Mycobacteriosis in Chesapeake Bay Striped Bass (Morone saxatilis): The Interaction of Nutrition and Disease

Field and laboratory studies were conducted from 1998 - 2005 to examine the relationship between nutritional status and mycobacteriosis in Chesapeake Bay striped bass (Morone saxatilis). A review of DNA from archived tissue blocks indicated that the disease has been present since at least 1984. Field surveys and feeding trials were conducted from 1998-1999 to determine the nutritional condition of striped bass and the association with disease state. Proximate composition revealed elevated moisture (~ 80%) and low storage lipids (< 0.5% ww), characteristic of a poorly nourished population. These findings were not consistent with data collected in 1990-1991, or with experimentally fed fish. Mycobacteriosis explained little of the variance in chemical composition (p > 0.2); however elevated moisture and low lipid concentration were associated with fish with ulcerative lesions (p < 0.05). This suggests that age 3 and 4 striped bass were in poor nutritional health in 1998-1999, which may be independent from the disease process. Challenge studies were performed to address the hypothesis that disease progression and severity may be altered by nutritional status of the host. Intraperitoneal inoculation of 104 CFU M. marinum resulted in high mortality, elevated bacterial density, and poor granuloma formation in low ration (0.15% bw/d) groups while adequately fed fish (1% bw/d) followed a normal course of granulomatous inflammation with low mortality to a steady, equilibrium state. Further, we demonstrated that an active inflammatory state could be reactivated in fish through reductions in total diet. The energetic demand of mycobacteriosis, was insignificant in comparison to sham inoculated controls in adequately fed fish (p > 0.05). Declines in total body energy were only apparent during active, inflammatory stages of disease. Overall, these findings suggest that: 1) mycobacteriosis is not a new disease of Chesapeake Bay striped bass, 2) the disease has little energetic demand in the normal, chronic progression, and 3) poor nutritional health can greatly enhance the progression and severity, and reactivation of disease. The implications of this research are that management strategies focused on enhancing the nutritional state of striped bass could potentially alter the disease dynamics in Chesapeake Bay.

Comparison of pattern detection methods in microarray time series of the segmentation clock.

While genome-wide gene expression data are generated at an increasing rate, the repertoire of approaches for pattern discovery in these data is still limited. Identifying subtle patterns of interest in large amounts of data (tens of thousands of profiles) associated with a certain level of noise remains a challenge. A microarray time series was recently generated to study the transcriptional program of the mouse segmentation clock, a biological oscillator associated with the periodic formation of the segments of the body axis. A method related to Fourier analysis, the Lomb-Scargle periodogram, was used to detect periodic profiles in the dataset, leading to the identification of a novel set of cyclic genes associated with the segmentation clock. Here, we applied to the same microarray time series dataset four distinct mathematical methods to identify significant patterns in gene expression profiles. These methods are called: Phase consistency, Address reduction, Cyclohedron test and Stable persistence, and are based on different conceptual frameworks that are either hypothesis- or data-driven. Some of the methods, unlike Fourier transforms, are not dependent on the assumption of periodicity of the pattern of interest. Remarkably, these methods identified blindly the expression profiles of known cyclic genes as the most significant patterns in the dataset. Many candidate genes predicted by more than one approach appeared to be true positive cyclic genes and will be of particular interest for future research. In addition, these methods predicted novel candidate cyclic genes that were consistent with previous biological knowledge and experimental validation in mouse embryos. Our results demonstrate the utility of these novel pattern detection strategies, notably for detection of periodic profiles, and suggest that combining several distinct mathematical approaches to analyze microarray datasets is a valuable strategy for identifying genes that exhibit novel, interesting transcriptional patterns.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

BACKGROUND: Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. RESULTS: Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. CONCLUSIONS: Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Evaluation of Altered Kras Codon Bias and NOS Inhibition During Lung Tumorigenesis

The small GTPases HRAS, NRAS and KRAS are mutated in approximately one-third of all human cancers, rendering the proteins constitutively active and oncogenic. Lung cancer is the leading cause of cancer deaths worldwide, and more than 20% of human lung cancers harbor mutations in RAS, with 98% of those occurring in the KRAS isoform. While there have been many advances in the understanding of KRAS–driven lung tumorigenesis, it remains a therapeutic challenge. To further this understanding and assess novel approaches for treatment, I have investigated two aspects of Kras–driven tumorigenesis in the lung:

(I) Despite nearly identical protein sequences, the three RAS proto-oncogenes exhibit divergent codon usage. Of the three isoforms, KRAS contains the most rare codons resulting in lower levels of KRAS protein expression relative to HRAS and NRAS. To determine the consequences of rare codon bias during de novo tumorigenesis, we created a knock-in Krasex3op mouse in which synonymous mutations in exon 3 converted codons from rare to common. These mice had reduced tumor burden and fewer oncogenic mutations in the Krasex3op allele following carcinogen exposure. The reduction in tumorigenesis appeared to be a product of rare codons affecting both the oncogenic and non–oncogenic alleles. Converting rare codons to common codons yielded a more potent oncogenic allele that promoted growth arrest and enhanced tumor suppression by the non-oncogenic allele. Thus, rare codons play an integral role in Kras tumorigenesis.

(II) Lung cancer patients exhale higher levels of NO and iNOS-/- mice are resistant to chemically induced lung tumorigenesis. I hypothesize that NO promotes Kras–driven lung adenocarcinoma, and NOS inhibition may decrease Kras–driven lung tumorigenesis. To test this hypothesis, I assessed efficacy of the NOS inhibitor L–NAME in a genetically engineered mouse model of Kras-driven lung adenocarcinoma. Adenoviral Cre recombinase was delivered into the lungs intranasally, resulting in expression of oncogenic KrasG12D and dominant-negative Trp53R172H in lung epithelial cells. L–NAME treatment was provided in the water and continued until survival endpoints. In this model, L–NAME treatment decreased tumor growth and prolonged survival. These data establish a potential clinical role for NOS inhibition in lung cancer treatment.

The induced innovation hypothesis and energy-saving technological change

We develop a methodology for testing Hicks's induced innovation hypothesis by estimating a product-characteristics model of energy-using consumer durables, augmenting the hypothesis to allow for the influence of government regulations. For the products we explored, the evidence suggests that (i) the rate of overall innovation was independent of energy prices and regulations; (ii) the direction of innovation was responsive to energy price changes for some products but not for others; (iii) energy price changes induced changes in the subset of technically feasible models that were offered for sale; (iv) this responsiveness increased substantially during the period after energy-efficiency product labeling was required; and (v) nonetheless, a sizable portion of efficiency improvements were autonomous.

The reappearance hypothesis revisited: recurrent involuntary memories after traumatic events and in everyday life.

Recurrent involuntary memories are autobiographical memories that come to mind with no preceding retrieval attempt and that are subjectively experienced as being repetitive. Clinically, they are classified as a symptom of posttraumatic stress disorder. The present work is the first to systematically examine recurrent involuntary memories outside clinical settings. Study 1 examines recurrent involuntary memories among survivors of the tsunami catastrophe in Southeast Asia in 2004. Study 2 examines recurrent involuntary memories in a large general population. Study 3 examines whether the contents of recurrent involuntary memories recorded in a diary study are duplicates of, or differ from, one another. We show that recurrent involuntary memories are not limited to clinical populations or to emotionally negative experiences; that they typically do not come to mind in a fixed and unchangeable form; and that they show the same pattern regarding accessibility as do autobiographical memories in general. We argue that recurrent involuntary memories after traumas and in everyday life can be explained in terms of general and well-established mechanisms of autobiographical memory.

Revisiting the monoamine hypothesis of depression: a new perspective.

As the incidence of depression increases, depression continues to inflict additional suffering to individuals and societies and better therapies are needed. Based on magnetic resonance spectroscopy and laboratory findings, gamma aminobutyric acid (GABA) may be intimately involved in the pathophysiology of depression. The isoelectric point of GABA (pI = 7.3) closely approximates the pH of cerebral spinal fluid (CSF). This may not be a trivial observation as it may explain preliminary spectrophotometric, enzymatic, and HPLC data that monoamine oxidase (MAO) deaminates GABA. Although MAO is known to deaminate substrates such as catecholamines, indoleamines, and long chain aliphatic amines all of which contain a lipophilic moiety, there is very good evidence to predict that a low concentration of a very lipophilic microspecies of GABA is present when GABA pI = pH as in the CSF. Inhibiting deamination of this microspecies of GABA could explain the well-established successful treatment of refractory depression with MAO inhibitors (MAOI) when other antidepressants that target exclusively levels of monoamines fail. If further experimental work can confirm these preliminary findings, physicians may consider revisiting the use of MAOI for the treatment of non-intractable depression because the potential benefits of increasing GABA as well as the monoamines may outweigh the risks associated with MAOI therapy.

Chronic opioid therapy and opioid tolerance: a new hypothesis.

Opioids are efficacious and cost-effective analgesics, but tolerance limits their effectiveness. This paper does not present any new clinical or experimental data but demonstrates that there exist ascending sensory pathways that contain few opioid receptors. These pathways are located by brain PET scans and spinal cord autoradiography. These nonopioid ascending pathways include portions of the ventral spinal thalamic tract originating in Rexed layers VI-VIII, thalamocortical fibers that project to the primary somatosensory cortex (S1), and possibly a midline dorsal column visceral pathway. One hypothesis is that opioid tolerance and opioid-induced hyperalgesia may be caused by homeostatic upregulation during opioid exposure of nonopioid-dependent ascending pain pathways. Upregulation of sensory pathways is not a new concept and has been demonstrated in individuals impaired with deafness or blindness. A second hypothesis is that adjuvant nonopioid therapies may inhibit ascending nonopioid-dependent pathways and support the clinical observations that monotherapy with opioids usually fails. The uniqueness of opioid tolerance compared to tolerance associated with other central nervous system medications and lack of tolerance from excess hormone production is discussed. Experimental work that could prove or disprove the concepts as well as flaws in the concepts is discussed.

A finite volume unstructured mesh approach to dynamic fluid-structure interaction: an assessment of the challenge of flutter analysis

Computational modelling of dynamic fluid-structure interaction (DFSI) is problematical since conventionally computational fluid dynamics (CFD) is solved using finite volume (FV) methods and computational structural mechanics (CSM) is based entirely on finite element (FE) methods. Hence, progress in modelling the emerging multi-physics problem of dynamic fluid-structure interaction in a consistent manner is frustrated and significant problems in computation convergence may be encountered in transferring and filtering data from one mesh and solution procedure to another, unless the fluid-structure coupling is either one way, very weak or both. This paper sets out the solution procedure for modelling the multi-physics dynamic fluid-structure interaction problem within a single software framework PHYSICA, using finite volume, unstructured mesh (FV-UM) procedures and will focus upon some of the problems and issues that have to be resolved for time accurate closely coupled dynamic fluid-structure flutter analysis.

A finite volume unstructured mesh approach to dynamic fluid–structure interaction: an assessment of the challenge of predicting the onset of flutter

Computational modelling of dynamic fluid–structure interaction (DFSI) is a considerable challenge. Our approach to this class of problems involves the use of a single software framework for all the phenomena involved, employing finite volume methods on unstructured meshes in three dimensions. This method enables time and space accurate calculations in a consistent manner. One key application of DFSI simulation is the analysis of the onset of flutter in aircraft wings, where the work of Yates et al. [Measured and Calculated Subsonic and Transonic Flutter Characteristics of a 45° degree Sweptback Wing Planform in Air and Freon-12 in the Langley Transonic Dynamic Tunnel. NASA Technical Note D-1616, 1963] on the AGARD 445.6 wing planform still provides the most comprehensive benchmark data available. This paper presents the results of a significant effort to model the onset of flutter for the AGARD 445.6 wing planform geometry. A series of key issues needs to be addressed for this computational approach. • The advantage of using a single mesh, in order to eliminate numerical problems when applying boundary conditions at the fluid-structure interface, is counteracted by the challenge of generating a suitably high quality mesh in both the fluid and structural domains. • The computational effort for this DFSI procedure, in terms of run time and memory requirements, is very significant. Practical simulations require even finer meshes and shorter time steps, requiring parallel implementation for operation on large, high performance parallel systems. • The consistency and completeness of the AGARD data in the public domain is inadequate for use in the validation of DFSI codes when predicting the onset of flutter.

C. G. Jung and literary theory: the challenge from fiction

C.G. Jung and Literary Theory remedies a significant omission in literary studies by doing for Jung and poststructuralist literary theories what has been done extensively for Freud, Lacan and post-Freudian psychoanalysis. This work represents a complete departure from traditional Jungian literary criticism. Instead, radically new Jungian literary theories are developed of deconstruction, feminist theory, gender and psyche, the body and sexuality, spirituality, postcolonialism, historicism and reader-response. As well as linking Jung to the work of Derrida, Kristeva and Irigaray, the book traces contentious occult, cultural and political narratives in Jung's career. It contains a chapter on Jung and fascism in a literary context. [From the Publisher]