Freshwater resources play a pivotal role in sustaining life and meeting various domestic, agricultural, economic, and industrial demands. As such, there is a significant need to monitor the water quality of these resources. Water quality index (WQI) models have gradually gained popularity since their maiden introduction in the 1960s for evaluating and classifying the water quality of aquatic ecosystems. WQIs transform complex water quality data into a single dimensionless number to enable accessible communication of the water quality status of water resource ecosystems. To screen relevant articles, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed to include or exclude articles. A total of 17 peer-reviewed articles were used in the final paper synthesis. Among the reviewed WQIs, only the Canadian Council for Ministers of the Environment (CCME) index, Irish water quality index (IEWQI) and Hahn index were used to assess both lotic and lentic ecosystems. Furthermore, the CCME index is the only exception from rigidity because it does not specify parameters to select. Except for the West-Java WQI and the IEWQI, none of the reviewed WQI performed sensitivity and uncertainty analysis to improve the acceptability and reliability of the WQI. It has been proven that all stages of WQI development have a level of uncertainty which can be determined using statistical and machine learning tools. Extreme gradient boosting (XGB) has been reported as an effective machine learning tool to deal with uncertainties during parameter selection, the establishment of parameter weights, and determining accurate classification schemes. Considering the IEWQI model architecture and its effectiveness in coastal and transitional waters, this review recommends that future research in lotic or lentic ecosystems focus on addressing the underlying uncertainty issues associated with the WQI model in addition to the use of machine learning techniques to improve the predictive accuracy and robustness and increase the domain of application.

The biodiversity of medicinal plants in South Africa makes them rich sources of leading compounds for the development of novel drugs. Peltophorum africanum (Fabaceae) is a deciduous tree widespread in South Africa. The stem bark has been traditionally employed to treat diarrhoea, dysentery, sore throat, wounds, human immunodeficiency virus/ acquired immune deficiency syndrome (HIV/AIDS), venereal diseases and infertility. To evaluate these ethnobotanical clues and isolate lead compounds, butanol and ethyl acetate extracts of the stem bark were screened for their inhibitory activities against HIV-1 using MAGI CCR5+ cells, which are derived from HeLa cervical cancer cells and express HIV receptor CD4, a chemokine receptor CCR5 and HIV-LTR-β- galactosidase. Bioassay-guided fractionation using silica gel chromatography was also conducted. The ethyl acetate and butanol extracts of the stem bark of Peltophorum africanum showed inhibitory activity against HIV-1, CXCR4 (X4) and CCR5 (R5) tropic viruses. The ethyl acetate and butanol extracts yielded previously reported anti-HIV compounds, (+)-catechin, a flavonoid, and bergenin, a C-galloylglycoside, respectively. Furthermore, we identified betulinic acid from the ethyl acetate fraction for the first time. The fractions, which contained betulinic acid, showed the highest selective index. We therefore describe the presence of betulinic acid, a not well-known anti-HIV compound, in an African medicinal herb, which has been used for therapy, and claim that betulinic acid is the predominant anti-HIV-1 constituent of Peltophorum africanum. These data suggest that betulinic acid and its analogues could be used as potential therapeutics for HIV-1 infection.

Ticks are amongst the important ectoparasites where livestock are concerned, as they adversely affect the animals through bloodsucking. In tropical and subtropical countries, they transmit pathogens such as babesiosis, theileriosis, ehrlichiosis, and anaplasmosis in cattle, causing a reduction in production rate and significant concomitant economic losses. Ticks affect 80% of the cattle population across the world, with an estimated economic loss of USD 20–30 billion per year. In South Africa, economic losses in the livestock industry caused by ticks and tick-borne diseases are estimated to exceed USD 33 million per year (ZAR 500 million). There are seven major genera of ixodid ticks in Southern Africa (i.e., Amblyomma, Dermacentor, Haemaphysalis, Hyalomma, Ixodes and Rhipicephalus). The environment in which a tick lives is made up of all the various biological and abiotic factors that are either necessary or unnecessary for its life. The areas where various ticks have been found have been documented in many publications. Using these data, maps of possible species’ habitats can be made. Historical records on tick distribution may be incorrect due to identification mistakes or a change in the tick’s name. All the sources used to generate the maps for this review were unpublished and came from a wide range of sources. To identify tick species and the accompanying microbial ecosystems, researchers are increasingly adopting tick identification methods including 16S and 18S rDNA gene sequencing. Indeed, little is known about the genetic alterations that give important traits, including the predilection for tick hosts, transmission, and acaricide resistance. Opportunities for exploring these changes in tick populations and subpopulations are provided by advancements in omics technologies. The literature on the variety of ixodid ticks, their direct and indirect effects, and control methods in South Africa is compiled in this review.

Prevalence of Antiretroviral Drug Resistance Mutations and HIV-1 Subtypes among Newly-diagnosed Drugnaïve Persons Visiting A Voluntary Testing and Counselling Centre in Northeastern South Africa

Bacterial endophytes have emerged as critical components of plant microbiomes, offering multifaceted benefits ranging from growth promotion to stress resilience. This review synthesizes two decades of research, from 2004 to 2024, on bacterial endophyte identification and applications, highlighting advances in both traditional culture-based techniques and modern omics approaches. The review also focuses on interactions between these microorganisms and their host plants, emphasizing their roles in biocontrol, phytoremediation, and nanoparticle biosynthesis. While significant progress has been made in characterizing cultivable bacterial endophytes, challenges persist in accessing unculturable species and understanding strain-specific functional mechanisms. The integration of metagenomics, metatranscriptomics, and metabolomics has begun unraveling this hidden diversity, revealing novel metabolic pathways and plant–microbe communication systems. There have been limitations in endophyte isolation protocols and field applications, and therefore a need exists for standardized frameworks to bridge lab-based discoveries with agricultural practices. Cutting-edge multi-omics techniques, such as genomics, transcriptomics, metabolomics, proteomics, and phenomics, should be used more in future research to clarify the mechanistic underpinnings of plant–endophyte interactions to thoroughly profile the microbial communities and unlock their functional potential under diverse environmental conditions. Overall, bacterial endophytes present viable paths toward sustainable farming methods, supporting food security and crop resilience in the face of environmental difficulties by providing a transformative opportunity for next-generation agriculture, mitigating climate-related agricultural stressors, reducing dependence on synthetic agrochemicals, and enhancing crop productivity.

Deciphering the interactions between ticks and their microbiome is key to revealing new insights on tick biology and pathogen transmission. However, knowledge on tick-borne microbiome diversity and their contribution to drug resistance is scarce in sub–Saharan Africa (SSA), despite endemism of ticks. In this study, high-throughput 16S rRNA amplicon sequencing and PICRUSt predictive function profiling were used to characterize the bacterial community structure and associated antibiotic resistance markers in Amblyomma variegatum, A. hebraeum, and Hyalomma truncatum ticks infesting Nguni cattle (Bos spp.). Twenty-one (seven families and fourteen genera) potentially pathogenic and endosymbiotic bacterial taxa were differentially enriched in two tick genera. In H. truncatum ticks, a higher abundance of Corynebacterium (35.6%), Porphyromonas (14.4%), Anaerococcus (11.1%), Trueperella (3.7%), and Helcococcus (4.7%) was detected. However, Rickettsia (38.6%), Escherichia (7%), and Coxiellaceae (2%) were the major differentially abundant taxa in A. variegatum and A. hebraeum. Further, an abundance of 50 distinct antibiotic resistance biomarkers relating to multidrug resistance (MDR) efflux pumps, drug detoxification enzymes, ribosomal protection proteins, and secretion systems, were inferred in the microbiome. This study provides theoretical insights on the microbiome and associated antibiotic resistance markers, important for the design of effective therapeutic and control decisions for tick-borne diseases in the SSA region.