PITTSBURGH’S RACIAL DEMOGRAPHICS: DIFFERENCES AND DISPARITIES

Pittsburgh’s Racial Demographics: Differences and Disparities provides indicators of quality of life by race and ethnicity in the Pittsburgh region. Data are provided for four groups (Whites, African Americans, Asians, and Hispanics) and for four geographic areas (city of Pittsburgh, Allegheny County, Pittsburgh Metropolitan Statistical Area, and the U.S.). The most recent data available for the Pittsburgh area and the nation were used in this report. In some instances, however, only data from the 2000 census were available to make comparisons. It is also the case that data were not available on all of our topic areas in the same years. It is our hope to update this report every three years, particularly if the American Community Survey (which is designed to replace the decennial census) produces regular, reliable data by race for cities, counties, and regions

2001 AAPP Monograph Series

The African American Professors Program (AAPP) at the University of South Carolina is pleased to produce this premier edition of its annual monograph series. It is fitting that the program assume a leadership role in promoting scholarly products that will prove to be useful in future research efforts by faculty and students in higher education. Scholars who have contributed manuscripts for this monograph are to be commended for adding this additional responsibility to their academic workload. Writing across disciplines adds to the intellectual diversity of these papers. From neophytes, relatively speaking, to an array of very experienced individuals, the chapters have been researched and, comprehensively, written. AAPP was created in 1997 under the leadership of Drs. Aretha B. Pigford and Leonard 0. Pellicer, Department of Educational Leadership and Policies. It was designed to address the underrepresentation of African American professors on college and university campuses. Its mission is to expand the pool of these professors in critical academic and research areas. Sponsored by the University of South Carolina, the W. K. Kellogg Foundation, and the South Carolina General Assembly, the program recruits students with bachelor\u27s, master\u27s, and doctoral degrees for disciplines in which African Americans, currently, are underrepresented. An important component of the program is the mentoring experience that is provided. Each student is assigned to a mentor professor who guides the student through a selected academic program and provides various learning experiences. When possible, the mentor serves as chair of the student\u27s doctoral committee. The mentor, also, provides opportunities for the student to team teach, conduct research, and co-author publications. Students have opportunities to attend committee, faculty, and professional meetings, as well as engage in a range of activities that characterize professional life in academia. Scholars enrolled in the program, also, are involved in programmatic and institutional workshops, independent research, and program development. The establishment or genesis of this monograph series is seen as responding to an opportunity to be sensitive to an academic expectation of graduates as they pursue career placement and, also, one that allows for the dissemination of AAPP products to a broader community. We hope that you, likewise, will read this premier monograph of the African American Professors Program with enthusiasm or enlightenment. John McFadden, Ph.D. The Benjamin Elijah Mays Professor Director, African American Professors Program University of South Carolinahttps://scholarcommons.sc.edu/mcfadden_monographs/1005/thumbnail.jp

2002 AAPP Monograph Series: African American Professors Program

The African American Professors Program (AAPP) at the University of South Carolina is pleased to produce the second edition of its annual monograph series. It is fitting that the program contrives to assume a leadership role in promoting scholarly products that prove to be useful in research endeavors by faculty and students in higher education. Scholars who have contributed manuscripts for this monograph are to be commended for adding this additional responsibility to their academic workload. Writing across disciplines adds to the intellectual diversity of these papers. From neophytes, relatively speaking, to an array of very experienced individuals, the chapters have been researched and comprehensively written. Founded in 1997 through the Department of Educational Leadership and Policies in the College of Education, AAPP was designed to address the underrepresentation of African American professors on college and university campuses. Its mission is to expand the pool of these professors in critical academic and research areas. Sponsored by the University of South Carolina, the W.K. Kellogg Foundation, and the South Carolina General Assembly, the program recruits students with bachelor\u27s, master\u27s, and doctoral degrees for disciplines in which African Americans, currently, are underrepresented. An important component of the program is the mentoring experience that is provided. Each student is assigned to a mentor professor who guides the student through a selected academic program and provides various learning experiences. When possible, the mentor serves as chair of the student\u27s doctoral committee. The mentor, also, provides opportunities for the student to team teach, conduct research, and co-author publications. Students have opportunities to attend committee, faculty, and professional meetings, as well as to engage in a range of activities that characterize professional life in academia. Scholars enrolled in the program also are involved in programmatic and institutional workshops, independent research, and program development. The continuation of this monograph series is seen as responding to an opportunity to be sensitive to an academic expectation of graduates as they pursue career placement and, also, one that allows for the dissemination of AAPP products to a broader community. We hope that you will read this monograph of the African American Professors Program with enthusiasm or enlightenment. John McFadden, Ph.D. The Benjamin Elijah Mays Professor Director, African American Professors Program University of South Carolinahttps://scholarcommons.sc.edu/mcfadden_monographs/1000/thumbnail.jp

