Posted on by Dr. Francis Collins
At the end of last year, you may recall hearing news reports that the number of COVID-19 cases in the United States had topped 20 million. While that number came as truly sobering news, it also likely was an underestimate. Many cases went undetected due to limited testing early in the year and a large number of infections that produced mild or no symptoms.
Now, a recent article published in Nature offers a more-comprehensive estimate that puts the true number of infections by the end of 2020 at more than 100 million . That’s equal to just under a third of the U.S. population of 328 million. This revised number shows just how rapidly this novel coronavirus spread through the country last year. It also brings home just how timely the vaccines have been—and continue to be in 2021—to protect our nation’s health in this time of pandemic.
The work comes from NIH grantee Jeffrey Shaman, Sen Pei, and colleagues, Columbia University, New York. As shown above in the map, the researchers estimated the percentage of people who had been infected with SARS-CoV-2, the novel coronavirus that causes COVID-19, in communities across the country through December 2020.
To generate this map, they started with existing national data on the number of coronavirus cases (both detected and undetected) in 3,142 U.S. counties and major metropolitan areas. They then factored in data from the Centers for Disease Control and Prevention (CDC) on the number of people who tested positive for antibodies against SARS-CoV-2. These CDC data are useful for picking up on past infections, including those that went undetected.
From these data, the researchers calculated that only about 11 percent of all COVID-19 cases were confirmed by a positive test result in March 2020. By the end of the year, with testing improvements and heightened public awareness of COVID-19, the ascertainment rate (the number of infections that were known versus unknown) rose to about 25 percent on average. This measure also varied a lot across the country. For instance, the ascertainment rates in Miami and Phoenix were higher than the national average, while rates in New York City, Los Angeles, and Chicago were lower than average.
How many people were potentially walking around with a contagious SARS-CoV-2 infection? The model helps to answer this, too. On December 31, 2020, the researchers estimate that 0.77 percent of the U.S. population had a contagious infection. That’s about 1 in every 130 people on average. In some places, it was much higher. In Los Angeles, for example, nearly 1 in 40 (or 2.42 percent) had a SARS-CoV-2 infection as they rang in the New Year.
Over the course of the year, the fatality rate associated with COVID-19 dropped, at least in part due to earlier diagnosis and advances in treatment. The fatality rate went from 0.77 percent in April to 0.31 percent in December. While this is great news, it still shows that COVID-19 remains much more dangerous than seasonal influenza (which has a fatality rate of 0.08 percent).
Today, the landscape has changed considerably. Vaccines are now widely available, giving many more people immune protection without ever having to get infected. And yet, the rise of the Delta and other variants means that breakthrough infections and reinfections—which the researchers didn’t account for in their model—have become a much bigger concern.
Looking ahead to the end of 2021, Americans must continue to do everything they can to protect their communities from the spread of this terrible virus. That means getting vaccinated if you haven’t already, staying home and getting tested if you’ve got symptoms or know of an exposure, and taking other measures to keep yourself and your loved ones safe and well. These measures we take now will influence the infection rates and susceptibility to SARS-CoV-2 in our communities going forward. That will determine what the map of SARS-CoV-2 infections will look like in 2021 and beyond and, ultimately, how soon we can finally put this pandemic behind us.
 Burden and characteristics of COVID-19 in the United States during 2020. Pei S, Yamana TK, Kandula S, Galanti M, Shaman J. Nature. 2021 Aug 26.
COVID-19 Research (NIH)
Sen Pei (Columbia University, New York)
Jeffrey Shaman (Columbia University, New York)
Posted on by Dr. Francis Collins
Today, you may have opened a jar, done an upper body workout, played a guitar or a piano, texted a friend, or maybe even jotted down a grocery list longhand. All of these “skilled” arm, wrist, and hand movements are made possible by the bundled nerves, or circuits, running through a part of the central nervous system in the neck area called the cervical spine.
This video, which combines sophisticated imaging and computation with animation, shows the density of three types of nerve cells in the mouse cervical spine. There are the V1 interneurons (red), which sit between sensory and motor neurons; motor neurons associated with controlling the movement of the bicep (blue); and motor neurons associated with controlling the tricep (green).
At 4 seconds, the 3D animation morphs to show all the colors and cells intermixed as they are naturally in the cervical spine. At 8 seconds, the animation highlights the density of these three cells types. Notice in the bottom left corner, a light icon appears indicating the different imaging perspectives. What’s unique here is the frontal, or rostral, view of the cervical spine. The cervical spine is typically imaged from a lateral, or side, perspective.
