A new AI-powered test, IICM+, may enhance recurrence risk prediction in HR+, HER2-negative breast cancer. Developed and independently validated in over 4,400 participants from the landmark TAILORx trial, IICM+ outperformed a widely used test. However, further validation is needed. By analyzing TAILORx tumor specimens and more than a decade of patient outcomes, this research extends the impact of this groundbreaking trial.

Researchers at San Diego State University, Arizona State University and the University of Utah are developing a new cybersecurity infrastructure for secure private data sharing. The work is part of a new $5 million grant from the National Science Foundation. 

Over the next five years, the team will deploy and support a novel cyberinfrastructure called Prototype Architecture for Research Advances using Privacy Enhancing Technologies (PARAPET), that could be used in a range of fields that require data analysis, like healthcare, internet security, science, finance and the social sciences, to protect sensitive information such as medical records, financial information and census statistics.

Using privacy-enhancing technologies, PARAPET is designed to be a more secure way to share and collaborate on sensitive data, safeguard data at rest and during computation, and train AI models without exposing private data. 

The rapid advancement of solid-state lighting technology has made white LEDs the preferred choice for energy-efficient illumination. Nevertheless, commercial white LEDs based on blue chips and yellow phosphors suffer from inadequate red components and poor spectral continuity, leading to low color rendering index (CRI). Lead-free Cs-Cu-I perovskites, with their unique self-trapped exciton (STE) emission, offer a promising single-component white-light platform, yet their low photoluminescence quantum yield (PLQY) remains a major obstacle. Therefore, enhancing both the PLQY and spectral coverage of Cs-Cu-I is critically important.

A team led by Aiwei Tang professor from Beijing Jiaotong University recently reported a Zn²⁺ doping strategy for Cs-Cu-I perovskite nanocrystals (NCs) to achieve high-CRI white LEDs, advancing eco-friendly solid-state lighting.

The research group led by Mingyu Li at Harbin Institute of Technology (Shenzhen) developed a bayberry-like AgMP/AgNP micro–nano composite sintered silver paste (AgPs-BM), in which bayberry-like porous silver microparticles serve as the primary structural framework and silver nanoparticles act as the filling and interconnecting phase. The bayberry-like AgMPs feature a low surface organic content, a relatively high specific surface area, and abundant surface pores. The AgNPs not only fill the large voids formed by the packing of AgMPs but are also distributed between adjacent AgMPs and at particle–interface regions, thereby increasing the number of effective contact sites and establishing interparticle connections. In addition, the AgNPs can fill the surface pores of the AgMPs, shifting the sintering behavior of the AgMPs from predominantly individual-particle self-sintering toward the growth of an interparticle interconnected network.