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Item Study of elastic modulus of Ti(70-x)-Nbx-Ta25-Zr5 alloys for biomedical applications(2025-11) Madigoe, Mandy N; Nyakane, N; Modiba, RosinahIn this study, titanium alloy Ti(70-x)-Nbx-Ta25-Zr5 (x = 5, 10 at.%) was synthesized using arc melting followed by water cooling and a series of heat treatments, specifically a solution treatment at 950ºC for one hour, water quenching, and aging at 480ºC for twelve hours under an argon atmosphere. The resulting microstructures predominantly exhibited a dendritic β phase, and prior β grain boundaries. Nanoindentation tests indicated that the lowest elastic Young’s modulus recorded for heat-treated sample Ti60-Nb10-Ta25-Zr5 was 66.6 ± 15.2 GPa. The XRD, EBSD and indentation and hardness results are presented in the paper.Item The utility of radiative transfer models (RTM) on remotely sensed data in retrieving biophysical and biochemical properties of terrestrial biomes: A systematic review(2025-05) Sibiya, Bongokuhle S; Odindi, J; Mutanga, Onisimo; Cho, Moses A; Masemola, Cecilia ROver the past few decades, there has been significant recognition of the value of Radiative Transfer Models (RTMs) for ecological remote sensing applications. This has led to various studies aimed at utilizing RTM techniques to quantify and map a range of biophysical and biochemical properties at different scales. Most literature reviews have predominantly focused on 1D models, such as PROSAIL, overlooking the more robust 3D models. This paper provides a detailed systematic review on the progress, gaps, and opportunities associated with both 1D and 3D RTM models in the context of remote sensing of terrestrial biomes. The review reveals a skewed distribution of research efforts between the Global North and South, with a significant concentration of studies conducted in the United States, China, and Germany, while fewer investigations have been conducted in Africa. Furthermore, most studies have primarily utilized MODIS and Landsat sensors, focusing on plant attributes such as Leaf Area Index (LAI) and chlorophyll content. These studies have been predominantly conducted in grassland and forest landscapes. Overall, the findings indicate that PROSPECT and PROSAIL have been the most popular models over the past two decades. In the realm of 3D models, the Discrete Anisotropic Radiative Transfer (DART) and Forest Light Interaction Model (FLIGHT) models have been the most popular. These models have been primarily utilized through the look-up table (LUT) method, followed by the hybrid approach combining machine learning and RTMs. Understanding both 1D and 3D models offers an opportunity to assess the current state of research and identify future opportunities in the application of radiative transfer modeling for ecological remote sensing. By addressing the existing gaps and leveraging advancements in modeling techniques, researchers can enhance the accuracy and applicability of remote sensing on various ecosystems.Item In-silico Lactochassis: In silico prediction of essential genes in Lacticaseibacillus casei: A step towards genome minimisation(2025) Mugwanda, Kanganwiro; Hamese, Saltiel; Takundwa, Mutsa M; Plessis, MD; Dicks, LMT; Prinsloo, E; Thimiri Govindaraj, Deepak BSynthetic biology using minimal-genome engineering has been proposed as the best way to optimize probiotic chassis. A minimal genome presents a significant advantage of enhanced production of heterologous proteins. This research article presents a comprehensive computational biology study for bacterial gene essentiality and genome reduction design within Lacticaseibacillus casei ATCC 393. This study used a computational biology approach to identify the essential genes of L.casei ATCC 393. Essential genes were identified using DELetion design by Essentiality Analysis Tool (DELEATv0.1), Gene Essentiality Prediction Tool for Complete-Genome Based on Orthology and Phylogeny (Geptop2), the Database of Essential Genes (DEG), and Alignable Tight Genomic Clusters-Clusters of Orthologous Genes (ATGC-COG). The criteria for identification of essential genes included phyletic retention (essential orthologs), codon usage, G + C content, length, hydrophobicity score, and essential genomic elements, such as protein-coding genes and noncoding RNAs, among other factors. Using a consensus approach, 633 putative essential genes were identified. In addition, 145 genes associated with probiotic attributes, such as the production of bacteriocins, bile and acid resistance, immune modulation, and adherence to host gut epithelia, were identified. The directed evolution by serial passage was initiated by streaking L. casei ATCC 393 as part of