Making Science Relevant: a Faculty-wide Initiative Towards Enhancing the Student Experience Through Authentic Learning Activities

Authentic learning describes an educational approach in which students are presented with problems of real-world relevance within an environment that mirrors professional practice. (Herrington and Herrington 2006). There is substantial evidence that authentic learning is a powerful tool with which to encourage deeper learning and improve learning outcomes (Newmann et al. 1995). Our project aims to improve student learning outcomes and engagement by embedding authentic learning practice into the curriculum across our large and diverse faculty. We are employing a hub and spoke model of project management: the project team forms the hub, with discipline participants as the spokes, firmly connected to the rim of school-based colleagues. We have devised checklists that allow evaluation of units or learning activities against the principles of authentic learning articulated by Herrington and Herrington (2006). To date, we have run two workshops with discipline participants, who have received peer feedback on teaching initiatives they will trial in semester 2, 2010. In addition, we have initiated a faculty-wide scan for examples of good practice in authentic learning. Outcomes of this project include: broad dissemination of the concept of authentic learning; a web-based resource of exemplars of authentic learning activities; and increased engagement of our students

Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software

Purpose: A novel phantom-imaging platform, a set of software tools, for automated and high-precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed. Methods: The key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife-edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate μ -map for PET/MR systems with a robust alignment based on two-stage image registration using specifically designed PET templates. The proposed platform is based on the open-source NiftyPET software package used to generate multiple list-mode data bootstrap realizations and image reconstructions to determine the precision of the two-stage registration and any image-derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift-invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV. Results: The utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1–2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two-stage registration. Conclusions: We demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies

SIRF: Synergistic Image Reconstruction Framework

The combination of positron emission tomography (PET) with magnetic resonance (MR) imaging opens the way to more accurate diagnosis and improved patient management. At present, the data acquired by PET-MR scanners are essentially processed separately, but the opportunity to improve accuracy of the tomographic reconstruction via synergy of the two imaging techniques is an active area of research. In this paper, we present Release 2.1.0 of the CCP-PETMR Synergistic Image Reconstruction Framework (SIRF) software suite, providing an open-source software platform for efficient implementation and validation of novel reconstruction algorithms. SIRF provides user-friendly Python and MATLAB interfaces built on top of C++ libraries. SIRF uses advanced PET and MR reconstruction software packages and tools. Currently, for PET this is Software for Tomographic Image Reconstruction (STIR); for MR, Gadgetron and ISMRMRD; and for image registration tools, NiftyReg. The software aims to be capable of reconstructing images from acquired scanner data, whilst being simple enough to be used for educational purposes

Demographic and biologic influences on survival in whites and blacks: 40 years of follow-up in the Charleston heart study

BACKGROUND: In the United States, life expectancy is significantly lower among blacks than whites. We examined whether socioeconomic status (SES) and cardiovascular disease (CVD) risk factors may help explain this disparity. METHODS: Forty years (1961 through 2000) of all-cause mortality data were obtained on a population-based cohort of 2,283 subjects in the Charleston Heart Study (CHS). We examined the influence of SES and CVD risk factors on all-cause mortality. RESULTS: Complete data were available on 98% of the original sample (647 white men, 728 white women, 423 black men, and 443 black women). After adjusting for SES and CVD risk factors, the hazard ratios (HRs) for white ethnicity were 1.14 (0.98 to 1.32) among men and 0.90 (0.75 to 1.08) among women, indicating that the mortality risk was 14% greater for white men and 10% lower for white women compared to their black counterparts. However the differences were not statistically significant. CONCLUSION: While there are marked contrasts in mortality among blacks and whites in the CHS, the differences can be largely explained by SES and CVD risk factors. Continued focus on improving and controlling cardiovascular disease risk factors may reduce ethnic disparities in survival

In situ Biofilm Quantification in Bioelectrochemical Systems by using Optical Coherence Tomography

