University College, 1955-1983, Summer Sessions, 1979-1983

This departmental history was written on the occasion of the UND Centennial in 1983.https://commons.und.edu/departmental-histories/1108/thumbnail.jp

DICER1 Syndrome: \u3cem\u3eDICER1\u3c/em\u3e Mutations in Rare Cancers

DICER1 syndrome is a rare genetic disorder that predisposes individuals to multiple cancer types. Through mutations of the gene encoding the endoribonuclease, Dicer, DICER1 syndrome disrupts the biogenesis and processing of miRNAs with subsequent disruption in control of gene expression. Since the first description of DICER1 syndrome, case reports have documented novel germline mutations of the DICER1 gene in patients with cancers as well as second site mutations that alter the function of the Dicer protein expressed. Here, we present a review of mutations in the DICER1 gene, the respective protein sequence changes, and clinical manifestations of DICER1 syndrome. Directions for future research are discussed

A population-based matched cohort study of major congenital anomalies following COVID-19 vaccination and SARS-CoV-2 infection

Evidence on associations between COVID-19 vaccination or SARS-CoV-2 infection and the risk of congenital anomalies is limited. Here we report a national, population-based, matched cohort study using linked electronic health records from Scotland (May 2020-April 2022) to estimate the association between COVID-19 vaccination and, separately, SARS-CoV-2 infection between six weeks pre-conception and 19 weeks and six days gestation and the risk of [1] any major congenital anomaly and [2] any non-genetic major congenital anomaly. Mothers vaccinated in this pregnancy exposure period mostly received an mRNA vaccine (73.7% Pfizer-BioNTech BNT162b2 and 7.9% Moderna mRNA-1273). Of the 6731 babies whose mothers were vaccinated in the pregnancy exposure period, 153 had any anomaly and 120 had a non-genetic anomaly. Primary analyses find no association between any vaccination and any anomaly (adjusted Odds Ratio [aOR] = 1.01, 95% Confidence Interval [CI] = 0.83-1.24) or non-genetic anomalies (aOR = 1.00, 95% CI = 0.81-1.22). Primary analyses also find no association between SARS-CoV-2 infection and any anomaly (aOR = 1.02, 95% CI = 0.66-1.60) or non-genetic anomalies (aOR = 0.94, 95% CI = 0.57-1.54). Findings are robust to sensitivity analyses. These data provide reassurance on the safety of vaccination, in particular mRNA vaccines, just before or in early pregnancy

A population-based matched cohort study of early pregnancy outcomes following COVID-19 vaccination and SARS-CoV-2 infection

Our thanks to the EAVE II Patient Advisory Group and Sands charity for their support. COPS is a sub-study of EAVE II, which is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE—The Health Data Research Hub for Respiratory Health [MC_PC_19004], which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. Additional support has been provided through Public Health Scotland and Scottish Government DG Health and Social Care and the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation. COPS has received additional funding from Tommy’s charity. S.J.S. is funded by a Wellcome Trust Clinical Career Development Fellowship (209560/Z/17/Z). S.V.K. acknowledges funding from an NRS Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17). K.B. is funded by a Wellcome Senior Research Fellowship (220283/Z/20/Z).Peer reviewedPublisher PD

Not just a matter of size:a hospital-level risk factor analysis of MRSA bacteraemia in Scotland

Background: Worldwide, there is a wealth of literature examining patient-level risk 6 factors for methicillin-resistant Staphylococcus aureus (MRSA) bacteraemia. At the hospital-level it is generally accepted that MRSA bacteraemia is more common in larger hospitals. In Scotland, size does not fully explain all the observed variation among hospitals. The aim of this study was to identify risk factors for the presence and rate of MRSA bacteraemia cases in Scottish mainland hospitals. Specific hypotheses regarding hospital size, type and connectivity were examined. Methods: Data from 198 mainland Scottish hospitals (defined as having at least one inpatient per year) were analysed for financial year 2007-08 using logistic regression (Model 1: presence/absence of MRSA bacteraemia) and Poisson regression (Model 2: rate of MRSA bacteraemia). The significance of risk factors representing various measures of hospital size, type and connectivity were investigated. Results: In Scotland, size was not the only significant risk factor identified for the presence and rate of MRSA bacteraemia. The probability of a hospital having at least one case of MRSA bacteraemia increased with hospital size only if the hospital exceeded a certain level of connectivity. Higher levels of MRSA bacteraemia were associated with the large, highly connected teaching hospitals with high ratios of patients to domestic staff. Conclusions: A hospital’s level of connectedness within a network may be a better measure of a hospital’s risk of MRSA bacteraemia than size. This result could be used to identify high risk hospitals which would benefit from intensified infection control measures

A population-based matched cohort study of major congenital anomalies following COVID-19 vaccination and SARS-CoV-2 infection.

