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

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

Adapting to adaptive testing

Adaptive testing is a generic term for a number of techniques which aim at improving the test quality and/or reducing the test\u3cbr/\u3eapplication costs. In adaptive tests, the test content or pass/fail limits are not fixed as in conventional tests, but dependent on other\u3cbr/\u3etest results of the currently or previously tested chips. Part-average testing, outlier detection, and neighborhood screening are just a\u3cbr/\u3efew examples of adaptive testing. With this Embedded Tutorial, we are offering an introduction to this topic, which is hot in the test\u3cbr/\u3ecommunity, to the wider DATE audience

Quantification of JCV DNA and VP1 capsid protein.

<p>Log-log plot of the concentration of JCV genomes vs capsids per microliter tissue for all 9 PML blocks (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155897#pone.0155897.t002" target="_blank">Table 2</a>). Data are means ± standard deviation based on triplicate measurements. Blue dashed line indicates theoretical relationship for one capsid per viral genome. Linear regression reveals a positive relationship with <i>r</i>² = 0.96, <i>p</i><0.0001 (regression line not shown). Asterisk designates the uncertainty of the protein measurement of VP1 in NL3, which was below the assay’s lower limit of quantitation (not shown).</p

VP1 colocalizes with nearby myelin in recently lysed cells.

<p>Representative 5-μm confocal Z-axis stack images of regions of recent virus-induced cell lysis in otherwise intact white matter (A, B, D, E) or gray matter (C) of human PML, or white matter in an SIV-positive rhesus macaque with SV40 PML-like CNS disease (F), stained for VP1 (green in A-F, A″–F″, and A*-F*) and MBP (red in A-C, F, A′–C′, F′, and A*-C*, F*), GFAP (red in D, D′, D*), or IBA1 (red in E, E′, E*). A*–F* show representative colocalization (coloc) images from a single image from each Z-stack, with magenta pixels designating VP1/MBP colocalization (magenta arrows); Image quantitation of these representative Z-stack images revealed 89% and 86% of VP1 colocalized with MBP in white matter (A* and B*, respectively); 34% colocalized in gray matter (C*); and 13% and 2.9% of VP1 colocalized with GFAP or IBA1 (D* and E*, respectively). In SV40 PML-like disease (F), a subset of VP1 was dispersed in a linear pattern and colocalized with partially demyelinated MBP-positive axons (magenta arrow in F*). Occasional cytoplasmic VP1 viral aggregates were seen in cytoplasm of microglia (green arrow in E) or astrocytes, but nuclei of these cell types did not show VP1 positivity that would be indicative of productive infection. Scale bar in panel A = 10 μm.</p

Spatial correlation of dispersed VP1 and early demyelination.

<p>A) Thumbnail IHC images of each block stained for VP1 (top row, left to right based on ranking from highest to lowest VP1 stain index) and MBP (bottom row). Linear plots of (B) JCV concentration vs. the percentage of section area stained darkly with VP1 at 0.01 μg/ml PAB597 (“VP1 stain index”), (C) JCV DNA concentration vs. the fraction of section area positive for MBP stain (“MBP stain index”) as a measure of residual myelin, and (D) MBP vs. VP1 stain indices. There were positive, statistically significant relationships between VP1 stain index and JCV genome or capsid concentrations (<i>p</i><0.0001 for both lines in panel B), but not between MBP stain index and JCV concentrations (C), or between VP1 and MBP stain indices (D), with <i>r</i>² and <i>p</i> values in boxes. E-E”) NL1 stained for VP1 (green; gray scale image of channel in panel E’), MBP (red; gray scale image of channel in panel E”), and DNA (blue) with fluorescence detection. White box on thumbnail image in right upper corner of panel E shows magnified area in E-E”, with gray (G) and white (W) matter regions designated. Demyelinated foci (red asterisks) are spatially coincident with dispersed VP1, whereas numerous VP1-positive cells (green arrowheads) can be seen in areas with intact myelin.</p

Distinct VP1 distributions in gray and white matter.

<p>VP1-stained NL1 (A) and L3 (B) with gray (G) and white (W) matter regions labeled, and black arrowheads (and line in A) demarcating the gray/white matter boundary. Red boxes in panels A and B show areas magnified below in panels A' and B', with blue arrows designating VP1-positive late stage (A’) or recently lysed (B’) cells. Note extensive linear VP1 throughout white matter (e.g., blue arrowheads in A') and little to no dispersed VP1 in gray matter. (C, D) JCV DNA distribution in PML white matter. RNAScope ISH for early (C) or Late (D) JCV probes labels individually infected cells with oligodendrocytic morphology (red and green arrows) as well as linear structures consistent with axons (red and green arrowheads). Scale bar = 5 mm in A, B; 100 μm in A', B'; C, D.</p

Spectrum of PML histopathology.

<p>H&E (A-C) and IHC (brown, with blue hematoxylin counterstain) for NFP to label neuronal processes (D-F), MBP to label myelin (G-I), GFAP to label astrocytes (black arrows) (J-L), and IBA1 to label microglia/macrophages (blue arrowheads) (M-O) from grossly unaffected, actively infected, and end-stage white matter (blocks NL3, PL3, and L3, respectively). NL3 (left column) had largely normal white matter composed of linear axons/myelin throughout the neuropil, oligodendrocytes with characteristic perinuclear “fried egg” halos (green arrowheads), astrocytes with thin and elongated processes, and microglia with short, thick processes. PL3 (middle column) showed active infection with viral nuclear inclusions (red arrows), hypertrophied astrocytes with thickened processes, swollen myelin, and some enlarged macrophages (this section also had foci of demyelination, not shown here). L3 (right column) had end-stage lesions with rare viral inclusions, reduced number and fragmentation of axons, residual axonal myelin (magenta arrowhead), and variable amounts of MBP within engorged macrophages and massively hypertrophied (“bizarre”) astrocytes. Asterisks in B and C designate thinning of neuropil secondary to axonal loss. Scale bar = 30 μm for all panels.</p

White matter “wave” of JCV infection.

<p>(A-D) Top of each panel shows low magnification views of sequential sections of block L1, stained for H&E (A) or indicated IHCs (B-D), with higher magnification of region designated by red box shown in bottom of each panel. Black asterisk designates confluent area of demyelination behind wave; blue asterisks designate two foci of MBP pallor ahead of VP1 wave, indicative of recent demyelination. Panel D is a dual IHC, revealing TAg with alkaline phosphatase/fast red detection (red arrows) and VP1 with HRP/DAB detection (green arrow). (E) Schematic of four zones (1–4) relative to wave front of dispersed virus (blue line demarcated by blue arrowheads at the edge of the section) overlying the tissue image in panel D following manual segmentation of TAg-positive cells (red dots) and VP1-positive cells (green dots). Orange arrows indicate putative direction of wave movement through the section. Graphs show cell counts for TAg (red) and VP1 (green) (bottom left), and ratio of early (TAg positive) to late (VP1 positive) infected cells as a function of zone (bottom right). (F) Magnified area of wave front indicated by black box in panels D and E, with TAg-positive cells false-colored red, VP1-positive cells false-colored green, and wave front (gray line) inferred to be progressing in the direction indicated by orange arrow. G–G"–confocal image at wave front stained for TAg (red), VP1 (green), and DNA (blue), with orange arrow showing direction of wave. (Punctate, non-nuclear red stain represents nonspecific autofluorescence due to endogenous lipofuscin.) Scale bar in G" = 2 mm in top panels of A-E, 50 μm in bottom panels of A–D and in G–G" and 70 μm in F.</p

JCV sequence analysis.

<p>(A) Schematic of circular viral DNA showing sites of transcription initiation and directions of early and late transcription (arrows) adjacent to the NCCR. Regions encoding Early T-Ag (T and t) and late agnoprotein (Agno) and VP1, VP2, and VP3 proteins are indicated by colored boxes. (B) Summary of NCCR variants, with the archetype NCCR shown for reference consisting of an origin of replication (ORI) followed by intact sequence blocks A-F. The percent of sequences showing the schematized rearrangements, duplications, and/or mutant/deleted sequence blocks (indicated by lower case letters) are listed. (C) VP1 variants identified. WT (1B) = wild type, strain 1B. (D) Agnoprotein variants identified; del(51-end) = deletion of C-terminal 21 amino acids. (E) VP2 variants identified; del(283-end) = deletion of C-terminal 60 amino acids. P174S and R207G were identified in the VP1 amplicon, which overlaps the C-terminal region of VP2/3, with asterisks designating percent of VP1 region clones that harbored the VP2 mutation. Representative DNA sequences and alignments are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0155897#pone.0155897.s002" target="_blank">S1 File</a>, and have been deposited at NCBI under accession nos. KX216358-KX216371.</p