Spontaneous Cell Detachment and Reattachment in Cancer Cell Lines: An In Vitro Model of Metastasis and Malignancy

There is an unmet need for simplified in vitro models of malignancy and metastasis that facilitate fast, affordable and scalable gene and compound analysis. “Adherent” cancer cell lines frequently release “free-floating” cells into suspension that are viable and can reattach. This, in a simplistic way, mimics the metastatic process. We compared the gene expression profiles of naturally co-existing populations of floating and adherent cells in SW620 (colon), C33a (cervix) and HeLa (cervix) cancer cells. We found that 1227, 1367 and 1333 genes were at least 2-fold differentially expressed in the respective cell lines, of which 122 were shared among the three cell lines. As proof of principle, we focused on the anti-metastatic gene NM23-H1, which was downregulated both at the RNA and protein level in the floating cell populations of all three cell lines. Knockdown of NM23-H1 significantly increased the number of floating (and viable) cells, whereas overexpression of NM23-H1 significantly reduced the proportion of floating cells. Other potential regulators of these cellular states were identified through pathway analysis, including hypoxia, mTOR (mechanistic target of rapamycin), cell adhesion and cell polarity signal transduction pathways. Hypoxia, a condition linked to malignancy and metastasis, reduced NM23-H1 expression and significantly increased the number of free-floating cells. Inhibition of mTOR or Rho-associated protein kinase (ROCK) significantly increased cell death specifically in the floating and not the adherent cell population. In conclusion, our study suggests that dynamic subpopulations of free-floating and adherent cells is a useful model to screen and identify genes, drugs and pathways that regulate the process of cancer metastasis, such as cell detachment and anoikis.     

Analytical approach on magnetohydrodynamic Casson fluid flow past a stretching sheet via Adomian decomposition method

Flow phenomena of three-dimensional conducting Casson fluid through a stretching sheet are proposed in the present investigation with the impact of the magnetic parameter in a permeable medium. The adaptation of particular transformations is useful to modify the governing equations into their nondimensional as well as the ordinary form. However, these transformed equations are nonlinear and approximate analytical methods for the solution of the complex form of governing equations. In particular, the Adomian decomposition method is proposed for the solution. The behavior of several variables, such as the magnetic and porous matrix, on the flow profile as well as the rate of shear stress, are discussed via graphs and tables. The conformity of the current result with the earlier study shows a road map for further investigation. The major concluding remarks are; the retardation in the velocity distribution is rendered due to an increase in the Casson parameter moreover, the Casson parameter favors in reducing the rate of shear stress coefficient in magnitude.     

Alpha Synuclein only Forms Fibrils In Vitro when Larger than its Critical Size of 70 Monomers

The aggregation of α-synuclein into small soluble aggregates and then fibrils is important in the development and spreading of aggregates through the brain in Parkinson's disease. Fibrillar aggregates can grow by monomer addition and then break into fragments that could spread into neighboring cells. The rate constants for fibril elongation and fragmentation have been measured but it is not known how large an aggregate needs to be before fibril formation is thermodynamically favorable. This critical size is an important parameter controlling at what stage in an aggregation reaction fibrils can form and replicate. We determined this value to be approximately 70 monomers using super-resolution and atomic force microscopy imaging of individual α-synuclein aggregates formed in solution over long time periods. This represents the minimum size for a stable α-synuclein fibril and we hypothesis the formation of aggregates of this size in a cell represents a tipping point at which rapid replication occurs.     

Inhibition of Soluble Epoxide Hydrolase Ameliorates Phenotype and Cognitive Abilities in a Murine Model of Niemann Pick Type C Disease

Niemann–Pick type C (NPC) disease is a rare autosomal recessive inherited childhood neurodegenerative disease characterized by the accumulation of cholesterol and glycosphingolipids, involving the autophagy-lysosome system. Inhibition of soluble epoxide hydrolase (sEH), an enzyme that metabolizes epoxy fatty acids (EpFAs) to 12-diols, exerts beneficial effects in modulating inflammation and autophagy, critical features of the NPC disease. This study aims to evaluate the effects of UB-EV-52, an sEH inhibitor (sEHi), in an NPC mouse model (Npc) by administering it for 4 weeks (5 mg/kg/day). Behavioral and cognitive tests (open-field test (OF)), elevated plus maze (EPM), novel object recognition test (NORT) and object location test (OLT) demonstrated that the treatment produced an improvement in short- and long-term memory as well as in spatial memory. Furthermore, UB-EV-52 treatment increased body weight and lifespan by 25% and reduced gene expression of the inflammatory markers (i.e., Il-1β and Mcp1) and enhanced oxidative stress (OS) markers (iNOS and Hmox1) in the treated Npc mice group. As for autophagic markers, surprisingly, we found significantly reduced levels of LC3B-II/LC3B-I ratio and significantly reduced brain protein levels of lysosomal-associated membrane protein-1 (LAMP-1) in treated Npc mice group compared to untreated ones in hippocampal tissue. Lipid profile analysis showed a significant reduction of lipid storage in the liver and some slight changes in homogenated brain tissue in the treated NPC mice compared to the untreated groups. Therefore, our results suggest that pharmacological inhibition of sEH ameliorates most of the characteristic features of NPC mice, demonstrating that sEH can be considered a potential therapeutic target for this disease.     

