Course Review Self Assessment

The goal of this course review self-assessment is to help faculty reflect on course format and design and it may be completed by the course instructor alone or with input from other faculty, adjuncts or lab assistants. The findings in this review may serve as the basis for discussion with faculty and/or administrators to identify potential changes in course format or design that can enhance student outcomes

Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection

Quality assessment of medical images is essential for complete automation of image processing pipelines. For large population studies such as the UK Biobank, artefacts such as those caused by heart motion are problematic and manual identification is tedious and time-consuming. Therefore, there is an urgent need for automatic image quality assessment techniques. In this paper, we propose a method to automatically detect the presence of motion-related artefacts in cardiac magnetic resonance (CMR) images. As this is a highly imbalanced classification problem (due to the high number of good quality images compared to the low number of images with motion artefacts), we propose a novel k-space based training data augmentation approach in order to address this problem. Our method is based on 3D spatio-temporal Convolutional Neural Networks, and is able to detect 2D+time short axis images with motion artefacts in less than 1ms. We test our algorithm on a subset of the UK Biobank dataset consisting of 3465 CMR images and achieve not only high accuracy in detection of motion artefacts, but also high precision and recall. We compare our approach to a range of state-of-the-art quality assessment methods.Comment: Accepted for MICCAI2018 Conferenc

The Effects of Stimulant Medication on the Online Story Narrations of Children with ADHD

The current study investigated the inclusion of goal-based story events in the online story narrations of children with ADHD, as compared with their peers, and explored the effect of stimulant medication on the narrations in children with ADHD. Children completed a narration task on two separate occasions. Children with ADHD (n = 17) completed one narration on medication and the other one on placebo. Results indicated that narrations of comparison children (n= 25) were significantly more likely than narrations of children with ADHD to include the story’s positive outcome, completion of the story’s overall goal, and specific attempts linked to the goal. Children with ADHD included a larger total number of clauses in their narrations when on stimulant medication than when on placebo, but medication showed no significant effects for any other variables. Results indicate that stimulant medication may not be effective at reducing goal-based story comprehension deficits in children with ADHD

The Effects of Stimulant Medication on Free Recall of Story Events among Children with ADHD

This study investigated group differences in the recalls of stories by children with attention-deficit/hyperactivity disorder (ADHD) and comparison peers. Further, the study examined whether stimulant medication improved the story recall of children with ADHD relative to a placebo condition. Children were asked to recall both televised and audio taped stories. Free recall protocols were assessed for what information was recalled as a function of story structure features (i.e. status on or off the causal chain and event importance) and were rated for overall coherence. Relative to comparison peers, children with ADHD showed less influence of story structure features on recall, and produced less coherent recall of the audio taped stories. Medication had only limited effects on the story recall of children with ADHD. Specifically, medication did not increase these children’s sensitivity to events central to the stories and had no effect on the coherence of children’s recalls. The implications of the results for guiding future academic interventions are discussed

On the minimization of Dirichlet eigenvalues of the Laplace operator

We study the variational problem \inf \{\lambda_k(\Omega): \Omega\ \textup{open in}\ \R^m,\ |\Omega| < \infty, \ \h(\partial \Omega) \le 1 \}, where $\lambda_k(\Omega)$ is the $k$'th eigenvalue of the Dirichlet Laplacian acting in $L^2(\Omega)$, \h(\partial \Omega) is the $(m-1)$- dimensional Hausdorff measure of the boundary of $\Omega$, and $|\Omega|$ is the Lebesgue measure of $\Omega$. If $m=2$, and $k=2,3, \cdots$, then there exists a convex minimiser $\Omega_{2,k}$. If $m \ge 2$, and if $\Omega_{m,k}$ is a minimiser, then $\Omega_{m,k}^*:= \textup{int}(\overline{\Omega_{m,k}})$ is also a minimiser, and $\R^m\setminus \Omega_{m,k}^*$ is connected. Upper bounds are obtained for the number of components of $\Omega_{m,k}$. It is shown that if $m\ge 3$, and $k\le m+1$ then $\Omega_{m,k}$ has at most $4$ components. Furthermore $\Omega_{m,k}$ is connected in the following cases : (i) $m\ge 2, k=2,$ (ii) $m=3,4,5,$ and $k=3,4,$ (iii) $m=4,5,$ and $k=5,$ (iv) $m=5$ and $k=6$. Finally, upper bounds on the number of components are obtained for minimisers for other constraints such as the Lebesgue measure and the torsional rigidity.Comment: 16 page

