Reliability Assessment of Low-Power Processor Packages for Supercomputers

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Unleashing the full potential of Hsp90 inhibitors as cancer therapeutics through simultaneous inactivation of Hsp90, Grp94, and TRAP1

Cancer therapeutics: Extending a drug's reach A new drug that blocks heat shock proteins (HSPs), helper proteins that are co-opted by cancer cells to promote tumor growth, shows promise for cancer treatment. Several drugs have targeted HSPs, since cancer cells are known to hijack these helper proteins to shield themselves from destruction by the body. However, the drugs have had limited success. Hye-Kyung Park and Byoung Heon Kang at Ulsan National Institutes of Science and Technology in South Korea and coworkers noticed that the drugs were not absorbed into mitochondria, a key cellular compartment, and HSPs in this compartment were therefore not being blocked. They identified a new HSP inhibitor that can reach every cellular compartment and inhibit all HSPs. Testing in mice showed that this inhibitor effectively triggered death of tumor cells, and therefore shows promise for anti-cancer therapy. The Hsp90 family proteins Hsp90, Grp94, and TRAP1 are present in the cell cytoplasm, endoplasmic reticulum, and mitochondria, respectively; all play important roles in tumorigenesis by regulating protein homeostasis in response to stress. Thus, simultaneous inhibition of all Hsp90 paralogs is a reasonable strategy for cancer therapy. However, since the existing pan-Hsp90 inhibitor does not accumulate in mitochondria, the potential anticancer activity of pan-Hsp90 inhibition has not yet been fully examined in vivo. Analysis of The Cancer Genome Atlas database revealed that all Hsp90 paralogs were upregulated in prostate cancer. Inactivation of all Hsp90 paralogs induced mitochondrial dysfunction, increased cytosolic calcium, and activated calcineurin. Active calcineurin blocked prosurvival heat shock responses upon Hsp90 inhibition by preventing nuclear translocation of HSF1. The purine scaffold derivative DN401 inhibited all Hsp90 paralogs simultaneously and showed stronger anticancer activity than other Hsp90 inhibitors. Pan-Hsp90 inhibition increased cytotoxicity and suppressed mechanisms that protect cancer cells, suggesting that it is a feasible strategy for the development of potent anticancer drugs. The mitochondria-permeable drug DN401 is a newly identified in vivo pan-Hsp90 inhibitor with potent anticancer activity

Block Design-Based Local Differential Privacy Mechanisms

In this paper, we propose a new class of local differential privacy (LDP) schemes based on combinatorial block designs for a discrete distribution estimation. This class not only recovers many known LDP schemes in a unified framework of combinatorial block design, but also suggests a novel way of finding new schemes achieving the optimal (or near-optimal) privacy-utility trade-off with lower communication costs. Indeed, we find many new LDP schemes that achieve both the optimal privacy-utility trade-off and the minimum communication cost among all the unbiased schemes for a certain set of input data size and LDP constraint. Furthermore, to partially solve the sparse existence issue of block design schemes, we consider a broader class of LDP schemes based on regular and pairwise-balanced designs, called RPBD schemes, which relax one of the symmetry requirements on block designs. By considering this broader class of RPBD schemes, we can find LDP schemes achieving near-optimal privacy-utility trade-off with reasonably low communication costs for a much larger set of input data size and LDP constraint.Comment: 18 pages, 3 figures, and 1 table. This manuscript was submitted to IEEE Transactions on Information Theory and a short version of this manuscript will be presented at 2023 IEEE International Symposium on Information Theor

Perception-Oriented Single Image Super-Resolution using Optimal Objective Estimation

Single-image super-resolution (SISR) networks trained with perceptual and adversarial losses provide high-contrast outputs compared to those of networks trained with distortion-oriented losses, such as L1 or L2. However, it has been shown that using a single perceptual loss is insufficient for accurately restoring locally varying diverse shapes in images, often generating undesirable artifacts or unnatural details. For this reason, combinations of various losses, such as perceptual, adversarial, and distortion losses, have been attempted, yet it remains challenging to find optimal combinations. Hence, in this paper, we propose a new SISR framework that applies optimal objectives for each region to generate plausible results in overall areas of high-resolution outputs. Specifically, the framework comprises two models: a predictive model that infers an optimal objective map for a given low-resolution (LR) input and a generative model that applies a target objective map to produce the corresponding SR output. The generative model is trained over our proposed objective trajectory representing a set of essential objectives, which enables the single network to learn various SR results corresponding to combined losses on the trajectory. The predictive model is trained using pairs of LR images and corresponding optimal objective maps searched from the objective trajectory. Experimental results on five benchmarks show that the proposed method outperforms state-of-the-art perception-driven SR methods in LPIPS, DISTS, PSNR, and SSIM metrics. The visual results also demonstrate the superiority of our method in perception-oriented reconstruction. The code and models are available at https://github.com/seungho-snu/SROOE.Comment: Code and trained models will be available at https://github.com/seungho-snu/SROO

REGNET: Mining context-specific human transcription networks using composite genomic information

