A research team from ShanghaiTech University has created a new method for designing two-dimensional patterned hollow structures (2D-PHS) with improved mechanical properties for aerospace and automotive applications. By using Conditional Generative Adversarial Networks (cGAN) and Deep Q-Networks (DQN), they optimized the design of 2D-PHS much faster than traditional finite element analysis (FEA). Their optimization enhanced stress uniformity by 4.3% and reduced maximum stress concentrations by 23.1%. These improvements were validated through simulations and tensile tests on 3D-printed samples, which showed tensile strength increased from 5.9 to 6.6 MPa. This study highlights the effectiveness of AI in efficient material design.

Precise tumor diagnosis and treatment require the support of abundant molecular information. However, conventional molecular diagnostic technologies gradually fail to satisfy the demands of clinical therapy due to limited detection performance. Benefiting from highly specific target sequence recognition and efficient cis/trans cleavage activity, CRISPR/Cas system has been widely employed to construct novel molecular diagnostic strategies, hailed as the “next-generation molecular diagnostic technology”. This review focuses on recent advances in CRISPR molecular diagnostic systems for the detection of tumor variant gene, protein, and liquid biopsy biomarker, and outlines strategies for CRISPR in situ molecular detection. In addition, we explore general principles and development trends in the construction of CRISPR molecular diagnostic system and emphasize the revolutionary impact that it has brought to the field of molecular diagnostics.

Just the word “quantum” can make even seasoned science teachers break into a sweat. But a national pilot program led by The University of Texas at Arlington is helping take the mystery out of the subject for students and educators alike. This week, 50 high school students and science teachers gathered at Arlington Martin High School to dive into the topic through Quantum for All, a program launched by Karen Jo Matsler, a professor of practice and master teacher in UT Arlington’s UTeach program.