The debilitating effects of chronic pain affect millions worldwide. Researchers at the University of Southern California’s (USC) Alfred E. Mann Department of Biomedical Engineering have developed a groundbreaking solution: a flexible ultrasound-induced wireless implantable (UIWI) stimulator designed for self-adaptive, personalized pain management. This revolutionary device harnesses machine learning algorithms to customize treatment for each patient and eliminates the need for bulky batteries or complex wired interfaces.

The UIWI stimulator’s core is a miniaturized piezoelectric element made from lead zirconate titanate (PZT), efficiently converting incoming ultrasound energy into electrical power. This wireless power supply allows the device to bend and twist with movement, ensuring optimal placement on the spinal cord. The electrical stimulation it provides rebalances signals that transmit and inhibit pain, effectively suppressing the sensation of pain.

Researchers successfully relieved chronic neuropathic pain in rodent models, demonstrating the effectiveness of the UIWI stimulator. Lab tests showed significant reductions in pain indicators, and rodents even preferred environments where the pain management system was activated, further confirming its efficacy.

The future of personalized pain relief is bright with this innovative technology. Future designs could miniaturize components for less invasive device implantation and evolve the wearable ultrasound transmitter into an untethered, miniaturized device or a wearable ultrasound array patch with imaging capabilities. With smartphone-controlled software, even more robust personalized pain management is possible.

This groundbreaking UIWI stimulator has the potential to transform chronic pain management by offering a truly personalized, intelligent, and effective pathway to pain relief.

The Rutgers Health researchers have made a groundbreaking discovery about how our brains process hunger and fullness cues. Two new studies, published in Nature Metabolism and Nature Communications, have mapped the first complementary wiring diagram of hunger and satiety in ways that could refine today’s blockbuster weight-loss drugs and blunt their side effects.

One study, led by Zhiping Pang of Robert Wood Johnson Medical School’s Center for NeuroMetabolism, pinpointed a slender bundle of neurons that runs from the hypothalamus to the brainstem. This pathway, known as GLP-1 receptors, is mimicked by weight-loss drugs such as Ozempic. When Pang’s team used optogenetics to fire axons with laser light, well-fed mice quit eating; when they silenced the circuit or deleted the receptor, the animals packed on weight.

The cells in this pathway bristle with GLP-1 receptors, which are proteins that play a key role in regulating energy balance. The study found that fasting weakened the connection until a burst of natural or synthetic GLP-1 restored it. Pang warns that drugs that keep the signal high around the clock could disrupt the brain’s normal rhythm and create some of the side effects of GLP-1 drugs, such as nausea, vomiting, constipation or diarrhea and muscle wasting.

For the other paper, Mark Rossi, who co-leads the Center for NeuroMetabolism with Pang, charted the circuit that triggers hunger. His group traced inhibitory neurons in the stria terminalis to similar cells in the lateral hypothalamus. When researchers triggered the connection, a suddenly hungry mouse would sprint for sugar water; when they blocked it, the animals lounged even after a long fast.

Hormones modulated the effect. An injection of ghrelin, the gut’s hunger messenger, revved food seeking, while leptin, the satiety signal, slammed it shut. Overfed mice gradually lost the response, but it returned after diets made them thin again.

Pang’s pathway shuts things down,” Rossi said. “Ours steps on the accelerator.” Although the circuits sit in different corners of the brain, members of both teams saw the same principle: Energy state rewires synapses quickly. During a fast, the hunger circuit gains sensitivity while the satiety circuit loosens; after a meal, the relationship flips.

It is the first time researchers have watched the push-pull mechanism operate in parallel pathways, a yin-yang arrangement that may explain why diets and drugs that treat only one side of the equation often lose power over time. The studies suggest a therapy targeting only the brainstem circuit and sparing peripheral organs might curb eating without the side effects.

Conversely, Rossi’s work hints that restoring the body’s response to the hunger-regulating hormone ghrelin could help dieters who plateau after months of calorie cutting. Both projects relied on the modern toolkit of neural biology – optogenetics to fire axons with laser light, chemogenetics to silence them, fiber-optic photometry to watch calcium pulses and old-fashioned patch-clamp recordings to monitor single synapses.

Follow-up work from both teams will explore more questions that could improve drug design. Pang wants to measure GLP-1 release in real time to see whether short bursts, rather than constant exposure, are enough to calm appetite. Rossi is cataloging the molecular identity of his hunger-trigger cells in hopes of finding drug targets that steer craving without crushing the joy of eating.

“You want to keep the system’s flexibility,” Rossi said. “It’s the difference between dimming the lights and flicking them off.”

The breakthroughs in brain mapping technology have brought us closer than ever before to understanding how our minds work. Researchers at Weill Cornell Medicine have developed an algorithm called the Krakencoder, which can accurately predict individual’s functional connectome about 20 times better than previous approaches. This study, published in Nature Methods, utilized imaging data from the Human Connectome Project to align neural activity with its underlying circuitry.

The brain’s wiring and activity patterns are crucial for understanding behavior, identifying biomarkers of disease, predicting outcomes in neurological disorders, and designing personalized interventions. Dr. Amy Kuceyeski, a senior author of the study, explains that regions “wired together” don’t always “fire together.” This patchwork approach to examining the brain has led scientists to develop different methods for processing raw images, resulting in various maps of the brain’s networks.

To overcome this limitation, Dr. Kuceyeski and her team built a tool that can take multiple views of the brain’s underlying system and collapse them into one unified interpretation. This autoencoder program, known as the Krakencoder, compresses and reconstructs more than a dozen different “flavors” of input data.

The researchers trained the Krakencoder on data from over 700 subjects who participated in the Human Connectome Project. They found that the Krakencoder allowed them to take an individual’s structural connectome and correctly predict their functional connectome about 20 times more accurately than previously published approaches.

The combined and compressed representation also predicted an individual’s age, sex, and cognitive performance scores received on tests administered along with imaging scans. This breakthrough has significant implications for understanding how anatomy and physiology give rise to our behaviors and abilities.

In the future, Dr. Kuceyeski and her colleagues plan to combine the Krakencoder with a network modification tool called NeMo that will allow them to examine the connectomes of people whose brains have been damaged by diseases. This approach could identify brain network connections associated with improved cognitive or motor performance and boost the activity of damaged circuits through transcranial magnetic stimulation, potentially hastening recovery.