Prospectus, September 23, 1974

ALL SET FOR STUGO ELECTION; Trustees Approve Budget For \u2774-\u2775, Partial Figures On Page 12; 16 Candidates On Ballot For 1st \u2774 Election; PC Counselors Offer More Than Counseling; Attention: Transfer Students; mercy for who?; The Short Circuit; The Kaleidoscope; Letters; Point-Counterpoint: How Do You View America\u27s Future?; Here Are Candidates\u27 Platforms; State House Candidates To Debate Here; Friends; Untitled; Lit. 1.: A Secret Something, Untitled, Rebirth, Everyone\u27s looking for...; \u27DIRT\u27 Comes Off Clean; Really Raunchy Record Review: Eric Clapton, 461 Ocean Boulevard; Meeting For Prospective Debators; Classified Ads; Books: All The President\u27s Men; Republicans To Have Coffee Wednesday; Phi Beta Lambda Meetings Scheduled; APO Chapter Formed Here; In The Dark: That\u27s Entertainment ; Jock Talk; Harriers Perform Well, Abbey Pleased; IM Football Starts Play On 25th; Howell First \u27Fast Freddy\u27; Bowling Bulletin Board; Watching A Counselor At Work; Registration Drive; Cross Country Schedule; Last Chance For Girls IM Football; Fast Freddy\u27s Football Forecast; Callboard; Parkland Events; Summary Of Approved Budget; Vets Elect Officers; A Column By And For Women; Fashion Forecasthttps://spark.parkland.edu/prospectus_1974/1009/thumbnail.jp

The mental health care context and patient characteristics: Implications for provider job satisfaction

This research examines job satisfaction among 282 staff providing mental health care to 574 patients with serious mental illness. The mental health staff worked in 18 Department of Veterans Affairs inpatient and outpatient mental health care units at 12 Veterans Affairs Medical Centers located across the contiguous 48 states. The purpose was to identify (1) aspects of the health care context that were associated with provider job satisfaction and (2) administrative and organizational procedures/interventions that might sustain or improve provider job satisfaction. The association of provider job satisfaction with patients' functional status and symptom severity was tested in multilevel statistical models that accounted for provider and unit characteristics. Provider job satisfaction was found to be greater on smaller units and units with higher patient functioning and lower illness severity. Implications of these results are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45774/1/11414_2005_Article_BF02287373.pd

Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees

Significance Contributions of rare variants to common and complex traits such as type 2 diabetes (T2D) are difficult to measure. This paper describes our results from deep whole-genome analysis of large Mexican-American pedigrees to understand the role of rare-sequence variations in T2D and related traits through enriched allele counts in pedigrees. Our study design was well-powered to detect association of rare variants if rare variants with large effects collectively accounted for large portions of risk variability, but our results did not identify such variants in this sample. We further quantified the contributions of common and rare variants in gene expression profiles and concluded that rare expression quantitative trait loci explain a substantive, but minor, portion of expression heritability.</jats:p

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study

Objective To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. Patients and Methods This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. Results Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001). Conclusions A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer

Disease in Central Valley Salmon: Status and Lessons from Other Systems

Chinook Salmon (Oncorhynchus tshawytscha) are increasingly vulnerable to anthropogenic activities and climate change, especially at their most southern species range in California’s Central Valley. There is considerable interest in understanding stressors that contribute to population decline and in identifying management actions that reduce the impacts of those stressors. Along the west coast of North America, disease has been linked to declining numbers of salmonids and identified as a key stressor resulting in mortality. In the Central Valley, targeted studies have revealed extremely high prevalence of infectious agents and disease. However, there has been insufficient monitoring to understand the effect that disease may have on salmon populations. In order to inform future research, monitoring, and management efforts, a two-day workshop on salmon disease was held at UC Davis on March 14-15, 2018. This paper summarizes the science presented at this workshop, including the current state of knowledge of salmonid disease in the Central Valley and current and emerging tools to better understand its impacts on salmon. We highlight case studies from other systems where successful monitoring programs have been implemented. First, in the Klamath River where the integration of several data collection and modeling approaches led to the development of successful management actions, and second in British Columbia where investment in researching novel technologies led to breakthroughs in the understanding of salmon disease dynamics. Finally, we identify key information and knowledge gaps necessary to guide research and management of disease in Central Valley salmon populations