Coordination and resource-related difficulties encountered by Quebec's public health specialists and infectious diseases/medical microbiologists in the management of A (H1N1) - a mixed-method, exploratory survey

<p>Abstract</p> <p>Background</p> <p>In Quebec, the influenza A (H1N1) pandemic was managed using a top-down style that left many involved players with critical views and frustrations. We aimed to describe physicians' perceptions - infectious diseases specialists/medical microbiologists (IDMM) and public health/preventive medicine specialists (PHPMS) - in regards to issues encountered with the pandemics management at the physician level and highlight suggested improvements for future healthcare emergencies.</p> <p>Methods</p> <p>In April 2010, Quebec IDMM and PHPMS physicians were invited to anonymously complete a web-based learning needs assessment. The survey included both open-ended and multiple-choice questions. Descriptive statistics were used to report on the frequency distribution of multiple choice responses whereas thematic content analysis was used to analyse qualitative data generated from the survey and help understand respondents' experience and perceptions with the pandemics.</p> <p>Results</p> <p>Of the 102 respondents, 85.3% reported difficulties or frustrations in their practice during the pandemic. The thematic analysis revealed two core themes describing the problems experienced in the pandemic management: coordination and resource-related difficulties. Coordination issues included communication, clinical practice guidelines, decision-making, roles and responsibilities, epidemiological investigation, and public health expert advisory committees. Resources issues included laboratory resources, patient management, and vaccination process.</p> <p>Conclusion</p> <p>Together, the quantitative and qualitative data suggest a need for improved coordination, a better definition of roles and responsibilities, increased use of information technologies, merged communications, and transparency in the decisional process. Increased flexibility and less contradiction in clinical practice guidelines from different sources and increased laboratory/clinical capacity were felt critical to the proper management of infectious disease emergencies.</p

Development and evolution of dentition pattern and tooth order in the Skates and Rays (Batoidea; Chondrichthyes)

Shark and ray (elasmobranch) dentitions are well known for their multiple generations of teeth, with isolated teeth being common in the fossil record. However, how the diverse dentitions characteristic of elasmobranchs form is still poorly understood. Data on the development and maintenance of the dental patterning in this major vertebrate group will allow comparisons to other morphologically diverse taxa, including the bony fishes, in order to identify shared pattern characters for the vertebrate dentition as a whole. Data is especially lacking from the Batoidea (skates and rays), hence our objective is to compile data on embryonic and adult batoid tooth development contributing to ordering of the dentition, from cleared and stained specimens and micro-CT scans, with 3D rendered models. We selected species (adult and embryonic) spanning phylogenetically significant batoid clades, such that our observations may raise questions about relationships within the batoids, particularly with respect to current molecular-based analyses. We include developmental data from embryos of recent model organisms Leucoraja erinacea and Raja clavata to evaluate the earliest establishment of the dentition. Characters of the batoid dentition investigated include alternate addition of teeth as offset successional tooth rows (versus single separate files), presence of a symphyseal initiator region (symphyseal tooth present, or absent, but with two parasymphyseal teeth) and a restriction to tooth addition along each jaw reducing the number of tooth families, relative to addition of successor teeth within each family. Our ultimate aim is to understand the shared characters of the batoids, and whether or not these dental characters are shared more broadly within elasmobranchs, by comparing these to dentitions in shark outgroups. These developmental morphological analyses will provide a solid basis to better understand dental evolution in these important vertebrate groups as well as the general plesiomorphic vertebrate dental condition

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis

The added value of incorporating information from repeated blood pressure and cholesterol measurements to predict cardiovascular disease (CVD) risk has not been rigorously assessed. We used data on 191,445 adults from the Emerging Risk Factors Collaboration (38 cohorts from 17 countries with data encompassing 1962-2014) with more than 1 million measurements of systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative mean values of repeated measurements and summary measures from longitudinal modeling of the repeated measurements were compared with models using measurements from a single time point. Risk discrimination (Cindex) and net reclassification were calculated, and changes in C-indices were meta-analyzed across studies. Compared with the single-time-point model, the cumulative means and longitudinal models increased the C-index by 0.0040 (95% confidence interval (CI): 0.0023, 0.0057) and 0.0023 (95% CI: 0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared with the single-time-point model, overall net reclassification improvements were 0.0369 (95% CI: 0.0303, 0.0436) for the cumulative-means model and 0.0177 (95% CI: 0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction