62 research outputs found

    Tuberculosis immunopathology: the neglected role of extracellular matrix destruction

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    The extracellular matrix in the lung must be destroyed for Mycobacterium tuberculosis—the agent that causes tuberculosis (TB)—to spread. The current paradigm proposes that this destruction occurs as a result of the action of proinflammatory cytokines, chemokines, immune cells, and lipids that mediate TB-associated necrosis in the lung. However, this view neglects the fact that lung matrix can only be degraded by proteases. We propose an original conceptual framework of TB immunopathology that may lead directly to treatments that involve inhibition of matrix metalloproteinase activity to hinder matrix destruction and reduce the morbidity and mortality associated with T

    Delineation of prognostic biomarkers in prostate cancer

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    Prostate cancer is the most frequently diagnosed cancer in American men(1,2). Screening for prostate-specific antigen (PSA) has led to earlier detection of prostate cancer(3), but elevated serum PSA levels may be present in non-malignant conditions such as benign prostatic hyperlasia (BPH). Characterization of gene-expression profiles that molecularly distinguish prostatic neoplasms may identify genes involved in prostate carcinogenesis, elucidate clinical biomarkers, and lead to an improved classification of prostate cancer(4-6). Using microarrays of complementary DNA, we examined gene-expression profiles of more than 50 normal and neoplastic prostate specimens and three common prostate-cancer cell lines. Signature expression profiles of normal adjacent prostate (NAP), BPH, localized prostate cancer, and metastatic, hormone-refractory prostate cancer were determined. Here we establish many associations between genes and prostate cancer. We assessed two of these genes-hepsin, a transmembrane serine protease, and pim-1, a serine/threonine kinase-at the protein level using tissue microarrays consisting of over 700 clinically stratified prostate-cancer specimens. Expression of hepsin and pim-1 proteins was significantly correlated with measures of clinical outcome. Thus, the integration of cDNA microarray, high-density tissue microarray, and linked clinical and pathology data is a powerful approach to molecular profiling of human cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62849/1/412822a0.pd

    The Democratic Biopolitics of PrEP

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    PrEP (Pre-Exposure Prophylaxis) is a relatively new drug-based HIV prevention technique and an important means to lower the HIV risk of gay men who are especially vulnerable to HIV. From the perspective of biopolitics, PrEP inscribes itself in a larger trend of medicalization and the rise of pharmapower. This article reconstructs and evaluates contemporary literature on biopolitical theory as it applies to PrEP, by bringing it in a dialogue with a mapping of the political debate on PrEP. As PrEP changes sexual norms and subjectification, for example condom use and its meaning for gay subjectivity, it is highly contested. The article shows that the debate on PrEP can be best described with the concepts ‘sexual-somatic ethics’ and ‘democratic biopolitics’, which I develop based on the biopolitical approach of Nikolas Rose and Paul Rabinow. In contrast, interpretations of PrEP which are following governmentality studies or Italian Theory amount to either farfetched or trivial positions on PrEP, when seen in light of the political debate. Furthermore, the article is a contribution to the scholarship on gay subjectivity, highlighting how homophobia and homonormativity haunts gay sex even in liberal environments, and how PrEP can serve as an entry point for the destigmatization of gay sexuality and transformation of gay subjectivity. ‘Biopolitical democratization’ entails making explicit how medical technology and health care relates to sexual subjectification and ethics, to strengthen the voice of (potential) PrEP users in health politics, and to renegotiate the profit and power of Big Pharma

    Microarray-based gene set analysis: a comparison of current methods

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    BACKGROUND: The analysis of gene sets has become a popular topic in recent times, with researchers attempting to improve the interpretability and reproducibility of their microarray analyses through the inclusion of supplementary biological information. While a number of options for gene set analysis exist, no consensus has yet been reached regarding which methodology performs best, and under what conditions. The goal of this work was to examine the performance characteristics of a collection of existing gene set analysis methods, on both simulated and real microarray data sets. Of particular interest was the potential utility gained through the incorporation of inter-gene correlation into the analysis process. RESULTS: Each of six gene set analysis methods was applied to both simulated and publicly available microarray data sets. Overall, the various methodologies were all found to be better at detecting gene sets that moved from non-active (i.e., genes not expressed) to active states (or vice versa), rather than those that simply changed their level of activity. Methods which incorporate correlation structures were found to provide increased ability to detect altered gene sets in some settings. CONCLUSION: Based on the results obtained through the analysis of simulated data, it is clear that the performance of gene set analysis methods is strongly influenced by the features of the data set in question, and that methods which incorporate correlation structures into the analysis process tend to achieve better performance, relative to methods which rely on univariate test statistics