Dictionary-based classifiers for exploiting feature sequence information and their application to hyperspectral remotely sensed data

The problem of classification is shared across various disciplines. Designing even less computationally demanding and more effective classifiers has been a key challenge for researchers for many years. No single classifier can be highly effective for all types of datasets and thus, depending on the data distribution, various classifiers have been proposed in the literature. To our knowledge, feature values have been vastly exploited as the base for discriminating classes, while feature sequence information has been somehow under-exploited so far. In the proposed approach normalised features are sorted and ranked, creating a sequence of finite numbers. The associated rank of the created sequence is used as an additional feature, which in a way defines the sample-specific intra-feature relationship. Three novel dictionary-based approaches such as Sequence Classifier (SC), Sequence-dictionary-based k-Nearest Neighbours Classifier (SDk-NN) and Combined-dictionary-based k-Nearest Neighbours Classifier (CDk-NN) are proposed in this paper.

In the case of remotely sensed data, and specifically in Hyper-Spectral Images (HSI), the spectral features (Spectral signatures) represent a strong, object-specific spectral relationship, which is a key point in our proposed approach. In this case, indeed, the proposed classifiers were tested over various (five) HS datasets and found to be effective. Based on the classifiers features, two derived distance measures are proposed and validated for the HS dataset, namely: the Normalised Sequence Distance (NSD) measure and Combined Distance (CD) measure. These measures appear to overperform the conventional Normalised Euclidean Distance (NED) in this context. Also, validation for both binary and multi-class datasets are experimented and their performances are evaluated in terms of accuracy and other standard measures. Experimental results over 21 datasets revealed that the proposed approaches perform comparably, and in some cases even better than other classifiers. Stack-operated, class-specific sparse dictionaries are also introduced in order to reduce the computational complexity, which can be used as an active learning-based approach for optimal training sample selection. Additional tests were performed with variable levels of dictionary sparsity for assessing its impact on accuracy.     

Introducing the Planar Laser-Induced Fluorescence Technique (PLIF) to Measure Mixing Time in Gas-Stirred Ladles

Metallurgical and Materials Transactions B - The planar laser-induced fluorescence (PLIF) technique was implemented to measure mixing time in a 1/17 water model of a 200-ton ladle furnace. The...     

2015年世博会卡里塔斯展馆及埃内尔展馆 意大利米兰

正Piuarch建筑师事务所负责设计了2015年米兰世博会埃内尔(意大利国家电力公司)展馆及卡里塔斯展馆。为了将客户想表达的含义与价值观更好地传达给观众,Piuarch选择了一种特殊的建筑语言来体现两个展馆的特点。埃内尔展馆沿东西大街而建,占地900平方米。设计体现出智能电网这一概念,传达出以智能科技优化世博会整体用电的理念。     

Synthesis and characterization of Y (In,Mn) O3 blue pigment using the complex polymerization method (CPM)

In this paper, a new synthetic pathway is proposed for the system YIn_1-xMn_xO₃, a bright blue inorganic pigment, discovered in 2009. Blue pigment samples with increasing concentration of Mn³⁺ (x?=?0.08, 0.12 and 0.16) were prepared using the complex polymerization method (CPM) and compared with those synthesized via solid state reaction. All powders, the amorphous precursor from CPM and the starting materials for solid state method, were calcined at 1000, 1100, 1200 and 1300?°C for 12?h, and the resulting blue pigments were characterized by X-ray diffraction (XRD), colorimetric system CIE L*a*b* and Near infrared (NIR) reflectance measurements. XRD patterns and Rietveld Refinement show that the lowest temperature at which single hexagonal phase (isostructural to YInO₃) is formed is 1000?°C for CPM method and 1300?°C for conventional solid state method, respectively. The L*a*b* values demonstrate that the coloration of powders prepared by CPM exhibit temperature dependence below 1300?°C, a color shade shift from grayish blue to intense deep blue is observed when heating the samples from 1000 to 1300?°C. Blue pigments obtained by CPM have smaller particle size due to low temperatures and excellent near-infrared reflectance comparable to those by solid state method. Thus, providing advantages for application process and energy efficiency.