Quantitative Proteomic Analysis of Human Embryonic Stem Cell Differentiation by 8-Plex iTRAQ Labelling

Analysis of gene expression to define molecular mechanisms and pathways involved in human embryonic stem cells (hESCs) proliferation and differentiations has allowed for further deciphering of the self-renewal and pluripotency characteristics of hESC. Proteins associated with hESCs were discovered through isobaric tags for relative and absolute quantification (iTRAQ). Undifferentiated hESCs and hESCs in different stages of spontaneous differentiation by embryoid body (EB) formation were analyzed. Using the iTRAQ approach, we identified 156 differentially expressed proteins involved in cell proliferation, apoptosis, transcription, translation, mRNA processing, and protein synthesis. Proteins involved in nucleic acid binding, protein synthesis, and integrin signaling were downregulated during differentiation, whereas cytoskeleton proteins were upregulated. The present findings added insight to our understanding of the mechanisms involved in hESC proliferation and differentiation

Fully Bayesian field slam using Gaussian Markov random fields

This paper presents a fully Bayesian way to solve the simultaneous localization and spatial prediction problem using a Gaussian Markov random field (GMRF) model. The objective is to simultaneously localize robotic sensors and predict a spatial field of interest using sequentially collected noisy observations by robotic sensors. The set of observations consists of the observed noisy positions of robotic sensing vehicles and noisy measurements of a spatial field. To be flexible, the spatial field of interest is modeled by a GMRF with uncertain hyperparameters. We derive an approximate Bayesian solution to the problem of computing the predictive inferences of the GMRF and the localization, taking into account observations, uncertain hyperparameters, measurement noise, kinematics of robotic sensors, and uncertain localization. The effectiveness of the proposed algorithm is illustrated by simulation results as well as by experiment results. The experiment results successfully show the flexibility and adaptability of our fully Bayesian approach in a data-driven fashion.Huan N. Do, Mahdi Jadaliha, Mehmet Temel, and Jongeun Cho

Feature selection for position estimation using an omnidirectional camera

This paper considers visual feature selection to implement position estimation using an omnidirectional camera. The localization is based on a maximum likelihood estimation (MLE) with a map from optimally selected visual features using Gaussian process (GP) regression. In particular, the collection of selected features over a surveillance region is modeled by a multivariate GP with unknown hyperparameters. The hyperparameters are identified through the learning process by an MLE, which are used for prediction in an empirical Bayes fashion. To select features, we apply a backward sequential elimination technique in order to improve the quality of the position estimation with compressed features for efficient localization. The excellent results of the proposed algorithm are illustrated by the experimental studies with different visual features under both indoor and outdoor real-world scenarios.Huan N. Do, Mahdi Jadaliha, Jongeun Choi, Chae Young Li

A natural antisense lncRNA controls breast cancer progression by promoting tumor suppressor gene mRNA stability.

The human genome encodes thousands of long noncoding RNA (lncRNA) genes; the function of majority of them is poorly understood. Aberrant expression of a significant number of lncRNAs is observed in various diseases, including cancer. To gain insights into the role of lncRNAs in breast cancer progression, we performed genome-wide transcriptome analyses in an isogenic, triple negative breast cancer (TNBC/basal-like) progression cell lines using a 3D cell culture model. We identified significantly altered expression of 1853 lncRNAs, including ~500 natural antisense transcript (NATs) lncRNAs. A significant number of breast cancer-deregulated NATs displayed co-regulated expression with oncogenic and tumor suppressor protein-coding genes in cis. Further studies on one such NAT, PDCD4-AS1 lncRNA reveal that it positively regulates the expression and activity of the tumor suppressor PDCD4 in mammary epithelial cells. Both PDCD4-AS1 and PDCD4 show reduced expression in TNBC cell lines and in patients, and depletion of PDCD4-AS1 compromised the cellular levels and activity of PDCD4. Further, tumorigenic properties of PDCD4-AS1-depleted TNBC cells were rescued by exogenous expression of PDCD4, implying that PDCD4-AS1 acts upstream of PDCD4. Mechanistically, PDCD4-AS1 stabilizes PDCD4 RNA by forming RNA duplex and controls the interaction between PDCD4 RNA and RNA decay promoting factors such as HuR. Our studies demonstrate crucial roles played by NAT lncRNAs in regulating post-transcriptional gene expression of key oncogenic or tumor suppressor genes, thereby contributing to TNBC progression

A Fresh look at the male-specific region of the human Y chromosome

The Chromosome-centric Human Proteome Project (C-HPP) aims to systematically map the entire human proteome with the intent to enhance our understanding of human biology at the cellular level. This project attempts simultaneously to establish a sound basis for the development of diagnostic, prognostic, therapeutic, and preventive medical applications. In Iran, current efforts focus on mapping the proteome of the human Y chromosome. The male-specific region of the Y chromosome (MSY) is unique in many aspects and comprises 95% of the chromosome's length. The MSY continually retains its haploid state and is full of repeated sequences. It is responsible for important biological roles such as sex determination and male fertility. Here, we present the most recent update of MSY protein-encoding genes and their association with various traits and diseases including sex determination and reversal, spermatogenesis and male infertility, cancers such as prostate cancers, sex-specific effects on the brain and behavior, and graft-versus-host disease. We also present information available from RNA sequencing, protein-protein interaction, post-translational modification of MSY protein-coding genes and their implications in biological systems. An overview of Human Y chromosome Proteome Project is presented and a systematic approach is suggested to ensure that at least one of each predicted protein-coding gene's major representative proteins will be characterized in the context of its major anatomical sites of expression, its abundance, and its functional relevance in a biological and/or medical context. There are many technical and biological issues that will need to be overcome in order to accomplish the full scale mapping.17 page(s