    Referral patterns and attitudes of Primary Care Physicians towards chiropractors

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    BACKGROUND: Despite the increasing usage and popularity of chiropractic care, there has been limited research conducted to examine the professional relationships between conventional trained primary care physicians (PCPs) and chiropractors (DCs). The objectives of our study were to contrast the intra-professional referral patterns among PCPs with referral patterns to DCs, and to identify predictors of PCP referral to DCs. METHODS: We mailed a survey instrument to all practicing PCPs in the state of Iowa. Descriptive statistics were used to summarize their responses. Multivariable logistic regression analyses were conducted to identify demographic factors associated with inter-professional referral behaviors. RESULTS: A total of 517 PCPs (33%) participated in the study. PCPs enjoyed strong intra-professional referral relationships with other PCPs. Although patients exhibited a great deal of interest in chiropractic care, PCPs were unlikely themselves to make formal referral relationships with DCs. PCPs in a private practice arrangement were more likely to exhibit positive referral attitudes towards DCs (p = 0.01). CONCLUSION: PCPs enjoy very good professional relationships with other PCPs. However, the lack of direct formalized referral relationships between PCPs and chiropractors has implications for efficiency, continuity, quality, and patient safety in the health care delivery system. Future research must focus on identifying facilitators and barriers for developing positive relationships between PCPs and chiropractors

    Functional Analysis: Evaluation of Response Intensities - Tailoring ANOVA for Lists of Expression Subsets

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    Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions. Geneset analysis methods have been described previously to analyze the expression values of several genes related by known biological criteria (metabolic pathway, pathology signature, co-regulation by a common factor, etc.) at the same time and the cost of these methods allows for the use of more values to help discover the underlying biological mechanisms. Results: As several methods assume different null hypotheses, we propose to reformulate the main question that biologists seek to answer. To determine which genesets are associated with expression values that differ between two experiments, we focused on three ad hoc criteria: expression levels, the direction of individual gene expression changes (up or down regulation), and correlations between genes. We introduce the FAERI methodology, tailored from a two-way ANOVA to examine these criteria. The significance of the results was evaluated according to the self-contained null hypothesis, using label sampling or by inferring the null distribution from normally distributed random data. Evaluations performed on simulated data revealed that FAERI outperforms currently available methods for each type of set tested. We then applied the FAERI method to analyze three real-world datasets on hypoxia response. FAERI was able to detect more genesets than other methodologies, and the genesets selected were coherent with current knowledge of cellular response to hypoxia. Moreover, the genesets selected by FAERI were confirmed when the analysis was repeated on two additional related datasets. Conclusions: The expression values of genesets are associated with several biological effects. The underlying mathematical structure of the genesets allows for analysis of data from several genes at the same time. Focusing on expression levels, the direction of the expression changes, and correlations, we showed that two-step data reduction allowed us to significantly improve the performance of geneset analysis using a modified two-way ANOVA procedure, and to detect genesets that current methods fail to detect

    The neutron and its role in cosmology and particle physics

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    Experiments with cold and ultracold neutrons have reached a level of precision such that problems far beyond the scale of the present Standard Model of particle physics become accessible to experimental investigation. Due to the close links between particle physics and cosmology, these studies also permit a deep look into the very first instances of our universe. First addressed in this article, both in theory and experiment, is the problem of baryogenesis ... The question how baryogenesis could have happened is open to experimental tests, and it turns out that this problem can be curbed by the very stringent limits on an electric dipole moment of the neutron, a quantity that also has deep implications for particle physics. Then we discuss the recent spectacular observation of neutron quantization in the earth's gravitational field and of resonance transitions between such gravitational energy states. These measurements, together with new evaluations of neutron scattering data, set new constraints on deviations from Newton's gravitational law at the picometer scale. Such deviations are predicted in modern theories with extra-dimensions that propose unification of the Planck scale with the scale of the Standard Model ... Another main topic is the weak-interaction parameters in various fields of physics and astrophysics that must all be derived from measured neutron decay data. Up to now, about 10 different neutron decay observables have been measured, much more than needed in the electroweak Standard Model. This allows various precise tests for new physics beyond the Standard Model, competing with or surpassing similar tests at high-energy. The review ends with a discussion of neutron and nuclear data required in the synthesis of the elements during the "first three minutes" and later on in stellar nucleosynthesis.Comment: 91 pages, 30 figures, accepted by Reviews of Modern Physic

    Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges

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    Pathway analysis has become the first choice for gaining insight into the underlying biology of differentially expressed genes and proteins, as it reduces complexity and has increased explanatory power. We discuss the evolution of knowledge base–driven pathway analysis over its first decade, distinctly divided into three generations. We also discuss the limitations that are specific to each generation, and how they are addressed by successive generations of methods. We identify a number of annotation challenges that must be addressed to enable development of the next generation of pathway analysis methods. Furthermore, we identify a number of methodological challenges that the next generation of methods must tackle to take advantage of the technological advances in genomics and proteomics in order to improve specificity, sensitivity, and relevance of pathway analysis
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