Detailed studies of microbial growth in bioelectrochemical systems (BESs) are required for their suitable design and operation. Here, we report the use of optical coherence tomography (OCT) as a tool for in situ and noninvasive quantification of biofilm growth on electrodes (bioanodes). An experimental platform is designed and described in which transparent electrodes are used to allow real‐time, 3D biofilm imaging. The accuracy and precision of the developed method is assessed by relating the OCT results to well‐established standards for biofilm quantification (chemical oxygen demand (COD) and total N content) and show high correspondence to these standards. Biofilm thickness observed by OCT ranged between 3 and 90 μm for experimental durations ranging from 1 to 24 days. This translated to growth yields between 38 and 42 mgurn:x-wiley:18645631:media:cssc201800589:cssc201800589-math-0001  gurn:x-wiley:18645631:media:cssc201800589:cssc201800589-math-0002 −1 at an anode potential of −0.35 V versus Ag/AgCl. Time‐lapse observations of an experimental run performed in duplicate show high reproducibility in obtained microbial growth yield by the developed method. As such, we identify OCT as a powerful tool for conducting in‐depth characterizations of microbial growth dynamics in BESs. Additionally, the presented platform allows concomitant application of this method with various optical and electrochemical techniques

Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology:The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

OBJECTIVE: One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual’s emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them. METHODS: To evaluate this, we crowdsourced the analysis of one individual patient’s ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. RESULTS: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0–16) and nature of selected targets varied widely. CONCLUSION: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation

Impact of CD4 and CD8 dynamics and viral rebounds on loss of virological control in HIV controllers

Objective: HIV controllers (HICs) spontaneously maintain HIV viral replication at low level without antiretroviral therapy (ART), a small number of whom will eventually lose this ability to control HIV viremia. The objective was to identify factors associated with loss of virological control. Methods: HICs were identified in COHERE on the basis of \ue2\u89\ua55 consecutive viral loads (VL) \ue2\u89\ua4500 copies/mL over \ue2\u89\ua51 year whilst ART-naive, with the last VL \ue2\u89\ua4500 copies/mL measured \ue2\u89\ua55 years after HIV diagnosis. Loss of virological control was defined as 2 consecutive VL >2000 copies/mL. Duration of HIV control was described using cumulative incidence method, considering loss of virological control, ART initiation and death during virological control as competing outcomes. Factors associated with loss of virological control were identified using Cox models. CD4 and CD8 dynamics were described using mixed-effect linear models. Results: We identified 1067 HICs; 86 lost virological control, 293 initiated ART, and 13 died during virological control. Six years after confirmation of HIC status, the probability of losing virological control, initiating ART and dying were 13%, 37%, and 2%. Current lower CD4/CD8 ratio and a history of transient viral rebounds were associated with an increased risk of losing virological control. CD4 declined and CD8 increased before loss of virological control, and before viral rebounds. Discussion: Expansion of CD8 and decline of CD4 during HIV control may result from repeated low-level viremia. Our findings suggest that in addition to superinfection, other mechanisms, such as low grade viral replication, can lead to loss of virological control in HICs

Prospective individual patient data meta-analysis of two randomized trials on convalescent plasma for COVID-19 outpatients

Data on convalescent plasma (CP) treatment in COVID-19 outpatients are scarce. We aimed to assess whether CP administered during the first week of symptoms reduced the disease progression or risk of hospitalization of outpatients. Two multicenter, double-blind randomized trials (NCT04621123, NCT04589949) were merged with data pooling starting when = 50 years and symptomatic for <= 7days were included. The intervention consisted of 200-300mL of CP with a predefined minimum level of antibodies. Primary endpoints were a 5-point disease severity scale and a composite of hospitalization or death by 28 days. Amongst the 797 patients included, 390 received CP and 392 placebo; they had a median age of 58 years, 1 comorbidity, 5 days symptoms and 93% had negative IgG antibody-test. Seventy-four patients were hospitalized, 6 required mechanical ventilation and 3 died. The odds ratio (OR) of CP for improved disease severity scale was 0.936 (credible interval (CI) 0.667-1.311); OR for hospitalization or death was 0.919 (CI 0.592-1.416). CP effect on hospital admission or death was largest in patients with <= 5 days of symptoms (OR 0.658, 95%CI 0.394-1.085). CP did not decrease the time to full symptom resolution

A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates