In a new study in mice, a team of researchers from UCLA, the Swiss Federal Institute of Technology, and Harvard University have uncovered a crucial component for restoring functional activity after spinal cord injury. The neuroscientists have shown that re-growing specific neurons back to their natural target regions led to recovery, while random regrowth was not effective.
In a 2018 study published in Nature, the team identified a treatment approach that triggers axons —the tiny fibers that link nerve cells and enable them to communicate—to regrow after spinal cord injury in rodents. But even as that approach successfully led to the regeneration of axons across severe spinal cord lesions, achieving functional recovery remained a significant challenge.
In a new study, published in Science, the team aimed to determine whether directing the regeneration of axons from specific neuronal subpopulations to their natural target regions could lead to meaningful functional restoration after spinal cord injury in mice. They first used advanced genetic analysis to identify nerve cell groups that enable walking improvement after a partial spinal cord injury.
To make a gene-editing tool more precise and easier to control, Rice University engineers split it into two pieces that only come back together when a third small molecule is added.
Researchers in the lab of chemical and biomolecular engineer Xue Sherry Gao created a CRISPR-based gene editor designed to target adenine ⎯ one of the four main DNA building blocks ⎯ that remains inactive when disassembled but kicks into gear once the binding molecule is added.
Compared to the intact original, the split editor is more precise and stays active for a narrower window of time, which is important for avoiding off-target edits. Moreover, the activating small molecule used to bind the two pieces of the tool together is already being used as an anticancer and immunosuppressive drug.
Still seems unsafe to me until its 100% error free, but step in correct direction at least.
Researchers have found that splitting the gene editor used in traditional CRISPR technology creates a more precise tool that can be switched on and off, with significantly less chance of causing unintended genome mutations. They say their novel tool can potentially correct around half of the mutations that cause disease.
CRISPR is one of those scientific terms that has made it into the everyday lexicon. Arguably one of the biggest discoveries of the 21st century, the gene-editing tool has revolutionized research and the treatment of genetic and non-genetic diseases. But the primary risk associated with CRISPR technology is ‘off-target edits,’ namely unexpected, unwanted, or even adverse alterations at locations in the genome other than the targeted site.
Now, researchers at Rice University have developed a new CRISPR-based gene-editing tool that’s more precise and significantly reduces the likelihood of off-target edits occurring.
Many of the genetic mutations that directly cause a condition, such as those responsible for cystic fibrosis and sickle-cell disease, tend to change the amino acid sequence of the protein that they encode. But researchers have observed only a few million of these single-letter ‘missense mutations’. Of the more than 70 million such mutations that can occur in the human genome, only a sliver have been linked conclusively to disease, and most seem to have no ill effect on health.
So when researchers and doctors find a missense mutation that they’ve never seen before, it can be difficult to know what to make of it. To help interpret such ‘variants of unknown significance’, researchers have developed dozens of computational tools that can predict whether a variant is likely to cause disease. AlphaMissense incorporates existing approaches to the problem, which are increasingly being addressed with machine learning.
An international research team led by scientists in the Center for Genetic Epidemiology at the Keck School of Medicine of USC and USC Norris Comprehensive Cancer Center has singled out mutations in 11 genes that are associated with aggressive forms of prostate cancer.
These findings come from the largest-scale prostate cancer study ever exploring the exome—that is, the key sections of the genetic code that contain the instructions to make proteins. The scientists analyzed samples from about 17,500 prostate cancer patients.
Today, oncologists customize care for certain individuals with aggressive prostate cancer with help from genetic tests. The results can inform treatment, as one class of targeted therapies has proved effective against some inherited prostate cancers. Test findings also can lead to genetic screening among patients’ family members, so they have the chance to take measures that reduce risk and to work with their doctors to be more vigilant in early detection.
A team of scientists led by researchers from the University of Leicester has determined that genes responsible for learning, memory, aggression, and other complex behaviors emerged approximately 650 million years ago.
The research spearheaded by Dr. Roberto Feuda, of the Neurogenetic group within the Department of Genetics and Genome Biology, in collaboration with colleagues from the University of Leicester and the University of Fribourg (Switzerland), has recently been published in the journal Nature Communications.
<em>Nature Communications</em> is a peer-reviewed, open-access, multidisciplinary, scientific journal published by Nature Portfolio. It covers the natural sciences, including physics, biology, chemistry, medicine, and earth sciences. It began publishing in 2010 and has editorial offices in London, Berlin, New York City, and Shanghai.
DeepMind has released a catalog of 71 million possible variants that can cause diseases.
Genetic mutations are changes to our DNA sequence. This happens when cells make copies of themselves during cell division. Mutation is the ultimate source of human genetic variation and has evolutionary and disease genetics implications. A mutation affecting our genes might give birth to a genetic disorder. But just because you have a mutation doesn’t mean it will be a genetic disorder.
That is why researchers at DeepMind, the artificial intelligence arm of Google, have announced that they have trained a machine learning model called AlphaMissense to classify which DNA variations in our genomes are likely to cause disease.
There is powerful science behind how our beliefs inform our genetic expression. It’s not our genes alone that dictate our health outcomes, rather it’s the biology of belief that determines our destiny.
Today on The Doctor’s Farmacy, I’m excited to talk to Dr. Bruce Lipton about how exactly our thoughts determine our genetic expression, and how we can influence our health using our minds.
Dr. Bruce Lipton is a stem cell biologist and author of the bestselling books, The Biology of Belief, Spontaneous Evolution, and The Honeymoon Effect. Dr. Lipton is the recipient of the prestigious Japanese Goi Peace Award and has been listed in the top 100 of “the world’s most spiritually influential people” by Briton’s Watkins Journal for the last 13 years.
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