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A Global Perspective on Cardiovascular Risk Factors by Educational Level in CHD Patients SURF CHD II
No full textDesign and Synthesis of Hybrid Compounds for Potential Treatment of Bacterial CoInfections In Vitro Antibacterial and In Silico Studies
No full textMicrosampling with dried blood spots and mass spectrometry enables PKPD profiling of responses to praziquantel in a Schistosoma haematobium exposed Zimbabwean population
No full textEpidemiology of Laboratory Confirmed Mucosal and Disseminated Gonococcal Infections in South Africa, 2012–2021
No full textA research report submitted in fulfillment of the requirements for the Master of Medicine, in the Faculty of Health Sciences, School of Medicine, University of the Witwatersrand, Johannesburg, 2025Background Gonorrhoeal disease, caused by Neisseria gonorrhoeae is an important sexually transmitted infection (STI). With global guidelines recommending moving from syndromic management to aetiological screening and diagnostic testing of STIs, laboratory identification of gonococcal infection is of importance. Disseminated gonococcal infections (DGI) are well characterized manifestations of gonococcal infections. In South Africa the extent of DGI and the sites involved as well as overall gonococcal infections has not been fully studied or described. Methods This study was a retrospective analysis spanning 10 years, utilizing specimen data obtained from the Laboratory Information System (LIS) of the National Health Laboratory Service (NHLS), covering public health facilities across South Africa. Data was obtained on specimens collected from patients who were 15 years and older at both mucosal and disseminated sites and where N. gonorrhoeae testing was requested. Human Immunodeficiency Virus (HIV) status of study individuals was determined based on CD4 count and HIV viral load. South African population data for each study year was collected from PopulationPyramid.net for those 15 years and older and this was used to calculate testing rates expressed per 1 000 000 per population. Testing rates were also calculated for each province also expressed per 1 000 000. Median and Interquartile ranges were used to describe the age of those who tested positive for N. gonorrhoeae. Frequencies and percentages were used for sex, province, specimen site, location of infection – mucosal vs disseminated, year of specimen collection and HIV status. Results 4804 samples were sent to the NHLS laboratories for gonococcal testing over the study period. The highest testing rates were recorded in 2019, reaching 19.7 per 1 000 000 population. 2646 samples had valid results and were used to determine the prevalence. The overall prevalence of laboratory confirmed gonococcal infections was 20% over the 10-year period. Highest percentage of cases was noted in 2015 of 76% and lowest in 2012 of 0%. Females accounted for 60% of total gonococcal infections diagnosed. Disseminated gonococcal infection (DGI) rate was 18% of confirmed gonococcal infections with synovial fluid accounting for the main (61%) disseminated 3 site. 40% of gonococcal cases had laboratory confirmed HIV positive status, of which 38% were mucosal infections and 49% disseminated infections (p=0.048). Conclusion Gonococcal infections remain important STIs. There was varied prevalence over the different provinces and across the years with a predominant female occurrence. The most common DGI specimen was synovial fluid which is in keeping with various studies. Due to limitations with culture testing and laboratory reporting, underreporting of the burden of disease is expected and further studies including clinical data or patient records may allow for further determination of missing data and clinical spectrum related to DGI.MM202
Community and Universal Testing for TB among close contacts of microbiologically confirmed pulmonary TB patients in two high TB burden countries a protocol for a pragmatic clusterrandomised control trial
No full textComparing shear bond strength of a composite to PEEK, PEKK and titanium
No full textA research report submitted in fulfillment of the requirements for the Master of Dentistry degree in Prosthodontics, in the Faculty of Health Sciences, School of Oral Health Sciences, University of the Witwatersrand, Johannesburg, 2025Purpose This in vitro study aims to compare the shear bond strength (SBS) of veneering composite to PEEK, PEKK, and titanium, as well as their failure modes (adhesive, cohesive, mixed).
