Development and Validation of a Deep Learning Algorithm for Gleason Grading of Prostate Cancer From Biopsy Specimens.

Importance: For prostate cancer, Gleason grading of the biopsy specimen plays a pivotal role in determining case management. However, Gleason grading is associated with substantial interobserver variability, resulting in a need for decision support tools to improve the reproducibility of Gleason grading in routine clinical practice.

Objective: To evaluate the ability of a deep learning system (DLS) to grade diagnostic prostate biopsy specimens.

Identifying Ortholog Selective Fragment Molecules for Bacterial Glutaredoxins by NMR and Affinity Enhancement by Modification with an Acrylamide Warhead.

Illustrated here is the development of a new class of antibiotic lead molecules targeted at glutaredoxin (PaGRX). This lead was produced to (a) circumvent efflux-mediated resistance mechanisms via covalent inhibition while (b) taking advantage of species selectivity to target a fundamental metabolic pathway. This work involved four components: a novel workflow for generating protein specific fragment hits via independent nuclear magnetic resonance (NMR) measurements, NMR-based modeling of the target protein structure, NMR guided docking of hits, and synthetic modification of the fragment hit with a vinyl cysteine trap moiety, i.

Variation of clinical target volume definition in three-dimensional conformal radiation therapy for prostate cancer.

Purpose: Currently, three-dimensional conformal radiation therapy (3D-CRT) planning relies on the interpretation of computed tomography (CT) axial images for defining the clinical target volume (CTV). This study investigates the variation among multiple observers to define the CTV used in 3D-CRT for prostate cancer.

Methods And Materials: Seven observers independently delineated the CTVs (prostate +/- seminal vesicles [SV]) from the CT simulation data of 10 prostate cancer patients undergoing 3D-CRT.

Experimental verification of a three-dimensional dose calculation algorithm using a specially designed heterogeneous phantom.

A solid heterogeneous phantom made up of 25- and 50-mm cubes of materials with different electron densities was used to verify the accuracy of a three-dimensional (3-D) dose calculation algorithm. This algorithm uses 3-D information obtained from contiguous CT (computed tomography) slices, spaced 5 mm apart. Primary and scatter doses at a point are calculated by using information from ray-tracing CT voxels.