As new coronavirus variants sweep across the world, scientists are racing to understand how dangerous they could be. WSJ explains. Illustration: Alex Kuzoian/WSJ
Messenger RNA—or mRNA—vaccines have been in development for decades, and are now approved for use against COVID-19. Here’s how they work and what you should know about them. Visit https://www.jhsph.edu/covid-19 for even more resources.
Over the course of the pandemic, scientists have been monitoring emerging genetic changes to Sars-Cov-2. Mutations occur naturally as the virus replicates but if they confer an advantage – like being more transmissible – that variant of the virus may go on to proliferate.
This was the case with the ‘UK’ or B117 variant, which is about 50% more contagious and is rapidly spreading around the country. So how does genetic surveillance of the virus work? And what do we know about the new variants? Ian Sample speaks to Dr Jeffrey Barrett, the director of the Covid-19 genomics initiative at the Wellcome Sanger Institute, to find out Coronavirus – latest updates See all our coronavirus coverage.
From the race to roll-out coronavirus vaccinations around the world, to other concerns such as mental health and measles, BBC Health Reporter Smitha Mundasad looks at the health challenges facing the world in the next year.
Stephen Hahn, U.S. Food and Drug Administration Commissioner, Sigal Atzmon, founder and chief executive officer of Medix Global, and Roche CEO Severin Schwan, on the pandemic, Covid-19 vaccines and the new mutation.
Stroke is far more common than you might realize, affecting more than 795,000 people in the U.S. every year. It is a leading cause of death and long-term disability. Yet until now, treatment options have been limited, despite the prevalence and severity of stroke.
Not so long ago, doctors didn’t have much more to offer stroke victims than empathy, says Kevin Sheth, MD, Division Chief of Neurocritical Care and Emergency Neurology. “There wasn’t much you could do.” But that is changing. Recent breakthroughs offer new hope to patients and families. Beating the Clock Think of stroke as a plumbing problem in the brain. It occurs when there is a disruption of blood flow, either because of a vessel blockage (ischemic stroke) or rupture (hemorrhagic stroke).
In both cases, the interruption of blood flow starves brain cells of oxygen, causing them to become damaged and die. Delivering medical interventions early after a stroke can mean the difference between a full recovery and significant disability or death. Time matters. Unfortunately, stroke care often bottlenecks in the first stage: diagnosis. Sometimes, it’s a logistical issue; to identify the type, size, and location of a stroke requires MRI imaging, and the machinery itself can be difficult to access.
MRIs use powerful magnets to create detailed images of the body, which means they must be kept in bunker-type rooms, typically located in hospital basements. As a result, there is often a delay in getting MRI scans for stroke patients. Dr. Sheth collaborated with a group of doctors and engineers to develop a portable MRI machine. Though it captures the images doctors need to properly diagnose stroke, it uses a less powerful magnet. It is lightweight and can be easily wheeled to a patient’s bedside.
“It’s a paradigm shift – from taking a sick patient to the MRI to taking an MRI to a sick patient,” says Dr. Sheth. Stopping the Damage Once a stroke has been diagnosed, the work of mitigating the damage can begin. “Brain tissue is very vulnerable during the first hours after stroke,” says vascular neurologist Nils Petersen, MD. He and his team are using advanced neuro-monitoring technology to study how to manage a patient’s blood pressure in the very acute phase after a stroke.
Dr. Petersen’s research shows that optimal stroke treatment depends on personalization of blood pressure parameters. But calculating the ideal blood pressure for the minutes and hours after a patient has a stroke can be complicated. It depends on a variety of factors—it is not a one-size-fits-all scenario. Harnessing the Immune System Launching an inflammatory reaction is how the body responds to injury anywhere in the body – including the brain, following stroke. However, in this case, the resulting inflammation can sometimes cause even more damage.
But what if that immune response could be used to the patient’s advantage? “We’re trying to understand how we can harness the immune system’s knowledge about how to repair tissues after they’ve been injured,” says Lauren Sansing, MD, Academic Chief of the Division of Stroke and Vascular Neurology. Her team is working to understand the biological signals guiding the immune response to stroke.
