75 research outputs found
Using Bad Learners to find Good Configurations
Finding the optimally performing configuration of a software system for a
given setting is often challenging. Recent approaches address this challenge by
learning performance models based on a sample set of configurations. However,
building an accurate performance model can be very expensive (and is often
infeasible in practice). The central insight of this paper is that exact
performance values (e.g. the response time of a software system) are not
required to rank configurations and to identify the optimal one. As shown by
our experiments, models that are cheap to learn but inaccurate (with respect to
the difference between actual and predicted performance) can still be used rank
configurations and hence find the optimal configuration. This novel
\emph{rank-based approach} allows us to significantly reduce the cost (in terms
of number of measurements of sample configuration) as well as the time required
to build models. We evaluate our approach with 21 scenarios based on 9 software
systems and demonstrate that our approach is beneficial in 16 scenarios; for
the remaining 5 scenarios, an accurate model can be built by using very few
samples anyway, without the need for a rank-based approach.Comment: 11 pages, 11 figure
Automated Whole Animal Bio-Imaging Assay for Human Cancer Dissemination
A quantitative bio-imaging platform is developed for analysis of human cancer dissemination in a short-term vertebrate xenotransplantation assay. Six days after implantation of cancer cells in zebrafish embryos, automated imaging in 96 well plates coupled to image analysis algorithms quantifies spreading throughout the host. Findings in this model correlate with behavior in long-term rodent xenograft models for panels of poorly- versus highly malignant cell lines derived from breast, colorectal, and prostate cancer. In addition, cancer cells with scattered mesenchymal characteristics show higher dissemination capacity than cell types with epithelial appearance. Moreover, RNA interference establishes the metastasis-suppressor role for E-cadherin in this model. This automated quantitative whole animal bio-imaging assay can serve as a first-line in vivo screening step in the anti-cancer drug target discovery pipeline
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Neutrophil-Mediated Experimental Metastasis Is Enhanced by VEGFR Inhibition in a Zebrafish Xenograft Model
Inhibition of VEGF signalling effectively suppresses localized tumour growth but accelerates tumour invasiveness and micrometastasis by unknown mechanisms. To study the dynamic and reciprocal interactions between tumour cells and their microenvironment during these processes, we established a xenograft model by injecting tumour cells into the blood circulation of transparent zebrafish embryos. This reproducibly results in rapid simultaneous formation of a localized tumour and experimental micrometastasis, allowing time-resolved imaging of both processes at single-cell resolution within 1 week. The tumour vasculature was initiated de novo by remodelling of primitive endothelial cells into a functional network. Roles of myeloid cells in critical tumourigenesis steps such as vascularization and invasion were revealed by genetic and pharmaceutical approaches. We discovered that the physiological migration of neutrophils controlled tumour invasion by conditioning the collagen matrix and forming the metastatic niche, as detected by two-photon confocal microscopy and second harmonic generation. Administration of VEGFR inhibitors blocked tumour vascularization and a localized tumour growth but enhanced migration of neutrophils, which in turn promoted tumour invasion and formation of micrometastasis. This demonstrates the in vivo cooperation between VEGF signalling and myeloid cells in metastasis and provides a new mechanism underlying the recent findings that VEGFR targeting can promote tumour invasiveness
Electron spin polarization in realistic trajectories around the magnetic node of two counter-propagating, circularly polarized, ultra-intense lasers
It has recently been suggested that two counter-propagating, circularly polarized, ultra-intense lasers can induce a strong electron spin polarization at the magnetic node of the electromagnetic field that they setup (Del Sorbo et al 2017 Phys. Rev. A 96 043407). We confirm these results by considering a more sophisticated description that integrates over realistic trajectories. The electron dynamics is weakly affected by the variation of power radiated due to the spin polarization. The degree of spin polarization differs by approximately 5% if considering electrons initially at rest or already in a circular orbit. The instability of trajectories at the magnetic node induces a spin precession associated with the electron migration that establishes an upper temporal limit to the polarization of the electron population of about one laser period
Robotic injection of zebrafish embryos for high-throughput screening in disease models
The increasing use of zebrafish larvae for biomedical research applications is resulting in versatile models for a variety of human diseases. These models exploit the optical transparency of zebrafish larvae and the availability of a large genetic tool box. Here we present detailed protocols for the robotic injection of zebrafish embryos at very high accuracy with a speed of up to 2000 embryos per hour. These protocols are benchmarked for several applications: (1) the injection of DNA for obtaining transgenic animals, (2) the injection of antisense morpholinos that can be used for gene knock-down, (3) the injection of microbes for studying infectious disease, and (4) the injection of human cancer cells as a model for tumor progression. We show examples of how the injected embryos can be screened at high-throughput level using fluorescence analysis. Our methods open up new avenues for the use of zebrafish larvae for large compound screens in the search for new medicines
