Reducing Traffic Congestions by Introducing CACC-Vehicles on a Multi-Lane Highway Using Agent-Based Approach

Traffic congestion is an ongoing problem of great interest to researchers from different areas in academia. With the emerging technology for inter-vehicle communication, vehicles have the ability to exchange information with predecessors by wireless communication. In this paper, we present an agent-based model of traffic congestion and examine the impact of having CACC (Cooperative Adaptive Cruise Control) embedded vehicle(s) on a highway system consisting of 4 traffic lanes without overtaking. In our model, CACC vehicles adapt their acceleration/deceleration according to vehicle-to-vehicle inter-communication. We analyze the average speed of the cars, the shockwaves, and the evolution of traffic congestion throughout the lifecycle of the model. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce the oscillatory behavior (stop and go) resulting from the acceleration/deceleration of the vehicles

Antithrombotic Prophylaxis in the Middle East

Several factors have been proposed to explain the persistence of a high incidence of venous thromboembolism worldwide with its associated morbidity and mortality. Underutilization of anticoagulants and failure of adherence to thromboprophylaxis guidelines are emerging global health concerns. We herein review this alarming observation with special emphasis on the Middle East region. We also discuss strategies that could help control this increasingly reported problem

The next frontier: Fostering innovation by improving health data access and utilization

Beneath most lively policy debates sit dry-as-dust theoretical and methodological discussions. Current disputes over the EU Adaptive Pathways initiative and the proposed US 21st Century Cures Act may ultimately rest on addressing arcane issues of data curation, standardization, and utilization. Improved extraction of inform ation on the safety and effectiveness of drugs-in-use must parallel adjustments in evidence requirements at the time of licensing. To do otherwise may compromise safety and efficacy in the name of fostering innovation

Deep neural networks allow expert-level brain meningioma segmentation and present potential for improvement of clinical practice

Accurate brain meningioma segmentation and volumetric assessment are critical for serial patient follow-up, surgical planning and monitoring response to treatment. Current gold standard of manual labeling is a time-consuming process, subject to inter-user variability. Fully-automated algorithms for meningioma segmentation have the potential to bring volumetric analysis into clinical and research workflows by increasing accuracy and efficiency, reducing inter-user variability and saving time. Previous research has focused solely on segmentation tasks without assessment of impact and usability of deep learning solutions in clinical practice. Herein, we demonstrate a three-dimensional convolutional neural network (3D-CNN) that performs expert-level, automated meningioma segmentation and volume estimation on MRI scans. A 3D-CNN was initially trained by segmenting entire brain volumes using a dataset of 10,099 healthy brain MRIs. Using transfer learning, the network was then specifically trained on meningioma segmentation using 806 expert-labeled MRIs. The final model achieved a median performance of 88.2% reaching the spectrum of current inter-expert variability (82.6-91.6%). We demonstrate in a simulated clinical scenario that a deep learning approach to meningioma segmentation is feasible, highly accurate and has the potential to improve current clinical practice

Chromosome Conformation Capture Carbon Copy (5C): a massively parallel solution for mapping interactions between genomic elements

Physical interactions between genetic elements located throughout the genome play important roles in gene regulation and can be identified with the Chromosome Conformation Capture (3C) methodology. 3C converts physical chromatin interactions into specific ligation products, which are quantified individually by PCR. Here we present a high-throughput 3C approach, 3C-Carbon Copy (5C), that employs microarrays or quantitative DNA sequencing using 454-technology as detection methods. We applied 5C to analyze a 400-kb region containing the human beta-globin locus and a 100-kb conserved gene desert region. We validated 5C by detection of several previously identified looping interactions in the beta-globin locus. We also identified a new looping interaction in K562 cells between the beta-globin Locus Control Region and the gamma-beta-globin intergenic region. Interestingly, this region has been implicated in the control of developmental globin gene switching. 5C should be widely applicable for large-scale mapping of cis- and trans- interaction networks of genomic elements and for the study of higher-order chromosome structure

Modulation of surface CD11/CD18 glycoproteins (Mo1, LFA-1, p150,95) by human mononuclear phagocytes

Mo1, LFA-1, and p150,95 are structurally related glycoproteins of the CD11/CD18 complex that are expressed on the membrane of human leukocytes. In the neutrophil, the surface expression of the CD11/CD18 complex is up-modulated (Mo1 > p150,95 >> LFA-1) by stimulatory factors that include calcium ionophore A23187, phorbol myristate acetate (PMA), and N--formyl--leucyl--phenylalanine (fMLP). Here, in an immunofluorescence analysis, we have examined CD11/CD18 glycoprotein expression by human monocytes, pulmonary alveolar macrophages (PAM, obtained by bronchoalveolar lavage), and breast milk macrophages (BMM) as compared to neutrophils before and after exposure to A23187 (1 [mu]M), fMLP (0.1 [mu]M), or PMA (0.1 [mu]g/ml) ft 37[deg]C. Unstimulated monocytes within unfractionated blood mononuclear cells kept at 4[deg]C (n = 13) expressed all three CD11/CD18 glycoproteins, and exposure to A23187 resulted in significant increases in the surface expression of Mol (median of 5.7-fold), LFA-1 (median of 2.1-fold), and p150,95 (median of 7.2-fold). Exposure to fMLP- or PMA-stimulated increases of lesser magnitude. CD11/CD18 expression by PAM (n = 9) was barely detectable and was unaffected by exposure to A23187. In contrast, BMM (n = 11) expressed all three CD11/CD18 glycoproteins (with considerable variability among specimens), but no increase was stimulated by A23187. These results demonstrate that monocytes, like neutrophils, have the capacity to respond to activating factors with an increase in CD11/CD18 glycoprotein expression; macrophage differentiation is accompanied by a loss (PAM) or retention (BMM) of CD11/CD18 expression that is unmodulated in response to activation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/27416/1/0000453.pd

On modeling two immune effectors two strain antigen interaction

In this paper we consider the fractional order model with two immune effectors interacting with two strain antigen. The systems may explain the recurrence of some diseases e.g. tuberculosis (TB). The stability of equilibrium points are studied. Numerical solutions of this model are given. Using integer order system the system oscillates. Using fractional order system the system converges to a stable internal equilibrium. Ulam-Hyers stability of the system has been studied

Genetic and Physiologic Dissection of the Vertebrate Cardiac Conduction System

Vertebrate hearts depend on highly specialized cardiomyocytes that form the cardiac conduction system (CCS) to coordinate chamber contraction and drive blood efficiently and unidirectionally throughout the organism. Defects in this specialized wiring system can lead to syncope and sudden cardiac death. Thus, a greater understanding of cardiac conduction development may help to prevent these devastating clinical outcomes. Utilizing a cardiac-specific fluorescent calcium indicator zebrafish transgenic line, Tg(cmlc2:gCaMP)s878, that allows for in vivo optical mapping analysis in intact animals, we identified and analyzed four distinct stages of cardiac conduction development that correspond to cellular and anatomical changes of the developing heart. Additionally, we observed that epigenetic factors, such as hemodynamic flow and contraction, regulate the fast conduction network of this specialized electrical system. To identify novel regulators of the CCS, we designed and performed a new, physiology-based, forward genetic screen and identified for the first time, to our knowledge, 17 conduction-specific mutations. Positional cloning of hobgoblins634 revealed that tcf2, a homeobox transcription factor gene involved in mature onset diabetes of the young and familial glomerulocystic kidney disease, also regulates conduction between the atrium and the ventricle. The combination of the Tg(cmlc2:gCaMP)s878 line/in vivo optical mapping technique and characterization of cardiac conduction mutants provides a novel multidisciplinary approach to further understand the molecular determinants of the vertebrate CCS

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Regulation of mammary gland branching morphogenesis by the extracellular matrix and its remodeling enzymes.

A considerable body of research indicates that mammary gland branching morphogenesis is dependent, in part, on the extracellular matrix (ECM), ECM-receptors, such as integrins and other ECM receptors, and ECM-degrading enzymes, including matrix metalloproteinases (MMPs) and their inhibitors, tissue inhibitors of metalloproteinases (TIMPs). There is some evidence that these ECM cues affect one or more of the following processes: cell survival, polarity, proliferation, differentiation, adhesion, and migration. Both three-dimensional culture models and genetic manipulations of the mouse mammary gland have been used to study the signaling pathways that affect these processes. However, the precise mechanisms of ECM-directed mammary morphogenesis are not well understood. Mammary morphogenesis involves epithelial 'invasion' of adipose tissue, a process akin to invasion by breast cancer cells, although the former is a highly regulated developmental process. How these morphogenic pathways are integrated in the normal gland and how they become dysregulated and subverted in the progression of breast cancer also remain largely unanswered questions