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Exploratory conversations with biodiversity‑oriented civil society groups on the potential applications of gene drive‑modified mosquitoes for malaria control in Tanzania
(Springer Nature, 2026-01-13) Finda, Marceline; Sambo, Maganga; Malika, Goodluck; Njalambaha, Rukiya; Salum, Sheikha; Okumu, Fredros
Gene drive-modified mosquitoes (GDMMs) are gaining attention as sustainable tools to complement existing malaria control strategies. Their ability to self-propagate and spread through wild mosquito populations offers the promise of low-cost, long-lasting impact, but also raises ecological, ethical, and governance concerns. In this evolving debate, civil society organizations (CSOs) are pivotal actors in shaping dialogue, representing community concerns, and influencing policy decisions. This study examined the perspectives and recommendations of biodiversity-oriented CSOs on the governance, testing, and potential application of GDMMs for malaria control in Tanzania. An exploratory qualitative design was employed, involving eight in-depth interviews, one focus group discussion, and three large group discussions with representatives from ten biodiversity-focused CSOs in Tanzania. Participants were selected purposively based on prior involvement in national or regional dialogues related to biotechnology; and the discussions focused on concerns, uncertainties and needs associated with testing and potential use of GDMMs for malaria control, as well as the balance of prospective benefits against long-term environmental risks. Transcripts were analyzed thematically using NVivo 12 Plus. Participants expressed cautious support for research on GDMMs for malaria control but raised concerns about scientific uncertainty, limited local expertise, inadequate transparency, potential transboundary effects and technological dependency. They emphasized the importance of generating robust, context-specific evidence before considering any environmental releases of gene drives; and highlighted concerns over inadequate accountability, particularly the lack of clarity on who would assume responsibility if adverse outcomes arise. They also advocated for early, inclusive, transparent, and continuous engagement with both target communities and the broader public. Lastly, to ensure objective and impartial oversight, they recommended development of local expertise that is independent of technology developers and sponsors. The CSOs’ perspectives were diverse but broadly aligned with the precautionary principle, calling for preventive action amid uncertainty, clear accountability, and the pursuit of safer alternatives. Although many expressed serious reservations about gene drive mosquitoes, there was a shared recognition that research on the technology is necessary, provided it is conducted under controlled, transparent, and auditable conditions. Overall, these exploratory discussions underscored the need for: (i) balanced dialogue between advocates and skeptics, (ii) robust ethical and regulatory frameworks covering the full life cycle of the technology, (iii) sustained community and stakeholder engagement from the early stages of research and development, (iv) enhancements of in-country capacity, and (v) national sovereignty in decision-making regarding GDMMs. Demonstrating and effectively communicating these elements will be as critical as ensuring their existence.
Financial management practices and Agri-SME performance: does subjective financial literacy hold the key?
(Taylor & Francis Online, 2026-01-10) Mang’ana, Kulwa
this study investigates how four key financial management practices (FMps), namelythe working capital, capital budgeting, financial reporting, and financing affect agri-sMEperformance in tanzania, focusing on the mediating role of the manager’s subjectivefinancial literacy (self-perceived competence). using a cross-sectional survey of 385tanzanian agri-sME managers, data were analyzed via pls-sEM with 5,000 bootstraps.anchored in the resource Based view and behavioral finance, results show thatfinancing practices (β ≈ 0.17) and subjective literacy (β ≈ 0.13) significantly enhanceperformance (p < 0.05). Furthermore, working capital management and capital budgetingsignificantly boosted subjective literacy (p < 0.05). importantly, financial reportingsignificantly reduced perceived competence (β≈−0.23, p < 0.05), suggesting potentialcognitive misalignment. indirect paths via literacy were positive but not statisticallysignificant (p > 0.05). the study recommended that support programs must pair accessto finance with capability building that bolsters perceived financial competence, andreporting tools must be simplified.
From Forest to Fuel: Exploring Uapaca Kirkiana (Wild Loquat) Extracts to Enhance Biodiesel Life
(Springer Nature, 2026-01-12) Kivevele, Thomas; Kahimbi, Henry
Biodiesel is a renewable, low-emission fuel; however, its poor oxidative stability limits its practical use. Although synthetic antioxidants like Pyrogallol can improve stability, they raise toxicity concerns, prompting interest in safer, plant-based alternatives. This study evaluates the antioxidant potential of Uapaca kirkiana extracts, specifically from fruit peels, pulp, and root bark, for enhancing the oxidation stability of biodiesel. Methanolic extraction was employed to obtain the plant extracts, and the total phenolic content (TPC) was determined using the Folin–Ciocalteu (FC) reagent. Antioxidant activity was assessed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay, while oxidation stability of croton biodiesel was measured using the OXITEST method. Among the tested samples, fruit peel extracts exhibited the highest phenolic content and antioxidant activity. At a concentration of 1000 ppm, the fruit peel extract extended the biodiesel induction period from 3.02 h (control) to 16.25 h, compared to 14.18 h and 10.10 h for the pulp and root bark extracts, respectively. These results were benchmarked against Pyrogallol (PY), which extended the induction period to 18.30 h at the same concentration. Although PY demonstrated slightly higher effectiveness, the natural extracts, particularly from fruit peels, showed substantial potential. Notably, the fruit peel extract met and exceeded the minimum oxidation stability requirements of EN 14112 and ASTM D6751 (8 h) at just 500 ppm. These findings highlight the promise of Uapaca kirkiana extracts as eco-friendly, natural alternatives to synthetic antioxidants for improving biodiesel stability and shelf life.
