Preclinical evaluation of Ga-labeled folic acid conjugates for visualization of inflammatory foci.

Introduction: Folate receptors (FR) have been considered a convenient target for different radiopharmaceuticals in recent years. Multifarious Ga-labeled folate conjugates have been proposed as promising agents for the PET imaging of FR-overexpressing malignant neoplasms. In addition, radiolabeled folate-based conjugates can be effective for imaging non-tumor pathological foci characterized by a pronounced cluster of activated macrophages.

Improvement of End-of-Synthesis Radiochemical Purity of Lu-DOTA-PSMA-Ligands with Alternative Synthesis Approaches: Conversion Upswing and Side-Products Minimization.

Background: Radiochemical purity is a key criterion for the quality of radiopharmaceuticals used in clinical practice. The joint improvement of analytical methods capable of identifying related radiochemical impurities and determining the actual radiochemical purity, as well as the improvement of synthesis methods to minimize the formation of possible radiochemical impurities, is integral to the implementation of high-tech nuclear medicine procedures. PSMA-targeted radionuclide therapy with lutetium-177 has emerged as an effective treatment option for prostate cancer, and [Lu]Lu-PSMA-617 and [Lu]Lu-PSMA have achieved global recognition as viable radiopharmaceuticals.

Computational Research of the Efficiency of Using a Three-Layer Panel Made of Highly Porous Polystyrene Concrete.

This paper presents linking computational research of the multilayer structure of the cladding of a three-layer panel made of highly porous polystyrene concrete developed using a new technology in comparison with traditional ones. The calculation of the thermal efficiency of the exterior fence was carried out in three stages, where the thermal regime was calculated from the values of temperature fields in the ELCUT 6.6 system, and the humidity and air modes were determined by the analytical method in the Maple system.

Enhancing Automated Brain Tumor Detection Accuracy Using Artificial Intelligence Approaches for Healthcare Environments.

Medical imaging and deep learning models are essential to the early identification and diagnosis of brain cancers, facilitating timely intervention and improving patient outcomes. This research paper investigates the integration of YOLOv5, a state-of-the-art object detection framework, with non-local neural networks (NLNNs) to improve brain tumor detection's robustness and accuracy. This study begins by curating a comprehensive dataset comprising brain MRI scans from various sources.

Radiolysis-Associated Decrease in Radiochemical Purity of Lu-Radiopharmaceuticals and Comparison of the Effectiveness of Selected Quenchers against This Process.

The radiolytic degradation of vector molecules is a major factor affecting the shelf life of therapeutic radiopharmaceuticals. The development of time-stable dosage forms of radiopharmaceuticals is the key to their successful implementation in clinical practice. Using [Lu]Lu-PSMA-617 molecule as an example, the time dependence of the change in radiochemical purity (RCP, %) under radiolysis conditions was studied.