Multiprocessor Approximate Message Passing with Column-Wise Partitioning

Solving a large-scale regularized linear inverse problem using multiple processors is important in various real-world applications due to the limitations of individual processors and constraints on data sharing policies. This paper focuses on the setting where the matrix is partitioned column-wise. We extend the algorithmic framework and the theoretical analysis of approximate message passing (AMP), an iterative algorithm for solving linear inverse problems, whose asymptotic dynamics are characterized by state evolution (SE). In particular, we show that column-wise multiprocessor AMP (C-MP-AMP) obeys an SE under the same assumptions when the SE for AMP holds. The SE results imply that (i) the SE of C-MP-AMP converges to a state that is no worse than that of AMP and (ii) the asymptotic dynamics of C-MP-AMP and AMP can be identical. Moreover, for a setting that is not covered by SE, numerical results show that damping can improve the convergence performance of C-MP-AMP.Comment: This document contains complete details of the previous version (i.e., arXiv:1701.02578v1), which was accepted for publication in ICASSP 201

Does Haze Removal Help CNN-based Image Classification?

Hazy images are common in real scenarios and many dehazing methods have been developed to automatically remove the haze from images. Typically, the goal of image dehazing is to produce clearer images from which human vision can better identify the object and structural details present in the images. When the ground-truth haze-free image is available for a hazy image, quantitative evaluation of image dehazing is usually based on objective metrics, such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM). However, in many applications, large-scale images are collected not for visual examination by human. Instead, they are used for many high-level vision tasks, such as automatic classification, recognition and categorization. One fundamental problem here is whether various dehazing methods can produce clearer images that can help improve the performance of the high-level tasks. In this paper, we empirically study this problem in the important task of image classification by using both synthetic and real hazy image datasets. From the experimental results, we find that the existing image-dehazing methods cannot improve much the image-classification performance and sometimes even reduce the image-classification performance

AutoNet-generated deep layer-wise convex networks for ECG classification

The design of neural networks typically involves trial-and-error, a time-consuming process for obtaining an optimal architecture, even for experienced researchers. Additionally, it is widely accepted that loss functions of deep neural networks are generally non-convex with respect to the parameters to be optimised. We propose the Layer-wise Convex Theorem to ensure that the loss is convex with respect to the parameters of a given layer, achieved by constraining each layer to be an overdetermined system of non-linear equations. Based on this theorem, we developed an end-to-end algorithm (the AutoNet) to automatically generate layer-wise convex networks (LCNs) for any given training set. We then demonstrate the performance of the AutoNet-generated LCNs (AutoNet-LCNs) compared to state-of-the-art models on three electrocardiogram (ECG) classification benchmark datasets, with further validation on two non-ECG benchmark datasets for more general tasks. The AutoNet-LCN was able to find networks customised for each dataset without manual fine-tuning under 2 GPU-hours, and the resulting networks outperformed the state-of-the-art models with fewer than 5% parameters on all the above five benchmark datasets. The efficiency and robustness of the AutoNet-LCN markedly reduce model discovery costs and enable efficient training of deep learning models in resource-constrained settings

An In Vivo Screen Identifies PYGO2 as a Driver for Metastatic Prostate Cancer

Advanced prostate cancer displays conspicuous chromosomal instability and rampant copy number aberrations, yet the identity of functional drivers resident in many amplicons remain elusive. Here, we implemented a functional genomics approach to identify new oncogenes involved in prostate cancer progression. Through integrated analyses of focal amplicons in large prostate cancer genomic and transcriptomic datasets as well as genes upregulated in metastasis, 276 putative oncogenes were enlisted into an in vivo gain-of-function tumorigenesis screen. Among the top positive hits, we conducted an in-depth functional analysis on Pygopus family PHD finger 2 (PYGO2), located in the amplicon at 1q21.3. PYGO2 overexpression enhances primary tumor growth and local invasion to draining lymph nodes. Conversely, PYGO2 depletion inhibits prostate cancer cell invasion in vitro and progression of primary tumor and metastasis in vivo In clinical samples, PYGO2 upregulation associated with higher Gleason score and metastasis to lymph nodes and bone. Silencing PYGO2 expression in patient-derived xenograft models impairs tumor progression. Finally, PYGO2 is necessary to enhance the transcriptional activation in response to ligand-induced Wnt/β-catenin signaling. Together, our results indicate that PYGO2 functions as a driver oncogene in the 1q21.3 amplicon and may serve as a potential prognostic biomarker and therapeutic target for metastatic prostate cancer.Significance: Amplification/overexpression of PYGO2 may serve as a biomarker for prostate cancer progression and metastasis. Cancer Res; 78(14); 3823-33. ©2018 AACR

Integrated phylogenomic analyses unveil reticulate evolution in Parthenocissus (Vitaceae), highlighting speciation dynamics in the Himalayan–Hengduan Mountains

Hybridization caused by frequent environmental changes can lead both to species diversification (speciation) and to speciation reversal (despeciation), but the latter has rarely been demonstrated. Parthenocissus, a genus with its trifoliolate lineage in the Himalayan-Hengduan Mountains (HHM) region showing perplexing phylogenetic relationships, provides an opportunity for investigating speciation dynamics based on integrated evidence.We investigated phylogenetic discordance and reticulate evolution in Parthenocissus based on rigorous analyses of plastome and transcriptome data. We focused on reticulations in the trifoliolate lineage in the HHM region using a population-level genome resequencing dataset, incorporating evidence from morphology, distribution, and elevation.Comprehensive analyses confirmed multiple introgressions within Parthenocissus in a robust temporal-spatial framework. Around the HHM region, at least three hybridization hot spots were identified, one of which showed evidence of ongoing speciation reversal.We present a solid case study using an integrative methodological approach to investigate reticulate evolutionary history and its underlying mechanisms in plants. It demonstrates an example of speciation reversal through frequent hybridizations in the HHM region, which provides new perspectives on speciation dynamics in mountainous areas with strong topographic and environmental heterogeneity.info:eu-repo/semantics/publishedVersio

PPAR-α Agonist Fenofibrate Upregulates Tetrahydrobiopterin Level through Increasing the Expression of Guanosine 5′-Triphosphate Cyclohydrolase-I in Human Umbilical Vein Endothelial Cells

Tetrahydrobiopterin (BH4) is an essential cofactor for endothelial nitric oxide (NO) synthase. Guanosine 5′-triphosphate cyclohydrolase-I (GTPCH-I) is a key limiting enzyme for BH4 synthesis. In the present in vitro study, we investigated whether peroxisome proliferator-activated receptor α (PPAR-α) agonist fenofibrate could recouple eNOS by reversing low-expression of intracellular BH4 in endothelial cells and discussed the potential mechanisms. After human umbilical vein endothelial cells (HUVECs) were treated with lipopolysaccharide (LPS) for 24 hours, the levels of cellular eNOS, BH4 and cell supernatant NO were significantly reduced compared to control group. And the fluorescence intensity of intracellular ROS was significantly increased. But pretreated with fenofibrate (10 umol/L) for 2 hours before cells were induced by LPS, the levels of eNOS, NO, and BH4 were significantly raised compared to LPS treatment alone. ROS production was markedly reduced in fenofibrate group than LPS group. In addition, our results showed that the level of intracellular GTPCH-I detected by western blot was increased in a concentration-dependent manner after being treated with fenofibrate. These results suggested that fenofibrate might help protect endothelial function and against atherosclerosis by increasing level of BH4 and decreasing production of ROS through upregulating the level of intracellular GTPCH-I

Identification of a putative competitive endogenous RNA network for lung adenocarcinoma using TCGA datasets

The mechanisms underlying the oncogenesis and progression of lung adenocarcinoma (LUAD) are currently unclear. The discovery of competitive endogenous RNA (ceRNA) regulatory networks has provided a new direction for the treatment and prognosis of patients with LUAD. However, the mechanism of action of ceRNA in LUAD remains elusive. In the present study, differentially expressed mRNAs, microRNAs (miRs) and long non-coding RNAs from the cancer genome atlas database were screened. CeRNAs for LUAD were then identified using online prediction software. Among the ceRNAs identified, family with sequence similarity 83 member A (FAM83A), miR-34c-5p, KCNQ1OT1 and FLJ26245 were observed to be significantly associated with the overall survival of patients with LUAD. Of note, FAM83A has potential significance in drug resistance, and may present a candidate biomarker for the prognosis and treatment of patients with LUAD

Effective combinatorial immunotherapy for penile squamous cell carcinoma

Penile squamous cell carcinoma (PSCC) accounts for over 95% of penile malignancies and causes significant mortality and morbidity in developing countries. Molecular mechanisms and therapies of PSCC are understudied, owing to scarcity of laboratory models. Herein, we describe a genetically engineered mouse model of PSCC, by co-deletion of Smad4 and Apc in the androgen-responsive epithelium of the penis. Mouse PSCC fosters an immunosuppressive microenvironment with myeloid-derived suppressor cells (MDSCs) as a dominant population. Preclinical trials in the model demonstrate synergistic efficacy of immune checkpoint blockade with the MDSC-diminishing drugs cabozantinib or celecoxib. A critical clinical problem of PSCC is chemoresistance to cisplatin, which is induced by Pten deficiency on the backdrop of Smad4/Apc co-deletion. Drug screen studies informed by targeted proteomics identify a few potential therapeutic strategies for PSCC. Our studies have established what we believe to be essential resources for studying PSCC biology and developing therapeutic strategies