The prediction of [Formula see text] values is one part of the statistical assessment of the modeling of proteins and ligands (SAMPL) blind challenges. Here, we use a molecular graph representation method called Geometric Scattering for Graphs (GSG) to transform atomic attributes to molecular features. The atomic attributes used here are parameters from classical molecular force fields including partial charges and Lennard-Jones interaction parameters. The molecular features from GSG are used as inputs to neural networks that are trained using a "master" dataset comprised of over 41,000 unique [Formula see text] values. The specific molecular targets in the SAMPL7 [Formula see text] prediction challenge were unique in that they all contained a sulfonyl moeity. This motivated a set of ClassicalGSG submissions where predictors were trained on different subsets of the master dataset that are filtered according to chemical types and/or the presence of the sulfonyl moeity. We find that our ranked prediction obtained 5th place with an RMSE of 0.77 [Formula see text] units and an MAE of 0.62, while one of our non-ranked predictions achieved first place among all submissions with an RMSE of 0.55 and an MAE of 0.44. After the conclusion of the challenge we also examined the performance of open-source force field parameters that allow for an end-to-end [Formula see text] predictor model General AMBER Force Field (GAFF), Universal Force Field (UFF), Merck Molecular Force Field 94 (MMFF94) and Ghemical. We find that ClassicalGSG models trained with atomic attributes from MMFF94 can yield more accurate predictions compared to those trained with CGenFF atomic attributes.Assessment of target druggability guided by search and characterization of hot spots is a pivotal step in early stages of drug-discovery. The raw output of FTMap provides the data to perform this task, but it relies on manual intervention to properly combine different sets of consensus sites, therefore allowing identification of hot spots and evaluation of strength, shape and distance among them. Thus, the user's previous experience on the target and the software has a direct impact on how data generated by FTMap server can be explored. DRUGpy plugin was developed to overcome this limitation. By automatically assembling and scoring all possible combinations of consensus sites, DRUGpy plugin provides FTMap users a straight-forward method to identify and characterize hot spots in protein targets. DRUGpy is available in all operating systems that support PyMOL software. DRUGpy promptly identifies and characterizes pockets that are predicted by FTMap to bind druglike molecules with high-affinity (druggable sites) or low-affinity (borderline sites) and reveals how protein conformational flexibility impacts on the target's druggability. The use of DRUGpy on the analysis of trypanothione reductases (TR), a validated drug target against trypanosomatids, showcases the usefulness of the plugin, and led to the identification of a druggable pocket in the conserved dimer interface present in this class of proteins, opening new perspectives to the design of selective inhibitors. End-stage kidney disease (ESKD) incidence has been increasing over time, contributing significantly to morbidity and mortality. However, there is limited data examining the psychosocial factors affecting people with ESKD and how the social worker fits within the multidisciplinary CKD care. This integrative systematic review aims to summarise the existing evidence on psychosocial determinants of outcomes in ESKD and the role of the social workerin nephrology care. The literature search was conducted using PubMed and MEDLINE, targeting articles published from database inception until May 2021. This systematic review was performed in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The Joanna Briggs Institute tools were employed to assess the quality of included studies. Of the 397 citations, 13 studies applicable to 1465 patients met the inclusion criteria. The studies were of cross-sectional, experimental, and exploratory qualitative design in nat physical and psychological stressors that patients with ESRD face, and highlights the positive role social workers can play in improving the psychosocial stressors in this patient group, and the need for large-scale randomised trials to understand the role of social workers as part of a multidisciplinary nephrology care.Renal biopsy is currently the gold standard for diagnosing active renal vasculitis. In this pilot study, metabolomics analysis was used to investigate the differences in metabolic profiles between paired patients' serum and urine samples collected during both the active and the remission phase of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAV). Ten patients with AAV renal disease were included. Mean age was 61 years, with 6 patients each being male and Caucasian. Mean Birmingham Vasculitis Activity Score (BVAS) and mean glomerular filtration rate (GFR) were 17 and 28, respectively. We found that while the citric acid cycle intermediates citrate, iso-citrate and oxaloacetate had lower intensities in the active phase samples as compared to the remission phase samples. The intensities of other metabolites of carbohydrate metabolism, amino acid metabolism, and nucleotide synthesis were significantly higher in the active phase samples, indicating the upregulation of these pathways for the production of energy and other biomolecules such as proteins and nucleic acids during the active phase of AAV. This pilot study suggests that serum and urinary metabolomic profiling may be useful to monitor disease activity in renal AAV.We aimed to evaluate the effectiveness and safety of single-course initial regimens in patients with low-risk gestational trophoblastic neoplasia (GTN). In this trial (NCT01823315), 276 patients were analyzed. Patients were allocated to three initiated regimens single-course methotrexate (MTX), single-course MTX + dactinomycin (ACTD), and multi-course MTX (control arm). The primary endpoint was the complete remission (CR) rate by initial drug(s). The primary CR rate was 64.4% with multi-course MTX in the control arm. For the single-course MTX arm, the CR rate was 35.8% by one course; it increased to 59.3% after subsequent multi-course MTX, with non-inferiority to the control (difference -5.1%,95% confidence interval (CI) -19.4% to 9.2%, P = 0.014). After further treatment with multi-course ACTD, the CR rate (93.3%) was similar to that of the control (95.2%, P = 0.577). Epacadostat cost For the single-course MTX + ACTD arm, the CR rate was 46.7% by one course, which increased to 89.1% after subsequent multi-course, with non-inferiority (difference 24.