Category: News Commentary

Vaccine hesitancy continues to be a hurdle in the development of widespread immunity within the U.S. population as the COVID-19 pandemic enters its second year.

Researchers at the University of Cincinnati College of Medicine have developed a computerized decision analytic model to compare projected outcomes of three vaccine strategies:

The second dose of a COVID-19 vaccine induces a powerful boost to a part of the immune system that provides broad antiviral protection, according to a study led by investigators at the Stanford University School of Medicine.

The finding strongly supports the view that the second shot should not be skipped.

Antimicrobials are used to kill or slow the growth of bacteria, viruses and other microorganisms. They can be in the form of antibiotics, used to treat bodily infections, or as an additive or coating on commercial products used to keep germs at bay. These life-saving tools are essential to preventing and treating infections in humans, animals and plants, but they also pose a global threat to public health when microorganisms develop resistance to them, a concept known as antimicrobial resistance.

A single dose of the Sputnik V vaccine may elicit significant antibody responses against SARS-CoV-2, finds a study published July 13 in the journal Cell Reports Medicine.

“Due to limited vaccine supply and uneven vaccine distribution in many regions of the world, health authorities urgently need data on the immune response to vaccines to optimize vaccination strategies,” says senior author Andrea Gamarnik of the Fundación Instituto Leloir-CONICET in Buenos Aires, Argentina.

In a new study of adults from the general population who were infected with COVID-19 in 2020, more than a quarter report not having fully recovered after six to eight months. Those findings are described this week in the open-access journal PLOS ONE by Milo Puhan and colleagues at the University of Zurich, Switzerland.

Writing in the July 12, 2021 online issue of Nature Communications, researchers at University of California San Diego School of Medicine describe a new approach that uses machine learning to hunt for disease targets and then predicts whether a drug is likely to receive FDA approval.