University of the Free State

Synthetic biology is transforming how we understand and teach microbial energy metabolism. In a recent study (F. Li, B. Zhang, X. Long, H. Yu, et al., Nat Commun 16:2882, 2025, https://doi.org/10.1038/s41467-025-57497-z), the authors demonstrated a synthetic gene circuit that enables Shewanella oneidensis to produce and release phenazine-1-carboxylic acid, a redox-active metabolite that enhances extracellular electron transfer and electricity generation. This perspective highlights the significance of their work, focusing on how controlling the production of redox mediators provides new insights into microbial electron flow and bioelectronic design. Beyond its technological implications, this system also serves as a valuable educational case study for teaching principles of redox balance, gene regulation, and metabolic engineering. Viewing this advancement in the context of biology education underscores the potential of synthetic circuits to deepen our understanding of microbial metabolism and to promote interdisciplinary learning in microbiology, biotechnology, and engineering.

We investigate the influence of Zinc (Zn) proportion on the structural, morphological and optical properties of Zinc doped Lead iodide (Zn–PbI 2 ). The doped precursors were synthesed by adding varying amount of Zinc acetate to Lead iodide from 2 % to 6 %. The X-ray diffraction analysis shows that the peaks positions slightly shifted towards high 2theta for Zn–PbI 2 . The film surfaces were improved with Zn incorporation and the thickness slight increases from 472.440 nm for PbI 2 –474.445 nm for 4 % Zn–PbI 2 . A noticeable decrease in the ratio of Pb–Zn from 2.7:1 for PbI 2 to 2.2:1 for the 4 % doped sample was observed. The lowest value (22.494 nm) of the root mean square roughness was observed in the 4 % doped sample. It was observed that the doped samples exhibit a blue shift in the major peaks of the photoluminescence intensity from 524 nm for PbI 2 to 519 nm. The energy gap was observed to decrease from 2.63 eV for 0 % Zn–PbI 2 –2.42 eV 4 % Zn–PbI 2 sample. The absorbance, reflectance, extinction coefficient and imaginary part of dielectric constant were found to have their peak intensities when 4 % Zn was added to PbI 2 .While transmittance, refractive index and real part of dielectric constant were found to have their least intensities when 4 % Zn was added. The 4 % doped sample was observed to be the most suitable material for optoelectronic and photovoltaic applications due to its outstanding properties.

Water contamination by heavy metals poses serious risks to human health, ecosystems, and food security. Established and commonly used remediation methods have limitations in terms of cost, sustainability, and environmental impact, especially in under-resourced, developing, and underdeveloped countries. Recently, the emergence of biodegradable polymer blend foams filled with carbonaceous materials, such as graphene oxide and carbon nanotubes, offers environmentally friendly adsorbents for heavy metals in water. However, a consolidated, synthetic overview of the evidence on material design, properties, adsorption capacities, and efficiencies remains lacking for these foams. The current systematic review aims to synthesise and critically evaluate the existing evidence on the fabrication, properties, adsorption mechanisms, and applicability of biodegradable polymer blend foams filled with carbonaceous materials for adsorbing heavy metals in water. The review also seeks to develop a consolidated evidence document that will inform policy, guide future research, and assist the development and implementation of sustainable treatment technologies for the removal of heavy metals in water in resource-limited areas. This systematic review protocol is based on the question, "What is the adsorption efficiency and capacity of biodegradable polymer blend foams filled with carbonaceous materials in the removal of heavy metals from water?" A comprehensive search will be conducted using electronic bibliographic sources like Web of Science (core collections), Scopus, ScienceDirect, and search engines like PubMed, together with grey literature like Google Scholar, targeting peer-reviewed studies on laboratory and pilot-scale investigations of biodegradable polymer blend foams filled with carbonaceous materials for the removal of heavy metals from water. Eligibility criteria include studies on any type of water contaminated with heavy metals such as lead, copper, chromium, and cadmium. The extraction of data will be focused on material composition, processing techniques, characterisation, and adsorption performance. Quantitative data will be tabulated and, where applicable, subjected to meta-analysis. Researchers, consultants, and municipalities - especially in South Africa- will be consulted to contextualise findings and assist in translating evidence into practical water treatment solutions.

