Recognition of RNA by the S9.6 antibody creates pervasive artifacts when imaging RNA:DNA hybrids

The S9.6 antibody is broadly used to detect RNA:DNA hybrids but has significant affinity for double-stranded RNA. The impact of this off-target RNA binding activity has not been thoroughly investigated, especially in the context of immunofluorescence microscopy. We report that S9.6 immunofluorescence signal observed in fixed human cells arises predominantly from ribosomal RNA, not RNA:DNA hybrids. S9.6 staining was unchanged by pretreatment with the RNA:DNA hybrid–specific nuclease RNase H1, despite verification in situ that S9.6 recognized RNA:DNA hybrids and that RNase H1 was active. S9.6 staining was, however, significantly sensitive to RNase T1, which specifically degrades RNA. Additional imaging and biochemical data indicate that the prominent cytoplasmic and nucleolar S9.6 signal primarily derives from ribosomal RNA. Importantly, genome-wide maps obtained by DNA sequencing after S9.6-mediated DNA:RNA immunoprecipitation (DRIP) are RNase H1 sensitive and RNase T1 insensitive. Altogether, these data demonstrate that imaging using S9.6 is subject to pervasive artifacts without pretreatments and controls that mitigate its promiscuous recognition of cellular RNAs.     

Exercise training in childhood-onset systemic lupus erythematosus: a controlled randomized trial

Introduction

Exercise training has emerged as a promising therapeutic strategy to counteract physical dysfunction in adult systemic lupus erythematosus. However, no longitudinal studies have evaluated the effects of an exercise training program in childhood-onset systemic lupus erythematosus (C-SLE) patients. The objective was to evaluate the safety and the efficacy of a supervised aerobic training program in improving the cardiorespiratory capacity in C-SLE patients.

Methods

Nineteen physically inactive C-SLE patients were randomly assigned into two groups: trained (TR, n = 10, supervised moderate-intensity aerobic exercise program) and non-trained (NT, n = 9). Gender-, body mass index (BMI)- and age-matched healthy children were recruited as controls (C, n = 10) for baseline (PRE) measurements only. C-SLE patients were assessed at PRE and after 12 weeks of training (POST). Main measurements included exercise tolerance and cardiorespiratory measurements in response to a maximal exercise (that is, peak VO₂, chronotropic reserve (CR), and the heart rate recovery (ΔHRR) (that is, the difference between HR at peak exercise and at both the first (ΔHRR1) and second (ΔHRR2) minutes of recovery after exercise).

Results

The C-SLE NT patients did not present changes in any of the cardiorespiratory parameters at POST (P > 0.05). In contrast, the exercise training program was effective in promoting significant increases in time-to-exhaustion (P = 0.01; ES = 1.07), peak speed (P = 0.01; ES = 1.08), peak VO₂ (P = 0.04; ES = 0.86), CR (P = 0.06; ES = 0.83), and in ΔHRR1 and ΔHRR2 (P = 0.003; ES = 1.29 and P = 0.0008; ES = 1.36, respectively) in the C-SLE TR when compared with the NT group. Moreover, cardiorespiratory parameters were comparable between C-SLE TR patients and C subjects after the exercise training intervention, as evidenced by the ANOVA analysis (P > 0.05, TR vs. C). SLEDAI-2K scores remained stable throughout the study.

Conclusion

A 3-month aerobic exercise training was safe and capable of ameliorating the cardiorespiratory capacity and the autonomic function in C-SLE patients.

Trial registration

NCT01515163.     

Automated Entire Thrombus Density Measurements for Robust and Comprehensive Thrombus Characterization in Patients with Acute Ischemic Stroke

Background and Purpose

In acute ischemic stroke (AIS) management, CT-based thrombus density has been associated with treatment success. However, currently used thrombus measurements are prone to inter-observer variability and oversimplify the heterogeneous thrombus composition. Our aim was first to introduce an automated method to assess the entire thrombus density and then to compare the measured entire thrombus density with respect to current standard manual measurements.

Materials and Method

In 135 AIS patients, the density distribution of the entire thrombus was determined. Density distributions were described using medians, interquartile ranges (IQR), kurtosis, and skewedness. Differences between the median of entire thrombus measurements and commonly applied manual measurements using 3 regions of interest were determined using linear regression.

