Size effects on dynamics of nanodroplets in binary head-on collisions

Head-on collision dynamics of 10, 50 and 100 nm droplets are investigated in vacuum by molecular dynamics, involving 35,858, 4,506,410 and 36,051,466 molecules, respectively. A variety of droplet collision dynamics are observed, such as coalescence, hole formation and shattering, as a function of the Weber number. It is found for the first time that the collision and reflexive separation can occur in the nanodroplet regime when the droplet diameter reaches 100 nm but not for 10 or 50 nm droplets. The size effect in droplet collisions is studied based on the analysis of stretching factors, energy dissipation and collision outcomes for droplets of different diameters. The kinetic energy dissipation due to the atomic interactions at nanoscales is identified to significantly influence the occurrence or otherwise of reflexive separation. Through quantitative analysis of the evolution of the internal structure of the 100 nm nanodroplets collision at the Weber number of 277, it is revealed for the first time that molecules from both parent nanodroplets have penetrated the full length of the merged nanodroplet in the direction of collision, due to a combination of molecular mixing and internal currents. Consequently, all three child nanodroplets have molecules from both parent nanodroplets, contrary to the perception gained from common imaging techniques. The results show that the dynamics, outcomes and mechanisms of nanodroplet collisions have both similarities and differences compared with their micro- and macro-counterparts

Immunomodulatory Effects of Bone Marrow-Derived Mesenchymal Stem Cells in a Swine Hemi-Facial Allotransplantation Model

BACKGROUND: In this study, we investigated whether the infusion of bone marrow-derived mesenchymal stem cells (MSCs), combined with transient immunosuppressant treatment, could suppress allograft rejection and modulate T-cell regulation in a swine orthotopic hemi-facial composite tissue allotransplantation (CTA) model. METHODOLOGY/PRINCIPAL FINDINGS: Outbred miniature swine underwent hemi-facial allotransplantation (day 0). Group-I (n = 5) consisted of untreated control animals. Group-II (n = 3) animals received MSCs alone (given on days -1, +1, +3, +7, +14, and +21). Group-III (n = 3) animals received CsA (days 0 to +28). Group-IV (n = 5) animals received CsA (days 0 to +28) and MSCs (days -1, +1, +3, +7, +14, and +21). The transplanted face tissue was observed daily for signs of rejection. Biopsies of donor tissues and recipient blood sample were obtained at specified predetermined times (per 2 weeks post-transplant) or at the time of clinically evident rejection. Our results indicated that the MSC-CsA group had significantly prolonged allograft survival compared to the other groups (P<0.001). Histological examination of the MSC-CsA group displayed the lowest degree of rejection in alloskin and lymphoid gland tissues. TNF-α expression in circulating blood revealed significant suppression in the MSC and MSC-CsA treatment groups, as compared to that in controls. IHC staining showed CD45 and IL-6 expression were significantly decreased in MSC-CsA treatment groups compared to controls. The number of CD4+/CD25+ regulatory T-cells and IL-10 expressions in the circulating blood significantly increased in the MSC-CsA group compared to the other groups. IHC staining of alloskin tissue biopsies revealed a significant increase in the numbers of foxp3(+)T-cells and TGF-β1 positive cells in the MSC-CsA group compared to the other groups. CONCLUSIONS: These results demonstrate that MSCs significantly prolong hemifacial CTA survival. Our data indicate the MSCs did not only suppress inflammation and acute rejection of CTA, but also modulate T-cell regulation and related cytokines expression

Adaptive Evolutionary Clustering

In many practical applications of clustering, the objects to be clustered evolve over time, and a clustering result is desired at each time step. In such applications, evolutionary clustering typically outperforms traditional static clustering by producing clustering results that reflect long-term trends while being robust to short-term variations. Several evolutionary clustering algorithms have recently been proposed, often by adding a temporal smoothness penalty to the cost function of a static clustering method. In this paper, we introduce a different approach to evolutionary clustering by accurately tracking the time-varying proximities between objects followed by static clustering. We present an evolutionary clustering framework that adaptively estimates the optimal smoothing parameter using shrinkage estimation, a statistical approach that improves a naive estimate using additional information. The proposed framework can be used to extend a variety of static clustering algorithms, including hierarchical, k-means, and spectral clustering, into evolutionary clustering algorithms. Experiments on synthetic and real data sets indicate that the proposed framework outperforms static clustering and existing evolutionary clustering algorithms in many scenarios.Comment: To appear in Data Mining and Knowledge Discovery, MATLAB toolbox available at http://tbayes.eecs.umich.edu/xukevin/affec

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 Global Burden of Alveolar Echinococcosis

