Academic literature on the topic 'University of Arkansas for Medical Sciences. College of Medicine'

Abstract The emergence of resistant bacteria forced the medical and animal agriculture communities to rethink how antibiotics are used. In Arkansas, medicated feed is mostly used to treat or control Anaplasmosis in beef cattle herds. Bovine Anaplasmosis is a tick-borne disease caused by the rickettsial bacteria, Anaplasma marginale. This disease causes over $300 million in losses annually for the U.S. cattle industry. With beef cattle being the fifth largest agricultural commodity in Arkansas, it is important to know the prevalence of Anaplasmosis infection in the state. The project described is a collaborative effort between the University of Arkansas-Fayetteville campus, the University of Arkansas Extension, and the Kansas State University (KSU) College of Veterinary Medicine. Extension agents from 33 Arkansas counties were trained to recruit producers for the study and to coordinate sample collection. On the day of blood collection, Extension agents discussed the purpose of the project and appropriate disclosures with the producers. A total of 578 mature beef cattle were randomly selected from six geographical regions for sampling between the months of November 2019 and February 2020. Both whole blood and serum samples were collected from each animal. PCR testing was completed at the KSU College of Veterinary Medicine andcELISA testing was completed at the University of Arkansas Veterinary Diagnostic Laboratory. Blood samples from 335 cattle (58.7%) were positive for Anaplasmosis on at least one test with the majority of animals testing positive (229; 68.4%) on both the cELISA and PCR tests. Rates of regional prevalence ranged from 36.7% to 93.8%. The overall results were discussed with Extension agents via Zoom prior to discussing results with individual producers. Data from this study were added to previous surveillance data collected by Kansas State University and will direct Extension education efforts pertaining to Anaplasmosis management in regional beef cattle herds.

Abstract Introduction: Focal lesions (FL) are detected by magnetic resonance imaging (MRI) and positron emission tomography (PET) and precede the development of osteolytic lesions in multiple myeloma (MM). FLs are absent in most patients with benign disease and their detection is associated with earlier disease progression suggesting that a distinct MM cell niche in the FLs is associated with conditions that promote the transition to MM. Studying the nature of this niche can significantly enhance our understanding of the biology and progression of MM. Methods: Random BM aspiration samples were taken from the posterior superior iliac crest whereas FL samples were sampled under CT guidance from newly diagnosed MM patients. Gene expression profiling (GEP) was performed on CD138-enriched plasma cells (PC, n=170) and non-enriched BM trephine biopsies (n=49) from paired RBM and FL samples from the same patients and from unrelated RBM cases with no detectable FL (n=79). 8-multicolor flow cytometry (MFC) analysis was performed on 25 paired PC samples and selected genes were validated using immunohistochemistry (IHC). Results: AComparison of GEP from paired RBM-PC and FL-PC showed discrepancies in GEP-based risk score and molecular subgroups and lower Polyclonal-PC score (reflecting the proportion of normal PC infiltration) in FL-PC samples (p=0.0001). There is 89% concordance for the GEP70 risk signature with 10 patients having low-risk PCs in RBM but high-risk PCs in the paired FL, and 8 patients showing high-risk PCs in RBM but low-risk PCs in the paired FL samples. In this setting progression-free and overall survival are mediated by the presence of a high-risk score in either sample. When molecular subgroups were identified there were more high risk-associated PR cases in FL samples (n=28) compared to only 16 PR cases in respective paired RBM-PC samples (p=0.005). Flow cytometry data from 25 paired MM cell samples showed consistently lower surface expression of CD138 in FL (p=0.0001). Cases with detectable CD81 had lower CD81 expression on FL-PC (p=0.03). Discrepancies were also observed in cell surface expression of CD38 and CD45. Pathway's analysis was based on of 523 differentially expressed genes between paired FL and RBM-PC samples (n=170; FDR<0.001) after adjusting for the level of normal PC infiltration. The top KEGG-based pathways enrichment analysis were associated with energy and drug metabolism, survival, cell-cell contact interaction and factors involved in activity of dexamethasone (e.g. NR3C1) and IMiDs (e.g. IZKF1), Figure 1A. Differential expression of ABCA1, the most upregulated gene in FL, was validated by IHC in biopsies. To test whether PCs from patients with FL have specific characteristics irrespective of their location, we compared RBM-PC GEP with RBM-PC GEP of unrelated patients with no detectable FLs. We detected increased expression of cell cycle genes in PC from patients with detectable FL. Reduced osteogenesis and interaction with mesenchymal and vascular lineages have been linked with MM cell phenotypes and dissemination in BM. Microenvironmental reactive stroma (e.g. POSTN, collagen genes) and angiogenic (e.g. EDNRA) gene signatures were significantly upregulated in non-enriched FL biopsies albeit expected high proportion of PC in this site, whereas osteoblastic markers such as BGLAP and IBSP were underexpressed in these samples in comparison to paired non-enriched RBM trephine biopsies, Figure 1B. Conclusions: PC in FL and RBM sites of the same patient are heterogeneous in their phenotype, molecular classification based on risk-score and subgroups, and pathways. GEP signatures of MM cells and the stroma in this niches stressing the biological and clinical relevance of FL as a hallmark in MM. Disclosures Yaccoby: University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Qu:Cancer Research and Biostatistics: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Jethava:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Mitchell:Cancer Research and Biostatistics: Employment. Heuck:Millenium: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Other: Advisory Board; Foundation Medicine: Honoraria. Davies:Millenium: Consultancy; Janssen: Consultancy; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Onyx: Consultancy. Crowley:Cancer Research and Biostatistics: Employment. Weinhold:Janssen Cilag: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; Weismann Institute: Honoraria; MMRF: Honoraria; University of Arkansas for Medical Sciences: Employment; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Background: Medical school learning communities benefit students. The College of Medicine (COM) at the University of Arkansas for Medical Sciences (UAMS) provides medical students with academic, professional, and personal support through a learning community (LC) made of 7 academic houses. Objectives: To evaluate the effectiveness of the academic house model at UAMS utilizing a mixed-methods survey. The aims were to: (1) assess student experience and satisfaction with academic houses, (2) describe the realms of advising and guidance, and (3) identify areas for improvement. Method: An online survey was assigned to 723 COM students (all students enrolled, first through fourth years) at UAMS in March 2019. The survey was comprised of 25 items (10 multiple-choice, 8 on the Likert scale, and 7 open-ended questions). Data was depicted using frequency and percentages and/or thematic review of free-form responses. Results: The survey response rate was 31% (227 students). The majority of students responding (132, 58.1%) attended 2 or more face-to-face meetings with the faculty advisor within the preceding year. However, 27 (11.9%) students did not have any meetings. Approximately two-thirds of the respondents were satisfied or very satisfied with the guidance and direction provided by their advisors [very satisfied (n = 83; 36.6%); satisfied (n = 77; 33.9%)]. Themes that emerged from student generated areas for improvement include time constraints, advisor/advisee interest mismatch, and perceived inadequacy of advising content/connections. Conclusions: This study confirms the effectiveness of the LC model for advising and mentoring in the COM at UAMS. Uniquely, this study identifies not only learners’ satisfaction with their LC but also highlights areas for improvement which are widely generalizable and important to consider for institutions with or planning to start an LC.

