From rock to living systems: Lanthanides toxicity and biological interactions.

Since the discovery of lanthanides, the expanding range of applications and the growing demand for lanthanides in different aspects of life have escalated their dispersion in the environment, raising concerns about their impact on the living world. This review explores the interaction between lanthanides and different groups of living organisms (bacteria, algae, lichens, plants, invertebrates, and low vertebrates), reflecting the current state of scientific knowledge. We have aimed to provide a comprehensive overview of relevant studies, highlight existing gaps, and suggest potential areas for future research to enhance the understanding of this topic.

Cancer Screening: Present Recommendations, the Development of Multi-Cancer Early Development Tests, and the Prospect of Universal Cancer Screening.

Cancer continues to pose a considerable challenge to global health. In the search for innovative strategies to combat this complex enemy, the concept of universal cancer screening has emerged as a promising avenue for early detection and prevention. In contrast to targeted approaches that focus on specific populations or high-risk individuals, universal screening seeks to cast a wide net to detect incipient malignancies in different demographic groups.

Acoustic Fractional Propagation in Terms of Porous Xerogel and Fractal Parameters.

This article portrays solid xerogel-type materials, based on chitosan, TEGylated phenothiazine, and TEG (tri-ethylene glycol), dotted with a large number of pores, that are effectively represented in their constitutive structure. They were assumed to be fractal geometrical entities and adjudged as such. The acoustic fractional propagation equation in a fractal porous media was successfully applied and solved with the help of Bessel functions.

AI Evaluation of Imaging Factors in the Evolution of Stage-Treated Metastases Using Gamma Knife.

Background: The study investigated whether three deep-learning models, namely, the CNN_model (trained from scratch), the TL_model (transfer learning), and the FT_model (fine-tuning), could predict the early response of brain metastases (BM) to radiosurgery using a minimal pre-processing of the MRI images. The dataset consisted of 19 BM patients who underwent stereotactic-radiosurgery (SRS) within 3 months. The images used included axial fluid-attenuated inversion recovery (FLAIR) sequences and high-resolution contrast-enhanced T1-weighted (CE T1w) sequences from the tumor center.