Evidence on associations between COVID-19 vaccination or SARS-CoV-2 infection and the risk of congenital anomalies is limited. Here we report a national, population-based, matched cohort study using linked electronic health records from Scotland (May 2020-April 2022) to estimate the association between COVID-19 vaccination and, separately, SARS-CoV-2 infection between six weeks pre-conception and 19 weeks and six days gestation and the risk of [1] any major congenital anomaly and [2] any non-genetic major congenital anomaly. Mothers vaccinated in this pregnancy exposure period mostly received an mRNA vaccine (73.7% Pfizer-BioNTech BNT162b2 and 7.9% Moderna mRNA-1273). Of the 6731 babies whose mothers were vaccinated in the pregnancy exposure period, 153 had any anomaly and 120 had a non-genetic anomaly. Primary analyses find no association between any vaccination and any anomaly (adjusted Odds Ratio [aOR] = 1.01, 95% Confidence Interval [CI] = 0.83-1.24) or non-genetic anomalies (aOR = 1.00, 95% CI = 0.81-1.22). Primary analyses also find no association between SARS-CoV-2 infection and any anomaly (aOR = 1.02, 95% CI = 0.66-1.60) or non-genetic anomalies (aOR = 0.94, 95% CI = 0.57-1.54). Findings are robust to sensitivity analyses. These data provide reassurance on the safety of vaccination, in particular mRNA vaccines, just before or in early pregnancy

Should I and Can I?: a mixed methods study of clinician beliefs and attitudes in the management of lifestyle risk factors in primary health care

BackgroundPrimary health care (PHC) clinicians have an important role to play in addressing lifestyle risk factors for chronic diseases. However they intervene only rarely, despite the opportunities that arise within their routine clinical practice. Beliefs and attitudes have been shown to be associated with risk factor management practices, but little is known about this for PHC clinicians working outside general practice. The aim of this study was to explore the beliefs and attitudes of PHC clinicians about incorporating lifestyle risk factor management into their routine care and to examine whether these varied according to their self reported level of risk factor management.MethodsA cross sectional survey was undertaken with PHC clinicians (n = 59) in three community health teams. Clinicians\u27 beliefs and attitudes were also explored through qualitative interviews with a purposeful sample of 22 clinicians from the teams. Mixed methods analysis was used to compare beliefs and attitudes for those with high and low levels of self reported risk factor management.ResultsRole congruence, perceived client acceptability, beliefs about capabilities, perceived effectiveness and clinicians\u27 own lifestyle were key themes related to risk factor management practices. Those reporting high levels of risk factor screening and intervention had different beliefs and attitudes to those PHC clinicians who reported lower levels.ConclusionPHC clinicians\u27 level of involvement in risk factor management reflects their beliefs and attitudes about it. This provides insights into ways of intervening to improve the integration of behavioural risk factor management into routine practice

Incorporating Genomics and Bioinformatics across the Life Sciences Curriculum

Undergraduate life sciences education needs an overhaul, as clearly described in the National Research Council of the National Academies’ publication BIO 2010: Transforming Undergraduate Education for Future Research Biologists. Among BIO 2010’s top recommendations is the need to involve students in working with real data and tools that reflect the nature of life sciences research in the 21st century [1]. Education research studies support the importance of utilizing primary literature, designing and implementing experiments, and analyzing results in the context of a bona fide scientific question [1–12] in cultivating the analytical skills necessary to become a scientist. Incorporating these basic scientific methodologies in undergraduate education leads to increased undergraduate and post-graduate retention in the sciences [13–16]. Toward this end, many undergraduate teaching organizations offer training and suggestions for faculty to update and improve their teaching approaches to help students learn as scientists, through design and discovery (e.g., Council of Undergraduate Research [www.cur.org] and Project Kaleidoscope [ www.pkal.org])

A Seriation Approach for Visualization-Driven Discovery of Co-Expression Patterns in Serial Analysis of Gene Expression (SAGE) Data

Background: Serial Analysis of Gene Expression (SAGE) is a DNA sequencing-based method for large-scale gene expression profiling that provides an alternative to microarray analysis. Most analyses of SAGE data aimed at identifying co-expressed genes have been accomplished using various versions of clustering approaches that often result in a number of false positives. Principal Findings: Here we explore the use of seriation, a statistical approach for ordering sets of objects based on their similarity, for large-scale expression pattern discovery in SAGE data. For this specific task we implement a seriation heuristic we term ‘progressive construction of contigs ’ that constructs local chains of related elements by sequentially rearranging margins of the correlation matrix. We apply the heuristic to the analysis of simulated and experimental SAGE data and compare our results to those obtained with a clustering algorithm developed specifically for SAGE data. We show using simulations that the performance of seriation compares favorably to that of the clustering algorithm on noisy SAGE data. Conclusions: We explore the use of a seriation approach for visualization-based pattern discovery in SAGE data. Using both simulations and experimental data, we demonstrate that seriation is able to identify groups of co-expressed genes more accurately than a clustering algorithm developed specifically for SAGE data. Our results suggest that seriation is a usefu