Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
52,617
result(s) for
"Small, S."
Sort by:
Comics confidential : thirteen graphic novelists talk story, craft, and life outside the box
\"Marcus turns his literary microscope to the world of comics, which has lately morphed and matured at a furious pace. Powerful influences from manga to the movies to underground comix have influenced the thirteen artists and writers interviewed in these pages to create their own word-and-picture narratives\"-- Provided by publisher.
Book
STATISTICAL INFERENCE IN TWO-SAMPLE SUMMARY-DATA MENDELIAN RANDOMIZATION USING ROBUST ADJUSTED PROFILE SCORE
Mendelian randomization (MR) is a method of exploiting genetic variation to unbiasedly estimate a causal effect in presence of unmeasured confounding. MR is being widely used in epidemiology and other related areas of population science. In this paper, we study statistical inference in the increasingly popular two-sample summary-data MR design. We show a linear model for the observed associations approximately holds in a wide variety of settings when all the genetic variants satisfy the exclusion restriction assumption, or in genetic terms, when there is no pleiotropy. In this scenario, we derive a maximum profile likelihood estimator with provable consistency and asymptotic normality. However, through analyzing real datasets, we find strong evidence of both systematic and idiosyncratic pleiotropy in MR, echoing the omnigenic model of complex traits that is recently proposed in genetics. We model the systematic pleiotropy by a random effects model, where no genetic variant satisfies the exclusion restriction condition exactly. In this case, we propose a consistent and asymptotically normal estimator by adjusting the profile score.We then tackle the idiosyncratic pleiotropy by robustifying the adjusted profile score. We demonstrate the robustness and efficiency of the proposed methods using several simulated and real datasets.
Journal Article
فيزياء العقل البشري والعالم من منظورين
في هذا السفر النفيس، نوقشت آراء روجر بنروز المثيرة للجدل والمتعلقة بفيزياء الكون واسعة النطاق وعالم فيزياء الكم ضيق النطاق، إلى جانب فيزياء العقل البشري، مناقشة شاملة. ويعد هذا الكتاب في الواقع ملخصا رائعا لأفكار بنروز حول هذه الموضوعات الخاصة بالفيزياء التي يشعر أنها مشكلات كبرى لم يتوصل بعد إلى حلول لها. والكتاب أيضا يمكن اعتباره مقدمة نموذجية إلى المفاهيم الجديدة جذريا التي يعتقد أنها ستؤتي ثمارها مستقبلا فيما يتعلق بفهم وظائف المخ وطبيعة العقل البشري.
BOOK
Hippocampal dysfunction in the pathophysiology of schizophrenia: a selective review and hypothesis for early detection and intervention
Scientists have long sought to characterize the pathophysiologic basis of schizophrenia and develop biomarkers that could identify the illness. Extensive postmortem and in vivo neuroimaging research has described the early involvement of the hippocampus in the pathophysiology of schizophrenia. In this context, we have developed a hypothesis that describes the evolution of schizophrenia—from the premorbid through the prodromal stages to syndromal psychosis—and posits dysregulation of glutamate neurotransmission beginning in the CA1 region of the hippocampus as inducing attenuated psychotic symptoms and initiating the transition to syndromal psychosis. As the illness progresses, this pathological process expands to other regions of the hippocampal circuit and projection fields in other anatomic areas including the frontal cortex, and induces an atrophic process in which hippocampal neuropil is reduced and interneurons are lost. This paper will describe the studies of our group and other investigators supporting this pathophysiological hypothesis, as well as its implications for early detection and therapeutic intervention.
Journal Article
Non-parametric methods for doubly robust estimation of continuous treatment effects
Continuous treatments (e.g. doses) arise often in practice, but many available causal effect estimators are limited by either requiring parametric models for the effect curve, or by not allowing doubly robust covariate adjustment. We develop a novel kernel smoothing approach that requires only mild smoothness assumptions on the effect curve and still allows for misspecification of either the treatment density or outcome regression. We derive asymptotic properties and give a procedure for data-driven bandwidth selection. The methods are illustrated via simulation and in a study of the effect of nurse staffing on hospital readmissions penalties.
