Posts Tagged Research

[WEB] Taking epilepsy drugs during pregnancy is not linked to cognitive problems in babies

Reviewed by Emily Henderson, B.Sc. Jun 8 2021

New findings published in JAMA Neurology suggest there is no difference in cognitive outcomes at age 2 among children of healthy women and children of women with epilepsy who took antiseizure medication during pregnancy.

The findings are part of the large research project Maternal Outcomes and Neurodevelopmental Effects of Antiepileptic Drugs (MONEAD), which is a prospective, long-term study looking at outcomes in pregnant women with epilepsy and their children. The study was funded by the National Institute of Neurological Disorders and Stroke (NINDS), part of the National Institutes of Health.

This study reports findings from 382 children (292 children born to women with epilepsy and 90 born to healthy women) who were assessed for language development at age 2. The researchers also compared developmental scores with third trimester blood levels of antiseizure medication in these children.

Results suggest that children born to healthy women and those born to women with epilepsy do not show significant differences in language development scores at age 2. Neither was language development linked to third trimester blood levels of epilepsy medications. Most women with epilepsy in the study were taking lamotrigine and/or levetiracetam.

However, the study did find that those children born to mothers with the very highest levels of antiseizure medication in the blood during the third trimester did have somewhat lower scores on tests in the motor and general adaptive domains, which refer to skills related to self-care, such as feeding.

The children in this study will continue to be followed and will participate in additional cognitive tests through age 6. Results so far indicate that controlling epilepsy with these medications during pregnancy may be safe for babies.

Source: NIH/National Institute of Neurological Disorders and Stroke

Journal reference: Meador, K. J., et al. (2021) Two-Year-Old Cognitive Outcomes in Children of Pregnant Women With Epilepsy in the Maternal Outcomes and Neurodevelopmental Effects of Antiepileptic Drugs Study. JAMA Neurologydoi.org/10.1001/jamaneurol.2021.1583.

Source

, , , , , , , , ,

Leave a comment

[WEB] Neuroimaging technology used to study how brain stimulation works for treatment of depression

Reviewed by Emily Henderson, B.Sc. May 4 2021

Repetitive transcranial magnetic stimulation, or rTMS, was FDA approved in 2008 as a safe and effective noninvasive treatment for severe depression resistant to antidepressant medications. A small coil positioned near the scalp generates repetitive, pulsed magnetic waves that pass through the skull and stimulate brain cells to relieve symptoms of depression. The procedure has few side effects and is typically prescribed as an alternative or supplemental therapy when multiple antidepressant medications and/or psychotherapy do not work.

Despite increased use of rTMS in psychiatry, the rates at which patients respond to therapy and experience remission of often-disabling symptoms have been modest at best.

Now, for the first time, a team of University of South Florida psychiatrists and biomedical engineers applied an emerging functional neuroimaging technology, known as diffuse optical tomography (DOT), to better understand how rTMS works so they can begin to improve the technique’s effectiveness in treating depression. DOT uses near-infrared light waves and sophisticated algorithms (computer instructions) to produce three-dimensional images of soft tissue, including brain tissue.

Comparing depressed and healthy individuals, the USF researchers demonstrated that this newer optical imaging technique can safely and reliably measure changes in brain activity induced during rTMS in a targeted region of the brain implicated in mood regulation. Their findings were published April 1 in the Nature journal Scientific Reports.

This study is a good example of how collaboration between disciplines can advance our overall understanding of how a treatment like TMS works. We want to use what we learned from the application of the diffuse optical tomography device to optimize TMS, so that the treatments become more personalized and lead to more remission of depression.”

Shixie Jiang, MD, study lead author, third-year psychiatry resident, USF Health Morsani College of Medicine

DOT has been used clinically for imaging epilepsy, breast cancer, and osteoarthritis and to visualize activation of cortical brain regions, but the USF team is the first to introduce the technology to psychiatry to study brain stimulation with TMS.

“Diffuse optical tomography is really the only modality that can image brain function at the same time that TMS is administered,” said study principal investigator Huabei Jiang, PhD, a professor in the Department of Medical Engineering and father of Shixie Jiang. The DOT imaging system used for USF’s collaborative study was custom built in his laboratory at the USF College of Engineering.

The researchers point to three main reasons why TMS likely has not lived up to its full potential in treating major depression: nonoptimized brain stimulation targeting; unclear treatment parameters (i.e., rTMS dose, magnetic pulse patterns and frequencies, rest periods between stimulation intervals), and incomplete knowledge of how nerve cells in the brain respond physiologically to the procedure.

Related Stories

Portable, less expensive, and less confining than some other neuroimaging equipment like MRIs, DOT still renders relatively high-resolution, localized 3D images. More importantly, Dr. Huabei Jiang said, DOT can be used during TMS without interfering with treatment’s magnetic pulses and without compromising the images and other data generated.

DOT relies on the fact that higher levels of oxygenated blood correlate with more brain activity and increased cerebral blood flow, and lower levels indicate less activity and blood flow. Certain neuroimaging studies have also revealed that depressed people display abnormally low brain activity in the prefrontal cortex, a brain region associated with emotional responses and mood regulation.

By measuring changes in near-infrared light, DOT detects changes in brain activity and, secondarily, changes in blood volume (flow) that might be triggering activation in the prefrontal cortex. In particular, the device can monitor altered levels of oxygenated, deoxygenated, and total hemoglobin, a protein in red blood cells carrying oxygen to tissues.

The USF study analyzed data collected from 13 adults (7 depressed and 6 healthy controls) who underwent DOT imaging simultaneously with rTMS at the USF Health outpatient psychiatry clinic. Applying the standard rTMS protocol, the treatment was aimed at the brain’s left dorsolateral prefrontal cortex – the region most targeted for depression.

The researchers found that the depressed patients had significantly less brain activation in response to rTMS than the healthy study participants. Furthermore, peak brain activation took longer to reach in the depressed group, compared to the healthy control group.

This delayed, less robust activation suggests that rTMS as currently administered under FDA guidelines may not be adequate for some patients with severe depression, Dr. Shixie Jiang said. The dose and timing of treatment may need to be adjusted for patients who exhibit weakened responses to brain stimulation at baseline (initial treatment), he added.

Larger clinical trials are needed to validate the USF preliminary study results, as well as to develop ideal treatment parameters and identify other dysfunctional regions in the depression-affected brain that may benefit from targeted stimulation.

“More work is needed,” Dr. Shixie Jiang said, “but advances in neuroimaging with new approaches like diffuse optical tomography hold great promise for helping us improve rTMS and depression outcomes.”

Source

, , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Leave a comment

[NEWS] ‘The Virtual Brain’: A new tool for epilepsy surgery planning

Reviewed by Emily Henderson, B.Sc. Feb 20 2021

Epilepsy is one of the most common neurological disorders, affecting over 50 Million people worldwide. Patients suffer from seizures caused by sudden neuronal activity engaging at times large networks of the brain. In a third of all cases the disease is resistant to drugs. The most common treatment option for these patients is surgical removal of the “epileptogenic zone”, the areas of the brain, where the seizures emerge.

“Surgery success depends on locating these areas as precisely as possible. But in clinical practice, this often proves very difficult, and the average surgery success rate remains at only around 60%”, says Viktor Jirsa. Any improvement would have major impact for many patients”.

The scientist has developed a computational tool, called “The Virtual Brain” (TVB), to model and predict activity in an individual patient brain. In collaboration with the neurologist Fabrice Bartolomei, they adapted the model to epilepsy, simulating the spread of individual seizure activity. The model thus can become an additional advisory tool for neurosurgeons to help target surgeries more precisely.

A clinical trial is currently underway to evaluate the personalized brain models of TVB as a new tool for epilepsy surgery planning, with promising first results. It is important to underscore that the Virtual Brain tool is still at clinical investigating stage and is therefore not yet available to patients.

The team now works on the next generation of The Virtual Brain, which boosts the accuracy of the model further using the EBRAINS research infrastructure. The objective is to significantly scale up the potential for personalized brain representation with the help of large brain data sets from the EBRAINS Brain Atlas. This includes the most detailed 3D representation of the brain’s anatomy, the BigBrain, at a resolution of 20 micrometers.

