The Daily Dose: Who needs Superwoman or Captain Marvel when you have female scientists?

Who needs Superwoman or Captain Marvel when you have female scientists? A almost all-female team, led by virologist Minal Dakhave Bhosale, developed and designed a COVID-19 test for use in India in record time. Per The Scientist, “Bhosale and her colleagues drew on their experience developing DNA and RNA tests for applications in clinical, veterinary, and food safety settings, and also on the work of researchers who had studied the SARS family of viruses extensively in the past. Following the World Health Organization guidelines for COVID-19 tests, Bhosale and colleagues put together the reagents they’d need to extract nucleic acids from patient samples and to carry out real time PCR.” Not only that, hours after finalizing the test, Bhosale went to the hospital and had a baby. Let’s see a man do that.

Vaccine nationalism? It may actually be a thing. While the most prudent thing to do with any COVID-19 vaccine that comes to fruition would be to prioritize healthcare and other frontline workers, emerging trends indicate that it might not happen. According to an article in Science, “Yet money and national interest may win out. The United States and Europe are placing advance orders for hundreds of millions of doses of successful vaccines, potentially leaving little for poorer parts of the world. ‘I’m very concerned,’ says John Nkengasong, director of the Africa Centres for Disease Control and Prevention.”

While we’re on the subject of money, the Trump Administration has thrown the mother of all lifelines to a former photography giant. Per CNBC, “Eastman Kodak shares soared on Wednesday after President Donald Trump announced a deal to work with the photography pioneer to produce ingredients in generic drugs in response to the coronavirus pandemic… Shares of Kodak skyrocketed more than 570%.” We’d like to see Kodak succeed and are pulling for them. The U.S. could also use the pharmaceutical manufacturing boost, as well.

The natural production of active pharmaceutical agents in plants is well known, but for the most part, not well understood. One example is the plant Gloriosa superba, known for making colchicine. A team of researchers studied how the so-called fire lily synthesizes the notoriously complex molecule. As per Nature, “The authors identify eight G. superba genes that encode a series of specialized metabolic enzymes, which collectively convert 1-phenethylisoquinoline, a compound produced early in the biosynthetic pathway, to N-formyldemecolcine, the first colchicine precursor that harbours the natural product’s signature molecular scaffold. The study not only reveals the ingenuity of plant biosynthesis, but also opens the way to the development of metabolically engineered organisms that make colchicine more efficiently than do its natural producers.” Colchicine is used to treat gout.

Modelling has been in the popular spotlight lately thanks to the COVID-19 pandemic. Reliance on computer simulations extends way past epidemiology, though. A recent study investigated how well life trajectory models succeed in predicting people’s futures. The researchers investigated the question with a scientific mass collaboration using the common task method. Over a hundred teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study. According to the Proceedings of the National Academy of Sciences journal, “Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.” It’s important to remember that models should not be considered reality or even representative of it. As the saying goes, “All models are wrong, but some may be useful.”


IMAGE SOURCE: Creative Commons

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