Angiotensin-(1-7) and angiotensin-(1-9): function in cardiac and vascular remodeling

The renin angiotensin system (RAS) is integral to cardiovascular physiology, however, dysregulation of this system largely contributes to the pathophysiology of cardiovascular disease (CVD). It is well established that angiotensin II (Ang II), the main effector of the RAS, engages the angiotensin type 1 receptor and promotes cell growth, proliferation, migration and oxidative stress, all processes which contribute to remodeling of the heart and vasculature, ultimately leading to the development and progression of various CVDs including heart failure and atherosclerosis. The counter-regulatory axis of the RAS, which is centered on the actions of angiotensin converting enzyme 2 (ACE2) and the resultant production of angiotensin-(1-7) (Ang-(1-7) from Ang II, antagonizes the actions of Ang II via the receptor Mas, thereby providing a protective role in CVD. More recently, another ACE2 metabolite, Ang-(1-9), has been reported to be a biologically active peptide within the counter-regulatory axis of the RAS. This review will discuss the role of the counter-regulatory RAS peptides, Ang-(1-7) and Ang-(1-9) in the cardiovascular system, with a focus on their effects in remodeling of the heart and vasculature

Statistical Learning Methods for High-dimensional Classification and Regression

With the recent advancement of technology, large and heterogeneous data containing enormous variables of mixed types have become increasingly popular, great challenges in computation and theory have arisen for classical methods in classification and regression. It is of great interest to develop new statistical methods that are computationally efficient and theoretically sound for classification and regression using high-dimensinoal and heterogeneous data. In this dissertation, we specifically address the problems in the computation of high-dimensional linear discriminant analysis, and in high-dimensional linear regression and ordinal classification with mixed covariates. First, we propose an efficient greedy search algorithm that depends solely on closed-form formulae to learn a high-dimensional linear discriminant analysis (LDA) rule. We establish theoretical guarantee of its statistical properties in terms of variable selection and error rate consistency; in addition, we provide an explicit interpretation of the extra information brought by an additional feature in a LDA problem under some mild distributional assumptions. We demonstrate that this new algorithm drastically improves computational speed compared with other high-dimensional LDA methods, while maintaining comparable or even better classification performance through extensive simulation studies and real data analysis. Second, we propose a semiparametric Latent Mixed Gaussian Copula Regression (LMGCR) model to perform linear regression for high-dimensional mixed data. The model assumes that the observed mixed covariates are generated from latent variables that follow the Gaussian copula. We develop an estimator of the regression coefficients in LMGCR and prove its estimation and variable selection consistency. In addition, we devise a prediction rule given by LMGCR and quantify its prediction error under mild conditions. We demonstrate that the proposed model has superior performance in both coefficient estimation and prediction through extensive simulation studies and real data analysis. Finally, we propose a semiparametric Latent Mixed Gaussian Copula Classification (LMGCC)rule to perform classification of ordinal response using unnormalized high-dimensional data. Our clas- sification rule learns the Bayes rule derived from joint modeling of ordinal response and continuous features through a latent Gaussian copula model. We develop an estimator of the regression coeffi- cients in predicting the latent response and prove its estimation and variable selection consistency. In addition, we establish that our devised LMGCC has error rate consistency. We demonstrate that the proposed method has superior performance in ordinal classification through extensive simulation studies and real data analysis.Doctor of Philosoph

An Efficient Greedy Search Algorithm for High-dimensional Linear Discriminant Analysis.

High-dimensional classification is an important statistical problem that has applications in many areas. One widely used classifier is the Linear Discriminant Analysis (LDA). In recent years, many regularized LDA classifiers have been proposed to solve the problem of high-dimensional classification. However, these methods rely on inverting a large matrix or solving large-scale optimization problems to render classification rules-methods that are computationally prohibitive when the dimension is ultra-high. With the emergence of big data, it is increasingly important to develop more efficient algorithms to solve the high-dimensional LDA problem. In this paper, we propose an efficient greedy search algorithm that depends solely on closed-form formulae to learn a high-dimensional LDA rule. We establish theoretical guarantee of its statistical properties in terms of variable selection and error rate consistency; in addition, we provide an explicit interpretation of the extra information brought by an additional feature in a LDA problem under some mild distributional assumptions. We demonstrate that this new algorithm drastically improves computational speed compared with other high-dimensional LDA methods, while maintaining comparable or even better classification performance

The identification of a novel role for BRCA1 in regulating RNA Polymerase I transcription

The unrestrained proliferation of cancer cells requires a high level of ribosome biogenesis. The first stage of ribosome biogenesis is the transcription of the large ribosomal RNAs (rRNAs); the structural and functional components of the ribosome. Transcription of rRNA is carried out by RNA polymerase I (Pol-I) and its associated holoenzyme complex. Here we report that BRCA1, a nuclear phosphoprotein, and a known tumour suppressor involved in variety of cellular processes such as DNA damage response, transcriptional regulation, cell cycle control and ubiquitylation, is associated with rDNA repeats, in particular with the regulatory regions of the rRNA gene. We demonstrate that BRCA1 interacts directly with the basal Pol-I transcription factors; upstream binding factor (UBF), selectivity factor-1 (SL1) as well as interacting with RNA Pol-I itself. We show that in response to DNA damage, BRCA1 occupancy at the rDNA repeat is decreased and the observed BRCA1 interactions with the Pol-I transcription machinery are weakened. We propose, therefore, that there is a rDNA associated fraction of BRCA1 involved in DNA damage dependent regulation of Pol-I transcription, regulating the stability and formation of the Pol-I holoenzyme during initiation and/or elongation in response to DNA damage