Quantifying the Effects of Contact Tracing, Testing, and Containment Measures in the Presence of Infection Hotspots

Multiple lines of evidence strongly suggest that infection hotspots, where a single individual infects many others, play a key role in the transmission dynamics of COVID-19. However, most of the existing epidemiological models fail to capture this aspect by neither representing the sites visited by individuals explicitly nor characterizing disease transmission as a function of individual mobility patterns. In this work, we introduce a temporal point process modeling framework that specifically represents visits to the sites where individuals get in contact and infect each other. Under our model, the number of infections caused by an infectious individual naturally emerges to be overdispersed. Using an efficient sampling algorithm, we demonstrate how to apply Bayesian optimization with longitudinal case data to estimate the transmission rate of infectious individuals at the sites they visit and in their households. Simulations using fine-grained and publicly available demographic data and site locations from Bern, Switzerland showcase the flexibility of our framework. To facilitate research and analyses of other cities and regions, we release an open-source implementation of our framework

Protein free microcapsules obtained from plant spores as a model for drug delivery: Ibuprofen encapsulation, release and taste masking

Sporopollenin exine capsules (SEC) extracted from Lycopodium clavatum spores were shown to encapsulate ibuprofen as a drug model, with 97 ± 1% efficiency as measured by recovery of the loaded drug and absence of the drug on the SEC surface by scanning electron microscopy (SEM). The encapsulated ibuprofen was shown to be unchanged from its bulk crystalline form by solid state NMR, FTIR and XRD. Essential for drug delivery applications, SEC were shown to be non-toxic to human endothelial cells and free of allergenic protein epitopes by MALDI-TOF-MS and ESI-QqToF-MS. Potential application for targeted release into the intestinal region of the gastrointestinal tract (GIT) was demonstrated by 88 ± 1% of the drug being retained in simulated gastric fluid (SGF) after 45 minutes and 85 ± 2% being released after 5 min in buffer (PBS; pH 7.4). The SEC were shown to provide significant taste masking of encapsulated ibuprofen in a double blind trial with 10 human volunteers. © The Royal Society of Chemistry 2013

Large well-relaxed models of vitreous silica, coordination numbers and entropy

A Monte Carlo method is presented for the simulation of vitreous silica. Well-relaxed networks of vitreous silica are generated containing up to 300,000 atoms. The resulting networks, quenched under the BKS potential, display smaller bond-angle variations and lower defect concentrations, as compared to networks generated with molecular dynamics. The total correlation functions T(r) of our networks are in excellent agreement with neutron scattering data, provided that thermal effects and the maximum inverse wavelength used in the experiment are included in the comparison. A procedure commonly used in experiments to obtain coordination numbers from scattering data is to fit peaks in rT(r) with a gaussian. We show that this procedure can easily produce incorrect results. Finally, we estimate the configurational entropy of vitreous silica.Comment: 7 pages, 4 figures (two column version to save paper

A first-in-human phase 1 study of cavrotolimod, a TLR9 agonist spherical nucleic acid, in healthy participants: Evidence of immune activation

IntroductionTumor immunotherapy is designed to control malignancies through the host immune response but requires circumventing tumor-dysregulated immunomodulation through immunostimulation, relieving immunorepression, or a combination of both approaches. Here we designed and characterized cavrotolimod (formerly AST-008), an immunostimulatory spherical nucleic acid (SNA) compound targeting Toll-like receptor 9 (TLR9). We assessed the safety and pharmacodynamic (PD) properties of cavrotolimod in healthy participants in a first-in-human Phase 1 study under protocol AST-008-101 (NCT03086278; https://clinicaltrials.gov/ct2/show/NCT03086278).MethodsHealthy participants aged 18 to 40 years were enrolled to evaluate four dose levels of cavrotolimod across four cohorts. Each cohort included four participants, and all received a single subcutaneous dose of cavrotolimod. The dose levels were 5, 10, 12.5 and 18.8 µg/kg.Results and discussionCavrotolimod was well tolerated and elicited no serious adverse events or dose limiting toxicities at the doses tested. The results demonstrated that cavrotolimod is a potent innate immune activator, specifically stimulating Th1-type immune responses, and exhibits PD properties that may result in anti-tumor effects in patients with cancer. This study suggests that cavrotolimod is a promising clinical immunotherapy agent