Recent studies of attitudes toward fear of death and dying among under-graduates have been sparse. Hoelter's Multidimensional Fear of Death Scale (MFODS) [1] was developed among undergraduates to discern fear of death or death anxiety. The purposes of this study were to 1) examine the factor structure and reliability estimates of Hoelter's MFODS in a contemporary sample of college students and 2) compare the attitudes of nursing majors with those of other college students at a small liberal arts university in rural, southwestern Arkansas. It was hypothesized that the 1) attitudes of nursing majors would differ from those preparing for other careers and 2) attitudes of nursing majors and other undergraduates would differ at each level of student status (freshman through senior years). This was a descriptive study surveying attitudes among students who were recruited through cooperating faculty in courses serving all undergraduate majors. Informed consents were signed after review of the introductory information by the students. The sample consisted of 405 students, ages eighteen to sixty-four years (mean age 26 years); 27 percent were males and 73 percent females. Nursing students comprised 24 percent of the sample and were marginally different demographically from other students. The MFODS (a 42-item, pencil-and-paper instrument including a demographic questionnaire) was administered in one classroom session. Factor structure was derived using principal components analysis with varimax rotation and revealed eight subscales accounting for 21 percent of the variance. The total scale alpha reliability was .88, with eight subscale alpha reliabilities ranging from .75 to .85. The results of comparisons of nursing students with others revealed differences on three subscales and the total MFODS. Nursing students were less fearful of the dead, less fearful of being conscious while dead, and less fearful of being destroyed after death. Analyses of students by levels of student status revealed that freshman nursing students were most fearful of the dead and junior nursing students were most fearful of discovering a dead body. Other undergraduate freshmen were most fearful of events after death such as treatment of the body after death, being practiced on by medical students, being embalmed, being conscious in a morgue, and the thought of never being found after death. There were no significant findings among comparisons of nursing and other undergraduate majors by level of student status (freshman through senior). It was concluded the MFODS was a reliable instrument. Nursing students displayed significant attitudinal differences as compared to other students examined. Students who study nursing may bring greater acceptance of death and the dying process to health care arenas. Longitudinal comparison studies and qualitative analyses of attitudes were recommended to further elucidate professional socialization processes.

Abstract Objectives To identify possible mechanisms involved in the development and progression of NAFLD through protein expression (shotgun proteomics) analysis on liver samples of obese Zucker rats fed with either casein (CAS) or soy protein isolate (SPI) during 8 and 16 weeks. Methods 7 weeks old rats (n = 8–9 per group) were randomly assigned to an either CAS-based or a SPI-based diet. Rats were sacrificed after 8 weeks or 16 weeks of SPI feeding. Livers were immediately obtained and stored at −80 C. Ingenuity Pathway Analysis (IPA) software was used to facilitate interpretation of proteomics data. Predictions of activation or inhibition of molecules in the data was made based on activation z-score and P value of overlap (P &lt; 0.05). Activation z-scores &gt; 2.0 indicate that a molecule is activated, whereas activation z-scores of &lt; −2.0 indicate that a target molecule is inhibited. Results Upstream regulator analysis by IPA revealed 6 molecules predicted to be activated (z-scores between 2 and 2.8) and 9 inhibited (z-scores between −2 and −2.6) in SPI vs CAS-fed rats in proteomics data at 8 weeks of SPI feeding. In contrast, at 16 weeks of SPI feeding there were 12 molecules activated (z-scores between 2 and 2.5) and 18 inhibited (z-scores between −2 and −2.8) in SPI vs CAS-fed. All p values were &lt;0.05. Regulator effects analysis also revealed that some of these molecules would be participating, directly or indirectly, in the inhibition of the immune response of cells (such as IL27 and CSF2) and synthesis of lipids (CEBPA, Ins1 and IRF8) in SPI-fed rats. Conclusions These molecules and their downstream target proteins may provide clues by which soy protein produces the observed attenuation of liver steatosis that can be tested in future experiments in this obese rat model. Funding Sources This study was supported in part by the College of Medicine's University Medical Group (RH) and the Arkansas Biosciences Institute (WB, RH).

Purpose: Prescription stimulant use as "cognitive enhancers" has been described among undergraduate college students. However, the use of prescription stimulants among future health care professionals is not well characterized. This study was designed to determine the prevalence of prescription stimulant misuse among students at an academic health sciences center. Method: Electronic surveys were e-mailed to 621 medical, pharmacy, and respiratory therapy students at East Tennessee State University for four consecutive weeks in fall 2011. Completing the survey was voluntary and anonymous. Surveys asked about reasons for, frequency of, and side effects of nonprescription misuse of prescription stimulants. Given the sensitive material, an opportunity to win one of ten $50 gift cards was used as an incentive. Results: Three hundred seventy-two (59.9%) students completed the survey from three disciplines (47.6% medical, 70.5% pharmacy, and 57.6% respiratory therapy). Overall, 11.3% of responders admitted to misusing prescription stimulants. There was more misuse by respiratory therapy students, although this was not statistically significant (10.9% medicine, 9.7% pharmacy, 26.3% respiratory therapy; P = .087). Reasons for prescription stimulant misuse included to enhance alertness/energy (65.9%), to improve academic performance (56.7%), to experiment (18.2%), and to use recreationally/get high (4.5%). Conclusions: Prescription stimulant misuse was prevalent among participating students, but further research is needed to describe prevalence among future health care workers more generally. The implications and consequences of such misuse require further study across professions with emphasis on investigating issues of academic dishonesty (e.g., "cognitive enhancement"), educational quality, and patient safety or health care quality.

Indiana University-Purdue University Indianapolis (IUPUI)
Background. Traditionally, departmental appointment type (basic science or clinical) and/or degree earned (PhD, MD, or MD-PhD) have served as proxies for how we conceptualize clinical and basic science faculty. However, the landscape in which faculty work has considerably changed and now challenges the meaning of these cohorts. Within this context I introduce a behavior-based role variable that is defined by how faculty spend their time in four academic activities: teaching, research, patient care, and administrative duties. Methods. Two approaches to role were compared to department type and degree earned in terms of their effects on how faculty report their perceptions and experiences of faculty vitality and its related constructs. One approach included the percent of time faculty spent engaged in each of the four academic activities. The second approach included role groups described by a time allocation rubric. This study included faculty from four U.S. medical schools (N = 1,497) and data from the 2011 Indiana University School of Medicine Faculty Vitality Survey. Observed variable path analysis evaluated models that included traditional demographic variables, the role variable, and faculty vitality constructs (e.g., productivity, professional engagement, and career satisfaction). Results. Role group effects on faculty vitality constructs were much stronger than those of percent time variables, suggesting that patterns of how faculty distribute their time are more important than exactly how much time they allocate to single activities. Role group effects were generally similar to, and sometimes stronger than, those of department type and degree earned. Further, the number of activities that faculty participate in is as important a predictor of how faculty experience vitality constructs as their role groups. Conclusions. How faculty spend their time is a valuable and significant addition to vitality models and offers several advantages over traditional cohort variables. Insights into faculty behavior can also show how institutional missions are (or are not) being served. These data can inform hiring practices, development of academic tracks, and faculty development interventions. As institutions continue to unbundle faculty roles and faculty become increasingly differentiated, the role variable can offer a simple way to study faculty, especially across multiple institutions.

The proper education of a doctor must not be restricted to the sciences but rather must include study of the humanities and the social sciences. This is best achieved by having an interactive and physically integrally located medical school. Not only must medicine be based on modern biology, a biology education is also essential for all college undergraduates. One cannot consider genetic engineering if one does not understand what a gene is and how it is controlled. Unique to medical education are the places of medical practice. Besides providing a site of learning, the teaching hospital must provide excellent patient care and be responsive to the surrounding community. The university must embrace these other goals. Society should provide high quality health care for all. This cannot be achieved if only the lowest cost is the goal. While resources are limited, economic efficiency cannot be the only parameter.

The expansion of the functions of medical schools since mid-century has had many unanticipated and adverse consequences for medical education. As a result, medical schools have lost some of their societal support. In the years since 1900, medical schools have made major changes in their structure in order to solve specific educational problems. University hospitals were built to provide clinical training in hospitals that emphasized education and research rather than patient care. Full-time clinical faculty members were employed in order to professionalize a role previously occupied by part-time practitioner-educators. Biomedical research was undertaken to enable faculty members to advance medical knowledge and enhance their skills as educators. Internships and residencies became restricted to hospitals affiliated with medical schools to replace the poorly supervised practical experience provided in community hospitals with a more structured education administered by professional educators. Each of these changes assumed that medical schools could be removed from the hurly-burly of professional life and made to fit the model of the liberal arts college. This assumption failed to recognize the fundamental differences between the two types of institutions. In liberal arts education, the body of knowledge taught to students need not be suitable for practical application in the community. In many fields, like most of the humanities, it has rarely been used outside of institutions of higher education. In others, like the social sciences, the knowledge has been sufficiently tentative that its direct application has been problematic. In still others, like most natural sciences, the knowledge has been so highly specialized that it could not provide a basis for viable careers. As a result, most faculty members in the liberal arts and sciences have spent their careers in teaching and research without the option of nonacademic employment in their disciplines. Medical schools, on the other hand, have continually influenced and been influenced by the practice of medicine in the community. The knowledge taught in medical schools has affected the way that physicians have practiced medicine, but it has also been tested by practitioners and fed back to the faculty for modification and refinement.

By the end of World War I, the basic structures of undergraduate medical education in both Europe and America were largely in place. Future practitioners on both sides of the Atlantic now began their training with a lengthy preparation in liberal studies, with special attention to physics, chemistry, and biology, then studied for two or more years in laboratory based courses in the preclinical medical sciences followed by a like period of clinical study, and finally spent at least a year in acquiring practical, hands-on training in a hospital. With few changes, except for the growth of postgraduate education, this basic pattern prevailed everywhere in the interwar years before 1945. In the transatlantic nations, in short, these were years of consolidation of patterns formed well before 1914. The study of medicine now consumed a minimum of five years beyond the school-leaving or college experience and frequently took six to ten years to complete. Except for the hospital schools of London, nearly every medical school in the Western world was attached to a university. Almost no school of medicine was without its teaching hospital where training students was a primary concern. Governments everywhere played an ever larger role in setting basic requirements and providing financial support of medical education. Physicians’ associations became more and more powerful and sometimes dominant in setting standards of education and licensure. And in these postwar years, the practice of medicine became an almost wholly middle-class occupation, exacting high standards of preparation and social expectation and open to only the most exceptional among the less affluent. The costs of study were rising so steeply that it was largely unavailable to the poor, even in the United States. The national differences of a quarter-century before, though evened out in many particulars, were still discernible in 1920. The war, after all, permitted no major changes in instruction, equipment, or curriculum in Europe, and reform efforts after the war were hampered by the need to restore and rebuild.