Masked Image Modeling Meets Self-Distillation: A Transformer-Based Prostate Gland Segmentation Framework for Pathology Slides.

Detailed evaluation of prostate cancer glands is an essential yet labor-intensive step in grading prostate cancer. Gland segmentation can serve as a valuable preliminary step for machine-learning-based downstream tasks, such as Gleason grading, patient classification, cancer biomarker building, and survival analysis. Despite its importance, there is currently a lack of a reliable gland segmentation model for prostate cancer.

Multidisciplinary care for children with cleft lip and palate and their families: Family-Centered Care.

Objective: To understand the multidisciplinary care provided to children with cleft lip and palate and their families.

Method: Descriptive, exploratory and qualitative study, based on the theoretical-philosophical framework of Family-Centered Care, conducted with professionals from the multidisciplinary team of an association supporting individuals with cleft lip and palate. The data were processed using the Iramuteq® software and systematized using Similarity Analysis.

Palbociclib and letrozole for hormone receptor-positive HER2-negative breast cancer with residual disease after neoadjuvant chemotherapy.

With the incorporation of cyclin-dependent kinase inhibitors in early breast cancer (BC), a better identification of biomarkers is needed. The PROMETEO II trial aimed to evaluate the antitumor activity of palbociclib plus letrozole and to identify response biomarkers in patients with operable HR+/HER2- BC and residual disease after neoadjuvant chemotherapy (NAC). The primary endpoint was the rate of complete cell cycle arrest (CCCA), centrally determined by Ki67 ≤ 2.