the test phase of the Design-Build-Test-Learn (DBTL) cycle. The survival rate data were calculated from mean 0D600 nm readings. The data revealed a significant difference in survival rates between E1 and E2 from day 1 to day 38 (V = 224, p = 0.00745), indicating that factors, possibly inherent to the isolates themselves or subtle variations in the environment, may be influencing the results. Overall, the significant differences suggest that survival rates were affected by specific NaCl concentrations. Lower survival rates were observed at 50 g/L and 71g/L compared to other concentrations. The in-silico analysis yielded valuable insights into the essential genes of L. casei ATCC 393. Further, it contributes to understanding the fundamental genetic makeup of L. casei ATCC 393 and its potential as a probiotic chassis for various applications, including the development of novel biotherapeuticsItem Building sustainable learning factories: Lessons from four case studies in South Africa(2025-10) Hattingh, T; Matebese, Belinda T; Louw, L; Lourens, A; Du Plessis, CAlthough learning factories are a proven approach to develop graduates who are prepared for the challenges of the real world, ensuring their sustainability can be a challenge. This is particularly true for learning factories in developing countries that experience unique contextual challenges. This study aims to understand what drives sustainability by reporting on the experiences of four learning factories in South Africa to identify successes and challenges. This study adopts a qualitative, multiple-case study approach, focusing on the experiences of involved individuals. Data collection included personal reflections and collaborative discussions between participants actively involved in the learning factory cases. This was followed by an analysis to draw out key themes and insights. The findings of this study present six emergent themes that support the sustainability of learning factories. These include alignment, collaboration, operational focus, diverse funding, adaptability and improvement. This study contributes to the existing literature on the sustainability of learning factories and proposes critical success factors that can support those proposing, establishing, or managing learning factories. It further draws attention to factors relevant to developing countries where contextual factors create unique challenges.Item Appraisal of the composition, structure, diversity, and functioning of bacterial and fungal communities in drinking water systems: A case study in the developing world(2025-08) Nduli, S; Tekere, M; Masenya, K; Masindi, Vhahangwele; Foteinis, SBacterial and fungal communities’ successions were examined in a typical drinking water system in South Africa (Global South) using metagenomic sequencing. Bacterial taxa abundance was similar in water matrices but not in biofilm samples with Bacteroidota being higher in tap water and Actinobacteriota, Firmicutes, and Chloroflexi in biofilms. Fungal taxa abundance varied less, with Rozellomycota and Basidiomycota being interchangeably abundant. Both bacterial and fungal taxa and richness decreased during chlorination, but bacterial increased and fungal decreased in the distribution system. Fungal and particularly bacterial communities’ diversity in raw water was closely clustered together with biofilm samples, which could suggest that biofilms act as a sink and reservoir for microbes found in raw water, however microbes’ resuspension or dispersion from biofilms was less likely. Functional profile prediction revealed the presence of mainly common metabolic pathways for pathogenesis, antibiotic or chlorine resistance, with the denitrification pathway being significantly enriched within the distribution network. Finally, changes in residual chlorine had a larger influence on the composition and structure of bacterial fractions than the fungal communities. Given that drinking water systems in the developing world are ridden with many challenges, assessing both planktonic and biofilm communities is much-needed, particularly at their distal ends where chlorine decay is more pronounced and microbial regrowth can be an issue of prime concern. Finally, metagenomics analyses can shed light on bacterial and fungal succession and dynamics across the water supply chain and identify microbial risks. This can inform evidence-based interventions to underpin improved water quality and protect public health in South Africa and further afield.Item Privacy and legal implications regarding the processing of Honeypot Data(2025) Ngoma, B; Mpekoa, N; Pieterse, HeloiseCyberattacks have been an ever-increasing threat against the cyber infrastructure of