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Advanced Neural Probes Reveal Predictable Patterns in Epileptic Brain Activity
In addition to suffering seizures, many people with epilepsy also experience bursts of abnormal brain activity called interictal epileptiform discharges (IEDs). These can happen thousands of times a day and interfere with attention, memory, language, and sleep. New data from a study led by scientists at University of California, San Francisco (UCSF) shows that these brain blips are not random events as once thought. The data shows that they unfold in a predictable pattern that can be detected before they occur, suggesting it may be possible to prevent them.
Details of their work are published in Nature Neuroscience in a paper titled “Laminar organization of cellular microcircuits modulating human interictal epileptiform discharges.” In it, the scientists explain that they used a high-resolution technology recently adapted for humans that records individual neuron activity to track more than 1000 neurons in four patients undergoing surgery for epilepsy. The so-called Neuropixel probes provide “a view into new ways we might address a debilitating aspect of epilepsy that we haven’t been able to tackle,” said Jon Kleen, MD, PhD, an associate professor of neurology at UCSF and co-senior author of the study.
Preventing brain blips would be a boon for patients’ quality of life because over time, the effects of these mental disruptions can be significant and may account for some of the cognitive impairment experienced by about half of people with epilepsy.
Neuropixels probes, which are thin devices lined with hundreds of sensors, are designed to record activity throughout the human cortex. This means that unlike current sensors which are limited to brain signals on the surface of the brain, Neuropixels can provide a three-dimensional view of brain activity. For the study, the scientists implanted the probes seven millimeters deep into the part of the brain where patients’ seizures originate—this is the tissue that surgeons typically remove to reduce epilepsy symptoms.
Inserting the probes here made it possible to observe what happened in the neurons before, during, and after each IED. While seizures appear as a burst of neurons firing in synchrony, when IEDs occur, they unfold sequentially. Specifically, one set of neurons was active about a second before the IED started followed by another set that generated the sharp electrical spike at its peak, and then a third set became active as the IED faded. “We could see individual neurons that were just microns apart from each other playing different roles in the process,” said Alex Silva, the study’s first author and a medical student and doctoral candidate in the UCSF-UC Berkeley Joint PhD program in bioengineering. “It was really striking.”
Previous studies have demonstrated that most neurons involved in IEDs are used in normal cognitive processing. According to this study, nearly 80% of the neurons involved in IEDs were also involved in language and perception. Current implantable devices for epilepsy may be able to help. They include closed loop neurostimulators that can detect abnormal brain activity and deliver electrical pulses that interrupt it. So in the case of IEDs, devices that monitor single neurons could use the activity of the first set of neurons announcing the arrival of the abnormal pattern as a warning signal. “That would be a major step forward, changing treatment from reactively responding to abnormal brain bursts to proactively preventing them in the first place,” Kleen said.
The post Advanced Neural Probes Reveal Predictable Patterns in Epileptic Brain Activity appeared first on GEN – Genetic Engineering and Biotechnology News.
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AI Predicts Gene Regulation for Drug Discovery Using Condensate Morphology
In a study published in Cell titled, “Deep learning of functional perturbations from condensate morphology,” researchers at Princeton University have applied AI to understand how drugs affect the dynamics of key structures within the cell. The work introduces a tool that can map morphology to functional outcomes and shed light on markers of health.
The authors examined the changes in shape of biomolecular condensates, tiny droplets in cells that drive transcription and other gene regulation processes linked to disease, including Alzheimer’s, ALS and cancer. The findings support a robust system for monitoring and evaluating cellular responses to drugs at a single-cell level.
“The central problem in biology is how do you get emergent structure from individual molecular interactions,” said Cliff Brangwynne, PhD, professor of chemical and biological engineering at Princeton and corresponding author of the study. “The key innovation here was to develop a way to learn from the images and classify the patterns that are emergent.”
The team used an advanced microscope to image nucleolar morphology changes in hundreds of human cells under a range of drug-controlled conditions. Machine learning tools sorted the images into four basic categories based on the shape of the nucleolus, uncovering “cap” and “necklace” shapes linked to cellular stress responses.
The authors ran a panel of drugs to examine the effect on nucleolar formation and measured changes in the condensate’s development. Varying concentrations caused different degrees of change in both caps and necklaces.
Two known anti-cancer drugs caused caps, while a third drug, called topotecan, triggered a new nucleolus morphology that the researchers labeled “flower.” While topotecan inhibits TOP1, an key enzyme during DNA replication, loss of TOP1 induced the flower shape and uncovered the enzyme’s role in maintaining nucleolar organization by regulating RNA processing.
“No one’s seen this flower morphology before,” said Brangwynne. “The network flagged it as not fitting neatly into the other three categories.”
The team also tested their neural network on other condensates related to RNA processes, observing similar dose-and-response results for drugs specific to nuclear speckles, a hub for messenger RNA activity, and condensates from respiratory syncytial virus.
This finding underscores the value of analyzing morphological changes. “You could be missing other important features,” said Anita Donlic, PhD, postdoctoral researcher and first author of the study. “Things that could tell you there’s new biology.”
The post AI Predicts Gene Regulation for Drug Discovery Using Condensate Morphology appeared first on GEN – Genetic Engineering and Biotechnology News.
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Elicio crashes on midstage pancreatic cancer miss but will advance to Phase 3
Elicio Therapeutics’ investigational cancer immunotherapy failed to meet the primary endpoint of disease-free survival in a Phase 2 trial—a result the company attributed mostly to a disproportionate number of patients with higher residual disease.
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STAT+: Lilly’s Ajax acquisition may have been worth it
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A worsening shortage of Bicillin, Pfizer’s injectable form of penicillin, left an Arizona woman unable to receive timely treatment for syphilis during pregnancy.
Also, the FDA approved Sanofi’s diabetes drug Tzield after an unusually contentious review process, and the Trump administration has proposed closing a Medicare negotiation loophole.
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A worsening shortage of Bicillin, Pfizer’s injectable form of penicillin, left an Arizona woman unable to receive timely treatment for syphilis during pregnancy.
Also, the FDA approved Sanofi’s diabetes drug Tzield after an unusually contentious review process, and the Trump administration has proposed closing a Medicare negotiation loophole.
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