Concurrent Application Bias Scheduling for Energy Efficiency of Heterogeneous Multi-Core platforms

Minimizing energy consumption of concurrent applications on heterogeneous multi-core platforms is challenging given the diversity in energy-performance profiles of both the applications and hardware. Adaptive learning techniques made the exhaustive Pareto-optimal space exploration practically feasible to identify an energy-efficient configuration. The existing approaches consider a single application's characteristic for optimizing energy consumption. However, an optimal configuration for a given single application may not be optimal when a new application arrives. Although some related works do consider concurrent applications scenarios, these approaches overlook the weight of total energy consumption per application, restricting those from prioritizing among applications. We address this limitation by considering the mutual effect of concurrent applications on system-wide energy consumption to adapt resource configuration at run-time. We characterize each application's power-performance profile as a weighted bias through off-line profiling. We infer this model combined with an on-line predictive strategy to make resource allocation decisions for minimizing energy consumption while honoring performance requirements. The proposed strategy is implemented as a user-space process and evaluated on a heterogeneous hardware platform of Odroid XU3 over the Rodinia benchmark suite. Experimental results show up to 61% of energy saving compared to the standard baseline of Linux governors and up to 27% of energy gain compared to state-of-the-art adaptive learning-based resource management techniques.</p

Digital Health-Enabled Community-Centered Care: Scalable Model to Empower Future Community Health Workers Using Human-in-the-Loop Artificial Intelligence

Digital health–enabled community-centered care (D-CCC) represents a pioneering vision for the future of community-centered care. D-CCC aims to support and amplify the digital footprint of community health workers through a novel artificial intelligence–enabled closed-loop digital health platform designed for, and with, community health workers. By focusing digitalization at the level of the community health worker, D-CCC enables more timely, supported, and individualized community health worker–delivered interventions. D-CCC has the potential to move community-centered care into an expanded, digitally interconnected, and collaborative community-centered health and social care ecosystem of the future, grounded within a robust and digitally empowered community health workforce.</p

Combining Network Modeling and Gene Expression Microarray Analysis to Explore the Dynamics of Th1 and Th2 Cell Regulation

Two T helper (Th) cell subsets, namely Th1 and Th2 cells, play an important role in inflammatory diseases. The two subsets are thought to counter-regulate each other, and alterations in their balance result in different diseases. This paradigm has been challenged by recent clinical and experimental data. Because of the large number of genes involved in regulating Th1 and Th2 cells, assessment of this paradigm by modeling or experiments is difficult. Novel algorithms based on formal methods now permit the analysis of large gene regulatory networks. By combining these algorithms with in silico knockouts and gene expression microarray data from human T cells, we examined if the results were compatible with a counter-regulatory role of Th1 and Th2 cells. We constructed a directed network model of genes regulating Th1 and Th2 cells through text mining and manual curation. We identified four attractors in the network, three of which included genes that corresponded to Th0, Th1 and Th2 cells. The fourth attractor contained a mixture of Th1 and Th2 genes. We found that neither in silico knockouts of the Th1 and Th2 attractor genes nor gene expression microarray data from patients with immunological disorders and healthy subjects supported a counter-regulatory role of Th1 and Th2 cells. By combining network modeling with transcriptomic data analysis and in silico knockouts, we have devised a practical way to help unravel complex regulatory network topology and to increase our understanding of how network actions may differ in health and disease

Regulation of Pax6 by CTCF during Induction of Mouse ES Cell Differentiation

Pax6 plays an important role in embryonic cell (ES) differentiation during embryonic development. Expression of Pax6 undergoes from a low level to high levels following ES cell differentiation to neural stem cells, and then fades away in most of the differentiated cell types. There is a limited knowledge concerning how Pax6 is regulated in ES cell differentiation. We report that Pax6 expression in mouse ES cells was controlled by CCCTC binding factor (CTCF) through a promoter repression mechanism. Pax6 expression was significantly enhanced while CTCF activity was kept in the constant during ES cell differentiation to radial glial cells. Instead, the interaction of CTCF with Pax6 gene was regulated by decreased CTCF occupancy in its binding motifs upstream from Pax6 P0 promoter following the course of ES cell differentiation. Reduced occupancy of CTCF in the binding motif region upstream from the P0 promoter was due to increased DNA methylations in the CpG sites identified in the region. Furthermore, changes in DNA methylation levels in vitro and in vivo effectively altered methylation status of these identified CpG sites, which affected ability of CTCF to interact with the P0 promoter, resulting in increases in Pax6 expression. We conclude that there is an epigenetic mechanism involving regulations of Pax6 gene during ES cell differentiation to neural stem cells, which is through increases or decreases in methylation levels of Pax6 gene to effectively alter the ability of CTCF in control of Pax6 expression, respectively

DNA Methylation Signatures Identify Biologically Distinct Subtypes in Acute Myeloid Leukemia

