Raymond Otteson v. M. K. Baird et al : Petition for Rehearing

Appeal from a Judgment of the District Court of Juab County. Hon. C. Nelson Day, District Judge

Raymond Otteson v. M. K. Baird et al : Plaintiff-Brief of Respondent

On appeal from a Judgment of the District Court of Juab County, Utah, Honorable C. Nelson Day, Judge

Raymond Otteson v. M. K. Baird et al : Brief of Defendant and Appellant

On appeal from a Judgment of the District Court of Juab County, Utah, Honorable C. Nelson Day, Judge

Identification of Single- and Multiple-Class Specific Signature Genes from Gene Expression Profiles by Group Marker Index

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases

Kinetics of diffusional droplet growth in a liquid/liquid two-phase system

In the case of the diaphragm cell transport equation where the interdiffusion coefficient is a function of concentration, we have derived an integral of the form, t = B(sub 0) + B(sub L)ln(delta(c)) + B(sub 1)(delta(c)) + B(sub 2)(delta(c))(exp 2) +... where t is the time and (delta(c)) is the concentration difference across the frit. The coefficient, B(sub 0), is a constant of integration, while the coefficient, B(sub L), B(sub 1), B(sub 2), ..., depend in general upon the cell constant, the compartment volumes, the interdiffusion coefficient, and various of its concentration derivatives evaluated at the mean concentration for the cell. Explicit formulae for B(sub L), B(sub 1), B(sub 2), ... are given

Addressing disparities in maternal health care in Pakistan: gender, class and exclusion

Background: After more than two decades of the Safe Motherhood Initiative and Millennium Development Goals aimed at reducing maternal mortality, women continue to die in childbirth at unacceptably high rates in Pakistan. While an extensive literature describes various programmatic strategies, it neglects the rigorous analysis of the reasons these strategies have been unsuccessful, especially for women living at the economic and social margins of society. A critical gap in current knowledge is a detailed understanding of the root causes of disparities in maternal health care, and in particular, how gender and class influence policy formulation and the design and delivery of maternal health care services. Taking Pakistan as a case study, this research builds upon two distinct yet interlinked conceptual approaches to understanding the phenomenon of inequity in access to maternal health care: social exclusion and health systems as social institutions. Methods/Design: This four year project consists of two interrelated modules that focus on two distinct groups of participants: (1) poor, disadvantaged women and men and (2) policy makers, program managers and health service providers. Module one will employ critical ethnography to understand the key axes of social exclusion as related to gender, class and zaat and how they affect women’s experiences of using maternal health care. Through health care setting observations, interviews and document review, Module two will assess policy design and delivery of maternal health services. Discussion: This research will provide theoretical advances to enhance understanding of the power dynamics of gender and class that may underlie poor women’s marginalization from health care systems in Pakistan. It will also provide empirical evidence to support formulation of maternal health care policies and health care system practices aimed at reducing disparities in maternal health care in Pakistan. Lastly, it will enhance inter-disciplinary research capacity in the emerging field of social exclusion and maternal health and help reduce social inequities and achieve the Millennium Development Goal No. 5

DNA Damage, Somatic Aneuploidy, and Malignant Sarcoma Susceptibility in Muscular Dystrophies

Albeit genetically highly heterogeneous, muscular dystrophies (MDs) share a convergent pathology leading to muscle wasting accompanied by proliferation of fibrous and fatty tissue, suggesting a common MD–pathomechanism. Here we show that mutations in muscular dystrophy genes (Dmd, Dysf, Capn3, Large) lead to the spontaneous formation of skeletal muscle-derived malignant tumors in mice, presenting as mixed rhabdomyo-, fibro-, and liposarcomas. Primary MD–gene defects and strain background strongly influence sarcoma incidence, latency, localization, and gender prevalence. Combined loss of dystrophin and dysferlin, as well as dystrophin and calpain-3, leads to accelerated tumor formation. Irrespective of the primary gene defects, all MD sarcomas share non-random genomic alterations including frequent losses of tumor suppressors (Cdkn2a, Nf1), amplification of oncogenes (Met, Jun), recurrent duplications of whole chromosomes 8 and 15, and DNA damage. Remarkably, these sarcoma-specific genetic lesions are already regularly present in skeletal muscles in aged MD mice even prior to sarcoma development. Accordingly, we show also that skeletal muscle from human muscular dystrophy patients is affected by gross genomic instability, represented by DNA double-strand breaks and age-related accumulation of aneusomies. These novel aspects of molecular pathologies common to muscular dystrophies and tumor biology will potentially influence the strategies to combat these diseases

Gene expression profiling identifies distinct molecular subgroups of leiomyosarcoma with clinical relevance

YesBackground: Soft tissue sarcomas are heterogeneous and a major complication in their management is that the existing classification scheme is not definitive and is still evolving. Leiomyosarcomas, a major histologic category of soft tissue sarcomas, are malignant tumours displaying smooth muscle differentiation. Although defined as a single group, they exhibit a wide range of clinical behaviour. We aimed to carry out molecular classification to identify new molecular subgroups with clinical relevance. Methods: We used gene expression profiling on 20 extra-uterine leiomyosarcomas and cross-study analyses for molecular classification of leiomyosarcomas. Clinical significance of the subgroupings was investigated. Results: We have identified two distinct molecular subgroups of leiomyosarcomas. One group was characterised by high expression of 26 genes that included many genes from the sub-classification gene cluster proposed by Nielsen et al. These sub-classification genes include genes that have importance structurally, as well as in cell signalling. Notably, we found a statistically significant association of the subgroupings with tumour grade. Further refinement led to a group of 15 genes that could recapitulate the tumour subgroupings in our data set and in a second independent sarcoma set. Remarkably, cross-study analyses suggested that these molecular subgroups could be found in four independent data sets, providing strong support for their existence. Conclusions: Our study strongly supported the existence of distinct leiomyosarcoma molecular subgroups, which have clinical association with tumour grade. Our findings will aid in advancing the classification of leiomyosarcomas and lead to more individualised and better management of the disease.Alexander Boag Sarcoma Fund