Socially Isolated Cambodians in the US: Recommendations for Health Promotion

Cambodian genocide survivors experience health disparities associated with their traumatic experiences. Cambodian community organizations in the United States are severely challenged to serve these survivors. Community leaders have identified a sub-set of community members of particular concern: those at either end of the age spectrum (elders and young people) who are socially isolated. As part of a larger community-based participatory research project, we conducted a focus group with seven Cambodian community leaders from six cities that sought to better understand the phenomenon of social isolation of Cambodian elders and young people in order to inform health promotion efforts. Cambodian leaders expressed keen concern for those community members who rarely seem to leave their homes or interact with the Cambodian community. Prominent themes identified by leaders related to isolation were: a generational pattern; benefits of extended family; health concerns; the impact of stigma and fear; lack of sufficient resources; and cultural influences. In addition, leaders identified several possible solutions to address the phenomenon of social isolation in their communities. Health promotion efforts in this population should identify isolated individuals and enhance their social connectedness and support networks as part of a larger integrated effort

An Ontology-Based Framework for Clinical Research Databases

The Ontology-Based eXtensible data model (OBX) was developed to serve as a framework for the development of a clinical research database in the Immunology Database and Analysis Portal (ImmPort) system. OBX was designed around the logical structure provided by the Basic Formal Ontology (BFO) and the Ontology for Biomedical Investigations (OBI). By using the logical structure provided by these two well-formulated ontologies, we have found that a relatively simple, extensible data model could be developed to represent the relatively complex domain of clinical research. In addition, the common framework provided by the BFO should make it straightforward to utilize OBX database data dictionaries based on reference and application ontologies from the OBO Foundry

Development of a Virtual Training Program to Reduce Gun Violence Amidst the Covid-19 Era

Firearm deaths and related health issues have increased and disproportionately affected minorities in the COVID-19 era. We developed an accessible virtual training program, including topics on gun violence epidemiology, depression, substance use, intimate partner violence (IPV), intervention resources, safety planning, and COVID-19-related issues. The training program was distributed to participants from the Northeast region, particularly New Jersey, through text, email, and social media. Among the 202 survey responses from the participants, the mean age was 22.6, 50% were male, and 84.4% were minorities. Only 49.5% of participants were familiar with the related topics before the program, with participants having the least knowledge in gun violence epidemiology (9.5%). The mean test score for knowledge on all related topics after the training was 98.0 out of 100. Most participants were satisfied with the training program (92.1%), felt comfortable seeking help (86.1%), and would promote the program (83.7%). The participants were least comfortable seeking help for depression, particularly among non-African and non-Hispanic minority groups. We concluded that brief online interventions can improve community health outreach, knowledge, awareness, and likelihood of help-seeking and treatment. Tailored training programs are needed to target various populations for prevention and intervention

Ontology-based knowledge representation of experiment metadata in biological data mining

According to the PubMed resource from the U.S. National Library of Medicine, over 750,000 scientific articles have been published in the ~5000 biomedical journals worldwide in the year 2007 alone. The vast majority of these publications include results from hypothesis-driven experimentation in overlapping biomedical research domains. Unfortunately, the sheer volume of information being generated by the biomedical research enterprise has made it virtually impossible for investigators to stay aware of the latest findings in their domain of interest, let alone to be able to assimilate and mine data from related investigations for purposes of meta-analysis. While computers have the potential for assisting investigators in the extraction, management and analysis of these data, information contained in the traditional journal publication is still largely unstructured, free-text descriptions of study design, experimental application and results interpretation, making it difficult for computers to gain access to the content of what is being conveyed without significant manual intervention. In order to circumvent these roadblocks and make the most of the output from the biomedical research enterprise, a variety of related standards in knowledge representation are being developed, proposed and adopted in the biomedical community. In this chapter, we will explore the current status of efforts to develop minimum information standards for the representation of a biomedical experiment, ontologies composed of shared vocabularies assembled into subsumption hierarchical structures, and extensible relational data models that link the information components together in a machine-readable and human-useable framework for data mining purposes

