Pwani University

The virulence of Plasmodium falciparum is closely linked to P. falciparum erythrocyte membrane protein 1 (PfEMP1), encoded by a diverse var gene family. PfEMP1 mediates parasite immune evasion and vascular adhesion of infected red blood cells, contributing to severe disease. While expression of group A or domain cassettes (DC8 and DC13)-containing var genes have been associated with severe malaria, comparisons between the severe malaria syndromes remain limited. Furthermore, interactions between specific var gene expression and the rosetting phenotype, a known marker of severe malaria, are incompletely understood across severe malaria syndromes. We analyzed parasites and clinical data from 712 Kenyan children with non-severe and severe malaria syndromes collected over 18 years in Kilifi, Kenya. We used RT-qPCR and DBLα-tag sequencing to quantify var gene expression. We show that parasites expressing var genes containing the cys2 MFK+REY−motif or encoding DC8 domains were associated with impaired consciousness (IC), while rosetting was associated with respiratory distress (RD) and severe malarial anaemia (SMA), but not IC. These findings demonstrate that distinct PfEMP1 variants are preferentially expressed in specific severe malaria syndromes, highlighting potential targets for variant-specific future therapeutic and diagnostic strategies.

Abstract Chloroplast genomes are invaluable resources for plant genomic research, providing insights into genome evolution and molecular adaptation. With the growing scientific and economic interest in Adansonia digitata , a comprehensive characterization of its chloroplast is timely and necessary. A complete chloroplast genome of A. digitata was assembled, annotated, and characterized. Comparative structural analysis was conducted against other Adansonia species, and the assembly was validated through phylogenetic placement within Malvaceae. The assembled genome exhibits the canonical quadripartite organization, spanning 160,061 bp with a GC content of 36.88%, 79 protein-coding genes, 32 tRNAs, and 4 rRNAs. Repeat analysis identified 100 simple sequence repeat motifs, predominantly A/T-rich mononucleotide types (76%), alongside 50 long sequence repeats dominated by forward (26) and palindromic (17) repeats. Comparative analysis with other Adansonia species revealed conserved genome structure, with minor IR boundary shifts involving the ndhF gene, and ycf1 duplication in A. gregorii and A. grandidieri. Average nucleotide identity exceeded 99% across all Adansonia species, with near-complete similarity (ANI ≈ 99.96%) observed with the putative A. kilima. All predicted RNA editing events were nonsynonymous, dominated by C→U conversions (55.02%). Codon usage showed non-random synonymous preferences biased toward A/U-ending codons, driven primarily by mutational pressure with detectable gene-specific translational selection. Nucleotide diversity (π) was higher in intergenic spacers (0.00490 ± 0.00574) than in coding regions (0.00167 ± 0.00199), with the majority of genomic regions showing no sequence variation (π = 0). Substitution patterns indicated pervasive purifying selection, with relatively high but insignificant signals in matK, ycf1, accD , and rpoB . Phylogenomic analyses placed the assembled A. digitata chloroplast genome within the Adansonia lineage, consistent with its established systematic position. This study provides detailed insight into the chloroplast genome of A. digitata , and the findings will contribute towards advancing its genomic research.

The purpose of the study was to determine the effect of financial literacy training on the financial performance of SACCOs in Kilifi County. The study employed a descriptive research design to gather data on factors affecting the performance of SACCOs in Kilifi County. The target population of this study was 174 active registered SACCOS in Kilifi County. The target population typically comprises all individuals or units that meet the study's criteria. The study sample comprised 122 savings and credit cooperative societies, selected from the total SACCO population in Kilifi County. Data was collected using primary techniques. The report emphasizes the importance of financial literacy education for improving SACCOs' financial performance. An informed and financially literate membership has a positive impact on co-operative societies' financial performance, as evidenced by the positive coefficient on financial literacy training. This underscores the need for microfinance organizations and policymakers to prioritize financial education initiatives to equip SACCO members with the knowledge and skills required to make sound financial decisions, manage their resources effectively, and fully leverage microfinance services. For policymakers, it is crucial to strengthen the regulatory framework governing SACCOs. Emphasizing transparency, accountability, and effective governance practices will ensure the sound operation of SACCOs and protect the interests of their members and the financial system as a whole. Additionally, policymakers should prioritize implementing financial literacy programs for SACCO members to enhance their financial decision-making and use of microfinance services.

