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.     

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.     

Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics

We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (GeneVec) for gene sequences, this representation can be widely used in applications of deep learning in proteomics and genomics. In the present paper, we focus on protein-vectors that can be utilized in a wide array of bioinformatics investigations such as family classification, protein visualization, structure prediction, disordered protein identification, and protein-protein interaction prediction. In this method, we adopt artificial neural network approaches and represent a protein sequence with a single dense n-dimensional vector. To evaluate this method, we apply it in classification of 324,018 protein sequences obtained from Swiss-Prot belonging to 7,027 protein families, where an average family classification accuracy of 93%±0.06% is obtained, outperforming existing family classification methods. In addition, we use ProtVec representation to predict disordered proteins from structured proteins. Two databases of disordered sequences are used: the DisProt database as well as a database featuring the disordered regions of nucleoporins rich with phenylalanine-glycine repeats (FG-Nups). Using support vector machine classifiers, FG-Nup sequences are distinguished from structured protein sequences found in Protein Data Bank (PDB) with a 99.8% accuracy, and unstructured DisProt sequences are differentiated from structured DisProt sequences with 100.0% accuracy. These results indicate that by only providing sequence data for various proteins into this model, accurate information about protein structure can be determined. Importantly, this model needs to be trained only once and can then be applied to extract a comprehensive set of information regarding proteins of interest. Moreover, this representation can be considered as pre-training for various applications of deep learning in bioinformatics. The related data is available at Life Language Processing Website: http://llp.berkeley.edu and Harvard Dataverse: http://dx.doi.org/10.7910/DVN/JMFHTN.     

A finite shell element for heart mitral valve leaflet mechanics, with large deformations and 3D constitutive material model

This paper presents a shell finite element formulation appropriate for simulating the heart valve leaflet mechanics, including three-dimensional (3D) stress and strain effects. A 4-node mixed-interpolation shell is formulated in convected coordinates. This shell model is made capable of handling arbitrary 3D material models by use of an algorithm that satisfies the shell stress assumption at every element integration point. A method for tracking the fiber direction is incorporated. The resulting shell element operates under the same conditions as a standard 4-node shell element with 5 degrees of freedom per node, but extends the modeling capabilities to handle large-deformation and anisotropic behavior.     

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.     

Buckling Behavior of Individual and Bundled Microtubules

As the major structural constituent of the cytoskeleton, microtubules (MTs) serve a variety of biological functions that range from facilitating organelle transport to maintaining the mechanical integrity of the cell. Neuronal MTs exhibit a distinct configuration, hexagonally packed bundles of MT filaments, interconnected by MT-associated protein (MAP) tau. Building on our previous work on mechanical response of axonal MT bundles under uniaxial tension, this study is focused on exploring the compression scenarios. Intracellular MTs carry a large fraction of the compressive loads sensed by the cell and therefore, like any other column-like structure, are prone to substantial bending and buckling. Various biological activities, e.g., actomyosin contractility and many pathological conditions are driven or followed by bending, looping, and buckling of MT filaments. The coarse-grained model previously developed in our lab has been used to study the mechanical behavior of individual and bundled in vivo MT filaments under uniaxial compression. Both configurations show tip-localized, decaying, and short-wavelength buckling. This behavior highlights the role of the surrounding cytoplasm and MAP tau on MT buckling behavior, which allows MT filaments to bear much larger compressive forces. It is observed that MAP tau interconnections improve this effect by a factor of two. The enhanced ability of MT bundles to damp buckling waves relative to individual MT filaments, may be interpreted as a self-defense mechanism because it helps axonal MTs to endure harsher environments while maintaining their function. The results indicate that MT filaments in a bundle do not buckle simultaneously implying that the applied stress is not equally shared among the MT filaments, that is a consequence of the nonuniform distribution of MAP tau proteins along the bundle length. Furthermore, from a pathological perspective, it is observed that axonal MT bundles are more vulnerable to failure in compression than tension.