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High fat, high carbohydrate (HFHC) diet-induced prediabetes as a risk factor for preeclampsia: assessing gender-specific infantile Sprague Dawley outcomes on selected markers of cardiovascular, haematological and cognitive function.
(2024) Xulu, Nombuso Duduzile.; Ngubane, Phikelelani Siphosethu.; Khathi, Andile.; Sibiya, Ntethelelo Hopewell.
Introduction. Pregestational prediabetes (PP), a precursor to type 2 diabetes and a risk factor for preeclampsia, profoundly affects the intrauterine environment, impairing cardiovascular, haematological, and cognitive development in offspring. This study investigates the impact of a high-fat, high-carbohydrate (HFHC) diet-induced prediabetic model on gender-specific infantile cardiovascular, haematological, and cognitive outcomes in Sprague-Dawley rat offspring. Methodology. Pups were born from dams with HFHC diet-induced prediabetes and L-NAME-induced preeclampsia (n=72) were divided into three groups: control (PCON), prediabetic (PPD), and preeclamptic (PPE). Offspring from each maternal group were divided into 2 subgroups. One subgroup was sacrificed at postnatal day 21 (n=36) for biomarker analysis which included BDNF and FGF2, while the second was retained until week 5 (n=36) for behavioural testing followed again by biomarker analysis specifically BDNF and FGF2. Cardiovascular parameters included mean arterial pressure (MAP), cardiac troponin I (cTnI), collagen I (COL I), malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPx). Cardiac tissue histology assessed cardiomyocyte size. Haematological evaluations included red blood cell markers [erythropoietin (EPO), red blood cell (RBC) count, haemoglobin (Hgb)], white blood cell markers [white blood cell count (WBC), granulocyte colony stimulating factor (G-CSF)], and platelet markers (platelet count) Neurodevelopmental assessments measured brain-derived neurotrophic factor (BDNF), fibroblast growth factor-2 (FGF2), and inflammatory cytokines (IL-6, IL-1β, TNF-α). Cognitive performance was evaluated using the Morris Water Maze (MWM) in the remaining pups (n=36) at five weeks Results. Cardiovascular biomarkers such as cTnI, COL I, and MAP were significantly elevated in PPD and PPE groups compared to PCON, with PPD showing the highest levels. Antioxidant enzymes (SOD, GPx) were significantly lower in PPD. Histological analysis revealed cardiomyocyte enlargement, particularly in PPD. In the haematological assessments, red blood cell indices were elevated in the PPD group, whereas haemoglobin concentration was reduced. White blood cell markers were higher in PPD, indicating inflammation. Platelet markers were altered in PPD, reflecting haemostatic disruption. Neurodevelopmental markers, including reduced BDNF and FGF2, were observed in PPD and PPE, alongside increased inflammatory cytokines. Male offspring showed more pronounced deficits than female offspring. Cognitive impairments assessed via MWM were more severe in PPD, correlating with altered hippocampal gene expression. Conclusion. In this study, the murine/rat model showed that PP exacerbates foetal dysfunction via intermediate hyperglycaemia, oxidative stress and inflammation highlighting the need for early, gender-specific interventions to mitigate long-term impacts in prediabetic pregnancies.
Investigating the effects of gossypetin on glucose homeostasis and selected complications of diet-induced prediabetes in male Sprague Dawley rats.
(2025) Naidoo, Karishma.; Khathi, Andile.
