Breathing Life into Polycations

The lack of efficient delivery systems is still limiting the full therapeutic potential of siRNA. For the purpose of nucleic acid transfer, among other synthetic carrier systems, polycations have been applied. Favorable characteristics of suitable polymers include nucleic acid binding, compaction, protection, and biocompatibility. However the lack of nucleic acid transfer activity in transfection-based screening often abandons promising candidates. Here we present that functionalization may turn polycations with poor delivery activity into efficient carriers:  for example, polylysine, on its own lacking nucleic acid transfer activity, displayed high efficiency in siRNA delivery after modification with polyethylene glycol and a pH-responsive endosomolytic peptide. Hence these findings have implication for the selection process of polymeric carriers for siRNA

Stateful Testing: Finding More Errors in Code and Contracts

Automated random testing has shown to be an effective approach to finding faults but still faces a major unsolved issue: how to generate test inputs diverse enough to find many faults and find them quickly. Stateful testing, the automated testing technique introduced in this article, generates new test cases that improve an existing test suite. The generated test cases are designed to violate the dynamically inferred contracts (invariants) characterizing the existing test suite. As a consequence, they are in a good position to detect new errors, and also to improve the accuracy of the inferred contracts by discovering those that are unsound. Experiments on 13 data structure classes totalling over 28,000 lines of code demonstrate the effectiveness of stateful testing in improving over the results of long sessions of random testing: stateful testing found 68.4% new errors and improved the accuracy of automatically inferred contracts to over 99%, with just a 7% time overhead.Comment: 11 pages, 3 figure

A human genome-wide loss-of-function screen identifies effective chikungunya antiviral drugs

Chikungunya virus (CHIKV) is a globally spreading alphavirus against which there is no commercially available vaccine or therapy. Here we use a genome-wide siRNA screen to identify 156 proviral and 41 antiviral host factors affecting CHIKV replication. We analyse the cellular pathways in which human proviral genes are involved and identify druggable targets. Twenty-one small-molecule inhibitors, some of which are FDA approved, targeting six proviral factors or pathways, have high antiviral activity in vitro, with low toxicity. Three identified inhibitors have prophylactic antiviral effects in mouse models of chikungunya infection. Two of them, the calmodulin inhibitor pimozide and the fatty acid synthesis inhibitor TOFA, have a therapeutic effect in vivo when combined. These results demonstrate the value of loss-of-function screening and pathway analysis for the rational identification of small molecules with therapeutic potential and pave the way for the development of new, host-directed, antiviral agents

Ventricular tachycardia (VT) storm after cryoballoon-based pulmonary vein isolation

Objective: Unusual clinical course. Background: Following catheter ablation of atrial fibrillation, increased incidence of ventricular arrhythmia has been observed. We report a case of sustained ventricular arrhythmia in a patient who underwent cryoballoon-based pulmonary vein isolation for symptomatic persistent atrial fibrillation. Case Report: A 57-year-old patient with dilated cardiomyopathy underwent CB-based pulmonary vein isolation for symptomatic persistent AF. On the day following an uneventful procedure, the patient for the first time experienced a sustained ventricular tachycardia that exacerbated into VT storm. Each arrhythmia was terminated by the ICD that had been implanted for primary prevention. Antiarrhythmic treatment with amiodarone was initiated immediately. The patient remained free from sustained ventricular arrhythmia during follow-up. Conclusions: After pulmonary vein isolation, physicians should be vigilant for ventricular arrhythmia. The influence of atrial autonomic innervation on ventricular electrophysiology is largely unknown

Constraining functional hypotheses: controls on the morphology of the concavo-convex brachiopod Rafinesquina

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72447/1/j.1502-3931.1998.tb00519.x.pd

Neural Processes of Psychological Stress and Relaxation Predict the Future Evolution of Quality of Life in Multiple Sclerosis

Health-related quality of life (HRQoL) is an essential complementary parameter in the assessment of disease burden and treatment outcome in multiple sclerosis (MS) and can be affected by neuropsychiatric symptoms, which in turn are sensitive to psychological stress. However, until now, the impact of neurobiological stress and relaxation on HRQoL in MS has not been investigated. We thus evaluated whether the activity of neural networks triggered by mild psychological stress (elicited in an fMRI task comprising mental arithmetic with feedback) or by stress termination (i.e., relaxation) at baseline (T0) predicts HRQoL variations occurring between T0 and a follow-up visit (T1) in 28 patients using a robust regression and permutation testing. The median delay between T0 and T1 was 902 (range: 363-1,169) days. We assessed HRQoL based on the Hamburg Quality of Life Questionnaire in MS (HAQUAMS) and accounted for the impact of established HRQoL predictors and the cognitive performance of the participants. Relaxation-triggered activity of a widespread neural network predicted future variations in overall HRQoL (t = 3.68, p(family-wise error [FWE])-corrected = 0.008). Complementary analyses showed that relaxation-triggered activity of the same network at baseline was associated with variations in the HAQUAMS mood subscale on an alpha(FWE) = 0.1 level (t = 3.37, p(FWE) = 0.087). Finally, stress-induced activity of a prefronto-limbic network predicted future variations in the HAQUAMS lower limb mobility subscale (t = -3.62, p(FWE) = 0.020). Functional neural network measures of psychological stress and relaxation contain prognostic information for future HRQoL evolution in MS independent of clinical predictors