Human alveolar echinococcosis (AE), caused by the larval stage of the fox tapeworm Echinococcus multilocularis, is amongst the world's most dangerous zoonoses. Transmission to humans is by consumption of parasite eggs which are excreted in the faeces of the definitive hosts: foxes and, increasingly, dogs. Transmission can be through contact with the definitive host or indirectly through contamination of food or possibly water with parasite eggs. We made an intensive search of English, Russian, Chinese and other language databases. We targeted data which could give country specific incidence or prevalence of disease and searched for data from every country we believed to be endemic for AE. We also used data from other sources (often unpublished). From this information we were able to make an estimate of the annual global incidence of disease and disease burden using standard techniques for calculation of DALYs. Our studies suggest that AE results in a median of 18,235 cases globally with a burden of 666,433 DALYs per annum. This is the first estimate of the global burden of AE both in terms of global incidence and DALYs and demonstrates the burden of AE is comparable to several diseases in the neglected tropical disease cluster

SNPs and real-time quantitative PCR method for constitutional allelic copy number determination, the VPREB1 marker case

<p>Abstract</p> <p>Background</p> <p>22q11.2 microdeletion is responsible for the DiGeorge Syndrome, characterized by heart defects, psychiatric disorders, endocrine and immune alterations and a 1 in 4000 live birth prevalence. Real-time quantitative PCR (qPCR) approaches for allelic copy number determination have recently been investigated in 22q11.2 microdeletions detection. The qPCR method was performed for 22q11.2 microdeletions detection as a first-level screening approach in a genetically unknown series of patients with congenital heart defects. A technical issue related to the <it>VPREB1 </it>qPCR marker was pointed out.</p> <p>Methods</p> <p>A set of 100 unrelated Italian patients with congenital heart defects were tested for 22q11.2 microdeletions by a qPCR method using six different markers. Fluorescence In Situ Hybridization technique (FISH) was used for confirmation.</p> <p>Results</p> <p>qPCR identified six patients harbouring the 22q11.2 microdeletion, confirmed by FISH. The <it>VPREB1 </it>gene marker presented with a pattern consistent with hemideletion in one 3 Mb deleted patient, suggestive for a long distal deletion, and in additional five non-deleted patients. The long distal 22q11.2 deletion was not confirmed by Comparative Genomic Hybridization. Indeed, the <it>VPREB1 </it>gene marker generated false positive results in association with the rs1320 G/A SNP, a polymorphism localized within the <it>VPREB1 </it>marker reverse primer sequence. Patients heterozygous for rs1320 SNP, showed a qPCR profile consistent with the presence of a hemideletion.</p> <p>Conclusions</p> <p>Though the qPCR technique showed advantages as a screening approach in terms of cost and time, the <it>VPREB1 </it>marker case revealed that single nucleotide polymorphisms can interfere with qPCR data generating erroneous allelic copy number interpretations.</p

Notch signaling during human T cell development

Notch signaling is critical during multiple stages of T cell development in both mouse and human. Evidence has emerged in recent years that this pathway might regulate T-lineage differentiation differently between both species. Here, we review our current understanding of how Notch signaling is activated and used during human T cell development. First, we set the stage by describing the developmental steps that make up human T cell development before describing the expression profiles of Notch receptors, ligands, and target genes during this process. To delineate stage-specific roles for Notch signaling during human T cell development, we subsequently try to interpret the functional Notch studies that have been performed in light of these expression profiles and compare this to its suggested role in the mouse

Clinical decision modeling system

<p>Abstract</p> <p>Background</p> <p>Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified.</p> <p>Methods</p> <p>We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer.</p> <p>Results</p> <p>Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to estimate clinical impact. High-performance combinations of clinical options may exist for breast and lung cancer detection.</p> <p>Conclusion</p> <p>The software could be found useful in simplifying the objective-driven planning of complex integrative clinical studies without requiring a multi-attribute utility function, and it could lead to efficient integrative translational clinical study designs that move beyond simple pair wise competitive studies. Collaborators, who traditionally might compete to prioritize their own individual clinical options, can use the software as a common framework and guide to work together to produce increased understanding on the benefits of using alternative clinical combinations to affect strategic and cost-effective clinical workflows.</p

A new multi-anticipative car-following model with consideration of the desired following distance

We propose in this paper an extension of the multi-anticipative optimal velocity car-following model to consider explicitly the desired following distance. The model on the following vehicle’s acceleration is formulated as a linear function of the optimal velocity and the desired distance, with reaction-time delay in elements. The linear stability condition of the model is derived. The results demonstrate that the stability of traffic flow is improved by introducing the desired following distance, increasing the time gap in the desired following distance or decreasing the reaction-time delay. The simulation results show that by taking into account the desired following distance as well as the optimal velocity, the multi-anticipative model allows longer reaction-time delay in achieving stable traffic flows