Robust Multivariate Regression

A robust multivariate linear regression estimator can be obtained by replacing the least squares estimator with the robust hbreg estimator. Then the robust multivariate linear regression estimator is asymptotically equivalent to the classical multivariate linear regression estimator since the probability that the robust estimator is equal to the classical estimator goes to one in probability as the sample size n tends to infinity for a large class of iid zero mean error distributions. This paper discusses the robust estimator and some tests using the robust estimator that are asymptotically equivalent to those using the classical estimator

Employee Recruitment: Question Formation for Employment Interviews based on Facial Cue Analytics

AbstractPrior research works have revealed that a relationship lies between a gainful interviewee and facial cues exhibited during the interview process. This study is focused on the formation of the questions to examine the interviewee which will use nonverbal behavioral cues presented. From nonverbal behavioral factors, ‘Facial expression variation’ was taken into the consideration with the assistance of a facial expression analysis tool. As such, this research proposes a novel approach in question formation for the assessment of interviewees. In the data collection and analysis phases of the study, qualitative and quantitative approaches have been followed. These approaches were used to identify the personality traits required in the IT related recruitments and to identify the traits that employed IT personnel already possess. Mock interviews were conducted to identify the valid questions that show a high sensitivity with facial expression variations while a tool was used to extract facial cues of the candidates. Seven primary emotions were captured with this approach during the interview. The facial emotions of joy, anger, contempt, disgust, fear, sadness, surprise were identified during the interview period which provided the percentage values for the emotional engagement of the candidate. Based on the video analytics, five questions were reported with a high emotional engagement values, three with an average variation level and remaining did not have a significant variance in candidate responses. During the final phase of this research, a cross reference analysis was conducted. For this analysis, data sets of emotional engagement were cross checked against the rankings given by the human raters regarding the extent of the question and response in total helped them to take the hiring decision. The evaluation of the results was done by comparing the result set obtained through video analytics with Human Rater result set obtained. Therefore, this research study and its suggested scientific approaches would assist the recruiters with identifying the set of questions which affect the recruitment decisions of their organizations in future.Keywords: Employment Interviews, Question Formation, Facial Expression Analysis, Nonverbal Behavioral Patterns, Personality Trait

Quercetin 3-Glucoside Protects Neuroblastoma (SH-SY5Y) Cells in Vitro against Oxidative Damage by Inducing Sterol Regulatory Element-binding Protein-2-mediated Cholesterol Biosynthesis

The flavonoid quercetin 3-glucoside (Q3G) protected SH-SY5Y, HEK293, and MCF-7 cells against hydrogen peroxide-induced oxidative stress. cDNA microarray studies suggested that Q3G-pretreated cells subjected to oxidative stress up-regulate the expression of genes associated with lipid and cholesterol biosynthesis. Q3G pretreatment elevated both the expression and activation of sterol regulatory element-binding protein-2 (SREBP-2) only in SH-SY5Y cells subjected to oxidative stress. Inhibition of SREBP-2 expression by small interfering RNA or small molecule inhibitors of 2,3-oxidosqualene:lanosterol cyclase or HMG-CoA reductase blocked Q3G-mediated cytoprotection in SH-SY5Y cells. By contrast, Q3G did not protect either HEK293 or MCF-7 cells via this signaling pathway. Moreover, the addition of isopentenyl pyrophosphate rescued SH-SY5Y cells from the inhibitory effect of HMG-CoA reductase inhibition. Last, Q3G pretreatment enhanced the incorporation of [(14)C]acetate into [(14)C]cholesterol in SH-SY5Y cells under oxidative stress. Taken together, these studies suggest a novel mechanism for flavonoid-induced cytoprotection in SH-SY5Y cells involving SREBP-2-mediated sterol synthesis that decreases lipid peroxidation by maintaining membrane integrity in the presence of oxidative stress

A Cell Permeable Peptide Targeting the Intracellular Loop 2 of Endothelin B Receptor Reduces Pulmonary Hypertension in a Hypoxic Rat Model

