Unsupervised meta-clustering identifies risk clusters in acute myeloid leukemia based on clinical and genetic profiles.

Background: Increasingly large and complex biomedical data sets challenge conventional hypothesis-driven analytical approaches, however, data-driven unsupervised learning can detect inherent patterns in such data sets.

Methods: While unsupervised analysis in the medical literature commonly only utilizes a single clustering algorithm for a given data set, we developed a large-scale model with 605 different combinations of target dimensionalities as well as transformation and clustering algorithms and subsequent meta-clustering of individual results. With this model, we investigated a large cohort of 1383 patients from 59 centers in Germany with newly diagnosed acute myeloid leukemia for whom 212 clinical, laboratory, cytogenetic and molecular genetic parameters were available.

Synthesis, biological evaluation, and molecular docking studies of aldotetronic acid-based LpxC inhibitors.

In order to develop novel inhibitors of the bacterial deacetylase LpxC bearing a substituent to target the UDP binding site of the enzyme, a series of aldotetronic acid-based hydroxamic acids was accessed in chiral pool syntheses starting from 4,6-O-benzylidene-d-glucose and l-arabinitol. The synthesized hydroxamic acids were tested for LpxC inhibitory activity in vitro, revealing benzyl ether 17a ((2S,3S)-4-(benzyloxy)-N,3-dihydroxy-2-[(4-{[4-(morpholinomethyl)phenyl]ethynyl}benzyl)oxy]butanamide) as the most potent LpxC inhibitor. This compound was additionally tested for antibacterial activity against a panel of clinically relevant Gram-negative bacteria, bacterial uptake, and susceptibility to efflux pumps.

Prediction of complete remission and survival in acute myeloid leukemia using supervised machine learning.

Achievement of complete remission signifies a crucial milestone in the therapy of acute myeloid leukemia (AML) while refractory disease is associated with dismal outcomes. Hence, accurately identifying patients at risk is essential to tailor treatment concepts individually to disease biology. We used nine machine learning (ML) models to predict complete remission and 2-year overall survival in a large multicenter cohort of 1,383 AML patients who received intensive induction therapy.

Antibacterial activity of xylose-derived LpxC inhibitors - Synthesis, biological evaluation and molecular docking studies.

LpxC inhibitors represent a promising class of novel antibiotics selectively combating Gram-negative bacteria. In chiral pool syntheses starting from D- and L-xylose, a series of four 2r,3c,4t-configured C-furanosidic LpxC inhibitors was obtained. The synthesized hydroxamic acids were tested for antibacterial and LpxC inhibitory activity, the acquired biological data were compared with those of previously synthesized C-furanosides, and molecular docking studies were performed to rationalize the observed structure-activity relationships.

Detection of a Novel gyrB Mutation Associated With Fluoroquinolone-Nonsusceptible Salmonella enterica serovar Typhimurium Isolated From a Bloodstream Infection in Ghana.

A multidrug-resistant Salmonella enterica serovar Typhimurium with reduced susceptibility to ciprofloxacin was isolated from the blood of a hospitalized child in Ghana. DNA sequencing identified a novel gyrB mutation at codon 466 (Glu466Asp). An increase in fluoroquinolone susceptibility after the introduction of a wild-type gyrB(+) allele demonstrated that the gyrB466 mutation had a direct effect on fluoroquinolone susceptibility.