2,497 publications from this institution
Abstract Family history is a strong risk factor for many common chronic diseases and summarizes shared environmental and genetic risk, but how this increased risk is mediated is unknown. We developed a “family history–wide association study” (FamWAS) to systematically and comprehensively test clinical and environmental quantitative traits (CEQTs) for their association with family history of disease. We implemented our method on 457 CEQTs for association with family history of diabetes, asthma, and coronary heart disease (CHD) in 42,940 adults spanning 8 waves of the 1999–2014 US National Health and Nutrition Examination Survey. We conducted pooled analyses of the 8 survey waves and analyzed trait associations using survey-weighted logistic regression. We identified 172 (37.6% of total), 32 (7.0%), and 78 (17.1%) CEQTs associated with family history of diabetes, asthma, and CHD, respectively, in subcohorts of individuals without the respective disease. Twenty associated CEQTs were shared across family history of diabetes, asthma, and CHD, far more than expected by chance. FamWAS can examine traits not previously studied in association with family history and uncover trait overlap, highlighting a putative shared mechanism by which family history influences disease risk.
This paper addresses timing and glitch detection problems involving charge sharing in acyclic resistor capacitor networks. Solutions to these problems are proposed and applied to real designs. Results are reported and compared with SPICE simulation. Our algorithms are intended for use in switch level simulators and timing verifiers which model transistors in digital VLSI designs as linear resistors. Computational complexity of our methods is also investigated. (Author)
Full chip mixed-signal validation requires simulating the entire design through a large number of test vectors, which makes fast, event-based Verilog models of analog circuits essential. We describe an extensible approach to creating these models that maps continuous signals into piecewise linear waveforms by creating analog events which contain a value and slope. By breaking analog circuits into sub-blocks with mostly unidirectional ports, we avoid explicit time integration, thus fitting well into an event-driven digital framework. The result is Verilog analog functional models that are pin-accurate, fast to simulate, and capture the key dynamics in analog circuits. A 250 Ms/s open-loop track and hold circuit, 2.5 V-1.8 V buck converter, and 1 GHz PLL models are demonstrated.
ABSTRACT Amino acids in variable positions of proteins may be correlated, with potential structural and functional implications. Here, we apply exact tests of independence in R × C contingency tables to examine noise-free associations between variable positions of the SARS-CoV-2 spike protein, using as a paradigm sequences from Greece deposited in GISAID ( N = 6,683/1,078 full length) for the period 29 February 2020 to 26 April 2021 that essentially covers the first three pandemic waves. We examine the fate and complexity of these associations by network analysis, using associated positions (exact P ≤ 0.001 and Average Product Correction ≥ 2) as links and the corresponding positions as nodes. We found a temporal linear increase of positional differences and a gradual expansion of the number of position associations over time, represented by a temporally evolving intricate web, resulting in a non-random complex network of 69 nodes and 252 links. Overconnected nodes corresponded to the most adapted variant positions in the population, suggesting a direct relation between network degree and position functional importance. Modular analysis revealed 25 k -cliques comprising 3 to 11 nodes. At different k -clique resolutions, one to four communities were formed, capturing epistatic associations of circulating variants (Alpha, Beta, B.1.1.318), but also Delta, which dominated the evolutionary landscape later in the pandemic. Cliques of aminoacidic positional associations tended to occur in single sequences, enabling the recognition of epistatic positions in real-world virus populations. Our findings provide a novel way of understanding epistatic relationships in viral proteins with potential applications in the design of virus control procedures. IMPORTANCE Paired positional associations of adapted amino acids in virus proteins may provide new insights for understanding virus evolution and variant formation. We investigated potential intramolecular relationships between variable SARS-CoV-2 spike positions by exact tests of independence in R × C contingency tables, having applied Average Product Correction (APC) to eliminate background noise. Associated positions (exact P ≤ 0.001 and APC ≥ 2) formed a non-random, epistatic network of 25 cliques and 1–4 communities at different clique resolutions, revealing evolutionary ties between variable positions of circulating variants and a predictive potential of previously unknown network positions. Cliques of different sizes represented theoretical combinations of changing residues in sequence space, allowing the identification of significant aminoacidic combinations in single sequences of real-world populations. Our analytic approach that links network structural aspects to mutational aminoacidic combinations in the spike sequence population offers a novel way to understand virus epidemiology and evolution.
This paper describes using adjacency lists to incrementally generate design rule spacing constraints. The algorithm generates the smallest complete set of constraints for a design, yielding fast compaction, and is as fast or faster than ordinary constraint generation methods even when the incremental features are not used. The adjacency list data structure allows one to very quickly move, insert or delete objects and generate an updated set of constraints.
ABSTRACT Background The ability to preferentially protect high-groups in COVID-19 is hotly debated. Here, the aim is to present simple metrics of such precision shielding of people at high-risk of death after infection by SARS-CoV-2; demonstrate how they can estimated; and examine whether precision shielding was successfully achieved in the first COVID-19 wave. Methods The shielding ratio, S, is defined as the ratio of prevalence of infection among people at a high-risk group versus among people in a low-risk group. The contrasted risk groups examined here are according to age (>=70 versus <70 years), and institutionalized (nursing home) setting. For age-related precision shielding, data were used from large seroprevalence studies with separate prevalence data for elderly versus non-elderly and with at least 1000 assessed people >=70 years old. For setting-related precision shielding, data were analyzed from 10 countries where information was available on numbers of nursing home residents, proportion of nursing home residents among COVID-19 deaths, and overall population infection fatality rate. Findings Across 17 seroprevalence studies, the shielding ratio S for elderly versus non-elderly varied between 0.4 (substantial shielding) and 1.6 (substantial inverse protection, i.e. low-risk people being protected more than high-risk people). Five studies in USA all yielded S=0.4-0.8, consistent with some shielding being achieved, while two studies in China yielded S=1.5-1.6, consistent with inverse protection. Assuming 25% infection fatality rate among nursing home residents, S values for nursing home residents ranged from 0.07 to 3.1. The best shielding was seen in South Korea (S=0.07) and modest shielding was achieved in Israel, Slovenia, Germany, and Denmark. No shielding was achieved in Hungary and Sweden. In Belgium (S=1.9), UK (S=2.2) and Spain (S=3.1), nursing home residents were far more frequently infected that the rest of the population. Interpretation The experience from the first wave of COVID-19 suggests that different locations and settings varied markedly in the extent to which they protected high-risk groups. Both effective precision shielding and detrimental inverse protection can happen in real-life circumstances. COVID-19 interventions should seek to achieve maximal precision shielding.
