Rapid Quantification of 3D Collagen Fiber Alignment and Fiber Intersection Correlations with High Sensitivity

Metastatic cancers aggressively reorganize collagen in their microenvironment. For example, radially orientated collagen fibers have been observed surrounding tumor cell clusters in vivo. The degree of fiber alignment, as a consequence of this remodeling, has often been difficult to quantify. In this paper, we present an easy to implement algorithm for accurate detection of collagen fiber orientation in a rapid pixel-wise manner. This algorithm quantifies the alignment of both computer generated and actual collagen fiber networks of varying degrees of alignment within 5°°. We also present an alternative easy method to calculate the alignment index directly from the standard deviation of fiber orientation. Using this quantitative method for determining collagen alignment, we demonstrate that the number of collagen fiber intersections has a negative correlation with the degree of fiber alignment. This decrease in intersections of aligned fibers could explain why cells move more rapidly along aligned fibers than unaligned fibers, as previously reported. Overall, our paper provides an easier, more quantitative and quicker way to quantify fiber orientation and alignment, and presents a platform in studying effects of matrix and cellular properties on fiber alignment in complex 3D environments.     

Inducible Nitric Oxide Synthase Promoter Haplotypes and Residential Traffic-Related Air Pollution Jointly Influence Exhaled Nitric Oxide Level in Children

BackgroundExhaled nitric oxide (FeNO), a biomarker of airway inflammation, predicts asthma risk in children. We previously found that the promoter haplotypes in inducible nitric oxide synthase (NOS2) and exposure to residential traffic independently influence FeNO level. Because NOS2 is inducible by environmental exposures such as traffic-related exposure, we tested the hypothesis that common NOS2 promoter haplotypes modulate the relationship between residential traffic-related exposure and FeNO level in children.MethodsIn a cross-sectional population-based study, subjects (N = 2,457; 7–11 year-old) were Hispanic and non-Hispanic white children who participated in the Southern California Children’s Health Study and had FeNO measurements. For residential traffic, lengths of local roads within circular buffers (50m, 100m and 200m radii around homes) around the subjects’ homes were estimated using geographic information system (GIS) methods. We interrogated the two most common NOS2 promoter haplotypes that were found to affect FeNO level.ResultsThe relationship between local road lengths within 100m and 200m circular buffers and FeNO level varied significantly by one of the NOS2 promoter haplotypes (P-values for interaction between road length and NOS2 promoter haplotype = 0.02 and 0.03, respectively). In children who had ≤250m of local road lengths within 100m buffer around their homes, those with two copies of the haplotype had significantly lower FeNO (adjusted geometric mean = 11.74ppb; 95% confidence intervals (CI): 9.99 to 13.80) than those with no copies (adjusted geometric mean = 15.28ppb; 95% CI: 14.04 to 16.63) with statistically significant trend of lower FeNO level with increasing number of haplotype copy (P-value for trend = 0.002). In contrast, among children who had >250m of local road lengths within 100m buffer, FeNO level did not significantly differ by the haplotype copy-number (P-value for trend = 0.34). Similar interactive effects of this haplotype and local road lengths within 200m buffer on FeNO were also observed.ConclusionsHigher exposure from residential traffic nullifies the protective effect of one common NOS2 promoter haplotype on FeNO level. Regulation of traffic-related pollution may protect children’s respiratory health.     

A Unified Framework for Creating Domain Dependent Polarity Lexicons from User Generated Reviews

The exponential increase in the explosion of Web-based user generated reviews has resulted in the emergence of Opinion Mining (OM) applications for analyzing the users’ opinions toward products, services, and policies. The polarity lexicons often play a pivotal role in the OM, indicating the positivity and negativity of a term along with the numeric score. However, the commonly available domain independent lexicons are not an optimal choice for all of the domains within the OM applications. The aforementioned is due to the fact that the polarity of a term changes from one domain to other and such lexicons do not contain the correct polarity of a term for every domain. In this work, we focus on the problem of adapting a domain dependent polarity lexicon from set of labeled user reviews and domain independent lexicon to propose a unified learning framework based on the information theory concepts that can assign the terms with correct polarity (+ive, -ive) scores. The benchmarking on three datasets (car, hotel, and drug reviews) shows that our approach improves the performance of the polarity classification by achieving higher accuracy. Moreover, using the derived domain dependent lexicon changed the polarity of terms, and the experimental results show that our approach is more effective than the base line methods.     

DisPredict: A Predictor of Disordered Protein Using Optimized RBF Kernel

Intrinsically disordered proteins or, regions perform important biological functions through their dynamic conformations during binding. Thus accurate identification of these disordered regions have significant implications in proper annotation of function, induced fold prediction and drug design to combat critical diseases. We introduce DisPredict, a disorder predictor that employs a single support vector machine with RBF kernel and novel features for reliable characterization of protein structure. DisPredict yields effective performance. In addition to 10-fold cross validation, training and testing of DisPredict was conducted with independent test datasets. The results were consistent with both the training and test error minimal. The use of multiple data sources, makes the predictor generic. The datasets used in developing the model include disordered regions of various length which are categorized as short and long having different compositions, different types of disorder, ranging from fully to partially disordered regions as well as completely ordered regions. Through comparison with other state of the art approaches and case studies, DisPredict is found to be a useful tool with competitive performance. DisPredict is available at https://github.com/tamjidul/DisPredict_v1.0.     

Effects of Porosity and Mixed Convection on MHD Two Phase Fluid Flow in an Inclined Channel

The present study deals with the flow and heat transfer analysis of two immiscible fluids in an inclined channel embedded in a porous medium. The channel is divided in two phases such that a third grade fluid occupies the phase I and a viscous fluid occupies the phase II. Both viscous and third grade fluids are electrically conducting. A constant magnetic field is imposed perpendicular to the channel walls. The mathematical model is developed by using Darcy''s and modified Darcy''s laws for viscous and third grade fluids respectively. The transformed ordinary differential equations are solved numerically using a shooting method. The obtained results are presented graphically and influence of emerging parameters is discussed in detail.     

Immune Derangements in Patients with Myelofibrosis: The Role of Treg,Th17, and sIL2Rα

Myelofibrosis (MF), including primary myelofibrosis, post-essential thrombocythemia MF, and post-polycythemia vera MF, has been reported to be associated with autoimmune phenomena. IMiDs have been reported to be effective in some patients with MF, presumably for their immune-modulator effects. We therefore sought to elucidate the immune derangements in patients with MF. We found no differences in T regulatory cells (Treg) and T helper 17 (Th17) cells in MF patients and normal healthy controls. However, we found significantly elevated soluble interleukin 2 alpha (sIL2Rα) in MF patients compared to those with other myeloproliferative neoplasm diseases and normal healthy controls. Our studies with MF patients further revealed that Treg cells were the predominant cells producing sIL2Rα. sIL2Rα and IL2 complex induced the formation of Treg cells but not the formation of Th1 or Th17 cells. sIL2Rα induced CD8⁺ T cell proliferation in the presence of Treg cells. Monocytes or neutrophils had no effect on the production of sIL2Rα by Treg cells. Furthermore, we found plasma sIL2Rα levels were correlated to the auto-immune serology in MPN patients and ruxolitinib significantly inhibits the sIL2Rα production by the Treg cells in MF patients which may explain the effects of ruxolitinib on the relief of constitutional symptoms. All these findings suggest that sIL2Rα likely plays a significant role in autoimmune phenomena seen in patients with MF. Further studies of immune derangement may elucidate the mechanism of IMiD, and exploration of immune modulators may prove to be important for treating myelofibrosis.     

Vitamin D Prevents Hypoxia/Reoxygenation-Induced Blood-Brain Barrier Disruption via Vitamin D Receptor-Mediated NF-kB Signaling Pathways

Maintaining blood-brain barrier integrity and minimizing neuronal injury are critical components of any therapeutic intervention following ischemic stroke. However, a low level of vitamin D hormone is a risk factor for many vascular diseases including stroke. The neuroprotective effects of 1,25(OH)2D3 (vitamin D) after ischemic stroke have been studied, but it is not known whether it prevents ischemic injury to brain endothelial cells, a key component of the neurovascular unit. We analyzed the effect of 1,25(OH)₂D₃ on brain endothelial cell barrier integrity and tight junction proteins after hypoxia/reoxygenation in a mouse brain endothelial cell culture model that closely mimics many of the features of the blood-brain barrier in vitro. Following hypoxic injury in bEnd.3 cells, 1,25(OH)₂D₃ treatment prevented the decrease in barrier function as measured by transendothelial electrical resistance and permeability of FITC-dextran (40 kDa), the decrease in the expression of the tight junction proteins zonula occludin-1, claudin-5, and occludin, the activation of NF—kB, and the increase in matrix metalloproteinase-9 expression. These responses were blocked when the interaction of 1,25(OH) )₂D₃ with the vitamin D receptor (VDR) was inhibited by pyridoxal 5’-phosphate treatment. Our findings show a direct, VDR-mediated, protective effect of 1,25(OH) )₂D₃ against ischemic injury-induced blood-brain barrier dysfunction in cerebral endothelial cells.     

A 3-Component Mixture of Rayleigh Distributions: Properties and Estimation in Bayesian Framework

To study lifetimes of certain engineering processes, a lifetime model which can accommodate the nature of such processes is desired. The mixture models of underlying lifetime distributions are intuitively more appropriate and appealing to model the heterogeneous nature of process as compared to simple models. This paper is about studying a 3-component mixture of the Rayleigh distributionsin Bayesian perspective. The censored sampling environment is considered due to its popularity in reliability theory and survival analysis. The expressions for the Bayes estimators and their posterior risks are derived under different scenarios. In case the case that no or little prior information is available, elicitation of hyperparameters is given. To examine, numerically, the performance of the Bayes estimators using non-informative and informative priors under different loss functions, we have simulated their statistical properties for different sample sizes and test termination times. In addition, to highlight the practical significance, an illustrative example based on a real-life engineering data is also given.     

Application of Central Upwind Scheme for Solving Special Relativistic Hydrodynamic Equations

The accurate modeling of various features in high energy astrophysical scenarios requires the solution of the Einstein equations together with those of special relativistic hydrodynamics (SRHD). Such models are more complicated than the non-relativistic ones due to the nonlinear relations between the conserved and state variables. A high-resolution shock-capturing central upwind scheme is implemented to solve the given set of equations. The proposed technique uses the precise information of local propagation speeds to avoid the excessive numerical diffusion. The second order accuracy of the scheme is obtained with the use of MUSCL-type initial reconstruction and Runge-Kutta time stepping method. After a discussion of the equations solved and of the techniques employed, a series of one and two-dimensional test problems are carried out. To validate the method and assess its accuracy, the staggered central and the kinetic flux-vector splitting schemes are also applied to the same model. The scheme is robust and efficient. Its results are comparable to those obtained from the sophisticated algorithms, even in the case of highly relativistic two-dimensional test problems.