Magnetotransport properties of a polarization-doped three-dimensional electron slab

We present evidence of strong Shubnikov-de-Haas magnetoresistance oscillations in a polarization-doped degenerate three-dimensional electron slab in an Al$_{x}$Ga$_{1-x}$N semiconductor system. The degenerate free carriers are generated by a novel technique by grading a polar alloy semiconductor with spatially changing polarization. Analysis of the magnetotransport data enables us to extract an effective mass of $m^{\star}=0.19 m_{0}$ and a quantum scattering time of $\tau_{q}= 0.3 ps$. Analysis of scattering processes helps us extract an alloy scattering parameter for the Al$_{x}$Ga$_{1-x}$N material system to be $V_{0}=1.8eV$

Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners. The series consisted of two webinars (August 2017 and September 2017) leading up to a workshop (November 2017) exploring the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. A third follow-up webinar was held after the workshop (January 2018) to report on outcomes and next steps. Program committee members were chosen to represent a broad spectrum of communities with a diversity of geography (West, Northeast, Midwest, and South), discipline (Computer Science, Math, Statistics, and Domains), as well as institution type (Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other Minority-Serving Institutions (MSI\u27s), Community College\u27s (CC’s), 4-year colleges, Tribal Colleges, R1 Universities, Government and Industry Partners)

Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners. The series consisted of two webinars (August 2017 and September 2017) leading up to a workshop (November 2017) exploring the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. A third follow-up webinar was held after the workshop (January 2018) to report on outcomes and next steps. Program committee members were chosen to represent a broad spectrum of communities with a diversity of geography (West, Northeast, Midwest, and South), discipline (Computer Science, Math, Statistics, and Domains), as well as institution type (Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other Minority-Serving Institutions (MSI\u27s), Community College\u27s (CC’s), 4-year colleges, Tribal Colleges, R1 Universities, Government and Industry Partners)

2D versus 3D human induced pluripotent stem cell-derived cultures for neurodegenerative disease modelling

Neurodegenerative diseases, such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD) and amyotrophic lateral sclerosis (ALS), affect millions of people every year and so far, there are no therapeutic cures available. Even though animal and histological models have been of great aid in understanding disease mechanisms and identifying possible therapeutic strategies, in order to find disease-modifying solutions there is still a critical need for systems that can provide more predictive and physiologically relevant results. One possible avenue is the development of patient-derived models, e.g. by reprogramming patient somatic cells into human induced pluripotent stem cells (hiPSCs), which can then be differentiated into any cell type for modelling. These systems contain key genetic information from the donors, and therefore have enormous potential as tools in the investigation of pathological mechanisms underlying disease phenotype, and progression, as well as in drug testing platforms. hiPSCs have been widely cultured in 2D systems, but in order to mimic human brain complexity, 3D models have been proposed as a more advanced alternative. This review will focus on the use of patient-derived hiPSCs to model AD, PD, HD and ALS. In brief, we will cover the available stem cells, types of 2D and 3D culture systems, existing models for neurodegenerative diseases, obstacles to model these diseases in vitro, and current perspectives in the field

Out of the maze Reaching and supporting Londoners with severe mental health problems

Includes bibliographical referencesAvailable from British Library Document Supply Centre- DSC:m02/44835 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

A complete genome screening program of clinical methicillin-resistant isolates identifies the origin and progression of a neonatal intensive care unit outbreak

Whole-genome sequencing (WGS) of is increasingly used as part of infection prevention practices. In this study we established a long-read technology-based WGS screening program of all first-episode MRSA blood infections at a major urban hospital. A survey of 132 MRSA genomes assembled from long reads enabled detailed characterization of an outbreak of a CC5/ST105/USA100 clone among 18 infants in a neonatal intensive care unit (NICU) lasting several months. Available hospital-wide genome surveillance data traced the origins of the outbreak to three patients admitted to adult wards during a 4-month period preceding the NICU outbreak. The pattern of changes among complete outbreak genomes provided full spatiotemporal resolution of its progression, which was characterized by multiple sub-transmissions and likely precipitated by equipment sharing between adults and infants. Compared to other hospital strains, the outbreak strain carried distinct mutations and accessory genetic elements that impacted genes with roles in metabolism, resistance and persistence. This included a DNA-recognition domain recombination in the gene of a Type-I restriction-modification system that altered DNA methylation. RNA-Seq profiling showed that the (epi)genetic changes in the outbreak clone attenuated gene expression and upregulated genes involved in stress response and biofilm formation. Overall our findings demonstrate the utility of long read sequencing for hospital surveillance and for characterizing accessory genomic elements that may impact MRSA virulence and persistence

Performance characteristics of five immunoassays for SARS-CoV-2: a head-to-head benchmark comparison

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic in 2020. Testing is crucial for mitigating public health and economic effects. Serology is considered key to population-level surveillance and potentially individual-level risk assessment. However, immunoassay performance has not been compared on large, identical sample sets. We aimed to investigate the performance of four high-throughput commercial SARS-CoV-2 antibody immunoassays and a novel 384-well ELISA.We did a head-to-head assessment of SARS-CoV-2 IgG assay (Abbott, Chicago, IL, USA), LIAISON SARS-CoV-2 S1/S2 IgG assay (DiaSorin, Saluggia, Italy), Elecsys Anti-SARS-CoV-2 assay (Roche, Basel, Switzerland), SARS-CoV-2 Total assay (Siemens, Munich, Germany), and a novel 384-well ELISA (the Oxford immunoassay). We derived sensitivity and specificity from 976 pre-pandemic blood samples (collected between Sept 4, 2014, and Oct 4, 2016) and 536 blood samples from patients with laboratory-confirmed SARS-CoV-2 infection, collected at least 20 days post symptom onset (collected between Feb 1, 2020, and May 31, 2020). Receiver operating characteristic (ROC) curves were used to assess assay thresholds.At the manufacturers' thresholds, for the Abbott assay sensitivity was 92·7% (95% CI 90·2–94·8) and specificity was 99·9% (99·4–100%); for the DiaSorin assay sensitivity was 96·2% (94·2–97·7) and specificity was 98·9% (98·0–99·4); for the Oxford immunoassay sensitivity was 99·1% (97·8–99·7) and specificity was 99·0% (98·1–99·5); for the Roche assay sensitivity was 97·2% (95·4–98·4) and specificity was 99·8% (99·3–100); and for the Siemens assay sensitivity was 98·1% (96·6–99·1) and specificity was 99·9% (99·4–100%). All assays achieved a sensitivity of at least 98% with thresholds optimised to achieve a specificity of at least 98% on samples taken 30 days or more post symptom onset.Four commercial, widely available assays and a scalable 384-well ELISA can be used for SARS-CoV-2 serological testing to achieve sensitivity and specificity of at least 98%. The Siemens assay and Oxford immunoassay achieved these metrics without further optimisation. This benchmark study in immunoassay assessment should enable refinements of testing strategies and the best use of serological testing resource to benefit individuals and population health.Public Health England and UK National Institute for Health Research