CRIPTO and its signaling partner GRP78 drive the metastatic phenotype in human osteotropic prostate cancer
CRIPTO (CR-1, TDGF1) is a cell surface/secreted oncoprotein actively involved in development and cancer. Here, we report that high expression of CRIPTO correlates with poor survival in stratified risk groups of prostate cancer (PCa) patients. CRIPTO and its signaling partner glucose-regulated protein 78 (GRP78) are highly expressed in PCa metastases and display higher levels in the metastatic ALDHhigh sub-population of PC-3M-Pro4Luc2 PCa cells compared with non-metastatic ALDHlow. Coculture of the osteotropic PC-3M-Pro4Luc2 PCa cells with differentiated primary human osteoblasts induced CRIPTO and GRP78 expression in cancer cells and increases the size of the ALDHhigh sub-population. Additionally, CRIPTO or GRP78 knockdown decreases proliferation, migration, clonogenicity and the size of the metastasis-initiating ALDHhigh sub-population. CRIPTO knockdown reduces the invasion of PC-3M-Pro4Luc2 cells in zebrafish and inhibits bone metastasis in a preclinical mouse model. These results highlight a functional role for CRIPTO and GRP78 in PCa metastasis and suggest that targeting CRIPTO/GRP78 signaling may have significant therapeutic potential.Oncogene advance online publication, 10 April 2017; doi:10.1038/onc.2017.87
Lewis Base Mediated β-Elimination and Lewis Acid Mediated Insertion Reactions of Disilazido Zirconium Compounds
The reactivity of a series of disilazido zirconocene complexes is dominated by the migration of anionic groups (hydrogen, alkyl, halide, OTf) between the zirconium and silicon centers. The direction of these migrations is controlled by the addition of two-electron donors (Lewis bases) or two-electron acceptors (Lewis acids). The cationic nonclassical [Cp2ZrN(SiHMe2)2]+ ([2]+) is prepared from Cp2Zr{N(SiHMe2)2}H (1) and B(C6F5)3 or [Ph3C][B(C6F5)4], while reactions of B(C6F5)3 and Cp2Zr{N(SiHMe2)2}R (R = Me (3), Et (5), n-C3H7 (7), CH═CHSiMe3 (9)) provide a mixture of [2]+ and [Cp2ZrN(SiHMe2)(SiRMe2)]+. The latter products are formed through B(C6F5)3 abstraction of a β-H and R group migration from Zr to the β-Si center. Related β-hydrogen abstraction and X group migration reactions are observed for Cp2Zr{N(SiHMe2)2}X (X = OTf (11), Cl (13), OMe (15), O-i-C3H7 (16)). Alternatively, addition of DMAP (DMAP = 4-(dimethylamino)pyridine) to [2]+ results in coordination to a Si center and hydrogen migration to zirconium, giving the cationic complex [Cp2Zr{N(SiHMe2)(SiMe2DMAP)}H]+ ([19]+). Related hydrogen migration occurs from [Cp2ZrN(SiHMe2)(SiMe2OCHMe2)]+ ([18]+) to give [Cp2Zr{N(SiMe2DMAP)(SiMe2OCHMe2)}H]+ ([22]+), whereas X group migration is observed upon addition of DMAP to [Cp2ZrN(SiHMe2)(SiMe2X)]+ (X = OTf ([12]+), Cl ([14]+)) to give [Cp2Zr{N(SiHMe2)(SiMe2DMAP)}X]+ (X = OTf ([26]+), Cl ([20]+)). The species involved in these transformations are described by resonance structures that suggest β-elimination. Notably, such pathways are previously unknown in early metal amide chemistry. Finally, these migrations facilitate direct Si–H addition to carbonyls, which is proposed to occur through a pathway that previously had been reserved for later transition metal compounds
Systems microscopy approaches to understand cancer cell migration and metastasis
Cell migration is essential in a number of processes, including wound healing, angiogenesis and cancer metastasis. Especially, invasion of cancer cells in the surrounding tissue is a crucial step that requires increased cell motility. Cell migration is a well-orchestrated process that involves the continuous formation and disassembly of matrix adhesions. Those structural anchor points interact with the extra-cellular matrix and also participate in adhesion-dependent signalling. Although these processes are essential for cancer metastasis, little is known about the molecular mechanisms that regulate adhesion dynamics during tumour cell migration. In this review, we provide an overview of recent advanced imaging strategies together with quantitative image analysis that can be implemented to understand the dynamics of matrix adhesions and its molecular components in relation to tumour cell migration. This dynamic cell imaging together with multiparametric image analysis will help in understanding the molecular mechanisms that define cancer cell migration
Understanding the cancer stem cell
The last 15 years has seen an explosion of interest in the cancer stem cell (CSC). Although it was initially believed that only a rare population of stem cells are able to undergo self-renewing divisions and differentiate to form all populations within a malignancy, a recent work has shown that these cells may not be as rare as thought first, at least in some malignancies. Improved experimental models are beginning to uncover a less rigid structure to CSC biology, in which the concepts of functional plasticity and clonal evolution must be incorporated into the traditional models. Slowly the genetic programmes and biological processes underlying stem cell biology are being elucidated, opening the door to the development of drugs targeting the CSC. The aim of ongoing research to understand CSCs is to develop novel stem cell-directed treatments, which will reduce therapy resistance, relapse and the toxicity associated with current, non-selective agents
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