The University of New Hampshire Engaged Scholars Academy: Instilling in Faculty Principles of Effective Partnership

Over the last decade, the University of New Hampshire (UNH) has promoted mutually beneficial partnerships between faculty and community partners vis-à-vis the Engaged Scholars Academy (ESA), a faculty development program aimed at enhancing faculty understanding of the principles of partnership and engaged scholarship. This research seeks to determine whether and how the ESA has impacted faculty-community partnerships around engaged scholarship. Findings suggest that Engaged Scholar Academy participants – as compared to non-participants – have a deeper understanding of the principles of partnership, are more likely to feel their scholarship is enhanced, spend more time with partners, engage their partners throughout the process of inquiry, and focus more on sustaining partnership outcomes

The screening power of methylenetetrahydrofolate reductase C677T polymorphism versus plasma homocysteine concentration in patients with stenosis of the internal carotid artery

BACKGROUND: Hyperhomocysteinemia is an important and independent risk factor for vascular disease. About 35% of patients with stroke and 47% of patients with peripheral arterial disease have elevated plasma homocysteine (HCY) concentrations. The relationship between plasma HCY and the methylentetrahydrofolate reductase (MTHFR) C677T polymorphism is still unclear, especially in regard to screening/diagnostic power. METHODS: This case-control study was performed on 96 patients, who underwent surgery due to asymptomatic or symptomatic high grade stenosis of the internal carotid artery (ICA), and 96 healthy age and sex-matched, controls. Plasma HCY concentration was determined using a commercial kit for fully automated analysis (AxSYM, Abbott). The C677T polymorphism of the MTHFR-gene was assessed by PCR. RESULTS: The mean plasma HCY concentration was significantly higher in the group with stenosis of ICA compared to the controls, 12.43 ± 6.96 μM and 10.16 ± 3.16 μM, respectively, (p < 0.05). An HCY plasma concentration of 1.5 SD above the mean value of the control group, was defined as cut-off for a pathological versus physiological plasma concentration. The sensitivity and specificity of HCY was 0.27 and 0.94, respectively. The positive predictive value was 0.82. There was no significant difference in the frequency of the MTHFR 677 CT and TT genotype between patients and controls (47% vs. 47% and 8.3% vs. 11.4%, respectively). Carriers of the T-allele (CT and TT genotypes) have significantly higher plasma HCY concentrations than CC patients, 14.1 ± 7.6 μM and 10.29 ± 5.2 μM, respectively, p < 0.05. Sensitivity and specificity of the MTHFR C677T polymorphism (T-allele) were 0.56 and 0.40, respectively. The positive predictive value was 0.48. There was no significant difference in plasma HCY or genotype frequency of the MTHFR C677T polymorphism between asymptomatic and symptomatic patients. CONCLUSION: Our study shows that in a population with a given pretest disease probability of 50%, the determination of plasma HCY concentration, with a positive predictive value of 0.82, is more suitable for screening of patients at risk than analysis of the MTHFR C677T polymorphism

Quantifying the economic cost of antibiotic resistance and the impact of related interventions rapid methodological review, conceptual framework and recommendations for future studies

BACKGROUND: Antibiotic resistance (ABR) poses a major threat to health and economic wellbeing worldwide. Reducing ABR will require government interventions to incentivise antibiotic development, prudent antibiotic use, infection control and deployment of partial substitutes such as rapid diagnostics and vaccines. The scale of such interventions needs to be calibrated to accurate and comprehensive estimates of the economic cost of ABR. METHODS: A conceptual framework for estimating costs attributable to ABR was developed based on previous literature highlighting methodological shortcomings in the field and additional deductive epidemiological and economic reasoning. The framework was supplemented by a rapid methodological review. RESULTS: The review identified 110 articles quantifying ABR costs. Most were based in high-income countries only (91/110), set in hospitals (95/110), used a healthcare provider or payer perspective (97/110), and used matched cohort approaches to compare costs of patients with antibiotic-resistant infections and antibiotic-susceptible infections (or no infection) (87/110). Better use of methods to correct biases and confounding when making this comparison is needed. Findings also need to be extended beyond their limitations in (1) time (projecting present costs into the future), (2) perspective (from the healthcare sector to entire societies and economies), (3) scope (from individuals to communities and ecosystems), and (4) space (from single sites to countries and the world). Analyses of the impact of interventions need to be extended to examine the impact of the intervention on ABR, rather than considering ABR as an exogeneous factor. CONCLUSIONS: Quantifying the economic cost of resistance will require greater rigour and innovation in the use of existing methods to design studies that accurately collect relevant outcomes and further research into new techniques for capturing broader economic outcomes

Infant hospitalisations and fatalities averted by the maternal pertussis vaccination programme in England, 2012-2017: Post-implementation economic evaluation