Materials and Method
Specimens of milled titanium, PEEK, and PEKK (n = 105) were abraded using 600-1000 grit silicon carbide paper. The specimens underwent surface treatment using sandblasting with 110μm aluminium oxide particles. The titanium specimens were bonded with a methacryloyloxydecyl dihydrogen phosphate-based (MDP) adhesive (Plafique Universal Bond), whilst the PEEK and PEKK specimens were bonded using a methyl methacrylate-based (MMA) adhesive (PEKKbond, AnaxDent, Ardmore, USA). A composite (Gradia® Plus Heavy body paste, GC, Europe) was bonded to the prepared surface of the specimens. An Instron universal testing machine (Instron, UK) was used to assess the SBS of titanium, PEEK, and PEKK when bonded to composite. The sheared interface of all specimens was evaluated with a stereomicroscope (Nikon SMZ 1500) at 16X magnification
Results
A comprehensive narrative analysis of material performance compared titanium, PEEK, and PEKK, focusing on their SBS to composite, including their failure modes. The data revealed substantial differences among the mean SBS of titanium, PEEK, and PEKK when bonded to composite. Titanium shows a high mean SBS of 28.60 MPa, with a 95% confidence interval (CI) (SD = 9.84 MPa). PEKK shows a moderate mean compressive stress of 25.80 MPa, with a 95% confidence interval (SD = 5.44 MPa). This mean value indicates that PEKK has a higher SBS to composite, closer to that of titanium. v PEEK has a lower mean SBS of 16.83 MPa, with a 95% confidence interval (SD = 5.71). This lower mean value indicates that PEEK has a lower SBS to composite compared to titanium and PEKK. A three-sample t-test revealed a difference of 3.77 MPa between titanium and PEEK (p < 0.0001), 2.87 MPa between PEKK and PEEK (p < 0.0001), and 0.90 MPa between titanium and PEKK (p = 0.1449). Titanium predominantly showed mixed failure mode, with 88.6% of failures involving mixed failures and 11.4% of adhesive failures. PEEK was more prone to adhesive failures, with 82.9% of failures occurring at the adhesive bonds. PEKK was also prone to adhesive failures, with 57.1% being adhesive and 42.9% being mixed failures.
Conclusions and Recommendations
The current study's results allow for the drawing of the following conclusions within its limitations: When bonded to composite, PEKK exhibited comparable SBS to titanium. In terms of their bond to composite, both PEKK and titanium were superior to PEEK. Therefore, PEKK may serve as a viable substitute for titanium, offering both cost-effectiveness and improved aesthetic results. While titanium and PEKK exhibited comparable SBS, their failure mechanisms varied. Titanium primarily displayed mixed-type failure, with only three specimens experiencing adhesive failure, while PEKK displayed predominantly adhesive-type failure. The PEEK specimens exhibited primarily adhesive failure. None of the specimens demonstrated cohesive failure. However, additional studies considering the oral environment and ageing effects are recommended to assess the long-term success.MM202
Dyschoriste Nees Acanthaceae Ruellieae Clarification of species previously recognised in Chaetacanthus Nees and two threatened new species from South Africa
No full textPredicting Wind Energy Production in South Africa Using Machine Learning
No full textA research report submitted in fulfillment of the requirements for the Master of Commerce, in the Faculty of Commerce Law and Management, School of Economics and Finance, University of the Witwatersrand, Johannesburg, 2025South Africa faces an urgent and escalating energy crisis driven by ageing coal infrastructure, frequent load shedding, and rising electricity demand. Wind energy presents a viable renewable energy alternative with significant potential to alleviate these challenges; however, its inherent variability complicates grid stability and energy planning. Accurate wind energy forecasting is essential for optimising power dispatch, minimising curtailment, and enhancing energy security. Despite advancements, traditional forecasting methods, such as physical models and statistical techniques, struggle to capture the complex and nonlinear nature of wind patterns, particularly in data-scarce environments like South Africa. This study investigates the application of machine learning models to improve wind power forecasting in South Africa, where data constraints and fluctuating meteorological conditions pose unique challenges. The research examines the effectiveness of machine learning in predicting wind energy production and assesses the role of explainable artificial intelligence techniques, such as SHapley Additive exPlanations, in enhancing model transparency and interpretability. Using historical meteorological data and turbine performance records from a South African independent power producer, the study evaluates multiple machine learning approaches to determine their predictive performance. A comparative analysis of different machine learning models highlights the most reliable techniques for wind energy prediction. The findings demonstrate that XGBoost outperforms Random Forest, Decision Tree, and K-Nearest Neighbour. Furthermore, the machine learning methods show a significant improvement over traditional statistical techniques, offering improved predictive accuracy while providing insights into key meteorological and operational factors influencing wind power generation. The integration of explainable artificial intelligence further ensures interpretability, fostering trust and practical usability among stakeholders. This research contributes to the renewable energy forecasting literature by adapting machine learning solutions to a data-scarce environment and emphasising the role of interpretability in real-world adoption. The results provide valuable insights for policymakers, energy planners, and grid operators, supporting South Africa’s transition to a more sustainable and resilient energy future. However, the study's findings may be limited in generalisability and accuracy due to the analysis focusing on a single wind turbine chosen based on data availability rather than representativeness. Consequently, the results may not extend to other wind farms or turbines operating under different geographic or climatic conditions.MM202
