170 research outputs found

    The Experiences of Being a Full-Time Firefighter: A Qualitative Study

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    Firefighters are exposed to stress both physically and psychologically on a nearly daily basis, which can have a profound effect on their physical and emotional well-being. In the present qualitative study we explore the effects of being a full time firefighter on both personal and professional aspects of life. Full time firefighters from departments around the southwest Ohio region are being interviewed using a semi-structured format. Those interviews are recorded and transcribed for the purpose of analysis, as we look for common themes among these professionals. Our questions specifically focus on the experiences a firefighter has had while being on call, expectations and motivations when first beginning their career, stressors and coping within the job itself, and how their career choice has affected their familial relationships, health habits, hobbies, and personality. Emerging themes include issues regarding sleep, risk-taking behaviors and habits, and the motivation of helping others

    A Qualitative Study of the Motivations and Affiliation Dynamics Involved with a Firefighting Career

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    We explored the experiences of full-time firefighters in the present phenomenological qualitative study, having conducted semi-structured interviews with 26 male full-time firefighters. Their personal constructs of motivation and affiliation were explored and, within the constructs of motivation, three themes emerged. First, firefighters were motivated by a love of the excitement firefighting provides. Second, firefighters reported that the work schedule, which allows them more time at home, was a motivation. Third (and most emphasized by the firefighters) was an altruistic motivation to help others. Under the construct of affiliation, the firefighters reported a strong sense of brotherhood with their shift-partners, and they extended this brotherhood to all firefighters and even other emergency workers. We relate these findings to the existing body of research regarding the relationship between motivation, affiliation and satisfaction of firefighters

    Ice-Cap: A Method for Growing Arabidopsis and Tomato Plants in 96-well Plates for High-Throughput Genotyping

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    It is becoming common for plant scientists to develop projects that require the genotyping of large numbers of plants. The first step in any genotyping project is to collect a tissue sample from each individual plant. The traditional approach to this task is to sample plants one-at-a-time. If one wishes to genotype hundreds or thousands of individuals, however, using this strategy results in a significant bottleneck in the genotyping pipeline. The Ice-Cap method that we describe here provides a high-throughput solution to this challenge by allowing one scientist to collect tissue from several thousand seedlings in a single day 1,2. This level of throughput is made possible by the fact that tissue is harvested from plants 96-at-a-time, rather than one-at-a-time

    The ISB Cancer Genomics Cloud: A Flexible Cloud-Based Platform for Cancer Genomics Research.

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    The ISB Cancer Genomics Cloud (ISB-CGC) is one of three pilot projects funded by the National Cancer Institute to explore new approaches to computing on large cancer datasets in a cloud environment. With a focus on Data as a Service, the ISB-CGC offers multiple avenues for accessing and analyzing The Cancer Genome Atlas, TARGET, and other important references such as GENCODE and COSMIC using the Google Cloud Platform. The open approach allows researchers to choose approaches best suited to the task at hand: from analyzing terabytes of data using complex workflows to developing new analysis methods in common languages such as Python, R, and SQL; to using an interactive web application to create synthetic patient cohorts and to explore the wealth of available genomic data. Links to resources and documentation can be found at www.isb-cgc.or

    A genome-wide association study identifies protein quantitative trait loci (pQTLs)

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    There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10 -57), CCL4L1 (p = 3.9×10-21), IL18 (p = 6.8×10-13), LPA (p = 4.4×10-10), GGT1 (p = 1.5×10-7), SHBG (p = 3.1×10-7), CRP (p = 6.4×10-6) and IL1RN (p = 7.3×10-6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10-40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways. © 2008 Melzer et al

    Lateral flow test engineering and lessons learned from COVID-19

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    The acceptability and feasibility of large-scale testing with lateral flow tests (LFTs) for clinical and public health purposes has been demonstrated during the COVID-19 pandemic. LFTs can detect analytes in a variety of samples, providing a rapid read-out, which allows self-testing and decentralized diagnosis. In this Review, we examine the changing LFT landscape with a focus on lessons learned from COVID-19. We discuss the implications of LFTs for decentralized testing of infectious diseases, including diseases of epidemic potential, the ‘silent pandemic’ of antimicrobial resistance, and other acute and chronic infections. Bioengineering approaches will play a key part in increasing the sensitivity and specificity of LFTs, improving sample preparation, incorporating nucleic acid amplification and detection, and enabling multiplexing, digital connection and green manufacturing, with the aim of creating the next generation of high-accuracy, easy-to-use, affordable and digitally connected LFTs. We conclude with recommendations, including the building of a global network of LFT research and development hubs to facilitate and strengthen future diagnostic resilience

    Deleterious Heteroplasmic Mitochondrial Mutations are associated With an increased Risk of Overall and Cancer-Specific Mortality

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    Mitochondria carry their own circular genome and disruption of the mitochondrial genome is associated with various aging-related diseases. Unlike the nuclear genome, mitochondrial DNA (mtDNA) can be present at 1000 s to 10,000 s copies in somatic cells and variants may exist in a state of heteroplasmy, where only a fraction of the DNA molecules harbors a particular variant. We quantify mtDNA heteroplasmy in 194,871 participants in the UK Biobank and find that heteroplasmy is associated with a 1.5-fold increased risk of all-cause mortality. Additionally, we functionally characterize mtDNA single nucleotide variants (SNVs) using a constraint-based score, mitochondrial local constraint score sum (MSS) and find it associated with all-cause mortality, and with the prevalence and incidence of cancer and cancer-related mortality, particularly leukemia. These results indicate that mitochondria may have a functional role in certain cancers, and mitochondrial heteroplasmic SNVs may serve as a prognostic marker for cancer, especially for leukemia

    Centers For Mendelian Genomics: a Decade of Facilitating Gene Discovery

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    PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients
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