Enhanced multi-class object detector for bone fracture diagnosis with prescription recommendation
(Frontiers, 2026-01-12) Migayo, Daudi; Kaijage, Shubi; Swetala, Stephen; Nyambo, Devotha
Bone fractures are among the most prominent injuries in the modern world that
affect all ages and races. Traditional treatment involves radiographic imaging that
relies heavily on radiologists manually analyzing images. There have been efforts
to develop computer-aided diagnosis tools that employ artificial intelligence
and deep learning approaches. Existing literature focuses on developing tools
that only detect and classify bone fractures, rather than addressing the broader
issue of bone fracture management. However, evidence of scholarly works that
include treatment recommendations is still lacking. Furthermore, deep learning
based object detectors that achieve state-of-the-art results are computationally
expensive and considered as black-box solutions. Developing countries, such
as Sub-Saharan Africa, face a shortage of radiologists and orthopedists. For this
reason, this paper proposes a methodological approach that uses a more efficient
object detection model to diagnose long bone fractures and provide prescription
recommendations. An enhanced anchoring process, known as adaptive anchoring,
is proposed to improve the performance of the Regional Proposal Network and
the object detection model. A Faster R-CNN model with ResNet-50/101 and
ResNext-50/101 backbones was used to develop an object detection model that
uses X-ray images as input. To understand and interpret the model’s decision, a
Gradient-based Class Activation Mapping method was used to assess the model’s
learnability. The results indicate that the proposed adaptive anchoring approach can
improve computational efficiency, reducing training time by up to 29% compared
to the traditional approach. Model accuracy during training and validation ranged
between 94% and 98%. Overall, adaptive anchoring performed better when applied
with the ResNet-101 backbone, yielding an Average Precision of 92.73%, an F1
score of 96.01%, a precision of 96.80%, and a recall of 95.23%. The study provides
valuable insights into the use of computationally efficient deep learning models
for medical recommendation systems. Future studies should develop models to
diagnose fractures using input images from various modalities and to provide
prescription recommendations.
Microsatellite analysis of genetic differentiation among populations of the malaria vector Anopheles funestus across mainland Tanzania reveals contrasted patterns of geographic isolation and gene flow
(Springer Nature, 2026-01-12) Mapua, Salum; Samb, Badara; Nambunga, Ismail; Kweyamba, Prisca; Mkandawile, Gustav; Bwanaly, Hamis; Kaindoa, Emmanuel; Odero, Joel; Masalu, John; Kahamba, Najat; Hape, Emmanuel; Galizi, Roberto; Govella, Nicodem; Okumu, Fredros; Tripet, Frederic
Background
Despite Anopheles funestus s.s. being a highly competent and widespread malaria vector in Africa, its population structure remains largely understudied in many countries, including Tanzania. Herein, we examine the genetic diversity, geographic isolation, and gene flow of An. funestus populations across ten administrative regions in mainland Tanzania.
Methods
We employed 12 previously used microsatellite DNA markers to describe genetic diversity, isolation by distance, and gene flow patterns among ten An. funestus s.s. populations (n = 654) and one An. parensis population (n = 28), used as an outgroup, sampled across ten regions in mainland Tanzania.
Results
Overall, allelic richness (Na) and genetic diversity (HS) did not differ significantly among populations. Although some loci and populations showed significant departures from Hardy–Weinberg equilibrium, the patterns were not indicative of substructuring within locations. Pairwise genetic divergence (FST) values indicated clear separation between An. parensis and An. funestus s.s., with values exceeding 0.2, consistent with species-level differentiation. Among An. funestus s.s. populations, the highest divergence was observed between southeastern coastal populations (Mtwara, Ruvuma, Lindi) and inland populations, with FST values up to 0.288. There was no evidence of isolation by distance. Instead, patterns of genetic divergence suggested connectivity across the Rift Valley and heterogeneity among southeastern populations. Neighbor-joining analysis and Bayesian genotype clustering identified three distinct population groups: (i) An. parensis (Dodoma), (ii) a genetically distinct An. funestus s.s. population from Mtwara, and (iii) a more homogeneous cluster comprising the remaining An. funestus s.s. populations. Notably, the Mtwara population appeared highly differentiated, with divergence approaching that between An. funestus s.s. and An. parensis, supporting its distinctiveness but not undermining the role of An. parensis as an outgroup.
Conclusions
Except for the Mtwara population, whose status will need to be clarified through whole-genome sequencing, moderate genetic divergence was found among An. funestus s.s. populations across Tanzania, despite geographical separation and the Rift Valley. The observed genetic structure suggests that anthropogenic gene flow may play a key role in shaping population divergence. Future studies should aim to delineate the effects of local adaptation from recent gene flow to further explore these dynamics