Crystal Composition Transformer: Self-Learning Neural Language Model for Generative and Tinkering Design of Materials.

Self-supervised neural language models have recently achieved unprecedented success from natural language processing to learning the languages of biological sequences and organic molecules. These models have demonstrated superior performance in the generation, structure classification, and functional predictions for proteins and molecules with learned representations. However, most of the masking-based pre-trained language models are not designed for generative design, and their black-box nature makes it difficult to interpret their design logic.

Are the European reference networks for rare diseases ready to embrace machine learning? A mixed-methods study.

Background: The delay in diagnosis for rare disease (RD) patients is often longer than for patients with common diseases. Machine learning (ML) technologies have the potential to speed up and increase the precision of diagnosis in this population group. We aim to explore the expectations and experiences of the members of the European Reference Networks (ERNs) for RDs with those technologies and their potential for application.

Glucagon- and insulin-immunopositive endocrine cells in porcine extrahepatic bile ducts and gallbladder.

Introduction: Pancreatic β-cells and α-cells have been found in the murine extrahepatic biliary ducts but not in the gallbladder. However, there has been no information reported in the specialized literature about the presence of glucagon- and insulin-expressing endocrine cells in porcine bile ducts and gallbladder.

Aim: We aimed to perform an immunohistochemical study to identify glucagon- and insulin-positive cells and their distribution in the porcine extrahepatic biliary ducts and gallbladder.

Doxorubicin Changes the Spatial Organization of the Genome around Active Promoters.

In this study, we delve into the impact of genotoxic anticancer drug treatment on the chromatin structure of human cells, with a particular focus on the effects of doxorubicin. Using Hi-C, ChIP-seq, and RNA-seq, we explore the changes in chromatin architecture brought about by doxorubicin and ICRF193. Our results indicate that physiologically relevant doses of doxorubicin lead to a local reduction in Hi-C interactions in certain genomic regions that contain active promoters, with changes in chromatin architecture occurring independently of Top2 inhibition, cell cycle arrest, and differential gene expression.

Stability study of extemporaneously compounded nitrofurantoin oral suspensions for pediatric patients.

To evaluate the stability of nitrofurantoin suspended in different extemporaneously compounded vehicles after storage at 4°C and at 25°C. To formulate an effective, readily available vehicle that can guarantee extended stability and precise dosing.