead to viral escape. By using a Machine Learning algorithm initially developed for human natural language, they could detect viruses that modified their look but sustained the infectivity, so as to bypass the immune system. This concept was synonymous to changing words to retain grammar coherency but changing the intent/meaning of the sentences. The researchers employed this on influenza A hemagglutinin, HIV-1 envelope glycoprotein, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein, and were able to accurately predict escape patterns.