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Why newborn memory circuits start crowded, then slim down as brains mature

The hippocampus is a key brain region involved in memory formation and spatial orientation. It transforms short-term memories into long-term ones, helping us retain and build upon our experiences. Researchers led by Magdalena Walz Professor for Life Sciences Peter Jonas at the Institute of Science and Technology Austria (ISTA) focus precisely on this area of the brain.

Their latest study, published in Nature Communications, reveals how the central neural network in the hippocampus develops after birth.

Imagine a blank sheet of paper in front of you. There’s nothing on it so you start writing, adding more and more information. This is the principle of tabula rasa—the “blank slate.”

Group averages obscure how an individual’s brain controls behavior, study finds

Studying cognition by averaging data from many people’s brain scans hides how individuals use their brains, new Stanford Medicine research has shown. In particular, children who struggle with goal-oriented tasks show distinct patterns of brain activity when their data is analyzed individually, rather than as part of a group of kids with mixed abilities. The findings, which have implications for understanding how the brain works in such conditions as attention-deficit/hyperactivity disorder, will be published April 27 in Nature Communications.

“Investigating how dynamics unfold within individual brains can provide significant insights into the neuroscience of individual differences and help us tackle questions that cannot be answered using conventional approaches,” said Percy Mistry, Ph.D., a research scholar in psychiatry and behavioral sciences, and a lead author of the study.

Mistry shares lead authorship with Nicholas Branigan, MS, a research data analyst in psychiatry and behavioral sciences. The senior author is Vinod Menon, Ph.D., a professor of psychiatry and behavioral sciences and the Rachael L. and Walter F. Nichols, MD, Professor.

AI tool may spot ADHD years before children are diagnosed

Attention-deficit/hyperactivity disorder (ADHD) affects millions of children, yet many go years without a diagnosis, missing the chance for early support that can change long-term outcomes even when early signs are present. In a new study, Duke Health researchers found that artificial intelligence tools can analyze routine electronic health records to accurately estimate a child’s risk of developing ADHD years before a typical diagnosis. By reviewing patterns in everyday medical data, the approach could help flag children who may benefit from earlier evaluation and follow-up.

The research, published in Nature Mental Health, highlights how powerful insights can come from information already collected during regular health care visits to help support early decision making by primary care providers.

“We have this incredibly rich source of information sitting in electronic health records,” said Elliot Hill, lead author of the study and data scientist in the Department of Biostatistics & Bioinformatics at Duke University School of Medicine.

The Ear as a Therapeutic Gateway to the Vagus Nerve

B cell-intrinsic type I interferon signaling contributes to defective antibody responses to a model antigen during persistent LCMV infection.

During persistent LCMV infection, Laulhé et al. reveal that B cell-intrinsic type I interferon (IFN-I) signaling drives defective affinity maturation. Although IFN-I acts directly within B cells, its absence alone fails to restore normal humoral responses, indicating that additional extrinsic mechanisms cooperate to sustain dysfunction.

Global genetic interaction network of a human cell maps conserved principles and informs functional interpretation of gene co-essentiality profiles

Now online! CRISPR perturbation of ∼4 million gene pairs in human HAP1 cells maps ∼89,000 genetic interactions, revealing a hierarchical network that links genes to complexes, pathways, and cellular processes and elucidates the genes underlying cancer cell genetic dependencies.

Oncostatin-M ligand-based CAR-T therapy displays robust anti-tumor activity against osteosarcoma

CAR-T therapy has revolutionized treatments for many hematologic malignancies, but it has shown far less efficacy against solid tumors. One reason for this lower efficacy in solid tumors is increased antigen heterogeneity. This study utilizes a ligand-based CAR-T approach, which allows targeting of multiple receptors by a single ligand. A high expression of the ligand oncostatin M’s (OSM) receptors, oncostatin M receptor (OSMR), and/or leukemic inhibitory factor receptor (LIFR) were noted in osteosarcoma cell lines and patient samples. Osteosarcoma is a bone cancer where treatment options have been stagnant for close to 40 years. Thus, this study explores the therapeutic potential of OSM ligand-based CAR-T cells against osteosarcoma.

Third-generation CAR-T cells expressing human OSM on their surface were created, with the surface expression of OSM confirmed by flow cytometry. Co-incubation of OSM CARs and osteosarcoma in vitro was performed, with cell death assessed via Incucyte and PI detection by flow cytometry. CAR-Ts were injected i.v. into mice with osteosarcoma cell line xenografts, and metastatic osteosarcoma. New patient-derived samples were tested for OSMR and LIFR expression and vulnerability to OSM CAR T cells. A new PDX model (named KKOS) from a patient with metastatic treatment-resistant osteosarcoma was characterized and tested for its susceptibility to OSM CAR T cells. All cytotoxic in vivo experiments were performed with n =3–6 mice per group per experiment.

OSM-CAR-T cells displayed cytotoxicity against osteosarcoma cell lines and patient samples expressing either one of OSM’s receptors in vitro and in vivo. Large increases in cytokine release, specifically IFNγ, were noted in a target-specific manner. One injection of OSM-CAR-T cells intravenously reduced tumor burden in two different mouse xenograft models. A similar anti-tumor effect was also noted in a metastatic model and a mouse model with multiple implanted KKOS tumors.

Room-temperature vibrations could transform how industry makes graphene

Researchers have demonstrated a new technique for creating 2D materials that runs at room temperature and increases production rates tenfold over current methods, without using toxic solvents. Scientists led by Dr. Jason Stafford from the Department of Mechanical Engineering demonstrated the method can produce nanosheets of conductors, semiconductors and insulators, which are the building blocks of all digital devices and technologies produced today. The research is published in the journal Small.

Dr. Stafford said, “Our work shows a new way of making 2D materials that overcomes the production capacity issues of current methods, while simultaneously embedding sustainable manufacturing practices.”

2D materials are ultra-thin materials that consist of a few layers of atoms. They have unique electronic, thermal, and mechanical properties that differ significantly from their 3D counterparts, and are ideal components for next-generation electronics, energy and sensor technologies.

This ultracold quantum device turns electricity into something far stranger that could unlock sound-based lasers

Researchers at McGill University have developed a novel device that generates sound-like particles known as phonons at extremely cold temperatures. The technology could be used to create phonon lasers, with possible applications in communications and medical diagnostics.

“Modern communication is largely based on light, including electromagnetic waves and electrical currents. In a medium such as oceans, sound can travel, whereas light and electrical currents cannot,” said Michael Hilke. “In the human body, sound waves can also be a useful tool.”

Hilke is Associate Professor of Physics and co-author of the study published in Physical Review Letters. The device was built and analyzed at McGill and the National Research Council of Canada. The material was synthesized at Princeton University.

Breaking connections helps ideas spread farther, says physics-based study

Sticking with the same people might feel safe and comfortable. But a new Northwestern University study suggests it can actually trap new ideas and behaviors inside tight echo chambers. By contrast, the research, published in Communications Physics, shows that when interactions shift away from familiar contacts—and toward new ones—activity can spread more widely.

To explore how activities spread across networks, physicists developed a new theoretical framework that includes simple “learning” rules. While traditional network models assume relationships do not change, the new model shows what happens when connections change with experience. As interactions strengthen or weaken relationships, they gradually reshape the entire network.

The findings apply not only to ideas moving through social networks but to a wide range of systems where activity spreads, including infections passing among people, signals traveling through the brain and behaviors proliferating through groups of animals. Ultimately, the study suggests that whether something spreads or stalls may hinge on a simple choice: revisit the same connections or explore new ones.

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