High-temperature field-free superconducting diode effect in high-T cuprates.

The superconducting diode effect (SDE) is defined by the difference in the magnitude of critical currents applied in opposite directions. It has been observed in various superconducting systems and attracted high research interests. However, the operating temperature of the SDE is typically low and/or the sample structure is rather complex.

In Silico-Guided Discovery of Polysaccharide Derivatives as Adjuvants in Nanoparticle Vaccines for Cancer Immunotherapy.

Cancer vaccines utilizing nanoparticle (NP) structures that integrate antigens and adjuvants to enhance delivery and stimulate immune responses are emerging as a promising avenue in cancer immunotherapy. However, the development of cancer vaccines has been significantly hindered by the low immunogenicity of tumor antigens. To address this challenge, substantial efforts have been made in developing innovative adjuvants to elicit effective immune responses.

Shenghui decoction inhibits neuronal cell apoptosis to improve Alzheimer's disease through the PDE4B/cAMP/CREB signaling pathway.

Background: Shenghui Decoction (SHD) is a frequently utilized traditional Chinese medicine formula in clinical settings for addressing cognitive impairment in elderly individuals. Nevertheless, the precise mechanism by which SHD exerts its effects on the most prevalent form of dementia, Alzheimer's disease (AD), remains to be elucidated.

Methods: Temperature-induced transgenic C.

Assessment of groundwater chemistry to predict arsenic contamination from a canal commanded area: applications of different machine learning models.

Groundwater arsenic (As), contamination is a significant issue worldwide including China and Pakistan, particularly in canal command areas. In this study, 131 groundwater samples were collected, and three machine learning models [Random Forest (RF), Logistic Regression (LR), and Artificial Neural Network (ANN)] were employed to predict As concentration. Descriptive statistics helped to conclude that all of the samples were inside the permitted limit of WHO for pH, Ca, Mg, Turbidity, Cl, K, Na, SO, NO, F and beyond limit of WHO for EC, HCO, TDS, and As.

Artificial intelligence and food flavor: How AI models are shaping the future and revolutionary technologies for flavor food development.

The food flavor science, traditionally reliant on experimental methods, is now entering a promising era with the help of artificial intelligence (AI). By integrating existing technologies with AI, researchers can explore and develop new flavor substances in a digital environment, saving time and resources. More and more research will use AI and big data to enhance product flavor, improve product quality, meet consumer needs, and drive the industry toward a smarter and more sustainable future.