Abstract Objective Artisanal gold mining has rapidly expanded in Burkina Faso, but its respiratory impacts remain poorly documented. This study aimed to determine the prevalence of respiratory diseases among differently exposed populations and to identify associated factors. Methods An analytical and comparative cross-sectional study was conducted from 2015 to 2020 in Séguénéga (exposed site) and Gourcy (control site). Patients aged ≥ 15 years with a documented medical diagnosis were included. Multivariate binary logistic regression was performed to identify factors associated with the occurrence of respiratory diseases. Results After exclusions, 1,274 records were retained (629 in Séguénéga, 645 in Gourcy). The overall prevalence of respiratory diseases was estimated at 29.4% (95% CI: 26.9–32.0), significantly higher (p = 0.01) in Séguénéga (32.8%, 95% CI: 29.1–36.6) compared to Gourcy (26.2%, 95% CI: 22.8–29.8). The main symptoms were cough (80.2%) and dyspnea (61.4%). Pulmonary tuberculosis was more common in Séguénéga than in Gourcy (3.2% vs. 0.5%; p = 0.01). In multivariate analysis, the exposed site (aOR = 1.41, 95% CI: 1.06–1.87; p = 0.018), age (aOR = 1.01, 95% CI: 1.01–1.02; p < 0.001), history of asthma (aOR = 9.85, 95% CI: 4.72–20.6; p < 0.001), previous tuberculosis (aOR = 28.1, 95% CI: 8.4–93.5; p < 0.001), and poor nutritional status (aOR = 1.94, 95% CI: 1.05–3.56; p = 0.035) were statistically associated with increased odds of respiratory diseases. Respiratory lethality reached 8.0% in Séguénéga compared to 1.2% in Gourcy (p < 0.001). Conclusion Artisanal gold mining is associated with an increased incidence of respiratory diseases and higher lethality in riverside areas, calling for preventive actions.
Background:The intensive use of insecticide-based control tools has led to the rapid evolution of resistant phenotypes in malaria vector populations. Understanding the evolutionary processes underlying these resistances is essential to inform the development and deployment of effective control interventions. This study investigated the geographical spread and the genetic background of insecticide resistance variants in Burkina Faso. Results:The study identified five pyrethroid-resistant mutations (995F, 995S, 402L(g > t,c), 1527T and 1570Y) at high frequencies. Six diplotype groups were identified, including novel combinations of the resistance-associated alleles (995F, V402L(g > t,c) and 1527T), which formed new genotypes within An. coluzzii populations. These results suggest the emergence of new resistance genotypes in An. coluzzii that are not associated with 995F, probably due to recombination and gene flow events. Interestingly, strong linkage disequilibrium (r 2 = 0.821) was observed between 1527T and 402L(g > t) compared to 1527T and 402L(g > c). The PCA revealed three clusters of An. coluzzii populations, driven by 995F, 402L(g > t,c) and 1527T. Other insecticide resistance associated variants such as copy number variations and SNPs in the Ace1 gene (Ace1-G280S), cytochrome P450s, esterases and glutathione S-transferases were identified at high frequencies in the same mosquito populations, indicating the intensity and diversity of resistance mechanisms in the country. Conclusion:The study underscores the extent and spreads of insecticide resistance variants in Burkina Faso. It highlights the importance of genomic surveillance of malaria vectors to monitor and detect new resistance variants and to understand the evolutionary processes in vector populations.
In this chapter, I am synthesizing the key contributions of the book and suggesting three areas of research for future work on meta-organizations, although there are many more: 1) the manifestations and consequences of meta-organizational proliferation, and especially of organizational monsters; 2) the roles of meta-organizations in sustainability transformation in territories; and 3) the use of counter-hegemonic meta-organizing for enacting or strengthening alternative worldviews and world making.
Camera-trap monitoring in African tropical forests increasingly extends beyond closed-canopy interiors to riverbanks, clearings, and park edges. Among available open tools for African forest camera-trap classification, DeepForestVision is the only one providing a matched offline workflow for both photographs and videos, and previous work showed that it outperformed other available baselines on a comparable benchmark. However, it was designed for closed-canopy, ground-level forest interiors and uses a 35-class prediction space that becomes too coarse when deployments encounter arboreal primates, birds, semi-aquatic taxa, or human-associated confounders such as livestock. We present DeepForestVisionV2, an ecology-driven expansion from 35 to 64 prediction classes (61 animal classes plus human, vehicle, and blank) designed to address three recurrent deployment gradients: vertical stratification, scene openness, and anthropogenic interfaces. DeepForestVisionV2 retains the same offline workflow and is trained on 1,535,010 photographs and 243,354 videos from multi-country African tropical-forest projects. Evaluation combines a cross-country cropped-photo validation set, used to assess robustness across sites and camera-trap settings, with three held-out Uganda video benchmarks spanning the targeted gradients. On the validation set, DeepForestVisionV2 reaches 0.86 accuracy, 0.82 macro-F1, and 0.81 balanced accuracy. On the deployment benchmarks, it preserves or improves baseline accuracy despite its harder classification task, while increasing the number of identified taxa from 22 to 29 in forest-interior videos and from 4 to 9 at riverbanks. In the park-edge use case, it raises accuracy from 0.62 to 0.86 and reduces false alarms from 11 to 0. These results show that DeepForestVisionV2 materially improves field utility while preserving robustness across sites, habitats, and camera-trap settings.
Abstract Electric organ discharge (EOD) waveform diversity in African elephantfish is often attributed to sexual selection, yet EODs also mediate active electrolocation during prey detection, raising the possibility that natural selection on foraging ecology contributes to waveform divergence. Paramormyrops kingsleyae exhibits an intraspecific polymorphism where certain populations emit biphasic EODs whereas other populations emit triphasic waveforms. The genes underlying this polymorphism show signatures of selection; the polymorphism persists despite gene flow and is behaviorally discriminable by the fish themselves. If waveform differences influence prey detection during active electrolocation, biphasic and triphasic fish should consume systematically different prey. We tested this prediction using DNA metabarcoding of gut contents from 186 mormyrids representing 16 species across eight sites in Gabon, employing two independent COI primer sets for cross-validation and pairing dietary data with environmental invertebrate sampling to distinguish active prey preference from passive availability. At the community level in the diverse Balé Creek mormyrid assemblage, species identity was the dominant predictor of diet composition (R² ≈ 24%), consistent with phylogenetic signal in foraging ecology. Within P. kingsleyae , waveform type was the strongest independent predictor of dietary composition (R² = 5–6%), explaining variance independently of geographic region, sex, body size, and parasitism status — a result concordant across both primer sets. Dietary differences were driven by prey species turnover rather than differential abundance of shared prey, and prey selectivity analyses confirmed that waveform types differ in which prey they actively prefer, not merely in what is locally available. These findings are consistent with natural selection on foraging ecology contributing to the maintenance of EOD waveform polymorphism, though the sensory mechanisms linking subtle waveform differences to prey detection remain an open question.