“Only EBRAINS allows to go to this massive scale and resolution”, Jirsa says. “Here brain data resources are made compatible and integrated with high-performance computing and informatics tools. EBRAINS enables the application of deep learning and other methods to find the configuration that most closely matches the patient’s own recordings of brain dynamics. This is an important step towards pinpointing the epileptogenic zone with greater precision.”

Katrin Amunts, Scientific Research Director of the HBP says: “The HBP’s multidisciplinary approach, gaining neuroscientific insight from the analysis of big data and neuroimaging studies, supported by brain modeling and advanced computing is a highly impactful way to advance brain research and bring innovation to patients and society.”

Pawel Swieboda, CEO of EBRAINS and Director General of the HBP, comments: “Prof Jirsa’s Virtual Brain computing tool is one of the many breakthrough achievements resulting from the cutting-edge scientific expertise of the Human Brain Project scientists and from the state-of-the art research infrastructure EBRAINS. We’re looking forward to sharing more brain health advances enabled by EBRAINS in the future. Meanwhile we invite researchers in different fields, such as neuroscience, neuroengineering, or neurotechnology – to list a few – to explore how the EBRAINS platform can enhance their own research.”

Source: Human Brain Project

, , , , , , , , , , , , , , , , ,

Leave a comment

[NEWS] Researchers develop a technique to predict epileptic seizures

Reviewed by Emily Henderson, B.Sc. Dec 18 2020

A third of epilepsy sufferers are resistant to treatment for this neurological disease that affects 1% of the population. The onset of seizures is unpredictable, and has been the subject of fruitless research since the 1970s. The unforeseeable nature of the disease means patients are forced to take medication and / or adjust their lifestyles.

Neuroscientists from the University of Geneva (UNIGE) and the University Hospital of Bern (Inselspital) – working with the University of California in San Francisco (UCSF) and Brown University in Providence – have succeeded in developing a technique that can predict seizures between one and several days in advance. By recording neuronal activity over at least six months using a device implanted directly in the brain, it is possible to detect individual cycles of epileptic activity and provide information about the probability of a future seizure. This approach, published in the journal Lancet Neurology, is remarkably reliable, and prospective clinical trials are now in the pipeline.

An epileptic brain can switch suddenly from a physiological state to a pathological state, characterized by a disturbance of neuronal activity which can cause, inter alia, convulsions typical of an epileptic seizure. How and why the brain swaps one state for another is still poorly understood, with the result that the onset of a seizure is difficult, if not impossible, to predict.

Specialists worldwide have been trying for over 50 years to predict seizures a few minutes in advance, but with limited success.”

Timothée Proix, Researcher, Department of Fundamental Neurosciences, University of Geneva Faculty of Medicine

Seizures do not appear to be preceded by any obvious warning signs that would make prediction easier. The frequency, depending on the individual, varies from once a year to once a day.

“It’s a huge problem for patients”, begins Maxime Baud, a neurologist at Inselspital. “This unpredictability is associated with a permanent threat that obliges patients to take medication on a daily basis. And in many cases, it prevents them from participating in certain sports. Living with this hanging over you can also affect your mental health”. Existing treatments are often difficult to bear: they depend on drugs with numerous potential side effects to reduce neuronal excitability and sometimes involve neurosurgery to remove the epileptic focus, i.e. the starting point of the brain seizures. Moreover, a quarter of patients do not respond to these treatments, meaning they have to learn to manage the chronicity of their disease.

Weather forecasting

Epileptic activity can be measured using cerebral electrical activity data recorded by electroencephalography. This can be used to identify interictal discharges – evanescent discharges that appear in between seizures without directly causing them. “We observe clinically that epileptic seizures recur in clusters and cyclically. To ascertain whether the interictal discharges can explain these cycles and forecast the onset of a seizure, we analyzed the data in greater detail,” continues Dr Baud.

Related Stories

To do this, Baud collaborated with Vikram Rao, neurologist at UCSF, to obtain neuronal activity data collected over several years using devices implanted long-term in the brains of patients with epilepsy. After confirming that there were indeed cycles of cerebral epileptic activity, the scientists turned their attention to statistical analysis.