That knowledge can then direct the development of targeted therapeutics for the treatment of stroke that minimize early injury and enhance recovery. “We want to be able to lead research efforts that change the lives of patients around the world,” says Dr. Sansing.
Learn about these developments and more in the video above.
In this episode of the JIM Podcast, Editor-in-Chief Richard McCallum speaks with David Cistola of Texas Tech University Health Sciences Center El Paso about American Diabetes Month.
Finding medicines that can kill cancer cells while leaving normal tissue unscathed is a Holy Grail of oncology research. In two new papers, scientists at UC San Francisco and Princeton University present complementary strategies to crack this problem with “smart” cell therapies—living medicines that remain inert unless triggered by combinations of proteins that only ever appear together in cancer cells.
Biological aspects of this general approach have been explored for several years in the laboratory of Wendell Lim, PhD, and colleagues in the UCSF Cell Design Initiative and National Cancer Institute– sponsored Center for Synthetic Immunology. But the new work adds a powerful new dimension to this work by combining cutting-edge therapeutic cell engineering with advanced computational methods.
For one paper, published September 23, 2020 in Cell Systems, members of Lim’s lab joined forces with the research group of computer scientist Olga G. Troyanskaya, PhD, of Princeton’s Lewis-Sigler Institute for Integrative Genomics and the Simons Foundation’s Flatiron Institute. Using a machine learning approach, the team analyzed massive databases of thousands of proteins found in both cancer and normal cells. They then combed through millions of possible protein combinations to assemble a catalog of combinations that could be used to precisely target only cancer cells while leaving normal ones alone.
In another paper, published in Science on November 27, 2020, Lim and colleagues then showed how this computationally derived protein data could be put to use to drive the design of effective and highly selective cell therapies for cancer. “Currently, most cancer treatments, including CAR T cells, are told ‘block this,’ or ‘kill this,’” said Lim, also professor and chair of cellular and molecular pharmacology and a member of the UCSF Helen Diller Family Comprehensive Cancer Center.
“We want to increase the nuance and sophistication of the decisions that a therapeutic cell makes.” Over the past decade, chimeric antigen receptor (CAR) T cells have been in the spotlight as a powerful way to treat cancer.
In CAR T cell therapy, immune system cells are taken from a patient’s blood, and manipulated in the laboratory to express a specific receptor that will recognize a very particular marker, or antigen, on cancer cells. While scientists have shown that CAR T cells can be quite effective, and sometimes curative, in blood cancers such as leukemia and lymphoma, so far the method hasn’t worked well in solid tumors, such as cancers of the breast, lung, or liver.
Cells in these solid cancers often share antigens with normal cells found in other tissues, which poses the risk that CAR T cells could have off-target effects by targeting healthy organs. Also, solid tumors also often create suppressive microenvironments that limit the efficacy of CAR T cells. For Lim, cells are akin to molecular computers that can sense their environment and then integrate that information to make decisions. Since solid tumors are more complex than blood cancers, “you have to make a more complex product” to fight them, he said.
It has taken time — some say far too long — but medicine stands on the brink of an AI revolution. In a recent article in the New England Journal of Medicine, Isaac Kohane, head of Harvard Medical School’s Department of Biomedical Informatics, and his co-authors say that AI will indeed make it possible to bring all medical knowledge to bear in service of any case.
Properly designed AI also has the potential to make our health care system more efficient and less expensive, ease the paperwork burden that has more and more doctors considering new careers, fill the gaping holes in access to quality care in the world’s poorest places, and, among many other things, serve as an unblinking watchdog on the lookout for the medical errors that kill an estimated 200,000 people and cost $1.9 billion annually.
“I’m convinced that the implementation of AI in medicine will be one of the things that change the way care is delivered going forward,” said David Bates, chief of internal medicine at Harvard-affiliated Brigham and Women’s Hospital, professor of medicine at Harvard Medical School and of health policy and management at the Harvard T.H. Chan School of Public Health. “It’s clear that clinicians don’t make as good decisions as they could. If they had support to make better decisions, they could do a better job.”