Platinum-DNA Origami Hybrid Structures in Concentrated Hydrogen Peroxide.

The DNA origami technique allows fast and large-scale production of DNA nanostructures that stand out with an accurate addressability of their anchor points. This enables the precise organization of guest molecules on the surfaces and results in diverse functionalities. However, the compatibility of DNA origami structures with catalytically active matter, a promising pathway to realize autonomous DNA machines, has so far been tested only in the context of bio-enzymatic activity, but not in chemically harsh reaction conditions. The latter are often required for catalytic processes involving high-energy fuels. Here, we provide proof-of-concept data showing that DNA origami structures are stable in 5 % hydrogen peroxide solutions over the course of at least three days. We report a protocol to couple these to platinum nanoparticles and show catalytic activity of the hybrid structures. We suggest that the presented hybrid structures are suitable to realize catalytic nanomachines combined with precisely engineered DNA nanostructures.

Light- and magnetically actuated FePt microswimmers.

Externally controlled microswimmers offer prospects for transport in biological research and medical applications. This requires biocompatibility of the swimmers and the possibility to tailor their propulsion mechanisms to the respective low Reynolds number environment. Here, we incorporate low amounts of the biocompatible alloy of iron and platinum (FePt) in its [Formula: see text] phase in microstructures by a versatile one-step physical vapor deposition process. We show that the hard magnetic properties of [Formula: see text] FePt are beneficial for the propulsion of helical micropropellers with rotating magnetic fields. Finally, we find that the FePt coatings are catalytically active and also make for Janus microswimmers that can be light-actuated and magnetically guided.

SnoReport 2.0: new features and a refined Support Vector Machine to improve snoRNA identification.

BACKGROUND: snoReport uses RNA secondary structure prediction combined with machine learning as the basis to identify the two main classes of small nucleolar RNAs, the box H/ACA snoRNAs and the box C/D snoRNAs. Here, we present snoReport 2.0, which substantially improves and extends in the original method by: extracting new features for both box C/D and H/ACA box snoRNAs; developing a more sophisticated technique in the SVM training phase with recent data from vertebrate organisms and a careful choice of the SVM parameters C and γ; and using updated versions of tools and databases used for the construction of the original version of snoReport. To validate the new version and to demonstrate its improved performance, we tested snoReport 2.0 in different organisms. RESULTS: Results of the training and test phases of boxes H/ACA and C/D snoRNAs, in both versions of snoReport, are discussed. Validation on real data was performed to evaluate the predictions of snoReport 2.0. Our program was applied to a set of previously annotated sequences, some of them experimentally confirmed, of humans, nematodes, drosophilids, platypus, chickens and leishmania. We significantly improved the predictions for vertebrates, since the training phase used information of these organisms, but H/ACA box snoRNAs identification was improved for the other ones. CONCLUSION: We presented snoReport 2.0, to predict H/ACA box and C/D box snoRNAs, an efficient method to find true positives and avoid false positives in vertebrate organisms. H/ACA box snoRNA classifier showed an F-score of 93 % (an improvement of 10 % regarding the previous version), while C/D box snoRNA classifier, an F-Score of 94 % (improvement of 14 %). Besides, both classifiers exhibited performance measures above 90 %. These results show that snoReport 2.0 avoid false positives and false negatives, allowing to predict snoRNAs with high quality. In the validation phase, snoReport 2.0 predicted 67.43 % of vertebrate organisms for both classes. For Nematodes and Drosophilids, 69 % and 76.67 %, for H/ACA box snoRNAs were predicted, respectively, showing that snoReport 2.0 is good to identify snoRNAs in vertebrates and also H/ACA box snoRNAs in invertebrates organisms.

Adherence management for patients with cancer taking capecitabine: a prospective two-arm cohort study.

OBJECTIVE: To develop and evaluate a multiprofessional modular medication management to assure adherence to capecitabine. METHODS: The study was conducted as a prospective, multicentred observational cohort study. All participants received pharmaceutical care consisting of oral and written information. Daily adherence was defined as percentage of days with correctly administered capecitabine doses and assessed using medication event monitoring. According to their daily adherence during the first cycle, patients were identified as initially non-adherent (<90% adherence) or adherent (≥90% adherence). Initially non-adherent patients received additional adherence support. RESULTS: Seventy-three patients with various tumour entities were enrolled, 58 were initially adherent and 15 non-adherent. Median daily adherence of initially non-adherent patients increased from 85.7% to 97.6% during the observation period of six cycles. Throughout all cycles, median daily adherence of initially adherent patients was 100.0%. Daily adherence was not associated with sociodemographic and disease-related factors. No patient was non-persistent. CONCLUSIONS: An early adherence screening effectively distinguishes between patients adhering and non-adhering to capecitabine. The provision of specific adherence support is associated with enhanced adherence of initially non-adherent patients, whereas initially adherent patients remain adherent for at least six cycles without specific support. Our needs-based approach helps to use available resources for adherence management efficiently.