This approach helped highlight a phenomenon known as the “pro-ictal state” where the probability of the onset of a seizure is high. “As with weather disturbances, there are several time scales in epileptic brain activity”, points out Dr Baud. “The weather is influenced by the cycle of the seasons or day and night. On an intermediate scale, when a weather front approaches, the probability that it will rain increases for several days and is, therefore, better predictable. These three scales of cyclic regulation also exist for epilepsy.”

The right timeframe

The electrical activity in the brain is a reflection of the cellular activity of its neurons, more precisely their action potentials, electrical signals propagating along the neural network to transmit information. Action potentials are well known to neuroscientists, and their probability can be modelled using mathematical laws. “We adapted these mathematical models to the epileptic discharges to find out whether they heralded or inhibited a seizure”, explains Dr Proix.

To boost the predictive reliability, recordings of brain activity over very long periods were required. Using this approach, fronts with a high probability of seizure lasting several days could be determined for a majority of patients, making it possible to predict seizures several days in advance in some. With brain activity data collected over periods of at least six months, seizure prediction is informative for two-thirds of patients.

The analytical approach is sufficiently “light” to allow the transmission of data in real time on a server or directly on a microprocessor with a device small enough to be implanted in the skull. The researchers are now working in collaboration with the Wyss Center for Bio and Neuroengineering, based at Campus Biotech in Geneva, to develop a minimally invasive brain monitoring device to record the long-term data needed to forecast seizures. The device, which slips under the skin of the scalp, could give people with epilepsy the power to plan their lives according to the likelihood of having a seizure.

Source: University of Geneva

Journal reference: Proix, T., et al. (2020) Forecasting seizure risk in adults with focal epilepsy: a development and validation study. Lancet Neurologydoi.org/10.1016/S1474-4422(20)30396-3.

Tags: BrainDrugsEpilepsyEpileptic SeizureFrequencyHospitalMedicineMental HealthNeurological DiseaseNeurologyNeuronsNeurosurgeryResearchSeizureSkin

, , , , , , , , , , , , , ,

Leave a comment

[WEB PAGE] Individual frequency can be used to control brain activity – News

Reviewed by Emily Henderson, B.Sc.Aug 17 2020

Individual frequency can be used to specifically influence certain areas of the brain and thus the abilities processed in them – solely by electrical stimulation on the scalp, without any surgical intervention. Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences have now demonstrated this for the first time.

Stroke, Parkinson’s disease and depression – these medical illnesses have one thing in common: they are caused by changes in brain functions. For a long time, research has therefore been conducted into ways of influencing individual brain functions without surgery in order to compensate for these conditions.

Scientists at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany, have taken a decisive step. They have succeeded in precisely influencing the functioning of a single area of the brain. For a few minutes, they inhibited exactly the area that processes the sense of touch by specifically intervening in its rhythm. As a result, the area that was less networked with other brain regions, its so-called functional connectivity, decreased, and thus also the exchange of information with other brain networks.

This was possible because the researchers had previously determined each participant’s individual brain rhythm that occurs when perceiving touch. With the personal frequency, they were able to modulate the targeted areas of the brain one at a time in a very precise manner using what is known as transcranial alternating current stimulation. “This is an enormous advance,” explains Christopher Gundlach, first author of the underlying study. “In previous studies, connectivity fluctuated extensively when the current was distributed in different areas of the brain. The electrical current randomly sought its own path in the brain and thus affected different brain areas simultaneously in a rather imprecise manner.

In a preliminary study, the neuroscientists had already observed that this form of stimulation not only reduces the exchange of the targeted brain networks with other networks, it also affects the brain’s ability to process information, in this case the sense of touch. When the researchers inhibited the responsible somatosensory network, the perception threshold increased. The study participants only perceived stimuli when they were correspondingly strong. When, on the other hand, they stimulated the region, the threshold value dropped and the study participants already felt very gentle electrical stimuli.

The deliberate change in brain rhythm lasted only briefly. As soon as the stimulation is switched off, the effect disappears again. Nevertheless, the results are an important step towards a targeted therapy for diseases or disorders caused by disturbed brain functions”.