Background. Prediabetes is an intermediate glycaemic state between normoglycaemia and chronic hyperglycaemia. This condition has become increasingly prevalent worldwide due to the consumption of high-calorie diets and a sedentary lifestyle. Prediabetes is characterised by abnormal glucose metabolism and is associated with complications such as non-alcoholic fatty liver disease (NAFLD), cardiovascular and renal dysfunctions, similar to that observed in type 2 diabetes mellitus. The current management strategy for prediabetes involves a combination of dietary and pharmacological interventions. However, patient adherence to dietary intervention is often low, leading to reduced pharmacological effectiveness. Therefore, anti-diabetic agents that are effective even without dietary intervention are needed. Gossypetin (GTIN), a hexahydroxylated flavonoid, has shown potent antioxidant and anti-inflammatory properties. This study sought to investigate the effects of GTIN on glucose homeostasis and selected markers of cardiovascular, hepatic and renal dysfunction in a prediabetic rat model, both with and without dietary intervention. Materials and Methods. Thirty-six male Sprague Dawley rats (150–180 g) were divided into Group 1 (n=6) and Group 2 (n=30). Prediabetes was induced by feeding Group 2 a high-fat, high-carbohydrate (HFHC) diet for 20 weeks, while Group 1 received a normal diet (ND). Prediabetes was confirmed by fasting blood glucose (FBG) and 2-hour oral glucose tolerance tests (OGTT) according to the American Diabetes Association criteria. The prediabetic rats (n = 30) were subdivided into five groups (n = 6 per group): one group received no therapeutic intervention, while the remaining four groups were treated with either GTIN (15 mg/kg) or metformin (MET, 500 mg/kg), with or without dietary intervention, for 12 weeks. Body mass index (BMI), waist circumference (WC), blood pressure, heart rate, caloric intake, fluid intake and urine output were monitored every four weeks during the treatment period. After treatment, animals were sacrificed; blood and tissues (skeletal muscle, heart, liver, kidney) were collected and stored for biochemical analysis. The thesis comprised four studies evaluating the effects of GTIN on glucose homeostasis, cardiovascular function, hepatic function and renal function in a diet-induced prediabetic rat model. Results. In the first study, animals in the untreated pre-diabetic (PD) control group exhibited significantly higher fasting and postprandial blood glucose levels, as well as elevated plasma insulin concentrations and increased homeostatic model assessment for insulin resistance (HOMA2-IR) index, relative to the non-prediabetic (NPD) group. Similarly, increased caloric intake, body weight and plasma ghrelin levels were observed in the PD control group. Notably, these parameters were significantly reduced in the PD animals receiving GTIN treatment. Additionally, glycogen levels in the liver and skeletal muscle, which was disturbed in the PD control group, showed significant improvement following GTIN treatment , both with and without dietary intervention. In the second study, the PD control group exhibited dyslipidaemia characterized by significantly higher plasma triglyceride, total cholesterol, low-density lipoprotein and very low-density lipoprotein levels, along with decreased high-density lipoprotein (HDL) levels compared with the NPD group. This was accompanied by cardiovascular dysfunction, as evidenced by significantly higher mean arterial pressure (MAP), body mass index (BMI), waist circumference (WC) and plasma endothelial nitric oxide synthase (eNOS) levels in the PD control. Additionally, there were increased heart malondialdehyde levels, reduced heart superoxide dismutase and glutathione peroxidase activity as well as increased plasma interleukin-6, tumour necrosis factor alpha and C-reactive protein levels, indicating enhanced oxidative stress and systemic inflammation. Notably, both GTIN-treated groups showed significantly reduced plasma lipid levels and increased HDL, as well as decreases in MAP, BMI, WC and eNOS levels compared with the PD control. Additionally, GTIN significantly decreased heart lipid peroxidation, enhanced antioxidant activity and decreased plasma inflammation markers. In the third study, the PD group exhibited hepatic steatosis and liver dysfunction evidenced by significantly higher liver triglyceride (TAG) content, liver weights, sterol regulatory element-binding protein-1c (SREBP-1c), malondialdehyde (MDA) levels, and liver injury enzyme levels, along with decreased liver superoxide dismutase (SOD) activity, glutathione peroxidase (GPx) activity, and plasma bilirubin levels in comparison to NPD. Histologically, there was increased lipid droplet accumulation and structural disarray in the PD group. GTIN treatment significantly reduced liver TAGs, liver weights and plasma SREBP-1c levels, as well as improved liver SOD and GPx activity while decreasing liver MDA levels and liver injury enzymes in comparison to the PD control. Notably, GTIN treatment increased plasma bilirubin levels. Liver histology in the GTIN-treated groups revealed decreased lipid droplet accumulation and improved tissue integrity. In the fourth study, GTIN significantly reduced fluid intake, urine output and kidney weights in both the presence and absence of dietary intervention compared with the PD group, indicating improved renal function. Additionally, GTIN administration improved glomerular filtration rate, and normalized creatinine, albumin, urea and uric acid levels. It also improved electrolyte homeostasis by restoring renal sodium and potassium handling along with reduced plasma aldosterone levels. GTIN attenuated renal oxidative stress as evidenced by lower kidney MDA, interleukin-6, tumour necrosis factor-α and higher total antioxidant status levels. Additionally, GTIN reduced kidney injury markers including plasma KIM-1 and urinary podocin mRNA expression. Conclusion. This study demonstrated that chronic consumption of high-calorie diets led to the development of prediabetes. This was associated with impairments in glucose homeostasis as well as cardiovascular, liver and kidney functions. However, treatment with GTIN regardless of dietary intervention may ameliorate disturbed glucose homeostasis as well as cardiovascular, liver and renal dysfunction during prediabetes. These findings suggest that GTIN may represent a promising therapeutic alternative for the management of prediabetes, particularly where adherence to dietary intervention is difficult to maintain. This may help delay the progression from PD to T2DM and reduce the burden of T2DM-associated complications.
