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Comparison between molecular and histological IDH-wild-type glioblastoma and extensive subgroup analysis of IDH-wild-type astrocytic tumors without genomic glioblastoma-defining alterations

This study compares clinical characteristics and survival between molecular (MolGBM) and histological IDH-wild-type (IDH-WT) glioblastoma (HistGBM), and further characterizes histological lower-grade IDH-WT astrocytic tumors without genomic GBM-defining alterations.

Adult patients with histologically lower-grade IDH–WT astrocytoma (WHO grade 2–3) and available tumor tissue were included. Tumors were classified according to the 2021 WHO Classification of CNS tumors. Biopsy-only cases were excluded. IDH1 and TERT promoter (TERTp) mutations were analyzed via Sanger and whole-exome sequencing (WES). TERTp-WT tumors underwent WES and subsequent DNA methylation profiling. Clinical, molecular, and outcome data were collected.

The cohort comprised 47 surgically resected histologically lower-grade IDH-WT astrocytic tumors. Thirty-nine fulfilled WHO 2021 criteria for MolGBM, mainly based on TERTp mutation (n = 36), while eight lacked GBM-defining molecular alterations. Compared with HistGBM (n = 54), MolGBM more frequently presented with seizures and showed a lower Ki-67 index. Median overall survival (OS) was 19.8 months in MolGBM and 14.6 months in HistGBM, without a significant difference in univariable analysis (p = 0.11). Patients aged ≥ 60 years showed longer overall survival in the MolGBM group (17.9 vs. 12.3 months; p = 0.0079). In multivariable Cox regression adjusted for age, extent of resection, and completion of the Stupp regimen, MolGBM was independently associated with more favorable OS (HR 0.40, 95% CI 0.24–0.67, p = 0.0005). The eight tumors lacking GBM-defining alterations showed longer survival and marked diagnostic heterogeneity.

An AI model that thinks like we do offers new ways to peer inside the black box

When a standard large language model (LLM) is confronted with a problem, it tries to solve it by matching it to similar information it has seen before, and then give an answer based on those past patterns. But how it decides which information to use and what value it gives to different pieces of information can be somewhat inscrutable from the outside. An EPFL team has created a new large language model that is structured similarly to a human brain, allowing users more control and moving away from “black box” AI.

The LLM MiCRo (Mixture of Cognitive Reasoners) is architecturally divided into four specialized areas that act like different parts of the human brain, allowing users to have more control over how it approaches a question and to better understand how it comes to its answers. The model, which was presented at the International Conference on Learning Representations (ICLR 2026), comes from the NLP Lab, part of the School of Computer and Communication Sciences (IC), and the NeuroAI Lab, part of IC and the School of Life Sciences at EPFL. The paper is posted to the arXiv preprint server.

How a brain messenger protein drives progression of Alzheimer’s disease

Alzheimer’s disease is driven by a buildup of a toxic protein called Tau that kills neurons. As toxic Tau spreads to new regions of the brain, symptoms worsen and ultimately become fatal.

Now, researchers have discovered that, in mice, a brain protein called Arc helps spread Tau from sick brain cells to healthy ones.

If therapies could be designed to target the spread, they could be a powerful tool to stop Alzheimer’s disease from getting worse.

Blood vessel cells keep fixed signaling roles for weeks, reshaping view of capillary communication

The cells lining skin capillaries are constantly sending each other messages—tiny pulses of calcium that help regulate blood flow, sense physical forces and keep vessel walls intact. Scientists have known about this signaling for decades. What they didn’t know, until now, is that it follows a remarkably organized pattern, one that persists across days and weeks, governed by a network of cells that have, in a sense, assigned themselves permanent roles.

A new study from Yale School of Medicine (YSM) and University of California, Los Angeles (UCLA), published in Proceedings of the National Academy of Sciences, reveals not only that this network exists, but also what happens when it breaks down—and how it might be restored.

The study was done in the lab of Valentina Greco, Ph.D., Carolyn Walch Slayman Professor of Genetics at YSM and a Howard Hughes Medical Institute investigator, in close collaboration with the labs of Julia Mack, Ph.D., and Chen Yuan Kam, Ph.D., both at UCLA.

Lockheed Martin unveils hypersonic glide body built for rapid mass production

Lockheed Martin has unveiled a next-generation hypersonic glide body designed to provide a more affordable and rapidly producible long-range strike capability.

The new system, called NXGB, is intended to combine advanced speed, survivability, and scalability to meet evolving national security requirements while supporting faster production and deployment.

According to the company, the hypersonic glide body is aimed at expanding strike options for defense forces by delivering high-performance capabilities in a cost-effective and adaptable platform.

Scientists discover how a single cell builds a brain with 170 billion cells

How does a single cell build a brain with billions of precisely organized neurons? Researchers suggest that brain cells use their lineage—their cellular family tree—as a kind of positional map. Cells that come from the same ancestor stay near one another, helping the brain organize itself without relying solely on chemical signals.

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