organisations. The act of exploiting known network vulnerabilities appears to be highly appealing to hackers where their potential payout is to find and collect valuable data housed by an organisation. To compensate for this matter, security teams can design and deploy highly advanced security tools to thwart cyberattacks, and one such tool is a honeypot. Honeypots possess the functionality of baiting intruders to interact with them whilst preventing said intruders from affecting real production and service systems. Ultimately, honeypots collect data associated with an intruder and the attack, which reveals valuable information that can be analysed and used to combat similar incidences. However, with the introduction of modern privacy laws, a number of consequences exist with the data honeypots collect. The paper will explore the limitations on processing honeypot data with the aid of related works published regarding honeypots, the POPI Act and the GDPR through literature revisions. Thus, this paper will discuss the privacy and legal implications that arise with processing data collected by a honeypot from the perspective of privacy laws established by both the European Union and the South African government.Item Refurbishment of small diameter nitrided spindles with laser based direct energy deposition(2025-11) Louw, Daniel F; Theron, Maritha; Rossouw, Jacob H; Scheepers, R; Amir, MLaser based direct energy deposition is a process that is commonly used to refurbish worn components in the power generation sector. In this work the potential for refurbishment of nitrided spindles manufactured from AISI 420 SS, with a small diameter (20 mm), is evaluated. Firstly, the required material removal from the nitrided surface was established. Secondly, the distortion of the shaft was measured as a function of the length of the refurbished section, and the thickness of the added material. It was found that the shaft must be pre-machined to a depth of 0.4 mm to ensure a pore-free weld on AISI 420 SS subjected to a typical gas nitriding cycle. Furthermore, it was shown that the distortion of a 20 mm diameter shaft, with a length of 1000 mm, can be 0.12 mm, if a 200 mm long section of the shaft is repaired. Reasons for the distortion are discussed, and possible mitigation measures are proposed.Item Comparing artificial neural networks with variational quantum circuits for biomedical data classification(2025-11) Mpofu, Kelvin T; Mthunzi-Kufa, PThis study presents a comparative evaluation of Artificial Neural Networks (ANNs) and Variational Quantum Circuits (VQCs) for biomedical classification, using the Wisconsin Breast Cancer Diagnostic dataset. Both models were optimized using Bayesian hyperparameter tuning via Optuna to ensure a fair performance comparison. The ANN achieved high predictive accuracy (98.2%), F1 score (98.2%), and Area Under the Curve (AUC) (0.98), exhibiting stable convergence and efficient training. The VQC, though trained under classical simulation, attained a respectable accuracy of 86.5% and an AUC of 0.85, with notably strong recall (99.1%) for malignant cases, highlighting its potential in scenarios requiring high sensitivity. Loss curves, confusion matrices, and hyperparameter importance visualizations were used to interpret each model’s training behaviour and decision boundaries. While classical models remain superior in current biomedical classification tasks, VQCs offer promising computational advantages and potential scalability for complex, high-dimensional datasets. This work provides early benchmarks for quantum-classical comparisons in biomedical machine learning and offers guidance for future implementations as quantum hardware becomes more accessible.Item Towards a fast image alignment technique for multi-aperture UAV and CubeSat payloads(2025-11) Nana, Muhammad A; Seletani, Rofhiwa; Virendra Naidoo, Shrikant VThis paper compares various image alignment techniques implemented on low-powered embedded devices for use in multi-aperture UAV and CubeSat payloads. A novel method was introduced and executed alongside two established methods on an embedded processor: utilising images taken from a dual-aperture UAV payload for the performance evaluation. The techniques were evaluated based on processing time, wherein significant differences were observed, outside of the universally comparable structural similarity index (SSIM). The outcomes of this research indicate that among the methods compared, the proposed method requires the least amount of processing time without sacrificing alignment quality, making it suitable for use in, applicable, low-power applications.Item A review of circular economy opportunities in the mining sector(2025-12) Khan, Sumaya; Magweregwede, FCircular economy opportunities for the mining sector are presented in this paper. A literature review was undertaken, followed by qualitative data gathering through survey questionnaires and unstructured interviews, and stakeholder engagements through workshops. The circular economy opportunities were identified and categorised according to the three circular economy principles of designing out waste and pollution, keeping products and materials in use, and regenerating natural systems. Opportunities aligned with the first principle include increased ore extraction efficiency processes, water recovery and recycling, substitution of raw materials, technology and waste utilisation for carbon capture and biotechnology. The second principle includes opportunities such as zero waste-to-landfill strategies, repurposing of mine waste, re-mining of tailings, recycling metals and processing of residues, and urban mining of electronic waste. Opportunities aligned with the third principle include the adoption of renewable energy, green hydrogen production, repurposing of post mining landscapes, and eradication of alien invasive vegetation. Furthermore, the challenges of implementing circular economy in the mining sector are discussed. The current rate of waste generation from mining activities far exceeds the rate of reuse and repurposing. Recycling of large tyres and characterisation of hazardous electronic waste also pose challenges. The most implementable circular economy opportunities in the mining sector are those aligned with the second principle of keeping materials in use. The high impact opportunities aligned with the first principle of designing out waste and pollution, and the third principle of regenerating natural systems, are more difficult to implement as they require large investments.Item Evaluation of thermal performance of window materials for satellite payloads in low earth orbit (LEO)(2025-11) Baloyi, Andrew A; Dikole, Realeboga G; Naidoo, Shrikant V; Seletani, RofhiwaSelecting the appropriate window materials for use in space products such as Low Earth Orbit (LEO) satellite optical payloads is of critical importance. Windows on satellite optical payloads are essential for mission success and functionality. They serve a dual purpose: shielding the optical instrument’s interior from environmental hazards and physical damage, while allowing beneficial radiation to pass through, ensuring optimal performance. However, temperature gradients can deform an inherently plane-parallel window and turn it into a weak meniscus, introducing Optical Path Difference (OPD) into the wavefront. This may lead to defocusing, thereby reducing the payload’s performance. Design considerations to account for thermal stresses to prevent window damages such as “cracking”, “crazing” and “delamination” due to “thermal cycling” are vital. This paper analyses the thermal performance of ULE Corning 7972 and Fused Silica window materials for LEO satellite optical payloads, considering solar radiation, Earth’s Albedo (solar reflection), and Earth infrared radiation. ULE Corning 7972 outperformed Fused Silica due to its near-zero CTE, exhibiting less deformation and lower thermal stress. This analysis offers valuable insights into window material selection for enhanced reliability, durability, and functionality for LEO satellite optical payloads.Item Synthesis of prilocaine hydrochloride in continuous flow systems(2025-08) Sagandira, MB; Sagandira, Cloudius R; Watts, PHerein, we showcase how continuous flow technology enables the development of time-efficient, high-yielding synthetic routes for the anesthetic drug prilocaine. Starting from toluene nitration, prilocaine was synthesized in 74% (high-performance liquid chromatography (HPLC)) overall yield with a total residence time of just 13.6 min. Continuous flow technology markedly enhanced the nitration step’s selectivity, increasing it from 59% in batch to 79%. The toluidine alkylation step benefited significantly from superheating at 150 °C and enhanced mixing in the flow system, reducing the reaction time from 48 h in batch to merely 4.4 min, affording 98% yield. Additionally, we present streamlined continuous flow reaction, telescoping, and inline workup strategies.Item Sugarcane bagasse: A sustainable feedstock for biorefinery portfolios in South Africa(2025-08) Nhleko, Lindile NG; Sekoai, PTRising global populations, infrastructural development, and rapid urbanization have heightened the reliance on a linear economy, resulting in severe environmental and human impacts. This crisis has triggered an urgent quest for sustainable and ecologically benign innovations, as outlined in the United Nations’ Sustainable Development Goals (SDGs). This review investigates the potential of sugarcane bagasse (SCB) as a promising feedstock for advancing circular bioeconomy initiatives in South Africa. It shows how this copious bioresource can be utilized to enhance the country’s biobased value chains by producing bio-commodities, such as biofuels and platform chemicals. The review also identifies the driving forces behind the circular bioeconomy model within the South African sugarcane industry. To achieve the circular bioeconomy, it outlines essential technological prerequisites, including critical pretreatment strategies and emerging bio-innovations necessary for the effective valorization of SCB. Furthermore, it showcases the R&D and commercial strides that have been achieved in South Africa. Finally, the study covers techno-economic studies that corroborate the economic viability of this domain. In conclusion, harnessing SCB not only presents a viable biorefinery pathway towards sustainable economic growth but also contributes to environmental preservation and social well-being, aligning with global sustainability imperatives. The successful integration of these innovative approaches could play a pivotal role in transforming the South African sugarcane industry into a continental leader in circular bioeconomy innovations.Item Diagnostic advances and public health challenges for Monkeypox Virus: Clade-Specific insight and the urgent need for rapid testing in Africa(2025-11) Sambo, Caroline N; Skepu, Amanda; Nxumalo, Nolwandle P; Polori, KIBackground: Monkeypox (MPX), caused by the Monkeypox virus (MPOX) of the Orthopoxvirus genus, has re-emerged as a significant global health threat. Once confined to Central and West Africa, the 2022–2025 multi-country outbreaks, predominantly caused by Clade IIb, demonstrated sustained human-to-human transmission and global spread. Objective: This review summarizes current knowledge on MPX virology, epidemiology, clinical presentation, and diagnostic technologies, with a focus on innovations supporting rapid and field-deployable detection in resource-limited settings. Methods: The recent literature (2019–2025), including peer-reviewed studies, WHO and Africa CDC reports, and clinical guidelines, was critically reviewed. Data were synthesized to outline key developments in diagnostic methodologies and surveillance approaches. Results: MPX comprises two genetic clades: Clade I (Congo Basin) and Clade II (West African), which differ in virulence and transmission. Clade IIb is associated with sexual and close-contact transmission during recent outbreaks. Clinical manifestations have shifted from classic disseminated rash to localized anogenital lesions and atypical or subclinical infections. RT-PCR remains the diagnostic gold standard, while emerging assays such as loop-mediated isothermal amplification (LAMP), recombinase polymerase amplification (RPA), and CRISPR/Cas-based platforms show promise for rapid point-of-care (POC) testing. Complementary serological tools, including ELISA and lateral flow assays, enhance surveillance and immune profiling. Conclusions: The resurgence of MPX highlights the urgent need for accessible, sensitive, and specific diagnostic platforms to strengthen surveillance and outbreak control, especially in endemic and resource-constrained regions.Item Valorization of invasive water hyacinth for nutrients removal from eutrophic waterbodies and biochar production(2025-10) Tshikovhi, NA; Mudzanani, K; Phadi, T; Masindi, Vhahangwele; Foteinis, SAmong many plights caused by eutrophication, the overabundance of algae and aquatic plants constitutes external pressures and stresses mounted on aquatic ecosystems. Of the aquatic plants known to infest rivers and dams, water hyacinth is considered the most problematic due to its invasiveness that disrupts waterways and pose detrimental environmental and health risks. This non-native (alien or exotic) species is already impairing aquatic ecosystems in South Africa, while vast harvested quantities, currently considered a waste, further exacerbate the problem. However, when viewed under the circular economy and waste valorization lenses, water hyacinth can be an important resource. Here, this was used for biochar production, by examining different temperatures, with 500 °C providing high carbon content. HR-SEM-EDS, HR-TEM-EDS, and XRF revealed varying biochar compositions, all enriched with notable phosphorus levels. This reflects the highly degraded state of freshwater bodies in South Africa since water hyacinth is a known phosphorus hyperaccumulator. Thermal analysis revealed that the raw water hyacinth mainly (96 %) comprises water, while weight losses for biochar at 167–990 °C correspond to moisture and volatile matter removal. Finally, biochar yield decreased from 32.5 % at 300 °C to 24.7 % at 700 °C, confirming progressive devolatilization and carbon enrichment at higher temperatures. Overall, results suggest that water hyacinth, an invasive species that wreaks havoc in aquatic ecosystems, can be sustainably managed to improve freshwater quality through nutrients removal and then used for biochar production. The produced biochar could be a good candidate for (waste)water treatment (adsorption) and particularly soil amelioration, given its high phosphorus content, and carbon dioxide removal (CDR) capabilities.Item Privacy versus utility in federated learning: An experimental analysis of noise injection techniques(2025) Leope, NR; Eloff, JHP; Dlamini, Thandokuhle MFederated Learning (FL) enables decentralized model training, while maintaining the privacy of the underlying individual datasets. Therefore, FL can resolve some intrinsically privacy-sensitive challenges in domains, such as healthcare and finance. However, privacy preservation usually comes with a trade-off on the usefulness (i.e., utility) of the information. The research problem is how to optimize this inversely proportional trade-off balance between privacy and utility. This study uses an experimental comparative analysis, in a synthetic healthcare setting, of different noise types (i.e., Gaussian, Laplacian, Poisson, Uniform, and Exponential) injected on the client side at the input-feature level prior to local training to enhance privacy in FL. We explore the impact of these noise types on the privacy–utility trade-off in FL data. The findings indicate that although Laplacian, Poisson, and Exponential types of noise provides stronger obfuscation which often comes at the cost of utility. This confirms and amplifies the trade-off in maintaining the usefulness of the data against its privacy. More importantly, the findings also show that Gaussian noise generally offers the best trade-off between privacy and utility on this task, suggesting a practical default for privacy-aware FL in healthcare-like environments.Item The contribution of South African mining companies to the sustainable development goals: A knowledge synthesis from text mining(2025-12) Haywood, Lorren K; Oelofse, Suzanna H; Khan, Sumaya; Pelders, Jodi L; Maphalala, BusiThis study examines how the United Nations Sustainable Development Goals (SDGs) are prioritised and integrated within South Africa’s mining sector through an analysis of sustainability and integrated reports from the top 13 Johannesburg Stock Exchange-listed mining companies between 2020 and 2023. Using the SDG Mapper, a text-mining tool that quantifies direct and indirect references to all 17 SDGs, the research identifies focus areas and reporting gaps. Findings show a steady rise in SDG references over time, with SDG 13 (climate action), SDG 12 (responsible consumption and production), and SDG 8 (decent work and economic growth) dominating corporate disclosures. SDG 7 (affordable and clean energy) also features strongly, reflecting responses to climate risks and regulatory pressure through emissions reduction and renewable energy adoption. In contrast, SDG 6 (clean water and sanitation) and SDG 15 (life on land) have only recently gained traction, exposing uneven sustainability practices. SDG 3 (good health and well-being) receives moderate attention despite its prominence in global mining frameworks. The study highlights the need for a more balanced, integrated approach that addresses environmental, social, and governance dimensions, and advocates systems thinking to strengthen sustainable mining in South Africa and other emerging economies.Item A phenomenological methodology for wave detection in epidemics(2025-12) Brettenny, W; Holloway, Jennifer P; Fabris-Rotelli, I; Dudeni-Tlhone, Nontembeko; Abdelatif, Nontembeko; Le Roux, Wouter J; Manjoo-Docrat, R; Debba, PraveshIn both the management and modelling of epidemic outbreaks, the ability to determine the start of a wave of infections is of vital importance. Not only does this advantage the modelling of the outbreak, but, if done in real-time, can assist with a nation’s response to the disease. In this study, a bidirectional long-short-term-memory (Bi-LSTM) network is used to determine the start and end of the COVID-19 waves experienced in the district and metropolitan municipalities of Gauteng, South Africa, from 2020-2022 as well as the waves of the cholera outbreaks occurring in the Beira area of Mozambique between 1999 and 2005, in real-time. The problem of real-time scaling of the data prior to the first wave of an epidemic is addressed using globally available real-time information from first waves experienced in other countries and independent territories alongside the observed South African data. The use of the Bi-LSTM predicted starting dates is demonstrated for the second waves of COVID-19 infections experienced in Gauteng in 2020/21. Using the predicted starting dates, spatial-SEIR models are used to predict hospitalisations as a result of COVID-19 infections in each of the district and metropolitan municipalities of Gauteng. The fitted Bi-LSTM model demonstrates effectiveness in predicting the start and end dates of epidemic waves in real-time, allowing for pre-emptive disease modelling and predictions of spread. Moreover, it is shown that the use cases for the fitted model are not limited to COVID-19 studies, but can also be applied to other disease outbreaks that follow similar wave patterns.Item Scoping the progress of e-Government services in South Africa: A journey from implementation to adoption and recommendations for addressing challenges that impede or slow down progression(2025-07) Nunu, Vuyisa; Maremi, Keneilwe J; Thulare, TumisoThis paper explores the development of e-government services in South Africa, tracing the journey from initial adoption to implementation based on literature findings. It emphasizes the stages of e-government evolution, highlighting the key drivers that promote advancements and the challenges that impede progress. The purpose of this paper is to inform government officials and policymakers about the obstacles that negatively impact e-government initiatives. Through a scoping review, the research examines existing studies on the implementation and adoption of e-government, focusing on technological, social, and economic factors. The findings indicate significant progress in the implementation of e-government services, driven by technological advancements and policy measures. However, the adoption phase faces challenges, including issues related to the digital divide, inadequate technological infrastructure, and user resistance. The paper concludes with a set of recommendations aimed at supporting evidencebased decision-making and advancing digital transformation within the public sector. These recommendations are presented for the consideration of government authorities and policymakers to foster a more inclusive and efficient public administration.Item Phosphite inhibits Phytophthora cinnamomi by downregulating oxidoreductases and disrupting energy metabolism(2025) Prabhu, SA; Naicker, P; Duong, TA; Govender, Ireshyn S; Engelbrecht, J; Backer, R; Stoychev, SH; Van den Berg, NPhytophthora root rot caused by the hemibiotrophic oomycete, Phytophthora cinnamomi is a major biotic hindrance in meeting the ever-increasing demand for avocados. In addition, the pathogen is a global menace to agriculture, horticulture and forestry. Phosphite trunk injections and foliar sprays remain the most effective chemical management strategy used in commercial avocado orchards against the pathogen. Phosphite is known to counter P. cinnamomi both directly and indirectly through fortification of host defense. However, phosphite's direct mode of action is still not understood completely. This study identified a P. cinnamomi isolate GKB4 sensitive to phosphite (EC50 of 27.9 μg/mL) and investigated the direct impact of phosphite on this isolate through label-free quantitative SWATH-MS. Proteomics data analysis of untreated vs. phosphite-treated samples revealed that the xenobiotic affects the pathogen's growth by targeting the oxidoreductases whose abundance is significantly reduced. Further, perturbations in the energy metabolism and membrane/transmembrane proteins and transporters, and oxidative stress contribute to growth inhibition. The current study also identified increased putrescine biosynthesis, a polyamine, that when present at non-optimal concentrations could be cytostatic/cytotoxic. The differential expression of enzymes involved in the biosynthesis of secondary metabolites and the intermediates/precursors involved in their biosynthesis is an interesting finding that needs further investigation to ascertain their role in phosphite-induced stress. The pathogen's attempt to counter phosphite's growth-inhibitory effects—through upregulation of alternate bioenergetics pathways (amino acid catabolism and β-oxidation of fatty acids), mitochondrial translation and translocation machinery, peroxisomal proteins, and antioxidants—appears ineffective. This research furthers our limited understanding of the direct in vitro effects of phosphite on P. cinnamomi and has identified potential candidates for molecular functional investigation.