Abstract Megaherbivores are increasingly promoted as agents of nature restoration, yet most research on their ecological effects has focused on temperate and non-forested systems, with limited consideration of tropical forests and their historical land-use contexts. A better understanding of megaherbivore impacts in tropical forests is essential to inform rewilding and restoration efforts. This is particularly important in regenerating secondary systems that historically supported megafaunga and remain highly valuable targets for ecological recovery. We address this knowledge gap by comparing tree species composition, forest structural attributes, and understory habitat composition across three disturbance regimes in an East African tropical dry forest: (1) primary forest with megaherbivores, (2) secondary forest with megaherbivores, and (3) primary forest without megaherbivores. Under megaherbivore presence, understory habitat and tree branching architecture converged across primary and secondary forests, suggesting functional consistency in disturbance effects imposed by large herbivores and indicating that key structural ecosystem processes can be rapidly restored. In contrast, canopy structure and tree species composition remained distinct between forest types and strongly constrained by persistent legacies of past human land use. Our findings underscore that restoration strategies relying on megaherbivores must explicitly account for historical land-use constraints rather than assuming spontaneous convergence toward primary-forest conditions.

Common bean (Phaseolus vulgaris L.) is a major legume crop of global and national importance, contributing significantly to food security, nutritional diversity, and the livelihoods of households by providing essential dietary protein, minerals and income. In Kenya, common bean production is carried out mainly by small holder farmers as a key food and cash crop. The crop is majorly grown at altitudes ranging from 600 and 2700 m above sea level, with average grain yield of less than 0.85 tons/ha, compared to variety specific potential yields of >2 tons/ha. This below optimum production is attributed to combination of socio economic, biotic and abiotic stresses such as land degradation, climate change effects, poor agronomic practices, poor pest and disease management and post-harvest handling, limited access to quality seeds, credit facilitates, value addition and organised markets. Understanding these interlinked factors is critical for designing targeted interventions, developing resilient varieties, and improving overall production efficiency. This review synthesizes current common bean knowledge by integrating fragmented research into a single reference, linking biological, agronomic, ecological, and socio-economic dimensions, and identifying key production constraints and research gaps. The findings provide a basis for future research and evidence-based policy interventions aimed at improving common bean productivity and sustainability in smallholder farming systems.

The explosion of Internet of things (IoT) devices has led to pretty much saturated network infrastructures, thus congestion often becomes severe, especially in applications where users require low latency, high throughput and real-time responses. Hence, traditional congestion control mechanisms like static routing protocols, Active Queue Management (AQM) and TCP variants are not suitable for this dynamic and heterogeneous IoT environment as they are reactive, rigid and cannot adapt to dynamic changes. The contribution is to investigate the potential of AI paradigms—such as ML, DL, RL and hybrid models- to provide Intelligent and proactive congestion Control in IoT systems. The paper compares the strengths and weaknesses of each method, such as RL’s generalizability and DL’s ability to capture patterns, as well as limitations in terms of scalability, interpretability, and computational resource requirements. Moreover, it emphasizes important research gaps in model generalization process, evaluation criteria and cross-platform fusion. Next steps in research discussions on the future of research take into account lightweight AI architectures, Explainable AI (XAI) frameworks, scalability of FL, and standard benchmarking data sets. The hybrid-AI congestion prediction model built in this work is validated across simulation tools and real-data sets and is observed to result in a significant decrease in latency, packet loss and energy consumption. This paper paves the way for scalable, intelligent and secure AI-based congestion management solutions for various IoT networks.

Globally, hypertension causes 10.8 million deaths annually. However, in Kenya, like in other low-and middle-income countries, access to hypertension care remains limited and inequitable. Understanding patients’ journeys in accessing care along the care cascade is critical to inform patient-centred care and policy improvements. This study aimed to explore patient experiences in accessing primary care services for hypertension along the care cascade in rural Coastal Kenya―a setting with a high hypertension burden. We conducted a qualitative cross-sectional study and collected data using in-depth interviews (n = 24) and five focus group discussions (n = 30) with hypertension patients and their adult family caregivers in two purposively selected sub-counties in Kilifi County. We conducted and transcribed the interviews in Kiswahili and Giriama (local languages) and translated them into English. We used QSR NVivo 12 for data management. We analysed the data using a framework approach and interpreted our findings using Levesque’s access framework. Access to hypertension screening and diagnosis services was undermined by information barriers which led to inadequate awareness and lack of knowledge about hypertension and its causes. There were perceptions of inadequate health facility capacity to offer hypertension screening services, particularly to ‘healthy’ individuals thus presenting as a barrier to demand for screening services. Acceptability of care was undermined by inadequate patient counselling at diagnosis and perceived disrespectful treatment of patients. Access to treatment and diagnostic tests was undermined by unaffordable care, limited availability of medicines and equipment, long waiting times, and inaccessible health facilities. Having health insurance enabled access to care; however, most participants were uninsured. Participants adapted to these access barriers by reducing/skipping daily medication doses, resorting to alternative forms of care (e.g., herbal treatments and faith healing), and changing health facilities for routine clinic appointments. Access to care for older patients (i.e., ≥70 years) and those with complications was enabled by family caregivers who coordinated and navigated the health system on their behalf. Our findings show that people living with hypertension experience a combination of interacting individual, community, and health system-related barriers to accessing care. There is a need to systematically address identified barriers and ensure patient-centred responses that meet patients’ needs. Strengthening the health system’s capacity to ensure availability and affordability of treatment and diagnosis services, creation of community hypertension awareness, adequate patient counselling at screening and diagnosis, and involvement of family caregivers for older patients are examples of urgent interventions to improve access to hypertension care.

