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Abstract South Africa was the most affected country in Africa by the coronavirus disease 2019 (COVID-19) pandemic, where over 4 million confirmed cases of COVID-19 and over 102,000 deaths have been recorded since 2019. Aside from clinical methods, artificial intelligence (AI)-based solutions such as machine learning (ML) models have been employed in treating COVID-19 cases. However, limited application of AI for COVID-19 in Africa has been reported in the literature. This study aimed to investigate the performance and interpretability of several ML algorithms, including deep multilayer perceptron (Deep MLP), support vector machine (SVM) and Extreme gradient boosting trees (XGBoost) for predicting COVID-19 mortality risk with an emphasis on the effect of cross-validation (CV) and principal component analysis (PCA) on the results. For this purpose, a dataset with 154 features from 490 COVID-19 patients admitted into the intensive care unit (ICU) of Tygerberg Hospital in Cape Town, South Africa, during the first wave of COVID-19 in 2020 was retrospectively analysed. Our results show that Deep MLP had the best overall performance (F1 = 0.92; area under the curve (AUC) = 0.94) when CV and the synthetic minority oversampling technique (SMOTE) were applied without PCA. By using the Shapley Additive exPlanations (SHAP) model to interpret the mortality risk predictions, we identified the Length of stay (LOS) in the hospital, LOS in the ICU, Time to ICU from admission, days discharged alive or death, D-dimer (blood clotting factor), and blood pH as the six most critical variables for mortality risk prediction. Also, Age at admission, Pf ratio (PaO2/FiO2 ratio), troponin T (TropT), ferritin, ventilation, C-reactive protein (CRP), and symptoms of acute respiratory distress syndrome (ARDS) were associated with the severity and fatality of COVID-19 cases. The study reveals how ML could assist medical practitioners in making informed decisions on handling critically ill COVID-19 patients with comorbidities. It also offers insight into the combined effect of CV, PCA, and SMOTE on the performance of ML models for COVID-19 mortality risk prediction, which has been little explored.

Rooibos tea, traditionally consumed by Indigenous populations, is naturally caffeine-free and contains unique polyphenols with strong antioxidant, anti-inflammatory and anti-hyperglycaemic properties. As such, a systematic review was conducted following PRISMA 2020 guidelines (PROSPERO ID: CRD42023467829) to evaluate the potential association between rooibos tea consumption and health outcomes. Relevant articles were searched from journal inception until October 2024 using five electronic databases (CINAHL, MEDLINE, Scopus, Web of Science Core Collection and Google Scholar) and one register (Cochrane Clinical Register of Controlled Trials). Included studies involved consumption of any rooibos tea beverage or supplement in humans 18 years or older and reported any health outcomes measured pre- and post-intervention. Following article screening and full text review, eight studies (175 participants) fulfilled the inclusion criteria and investigated the effects of rooibos consumption on biological [blood (n = 6); urine (n = 1)] and physiological [heart metrics (n = 2); muscle strength (n = 1)] health markers. Based on the included studies, the findings suggest benefits of rooibos consumption, particularly related to cardiometabolic health, with five studies supporting significant (p < 0.05) results. However, there is insufficient evidence to support the health benefits of rooibos consumption given the limited studies meeting inclusion criteria, the narrow scope of markers assessed and interstudy heterogeneity.

Abstract Chronic psychosocial stress is implicated in the onset and progression of noncommunicable diseases, and mechanisms underlying this relationship include alterations to the intracellular redox state. However, such changes are often investigated in isolation, with few studies adopting a system level approach. Here, male Wistar rats were exposed to 9.5 weeks of chronic unpredictable mild stress and redox status assays were subsequently performed on cardiac, hepatic, and brain tissues versus matched controls. The stressed rats displayed an anxious phenotype, with lowered plasma corticosterone levels (p = 0.04 vs. Controls) and higher plasma epinephrine concentrations (p = 0.03 vs. Controls). Our findings showed organ‐specific redox profiles, with stressed rats displaying increased myocardial lipid peroxidation (p = 0.04 vs. Controls) in the presence of elevated nonenzymatic antioxidant capacity (p = 0.04 vs. Controls). Conversely, hepatic tissues of stressed rats exhibited lowered nonenzymatic antioxidant capacity (p

