Researchers found that hematopoietic stem cell transplantation is a highly effective method for treating patients with monogenic inflammatory bowel disease, a more severe form of the illness that usually affects younger patients.
Category: biotech/medical
By Nina Bai
In a Stanford Medicine-led study, researchers combed through billions of compounds to find one that could enhance naloxone’s ability to fend off more potent opioids, with promising results in mice.
A research team led by the Borzage Laboratory at Children’s Hospital Los Angeles tested a new functional magnetic resonance imaging (fMRI) analysis method to measure cerebrovascular health in aging adults. What they found was unexpected and validated the usefulness of this method for measuring neurovascular aging in childhood diseases.
The researchers measured the cerebrovascular reactivity of the brains of 53 men and women between the ages of 51 to 83. Cerebrovascular reactivity is the ability of the blood vessels in the brain to dilate in response to a stimulus. The fMRI method they used—known as blood oxygen level dependent-cerebrovascular reactivity (BOLD-CVR)—measures the ability of the brain’s vessels to flexibly regulate blood flow in response to changes in carbon dioxide levels.
“How well the vessels react reveals a lot about your brain health,” says lead author Bethany Sussman, Ph.D., Research Scientist, Neonatology, at CHLA. “If a certain part of the brain can’t perform that function very well, that area is likely more susceptible to stroke.
Scientists have discovered a way to convert fluctuating lasers into remarkably stable beams that defy classical physics, opening new doors for photonic technologies that rely on both high power and high precision.
Lasers are essential tools in science, industry and medicine, but increasing their power often results in “noise”—unpredictable fluctuations in intensity that disrupt applications requiring consistent, stable light.
Researchers led by Cornell and the Massachusetts Institute of Technology have demonstrated how noisy, amplified lasers can be transformed into ultra-stable beams through the clever use of optical fibers and filters. The technique was detailed in Nature Photonics.
Chronic pain conditions, characterized by persistent or recurrent pain in specific parts of the body, can be highly debilitating and often significantly reduce the quality of life of the individuals experiencing them. Statistics suggest that approximately 20.9% of adults living in the United States have experienced chronic pain at some point in their lives, while 6.9% have experienced severe chronic pain that significantly impacted their daily functioning and well-being.
Currently, chronic pain is primarily treated using pain-relief medications, many of which are based on opioids. Yet many of these pharmaceutical drugs are highly addictive and have severe side effects, so they often end up causing more harm than good.
In recent years, some scientists and engineers have been trying to devise alternative pain-management strategies that do not rely on opioids and can ease the pain of patients without adversely impacting their health. One proposed solution entails the use of implantable electrical stimulators, devices that can be surgically inserted into a patient’s body, delivering electrical signals to their nerves or spinal cord to reduce the pain they are experiencing.
A pioneering method to simulate how nanoparticles move through the air could boost efforts to combat air pollution, suggests a study in the Journal of Computational Physics.
Tiny particles found in exhaust fumes, wildfire smoke and other forms of airborne pollution are linked with serious health conditions such as stroke, heart disease and cancer, but predicting how they move is notoriously difficult, researchers say.
Now, scientists have developed a new computer modeling approach that dramatically improves the accuracy and efficiency of simulating how nanoparticles behave in the air. In practice, this could mean simulations that can currently take weeks to run could be completed in a matter of hours, the team says.
Persons with Parkinson’s disease increasingly lose their mobility over time and are eventually unable to walk. Hope for these patients rests on deep brain stimulation, also known as a brain pacemaker.
In a current study, researchers at Ruhr University Bochum and Philipps-Universität Marburg, Germany, investigated whether and how stimulation of a certain region of the brain can have a positive impact on ambulatory ability and provide patients with a higher quality of life. To do this, the researchers used a technique in which the nerve cells are activated and deactivated via light. Their report is published in the journal Scientific Reports.
Researchers led by Maike Sander, Scientific Director of the Max Delbrück Center, have developed a vascularized organoid model of hormone secreting cells in the pancreas. The advance, published in “Developmental Cell,” promises to improve diabetes research and cell-based therapies.
An international team of researchers led by Max Delbrück Center Scientific Director Professor Maike Sander has for the first time developed an organoid model of human pluripotent stem cell-derived pancreatic islets (SC-islets) with integrated vasculature. Islets are cell clusters in the pancreas that house several different types of hormone-secreting cells, including insulin-producing beta cells. Researchers in the Sander lab at the University of California, San Diego, found that SC-islet organoids with blood vessels contained greater numbers of mature beta cells and secreted more insulin than their non-vascularized counterparts. The vascularized organoids more closely mimicked islet cells found in the body. The study was published in “Developmental Cell.”
“Our results highlight the importance of a vascular network in supporting pancreatic islet cell function,” says Sander. “This model brings us closer to replicating the natural environment of the pancreas, which is essential for studying diabetes and developing new treatments.”
Google DeepMind has developed a groundbreaking AI that can solve complex real-world problems like delivery planning and route optimization without needing exact answers or perfect data. By integrating a method called MCMC layers into neural networks, the system learns to make smart, flexible decisions in real time—even under tough constraints. This new approach outperforms older models and could transform industries like logistics, healthcare scheduling, and city traffic management.
🤖 What’s Inside:
DeepMind’s New AI That Solves Real-World Problems Without Exact Data.
https://arxiv.org/abs/2505.14240
How MCMC Layers Make Neural Networks Smarter at Planning.
AI vs Classical Methods in Solving NP-Hard Logistics Tasks.
🎥 What You’ll See:
Why traditional AI fails at scheduling and delivery planning.
How Google’s new AI tackles chaotic, constraint-heavy problems in milliseconds.
The secret behind MCMC layers and simulated annealing in neural networks.
Real-world results that could reshape logistics, healthcare, and urban planning.
📊 Why It Matters:
This isn’t about smarter chatbots—it’s about AI solving the hardest real-life decisions with speed and flexibility. From dynamic routing to hospital schedules, DeepMind’s breakthrough shows AI can finally plan like a pro—even with messy, incomplete data.
#ai #deepmind #google
Amidst the continued struggle to treat non-small-cell lung cancer, a new study led by Stanford University scientists suggests that a patient’s response to immunotherapy may hinge on how immune cells cluster around tumors. Their results reveal that spatial arrangements of certain immune cells within tumors can serve as powerful predictors of treatment response, surpassing existing biomarker tests.
Lung cancer leads global cancer mortality, and non-small-cell variants make up more than 80% of cases. Immune checkpoint inhibitors have transformed therapy yet help only 27–45% of recipients.
Reliable predictive biomarkers for immunotherapy response have eluded clinicians, who currently rely on PD-L1 immunohistochemistry, tumor mutational burden, and microsatellite stability tests, each offering modest predictive performance across trials and are prone to inconsistency.