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Groundbreaking new research suggests removing drug-associated memories could prevent relapse
The 2020 study successfully removed memories associated with morphine from the brains of mice with very promising results.
- Once the mice in the study had become dependent on the morphine, "switching off" (or silencing) that PVT pathway completely abolished their preference for the morphine.
- Stanford associate professor Xiaoke Chen's team was able to precisely control the activity of various pathways at different points of the animals' drug-use experience.
- Extinction training attempts to reduce the strength of those cue-drug memories which, if successful, could decrease the number of factors that induce cravings and aid in relapse. This new "erasure" method could eventually be considered an alternative to that - erasing the cues altogether instead of training your mind to forget them.
"The most difficult part of treating addiction is to prevent relapse, especially for opioids," explains Xiaoke Chen, an associate professor at Stanford University's School of Humanities and Sciences and lead for a new study."To prevent relapse, we really need to deal with the withdrawal."
According to Chen, both the reward of the high and the alleviation of agonizing withdrawal symptoms can serve as memory cues that trigger the drug cravings that lead to relapse. Because of this, he and his team have taken a look at drug addiction as a memory problem.
A study of morphine and mice show promising results for the battle against addiction
This study of mice and morphine shows very promising results for the battle of addiction in the human population.
Photo by Rudmer Zwerver on Shutterstock
The mice in this groundbreaking 2020 study were introduced to a two-sided chamber that was differentiated by tactile and visual cues. One side of the chamber had a drug-free saline solution and the other a small dose of morphine.
Over the course of four days, the mice went through a kind of "training" - associating the two sides of the chamber with either saline or morphine. When their memories were tested on the fifth day, the mice had already developed a compulsive preference for the chamber containing morphine.
Prior to this study, Chen's team had traced the animals' learning and memory abilities to a node in the brain known as the paraventricular thalamus (PVT for short). This area of the brain connects to multiple brain regions that are also involved in drug addiction.
By using a light-based technique (called optogenetics), Chen's team was able to precisely control the activity of various pathways at different points of the animals' drug-use experience.
Once the mice had become dependent on the morphine, "switching off" (or silencing) the PVT pathway that had previously been found to be important for withdrawal completely abolished their preference for the morphine. A day later, the mice were tested once more without the PVT silencing technique. There was still no preference for the chamber with morphine in it. This is a very surprising and potentially groundbreaking study in the world of addictions.
Even when the morphine was reintroduced to the mice, they still did not prefer the morphine-paired chamber — even as long as two weeks later.
"Our data suggest that after silencing this PVT pathway, environmental cues will not work to reactivate this memory," explains Chen. "We haven't tested a later time point than two weeks but we think it's very likely the memory is just gone."
What could this mean for the struggle of addictions in humans?
What could this mean for addiction in the human population?
Photo by Olivier Le Moal on Shutterstock
For a little more of an in-depth understanding of the future implications of this study, we should take a look at what the paraventricular thalamus is in the human brain and how it relates to drug addiction.
A brief explanation of the paraventricular thalamus in humans
According to Science Direct, "brain circuits that regulate reward and motivation are considered to be the neural substrate of drug addiction. An increasing body of literature indicates that the paraventricular thalamic nucleus (PVT) could serve as a key node in the neurocircuits that control goal-directed behaviors."
The PVT receives input from the brain stem and hypothalamus and is also connected to the limbic system. Neurons in the PVT are impacted by drug exposure as well as cue and context that become associated with drug-taking. You can see then how silencing the PVT could potentially impact the need for continued drug use.
"Erasure" and silencing of the PVT pathway
The scientists attached to this study have dubbed the silencing of this PVT pathway to be called "erasure" because it appears that the drug-associated memory is effectively erased from the brain (of mice).
Two crucial components for memory erasure are location and timeframe. Manipulation of this pathway must be done while the animal is inside the memory-associated environment (which, in this case, is the drug-associated chamber where the morphine was) and that the animal must be experiencing withdrawal at the time of erasure for this to be effective.
"The memory first needs to be reactivated to provide an opportunity for precise memory manipulation," said Chen. "You don't want to erase the entire memory; you only want to erase the part that's associated with the drug."
Once reactivated, there is a window of opportunity for updating the drug-associated memory, suggesting that scientists could strengthen and reinforce the memory by providing the drug or weaken the memory by changing the brain's association with the drug.
Extinction training versus erasure
There is already the practice of "extinction training", where the brain effectively "learns to forget" about addiction as a process of treating addiction. When environmental stimuli or cues become associated with drug use, they become powerful motivators of continued drug use. Extinction training attempts to reduce the strength of those cue-drug memories which, if successful, could decrease the number of factors that induce cravings and aid in relapse.
This new "erasure" method could eventually be considered an alternative to that - erasing the cues altogether (by silencing the PVT pathway) instead of training your mind to forget them.
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Northwell Health is using insights from website traffic to forecast COVID-19 hospitalizations two weeks in the future.
- The machine-learning algorithm works by analyzing the online behavior of visitors to the Northwell Health website and comparing that data to future COVID-19 hospitalizations.
- The tool, which uses anonymized data, has so far predicted hospitalizations with an accuracy rate of 80 percent.
- Machine-learning tools are helping health-care professionals worldwide better constrain and treat COVID-19.
The value of forecasting<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNTA0Njk2OC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzM2NDQzOH0.rid9regiDaKczCCKBsu7wrHkNQ64Vz_XcOEZIzAhzgM/img.jpg?width=980" id="2bb93" class="rm-shortcode" data-rm-shortcode-id="31345afbdf2bd408fd3e9f31520c445a" data-rm-shortcode-name="rebelmouse-image" data-width="1546" data-height="1056" />
Northwell emergency departments use the dashboard to monitor in real time.
Credit: Northwell Health<p>One unique benefit of forecasting COVID-19 hospitalizations is that it allows health systems to better prepare, manage and allocate resources. For example, if the tool forecasted a surge in COVID-19 hospitalizations in two weeks, Northwell Health could begin:</p><ul><li>Making space for an influx of patients</li><li>Moving personal protective equipment to where it's most needed</li><li>Strategically allocating staff during the predicted surge</li><li>Increasing the number of tests offered to asymptomatic patients</li></ul><p>The health-care field is increasingly using machine learning. It's already helping doctors develop <a href="https://care.diabetesjournals.org/content/early/2020/06/09/dc19-1870" target="_blank">personalized care plans for diabetes patients</a>, improving cancer screening techniques, and enabling mental health professionals to better predict which patients are at <a href="https://healthitanalytics.com/news/ehr-data-fuels-accurate-predictive-analytics-for-suicide-risk" target="_blank" rel="noopener noreferrer">elevated risk of suicide</a>, to name a few applications.</p><p>Health systems around the world have already begun exploring how <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315944/" target="_blank" rel="noopener noreferrer">machine learning can help battle the pandemic</a>, including better COVID-19 screening, diagnosis, contact tracing, and drug and vaccine development.</p><p>Cruzen said these kinds of tools represent a shift in how health systems can tackle a wide variety of problems.</p><p>"Health care has always used the past to predict the future, but not in this mathematical way," Cruzen said. "I think [Northwell Health's new predictive tool] really is a great first example of how we should be attacking a lot of things as we go forward."</p>
Making machine-learning tools openly accessible<p>Northwell Health has made its predictive tool <a href="https://github.com/northwell-health/covid-web-data-predictor" target="_blank">available for free</a> to any health system that wishes to utilize it.</p><p>"COVID is everybody's problem, and I think developing tools that can be used to help others is sort of why people go into health care," Dr. Cruzen said. "It was really consistent with our mission."</p><p>Open collaboration is something the world's governments and health systems should be striving for during the pandemic, said Michael Dowling, Northwell Health's president and CEO.</p><p>"Whenever you develop anything and somebody else gets it, they improve it and they continue to make it better," Dowling said. "As a country, we lack data. I believe very, very strongly that we should have been and should be now working with other countries, including China, including the European Union, including England and others to figure out how to develop a health surveillance system so you can anticipate way in advance when these things are going to occur."</p><p>In all, Northwell Health has treated more than 112,000 COVID patients. During the pandemic, Dowling said he's seen an outpouring of goodwill, collaboration, and sacrifice from the community and the tens of thousands of staff who work across Northwell.</p><p>"COVID has changed our perspective on everything—and not just those of us in health care, because it has disrupted everybody's life," Dowling said. "It has demonstrated the value of community, how we help one another."</p>
"You dream about these kinds of moments when you're a kid," said lead paleontologist David Schmidt.
