Posts Tagged ‘research’

Doctors have newly outlined a type of dementia that could be more common than Alzheimer’s among the oldest adults, according to a report published Tuesday in the journal Brain.

The disease, called LATE, may often mirror the symptoms of Alzheimer’s disease, though it affects the brain differently and develops more slowly than Alzheimer’s. Doctors say the two are frequently found together, and in those cases may lead to a steeper cognitive decline than either by itself.

In developing its report, the international team of authors is hoping to spur research — and, perhaps one day, treatments — for a disease that tends to affect people over 80 and “has an expanding but under-recognized impact on public health,” according to the paper.

“We’re really overhauling the concept of what dementia is,” said lead author Dr. Peter Nelson, director of neuropathology at the University of Kentucky Medical Center.

Still, the disease itself didn’t come out of the blue. The evidence has been building for years, including reports of patients who didn’t quite fit the mold for known types of dementia such as Alzheimer’s.

“There isn’t going to be one single disease that is causing all forms of dementia,” said Sandra Weintraub, a professor of psychiatry, behavioral sciences and neurology at Northwestern University Feinberg School of Medicine. She was not involved in the new paper.

Weintraub said researchers have been well aware of the “heterogeneity of dementia,” but figuring out precisely why each type can look so different has been a challenge. Why do some people lose memory first, while others lose language or have personality changes? Why do some develop dementia earlier in life, while others develop it later?

Experts say this heterogeneity has complicated dementia research, including Alzheimer’s, because it hasn’t always been clear what the root cause was — and thus, if doctors were treating the right thing.

What is it?

The acronym LATE stands for limbic-predominant age-related TDP-43 encephalopathy. The full name refers to the area in the brain most likely to be affected, as well as the protein at the center of it all.

“These age-related dementia diseases are frequently associated with proteinaceous glop,” Nelson said. “But different proteins can contribute to the glop.”

In Alzheimer’s, you’ll find one set of glops. In Lewy body dementia, another glop.

And in LATE, the glop is a protein called TDP-43. Doctors aren’t sure why the protein is found in a modified, misfolded form in a disease like LATE.

“TDP-43 likes certain parts of the brain that the Alzheimer’s pathology is less enamored of,” explained Weintraub, who is also a member of Northwestern’s Mesulam Center for Cognitive Neurology and Alzheimer’s Disease.

“This is an area that’s going to be really huge in the future. What are the individual vulnerabilities that cause the proteins to go to particular regions of the brain?” she said. “It’s not just what the protein abnormality is, but where it is.”

More than a decade ago, doctors first linked the TDP protein to amyotrophic lateral sclerosis, otherwise known as ALS or Lou Gehrig’s disease. It was also linked to another type of dementia, called frontotemporal lobar degeneration.

LATE “is a disease that’s 100 times more common than either of those, and nobody knows about it,” said Nelson.

The new paper estimates, based on autopsy studies, that between 20 and 50% of people over 80 will have brain changes associated with LATE. And that prevalence increases with age.

Experts say nailing down these numbers — as well as finding better ways to detect and research the disease — is what they hope comes out of consensus statements like the new paper, which gives scientists a common language to discuss it, according to Nelson.

“People have, in their own separate bailiwicks, found different parts of the elephant,” he said. “But this is the first place where everybody gets together and says, ‘This is the whole elephant.’ ”

What this could mean for Alzheimer’s

The new guidelines could have an impact on Alzheimer’s research, as well. For one, experts say some high-profile drug trials may have suffered as a result of some patients having unidentified LATE — and thus not responding to treatment.

In fact, Nelson’s colleagues recently saw that firsthand: a patient, now deceased, who was part of an Alzheimer’s drug trial but developed dementia anyway.

“So, the clinical trial was a failure for Alzheimer’s disease,” Nelson said, “but it turns out he didn’t have Alzheimer’s disease. He had LATE.”

Nina Silverberg, director of the Alzheimer’s Disease Research Centers Program at the National Institute on Aging, said she suspects examples like this are not the majority — in part because people in clinical trials tend to be on the younger end of the spectrum.