In October 2012, a maternal pertussis vaccination programme was implemented in England following an increased incidence and mortality in infants. We evaluated the cost-effectiveness of the programme by comparing pertussis-related infant hospitalisations and deaths in 2012-2017 with non-vaccination scenarios. Despite considerable uncertainties, findings support the cost-effectiveness of the programme

Metabolomics methods for the synthetic biology of secondary metabolism

Many microbial secondary metabolites are of high biotechnological value for medicine, agriculture, and the food industry. Bacterial genome mining has revealed numerous novel secondary metabolite biosynthetic gene clusters, which encode the potential to synthesize a large diversity of compounds that have never been observed before. The stimulation or “awakening” of this cryptic microbial secondary metabolism has naturally attracted the attention of synthetic microbiologists, who exploit recent advances in DNA sequencing and synthesis to achieve unprecedented control over metabolic pathways. One of the indispensable tools in the synthetic biology toolbox is metabolomics, the global quantification of small biomolecules. This review illustrates the pivotal role of metabolomics for the synthetic microbiology of secondary metabolism, including its crucial role in novel compound discovery in microbes, the examination of side products of engineered metabolic pathways, as well as the identification of major bottlenecks for the overproduction of compounds of interest, especially in combination with metabolic modeling. We conclude by highlighting remaining challenges and recent technological advances that will drive metabolomics towards fulfilling its potential as a cornerstone technology of synthetic microbiology

Functional Analysis of the Phycomyces carRA Gene Encoding the Enzymes Phytoene Synthase and Lycopene Cyclase

Phycomyces carRA gene encodes a protein with two domains. Domain R is characterized by red carR mutants that accumulate lycopene. Domain A is characterized by white carA mutants that do not accumulate significant amounts of carotenoids. The carRA-encoded protein was identified as the lycopene cyclase and phytoene synthase enzyme by sequence homology with other proteins. However, no direct data showing the function of this protein have been reported so far. Different Mucor circinelloides mutants altered at the phytoene synthase, the lycopene cyclase or both activities were transformed with the Phycomyces carRA gene. Fully transcribed carRA mRNA molecules were detected by Northern assays in the transformants and the correct processing of the carRA messenger was verified by RT-PCR. These results showed that Phycomyces carRA gene was correctly expressed in Mucor. Carotenoids analysis in these transformants showed the presence of ß-carotene, absent in the untransformed strains, providing functional evidence that the Phycomyces carRA gene complements the M. circinelloides mutations. Co-transformation of the carRA cDNA in E. coli with different combinations of the carotenoid structural genes from Erwinia uredovora was also performed. Newly formed carotenoids were accumulated showing that the Phycomyces CarRA protein does contain lycopene cyclase and phytoene synthase activities. The heterologous expression of the carRA gene and the functional complementation of the mentioned activities are not very efficient in E. coli. However, the simultaneous presence of both carRA and carB gene products from Phycomyces increases the efficiency of these enzymes, presumably due to an interaction mechanism

ICR142 Benchmarker: evaluating, optimising and benchmarking variant calling performance using the ICR142 NGS validation series.

Evaluating, optimising and benchmarking of next generation sequencing (NGS) variant calling performance are essential requirements for clinical, commercial and academic NGS pipelines. Such assessments should be performed in a consistent, transparent and reproducible fashion, using independently, orthogonally generated data. Here we present ICR142 Benchmarker, a tool to generate outputs for assessing germline base substitution and indel calling performance using the ICR142 NGS validation series, a dataset of Illumina platform-based exome sequence data from 142 samples together with Sanger sequence data at 704 sites. ICR142 Benchmarker provides summary and detailed information on the sensitivity, specificity and false detection rates of variant callers. ICR142 Benchmarker also automatically generates a single page report highlighting key performance metrics and how performance compares to widely-used open-source tools. We used ICR142 Benchmarker with VCF files outputted by GATK, OpEx and DeepVariant to create a benchmark for variant calling performance. This evaluation revealed pipeline-specific differences and shared challenges in variant calling, for example in detecting indels in short repeating sequence motifs. We next used ICR142 Benchmarker to perform regression testing with DeepVariant versions 0.5.2 and 0.6.1. This showed that v0.6.1 improves variant calling performance, but there was evidence of minor changes in indel calling behaviour that may benefit from attention. The data also allowed us to evaluate filters to optimise DeepVariant calling, and we recommend using 30 as the QUAL threshold for base substitution calls when using DeepVariant v0.6.1. Finally, we used ICR142 Benchmarker with VCF files from two commercial variant calling providers to facilitate optimisation of their in-house pipelines and to provide transparent benchmarking of their performance. ICR142 Benchmarker consistently and transparently analyses variant calling performance based on the ICR142 NGS validation series, using the standard VCF input and outputting informative metrics to enable user understanding of pipeline performance. ICR142 Benchmarker is freely available at https://github.com/RahmanTeamDevelopment/ICR142_Benchmarker/releases.This article is freely available online from the publisher's site via Open Access