Optically trapped bacteria pairs reveal discrete motile response to control aggregation upon cell–cell approach

Aggregation of bacteria plays a key role in the formation of many biofilms. The critical first step is cell–cell approach, and yet the ability of bacteria to control the likelihood of aggregation during this primary phase is unknown. Here, we use optical tweezers to measure the force between isolated Bacillus subtilis cells during approach. As we move the bacteria towards each other, cell motility (bacterial swimming) initiates the generation of repulsive forces at bacterial separations of ~3 μm. Moreover, the motile response displays spatial sensitivity with greater cell–cell repulsion evident as inter-bacterial distances decrease. To examine the environmental influence on the inter-bacterial forces, we perform the experiment with bacteria suspended in Tryptic Soy Broth, NaCl solution and deionised water. Our experiments demonstrate that repulsive forces are strongest in systems that inhibit biofilm formation (Tryptic Soy Broth), while attractive forces are weak and rare, even in systems where biofilms develop (NaCl solution). These results reveal that bacteria are able to control the likelihood of aggregation during the approach phase through a discretely modulated motile response. Clearly, the force-generating motility we observe during approach promotes biofilm prevention, rather than biofilm formation

Improving Fetal Head Contour Detection by Object Localisation with Deep Learning

Ultrasound-based fetal head biometrics measurement is a key indicator in monitoring the conditions of fetuses. Since manual measurement of relevant anatomical structures of fetal head is time-consuming and subject to inter-observer variability, there has been strong interest in finding automated, robust, accurate and reliable method. In this paper, we propose a deep learning-based method to segment fetal head from ultrasound images. The proposed method formulates the detection of fetal head boundary as a combined object localisation and segmentation problem based on deep learning model. Incorporating an object localisation in a framework developed for segmentation purpose aims to improve the segmentation accuracy achieved by fully convolutional network. Finally, ellipse is fitted on the contour of the segmented fetal head using least-squares ellipse fitting method. The proposed model is trained on 999 2-dimensional ultrasound images and tested on 335 images achieving Dice coefficient of$$97.73 \pm 1.32$$. The experimental results demonstrate that the proposed deep learning method is promising in automatic fetal head detection and segmentation

Inhibition of the tyrosine phosphatase SHP-2 suppresses angiogenesis in vitro and in vivo

Endothelial cell survival is indispensable to maintain endothelial integrity and initiate new vessel formation. We investigated the role of SHP-2 in endothelial cell survival and angiogenesis in vitro as well as in vivo. SHP-2 function in cultured human umbilical vein and human dermal microvascular endothelial cells was inhibited by either silencing the protein expression with antisense-oligodesoxynucleotides or treatment with a pharmacological inhibitor (PtpI IV). SHP-2 inhibition impaired capillary-like structure formation (p < 0.01; n = 8) in vitro as well as new vessel growth ex vivo (p < 0.05; n = 10) and in vivo in the chicken chorioallantoic membrane (p < 0.01, n = 4). Additionally, SHP-2 knock-down abrogated fibroblast growth factor 2 (FGF-2)-dependent endothelial proliferation measured by MTT reduction ( p ! 0.01; n = 12). The inhibitory effect of SHP-2 knock-down on vessel growth was mediated by increased endothelial apoptosis ( annexin V staining, p ! 0.05, n = 9), which was associated with reduced FGF-2-induced phosphorylation of phosphatidylinositol 3-kinase (PI3-K), Akt and extracellular regulated kinase 1/2 (ERK1/2) and involved diminished ERK1/2 phosphorylation after PI3-K inhibition (n=3). These results suggest that SHP-2 regulates endothelial cell survival through PI3-K-Akt and mitogen-activated protein kinase pathways thereby strongly affecting new vessel formation. Thus, SHP-2 exhibits a pivotal role in angiogenesis and may represent an interesting target for therapeutic approaches controlling vessel growth. Copyright (C) 2007 S. Karger AG, Basel

The rank reversal problem in multi-criteria decision making : a literature review

Despite the importance of multicriteria decision-making (MCDM) techniques for constructing effective decision models, there are many criticisms due to the occurrence of a problem called rank reversal. Nevertheless, there is a lack of a systematic literature review on this important subject which involves different methods. This study reviews the pertinent literature on rank reversal, based on 130 related articles published from 1980 to 2015 in international journals, which were gathered and analyzed according to the following perspectives: multicriteria technique, year and journal in which the papers were published, co-authorship network, rank reversal types, and research goal. Thus our survey provides recommendations for future research, besides useful information and knowledge regarding rank reversal in the MCDM field

Applying refinement to the use of mice and rats in rheumatoid arthritis research

Rheumatoid arthritis (RA) is a painful, chronic disorder and there is currently an unmet need for effective therapies that will benefit a wide range of patients. The research and development process for therapies and treatments currently involves in vivo studies, which have the potential to cause discomfort, pain or distress. This Working Group report focuses on identifying causes of suffering within commonly used mouse and rat ‘models’ of RA, describing practical refinements to help reduce suffering and improve welfare without compromising the scientific objectives. The report also discusses other, relevant topics including identifying and minimising sources of variation within in vivo RA studies, the potential to provide pain relief including analgesia, welfare assessment, humane endpoints, reporting standards and the potential to replace animals in RA research