AI-driven personalised learning is increasingly shaping mathematics education, yet evidence remains fragmented regarding its role in developing learners’ mathematical problem-solving skills. This systematic review examined how AI-driven personalised learning influences students’ mathematical problem-solving skills. A structured search of recent empirical studies (2019–2025) identified 20 eligible investigations, which were analysed thematically. Findings show that AI tools, such as adaptive learning systems, intelligent tutoring systems, and chatbots, can enhance mathematical problem solving by providing tailored feedback, adaptive challenges, and scaffolded support that align with learners’ needs. These benefits were observed across primary, secondary, and tertiary settings, contributing to enhanced conceptual understanding, improved strategic reasoning, and increased learner engagement. At the same time, the review highlights notable variations in effectiveness. Some studies have reported an over-reliance on AI hints, misaligned adaptivity, platform complexity, and limited teacher readiness, which have constrained learners’ development of independent problem-solving skills. Infrastructure disparities and data privacy concerns also emerged as persistent challenges. Despite the growing number of studies on AI in mathematics education, limited systematic evidence exists that focuses specifically on AI-driven personalised learning and its influence on mathematical problem-solving processes. This review addresses this gap by synthesising recent empirical studies and identifying the key mechanisms through which AI personalisation supports or constrains learners’ problem-solving development. In general, the review suggests that AI-driven personalised learning holds meaningful potential for strengthening mathematics instruction when grounded in sound pedagogy and supported by adequate technological and instructional resources. This synthesis contributes evidence-based insights for educators and policymakers aiming to integrate AI responsibly and effectively in mathematics education.

Illegal trade in leopard tortoises Stigmochelys pardalis is widespread, yet the origins of confiscated S. pardalis are often unknown. Accurate assignment to source populations is essential for informed conservation management and release. We expanded and tested a genetic reference database for assigning S. pardalis to their original wild populations in KwaZulu-Natal Province, South Africa, and Eswatini. We added 50 newly genotyped wild S. pardalis sampled across these regions to the database and then evaluated the updated database by sampling and assessing 50 S. pardalis of unknown geographic origin held at a rehabilitation centre in KwaZulu-Natal. Genetic assignment indicated that only a single S. pardalis at the rehabilitation-centre may have originated from KwaZulu-Natal, highlighting the extent of illegal trade, translocation, and possession of S. pardalis. Individuals of verified regional origin were subsequently rehabilitated and translocated for soft release at appropriate sites.

Tuberculosis is one of the world’s most infectious killers, and the rate at which resistance to available medication develops is alarming. Targeting the ATP synthase of Mycobacterium tuberculosis as a strategy to kill the bacteria therapeutically has gained traction. Currently, bedaquiline is used as the cornerstone to treat TB; however, the emergence of resistance to this drug has been reported. This underscores the need to develop novel therapeutic agents. In this study, we employed computational techniques through molecular docking, MMPBSA ranking, DFT, and molecular dynamics simulation to screen phytochemicals from Indian medicinal plants for potential ATP synthase inhibitors. Isoverticine and convallamarogenin were identified based on their good docking scores and total free binding energies (-29.27 Kcal/mol and − 28.37 Kcal/mol, respectively). These compounds were shown to possess good reactivity features from DFT studies. They exhibited similar interaction patterns to bedaquiline, characterized by uniquely strong hydrogen and salt bridge interactions with GLU65 of the subunit C in the Fo region. They also exhibited good druglikeness with minimal interference with metabolic enzymes and possessed good toxicity profiles. Molecular dynamics showed the compounds stabilized within the binding site with resultant reduction in the residual fluctuations of the subunit C. In conclusion, isoverticine and convallamarogenin could serve as lead compounds in the development of anti-TB agents.