Starting at 16 seconds, the animation highlights the location and density of each of the individual neurons. For the grand finale, viewers zoom off on a brief fly-through of the cervical spine and a flurry of reds, blues, and greens.
The video comes from Jamie Anne Mortel, a research assistant in the lab of Samuel Pfaff, Salk Institute, La Jolla, CA. Mortel is part of a team supported by the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative that’s developing a comprehensive atlas of the circuitry within the cervical spine that controls how mice control their forelimb movements, such as reaching and grasping.
This basic research will provide a better understanding of how the mammalian brain and spinal cord work together to produce movement. More than that, this research may provide valuable clues into better treating paralysis to arms, wrists, and/or hands caused by neurological diseases and spinal cord injuries.
As a part of this project, the Pfaff lab has been busy developing a software tool to take their imaging data from different parts of the cervical spine and present it in 3D. Mortel, who likes to make cute cartoon animations in her spare time, noticed that the software lacked animation capability. So she took the initiative and spent the next three weeks working after hours to produce this video—her first attempt at scientific animation. No doubt she must have been using a lot of wrist and hand movements!
With a positive response from her Salk labmates, Mortel decided to enter her scientific animation debut in the 2021 Show Us BRAINs! Photo and Video Contest. To her great surprise and delight, Mortel won third place in the video competition. Congratulations, and continued success for you and the team in producing this much-needed atlas to define the circuitry underlying skilled arm, wrist, and hand movements.
Spinal Cord Injury Information Page (National Institute of Neurological Disorders and Stroke/NIH)
Samuel Pfaff (Salk Institute, La Jolla, CA)
Show Us Your BRAINs! Photo and Video Contest (Brain Initiative/NIH)
NIH Support: National Institute of Neurological Disorders and Stroke
Posted on by Dr. Francis Collins
In days mostly gone by, it was fashionable in some circles for people to hand out calling cards to mark their arrival at special social events. This genteel human tradition is now being adapted to the lab to allow certain benign viruses to issue their own high-tech calling cards and mark their arrival at precise locations in the genome. These special locations show where there’s activity involving transcription factors, specialized proteins that switch genes on and off and help determine cell fate.
The idea is that myriad, well-placed calling cards can track brain development over time in mice and detect changes in transcription factor activity associated with certain neuropsychiatric disorders. This colorful image, which won first place in this year’s Show Us Your BRAINs! Photo and Video contest, provides a striking display of these calling cards in action in living brain tissue.
The image comes from Allen Yen, a PhD candidate in the lab of Joseph Dougherty, collaborating with the nearby lab of Rob Mitra. Both labs are located in the Washington University School of Medicine, St. Louis.
Yen and colleagues zoomed in on this section of mouse brain tissue under a microscope to capture dozens of detailed images that they then stitched together to create this high-resolution overview. The image shows neural cells (red) and cell nuclei (blue). But focus in on the neural cells (green) concentrated in the brain’s outer cortex (top) and hippocampus (two lobes in the upper center). They’ve been labelled with calling cards that were dropped off by adeno-associated virus .
Once dropped off, a calling card doesn’t bear a pretentious name or title. Rather, the calling card, is a small mobile snippet of DNA called a transposon. It gets dropped off with the other essential component of the technology: a specialized enzyme called a transposase, which the researchers fuse to one of many specific transcription factors of interest.
Each time one of these transcription factors of interest binds DNA to help turn a gene on or off, the attached transposase “grabs” a transposon calling card and inserts it into the genome. As a result, it leaves behind a permanent record of the interaction.
What’s also nice is the calling cards are programmed to give away their general locations. That’s because they encode a fluorescent marker (in this image, it’s a green fluorescent protein). In fact, Yen and colleagues could look under a microscope and tell from all the green that their calling card technology was in place and working as intended.
The final step, though, was to find out precisely where in the genome those calling cards had been left. For this, the researchers used next-generation sequencing to produce a cumulative history and map of each and every calling card dropped off in the genome.
These comprehensive maps allow them to identify important DNA-protein binding events well after the fact. This innovative technology also enables scientists to attribute past molecular interactions with observable developmental outcomes in a way that isn’t otherwise possible.
While the Mitra and Dougherty labs continue to improve upon this technology, it’s already readily adaptable to answer many important questions about the brain and brain disorders. In fact, Yen is now applying the technology to study neurodevelopment in mouse models of neuropsychiatric disorders, specifically autism spectrum disorder (ASD) . This calling card technology also is available for any lab to deploy for studying a transcription factor of interest.
This research is supported by the Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. One of the major goals of BRAIN Initiative is to accelerate the development and application of innovative technologies to gain new understanding of the brain. This award-winning image is certainly a prime example of striving to meet this goal. I’ll look forward to what these calling cards will tell us in the future about ASD and other important neurodevelopmental conditions affecting the brain.
 A viral toolkit for recording transcription factor-DNA interactions in live mouse tissues. Cammack AJ, Moudgil A, Chen J, Vasek MJ, Shabsovich M, McCullough K, Yen A, Lagunas T, Maloney SE, He J, Chen X, Hooda M, Wilkinson MN, Miller TM, Mitra RD, Dougherty JD. Proc Natl Acad Sci U S A. 2020 May 5;117(18):10003-10014.
 A MYT1L Syndrome mouse model recapitulates patient phenotypes and reveals altered brain development due to disrupted neuronal maturation. Jiayang Chen, Mary E. Lambo, Xia Ge, Joshua T. Dearborn, Yating Liu, Katherine B. McCullough, Raylynn G. Swift, Dora R. Tabachnick, Lucy Tian, Kevin Noguchi, Joel R. Garbow, John N. Constantino. bioRxiv. May 27, 2021.
Autism Spectrum Disorder (National Institute of Mental Health/NIH)
Dougherty Lab (Washington University School of Medicine, St. Louis)
Mitra Lab (Washington University School of Medicine)
Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative/NIH)
NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Center for Advancing Translational Sciences; National Human Genome Research Institute; National Institute of General Medical Sciences
Posted on by Dr. Francis Collins
Flip the image above upside down, and the shape may remind you of something. If you think it resembles a pyramid, then you and a lot of great neuroscientists are thinking alike. What you are viewing is a colorized, 3D reconstruction of a pyramidal tract, which are bundles of nerve fibers that originate from the brain’s cerebral cortex and relay signals to the brainstem or the spinal cord. These signals control many important activities, including the voluntary movement of our arms, legs, head, and face.
For a while now, it’s been possible to combine a specialized form of magnetic resonance imaging (MRI) with computer modeling tools to produce 3D reconstructions of complicated networks of nerve fibers, such as the pyramidal tract. Still, for technical reasons, the quality of these reconstructions has remained poor in parts of the brain where nerve fibers cross at angles of 40 degrees or less.
The video above demonstrates how adding a sophisticated algorithm, called Orientation Distribution Function (ODF)-Fingerprinting, to such modeling can help overcome this problem when reconstructing a pyramidal tract. It has potential to enhance the reliability of these 3D reconstructions as neurosurgeons begin to use them to plan out their surgeries to help ensure they are carried out with the utmost safety and precision.
In the first second of the video, you see gray, fuzzy images from a diffusion MRI of the pyramidal tract. But, very quickly, a more colorful, detailed 3D reconstruction begins to appear, swiftly filling in from the top down. Colors are used to indicate the primary orientations of the nerve fibers: left to right (red), back to front (green), and top to bottom (blue). The orange, magenta, and other colors represent combinations of these primary directional orientations.
About three seconds into the video, a rough draft of the 3D reconstruction is complete. The top of the pyramidal tract looks pretty good. However, looking lower down, you can see distortions in color and relatively poor resolution of the nerve fibers in the middle of the tract—exactly where the fibers cross each other at angles of less than 40 degrees. So, researchers tapped into the power of their new ODF-Fingerprinting software to improve the image—and, starting about nine seconds into the video, you can see an impressive final result.
The researchers who produced this amazing video are Patryk Filipiak and colleagues in the NIH-supported lab of Steven Baete, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York. The work paired diffusion MRI data from the NIH Human Connectome Project with the ODF-Fingerprinting algorithm, which was created by Baete to incorporate additional MRI imaging data on the shape of nerve fibers to infer their directionality .
This innovative approach to imaging recently earned Baete’s team second place in the 2021 “Show Us Your BRAINs” Photo and Video contest, sponsored by the NIH-led Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative. But researchers aren’t stopping there! They are continuing to refine ODF-Fingerprinting, with the aim of modeling the pyramidal tract in even higher resolution for use in devising new and better ways of helping people undergoing neurosurgery.
 Fingerprinting Orientation Distribution Functions in diffusion MRI detects smaller crossing angles. Baete SH, Cloos MA, Lin YC, Placantonakis DG, Shepherd T, Boada FE. Neuroimage. 2019 Sep;198:231-241.
Human Connectome Project (University of Southern California, Los Angeles)
Steven Baete (Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York)
Show Us Your BRAINs! Photo and Video Contest (BRAIN Initiative/NIH)
NIH Support: National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Cancer Institute
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