“I’m sure it plays some part, but maybe not as much as one might think at first,” said Silverberg, who co-chaired the working group that led to the new paper.

Advances in testing had already shown that some patients in these trials lacked “the telltale signs of Alzheimer’s,” she said.

In some cases, perhaps it was LATE — “and it’s certainly possible that there are other, as yet undiscovered, pathologies that people may have,” she added.

“We could go back and screen all the people that had failed their Alzheimer’s disease therapies,” Nelson said. “But what we really need to do is go forward and try to get these people out of the Alzheimer’s clinical trials — and instead get them into their own clinical trials.”

Silverberg describes the new paper as “a roadmap” for research that could change as we come to discover more about the disease. And researchers can’t do it without a large, diverse group of patients, she added.

“It’s probably going to take years and research participants to help us understand all of that,” she said.

https://www.cnn.com/2019/04/30/health/dementia-late-alzheimers-study/index.html

Advertisements


Two-photon imaging shows neurons firing in a mouse brain. Recordings like this enable researchers to track which neurons are firing, and how they potentially correspond to different behaviors. The image is credited to Yiyang Gong, Duke University.

Summary: Convolutional neural network model significantly outperforms previous methods and is as accurate as humans in segmenting active and overlapping neurons.

Source: Duke University

Biomedical engineers at Duke University have developed an automated process that can trace the shapes of active neurons as accurately as human researchers can, but in a fraction of the time.

This new technique, based on using artificial intelligence to interpret video images, addresses a critical roadblock in neuron analysis, allowing researchers to rapidly gather and process neuronal signals for real-time behavioral studies.

The research appeared this week in the Proceedings of the National Academy of Sciences.

To measure neural activity, researchers typically use a process known as two-photon calcium imaging, which allows them to record the activity of individual neurons in the brains of live animals. These recordings enable researchers to track which neurons are firing, and how they potentially correspond to different behaviors.

While these measurements are useful for behavioral studies, identifying individual neurons in the recordings is a painstaking process. Currently, the most accurate method requires a human analyst to circle every ‘spark’ they see in the recording, often requiring them to stop and rewind the video until the targeted neurons are identified and saved. To further complicate the process, investigators are often interested in identifying only a small subset of active neurons that overlap in different layers within the thousands of neurons that are imaged.

This process, called segmentation, is fussy and slow. A researcher can spend anywhere from four to 24 hours segmenting neurons in a 30-minute video recording, and that’s assuming they’re fully focused for the duration and don’t take breaks to sleep, eat or use the bathroom.

In contrast, a new open source automated algorithm developed by image processing and neuroscience researchers in Duke’s Department of Biomedical Engineering can accurately identify and segment neurons in minutes.

“As a critical step towards complete mapping of brain activity, we were tasked with the formidable challenge of developing a fast automated algorithm that is as accurate as humans for segmenting a variety of active neurons imaged under different experimental settings,” said Sina Farsiu, the Paul Ruffin Scarborough Associate Professor of Engineering in Duke BME.

“The data analysis bottleneck has existed in neuroscience for a long time — data analysts have spent hours and hours processing minutes of data, but this algorithm can process a 30-minute video in 20 to 30 minutes,” said Yiyang Gong, an assistant professor in Duke BME. “We were also able to generalize its performance, so it can operate equally well if we need to segment neurons from another layer of the brain with different neuron size or densities.”

“Our deep learning-based algorithm is fast, and is demonstrated to be as accurate as (if not better than) human experts in segmenting active and overlapping neurons from two-photon microscopy recordings,” said Somayyeh Soltanian-Zadeh, a PhD student in Duke BME and first author on the paper.

Deep-learning algorithms allow researchers to quickly process large amounts of data by sending it through multiple layers of nonlinear processing units, which can be trained to identify different parts of a complex image. In their framework, this team created an algorithm that could process both spatial and timing information in the input videos. They then ‘trained’ the algorithm to mimic the segmentation of a human analyst while improving the accuracy.

The advance is a critical step towards allowing neuroscientists to track neural activity in real time. Because of their tool’s widespread usefulness, the team has made their software and annotated dataset available online.

