SPECIAL COMMUNICATION Health Industry Practices That Create Conflicts of Interest A Policy Proposal for Academic Medical Centers

market incentives in the United States is posing extraordinary challenges to the principles of medical professionalism. Physicians’ commitment to altruism, putting the interests of the patients first, scientific integrity, and an absence of bias in medical decision making now regularly come up against financial conflicts of interest. Arguably, the most challenging and extensive of these conflicts emanate from relationships between physicians and pharmaceutical companies and medical device manufacturers. 1 As part of the health care industry

Use of chromatin immunoprecipitation (ChIP) to detect transcription factor binding to highly homologous promoters in chromatin isolated from unstimulated and activated primary human B cells

The Chromatin Immunoprecipiation (ChIP) provides a powerful technique for identifying the in vivo association of transcription factors with regulatory elements. However, obtaining meaningful information for promoter interactions is extremely challenging when the promoter is a member of a class of highly homologous elements. Use of PCR primers with small numbers of mutations can limit cross-hybridization with non-targeted sequences and distinguish a pattern of binding for factors with the regulatory element of interest. In this report, we demonstrate the selective in vivo association of NF-κB, p300 and CREB with the human Iγ1 promoter located in the intronic region upstream of the Cγ1 exons in the immunoglobulin heavy chain locus. These methods have the ability to extend ChIP analysis to promoters with a high degree of homology

Quantification of Cell Signaling Networks Using Kinase Activity Chemosensors

The ability to directly determine endogenous kinase activity in tissue homogenates provides valuable insights into signaling aberrations that underlie disease phenotypes. When activity data is collected across a panel of kinases, a unique “signaling fingerprint” is generated that allows for discrimination between diseased and normal tissue. Here we describe the use of peptide-based kinase activity sensors to fingerprint the signaling changes associated with disease states. This approach leverages the phosphorylation-sensitive sulfonamido-oxine (Sox) fluorophore to provide a direct readout of kinase enzymatic activity in unfractionated tissue homogenates from animal models or clinical samples. To demonstrate the application of this technology, we focus on a rat model of nonalcoholic fatty liver disease (NAFLD). Sox-based activity probes allow for the rapid and straightforward analysis of changes in kinase enzymatic activity associated with disease states, providing leads for further investigation using traditional biochemical approaches

T-Cell Memory Responses Elicited by Yellow Fever Vaccine are Targeted to Overlapping Epitopes Containing Multiple HLA-I and -II Binding Motifs

The yellow fever vaccines (YF-17D-204 and 17DD) are considered to be among the safest vaccines and the presence of neutralizing antibodies is correlated with protection, although other immune effector mechanisms are known to be involved. T-cell responses are known to play an important role modulating antibody production and the killing of infected cells. However, little is known about the repertoire of T-cell responses elicited by the YF-17DD vaccine in humans. In this report, a library of 653 partially overlapping 15-mer peptides covering the envelope (Env) and nonstructural (NS) proteins 1 to 5 of the vaccine was utilized to perform a comprehensive analysis of the virus-specific CD4+ and CD8+ T-cell responses. The T-cell responses were screened ex-vivo by IFN-γ ELISPOT assays using blood samples from 220 YF-17DD vaccinees collected two months to four years after immunization. Each peptide was tested in 75 to 208 separate individuals of the cohort. The screening identified sixteen immunodominant antigens that elicited activation of circulating memory T-cells in 10% to 33% of the individuals. Biochemical in-vitro binding assays and immunogenetic and immunogenicity studies indicated that each of the sixteen immunogenic 15-mer peptides contained two or more partially overlapping epitopes that could bind with high affinity to molecules of different HLAs. The prevalence of the immunogenicity of a peptide in the cohort was correlated with the diversity of HLA-II alleles that they could bind. These findings suggest that overlapping of HLA binding motifs within a peptide enhances its T-cell immunogenicity and the prevalence of the response in the population. In summary, the results suggests that in addition to factors of the innate immunity, "promiscuous" T-cell antigens might contribute to the high efficacy of the yellow fever vaccines. © 2013 de Melo et al

Enteric Neurospheres Are Not Specific to Neural Crest Cultures: Implications for Neural Stem Cell Therapies

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited

Mutual Information for Testing Gene-Environment Interaction

Despite current enthusiasm for investigation of gene-gene interactions and gene-environment interactions, the essential issue of how to define and detect gene-environment interactions remains unresolved. In this report, we define gene-environment interactions as a stochastic dependence in the context of the effects of the genetic and environmental risk factors on the cause of phenotypic variation among individuals. We use mutual information that is widely used in communication and complex system analysis to measure gene-environment interactions. We investigate how gene-environment interactions generate the large difference in the information measure of gene-environment interactions between the general population and a diseased population, which motives us to develop mutual information-based statistics for testing gene-environment interactions. We validated the null distribution and calculated the type 1 error rates for the mutual information-based statistics to test gene-environment interactions using extensive simulation studies. We found that the new test statistics were more powerful than the traditional logistic regression under several disease models. Finally, in order to further evaluate the performance of our new method, we applied the mutual information-based statistics to three real examples. Our results showed that P-values for the mutual information-based statistics were much smaller than that obtained by other approaches including logistic regression models