State of the art and future perspectives of new radionuclides in Nuclear Medicine.

This continuing education analyzes recent advances in Nuclear Medicine focused on the development of new radiopharmaceuticals that improve both the diagnosis and treatment of complex diseases. The focus is on teragnosis, which combines diagnosis and treatment by means of pairs of radiopharmaceuticals directed to the same molecular target, which allows the personalization of treatments. This first part specifically reviews the teragnostic pairs copper-64/copper-67, lead-212/lead-203 and scandium-44/scandium-47, highlighting their physical characteristics, methods of production and potential clinical applications.

Artificial intelligence-driven analysis of embryo morphokinetics in singleton, twin, and triplet pregnancies.

In recent years, the transfer of more than one embryo has become less frequent to diminish multiple pregnancies. Even so, there is still a risk of one embryo splitting into two or even three. This report presents the case of a triamniotic monochorionic gestation in a 35-year-old woman, obtained after the transfer of a single day 5 embryo that had been previously hatched with a laser and subsequently transferred in a fresh IVF cycle.

Molecular Detection of Lymph Node Metastases with One-Step Nucleic Acid Amplification (OSNA) Pooling in Prostate Cancer: The POPCORN Study.

Pelvic lymph node dissection (PLND) is the most accurate procedure for lymph node (LN) staging in prostate cancer (PCa) patients. LN sectioning and hematoxylin and eosin (H&E) staining of at least one slice remains the gold standard for LN evaluation, potentially leading to misdetection of small metastatic focus. Entire LN analysis is possible with One-Step Nucleic Acid Amplification (OSNA) by detecting cytokeratin 19 (CK19) mRNA as a surrogate for LN invasion.

What is the influence of psychosocial factors on artificial intelligence appropriation in college students?

Background: In recent years, the adoption of artificial intelligence (AI) has become increasingly relevant in various sectors, including higher education. This study investigates the psychosocial factors influencing AI adoption among Peruvian university students and uses an extended UTAUT2 model to examine various constructs that may impact AI acceptance and use.

Method: This study employed a quantitative approach with a survey-based design.