Abstract: We hypothesized that DNA methylation distributes into specific patterns in cancer cells, which reflect critical biological differences. We therefore examined the methylation profiles of 344 patients with acute myeloid leukemia (AML). Clustering of these patients by methylation data segregated patients into 16 groups. Five of these groups defined new AML subtypes that shared no other known feature. In addition, DNA methylation profiles segregated patients with CEBPA aberrations from other subtypes of leukemia, defined four epigenetically distinct forms of AML with NPM1 mutations, and showed that established AML1-ETO, CBFb-MYH11, and PML-RARA leukemia entities are associated with specific methylation profiles. We report a 15 gene methylation classifier predictive of overall survival in an independent patient cohort (p < 0.001, adjusted for known covariates)

The Insulator Binding Protein CTCF Positions 20 Nucleosomes around Its Binding Sites across the Human Genome

Chromatin structure plays an important role in modulating the accessibility of genomic DNA to regulatory proteins in eukaryotic cells. We performed an integrative analysis on dozens of recent datasets generated by deep-sequencing and high-density tiling arrays, and we discovered an array of well-positioned nucleosomes flanking sites occupied by the insulator binding protein CTCF across the human genome. These nucleosomes are highly enriched for the histone variant H2A.Z and 11 histone modifications. The distances between the center positions of the neighboring nucleosomes are largely invariant, and we estimate them to be 185 bp on average. Surprisingly, subsets of nucleosomes that are enriched in different histone modifications vary greatly in the lengths of DNA protected from micrococcal nuclease cleavage (106–164 bp). The nucleosomes enriched in those histone modifications previously implicated to be correlated with active transcription tend to contain less protected DNA, indicating that these modifications are correlated with greater DNA accessibility. Another striking result obtained from our analysis is that nucleosomes flanking CTCF sites are much better positioned than those downstream of transcription start sites, the only genomic feature previously known to position nucleosomes genome-wide. This nucleosome-positioning phenomenon is not observed for other transcriptional factors for which we had genome-wide binding data. We suggest that binding of CTCF provides an anchor point for positioning nucleosomes, and chromatin remodeling is an important component of CTCF function

Distinct Methylation Changes at the IGF2-H19 Locus in Congenital Growth Disorders and Cancer

Background: Differentially methylated regions (DMRs) are associated with many imprinted genes. In mice methylation at a DMR upstream of the H19 gene known as the Imprint Control region (IC1) is acquired in the male germline and influences the methylation status of DMRs 100 kb away in the adjacent Insulin-like growth factor 2 (Igf2) gene through long-range interactions. In humans, germline-derived or post-zygotically acquired imprinting defects at IC1 are associated with aberrant activation or repression of IGF2, resulting in the congenital growth disorders Beckwith-Wiedemann (BWS) and Silver-Russell (SRS) syndromes, respectively. In Wilms tumour and colorectal cancer, biallelic expression of IGF2 has been observed in association with loss of methylation at a DMR in IGF2. This DMR, known as DMR0, has been shown to be methylated on the silent maternal IGF2 allele presumably with a role in repression. The effect of IGF2 DMR0 methylation changes in the aetiology of BWS or SRS is unknown. Methodology/Principal Findings: We analysed the methylation status of the DMR0 in BWS, SRS and Wilms tumour patients by conventional bisulphite sequencing and pyrosequencing. We show here that, contrary to previous reports, the IGF2 DMR0 is actually methylated on the active paternal allele in peripheral blood and kidney. This is similar to the IC

A Non-Coding RNA Within the Rasgrf1 Locus in Mouse Is Imprinted and Regulated by Its Homologous Chromosome in Trans

BACKGROUND: Rasgrf1 is imprinted in mouse, displaying paternal allele specific expression in neonatal brain. Paternal expression is accompanied by paternal-specific DNA methylation at a differentially methylated domain (DMD) within the locus. The cis-acting elements necessary for Rasgrf1 imprinting are known. A series of tandem DNA repeats control methylation of the adjacent DMD, which is a methylation sensitive enhancer-blocking element. These two sequences constitute a binary switch that controls imprinting and represents the Imprinting Control Region (ICR). One paternally transmitted mutation, which helped define the ICR, induced paramutation, in trans, on the maternal allele. Like many imprinted genes, Rasgrf1 lies within an imprinted cluster. One of four noncoding transcripts in the cluster, AK015891, is known to be imprinted. METHODOLOGY/PRINCIPAL FINDINGS: Here we demonstrate that an additional noncoding RNA, AK029869, is imprinted and paternally expressed in brain throughout development. Intriguingly, any of several maternally inherited ICR mutations affected expression of the paternal AK029869 transcript in trans. Furthermore, we found that the ICR mutations exert different trans effects on AK029869 at different developmental times. CONCLUSIONS/SIGNIFICANCE: Few trans effects have been defined in mammals and, those that exist, do not show the great variation seen at the Rasgrf1 imprinted domain, either in terms of the large number of mutations that produce the effects or the range of phenotypes that emerge when they are seen. These results suggest that trans regulation of gene expression may be more common than originally appreciated and that where trans regulation occurs it can change dynamically during development