The ocean-climate relationship determines a unique tropical architecture which produces increased seasonal and temporal variation of wind, waves, currents and thermal stratification. The objective of the is to identify how Climate Information Systems (CIS) and emerging artificial intelligence (AI) technologies can benefit Africa's climate change resilience, with a focus on Kenya's exposed coastal economies. The study employed mixed-methods approach on the selected population stratified random sampling was used to select 225 individuals who were administered structured questionnaires, interviews and Focused Group Discussion. Quantitative and qualitative methods were both used to study data such as Statistical packages and regression analysis. The results were that CIS has a high level of awareness of 40.9% "Very Aware," and 41.8% of the respondents use AI occasionally. Regression analysis reveals a high positive relationship (R = 0.789) of CIS and AI with resilience explaining 61.9% of variance, highlighting indicators such as CIS awareness (coefficient = 0.441) and use of AI (coefficient = 0.358) as excellent predictors, whereas bottlenecks such as lack of infrastructure (36.0%) and awareness (28.4%) hinder effective implementation. The study recommends that mounting of gas analyzer sensors on smartphone to convert physical changes into electrical signals that can be interpreted by AI algorithm systems and automatically send collected data to various stations. The stakeholders should raise awareness and education on CIS and AI, invest in necessary infrastructure, and leverage partnership among the government, academia, and the private sector to mitigate challenges and develop resilience to climate change in Kenya's coastal economies.

Abstract Background Tuberculosis (TB) is a significant global health issue, mainly in developing countries. Despite the progress made in reducing TB rates, adverse treatment outcomes, such as deaths and treatment failures, continue to be a concern. We aimed to determine the treatment failure and death rates, and its predictors, among TB patients in Tanzania from January 2022 to December 2023. Methodology We conducted a cohort study utilizing data from the National Tuberculosis and Leprosy Programme database, focusing on TB patients who began treatment in 2022 and 2023. The Cox proportional hazards model was used to conduct univariate and multivariate analyses. Hazard ratios and their respective 95% confidence intervals were reported. Kaplan–Meier curves were employed to estimate the probabilities of these outcomes over time. A p -value ≤ 0.05 was considered significant. Results The overall death rate and treatment failure rate among participants was 2.76 and 0.11%, respectively. Older adults had significantly increased risk of adverse outcomes, with nearly four times the likelihood of death (AHR 3.62, 95%CI: 3.18–4.11, p < 0.001) and twice the likelihood of treatment failure (AHR 2.25, 95%CI: 1.12–4.52, p = 0.022). Male participants faced a higher risk of both death (AHR 1.10, 95%CI: 1.03–1.17, p = 0.003) and treatment failure (AHR 1.56, 95%CI: 1.12–2.17, p = 0.009) than females. Urban residents had increased risk of death (AHR 1.40, 95%CI: 1.32–1.49, p < 0.001) and treatment failure (AHR 1.46, 95%CI: 1.08–1.98, p = 0.014) compared to those in rural areas. Treatment in hospitals was associated with worse outcomes, including almost twice the risk of death (AHR 1.71, 95%CI: 1.57–1.86, p < 0.001) and a higher likelihood of treatment failure (AHR 1.49, 95%CI: 1.01–2.20, p = 0.042). Most deaths occurred within the first two months of treatment, whereas treatment failures peaked at six months. Conclusion The study revealed significant differences in death and treatment failure rates based on patients’ characteristics, with higher risks observed in older adults, males, urban residents, treatment at higher-level facilities, having pulmonary TB, TB/HIV co-infection, retreatment, being treated under Facility DOT, and being referred through other referral types other than self-referral, CTC referral and community referrals. The findings emphasize the need for targeted efforts to improve TB outcomes.