Bernhard Sehm, Study Leader

Targeted brain stimulation could help to improve, direct and, if necessary, attenuate the flow of information.

Source: Max Planck Institute for Human Cognitive and Brain Sciences

Journal reference: Gundlach, C., et al. (2020) Reduction of somatosensory functional connectivity by transcranial alternating current stimulation at endogenous mu-frequency.  NeuroImage. doi.org/10.1016/j.neuroimage.2020.117175.

, , , , , , ,

Leave a comment

[WEB PAGE] International researchers propose new classification system of seizures

Epilepsy is a wide-spread neurological disorder that affects around 50 million people worldwide. It is characterized by recurrent epileptic seizures, which are sudden bursts of electrical activity in the brain. There are many different types of seizures, and a person with epilepsy can experience more than one type.

Clinicians today use EEG measurements, with electrodes either placed on a patient’s scalp or inside the brain, to identify when and where a seizure begins. But these measurements alone do not always provide enough information to understand the type of seizure and make optimal decisions regarding treatment.

Now, an international team of researchers led by Aix-Marseille University in France and the University of Michigan has proposed a new classification system of seizures based on a deep understanding and mathematical modelling of brain oscillations. “It represents the first objective and unbiased taxonomy of its kind”, says one of the lead authors, HBP-scientist Prof. Viktor Jirsa from Aix-Marseille University.

The researchers used “bifurcation theory” – a method commonly used in fields such as physics and engineering – to analyze data from over a hundred patients across the globe. Researchers from the University of Melbourne and Monash University, both in Australia, the University of Freiburg in Germany, and Kyoto University in Japan also contributed to the work. Seizures with similar properties were categorized into groups.

They found sixteen types of seizure dynamics – or ‘dynamotypes’ – with distinct characteristics. “Similar to the periodic table of elements in chemistry, we demonstrated the existence of a clear classification system of seizures”, says Jirsa.

The system could lead clinicians to a better understanding of seizures and how they should be treated. “Seizure types react differently to treatments. For instance, some seizures can be stopped through electric stimulation, others not, dependent on their dynamotype. The systems scientific basis is theory work developed around the Epileptor, a central epilepsy model we developed in the Human Brain Project that is also at the heart of a large clinical trial running now”, the researcher explains.

Classification, however, is not explanation. There is much work ahead of us to better understand epilepsy mechanisms. This is where EBRAINS will play a key role, as it provides the tools connecting cellular, network and brain imaging signals aiding in mechanism discovery. ”

Prof. Viktor Jirsa, HBP-Scientist from Aix-Marseille University

EBRAINS is a new shared digital brain research infrastructure for the European Union that the Human Brain Project (HBP) is building.

Within the HBP, Jirsa and his team had first begun adapting the open network simulator The Virtual Brain towards applications in epilepsy. The work has laid the foundations for project EPINOV (“Improving EPilepsy surgery management and progNOsis using Virtual brain technology”) a multi-year project involving more than a dozen French hospitals that is funded by the French state. EPINOV tests whether the use of the personalized HBP modeling technology for epilepsy networks can improve surgery preparation in drug-resistant patients.

via International researchers propose new classification system of seizures

 

, , , , , , , , ,

Leave a comment

[NEWS] Novel artificial intelligence algorithm helps detect brain tumor

 

A brain tumor is a mass of abnormal cells that grow in the brain. In 2016 alone, there were 330,000 incident cases of brain cancer and 227,000 related-deaths worldwide. Early detection is crucial to improve patient prognosis, and thanks to a team of researchers, they developed a new imaging technique and artificial intelligence algorithm that can help doctors accurately identify brain tumors.

 

Image Credit: create jobs 51 / Shutterstock.com

Image Credit: create jobs 51 / Shutterstock.com

Published in the journal Nature Medicine, the study reveals a new method that combines modern optical imaging and an artificial intelligence algorithm. The researchers at New York University studied the accuracy of machine learning in producing precise and real-time intraoperative diagnosis of brain tumors.