Background: Genome-wide expression profiles reflect the transcriptional networks specific to the given cell context. However, most statistical models try to estimate the average connectivity of the networks from a collection of gene expression data, and are unable to characterize the context-specific transcriptional regulations. We propose an approach for mining context-specific transcription networks from a large collection of gene expression fold-change profiles and composite gene-set information.Results: Using a composite gene-set analysis method, we combine the information of transcription factor binding sites, Gene Ontology or pathway gene sets and gene expression fold-change profiles for a variety of cell conditions. We then collected all the significant patterns and constructed a database of context-specific transcription networks for human (REGNET). As a result, context-specific roles of transcription factors as well as their functional targets are readily explored. To validate the approach, nine predicted targets of E2F1 in HeLa cells were tested using chromatin immunoprecipitation assay. Among them, five (Gadd45b, Dusp6, Mll5, Bmp2 and E2f3) were successfully bound by E2F1. c-JUN and the EMT transcription networks were also validated from literature.Conclusions: REGNET is a useful tool for exploring the ternary relationships among the transcription factors, their functional targets and the corresponding cell conditions. It is able to provide useful clues for novel cell-specific transcriptional regulations. The REGNET database is available at http://mgrc.kribb.re.kr/regnet.open0

EST sequencing and gene expression profiling in Scutellaria baicalensis

Scutellaria baicalensis is an important medicinal plant, but few genomic resources are available for this species, as well as for other non-model plants. One of the major new directions in genome research is to discover the full spectrum of genes transcribed from the whole genome. Here, we report extensive transcriptome data of the early growth stage of S. baicalensis. This transcriptome consensus sequence was constructed by de novo assembly of shotgun sequencing data, obtained using multiple next-generation DNA sequencing (NGS) platforms (Roche/454 GS_FLX+ and Illumina/Solexa HiSeq2000). We show that this new approach to obtain extensive mRNA is an efficient strategy for genome-wide transcriptome analysis. We obtained 1,226,938 and 161,417,646 reads using the GS_FLX and the Illumina/Solexa HiS-eq2000, respectively. De novo assembly of the high-quality GS_FLX and Illumina reads (95 % and 75 %) resulted in more than 82 Mb of mRNA consensus sequence, which we assembled into 51,188 contigs, with at least 500 bp per contig. Of these contigs, 39,581 contained known genes, as determined by BLASTX searches against non-redundant NCBI database. Of these, 20,498 different genes were expressed during the early growth stage of S. baicalensis. We have made the expressed sequences available on a public database. Our results demonstrate the utility of combining NGS technologies as a basis for the development of genomic tools in non-model, medicinal plant species. Knowledge of all described genes and quantitation of the expressed genes, including the transcription factors involved, will be useful in studies of the biology of S. baicalensis gene regulation

Transcription Factor Sp1 Is Involved in Expressional Regulation of Coxsackie and Adenovirus Receptor in Cancer Cells

Coxsackie and adenovirus receptor (CAR) was first known as a virus receptor. Recently, it is also known to have tumor suppressive activity such as inhibition of cell proliferation, migration, and invasion. It is important to understand how CAR expression can be regulated in cancers. Based on an existence of putative Sp1 binding site within CAR promoter, we investigated whether indeed Sp1 is involved in the regulation of CAR expression. We observed that deletion or mutation of Sp1 binding motif (−503/−498) prominently impaired the Sp1 binding affinity and activity of CAR promoter. Histone deacetylase inhibitor (TSA) treatment enhanced recruitment of Sp1 to the CAR promoter in ChIP assay. Meanwhile, Sp1 binding inhibitor suppressed the recruitment. Exogenous expression of wild-type Sp1 increased CAR expression in CAR-negative cells; meanwhile, dominant negative Sp1 decreased the CAR expression in CAR-positive cells. These results indicate that Sp1 is involved in regulation of CAR expression

Urine-NMR metabolomics for screening of advanced colorectal adenoma and early stage colorectal cancer

Although colorectal cancer (CRC) is considered one of the most preventable cancers, no non-invasive, accurate diagnostic tool to screen CRC exists. We explored the potential of urine nuclear magnetic resonance (NMR) metabolomics as a diagnostic tool for early detection of CRC, focusing on advanced adenoma and stage 0 CRC. Urine metabolomics profiles from patients with colorectal neoplasia (CRN; 36 advanced adenomas and 56 CRCs at various stages, n = 92) and healthy controls (normal, n = 156) were analyzed by NMR spectroscopy. Healthy and CRN groups were statistically discriminated using orthogonal projections to latent structure discriminant analysis (OPLS-DA). The class prediction model was validated by three-fold cross-validation. The advanced adenoma and stage 0 CRC were grouped together as pre-invasive CRN. The OPLS-DA score plot showed statistically significant discrimination between pre-invasive CRN as well as advanced CRC and healthy controls with a Q2 value of 0.746. In the prediction validation study, the sensitivity and specificity for diagnosing pre-invasive CRN were 96.2% and 95%, respectively. The grades predicted by the OPLS-DA model showed that the areas under the curve were 0.823 for taurine, 0.783 for alanine, and 0.842 for 3-aminoisobutyrate. In multiple receiver operating characteristics curve analyses, taurine, alanine, and 3-aminoisobutyrate were good discriminators for CRC patients. NMR-based urine metabolomics profiles significantly and accurately discriminate patients with pre-invasive CRN as well as advanced CRC from healthy individuals. Urine-NMR metabolomics has potential as a screening tool for accurate diagnosis of pre-invasive CRN.Peer reviewe