Exploring doctors’ trade-offs between management, research, and clinical training in the medical curriculum : a protocol for a discrete choice experiment in Southern Africa

Funding This work was supported by the Department of Research and Innovation, University of Pretoria Research Development Programme and the University Capacity Development Programme for the University of Pretoria. Acknowledgements The authors thank the participants in the previous phases that informed the development of the DCE.Peer reviewedPublisher PD

The pPSU Plasmids for Generating DNA Molecular Weight Markers.

Visualizing nucleic acids by gel electrophoresis is one of the most common techniques in molecular biology, and reference molecular weight markers or ladders are commonly used for size estimation. We have created the pPSU1 & pPSU2 pair of molecular weight marker plasmids which produce both 100 bp and 1 kb DNA ladders when digested with two common restriction enzymes. The 100 bp ladder fragments have been optimized to migrate appropriately on both agarose and native polyacrylamide, unlike many currently available DNA ladders. Sufficient plasmid DNA can be isolated from 100 ml E. coli cultures for the two plasmids to produce 100 bp or 1 kb ladders for 1000 gels. As such, the pPSU1 and pPSU2 plasmids provide reference fragments from 50 to 10000 bp at a fraction of the cost of commercial DNA ladders. The pPSU1 and pPSU2 plasmids are available without licensing restrictions to nonprofit academic users, affording freely available high-quality, low-cost molecular weight standards for molecular biology applications

Serum concentration impacts myosin heavy chain expression but not cellular respiration in human LHCN‐M2 myoblasts undergoing differentiation

Abstract The human LHCN‐M2 myoblast cell line has the potential to be used to investigate skeletal muscle development and metabolism. Experiments were performed to determine how different concentrations of human serum affect myogenic differentiation and mitochondrial function of LHCN‐M2 cells. LHCN‐M2 myoblasts were differentiated in serum‐free medium, 0.5% or 2% human serum for 5 and 10 days. Myotube formation was assessed by immunofluorescence staining of myosin heavy chain (MHC) and molecularly by mRNA expression of Myogenic differentiation 1 (MYOD1) and Myoregulatory factor 5 (MYF5). Following differentiation, mitochondrial function was assessed to establish the impact of serum concentration on mitochondrial function. Time in differentiation increased mRNA expression of MYOD1 (day 5, 6.58 ± 1.33‐fold; and day 10, 4.28 ± 1.71‐fold) (P = 0.012), while suppressing the expression of MYF5 (day 5, 0.21 ± 0.11‐fold; and day 10, 0.06 ± 0.03‐fold) (P = 0.001), regardless of the serum concentration. Higher serum concentrations increased MHC area (serum free, 11.92 ± 0.85%; 0.5%, 23.10 ± 5.82%; 2%, 43.94 ± 8.92%) (P = 0.001). Absolute basal respiration approached significance (P = 0.06) with significant differences in baseline oxygen consumption rate (P = 0.025) and proton leak (P = 0.006) when differentiated in 2% human serum, but these were not different between conditions when normalised to total protein. Our findings show that increasing concentrations of serum of LHCN‐M2 skeletal muscle cells into multinucleated myotubes, but this does not affect relative mitochondrial function

Lung Cancer Metastasis Presenting as a Solitary Skull Mass

Lung cancer has been well documented to spread to bone and the axial skeleton after metastasis to adjacent organs. Bony metastasis is not, however, the typical presenting manifestation. The differential diagnosis for a tissue mass on the skull should warrant a workup for metastatic disease. Bony metastasis plays an important role in treatment and disease management. We report an exceptionally rare case of stage IV lung adenocarcinoma that presented with a solitary skull metastasis and a significant soft-tissue component. The lesion was treated by excision via craniotomy and subsequent medical management of the adenocarcinoma. This case illustrates a very rare presentation of lung adenocarcinoma and also represents what the authors believe to be the first report of a solitary skull mass originating from a lung primary. We also present a review of the literature surrounding bony metastasis to the skull and implications for patient care

High-performance Si microwire photovoltaics

Crystalline Si wires, grown by the vapor–liquid–solid (VLS) process, have emerged as promising candidate materials for lowcost, thin-film photovoltaics. Here, we demonstrate VLS-grown Si microwires that have suitable electrical properties for high-performance photovoltaic applications, including long minority-carrier diffusion lengths (L_n » 30 µm) and low surface recombination velocities (S « 70 cm·s^(-1)). Single-wire radial p–n junction solar cells were fabricated with amorphous silicon and silicon nitride surface coatings, achieving up to 9.0% apparent photovoltaic efficiency, and exhibiting up to ~600 mV open-circuit voltage with over 80% fill factor. Projective single-wire measurements and optoelectronic simulations suggest that large-area Si wire-array solar cells have the potential to exceed 17% energy-conversion efficiency, offering a promising route toward cost-effective crystalline Si photovoltaics

Si microwire-array solar cells

Si microwire-array solar cells with Air Mass 1.5 Global conversion efficiencies of up to 7.9% have been fabricated using an active volume of Si equivalent to a 4 μm thick Si wafer. These solar cells exhibited open-circuit voltages of 500 mV, short-circuit current densities (J_(sc)) of up to 24 mA cm^(-2), and fill factors >65% and employed Al_2O_3 dielectric particles that scattered light incident in the space between the wires, a Ag back reflector that prevented the escape of incident illumination from the back surface of the solar cell, and an a-SiN_x:H passivation/anti-reflection layer. Wire-array solar cells without some or all of these design features were also fabricated to demonstrate the importance of the light-trapping elements in achieving a high J_(sc). Scanning photocurrent microscopy images of the microwire-array solar cells revealed that the higher J_(sc) of the most advanced cell design resulted from an increased absorption of light incident in the space between the wires. Spectral response measurements further revealed that solar cells with light-trapping elements exhibited improved red and infrared response, as compared to solar cells without light-trapping elements

A framework for automated anomaly detection in high frequency water-quality data from in situ sensors

River water-quality monitoring is increasingly conducted using automated in situ sensors, enabling timelier identification of unexpected values. However, anomalies caused by technical issues confound these data, while the volume and velocity of data prevent manual detection. We present a framework for automated anomaly detection in high-frequency water-quality data from in situ sensors, using turbidity, conductivity and river level data. After identifying end-user needs and defining anomalies, we ranked their importance and selected suitable detection methods. High priority anomalies included sudden isolated spikes and level shifts, most of which were classified correctly by regression-based methods such as autoregressive integrated moving average models. However, using other water-quality variables as covariates reduced performance due to complex relationships among variables. Classification of drift and periods of anomalously low or high variability improved when we applied replaced anomalous measurements with forecasts, but this inflated false positive rates. Feature-based methods also performed well on high priority anomalies, but were also less proficient at detecting lower priority anomalies, resulting in high false negative rates. Unlike regression-based methods, all feature-based methods produced low false positive rates, but did not and require training or optimization. Rule-based methods successfully detected impossible values and missing observations. Thus, we recommend using a combination of methods to improve anomaly detection performance, whilst minimizing false detection rates. Furthermore, our framework emphasizes the importance of communication between end-users and analysts for optimal outcomes with respect to both detection performance and end-user needs. Our framework is applicable to other types of high frequency time-series data and anomaly detection applications

Learned Monocular Depth Priors in Visual-Inertial Initialization

Visual-inertial odometry (VIO) is the pose estimation backbone for most AR/VR and autonomous robotic systems today, in both academia and industry. However, these systems are highly sensitive to the initialization of key parameters such as sensor biases, gravity direction, and metric scale. In practical scenarios where high-parallax or variable acceleration assumptions are rarely met (e.g. hovering aerial robot, smartphone AR user not gesticulating with phone), classical visual-inertial initialization formulations often become ill-conditioned and/or fail to meaningfully converge. In this paper we target visual-inertial initialization specifically for these low-excitation scenarios critical to in-the-wild usage. We propose to circumvent the limitations of classical visual-inertial structure-from-motion (SfM) initialization by incorporating a new learning-based measurement as a higher-level input. We leverage learned monocular depth images (mono-depth) to constrain the relative depth of features, and upgrade the mono-depth to metric scale by jointly optimizing for its scale and shift. Our experiments show a significant improvement in problem conditioning compared to a classical formulation for visual-inertial initialization, and demonstrate significant accuracy and robustness improvements relative to the state-of-the-art on public benchmarks, particularly under motion-restricted scenarios. We further extend this improvement to implementation within an existing odometry system to illustrate the impact of our improved initialization method on resulting tracking trajectories