Novel essential amino acid supplements enriched with L-leucine facilitate increased protein and energy intakes in older women: a randomised controlled trial

Background: Inadequate protein intake (PI), containing a sub-optimal source of essential amino acids (EAAs), and reduced appetite are contributing factors to age-related sarcopenia. The satiating effects of dietary protein per se may negatively affect energy intake (EI), thus there is a need to explore alternative strategies to facilitate PI without compromising appetite and subsequent EI. Methods: Older women completed two experiments (EXP1 and EXP2) where they consumed either a Bar (565 kJ), a Gel (477 kJ), both rich in EAAs (7.5 g, 40% L-leucine), or nothing (Control). In EXP1, participants (n=10, 68±5 years, mean±SD) consumed Bar, Gel or Control with appetite sensations and appetite-related hormonal responses monitored for one hour, followed by consumption of an ad libitum breakfast (ALB). In EXP2, participants (n=11, 69±5 years) ingested Bar, Gel or Control alongside an ALB. Results: In EXP1, EI at ALB was not different (P=0.674) between conditions (1179±566, 1254±511, 1206±550 kJ for the Control, Bar, and Gel respectively). However, total EI was significantly higher in the Bar and Gel compared to the Control after accounting for the energy content of the supplements (P<0.0005). Analysis revealed significantly higher appetite Area under the Curve (AUC) (P<0.007), a tendency for higher acylated ghrelin AUC (P=0.087), and significantly lower pancreatic polypeptide AUC (P=0.02) in the Control compared with the Bar and Gel. In EXP2, EI at ALB was significantly higher (P=0.028) in the Control (1282±513 kJ) compared to the Bar (1026±565 kJ) and Gel (1064±495 kJ). However, total EI was significantly higher in the Bar and Gel after accounting for the energy content of the supplements (P<0.007). Conclusions: Supplementation with either the Bar or Gel increased total energy intake whether consumed one hour before or during breakfast. This may represent an effective nutritional means for addressing protein and total energy deficiencies in older women

The Arab world's contribution to solid waste literature: a bibliometric analysis

BACKGROUND: Environmental and health-related effects of solid waste material are considered worldwide problems. The aim of this study was to assess the volume and impact of Arab scientific output published in journals indexed in the Science Citation Index (SCI) on solid waste. METHODS: We included all the documents within the SCI whose topic was solid waste from all previous years up to 31 December 2012. In this bibliometric analysis we sought to evaluate research that originated from Arab countries in the field of solid waste, as well as its relative growth rate, collaborative measures, productivity at the institutional level, and the most prolific journals. RESULTS: A total of 382 (2.35 % of the overall global research output in the field of solid waste) documents were retrieved from the Arab countries. The annual number of documents published in the past three decades (1982–2012) indicated that research productivity demonstrated a noticeable rise during the last decade. The highest number of articles associated with solid waste was that of Egypt (22.8 %), followed by Tunisia (19.6), and Jordan (13.4 %). the total number of citations over the analysed years at the date of data collection was 4,097, with an average of 10.7 citations per document. The h-index of the citing articles was 31. Environmental science was the most researched topic, represented by 175 (45.8 %) articles. Waste Management was the top active journal. The study recognized 139 (36.4 %) documents from collaborations with 25 non-Arab countries. Arab authors mainly collaborated with countries in Europe (22.5 %), especially France, followed by countries in the Americas (9.4 %), especially the USA. The most productive institution was the American University of Beirut, Lebanon, with 6.3 % of total publications. CONCLUSIONS: Despite the expected increase in solid waste production from Arab world, research activity about solid waste is still low. Governments must invest more in solid waste research to avoid future unexpected problems. Finally, since solid waste is a multidisciplinary science, research teams in engineering, health, toxicology, environment, geology and others must be formulated to produce research in solid waste from different scientific aspects

Design, fabrication and control of soft robots

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.National Science Foundation (U.S.) (Grant IIS-1226883

Genome-wide analyses identify common variants associated with macular telangiectasia type 2

Idiopathic juxtafoveal retinal telangiectasis type 2 (macular telangiectasia type 2; MacTel) is a rare neurovascular degenerative retinal disease. To identify genetic susceptibility loci for MacTel, we performed a genome-wide association study (GWAS) with 476 cases and 1,733 controls of European ancestry. Genome-wide significant associations (P < 5 × 10−8) were identified at three independent loci (rs73171800 at 5q14.3, P = 7.74 × 10−17; rs715 at 2q34, P = 9.97 × 10−14; rs477992 at 1p12, P = 2.60 × 10−12) and then replicated (P < 0.01) in an independent cohort of 172 cases and 1,134 controls. The 5q14.3 locus is known to associate with variation in retinal vascular diameter, and the 2q34 and 1p12 loci have been implicated in the glycine/serine metabolic pathway. We subsequently found significant differences in blood serum levels of glycine (P = 4.04 × 10−6) and serine (P = 2.48 × 10−4) between MacTel cases and controls