In the past, the only way to diagnose brain tumors is through hematoxylin and eosin staining of processed tissue in time. Plus, interpretation of the findings relies on pathologists who examine the specimen. The researchers hope the new method will provide a better and more accurate diagnosis, which can help initiate effective treatments right away.

In cancer treatment, the earlier cancer has been diagnosed, the earlier the oncologists can start the treatment. In most cases, early detection improves health outcomes. The researchers have found that their novel method of detection yielded a 94.6 percent accuracy, compared to 93.9 percent for pathology-based interpretation.

The imaging technique

The researchers used a new imaging technique called stimulated Raman histology (SRH), which can reveal tumor infiltration in human tissue. The technique collects scattered laser light and emphasizes features that are not usually seen in many body tissue images.

With the new images, the scientists processed and studied using an artificial intelligence algorithm. Within just two minutes and thirty seconds, the researchers came up with a brain tumor diagnosis. The fast detection of brain cancer can help not only in diagnosing the disease early but also in implementing a fast and effective treatment plan. With cancer caught early, treatments may be more effective in killing cancer cells.

The team also utilized the same technology to accurately identify and remove undetectable tumors that cannot be detected by conventional methods.

“As surgeons, we’re limited to acting on what we can see; this technology allows us to see what would otherwise be invisible, to improve speed and accuracy in the OR, and reduce the risk of misdiagnosis. With this imaging technology, cancer operations are safer and more effective than ever before,” Dr. Daniel A. Orringer, associate professor of Neurosurgery at NYU Grossman School of Medicine, said.

Study results

The study is a walkthrough of various ideas and efforts by the research team. First off, they built the artificial intelligence algorithm by training a deep convolutional neural network (CNN), containing more than 2.5 million samples from 415 patients. The method helped them group and classify tissue samples into 13 categories, representing the most common types of brain tumors, such as meningioma, metastatic tumors, malignant glioma, and lymphoma.

For validation, the researchers recruited 278 patients who are having brain tumor resection or epilepsy surgery at three university medical centers. The tumor samples from the brain were examined and biopsied. The researchers grouped the samples into two groups – control and experimental.

The team assigned the control group to be processed traditionally in a pathology laboratory. The process spans 20 to 30 minutes. On the other hand, the experimental group had been tested and studied intraoperatively, from getting images and processing the examination through CNN.

There were noted errors in both the experimental and control groups but were unique from each other. The new tool can help centers detect and diagnose brain tumors, particularly those without expert neuropathologists.

“SRH will revolutionize the field of neuropathology by improving decision-making during surgery and providing expert-level assessment in the hospitals where trained neuropathologists are not available,” Dr. Matija Snuderl, associate professor in the Department of Pathology at NYU Grossman School of Medicine, explained.

Journal references:

Patel, A., Fisher, J, Nichols, E., et al. (2019). Global, regional, and national burden of brain and other CNS cancer, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. The Lancet Neurology. https://www.thelancet.com/journals/laneur/article/PIIS1474-4422(18)30468-X/fulltext#%20

Hollon, T., Pandian, B, Orringer, D. (2019). Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks. Nature Medicine. https://www.nature.com/articles/s41591-019-0715-9

 

via Novel artificial intelligence algorithm helps detect brain tumor

, , , , , , , , , , , , , , , , , , , , , ,

Leave a comment

[WEB SITE] Depression: MedlinePlus

Also called: Clinical depression, Dysthymic disorder, Major depressive disorder, Unipolar depression

See, Play and Learn

Resources

 

Summary

Depression is a serious medical illness. It’s more than just a feeling of being sad or “blue” for a few days. If you are one of the more than 19 million teens and adults in the United States who have depression, the feelings do not go away. They persist and interfere with your everyday life. Symptoms can include

  • Feeling sad or “empty”
  • Loss of interest in favorite activities
  • Overeating, or not wanting to eat at all
  • Not being able to sleep, or sleeping too much
  • Feeling very tired
  • Feeling hopeless, irritable, anxious, or guilty
  • Aches or pains, headaches, cramps, or digestive problems
  • Thoughts of death or suicide

Depression is a disorder of the brain. There are a variety of causes, including genetic, biological, environmental, and psychological factors. Depression can happen at any age, but it often begins in teens and young adults. It is much more common in women. Women can also get postpartum depression after the birth of a baby. Some people get seasonal affective disorder in the winter. Depression is one part of bipolar disorder.

