Association between cognitive performance and cortical glucose metabolism in patients with mild Alzheimer's disease

Background: Neuronal and synaptic function in Alzheimer's disease (AD) is measured in vivo by glucose metabolism using positron emission tomography (PET). Objective: We hypothesized that neuronal activation as measured by PET is a more sensitive index of neuronal dysfunction than activity during rest. We investigated if the correlations between dementia severity as measured with the Mini Mental State Examination (MMSE) and glucose metabolism are an artifact of brain atrophy. Method: Glucose metabolism was measured using {[}F-18]fluorodeoxyglucose PET during rest and activation due to audiovisual stimulation in 13 mild to moderate AD patients (MMSE score >= 17). PET data were corrected for brain atrophy. Results: In the rest condition, glucose metabolism was correlated with the MMSE score primarily within the posterior cingulate and parietal lobes. For the activation condition, additional correlations were within the primary and association audiovisual areas. Most local maxima remained significant after correcting for brain atrophy. Conclusion: PET activity measured during audiovisual stimulation was more sensitive to functional alterations in glucose metabolism in AD patients compared to the resting PET. The association between glucose metabolism and MMSE score was not dependent on brain atrophy. Copyright (C) 2005 S. Karger AG, Basel

DeepBrain: Functional Representation of Neural In-Situ Hybridization Images for Gene Ontology Classification Using Deep Convolutional Autoencoders

This paper presents a novel deep learning-based method for learning a functional representation of mammalian neural images. The method uses a deep convolutional denoising autoencoder (CDAE) for generating an invariant, compact representation of in situ hybridization (ISH) images. While most existing methods for bio-imaging analysis were not developed to handle images with highly complex anatomical structures, the results presented in this paper show that functional representation extracted by CDAE can help learn features of functional gene ontology categories for their classification in a highly accurate manner. Using this CDAE representation, our method outperforms the previous state-of-the-art classification rate, by improving the average AUC from 0.92 to 0.98, i.e., achieving 75% reduction in error. The method operates on input images that were downsampled significantly with respect to the original ones to make it computationally feasible

Phase transitions in contagion processes mediated by recurrent mobility patterns

Human mobility and activity patterns mediate contagion on many levels, including the spatial spread of infectious diseases, diffusion of rumors, and emergence of consensus. These patterns however are often dominated by specific locations and recurrent flows and poorly modeled by the random diffusive dynamics generally used to study them. Here we develop a theoretical framework to analyze contagion within a network of locations where individuals recall their geographic origins. We find a phase transition between a regime in which the contagion affects a large fraction of the system and one in which only a small fraction is affected. This transition cannot be uncovered by continuous deterministic models due to the stochastic features of the contagion process and defines an invasion threshold that depends on mobility parameters, providing guidance for controlling contagion spread by constraining mobility processes. We recover the threshold behavior by analyzing diffusion processes mediated by real human commuting data.Comment: 20 pages of Main Text including 4 figures, 7 pages of Supplementary Information; Nature Physics (2011

Cooperation and Contagion in Web-Based, Networked Public Goods Experiments

A longstanding idea in the literature on human cooperation is that cooperation should be reinforced when conditional cooperators are more likely to interact. In the context of social networks, this idea implies that cooperation should fare better in highly clustered networks such as cliques than in networks with low clustering such as random networks. To test this hypothesis, we conducted a series of web-based experiments, in which 24 individuals played a local public goods game arranged on one of five network topologies that varied between disconnected cliques and a random regular graph. In contrast with previous theoretical work, we found that network topology had no significant effect on average contributions. This result implies either that individuals are not conditional cooperators, or else that cooperation does not benefit from positive reinforcement between connected neighbors. We then tested both of these possibilities in two subsequent series of experiments in which artificial seed players were introduced, making either full or zero contributions. First, we found that although players did generally behave like conditional cooperators, they were as likely to decrease their contributions in response to low contributing neighbors as they were to increase their contributions in response to high contributing neighbors. Second, we found that positive effects of cooperation were contagious only to direct neighbors in the network. In total we report on 113 human subjects experiments, highlighting the speed, flexibility, and cost-effectiveness of web-based experiments over those conducted in physical labs

Exceptional Hyperthyroidism and a Role for both Major Histocompatibility Class I and Class II Genes in a Murine Model of Graves' Disease

Autoimmune hyperthyroidism, Graves' disease, can be induced by immunizing susceptible strains of mice with adenovirus encoding the human thyrotropin receptor (TSHR) or its A-subunit. Studies in two small families of recombinant inbred strains showed that susceptibility to developing TSHR antibodies (measured by TSH binding inhibition, TBI) was linked to the MHC region whereas genes on different chromosomes contributed to hyperthyroidism. We have now investigated TSHR antibody production and hyperthyroidism induced by TSHR A-subunit adenovirus immunization of a larger family of strains (26 of the AXB and BXA strains). Analysis of the combined AXB and BXA families provided unexpected insight into several aspects of Graves' disease. First, extreme thyroid hyperplasia and hyperthyroidism in one remarkable strain, BXA13, reflected an inability to generate non-functional TSHR antibodies measured by ELISA. Although neutral TSHR antibodies have been detected in Graves' sera, pathogenic, functional TSHR antibodies in Graves' patients are undetectable by ELISA. Therefore, this strain immunized with A-subunit-adenovirus that generates only functional TSHR antibodies may provide an improved model for studies of induced Graves' disease. Second, our combined analysis of linkage data from this and previous work strengthens the evidence that gene variants in the immunoglobulin heavy chain V region contribute to generating thyroid stimulating antibodies. Third, a broad region that encompasses the MHC region on mouse chomosome 17 is linked to the development of TSHR antibodies (measured by TBI). Most importantly, unlike other strains, TBI linkage in the AXB and BXA families to MHC class I and class II genes provides an explanation for the unresolved class I/class II difference in humans

Dendritic Cells Transduced to Express Interleukin 4 Reduce Diabetes Onset in Both Normoglycemic and Prediabetic Nonobese Diabetic Mice

Background: We and others have previously demonstrated that treatment with bone marrow derived DC genetically modified to express IL-4 reduce disease pathology in mouse models of collagen-induced arthritis and delayed-type hypersensitivity. Moreover, treatment of normoglycemic NOD mice with bone marrow derived DC, genetically modified to express interleukin 4 (IL-4), reduces the onset of hyperglycemia in a significant number of animals. However, the mechanism(s) through which DC expressing IL-4 function to prevent autoimmune diabetes and whether this treatment can reverse disease in pre-diabetic NOD mice are unknown. Methodology/Principal Findings: DC were generated from the bone marrow of NOD mice and transduced with adenoviral vectors encoding soluble murine IL-4 (DC/sIL-4), a membrane-bound IL-4 construct, or empty vector control. Female NOD mice were segregated into normoglycemic (<150mg/dL) and prediabetic groups (between 150 and 250 mg/dL) on the basis of blood glucose measurements, and randomized for adoptive transfer of 106 DC via a single i.v. injection. A single injection of DC/sIL-4, when administered to normoglycemic 12-week old NOD mice, significantly reduced the number of mice that developed diabetes. Furthermore, DC/sIL-4, but not control DC, decreased the number of mice progressing to diabetes when given to prediabetic NOD mice 12-16 weeks of age. DC/sIL-4 treatment also significantly reduced islet mononuclear infiltration and increased the expression of FoxP3 in the pancreatic lymph nodes of a subset of treated animals. Furthermore, DC/sIL-4 treatment altered the antigen-specific Th2:Th1 cytokine profiles as determined by ELISPOT of splenocytes in treated animals. Conclusions: Adoptive transfer of DC transduced to express IL-4 into both normoglycemic and prediabetic NOD mice is an effective treatment for T1D. © 2010 Ruffner, Robbins

Global quantitative indices reflecting provider process-of-care: data-base derivation

Background: Controversy has attended the relationship between risk-adjusted mortality and process-of-care. There would be advantage in the establishment, at the data-base level, of global quantitative indices subsuming the diversity of process-of-care. Methods: A retrospective, cohort study of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 1993-2003, at the level of geographic and ICU-level descriptors (n = 35), for both hospital survivors and non-survivors. Process-of-care indices were established by analysis of: (i) the smoothed time-hazard curve of individual patient discharge and determined by pharmaco-kinetic methods as area under the hazard-curve (AUC), reflecting the integrated experience of the discharge process, and time-to-peak-hazard (TMAX, in days), reflecting the time to maximum rate of hospital discharge; and (ii) individual patient ability to optimize output (as length-of-stay) for recorded data-base physiological inputs; estimated as a technical production-efficiency (TE, scaled [0,(maximum)1]), via the econometric technique of stochastic frontier analysis. For each descriptor, multivariate correlation-relationships between indices and summed mortality probability were determined. Results: The data-set consisted of 223129 patients from 99 ICUs with mean (SD) age and APACHE III score of 59.2(18.9) years and 52.7(30.6) respectively; 41.7% were female and 45.7% were mechanically ventilated within the first 24 hours post-admission. For survivors, AUC was maximal in rural and for-profit ICUs, whereas TMAX (≥ 7.8 days) and TE (≥ 0.74) were maximal in tertiary-ICUs. For non-survivors, AUC was maximal in tertiary-ICUs, but TMAX (≥ 4.2 days) and TE (≥ 0.69) were maximal in for-profit ICUs. Across descriptors, significant differences in indices were demonstrated (analysisof- variance, P ≤ 0.0001). Total explained variance, for survivors (0.89) and non-survivors (0.89), was maximized by combinations of indices demonstrating a low correlation with mortality probability. Conclusions: Global indices reflecting process of care may be formally established at the level of national patient databases. These indices appear orthogonal to mortality outcome.John L Moran, Patricia J Solomon and the Adult Database Management Committee (ADMC) of the Australian and New Zealand Intensive Care Society (ANZICS

Metabolic Factors Limiting Performance in Marathon Runners

Each year in the past three decades has seen hundreds of thousands of runners register to run a major marathon. Of those who attempt to race over the marathon distance of 26 miles and 385 yards (42.195 kilometers), more than two-fifths experience severe and performance-limiting depletion of physiologic carbohydrate reserves (a phenomenon known as ‘hitting the wall’), and thousands drop out before reaching the finish lines (approximately 1–2% of those who start). Analyses of endurance physiology have often either used coarse approximations to suggest that human glycogen reserves are insufficient to fuel a marathon (making ‘hitting the wall’ seem inevitable), or implied that maximal glycogen loading is required in order to complete a marathon without ‘hitting the wall.’ The present computational study demonstrates that the energetic constraints on endurance runners are more subtle, and depend on several physiologic variables including the muscle mass distribution, liver and muscle glycogen densities, and running speed (exercise intensity as a fraction of aerobic capacity) of individual runners, in personalized but nevertheless quantifiable and predictable ways. The analytic approach presented here is used to estimate the distance at which runners will exhaust their glycogen stores as a function of running intensity. In so doing it also provides a basis for guidelines ensuring the safety and optimizing the performance of endurance runners, both by setting personally appropriate paces and by prescribing midrace fueling requirements for avoiding ‘the wall.’ The present analysis also sheds physiologically principled light on important standards in marathon running that until now have remained empirically defined: The qualifying times for the Boston Marathon