A team from Stanford Medicine has developed AI-powered digital twins of the brain, trained on large datasets of brain activity. These models predict neural responses to new stimuli, offering profound insights into brain function.
Category: biotech/medical – Page 75
An optogenetic method for controlling the movement of starfish oocytes has been developed, which could have applications for drug delivery.
Genome editing has advanced at a rapid pace with promising results for treating genetic conditions-but there is always room for improvement. A new paper by investigators from Mass General Brigham published in Nature showcases the power of scalable protein engineering combined with machine learning to boost progress in the field of gene and cell therapy. In their study, authors developed a machine learning algorithm-known as PAMmla-that can predict the properties of about 64 million genome editing enzymes. The work could help reduce off-target effects and improve editing safety, enhance editing efficiency, and enable researchers to predict customized enzymes for new therapeutic targets. Their results are published in Nature.
“Our study is a first step in dramatically expanding our repertoire of effective and safe CRISPR-Cas9 enzymes. In our manuscript we demonstrate the utility of these PAMmla-predicted enzymes to precisely edit disease-causing sequences in primary human cells and in mice,” said corresponding author Ben Kleinstiver, PhD, Kayden-Lambert MGH Research Scholar associate investigator at Massachusetts General Hospital (MGH), a founding member of the Mass General Brigham healthcare system. “Building on these findings, we are excited to have these tools utilized by the community and also apply this framework to other properties and enzymes in the genome editing repertoire.”
CRISPR-Cas9 enzymes can be used to edit genes at locations throughout the genomes, but there are limitations to this technology. Traditional CRISPR-Cas9 enzymes can have off-target effects, cleaving or otherwise modifying DNA at unintended sites in the genome. The newly published study aims to improve this by using machine learning to better predict and tailor enzymes to hit their targets with greater specificity. The approach also offers a scalable solution-other attempts at engineering enzymes have had a lower throughput and typically yielded orders of magnitude fewer enzymes.
Researchers have developed a machine learning model that predicts Cas9 proteins that can be tailored with designer properties for therapeutic use.
Next-generation DNA sequencing (NGS)—the same technology which is powering the development of tailor-made medicines, cancer diagnostics, infectious disease tracking, and gene research—could become a prime target for hackers.
A study published in IEEE Access highlights growing concerns over how this powerful sequencing tool—if left unsecured—could be exploited for data breaches, privacy violations, and even future biothreats.
Led by Dr. Nasreen Anjum from the University of Portsmouth’s School of Computing, it is the first comprehensive research study of cyber-biosecurity threats across the entire NGS workflow.
The relationships between different people can change over time, as the result of their life choices, internal or external experiences and various other factors. Some people develop a greater tendency to avoid others in their lives, including friends, colleagues, family members and acquaintances.
Researchers at Icahn School of Medicine at Mount Sinai recently set out to test the hypothesis that social avoidance could be quantified as people’s navigation in an abstract social space. Their paper, published in Communications Psychology, introduces a new framework for studying and probing people’s social avoidance.
“This work grew out of the idea that the way that people often talk about navigating social relationships —’climbing the ladder’ at work, or ‘growing distant’ from a friend—might be more than a metaphor,” Matthew Schafer, first author of the paper, told Phys.org.
People with Alzheimer’s disease may retain their ability to empathize, despite declines in other social abilities, finds a new study led by University College London (UCL) researchers.
The researchers found that people with Alzheimer’s disease scored slightly higher on a measure of empathy than peers of the same age with mild cognitive impairment, despite scoring worse on other measures of social cognition such as recognizing facial emotions and understanding the thoughts of others.
The authors of the study, published in Alzheimer’s & Dementia, say this may be the first time a cognitive domain has been found to improve in dementia.
1 State Key Laboratory of Systems Medicine for Cancer, Renji-Med-X Stem Cell Research Center, Department of Urology, Renji Hospital, Shanghai Cancer Institute, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
2Department of Emergency Medicine, Shanghai Seventh People’s Hospital, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China.
3Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Over the past decades, electronics engineers developed increasingly small, flexible and sophisticated sensors that can pick up a wide range of signals, ranging from human motions to heartrate and other biological signals. These sensors have in turn enabled the development of new electronics, including smartwatches, biomedical devices that can help monitor the health of users over time and other wearable or implantable systems.
Strain sensors, which are designed to convert mechanical force into electrical signals, are among the most widely used sensing devices within the electronics industry, as they can be valuable for tracking both human movements and health-related biological signals. While these sensors are already embedded in many electronic devices, most existing solutions are only able to track movements in one direction.
Sensors that can accurately pick up movements and forces in multiple directions could be highly advantageous, as they could be applied to a wider range of scenarios. In addition, these sensors could be embedded in existing electronic devices to broaden their functions or enhance their capabilities.
In 2021, research led by Ryan Flynn, MD, Ph.D., and his mentor, Nobel laureate Carolyn Bertozzi, Ph.D., opened a new chapter in biology, characterizing a new kind of player on the cell surface: glycoRNAs. Extending this discovery recently in Cell, Flynn and colleagues showed that glycoRNAs form highly organized clusters with RNA-binding proteins on the cell surface. These clusters appear to regulate communication between cells and their environment.
Now, reporting in Nature Biotechnology, Flynn’s team in the Stem Cell Program at Boston Children’s Hospital and Dana-Farber/Boston Children’s Cancer and Blood Disorders Center demonstrate a first application of this newfound biology: fighting cancer.
With collaborators at the Cambridge (UK) Stem Cell Institute, led by Konstantinos Tzelepis, Ph.D., and Maria Eleftheriou, Ph.D., they show that one RNA-binding protein on the cell surface, NPM1, could be a potent, selective target for treating acute myeloid leukemia (AML), as well as solid tumors.