The Guanylate Cyclase C-cGMP Signaling Axis Opposes Intestinal Epithelial Injury and Neoplasia.

Guanylate cyclase C (GUCY2C) is a transmembrane receptor expressed on the luminal aspect of the intestinal epithelium. Its ligands include bacterial heat-stable enterotoxins responsible for traveler\u27s diarrhea, the endogenous peptide hormones uroguanylin and guanylin, and the synthetic agents, linaclotide, plecanatide, and dolcanatide. Ligand-activated GUCY2C catalyzes the synthesis of intracellular cyclic GMP (cGMP), initiating signaling cascades underlying homeostasis of the intestinal epithelium. Mouse models of GUCY2C ablation, and recently, human populations harboring GUCY2C mutations, have revealed the diverse contributions of this signaling axis to epithelial health, including regulating fluid secretion, microbiome composition, intestinal barrier integrity, epithelial renewal, cell cycle progression, responses to DNA damage, epithelial-mesenchymal cross-talk, cell migration, and cellular metabolic status. Because of these wide-ranging roles, dysregulation of the GUCY2C-cGMP signaling axis has been implicated in the pathogenesis of bowel transit disorders, inflammatory bowel disease, and colorectal cancer. This review explores the current understanding of cGMP signaling in the intestinal epithelium and mechanisms by which it opposes intestinal injury. Particular focus will be applied to its emerging role in tumor suppression. In colorectal tumors, endogenous GUCY2C ligand expression is lost by a yet undefined mechanism conserved in mice and humans. Further, reconstitution of GUCY2C signaling through genetic or oral ligand replacement opposes tumorigenesis in mice. Taken together, these findings suggest an intriguing hypothesis that colorectal cancer arises in a microenvironment of functional GUCY2C inactivation, which can be repaired by oral ligand replacement. Hence, the GUCY2C signaling axis represents a novel therapeutic target for preventing colorectal cancer

Neighbors Matter: Causal Community Effects and Stock Market Participation

This paper establishes a causal relation between an individual's decision of whether to own stocks and average stock market participation decision of the individual's community. We instrument for the average ownership of an individual's community with lagged average ownership of the states in which one's non-native neighbors were born. Combining this instrumental variables approach with controls for individual and community fixed effects, a broad set of time-varying individual and community controls, and state-by-year effects, rules out alternative explanations. To further establish that word-of-mouth communication drives this causal effect, we show that the results are stronger in more sociable communities.

The Geography of Stock Market Participation: The Influence of Communities and Local Firms

This paper is the first to investigate the importance of geography in explaining equity market participation. We provide evidence to support two distinct local area effects. The first is a community ownership effect, that is, individuals are influenced by the investment behavior of members of their community. Specifically, a ten percentage-point increase in equity market participation of the members of one's community makes it two percentage points more likely that the individual will invest in stocks. We find further evidence that the influence of community members is strongest for less financially sophisticated households and strongest within peer groups' as defined by age and income categories. The second is that proximity to publicly-traded firms also increases equity market participation. In particular, the presence of publicly-traded firms within 50 miles and the share of U.S. market value headquartered within the community are significantly correlated with equity ownership of individuals. These results are quite robust, holding up in the presence of a wide range of individual and community controls, instrumental variables estimation, the inclusion of individual fixed effects, and specification checks to rule out that the relations are driven solely by ownership of the stock of one's employer.

Conjugate-Gradient Preconditioning Methods for Shift-Variant PET Image Reconstruction

Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85979/1/Fessler85.pd

MONEY ILLUSION, GORMAN AND LAU

Any demand equation satisfying Lau’s (1982) Fundamental Theorem of Exact Aggregation and 0° homogeneity in prices and income will have a Gorman (1981) functional form for each income term. This property does not depend on symmetry or adding up. The implications of this result are illustrated by an extensive example.Demand, exact aggregation, functional form, homogeneity

Combined Diagonal/Fourier Preconditioning Methods for Image Reconstruction in Emission Tomography

Iterative methods for tomographic image reconstruction often converge slowly. Preconditioning methods can often accelerate gradient-based iterations. Previous preconditioning methods for PET reconstruction have used either diagonal or Fourier-based preconditioners. Fourier-based preconditioners are well suited to problems with near-circulant Hessian matrices. However, due to the nonuniform Poisson noise variance in PET, the circulant approximation to the Hessian is suboptimal. This paper shows that a particular combined diagonal/Fourier preconditioner yields a more accurate approximation to the Hessian and gives significantly faster convergence rates than does either preconditioner used alone.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85972/1/Fessler135.pd

A Tale of Three Cities: Crime and Displacement after Hurricane Katrina

When Hurricane Katrina struck New Orleans in August 2005, it greatly disrupted both the physical and social structures of that community. One consequence of the hurricane was the displacement of large numbers of New Orleans residents to other cities, including Houston, San Antonio, and Phoenix. There has been media speculation that such a grand-scale population displacement led to increased crime in communities that were recipient of large numbers of displaced New Orleans residents. This study was a case study of three cities with somewhat different experiences with Katrina\u27s diaspora. Time series analysis was used to examine the pre- and post-Katrina trends in six Part I offenses (murder, robbery, aggravated assault, rape, burglary, and auto theft) to assess any impact of such large-scale population shifts on crime in host communities. Contrary to much popular speculation, only modest effects were found on crime. Social disorganization theory was used to frame both the analysis and the interpretation of these result