Journal Article
The fecal metabolome as a functional readout of the gut microbiome
The human gut microbiome plays a key role in human health
1
, but 16S characterization lacks quantitative functional annotation
2
. The fecal metabolome provides a functional readout of microbial activity and can be used as an intermediate phenotype mediating host–microbiome interactions
3
. In this comprehensive description of the fecal metabolome, examining 1,116 metabolites from 786 individuals from a population-based twin study (TwinsUK), the fecal metabolome was found to be only modestly influenced by host genetics (heritability (
H
2
) = 17.9%). One replicated locus at the
NAT2
gene was associated with fecal metabolic traits. The fecal metabolome largely reflects gut microbial composition, explaining on average 67.7% (±18.8%) of its variance. It is strongly associated with visceral-fat mass, thereby illustrating potential mechanisms underlying the well-established microbial influence on abdominal obesity. Fecal metabolic profiling thus is a novel tool to explore links among microbiome composition, host phenotypes, and heritable complex traits.
Comprehensive fecal metabolic profiling in 786 individuals from TwinsUK provides insights into the influence of host genetics and gut microbial composition on metabolites that may mediate microbiome-associated phenotypes.
Journal Article
Randomized Trial of Four Financial-Incentive Programs for Smoking Cessation
In this randomized trial of financial incentives in smokers, both reward-based and deposit-based incentive programs were more effective than usual care in achieving smoking cessation. Reward programs were much more commonly accepted than deposit-based programs.
Financial incentives have been shown to promote a variety of health behaviors.
1
–
8
For example, in a randomized, clinical trial involving 878 General Electric employees, a bundle of incentives worth $750 for smoking cessation nearly tripled quit rates, from 5.0% to 14.7%,
8
and led to a program adapted by General Electric for its U.S. employees.
9
Although incentive programs are increasingly used by governments, employers, and insurers to motivate changes in health behavior,
10
,
11
their design is usually based on the traditional economic assumption that the size of the incentive determines its effectiveness. In contrast, behavioral economic theory suggests that incentives . . .
Journal Article
Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments
Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that “all genes affect every complex trait” complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.
Journal Article
Escape from X-inactivation in twins exhibits intra- and inter-individual variability across tissues and is heritable
X-chromosome inactivation (XCI) silences one X in female cells to balance sex-differences in X-dosage. A subset of X-linked genes escape XCI, but the extent to which this phenomenon occurs and how it varies across tissues and in a population is as yet unclear. To characterize incidence and variability of escape across individuals and tissues, we conducted a transcriptomic study of escape in adipose, skin, lymphoblastoid cell lines and immune cells in 248 healthy individuals exhibiting skewed XCI. We quantify XCI escape from a linear model of genes’ allelic fold-change and XIST -based degree of XCI skewing. We identify 62 genes, including 19 lncRNAs, with previously unknown patterns of escape. We find a range of tissue-specificity, with 11% of genes escaping XCI constitutively across tissues and 23% demonstrating tissue-restricted escape, including cell type-specific escape across immune cells of the same individual. We also detect substantial inter-individual variability in escape. Monozygotic twins share more similar escape than dizygotic twins, indicating that genetic factors may underlie inter-individual differences in escape. However, discordant escape also occurs within monozygotic co-twins, suggesting environmental factors also influence escape. Altogether, these data indicate that XCI escape is an under-appreciated source of transcriptional differences, and an intricate phenotype impacting variable trait expressivity in females.
Journal Article
Predicting Customer Value Using Clumpiness: From RFM to RFMC
In recent years, customer lifetime value (CLV) has gained increasing importance in both academia and practice. Although many advanced techniques have been proposed, the recency/frequency/monetary value (RFM) segmentation framework, and its related probability models, remain a CLV mainstay. In this article, we demonstrate the deficiency in RFM as a basis for summarizing customer history (data compression), and extend the framework to include clumpiness (C) by a metric-based approach. Our main empirical finding is that C adds to the predictive power, above and beyond RFM and firm marketing action, of both the churn, incidence, and monetary value parts of CLV. Hence, we recommend a significant implementation change: from RFM to RFMC.
This work is also motivated by noting that although statistical models based on RFM summaries can fit well in aggregate, their use can lead to significant micro-level (e.g., ranking of customers) prediction errors unless C is captured. A set of detailed empirical studies using data from a large North American retailer, in addition to six companies that vary in their business model: two traditional (e.g., CDNow.com) and four Internet (e.g., Hulu.com), demonstrate that the “clumpiness phenomena” is widely prevalent, and that companies with “bingeable content” have both high potential and high risk segments, previously unseen, but now uncovered because of the new framework: RFM to RFMC.
Journal Article