Cell permeable peptides (CPP) aid cellular uptake of targeted cargo across the hydrophobic plasma membrane. CPP-mediated cargo delivery of receptor signaling motifs provides an opportunity to regulate specific receptor initiated signaling cascades. Both endothelin-1 receptors, ETA and ETB, have been targets of antagonist therapies for individuals with pulmonary arterial hypertension (PAH). These therapies have had success but have been accompanied by adverse reactions. Also, unlike the CPP which target specific signaling cascades, the antagonists target the entire function of the receptor. Using the CPP strategy of biased antagonism of the ETB receptor’s intracellular loop 2 (ICB2), we demonstrate blunting of hypoxic pulmonary hypertension (HPH) in the rat, including indices of pulmonary arterial pressure, right ventricular hypertrophy and pulmonary vascular remodeling. Further, ex vivo analysis of the pulmonary artery treated with the IC2B peptide upon injection manifests marked reductions in Akt and ERK activation. Both kinases have been intimately related to cell proliferation and vascular contraction, the hallmarks of PAH. These observations in sum illustrate an involvement of the ETB receptor in HPH and furthermore provide a basis for a novel, CPP-based, strategy in the treatment of PAH, ultimately able to target not only ET-1, but also other factors involved in the development of PAH

Lipidomic profiling of adipose tissue reveals an inflammatory signature in cancer-related and primary Lymphedema

© 2016 Sedger et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Cancer-related and primary lymphedema (LE) are associated with the production of adipose tissue (AT). Nothing is known, however, about the lipid-based molecules that comprise LE AT. We therefore analyzed lipid molecules in lipoaspirates and serum obtained from LE patients, and compared them to lipoaspirates from cosmetic surgery patients and healthy control cohort serum. LE patient serum analysis demonstrated that triglycerides, HDL- and LDL-cholesterol and lipid transport molecules remained within the normal range, with no alterations in individual fatty acids. The lipidomic analysis also identified 275 lipid-based molecules, including triacylglycerides, diacylglycerides, fatty acids and phospholipids in AT oil and fat. Although the majority of lipid molecules were present in a similar abundance in LE and non-LE samples, there were several small changes: increased C20:5-containing triacylglycerides, reduced C10:0 caprinic and C24:1 nervonic acids. LE AT oil also contained a signature of increased cyclopropane-type fatty acids and inflammatory mediators arachidonic acid and ceramides. Interestingly C20:5 and C22:6 omega-3-type lipids are increased in LE AT, correlating with LE years. Hence, LE AT has a normal lipid profile containing a signature of inflammation and omega-3-lipids. It remains unclear, however, whether these differences reflect a small-scale global metabolic disturbance or effects within localised inflammatory foci

Cancer prevention and therapy through the modulation of the tumor microenvironment

Cancer arises in the context of an in vivo tumor microenvironment. This microenvironment is both a cause and consequence of tumorigenesis. Tumor and host cells co-evolve dynamically through indirect and direct cellular interactions, eliciting multiscale effects on many biological programs, including cellular proliferation, growth, and metabolism, as well as angiogenesis and hypoxia and innate and adaptive immunity. Here we highlight specific biological processes that could be exploited as targets for the prevention and therapy of cancer. Specifically, we describe how inhibition of targets such as cholesterol synthesis and metabolites, reactive oxygen species and hypoxia, macrophage activation and conversion, indoleamine 2,3-dioxygenase regulation of dendritic cells, vascular endothelial growth factor regulation of angiogenesis, fibrosis inhibition, endoglin, and Janus kinase signaling emerge as examples of important potential nexuses in the regulation of tumorigenesis and the tumor microenvironment that can be targeted. We have also identified therapeutic agents as approaches, in particular natural products such as berberine, resveratrol, onionin A, epigallocatechin gallate, genistein, curcumin, naringenin, desoxyrhapontigenin, piperine, and zerumbone, that may warrant further investigation to target the tumor microenvironment for the treatment and/or prevention of cancer

Applications of artificial intelligence to prostate multiparametric MRI (mpMRI): Current and emerging trends

Prostate carcinoma is one of the most prevalent cancers worldwide. Multiparametric magnetic resonance imaging (mpMRI) is a non-invasive tool that can improve prostate lesion detection, classification, and volume quantification. Machine learning (ML), a branch of artificial intelligence, can rapidly and accurately analyze mpMRI images. ML could provide better standardization and consistency in identifying prostate lesions and enhance prostate carcinoma management. This review summarizes ML applications to prostate mpMRI and focuses on prostate organ segmentation, lesion detection and segmentation, and lesion characterization. A literature search was conducted to find studies that have applied ML methods to prostate mpMRI. To date, prostate organ segmentation and volume approximation have been well executed using various ML techniques. Prostate lesion detection and segmentation are much more challenging tasks for ML and were attempted in several studies. They largely remain unsolved problems due to data scarcity and the limitations of current ML algorithms. By contrast, prostate lesion characterization has been successfully completed in several studies because of better data availability. Overall, ML is well situated to become a tool that enhances radiologists\u27 accuracy and speed