Results

Density distributions varied considerably with medians ranging from 20.0 to 62.8 HU and IQRs ranging from 9.3 to 55.8 HU. The average median of the thrombus density distributions (43.5 ± 10.2 HU) was lower than the manual assessment (49.6 ± 8.0 HU) (p<0.05). The difference between manual measurements and median density of entire thrombus decreased with increasing density (r = 0.64; p<0.05), revealing relatively higher manual measurements for low density thrombi such that manual density measurement tend overestimates the real thrombus density.

Conclusions

Automatic measurements of the full thrombus expose a wide variety of thrombi density distribution, which is not grasped with currently used manual measurement. Furthermore, discrimination of low and high density thrombi is improved with the automated method.     

Extracting the principal behavior of a probabilistic supervisor through neural networks ensemble

In this paper, we propose a model of a neural network ensemble that can be trained with a supervisor having two kinds of input-output functions where the occurrence probability of each function is not even. This condition can be likened to a learning condition, in which the learning data are hampered by noise. In this case, the neural network has the impression that the learning supervisor (object) has a probabilistic behavior in which the supervisor generates correct learning data most of the time but occasionally generates erroneous ones. The objective is to train the neural network to approximate the greatest distributed input-output relation, which can be considered to be the principal nature of the supervisor, so that we can obtain a neural network that is able, to some extent, to suppress the ill effect of erroneous data encountered during the learning process.     

Towards a framework for the evolutionary genomics of Kinetoplastids: what kind of data and how much?

The current status of kinetoplastids phylogeny and evolution is discussed in view of the recent progresses on genomics. Some ideas on a potential framework for the evolutionary genomics of kinetoplastids are presented.     

The role of intravascular ultrasound imaging in vascular brachytherapy

Intracoronary brachytherapy has recently emerged as a new therapy to prevent restenosis. Initial experimental work was achieved in animal models and the results were assessed by histomorphometry. Initial clinical trials used angiography to guide dosimetry and to assess efficacy. Intravascular ultrasound (IVUS) permits tomographic examination of the vessel wall, elucidating the true morphology of the lumen and transmural components, which cannot be investigated on the lumenogram obtained by angiography. This paper reviews the use of IVUS in the clinical studies of brachytherapy conducted to date. IVUS allows clinicians to make a thorough assessment of the remodeling of the vessel and appears to have a major role to play in facilitating understanding of the underlying mechanisms of action in this emerging field. The authors propose that state-of-the-art IVUS techniques should be employed to further knowledge of the mechanisms of action of brachytherapy in atherosclerotic human coronary arteries.     

Improving model construction of profile HMMs for remote homology detection through structural alignment

Background  

Remote homology detection is a challenging problem in Bioinformatics. Arguably, profile Hidden Markov Models (pHMMs) are one of the most successful approaches in addressing this important problem. pHMM packages present a relatively small computational cost, and perform particularly well at recognizing remote homologies. This raises the question of whether structural alignments could impact the performance of pHMMs trained from proteins in the Twilight Zone, as structural alignments are often more accurate than sequence alignments at identifying motifs and functional residues. Next, we assess the impact of using structural alignments in pHMM performance.     

Computational study of bindings of HL9, a nonapeptide fragment of human lysozyme, to HIV-1 fusion protein gp41

HL9 is a nonapeptide fragment of human lysozyme which has been shown to have anti-HIV-1 activity in nanomolar concentration. This study aims to explain this inhibitory activity by using molecular dynamics (MD) simulation, focusing on the ectodomain of gp41, the envelope glycoprotein of HIV-1 crucial to membrane fusion. It was found that in HL9, two Trp residues separated by two others occupy the conserved hydrophobic pocket on gp41 and thus inhibit fusion in dominant-negative manner. Detailed HL9-gp41 binding interactions and free energies of binding were obtained through MD simulation and solvated interaction energies (SIE) calculation, giving a binding free energy of −8.25 kcal/mol which is in close agreement with the experimental value of −9.96 kcal/mol. Since C-helical region (C34) of gp41 also has two Trp residues separated by two others, this arrangement may be generalised and used to scan peptide library and to find those having similar manner of inhibition.