Sustainable agricultural intensification necessitates precise deficit irrigation strategies to address global water scarcity. However, optimizing intra-seasonal scheduling under stochastic climatic conditions remains a complex control problem. While Deep Reinforcement Learning (DRL) offers a promising approach to flexible decision-making, existing applications often exhibit instability due to high-dimensional state spaces and an inability to enforce physical constraints. This study advances state-of-the-art irrigation control by proposing and benchmarking a tailored DRL framework based on Proximal Policy Optimization (PPO), coupled with the AquaCrop-OSPy simulation model. Moving beyond standard implementations, the research introduces specific enhancements to the learning agent: a reduced observation space limited to five causal biophysical variables, action masking to ensure strict adherence to seasonal water quotas, and a dense reward function based on transpiration efficiency. To rigorously quantify the value of information, the proposed approach is benchmarked against both a standard DRL baseline and a global Evolutionary Algorithm configured with perfect foresight of future weather events. This "oracle" defines the theoretical upper bound of achievable crop water productivity. Experimental validation on maize cultivation under deterministic and stochastic scenarios (Tunis and Nebraska) demonstrates that the proposed agent effectively navigates the trade-off between conservation and yield. The enhanced agent captures approximately 93.5% of the theoretical yield potential defined by the oracle, indicating a minimal performance penalty for the lack of future weather knowledge. Conversely, the standard reference implementation failed to converge under tight resource constraints. Economically, the proposed strategy not only stabilizes yields during extreme drought years but also increases mean net profits by up to 66% compared to the baseline. These findings confirm that integrating domain knowledge through action masking and feature selection transforms DRL into a robust tool for near-optimal irrigation scheduling without requiring extensive weather forecasting.

This study evaluated the effects of fly ash (F) and effective microorganisms (EM) on nutrient dynamics and heavy metal transformations during vermicomposting of camel manure (CM). Four treatments (CM, CM + F, CM + EM, and CM + F + EM) were arranged in a completely randomized design and monitored over 12 weeks. Significant (p < 0.05) treatment and time interactions were observed for pH, NH4-N, Mn, Pb, and Mo. The addition of EM resulted in a greater decline in pH compared to other treatments. After 12 weeks, Olsen P increased from 300.62 to 398.71 mg/kg in CM + EM, while NH4-N increased markedly from 22.74 to 86.62 mg/kg. In contrast, NO3/NO2-N declined in EM-amended treatments but increased in the control and CM + F. Trace metal concentrations generally increased due to mass reduction during vermicomposting yet remained within internationally acceptable limits. Germination index (GI) values varied significantly among crops and treatments, ranging from phytotoxic to non-phytotoxic responses. Although CM + EM produced superior nutrient enrichment, several vegetables exhibited GI values below 50%, indicating potential phytotoxicity for sensitive crops. In case of established crops for which nutrient supply outweighs early phytotoxic concerns, CM + EM represents the most agronomically beneficial option. Future studies should explore blending CM + EM and CM + F with stabilizing amendments such as biochar to optimize nutrient availability while minimizing salinity and phytotoxic risks.

ABSTRACT Drawing on recent insights in queer African studies, this article presents a three-part historiographic critique of selected written histories of women’s same-sex intimacies in Lesotho. Specifically, I critically analyse two widely cited twentieth-century studies by Kathryn Kendall and Judith Gay, as well as their numerous twenty-first-century academic afterlives. The first part of the critique focuses on the dangers of Western-authored (mis)translations and of subsequent citational chains that rely on a single source, as I discuss the disjuncture between how the word ‘motsoalle’ is used amongst contemporary Sesotho speakers in Lesotho and the ways that it has come to be (mis)used and (mis)interpreted in Western academic scholarship. The second part of my critique takes a closer look at specific examples of contentious (mis)readings of Kendall’s and Gay’s studies, while the third part counters this with a focus on the viewpoints of contemporary Basotho women scholars. In conclusion, the article calls not only for Basotho-led scholarship but also for the importance of recognising both cultural untranslatability and the unknowability of historical Basotho same-sex intimate practices.