There are effective treatments for depression, including antidepressants, talk therapy, or both.

NIH: National Institute of Mental Health

Start Here

Diagnosis and Tests

Treatments and Therapies

Living With

Related Issues

Specifics

Genetics

Health Check Tools

Statistics and Research

Clinical Trials

Find an Expert

Children

Men

Women

Older Adults

Patient Handouts

via Depression: MedlinePlus

, , , , , , , , , ,

Leave a comment

[WEB PAGE] Study reveals three effective treatments to stop epilepsy seizures

 

There are effective treatments to stop life-threatening epilepsy seizures when the initial treatment has failed, a sweeping new study reveals.

The study offers important answers about three such emergency drugs that are used to treat prolonged seizures, known as status epilepticus, even though physicians have had little understanding of the drugs’ effectiveness. Until now, there has been no clear indication of which is best or how much should be given.

The study found that the three drugs – intravenous levetiracetam, fosphenytoin, and valproate – were all about equally effective at stopping the potentially deadly seizures when the default choice, benzodiazepines, proved unable to do so. The results were so clear that the shocked researchers stopped their trial early.

When we planned the study, we didn’t even know if these drugs work 10%, 25% or 50% of the time. So the big, big takeaway is that each of these drugs works about 45 percent of the time. And this is an important finding because it tells us patients can get better. They don’t have to be placed on a on a ventilator [breathing machine].”

Jaideep Kapur, MBBS, PhD, investigator and the head of the University of Virginia Brain Institute

Effect on Clinical Practice

The study’s findings, published in the prestigious New England Journal of Medicine, both affirm existing clinical practices and suggest a major change.

Doctors can feel confident that their preferred drug of choice is as effective as the other options, Kapur noted, but they also should significantly increase how much levetiracetam they give when they choose it.

“Prior to this, people were using their best guess as to which drug to use and how much of it to use. And this puts those things to rest and tells you exactly how much of which to use, and what to expect,” said Kapur, of the UVA School of Medicine’s Department of Neurology.

The trial organizers tested the maximum safe dose of each of the drugs so there would be no question whether too little had been used to gauge the medicine’s effectiveness. In so doing, they gave twice as much levetiracetam as many doctors administer.

“When I started 25 years ago, there was not a single scientifically proven drug [for status epilepticus]. We didn’t know which drug to use, even for the first-line treatment, and how much of them to use,” Kapur said. “And 25 years later, we can treat more than 80% of the patients – 85% of the patients – using scientifically proven drugs. 85% of our patients will get better, will stop having seizures and start waking up. That is the effect of scientific research on improving care of patients, and this is real.”

About the Epilepsy Seizure Trial

The randomized, double-blinded trial looked at the effect of the drugs in 384 patients at 57 emergency departments in the United States between November 2015 and the end of October 2017.

The researchers originally planned to study 795 patients over five years, but the results were so clear that was deemed unnecessary. “Clinical trials are notorious for going over long and over budget, and we came in under budget,” Kapur said.

That was possible, he said, because of the participation of many top experts in both the United States and Europe. Participating sites included the University of Michigan, Medical University of South Carolina, UVA, Children’s National Medical Center in Washington, D.C., and many more.

“It was an amazingly accomplished group of people,” Kapur said. “We had the best experts from all over the United States and Europe. For me, it’s been a great joy working with the team as the leader of the Brain Institute. That’s the spirit I want to bring to UVA. That’s really what motivated me to start the Brain Institute: to fashion these teams within UVA, so that we can do really significant, societally impactful research.”

UVA Emergency Medicine physician Stephen Huff, MD, led the study at the UVA site, which enrolled seven subjects. Amy Fansler, Emily Gray and Lea Becker helped organize the study.

Kapur expressed his gratitute to all the patients who participated in the study. “President Ryan [UVA President Jim Ryan] has said we must be great and good,” Kapur said, “and this is the kind of good we want to do.”

Next Steps

The researchers are now looking more closely at the drugs’ effectiveness and dosing in children. That will offer important information on how best to treat the young patients, as the causes of status epilepticus in adults and children often differ.

 

via Study reveals three effective treatments to stop epilepsy seizures

, , , , , , , , , , , , ,

Leave a comment

[WEB SITE] Traumatic brain injuries could be healed using peptide hydrogels

Traumatic brain injury (TBI) –– defined as a bump, blow or jolt to the head that disrupts normal brain function –– sent 2.5 million people in the U.S. to the emergency room in 2014, according to statistics from the U.S. Centers for Disease Control and Prevention. Today, researchers report a self-assembling peptide hydrogel that, when injected into the brains of rats with TBI, increased blood vessel regrowth and neuronal survival.

The researchers will present their results at the American Chemical Society (ACS) Fall 2019 National Meeting & Exposition. ACS, the world’s largest scientific society, is holding the meeting here through Thursday. It features more than 9,500 presentations on a wide range of science topics.

“When we think about traumatic brain injuries, we think of soldiers and athletes,” says Biplab Sarkar, Ph.D., who is presenting the work at the meeting. “But most TBIs actually happen when people fall or are involved in motor vehicle accidents. As the average age of the country continues to rise, the number of fall-related accidents in particular will also increase.”

TBIs encompass two types of injuries. Primary injury results from the initial mechanical damage to neurons and other cells in the brain, as well as blood vessels. Secondary injuries, which can occur seconds after the TBI and last for years, include oxidative stress, inflammation and disruption of the blood-brain barrier. “The secondary injury creates this neurotoxic environment that can lead to long-term cognitive effects,” Sarkar says. For example, TBI survivors can experience impaired motor control and an increased rate of depression, he says. Currently, there is no effective regenerative treatment for TBIs.

Sarkar and Vivek Kumar, Ph.D., the project’s principal investigator, wanted to develop a therapy that could help treat secondary injuries.

We wanted to be able to regrow new blood vessels in the area to restore oxygen exchange, which is reduced in patients with a TBI. Also, we wanted to create an environment where neurons can be supported and even thrive.”

Biplab Sarkar, Ph.D., New Jersey Institute of Technology

The researchers, both at the New Jersey Institute of Technology, had previously developed peptides that can self-assemble into hydrogels when injected into rodents. By incorporating snippets of particular protein sequences into the peptides, the team can give them different functions. For example, Sarkar and Kumar previously developed angiogenic peptide hydrogels that grow new blood vessels when injected under the skin of mice.

To adapt their technology to the brain, Sarkar and Kumar modified the peptide sequences to make the material properties of the hydrogel more closely resemble those of brain tissue, which is softer than most other tissues of the body. They also attached a sequence from a neuroprotective protein called ependymin. The researchers tested the new peptide hydrogel in a rat model of TBI. When injected at the injury site, the peptides self-assembled into a hydrogel that acted as a neuroprotective niche to which neurons could attach.

A week after injecting the hydrogel, the team examined the rats’ brains. They found that in the presence of the hydrogel, survival of the brain cells dramatically improved, resulting in about twice as many neurons at the injury site in treated rats than in control animals with brain injury. In addition, the researchers saw signs of new blood vessel formation. “We saw some indications that the rats in the treated group were more ambulatory than those in the control group, but we need to do more experiments to actually quantify that,” Sarkar says.

According to Kumar, one of the next steps will be to study the behavior of the treated animals to assess their functional recovery from TBI. The researchers are also interested in treating rats with a combination of their previous angiogenic peptide and their new neurogenic version to see if this could enhance recovery. And finally, they plan to find out if the peptide hydrogels work for more diffuse brain injuries, such as concussions. “We’ve seen that we can inject these materials into a defined injury and get good tissue regeneration, but we’re also collaborating with different groups to find out if it could help with the types of injuries we see in soldiers, veterans and even people working at construction sites who experience blast injuries,” Kumar says.

via Traumatic brain injuries could be healed using peptide hydrogels

, , , , , , , , , , , , , , , , , , , , , , , ,

Leave a comment

%d bloggers like this: