Handling Discontinuous Effects in Modeling Spatial Correlation of Wafer-level Analog/RF Tests

Abstract-In an effort to reduce the cost of specification testing in analog/RF circuits, spatial correlation modeling of wafer-level measurements has recently attracted increased attention. Existing approaches for capturing and leveraging such correlation, however, rely on the assumption that spatial variation is smooth and continuous. This, in turn, limits the effectiveness of these methods on actual production data, which often exhibits localized spatial discontinuous effects. In this work, we propose a novel approach which enables spatial correlation modeling of waferlevel analog/RF tests to handle such effects and, thereby, to drastically reduce prediction error for measurements exhibiting discontinuous spatial patterns. The core of the proposed approach is a k-means algorithm which partitions a wafer into k clusters, as caused by discontinuous effects. Individual correlation models are then constructed within each cluster, revoking the assumption that spatial patterns should be smooth and continuous across the entire wafer. Effectiveness of the proposed approach is evaluated on industrial probe test data from more than 3,400 wafers, revealing significant error reduction over existing approaches

Inflammatory arthritis can be reined in by CpG-induced DC–NK cell cross talk

Unmethylated CpG-oligodeoxynucleotides (ODNs) are generally thought of as potent adjuvants with considerable therapeutic potential to enhance immune responses against microbes and tumors. Surprisingly, certain so-called stimulatory CpG-ODNs strongly inhibited the effector phase of inflammatory arthritis in the K/BxN serum transfer system, either preventively or therapeutically. Also unexpected was that the inhibitory influence did not depend on the adaptive immune system cells mobilized in an immunostimulatory context. Instead, they relied on cells of the innate immune system, specifically on cross talk between CD8α+ dendritic cells and natural killer cells, resulting in suppression of neutrophil recruitment to the joint, orchestrated through interleukin-12 and interferon-γ. These findings highlight potential applications of CpG-ODNs and downstream molecules as antiinflammatory agents

Management of systemic sclerosis: British Society for Rheumatology guideline scope

This guideline will provide a practical roadmap for management of SSc that builds upon the previous treatment guideline to incorporate advances in evidence-based treatment and increased knowledge about assessment, classification and management. General approaches to management as well as treatment of specific complications will be covered, including lung, cardiac, renal and gastrointestinal tract disease, as well as RP, digital vasculopathy, skin manifestations, calcinosis and impact on quality of life. It will include guidance related to emerging approved therapies for interstitial lung disease and account for National Health Service England prescribing policies and national guidance relevant to SSc. The guideline will be developed using the methods and processes outlined in Creating Clinical Guidelines: Our Protocol. This development process to produce guidance, advice and recommendations for practice has National Institute for Health and Care Excellence accreditation

Causal Modeling Using Network Ensemble Simulations of Genetic and Gene Expression Data Predicts Genes Involved in Rheumatoid Arthritis

Tumor necrosis factor α (TNF-α) is a key regulator of inflammation and rheumatoid arthritis (RA). TNF-α blocker therapies can be very effective for a substantial number of patients, but fail to work in one third of patients who show no or minimal response. It is therefore necessary to discover new molecular intervention points involved in TNF-α blocker treatment of rheumatoid arthritis patients. We describe a data analysis strategy for predicting gene expression measures that are critical for rheumatoid arthritis using a combination of comprehensive genotyping, whole blood gene expression profiles and the component clinical measures of the arthritis Disease Activity Score 28 (DAS28) score. Two separate network ensembles, each comprised of 1024 networks, were built from molecular measures from subjects before and 14 weeks after treatment with TNF-α blocker. The network ensemble built from pre-treated data captures TNF-α dependent mechanistic information, while the ensemble built from data collected under TNF-α blocker treatment captures TNF-α independent mechanisms. In silico simulations of targeted, personalized perturbations of gene expression measures from both network ensembles identify transcripts in three broad categories. Firstly, 22 transcripts are identified to have new roles in modulating the DAS28 score; secondly, there are 6 transcripts that could be alternative targets to TNF-α blocker therapies, including CD86 - a component of the signaling axis targeted by Abatacept (CTLA4-Ig), and finally, 59 transcripts that are predicted to modulate the count of tender or swollen joints but not sufficiently enough to have a significant impact on DAS28

Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.Peer reviewe

Compositional Heterogeneity and Patterns of Molecular Evolution in the Drosophila Genome

The rates and patterns of molecular evolution in many eukaryotic organisms have been shown to be influenced by the compartmentalization of their genomes into fractions of distinct base composition and mutational properties. We have examined the Drosophila genome to explore relationships between the nucleotide content of large chromosomal segments and the base composition and rate of evolution of genes within those segments. Direct determination of the G + C contents of yeast artificial chromosome clones containing inserts of Drosophila melanogaster DNA ranging from 140-340 kb revealed significant heterogeneity in base composition. The G + C content of the large segments studied ranged from 36.9% G + C for a clone containing the hunchback locus in polytene region 85, to 50.9% G + C for a clone that includes the rosy region in polytene region 87. Unlike other organisms, however, there was no significant correlation between the base composition of large chromosomal regions and the base composition at fourfold degenerate nucleotide sites of genes encompassed within those regions. Despite the situation seen in mammals, there was also no significant association between base composition and rate of nucleotide substitution. These results suggest that nucleotide sequence evolution in Drosophila differs from that of many vertebrates and does not reflect distinct mutational biases, as a function of base composition, in different genomic regions. Significant negative correlations between codon-usage bias and rates of synonymous site divergence, however, provide strong support for an argument that selection among alternative codons may be a major contributor to variability in evolutionary rates within Drosophila genomes

Compositional Heterogeneity and Patterns of Molecular Evolution in the Drosophila Genome

The rates and patterns of molecular evolution in many eukaryotic organisms have been shown to be influenced by the compartmentalization of their genomes into fractions of distinct base composition and mutational properties. We have examined the Drosophila genome to explore relationships between the nucleotide content of large chromosomal segments and the base composition and rate of evolution of genes within those segments. Direct determination of the G + C contents of yeast artificial chromosome clones containing inserts of Drosophila melanogaster DNA ranging from 140-340 kb revealed significant heterogeneity in base composition. The G + C content of the large segments studied ranged from 36.9% G + C for a clone containing the hunchback locus in polytene region 85, to 50.9% G + C for a clone that includes the rosy region in polytene region 87. Unlike other organisms, however, there was no significant correlation between the base composition of large chromosomal regions and the base composition at fourfold degenerate nucleotide sites of genes encompassed within those regions. Despite the situation seen in mammals, there was also no significant association between base composition and rate of nucleotide substitution. These results suggest that nucleotide sequence evolution in Drosophila differs from that of many vertebrates and does not reflect distinct mutational biases, as a function of base composition, in different genomic regions. Significant negative correlations between codon-usage bias and rates of synonymous site divergence, however, provide strong support for an argument that selection among alternative codons may be a major contributor to variability in evolutionary rates within Drosophila genomes

A Fast Spatial Variation Modeling Algorithm for Efficient Test Cost Reduction of Analog/RF Circuits

Abstract-In this paper, we adopt a novel numerical algorithm, referred to as dual augmented Lagrangian method (DALM), for efficient test cost reduction based on spatial variation modeling. The key idea of DALM is to derive the dual formulation of the L 1 -regularized least-squares problem posed by Virtual Probe (VP), which can be efficiently solved with substantially lower computational cost than its primal formulation. In addition, a number of unique properties associated with discrete cosine transform (DCT) are exploited to further reduce the computational cost of DALM. Our experimental results of an industrial RF transceiver demonstrate that the proposed DALM solver achieves up to 38 runtime speed-up over the conventional interior-point solver without sacrificing any performance on escape rate and yield loss for test applications

Consistency in Wafer Based Outlier Screening

Outlier screening is a popular approach for testing automotive products. In practice, developing an outlier model can be subjective, making justification of the model challenging. In this paper we propose a new concept called Consistency which provides a data-driven objective way to assess an outlier model. We study the development of outlier models in view of this new model consistency concept and report experimental findings on an automotive product line