An integrated consent-centred ethical framework for human tissue research in South Africa.
(2026) Moonega, Seonaid.; Pillay, Sibusisiwe Pamela.; De Gama, Brenda Zola.
Human tissue research is essential to medical advancement; however, it raises complex ethical, legal, and regulatory challenges, particularly regarding consent, ownership, privacy, commercialisation, and emerging contemporary uses. In South Africa, these challenges are exacerbated by fragmented oversight and regulatory inconsistencies, underscoring the need for ethically coherent and contextually responsive governance. The purpose of this study was to investigate and document the ethical values underpinning human tissue research, examine the processes and regulatory frameworks governing human tissue research and human biobanks, identify gaps within existing national and international guidelines, and develop a comprehensive ethical framework to guide ethically responsible human tissue research in South Africa. This study employed a qualitative, exploratory design within a constructivist paradigm, combining empirical investigation and ethical analysis. Data were collected through semi-structured interviews with twenty-four (24) anatomists and human tissue researchers from national and international settings, fifteen (15) Human Research Ethics Committee (HREC) members from two South African universities, and nine (9) human biobank managers across South Africa. Interview data were anonymised, transcribed, and thematically analysed using NVivo, and findings were corroborated with national and international literature and validated through expert consultation. Findings from Chapter 2 revealed that anatomists and researchers perceived research involving living participants and deceased donors as ethically different, requiring differentiated consent models and regulatory approaches. While broad consent was generally supported for living participants, fully informed consent was favoured for cadaveric research. Significant governance gaps were identified relating to legacy and unconsented collections, foetal tissue research, commercialisation, the public display of human remains, and contemporary secondary uses of human tissue. Chapter 3 demonstrated that HRECs and human biobanks operate within fragmented governance environments, characterised by unclear legislative guidance, limited oversight, and the absence of a national ethics authority or human biobanking governance framework. Participants highlighted ethical challenges related to vulnerable populations, high-risk research contexts, and emerging technologies, particularly artificial intelligence (AI)-driven research. Following the synthesis of the findings from Chapter 2 and 3, the study developed an Integrated Consent-Centred Ethical Framework (ICEF) for human tissue research presented in Chapter 4. This five-layer framework positions consent as the ethical anchor and integrates five domains: 1) Foundational Consent Ethics; 2) Governance of Legacy and Unconsented Collections; 3) Sensitive Consent Contexts; 4) Biobank, Commercialisation, and Secondary Research Governance; and 5) Ethical Adaptation for Emerging Technologies, supported by continuous Governance and Regulatory Oversight. This framework could make a significant contribution to science since it provides (i) contextually grounded ethical guidance for South African researchers and (ii) practical tools, viz. structured consent form checklists, thus strengthening ethical governance, protecting human dignity, and promoting public trust in human tissue research. Overall, this thesis established a consent-centred ethical framework that strengthens governance, promotes social justice, and supports ethically responsible human tissue research in South Africa amid evolving scientific and technological change. Keywords: human tissue research, ethics, biobank, consent, governance, South Africa, framework development.
Machine learning vs traditional portfolio optimisation under different market conditions in exchange traded funds portfolios.
(2025) Mutemeri, Linah.; McCullough, Kerry-Ann Frances.; Zhou, Helper.