Cardiovascular diseases (CVDs) are considered the predominant cause of death globally. An abnormal increase in biomarkers of oxidative stress and inflammation are consistently linked with the development and even progression of metabolic diseases, including enhanced CVD risk. Coffee is considered one of the most consumed beverages in the world, while reviewed evidence regarding its capacity to modulate biomarkers of oxidative stress and inflammation remains limited. The current study made use of prominent electronic databases, including PubMed, Google Scholar, and Scopus to retrieve information from randomized controlled trials reporting on any association between coffee consumption and modulation of biomarkers of oxidative stress and inflammation in healthy individuals or those at increased risk of developing CVD. In fact, summarized evidence indicates that coffee consumption, mainly due to its abundant antioxidant properties, can reduce biomarkers of oxidative stress and inflammation, which can be essential in alleviating the CVD risk in healthy individuals. However, more evidence suggests that regular/prolonged use or long term (>4 weeks) consumption of coffee appeared to be more beneficial in comparison with short-term intake (

The consumption of food-derived products, including the regular intake of pepper, is increasingly evaluated for its potential benefits in protecting against diverse metabolic complications. The current study made use of prominent electronic databases including PubMed, Google Scholar, and Scopus to retrieve clinical evidence linking the intake of black and red pepper with the amelioration of metabolic complications. The findings summarize evidence supporting the beneficial effects of black pepper (Piper nigrum L.), including its active ingredient, piperine, in improving blood lipid profiles, including reducing circulating levels of total cholesterol, low-density lipoprotein cholesterol, and triglycerides in overweight and obese individuals. The intake of piperine was also linked with enhanced antioxidant and anti-inflammatory properties by increasing serum levels of superoxide dismutase while reducing those of malonaldehyde and C-reactive protein in individuals with metabolic syndrome. Evidence summarized in the current review also indicates that red pepper (Capsicum annum), together with its active ingredient, capsaicin, could promote energy expenditure, including limiting energy intake, which is likely to contribute to reduced fat mass in overweight and obese individuals. Emerging clinical evidence also indicates that pepper may be beneficial in alleviating complications linked with other chronic conditions, including osteoarthritis, oropharyngeal dysphagia, digestion, hemodialysis, and neuromuscular fatigue. Notably, the beneficial effects of pepper or its active ingredients appear to be more pronounced when used in combination with other bioactive compounds. The current review also covers essential information on the metabolism and bioavailability profiles of both pepper species and their main active ingredients, which are all necessary to understand their potential beneficial effects against metabolic diseases.

Chromatographic fractionation of a methanol extract of Helichrysum rutilans afforded seven known compounds. The isolated compounds were identified as 5,7,8-trihydroxy-3,6-dimethoxyflavone-8-O-2-methyl-2-butanoate (C-1), 5,7-dihydroxy-3,6,8-trimethoxyflavone (C-2), 5-hydroxy-3,6,7,8-tetramethoxyflavone (C-3), 5-hydroxy-3,6,7-trimethoxyflavone (C-4), ent-kaurenoic acid (C-5), ent-kauran-18-al (C-6), and 15-α-hydroxy-(-)-ent-kaur-16-en-19-oic acid (C-7). Compounds C-1–C-4 demonstrated high antioxidant capacities on ORAC hydroxyl radical (2.114 ± 4.01; 2.413 ± 6.20; 1.924 ± 16.40; 1.917 ± 3.91) × 106; ORAC peroxyl radical (3.523 ± 3.22; 2.935 ± 0.13; 2.431 ± 8.63; 2.814 ± 5.20) × 103 µMTE/g; and FRAP (1251.45 ± 4.18; 1402.62 ± 5.77) µMAAE/g, respectively. Moderate inhibitory activities against Fe2+-induced lipid peroxidation were observed for C-1–C-4 as IC50 values of 13.123 ± 0.34, 16.421 ± 0.92, 11.64 ± 1.72, 14.90 ± 0.06 µg/mL, respectively, while their respective anti-tyrosinase activities with IC50 values of 25.735 ± 9.62, 24.062 ± 0.61, 39.03 ± 13.12, 37.67 ± 0.98 µg/mL were also observed. All compounds demonstrated TEAC values within the range of 1105–1424 µMTE/g. The result is an indication that a methanol extract of H. rutilans might possibly be a good source of natural antioxidants against ailments caused by cellular oxidative stress and as inhibitors against skin depigmentation, as well as possible raw materials needed for slowing down perishable agricultural products. This is the first report on the phytochemical and biological evaluation of H. rutilans.

Helichrysum species are prominent South African medicinal plants. From the essential oils (EOs) of three Helichrysum species, H. petiolare, H. odoratissimum, and H. cymosum, sixty-three constituent components were identified, with hydrocarbons and oxygenated monoterpenes and sesquiterpenes as major components. The compounds were analyzed by gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR) spectroscopy. In H. petiolare EO, the major components were faurinone (20.66%) and (E)-β-ocimene (17.21%). Faurinone was isolated from this EO for the first time. In H. odoratissimum, 1,8-cineole (17.44%) and α-pinene, and γ-curcumene (15.76%) were the major components whereas, in H. cymosum, α-pinene (29.82%) and (E)-caryophyllene (19.20%) were the major components. In the antibacterial activity study, the EOs were tested against Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. The EOs were found to possess low antibacterial, anti-tyrosinase, and photoprotection activities and moderate antioxidant capacities, thus establishing these Helichrysum EOs as valuable antioxidant agents.

Lipopolysaccharide (LPS), a well-conserved cell wall component of Gram positive bacteria, exerts its toxic effects via inducing oxidative and pro-inflammatory responses. Red palm oil (RPO) is a unique natural product with a balanced ratio of saturated and unsaturated fatty acids, with reported antioxidant and anti-inflammatory effects. In this study, we assess the protective effect and mechanistic action of RPO using a lipopolysaccharide (LPS)-induced hepatic injury model. Male Wistar rats were assigned into four groups (10 animals/group): normal control (NC), RPO, LPS and RPO + LPS. Animals in the RPO and RPO + LPS groups were administered RPO (200 μL/day) for 28 days. On the 27th day of experiment, animals in LPS and RPO + LPS groups were injected with LPS (0.5 mg/kg body weight). Animals were sacrificed 24 h later, and blood and liver tissues harvested for biochemical and molecular analysis. RPO resolved hepatic histological dysfunction induced by LPS, and lowered alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase and γ-glutamyl transferase activities in the serum. Hepatic malondialdehyde and conjugated dienes, as well as pro-inflammatory cytokines, including interleukin (IL)-1β, IL-6 and TNFα were significantly diminished (p < 0.05) by RPO pre-treatment. Activity of hepatic antioxidant enzymes including superoxide dismutase, glutathione reductase, glutathione peroxidase, as well as glutathione redox status (GSH:GSSG), and markers of antioxidant capacity that decreased as a result of LPS injection were improved by RPO pre-treatment. Mechanistically, RPO up-regulated mRNA expression of redox sensitive transcription factor Nrf2 and its downstream targets GCL and HO-1, while also suppressing the expression of NFκβ and associated inflammatory protein, Iκβ kinase (IκKβ). In conclusion, this study highlights the ameliorating effects of RPO against LPS-induced hepatic injury and revealed the Nrf2/GCL/HO-1 and NFκβ signaling axis as potential contributing mechanisms.

Diabetes mellitus (DM) is a group of systemic metabolic disorders with a high rate of morbidity and mortality worldwide. Due to the detrimental side effects of the current treatment, there is a great need to develop more effective antidiabetic drugs with fewer side effects. Natural products are a well-known source for the discovery of new scaffolds for drug discovery, including new antidiabetic drugs. The genus Helichrysum has been shown to produce antidiabetic natural products. In this investigation, the methanolic extract of H. cymosum and H. pandurifolium resulted in the isolation and identification of eleven known compounds viz 5,8-dihydroxy-7-methoxy-2-phenyl flavanone (1), pinostrobin (2), dihydrobaicalein (3), glabranin (4), allopatuletin (5), pinostrobin chalcone (6), helichrysetin (7), 5-hydroxy-3,7-dimethoxyflavone (8), 3,5-dihydroxy-6,7,8-trimethoxyflavone (9), 3-O-methylquercetin (10), and 3-methylethergalangin (11). The in vitro bio-evaluation of isolated compounds against alpha-glucosidase showed that 10, 5, and 11 demonstrated the highest alpha-glucosidase inhibitory activity with IC50 values of 9.24 ± 0.4, 12.94 ± 0.2, and 16.00 ± 2.4 μM respectively, followed by 7 and 3 with IC50 values of 18.16 ± 1.2 and 44.44 ± 0.2 μM respectively. However, none of these compounds showed a measurable inhibitory effect on alpha-amylase under the experimental conditions used except compound 10 which showed a poor alpha-amylase inhibitory activity with an IC50 value of 230.66 ± 15.8 μM. Additionally, strong total antioxidant capacities were demonstrated by 10, 5 and 7 in ferric-ion reducing antioxidant power assay (374.34 ± 69.7; 334.37 ± 1.7; 279.93 ± 0.8) µmol AAE/mmol. This is the first scientific report to be carried out on alpha-glucosidase inhibitory activities and antioxidant capacities of H. cymosum constituents and a first report on the isolation and identification of methoxyflavanoids from H. pandurifolium. Our findings suggest that these compounds are promising candidates to inhibit alpha-glucosidase as well as oxidative stress related to diabetes. Results from molecular docking provided insight into the observed in vitro alpha-glucosidase inhibitory activities for 5, 7, 10, and 11. It is envisaged that the isolated phytochemicals from these plants may contribute to the development of hypoglycemic lead compounds with anti-diabetic potential.

Background COVID-19 vaccines offer different levels of immune protection but do not provide 100% protection. Vaccinated persons with pre-existing comorbidities may be at an increased risk of SARS-CoV-2 breakthrough infection or reinfection. The aim of this study is to identify the critical variables associated with a higher probability of SARS-CoV-2 breakthrough infection using machine learning. Methods A dataset comprising symptoms and feedback from 257 persons, of whom 203 were vaccinated and 54 unvaccinated, was used for the investigation. Three machine learning algorithms – Deep Multilayer Perceptron (Deep MLP), XGBoost, and Logistic Regression – were trained with the original (imbalanced) dataset and the balanced dataset created by using the Random Oversampling Technique (ROT), and the Synthetic Minority Oversampling Technique (SMOTE). We compared the performance of the classification algorithms when the features highly correlated with breakthrough infection were used and when all features in the dataset were used. Result The results show that when highly correlated features were considered as predictors, with Random Oversampling to address data imbalance, the XGBoost classifier has the best performance (F1 = 0.96; accuracy = 0.96; AUC = 0.98; G-Mean = 0.98; MCC = 0.88). The Deep MLP had the second best performance (F1 = 0.94; accuracy = 0.94; AUC = 0.92; G-Mean = 0.70; MCC = 0.42), while Logistic Regression had less accurate performance (F1 = 0.89; accuracy = 0.88; AUC = 0.89; G-Mean = 0.89; MCC = 0.68). We also used Shapley Additive Explanations (SHAP) to investigate the interpretability of the models. We found that body temperature, total cholesterol, glucose level, blood pressure, waist circumference, body weight, body mass index (BMI), haemoglobin level, and physical activity per week are the most critical variables indicating a higher risk of breakthrough infection. Conclusion These results, evident from our unique data source derived from apparently healthy volunteers with cardiovascular risk factors, follow the expected pattern of positive or negative correlations previously reported in the literature. This information strengthens the body of knowledge currently applied in public health guidelines and may also be used by medical practitioners in the future to reduce the risk of SARS-CoV-2 breakthrough infection.