Researchers introduced malate biosynthetic capability into the yeast Candida glabrata to improve the oxidative stress tolerance. Due to the fact that malate biosynthesis activated the anti-oxidative defense system, the oxidative stress tolerance of C. glabrata exhibited a significant improvement. This strategy has application potential for the biosynthesis of pharmaceutical chemicals.

A major international collaboration between researchers in China and the U.S. has successfully synthesized a novel two-dimensional magnetic material (indium-based chromium telluride, CIT) using chemical vapor transport. A compound that exhibits robust ferromagnetism and magnetocaloric effect at room temperature with intriguing phase transition behavior and complex magnetic interaction. This discovery paves the way for novel applications in high-performance spintronics, magnetic refrigeration, and advanced electronic devices.

A research team uncovers a crucial molecular pathway by which sucrose, long known as a key energy source, also acts as a signaling molecule to regulate seed storage protein synthesis in maize.

Integrated carbon capture and utilization (ICCU) has become a promising technology to achieve carbon neutrality. However, conventional studies focused on the development of novel dual-functional materials while neglecting the impact of common impurities such as sulfur oxides (SOx) and nitrogen oxides (NOx), thereby limiting the practical industrial applicability of ICCU technology. A team of scientists has investigated the impact of SO₂ and NO₂ on the ICCU-dry reforming of methane (ICCU-DRM) process using a representative Ni-Ca dual-functional material. Their work is published in the journal Industrial Chemistry & Materials on 04 July 2025.

How to Improve the Overall Efficiency of Volume Additive Manufacturing?​

In IJEM, Dr. Huiyuan Wang and coworkers from Beihang University proposed sparse-view irradiation processing volume additive manufacturing (SVIP-VAM). Their work demonstrated that sparse-view irradiation can enhance single-projection efficiency, significantly reduce projection computation time, and achieve high-quality fabrication results through quantitative analysis. Such improvements will advance VAM technology, facilitating its broader application in rapid manufacturing fields, including tissue engineering, medical implants, and aerospace manufacturing et al.

Recent advances in glucose management are reshaping our understanding of cognitive decline and dementia prevention. Energy imbalance and glucose dysregulation are now recognized as central to Alzheimer’s disease (AD) risk. Brain-specific insulin signaling disruptions due to dysglycemia impair natural protective mechanisms. These findings are leading to updated diabetes care practices that prioritize cognitive outcomes, marking a significant shift in how comorbid AD is addressed in aging populations.

Despite being an excellent candidate for a photocathode, Cu₂ZnSnS₄ (CZTS) performance is limited by suboptimal bulk and interfacial charge carrier dynamics. In this work, we introduce a facile and versatile CZTS precursor seed layer engineering technique, which significantly enhances crystal growth and mitigates detrimental defects in the post-sulfurized CZTS light-absorbing films. This effective optimization of defects and charge carrier dynamics results in a highly efficient CZTS/CdS/TiO₂/Pt thin-film photocathode, achieving a record half-cell solar-to-hydrogen (HC-STH) conversion efficiency of 9.91%. Additionally, the photocathode exhibits a highest photocurrent density (J_ph) of 29.44 mA cm⁻² (at 0 V_RHE) and favorable onset potential (V_on) of 0.73 V_RHE. Furthermore, our CTZS photocathode demonstrates a remarkable J_ph of 16.54 mA cm⁻² and HC-STH efficiency of 2.56% in natural seawater, followed by an impressive unbiased STH efficiency of 2.20% in a CZTS-BiVO₄ tandem cell. The scalability of this approach is underscored by the successful fabrication of a 4 × 4 cm² module, highlighting its significant potential for practical, unbiased in situ solar seawater splitting applications.

This review summarizes recent advances in wind speed forecasting using artificial intelligence. It systematically analyzes multi-scale signal decomposition methods and intelligent model fusion strategies, highlighting their effectiveness in addressing the challenges of nonstationary and multiscale wind data. By identifying key methodological patterns and gaps, the review offers actionable insights for designing more accurate, efficient, and robust AI-based wind forecasting systems.