The rapid advancement of machine learning (ML), a branch of artificial intelligence that enables systems to learn from data, has significantly reshaped financial decisionmaking. This study examines the comparative performance of traditional and MLbased portfolio optimization methods in Exchange-Traded Funds (ETFs), which provide diversified exposure to equities, bonds, commodities, and alternative assets. ETFs’ liquidity, transparency, and cost-effectiveness make them an ideal context for testing optimization strategies. The research employs a three-stage methodology. First, a Systematic Literature Review (SLR) assesses the global application of ML techniques in portfolio optimization, highlighting models such as Random Forest (RF), Long Short-Term Memory (LSTM), and Support Vector Machines (SVM). Second, an empirical analysis uses daily return data from 33 JSE-listed ETFs spanning 2013–2023 to compare three traditional models Markowitz Model (MM), Conditional Value-at-Risk (CVaR), and Mean Absolute Deviation (MAD) with three ML models: Enhanced Radial Basis Function Artificial Neural Network (K4-RANN), Genetic Algorithms (GA), and Extreme Gradient Boosting (XGBoost). Third, event study methodology evaluates portfolio resilience during South African market shocks, namely the COVID-19 pandemic (2020–2022), the July 2021 social unrest, and the April 2022 KwaZulu-Natal floods. Performance is measured through mean return, standard deviation, and Sharpe ratio. Findings show that ML-based models generally outperform traditional approaches by generating higher risk-adjusted returns and improving diversification. Under normal market conditions, GA and K4-RANN produced portfolios with lower risk and stronger returns. During crises, XGBoost proved most effective, striking a balance between returns and volatility and demonstrating adaptability in turbulent markets. These results confirm the potential of ML models to enhance portfolio stability and resilience in both normal and distressed environments. The study concludes that portfolio managers and institutional investors should integrate ML-based optimization, particularly ensemble models like XGBoost, into dynamic allocation strategies. For policymakers and financial institutions in emerging markets, investment in ML infrastructure and data capabilities is recommended to drive innovation in asset management. Future research should investigate hybrid frameworks that merge traditional financial theory with ML to advance more comprehensive portfolio optimization approaches.
The potential of human serum S100 Calcium-binding Protein B, Glial Fibrillary Acidic Protein, Neuron-Specific Enolase, and Serum Amyloid A as biomarkers for Traumatic Brain injury in moderate and severe cohort.
(2026) Mafuika, Seke Nzau.; Lazarus, Lelika.; Harrichandparsad, Rohen.
Background: Traumatic brain injury (TBI) occurs due to a severe head injury caused by an external force during a vehicle accident, fall, domestic violence, or explosion. In sub-Saharan Africa, the prevalence of TBI is 150–170 per 100,000 individuals. It is estimated that by 2050, the prevalence of TBI in Africa will increase to 14.25±0.75 million. TBI is clinically evaluated and classified using the Glasgow Coma Score (GCS), with CT and MRI. However, GCS has many limitations. Therefore, the aim of this study was to investigate the role of serum GFAP, S100B, NSE and SAA as potential biomarkers for the detection and diagnosis of TBI. Methodology: The first phase of the experiment was the scan analysis (n=50) as recorded in the hybrid electronic medical registry, MediTech, at a large urban tertiary referral hospital in eThekwini, South Africa. The second phase utilized a multiplex immunoassay (ProcartaPlex, Thermo Fisher Scientific, 2024) to detect human serum GFAP, S100B, NSE and SAA in n=50 patients with moderate to severe TBI and n=25 control patients. Ethics approval was obtained from the Biomedical Research Ethics Committee (Ref. BREC/00002147/2020) of the University of KwaZulu-Natal. Statistical analysis was achieved using Statistical Package for the Social Sciences version 30.0.0.0 (SPSS; IBM Corporation 2025). Results: Serum GFAP and S100B concentrations were significantly elevated in patients with moderate and severe TBI compared with the control group (P < 0.001). No significant differences between the moderate and severe groups were detected for GFAP or S100B (P=0.2623, P>0.999). The serum concentrations of NSE and SAA proteins were also significantly upregulated in the moderate and severe TBI compared to the control group (p<0.0001) and (p= 0.0002), respectively. Conclusion: These findings suggest that elevated serum concentrations of GFAP, S100B, NSE and SAA are indicative of increasing severity of TBI. These findings suggest that combining GFAP, S100B, NSE, and SAA biomarkers with GCS and CT findings enhances the accuracy of TBI classification.