Saint Francis University

About: Saint Francis University is a education organization based out in Loretto, Pennsylvania, United States. It is known for research contribution in the topics: Population & Osteoblast. The organization has 1694 authors who have published 2038 publications receiving 87149 citations.

“Making Our Work of Art a Masterpiece”: The Aesthetics of Evil in Alfred Hitchcock’s Rope

Abstract: In his first Technicolor film, Rope (Hitchcock, Alfred, dir. 1948. Rope. Transatlantic Pictures.), Alfred Hitchcock explores the proposition of murder as a privileged art reserved for the intellectually superior. This article examines Hitchcock’s unorthodox techniques featured in the film, from exceptionally long takes (ranging from four to ten minutes of screen time) to disguised cuts achieved via close-ups of darkened set objects or costumes. Although incongruous with Rope’s more conventional storytelling elements, these daring methods synthesize the film’s ghoulish themes of consumption, decay, and death, evoking feelings of uncomfortable voyeuristic curiosity as Hitchcock toys with the aesthetic possibilities of murder for its own sake.

Victims of Violence and Post-Discharge Adverse Events: A Prospective Modified Trauma Quality Improvement Program (TQIP) Study.

Abstract: Introduction Trauma patients frequently return to an emergency department (ED) soon after discharge; often for non-urgent reasons. Social factors contribute to higher ED usage. At present, there is no standardized system for reporting of ED visits and readmissions among trauma care. We hypothesized that victims of violent crime suffer from many early post-discharge adverse events that has not been captured by current methods. Methods We prospectively consented and enrolled injured patients from January 1st, 2019 to December 31st, 2019. We documented 30-day post-discharge events using post-discharge phone calls and detailed chart abstraction. Patients were categorized as victims of violence (VV) or unintentional traumatic injury (UT). Results During the study period, 444 patients were enrolled. Fifty-one (11.5%) were victims of violence and 393 (88.5%) experienced unintentional injuries. The VV patients were younger (40.10 vs 60.36; p<0.0001), and more predominantly male (92.16% vs 57.51%; p<0.0001). Total injury severity score (ISS), critical care length of stay (LOS), and total LOS were similar. VV patients were more likely discharged home (70.59% vs 55.47%; p=0.0403). They were significantly more likely to return to an emergency department (47.06% vs 23.16%; p<0.0005) and had more total number of ED visits per patient. Readmission rates, however, were not different (21.57% vs 16.28%; p=NS). The VV patients more frequently were underinsured (72.5%, vs 20.6%, p<0.005). Discussion Victims of violence presented to the ED significantly more often, despite similar injury scores, LOS, and being of younger age. Of these patients, only 26.2% of ED presentations resulted in readmission, suggesting the majority of patient complaints may have been able to be managed in an office-based setting. VV had significantly more underinsured or subsidized patients. Victims of violence are vulnerable and may benefit from more resources provided in the early post-discharge period.

Intelligent and Efficient Web-Based Middleware for Data Management in Motif Finding in Gene Regulation

Abstract: Due to the latest developments in next generation sequencing and bioinformatics tools, efficient data management is a major challenge in bioinformatics related research. While the availability of biological data facilitates research in genetics and genomics and there are databases where researchers can access these data, downloading and managing data has been a daring task for individuals with little or no programming expertise. The discovery of the right motif in a DNA sequence has remained a challenge and important problem in the field of bioinformatics and regulatory genomics. While, a number of motif finding algorithms and applications have been developed over the years, the Gibbs sampling algorithm has shown great promise when it comes to discovering motifs in the promoter regions of genes. However Gibbs sampling algorithm does not extend to the processing of biological data obtained directly from laboratory experiments and stored in spread sheet applications, instead it focuses exclusively on processing of data already expressed as DNA sequences. In this work, we develop a middleware that assists researchers to download and manage data from public databases like the National Center for Biotechnology Information (NCBI) databases. This is made possible using Biopython - an open-source Python programming language module. A customized web-based interface is developed in order to assist non-programming scientists to easier access these biological databases. In the proposed middleware, HTML, CSS and PHP technologies are used for the front-end web-based interface and Python is used for the backend data processing. The proposed middleware was used in investigating motifs for gene regulation, where large number of DNA sequences were downloaded from NCBI and analyzed using customized and open-source motif finding tools such as Gibbs Sampler, Meme Chip, Align Ace and an in-house modified Gibbs Sampler implementation. Our web-based middleware was very effective in automating data management, it reduced the overall data download overhead and improved management time, from several days to only a few hours.