Timing offset and quantization error trade-off in interleaved multi-channel measurements

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 117-118).Time-interleaved analog-to-digital converters (ADCs) are traditionally designed with equal quantization granularity in each channel and uniform sampling offsets. Recent work suggests that it is often possible to achieve a better signal-to-quantization noise ratio (SQNR) with different quantization granularity in each channel, non-uniform sampling, and appropriate reconstruction filtering. This thesis develops a framework for optimal design of non-uniform sampling constellations to maximize SQNR in time-interleaved ADCs. The first portion of this thesis investigates discrepancies between the additive noise model and uniform quantizers. A simulation is implemented for the multi-channel measurement and reconstruction system. The simulation reveals a key inconsistency in the environment of time-interleaved ADCs: cross-channel quantization error correlation. Statistical analysis is presented to characterize error correlation between quantizers with different granularities. A novel ADC architecture is developed based on weighted least squares (WLS) to exploit this correlation, with particular application for time-interleaved ADCs. A "correlated noise model" is proposed that incorporates error correlation between channels. The proposed model is shown to perform significantly better than the traditional additive noise model for channels in close proximity. The second portion of this thesis focuses on optimizing channel configurations in time-interleaved ADCs. Analytical and numerical optimization techniques are presented that rely on the additive noise model for determining non-uniform sampling constellations that maximize SQNR. Optimal constellations for critically sampled systems are always uniform, while solution sets for oversampled systems are larger. Systems with diverse bit allocations often exhibit "clusters" of low-precision channels in close proximity. Genetic optimization is shown to be effective for quickly and accurately determining optimal timing constellations in systems with many channels. Finally, a framework for efficient design of optimal channel configurations is formulated that incorporates statistical analysis of cross-channel quantization error correlation and solutions based on the additive noise model. For homogeneous bit allocations, the framework proposes timing offset corrections to avoid performance degradation from the optimal scenario predicted by the additive noise model. For diverse bit allocations, the framework proposes timing corrections and a "unification" of low-precision quantizers in close proximity. This technique results in significant improvements in performance above the previously known optimal additive noise model solution.by Joseph Gary McMichael.S.M

CD6 attenuates early and late signaling events, setting thresholds for T-cell activation

The T lineage glycoprotein CD6 is generally considered to be a costimulator of T-cell activation. Here, we demonstrate that CD6 significantly reduces early and late T-cell responses upon superantigen stimulation or TCR triggering by Abs. Measuring calcium mobilization in single cells responding to superantigen, we found that human T cells expressing rat CD6 react significantly less well compared with T cells not expressing the exogenous receptor. When the cytoplasmic domain of rat CD6 was removed, calcium responses were recovered, indicating that the inhibitory properties of CD6 are attributable to its cytoplasmic domain. Calcium responses, and also late indicators of T-cell activation such as IL-2 release, were also diminished in TCR-activated Jurkat cells expressing human CD6, compared with CD6-deficient cells or cells expressing a cytoplasmic deletion mutant of human CD6. Similarly, calcium signals triggered by anti-CD3 were enhanced in human T lymphocytes following morpholino-mediated suppression of CD6 expression. Finally, the proliferation of T lymphocytes was increased when the CD6–CD166 interaction was blocked with anti-CD166 Abs, but inhibited when anti-CD6 Abs were used. Our data suggest that CD6 is a signaling attenuator whose expression alone, i.e. in the absence of ligand engagement, is sufficient to restrain signaling in T cells

The Origin and Evolution of Mutations in Acute Myeloid Leukemia

SummaryMost mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive clonal evolution. However, for acute myeloid leukemia (AML), normal karyotypes are common, and genomic instability is unusual. To better understand clonal evolution in AML, we sequenced the genomes of M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-AML samples and the exomes of hematopoietic stem/progenitor cells (HSPCs) from healthy people. Collectively, the data suggest that most of the mutations found in AML genomes are actually random events that occurred in HSPCs before they acquired the initiating mutation; the mutational history of that cell is “captured” as the clone expands. In many cases, only one or two additional, cooperating mutations are needed to generate the malignant founding clone. Cells from the founding clone can acquire additional cooperating mutations, yielding subclones that can contribute to disease progression and/or relapse

Genome modeling system: A knowledge management platform for genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms

Marketing as a means to transformative social conflict resolution: lessons from transitioning war economies and the Colombian coffee marketing system

Social conflicts are ubiquitous to the human condition and occur throughout markets, marketing processes, and marketing systems.When unchecked or unmitigated, social conflict can have devastating consequences for consumers, marketers, and societies, especially when conflict escalates to war. In this article, the authors offer a systemic analysis of the Colombian war economy, with its conflicted shadow and coping markets, to show how a growing network of fair-trade coffee actors has played a key role in transitioning the country’s war economy into a peace economy. They particularly draw attention to the sources of conflict in this market and highlight four transition mechanisms — i.e., empowerment, communication, community building and regulation — through which marketers can contribute to peacemaking and thus produce mutually beneficial outcomes for consumers and society. The article concludes with a discussion of implications for marketing theory, practice, and public policy

Pleiotropy of genetic variants on obesity and smoking phenotypes: Results from the Oncoarray Project of The International Lung Cancer Consortium

Obesity and cigarette smoking are correlated through complex relationships. Common genetic causes may contribute to these correlations. In this study, we selected 241 loci potentially associated with body mass index (BMI) based on the Genetic Investigation of ANthropometric Traits (GIANT) consortium data and calculated a BMI genetic risk score (BMI-GRS) for 17,037 individuals of European descent from the Oncoarray Project of the International Lung Cancer Consortium (ILCCO). Smokers had a significantly higher BMI-GRS than never-smokers (p = 0.016 and 0.010 before and after adjustment for BMI, respectively). The BMI-GRS was also positively correlated with pack-years of smoking (p<0.001) in smokers. Based on causal network inference analyses, seven and five of 241 SNPs were classified to pleiotropic models for BMI/smoking status and BMI/pack-years, respectively. Among them, three and four SNPs associated with smoking status and pack-years (p<0.05), respectively, were followed up in the ever-smoking data of the Tobacco, Alcohol and Genetics (TAG) consortium. Among these seven candidate SNPs, one SNP (rs11030104, BDNF) achieved statistical significance after Bonferroni correction for multiple testing, and three suggestive SNPs (rs13021737, TMEM18; rs11583200, ELAVL4; and rs6990042, SGCZ) achieved a nominal statistical significance. Our results suggest that there is a common genetic component between BMI and smoking, and pleiotropy analysis can be useful to identify novel genetic loci of complex phenotypes