Characterization of immune cell distributions in mouse models of spontaneous breast tumors

As immunotherapy grows in popularity as a cancer treatment option, we need to further understand how immune cells interact with the tumor microenvironment and influence tumor progression. The goal of this thesis was to characterize the different immune, cellular, and structural components within the breast tumor tissues of two orthotopic (MCaP0008 and M3C) and one spontaneous (MMTV-PyVT) murine models of immunogenic breast cancer. Identification of the tumor components in question, including CD3+ lymphocytes, CD11b+ myeloid cells, CD31+ endothelial cells, αSMA+ cancer associated fibroblasts, Ki67+ cells, cleaved caspase-3+ cells, collagen-1, and hyaluronan, were done by immunohistochemistry (IHC)-immunofluorescence (IF) staining of frozen tumor tissues with appropriate antibodies and imaging with multispectral confocal microscopy. Quantification and further data analysis were performed using a custom MATLAB program designed by Dr. Mei Rosa Ng. Gaining understanding of these stromal compositions will allow for better utilization of these breast cancer mouse models in future experiments.2019-10-3

The role of seaports in regional employment: evidence from South Korea

<p>The role of seaports in regional employment: evidence from South Korea. <i>Regional Studies</i>. This study examines the seaport’s influence on regional employment in all 16 regions of Korea, including seven metropolitan areas, based on panel data between 2002 and 2013. It expands an economic model of regional unemployment from labour economics and an autoregressive model from econometrics by employing port potentials separately estimated in a Tobit model. The result indicates that port activities significantly reduce regional unemployment rates relative to the national level. The role of population, gross domestic product (GDP) and household income on unemployment rate was highlighted, whilst various determinants of port potentials were investigated about whether they stimulate port potentials.</p

Flexible margin-based classification techniques

Classification is a very useful statistical tool for information extraction. Among numerous classification methods, margin-based classification techniques have attracted a lot of attention. It can be typically expressed as a general minimization problem in the form of $loss + penalty$, where the loss function controls goodness of fit of the training data and the penalty term enforces smoothness of the model. Since the loss function decides how functional margins affect the resulting margin-based classifier, one can modify the existing loss functions to obtain classifiers with desirable properties. In this research, we design several new margin-based classifiers, via modifying loss functions of two well-known classifiers, Penalized Logistic Regression (PLR) and the Support Vector Machine (SVM). In particular, we propose three new binary classification techniques, Robust Penalized Logistic Regression (RPLR), Bounded Constraint Machine (BCM), and the Balancing Support Vector Machine (BSVM). For multicategory case, we propose the multicagegory Composite Least Squares (CLS) classifier, a new multicategory classifier based on the squared loss function. We study properties of the new methods and provide efficient computational algorithms. Simulated and microarray gene expression data analysis examples are used to demonstrate competitive performance of the proposed methods

On the effect of the East/Japan Sea SST variability on the North Pacific atmospheric circulation in a regional climate model

Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Atmospheres 119 (2014): 418–444, doi:10.1002/2013JD020523.The East/Japan Sea (EJS) is a semi-enclosed marginal sea located in the upstream of the North Pacific storm track, where the leading modes of wintertime interannual variability in sea surface temperature (SST) are characterized by the basin-wide warming-cooling and the northeast-southwest dipole. Processes leading to local and remote atmospheric responses to these SST anomalies are investigated using the Weather Research and Forecast (WRF) model. The atmosphere in direct contact with anomalous diabatic forcing exhibits a linear and symmetric response with respect to the sign, pattern, and magnitude of SST anomalies, producing increased (decreased) wind speed and precipitation response over warm (cold) SSTs. This local response is due to modulation of both the vertical stability of the marine atmospheric boundary layer and the adjustment of sea level pressure, although the latter provides a better explanation of the quadrature relationship between SST and wind speed. The linearity in the local response suggests the importance of fine-scale EJS SSTs to predictability of the regional weather and climate variability. The remote circulation response, in contrast, is strongly nonlinear. An intraseasonal equivalent barotropic ridge emerges in the Gulf of Alaska as a common remote response independent of EJS SST anomalies. This downstream blocking response is reinforced by the enhanced storm track variability east of Japan via transient eddy vorticity flux convergence. Strong nonlinearity in remote response implies that detailed EJS SST patterns may not be critical to this downstream ridge response. Overall, results demonstrate a remarkably far-reaching impact of the EJS SSTs on the atmospheric circulation.H.S. gratefully acknowledges the support from the Penzance Endowed Fund in support of Assistant Scientists at WHOI. Y.-O.K. acknowledges NSF Climate and Large-Scale Dynamics program (AGS-1035423). H.S. and Y.-O.K. also thank NASA grant (NNX13AM59G)