Gong is already using the new method to more closely study the neural activity associated with different behaviors in mice. By better understanding which neurons fire for different activities, Gong hopes to learn how researchers can manipulate brain activity to modify behavior.

“This improved performance in active neuron detection should provide more information about the neural network and behavioral states, and open the door for accelerated progress in neuroscience experiments,” said Soltanian-Zadeh.

https://neurosciencenews.com/artificial-intelligence-neurons-11076/

By Emily Underwood

One of the thorniest debates in neuroscience is whether people can make new neurons after their brains stop developing in adolescence—a process known as neurogenesis. Now, a new study finds that even people long past middle age can make fresh brain cells, and that past studies that failed to spot these newcomers may have used flawed methods.

The work “provides clear, definitive evidence that neurogenesis persists throughout life,” says Paul Frankland, a neuroscientist at the Hospital for Sick Children in Toronto, Canada. “For me, this puts the issue to bed.”

Researchers have long hoped that neurogenesis could help treat brain disorders like depression and Alzheimer’s disease. But last year, a study in Nature reported that the process peters out by adolescence, contradicting previous work that had found newborn neurons in older people using a variety of methods. The finding was deflating for neuroscientists like Frankland, who studies adult neurogenesis in the rodent hippocampus, a brain region involved in learning and memory. It “raised questions about the relevance of our work,” he says.

But there may have been problems with some of this earlier research. Last year’s Nature study, for example, looked for new neurons in 59 samples of human brain tissue, some of which came from brain banks where samples are often immersed in the fixative paraformaldehyde for months or even years. Over time, paraformaldehyde forms bonds between the components that make up neurons, turning the cells into a gel, says neuroscientist María Llorens-Martín of the Severo Ochoa Molecular Biology Center in Madrid. This makes it difficult for fluorescent antibodies to bind to the doublecortin (DCX) protein, which many scientists consider the “gold standard” marker of immature neurons, she says.

The number of cells that test positive for DCX in brain tissue declines sharply after just 48 hours in a paraformaldehyde bath, Llorens-Martín and her colleagues report today in Nature Medicine. After 6 months, detecting new neurons “is almost impossible,” she says.

When the researchers used a shorter fixation time—24 hours—to preserve donated brain tissue from 13 deceased adults, ranging in age from 43 to 87, they found tens of thousands of DCX-positive cells in the dentate gyrus, a curled sliver of tissue within the hippocampus that encodes memories of events. Under a microscope, the neurons had hallmarks of youth, Llorens-Martín says: smooth and plump, with simple, undeveloped branches.

In the sample from the youngest donor, who died at 43, the team found roughly 42,000 immature neurons per square millimeter of brain tissue. From the youngest to oldest donors, the number of apparent new neurons decreased by 30%—a trend that fits with previous studies in humans showing that adult neurogenesis declines with age. The team also showed that people with Alzheimer’s disease had 30% fewer immature neurons than healthy donors of the same age, and the more advanced the dementia, the fewer such cells.

Some scientists remain skeptical, including the authors of last year’s Nature paper. “While this study contains valuable data, we did not find the evidence for ongoing production of new neurons in the adult human hippocampus convincing,” says Shawn Sorrells, a neuroscientist at the University of Pittsburgh in Pennsylvania who co-authored the 2018 paper. One critique hinges on the DCX stain, which Sorrells says isn’t an adequate measure of young neurons because the DCX protein is also expressed in mature cells. That suggests the “new” neurons the team found were actually present since childhood, he says. The new study also found no evidence of pools of stem cells that could supply fresh neurons, he notes. What’s more, Sorrells says two of the brain samples he and his colleagues looked at were only fixed for 5 hours, yet they still couldn’t find evidence of young neurons in the hippocampus.

Llorens-Martín says her team used multiple other proteins associated with neuronal development to confirm that the DCX-positive cells were actually young, and were “very strict,” in their criteria for identifying young neurons.

