Nuclear receptors as targets in brain cancer therapy
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Dec-2025 19:11 ET (24-Dec-2025 00:11 GMT/UTC)
Brain cancer remains one of the deadliest cancers, with limited treatment options and poor outcomes. In this review, researchers explore how nuclear receptors (NRs) influence brain tumor growth, invasion, and treatment resistance. The article details specific roles of different NRs and discusses how targeting them with drugs could improve therapy. These findings offer a promising direction for developing more precise, effective treatments against this highly aggressive and treatment-resistant cancer type.
Researchers from The Hong Kong University of Science and Technology and the Southern University of Science and Technology have developed a novel deep learning neural network, Electrode Net. By introducing signed distance fields and three-dimensional convolutional neural networks, this method can significantly accelerate electrode design while maintaining high accuracy. It is widely applicable to fuel cells, water electrolyzers, flow batteries, etc.
If AI’s intrinsic risks are real, governmental regulation and ethical frameworks are unlikely to contain them. Drawing on social theory, it highlights myths about the state’s capacity, global enforcement challenges, rapid technological decentralization, and the ambiguity of moral norms. The author presents a skeptical view that “meaning well” does not ensure effective outcomes, cautioning against overreliance on governments and ethics to mitigate advanced AI risks.