A mechanism for the inhibition of DNA-PK-mediated DNA sensing by a virus

The innate immune system is critical in the response to infection by pathogens and it is activated by pattern recognition receptors (PRRs) binding to pathogen associated molecular patterns (PAMPs). During viral infection, the direct recognition of the viral nucleic acids, such as the genomes of DNA viruses, is very important for activation of innate immunity. Recently, DNA-dependent protein kinase (DNA-PK), a heterotrimeric complex consisting of the Ku70/Ku80 heterodimer and the catalytic subunit DNA-PKcs was identified as a cytoplasmic PRR for DNA that is important for the innate immune response to intracellular DNA and DNA virus infection. Here we show that vaccinia virus (VACV) has evolved to inhibit this function of DNA-PK by expression of a highly conserved protein called C16, which was known to contribute to virulence but by an unknown mechanism. Data presented show that C16 binds directly to the Ku heterodimer and thereby inhibits the innate immune response to DNA in fibroblasts, characterised by the decreased production of cytokines and chemokines. Mechanistically, C16 acts by blocking DNA-PK binding to DNA, which correlates with reduced DNA-PK-dependent DNA sensing. The C-terminal region of C16 is sufficient for binding Ku and this activity is conserved in the variola virus (VARV) orthologue of C16. In contrast, deletion of 5 amino acids in this domain is enough to knockout this function from the attenuated vaccine strain modified vaccinia virus Ankara (MVA). In vivo a VACV mutant lacking C16 induced higher levels of cytokines and chemokines early after infection compared to control viruses, confirming the role of this virulence factor in attenuating the innate immune response. Overall this study describes the inhibition of DNA-PK-dependent DNA sensing by a poxvirus protein, adding to the evidence that DNA-PK is a critical component of innate immunity to DNA viruses

Particulate Matter Exposure Exacerbates High Glucose-Induced Cardiomyocyte Dysfunction through ROS Generation

Diabetes mellitus and fine particulate matter from diesel exhaust (DEP) are both important contributors to the development of cardiovascular disease (CVD). Diabetes mellitus is a progressive disease with a high mortality rate in patients suffering from CVD, resulting in diabetic cardiomyopathy. Elevated DEP levels in the air are attributed to the development of various CVDs, presumably since fine DEP (<2.5 µm in diameter) can be inhaled and gain access to the circulatory system. However, mechanisms defining how DEP affects diabetic or control cardiomyocyte function remain poorly understood. The purpose of the present study was to evaluate cardiomyocyte function and reactive oxygen species (ROS) generation in isolated rat ventricular myocytes exposed overnight to fine DEP (0.1 µg/ml), and/or high glucose (HG, 25.5 mM). Our hypothesis was that DEP exposure exacerbates contractile dysfunction via ROS generation in cardiomyocytes exposed to HG. Ventricular myocytes were isolated from male adult Sprague-Dawley rats cultured overnight and sarcomeric contractile properties were evaluated, including: peak shortening normalized to baseline (PS), time-to-90% shortening (TPS90), time-to-90% relengthening (TR90) and maximal velocities of shortening/relengthening (±dL/dt), using an IonOptix field-stimulator system. ROS generation was determined using hydroethidine/ethidium confocal microscopy. We found that DEP exposure significantly increased TR90, decreased PS and ±dL/dt, and enhanced intracellular ROS generation in myocytes exposed to HG. Further studies indicated that co-culture with antioxidants (0.25 mM Tiron and 0.5 mM N-Acetyl-L-cysteine) completely restored contractile function in DEP, HG and HG+DEP-treated myocytes. ROS generation was blocked in HG-treated cells with mitochondrial inhibition, while ROS generation was blocked in DEP-treated cells with NADPH oxidase inhibition. Our results suggest that DEP exacerbates myocardial dysfunction in isolated cardiomyocytes exposed to HG-containing media, which is potentially mediated by various ROS generation pathways

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P &lt; 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms

A Two-Stage Random Forest-Based Pathway Analysis Method

Pathway analysis provides a powerful approach for identifying the joint effect of genes grouped into biologically-based pathways on disease. Pathway analysis is also an attractive approach for a secondary analysis of genome-wide association study (GWAS) data that may still yield new results from these valuable datasets. Most of the current pathway analysis methods focused on testing the cumulative main effects of genes in a pathway. However, for complex diseases, gene-gene interactions are expected to play a critical role in disease etiology. We extended a random forest-based method for pathway analysis by incorporating a two-stage design. We used simulations to verify that the proposed method has the correct type I error rates. We also used simulations to show that the method is more powerful than the original random forest-based pathway approach and the set-based test implemented in PLINK in the presence of gene-gene interactions. Finally, we applied the method to a breast cancer GWAS dataset and a lung cancer GWAS dataset and interesting pathways were identified that have implications for breast and lung cancers