Heather Cameron, a neuroscientist at the National Institute of Mental Health in Bethesda, Maryland, remains persuaded by the new work. Based on the “beauty of the data” in the new study, “I think we can all move forward pretty confidently in the knowledge that what we see in animals will be applicable in humans, she says. “Will this settle the debate? I’m not sure. Should it? Yes.”

https://www.sciencemag.org/news/2019/03/new-neurons-life-old-people-can-still-make-fresh-brain-cells-study-finds?utm_campaign=news_daily_2019-03-25&et_rid=17036503&et_cid=2734364

by David Nield

How exactly do our brains sort between the five taste groups: sweet, sour, salty, bitter and umami? We’ve now got a much better idea, thanks to research that has pinned down where in the brain this taste processing happens.

Step forward: the insular cortex. Already thought to be responsible for everything from motor control to social empathy, we can now add flavour identification to its list of jobs.

It’s an area of the brain scientists have previously suspected could be responsible for sorting tastes, and which has been linked to taste in rodents, but this new study is much more precise in figuring out the role it plays in decoding what our tongues are telling us.

“We have known that tastes activate the human brain for some time, but not where primary taste types such as sweet, sour, salty, and bitter are distinguished,” says one of the team, Adam Anderson from Cornell University in New York.

“By using some new techniques that analyse fine-grained activity patterns, we found a specific portion of the insular cortex – an older cortex in the brain hidden behind the neocortex – represents distinct tastes.”

Anderson and his team used detailed fMRI scans of 20 adults as well as a new statistical model to dig deeper than previous studies into the link between the insular cortex and taste. This helped separate the taste response from other related responses – like the disgust we might feel when eating something sour or bitter.

Part of the problem in pinning down the taste-testing parts of the brain is that multiple regions of neurons get busy whenever we’re eating something. However, this study helps to cut through some of that noise.

In particular, it seems that different tastes don’t necessarily affect different parts of the insular cortex, but rather prompt different patterns of activity. Those patterns help the brain determine what it’s tasting.

For example, one particular section of the insular cortex was found to light up – in terms of neural activity – whenever something sweet was tasted. It’s a literal sweet spot, in other words, but it also showed that different brains have different wiring.

“While we identified a potential sweet spot, its precise location differed across people and this same spot responded to other tastes, but with distinct patterns of activity,” says Anderson.

“To know what people are tasting, we have to take into account not only where in the insula is stimulated, but also how.”

The work follows on from previous research showing just how big a role the brain plays in perceiving taste. It used to be thought that receptors on the tongue did most of the taste testing, but now it seems the brain is largely in charge of the process.

That prior study showed how switching certain brain cells on and off in mice was enough to prevent them from distinguishing between sweet and bitter. The conclusion is that while the tongue does identify certain chemicals, it’s the brain that interprets them.

The new research adds even more insight into what’s going on in the brain in humans when we need to work out what we’re tasting – and shows just how important a job the insular cortex is doing.

“The insular cortex represents experiences from inside our bodies,” says Anderson. “So taste is a bit like perceiving our own bodies, which is very different from other external senses such as sight, touch, hearing or smell.”

The research has been published in Nature Communications.

https://www.sciencealert.com/now-we-know-the-part-of-the-brain-that-tells-us-what-we-re-tasting

by CARLY CASSELLA

Scientists are closing in on a blood test for fibromyalgia, and the result could save patients from what is currently a lengthy and vague process of diagnosis.

Researchers at Ohio State University are now aiming to have a diagnostic blood test available for widespread use within the next five years.

Their confidence stems from a recently discovered biomarker – a “metabolic fingerprint” as the researchers put it – traceable in the blood of those with the disorder.

“We found clear, reproducible metabolic patterns in the blood of dozens of patients with fibromyalgia,” says lead author Kevin Hackshaw, a rheumatologist at Ohio State University.

“This brings us much closer to a blood test than we have ever been.”

Fibromyalgia is a common, debilitating, and poorly understood disorder, marked by widespread pain and fatigue, with no known cause and absolutely no cure.

In the United States, it’s the most common cause of chronic widespread pain, and that’s not even counting the thousands of patients who go undiagnosed every year.

Without a reliable way to detect this disorder, it’s estimated that up to three out of four people with the condition remain undiagnosed. And on average it can take five years from when a person’s symptoms first appear to them actually receiving a diagnosis.

In total, the US Centers for Disease Control and Prevention estimates that about two percent of the population – around four million adults – have fibromyalgia, with women making up a disproportionate slice.

Left with few options, many patients are simply forced to live with their pain.With nowhere to go, many become desperate and turn to potentially harmful treatments.

“When you look at chronic pain clinics, about 40 percent of patients on opioids meet the diagnostic criteria for fibromyalgia,” says Hackshaw.

“Fibromyalgia often gets worse, and certainly doesn’t get better, with opioids.”

It was Hackshaw’s goal to intervene sooner. Using vibrational spectroscopy, a technique which measures the energy of molecules, his team analysed blood samples from 50 people with fibromyalgia, 29 with rheumatoid arthritis, 19 with osteoarthritis, and 23 with lupus.

Despite the fact these disorders can present with similar symptoms, the blood of those participants with fibromyalgia was distinct.

Using these unique patterns, the researchers then tried to blindly predict participants’ diagnoses. Even without knowing their true disorder, the researchers were able to accurately diagnose every study participant based on that molecular fingerprint in the blood.

“These initial results are remarkable,” says co-author Luis Rodriguez-Saona, an expert in vibrational spectroscopy at Ohio State University.

“If we can help speed diagnosis for these patients, their treatment will be better and they’ll likely have better outlooks. There’s nothing worse than being in a grey area where you don’t know what disease you have.”

While the sample size is undoubtedly small, the results are promising. If the team can replicate their results on a larger scale, with a couple hundred diverse participants, then a blood test in five years might not seem so far-fetched.

Not to mention what that would mean for treatment. If the researchers can prove they really have identified a biological fingerprint for fibromyalgia, this could give us new drug targets in the future.

“Thus,” the authors conclude, “our studies have great importance both from development of a reproducible biomarker as well as identifying potential new therapeutic targets for treatment.”

This study has been published in the Journal of Biological Chemistry.

https://www.sciencealert.com/scientists-have-devised-a-blood-test-that-can-accurately-diagnose-fibromyalgia

Neuroscientists can read brain activity to predict decisions 11 seconds before people actFree will, from a neuroscience perspective, can look like quite quaint. In a study published this week in the journal Scientific Reports, researchers in Australia were able to predict basic choices participants made 11 seconds before they consciously declared their decisions.

In the study, 14 participants—each placed in an fMRI machine—were shown two patterns, one of red horizontal stripes and one of green vertical stripes. They were given a maximum of 20 seconds to choose between them. Once they’d made a decision, they pressed a button and had 10 seconds to visualize the pattern as hard as they could. Finally, they were asked “what did you imagine?” and “how vivid was it?” They answered these questions by pressing buttons.

Using the fMRI to monitor brain activity and machine learning to analyze the neuroimages, the researchers were able to predict which pattern participants would choose up to 11 seconds before they consciously made the decision. And they were able to predict how vividly the participants would be able to envisage it.

Lead author Joel Pearson, cognitive neuroscience professor at the University of South Wales in Australia, said that the study suggests traces of thoughts exist unconsciously before they become conscious. “We believe that when we are faced with the choice between two or more options of what to think about, non-conscious traces of the thoughts are there already, a bit like unconscious hallucinations,” he said in a statement. “As the decision of what to think about is made, executive areas of the brain choose the thought-trace which is stronger. In, other words, if any pre-existing brain activity matches one of your choices, then your brain will be more likely to pick that option as it gets boosted by the pre-existing brain activity.”

The work has implications for how we understand uncomfortable thoughts: Pearson believes the findings explain why thinking about something only leads to more thoughts on the subject, as it creates “a positive feedback loop.” The study also suggests that unwelcome visualizations, such as those experienced with post-traumatic stress disorder, begin as unconscious thoughts.

Though this is just one study, it’s not the first to show that thoughts can be predicted before they are conscious. As the researchers note, similar techniques have been able to predict motor decisions between seven and 10 seconds before they’re conscious, and abstract decisions up to four seconds before they’re conscious. Taken together, these studies show how understanding how the brain complicates our conception of free will.

Neuroscientists have long known that the brain prepares to act before you’re consciously aware, and there are just a few milliseconds between when a thought is conscious and when you enact it. Those milliseconds give us a chance to consciously reject unconscious impulses, seeming to form a foundation of free will.

Freedom, however, can be enacted by both the unconscious and conscious self—and there are neuroscientists who claim that being controlled by our own unconscious brain is hardly an affront to free will. Studies showing that neuroscientists can predict our actions long before we’re aware of them don’t necessarily negate the concept of free will, but they certainly complicate our conception of our own minds.

https://qz.com/1569158/neuroscientists-read-unconscious-brain-activity-to-predict-decisions/?utm_source=google-news

By David Freeman

No one is ditching the night-vision goggles just yet, but scientists working in the United States and China have developed a technique that they say could one day give humans the ability to see in the dark.

The technique involves injecting the eyes with particles that act like tiny antennae that take infrared light — wavelengths that are invisible to humans and other mammals — and convert it to visible wavelengths. Mammals can see wavelengths in just a sliver of the electromagnetic spectrum, and the new technique is designed to widen that sliver.

The nanoparticle injections haven’t been tried on humans, but experiments on mice show that they confer the ability to see infrared light without interfering with the perception of light in the visible range. The effect worked during the day and at night and lasted for several weeks. The rodents were left unharmed once it wore off.

Gang Han, a chemist at the University of Massachusetts Medical School and a co-author of a new paper describing the research, said in a statement that the technique could lead to a better understanding of visual perception and possibly lead to new ways to treat color blindness.

But those are far from the only possible applications if the technique can be made to work safely in other mammals, including humans. In an email to NBC News MACH, Han said it might be possible to use nanoparticle injections to create “superdogs” that could make it easier to apprehend lawbreakers in darkness.

“For ordinary people,” he added, “we may also see our sky in a completely different way” both at night and during the day because many celestial objects give off infrared light.

The technique doesn’t confer the ability to see the longer-wavelength infrared light given off by living bodies and other warm objects, Tian Xue, a neuroscientist at the University of Science and Technology of China and a co-author of the paper, said in an email. But at least theoretically, it could give humans the ability to see bodies and objects in darkness without the use of night-vision gear — though an infrared light would still be needed.

For their research, Han, Xue and their collaborators injected the rodents’ eyes with nanoparticles treated with proteins that helped “glue” the particles to light-sensitive cells in the animals’ retinas. Once the tiny antennae were in place, the scientists hypothesized, the nanoparticles would convert infrared light into shorter wavelengths, which the animals would then perceive as green light.

To make sure the mice were actually seeing the converted infrared light, the scientists subjected the animals to a number of tests, including one in which they were given a choice of entering a totally dark box or one illuminated only with infrared light. (Mice are nocturnal, and ordinarily they prefer darkness.) Control animals showed no preference — because both boxes appeared dark to them — while treated mice showed a distinct preference for the dark box.

Other scientists praised the research while expressing doubts about trying the technique in humans.

Harvard neuroscientist Michael Do said in an email that the experiments were “sophisticated” and that the technique was likely to work in humans as well as in mice. But he said it was unclear just how sharp the infrared vision would be in humans, and he cautioned that the injections might damage delicate structures in the eye.

Glen Jeffery, a neuroscientist at the University College London, expressed similar praise for the research — but even graver doubts. “Injecting any material under the retina is risky and should never be done unless there is a clear and justifiable clinical reason…” he said in an email. “I have no idea how you could use this technology to human advantage and would never support its application on healthy humans.”

But the researchers are moving ahead. Han said the team planned to test the technique in bigger animals — possibly dogs.

https://www.nbcnews.com/mach/science/scientists-create-super-mice-can-see-dark-here-s-what-ncna977966

Thanks to Kebmodee for bringing this to the It’s Interesting community.