- The triceratops skull was first discovered in 2019, but was excavated over the summer of 2020.
- It was discovered in the South Dakota Badlands, an area where the Triceratops roamed some 66 million years ago.
- Studying dinosaurs helps scientists better understand the evolution of all life on Earth.
Credit: David Schmidt / Westminster College<p style="margin-left: 20px;">"We had to be really careful," Schmidt told St. Louis Public Radio. "We couldn't disturb anything at all, because at that point, it was under law enforcement investigation. They were telling us, 'Don't even make footprints,' and I was thinking, 'How are we supposed to do that?'"</p><p>Another difficulty was the mammoth size of the skull: about 7 feet long and more than 3,000 pounds. (For context, the largest triceratops skull ever unearthed was about <a href="https://www.tandfonline.com/doi/abs/10.1080/02724634.2010.483632" target="_blank">8.2 feet long</a>.) The skull of Schmidt's dinosaur was likely a <em>Triceratops prorsus, </em>one of two species of triceratops that roamed what's now North America about 66 million years ago.</p>
Credit: David Schmidt / Westminster College<p>The triceratops was an herbivore, but it was also a favorite meal of the T<em>yrannosaurus rex</em>. That probably explains why the Dakotas contain many scattered triceratops bone fragments, and, less commonly, complete bones and skulls. In summer 2019, for example, a separate team on a dig in North Dakota made <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">headlines</a> after unearthing a complete triceratops skull that measured five feet in length.</p><p>Michael Kjelland, a biology professor who participated in that excavation, said digging up the dinosaur was like completing a "multi-piece, 3-D jigsaw puzzle" that required "engineering that rivaled SpaceX," he jokingly told the <a href="https://www.nytimes.com/2019/07/26/science/triceratops-skull-65-million-years-old.html" target="_blank">New York Times</a>.</p>
Morrison Formation in Colorado
James St. John via Flickr
|Credit: Nobu Tamura/Wikimedia Commons|
The Persian polymath and philosopher of the Islamic Golden Age teaches us about self-awareness.
Can computers do calculations in multiple universes? Scientists are working on it. Step into the world of quantum computing.
- While today's computers—referred to as classical computers—continue to become more and more powerful, there is a ceiling to their advancement due to the physical limits of the materials used to make them. Quantum computing allows physicists and researchers to exponentially increase computation power, harnessing potential parallel realities to do so.
- Quantum computer chips are astoundingly small, about the size of a fingernail. Scientists have to not only build the computer itself but also the ultra-protected environment in which they operate. Total isolation is required to eliminate vibrations and other external influences on synchronized atoms; if the atoms become 'decoherent' the quantum computer cannot function.
- "You need to create a very quiet, clean, cold environment for these chips to work in," says quantum computing expert Vern Brownell. The coldest temperature possible in physics is -273.15 degrees C. The rooms required for quantum computing are -273.14 degrees C, which is 150 times colder than outer space. It is complex and mind-boggling work, but the potential for computation that harnesses the power of parallel universes is worth the chase.