The ribosome assembly factor Nep1 responsible for Bowen–Conradi syndrome is a pseudouridine-N1-specific methyltransferase

Nep1 (Emg1) is a highly conserved nucleolar protein with an essential function in ribosome biogenesis. A mutation in the human Nep1 homolog causes Bowen–Conradi syndrome—a severe developmental disorder. Structures of Nep1 revealed a dimer with a fold similar to the SPOUT-class of RNA-methyltransferases suggesting that Nep1 acts as a methyltransferase in ribosome biogenesis. The target for this putative methyltransferase activity has not been identified yet. We characterized the RNA-binding specificity of Methanocaldococcus jannaschii Nep1 by fluorescence- and NMR-spectroscopy as well as by yeast three-hybrid screening. Nep1 binds with high affinity to short RNA oligonucleotides corresponding to nt 910–921 of M. jannaschii 16S rRNA through a highly conserved basic surface cleft along the dimer interface. Nep1 only methylates RNAs containing a pseudouridine at a position corresponding to a previously identified hypermodified N1-methyl-N3-(3-amino-3-carboxypropyl) pseudouridine (m1acp3-Ψ) in eukaryotic 18S rRNAs. Analysis of the methylated nucleoside by MALDI-mass spectrometry, HPLC and NMR shows that the methyl group is transferred to the N1 of the pseudouridine. Thus, Nep1 is the first identified example of an N1-specific pseudouridine methyltransferase. This enzymatic activity is also conserved in human Nep1 suggesting that Nep1 is the methyltransferase in the biosynthesis of m1acp3-Ψ in eukaryotic 18S rRNAs

Magnetotunneling spectroscopy of mesoscopic correlations in two-dimensional electron systems

An approach to experimentally exploring electronic correlation functions in mesoscopic regimes is proposed. The idea is to monitor the mesoscopic fluctuations of a tunneling current flowing between the two layers of a semiconductor double-quantum-well structure. From the dependence of these fluctuations on external parameters, such as in-plane or perpendicular magnetic fields, external bias voltages, etc., the temporal and spatial dependence of various prominent correlation functions of mesoscopic physics can be determined. Due to the absence of spatially localized external probes, the method provides a way to explore the interplay of interaction and localization effects in two-dimensional systems within a relatively unperturbed environment. We describe the theoretical background of the approach and quantitatively discuss the behavior of the current fluctuations in diffusive and ergodic regimes. The influence of both various interaction mechanisms and localization effects on the current is discussed. Finally a proposal is made on how, at least in principle, the method may be used to experimentally determine the relevant critical exponents of localization-delocalization transitions.Comment: 15 pages, 3 figures include

TotalSegmentator: robust segmentation of 104 anatomical structures in CT images

We present a deep learning segmentation model that can automatically and robustly segment all major anatomical structures in body CT images. In this retrospective study, 1204 CT examinations (from the years 2012, 2016, and 2020) were used to segment 104 anatomical structures (27 organs, 59 bones, 10 muscles, 8 vessels) relevant for use cases such as organ volumetry, disease characterization, and surgical or radiotherapy planning. The CT images were randomly sampled from routine clinical studies and thus represent a real-world dataset (different ages, pathologies, scanners, body parts, sequences, and sites). The authors trained an nnU-Net segmentation algorithm on this dataset and calculated Dice similarity coefficients (Dice) to evaluate the model's performance. The trained algorithm was applied to a second dataset of 4004 whole-body CT examinations to investigate age dependent volume and attenuation changes. The proposed model showed a high Dice score (0.943) on the test set, which included a wide range of clinical data with major pathologies. The model significantly outperformed another publicly available segmentation model on a separate dataset (Dice score, 0.932 versus 0.871, respectively). The aging study demonstrated significant correlations between age and volume and mean attenuation for a variety of organ groups (e.g., age and aortic volume; age and mean attenuation of the autochthonous dorsal musculature). The developed model enables robust and accurate segmentation of 104 anatomical structures. The annotated dataset (https://doi.org/10.5281/zenodo.6802613) and toolkit (https://www.github.com/wasserth/TotalSegmentator) are publicly available.Comment: Accepted at Radiology: Artificial Intelligenc