A distribution-free convolution model for background correction of oligonucleotide microarray data

IntroductionAffymetrix GeneChip® high-density oligonucleotide arrays are widely used in biological and medical research because of production reproducibility, which facilitates the comparison of results between experiment runs. In order to obtain high-level classification and cluster analysis that can be trusted, it is important to perform various pre-processing steps on the probe-level data to control for variability in sample processing and array hybridization. Many proposed preprocessing methods are parametric, in that they assume that the background noise generated by microarray data is a random sample from a statistical distribution, typically a normal distribution. The quality of the final results depends on the validity of such assumptions. ResultsWe propose a Distribution Free Convolution Model (DFCM) to circumvent observed deficiencies in meeting and validating distribution assumptions of parametric methods. Knowledge of array structure and the biological function of the probes indicate that the intensities of mismatched (MM) probes that correspond to the smallest perfect match (PM) intensities can be used to estimate the background noise. Specifically, we obtain the smallest q2 percent of the MM intensities that are associated with the lowest q1 percent PM intensities, and use these intensities to estimate background. ConclusionUsing the Affymetrix Latin Square spike-in experiments, we show that the background noise generated by microarray experiments typically is not well modeled by a single overall normal distribution. We further show that the signal is not exponentially distributed, as is also commonly assumed. Therefore, DFCM has better sensitivity and specificity, as measured by ROC curves and area under the curve (AUC) than MAS 5.0, RMA, RMA with no background correction (RMA-noBG), GCRMA, PLIER, and dChip (MBEI) for preprocessing of Affymetrix microarray data. These results hold for two spike-in data sets and one real data set that were analyzed. Comparisons with other methods on two spike-in data sets and one real data set show that our nonparametric methods are a superior alternative for background correction of Affymetrix data

Contributions of differential p53 expression in the spontaneous immortalization of a chicken embryo fibroblast cell line

BACKGROUND: The present study was carried out to determine whether the p53 pathway played a role in the spontaneous immortalization of the SC-2 chicken embryo fibroblast (CEF) cell line that has been in continuous culture for over three years. RESULTS: The SC-2 cell line emerged from an extended crisis period with a considerably slower growth rate than primary CEF cells. The phenotype of the SC-2 cells changed dramatically at about passage 80, appearing smaller than at earlier passages (e.g., passage 43) and possessing a small, compact morphology. This morphological change coincided with an increase in growth rate. Passage 43 SC-2 cells expressed undetectable levels of p53 mRNA, but by passage 95, the levels were elevated compared to primary passage 6 CEF cells and similar to levels in senescent CEF cells. However, the high level of p53 mRNA detected in passage 95 SC-2 cells did not correlate to functional protein activity. The expression levels of the p53-regulated p21(WAF1 )gene were significantly decreased in all SC-2 passages that were analyzed. Examination of the Rb pathway revealed that E2F-1 and p15(INK4b )expression fluctuated with increasing passages, with levels higher in passage 95 SC-2 cells compared to primary passage 6 CEF cells. CONCLUSION: The present study suggests that altered expression of genes involved in the p53 and Rb pathways, specifically, p53 and p21(WAF1), may have contributed to the immortalization of the SC-2 CEF cell line

A gene selection method for GeneChip array data with small sample sizes

<p>Abstract</p> <p>Background</p> <p>In microarray experiments with small sample sizes, it is a challenge to estimate p-values accurately and decide cutoff p-values for gene selection appropriately. Although permutation-based methods have proved to have greater sensitivity and specificity than the regular t-test, their p-values are highly discrete due to the limited number of permutations available in very small sample sizes. Furthermore, estimated permutation-based p-values for true nulls are highly correlated and not uniformly distributed between zero and one, making it difficult to use current false discovery rate (FDR)-controlling methods.</p> <p>Results</p> <p>We propose a model-based information sharing method (MBIS) that, after an appropriate data transformation, utilizes information shared among genes. We use a normal distribution to model the mean differences of true nulls across two experimental conditions. The parameters of the model are then estimated using all data in hand. Based on this model, p-values, which are uniformly distributed from true nulls, are calculated. Then, since FDR-controlling methods are generally not well suited to microarray data with very small sample sizes, we select genes for a given cutoff p-value and then estimate the false discovery rate.</p> <p>Conclusion</p> <p>Simulation studies and analysis using real microarray data show that the proposed method, MBIS, is more powerful and reliable than current methods. It has wide application to a variety of situations.</p

Socially Isolated Cambodians in the US

Community organizations in the United States are severely challenged to serve Cambodian refugees who experience health disparities associated with their traumatic experiences. Community leaders have identified a sub-set of community members of particular concern: those at either end of the age spectrum (elders and young people) who are socially isolated. As part of a larger community-based participatory research project, we conducted a focus group with seven Cambodian community leaders from six cities. The study sought to better understand the phenomenon of social isolation of Cambodian elders and young people in order to inform health promotion efforts. Cambodian leaders expressed keen concern for those community members who rarely seem to leave their homes or interact with the Cambodian community. Prominent themes identified by leaders related to isolation were: a generational pattern; benefits of extended family; health concerns; cultural influences and language; impact of stigma; fear and safety concerns; and lack of sufficient resources. In addition, leaders identified several possible solutions to address the phenomenon of social isolation in their communities. Health promotion efforts with this population should identify isolated individuals and enhance their social connectedness and support networks as part of a larger integrated effort

The hermeneutics of recovery

The widespread use of faith-based and traditional healing for mental disorders within African contexts is well known. However, normative responses tend to fall within two camps: on one hand, those oriented towards the biomedical model of psychiatry stress the abuses and superstition of such healing, whilst critics adopting a more ‘local’ perspective have fundamentally challenged the universalist claims of biomedical diagnostic categories and psychiatric treatments. What seemingly emerges is a dichotomy between those who endorse more ‘universalist’ or ‘relativist’ approaches as an analytical lens to the challenges of the diverse healing strands within African contexts. In this article, we draw upon the resources of philosophy and existing empirical work to challenge the notion that constructive dialogue cannot be had between seemingly incommensurable healing practices in global mental health. First, we suggest the need for much-needed conceptual clarity to explore the hermeneutics of meaning, practice, and understanding, in order to forge constructive normative pathways of dialogue between seemingly incommensurable values and conceptual schemas around mental disorder and healing. Second, we contextualise the complex motives to emphasise difference amongst health practitioners within a competitive healing economy. Finally, we appeal to the notion of recovery as discovery as a fruitful conceptual framework which incorporates dialogue, comparative evaluation, and cross-cultural enrichment across divergent conceptualisations of mental health

Does habitat stability structure intraspecific genetic diversity? It’s complicated...

Regional phylogeographic studies have long been conducted in the southeastern United States for a variety of species. With some exceptions, many of these studies focus on single species or single clades of organisms, and those considering multiple species tend to focus on deep historical breaks causing differentiation. However, in many species more recent factors may be influencing genetic diversity. To understand the roles of historic and contemporary processes in structuring genetic diversity, we reanalyzed existing genetic data from Southeast of North America using approaches gleaned from phylogeographic and landscape genetic literature that were implemented across species including AMOVAs, PCoAs, Species Distribution Modelling, and tests of isolation by distance, environment, and habitat instability. Genetic variance was significantly partitioned by ecoregions, watersheds, and across phylogeographic breaks in the majority of species. Similarly, genetic variation was significantly associated with some combination of geographic or environmental distance or habitat instability in most species. Patterns of genetic variation were largely idiosyncratic across species. While habitat instability over time is significantly correlated with genetic diversity in some species, it appears generally less important than isolation by geographic or environmental distance. Our results suggest that many factors, both historical and contemporary, impact genetic diversity within a species, and more so, that these patterns aren’t always similar in closely related species. This supports the importance of species- specific factors and cautions against assumptions that closely related species will respond to historical and contemporary forces in similar ways