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The nutritional value, heavy metal content and lipid quality of five marine fishes from, Cameroon coast were be investigated. Fish samples from Ilisha africana, Sardinella, maderensis, Cyprinus carpio, Arius parkii and Ethmalosa fimbriata were collected at, the Douala sea port, carried to the laboratory, washed with distilled water and, processed. Proximal composition, minerals, lipid quality and heavy metal analyses, were performed using AOAC standard methods. Results show that proteins (18.43%), and lipids (3.69%) contents were higher in Ilisha africana. Cyprinus carpio had the, highest ash content (4.59%). Contents of minerals and heavy metals were found as, follows: P > Mg > K > Ca > Na > Fe > Zn > Cu > Mn and Hg > Pb > Cd > As. Oils extracted from C. carpio, A. parkii and E. fimbriata were semi-siccative while those of I. africana and S. maderensis were siccative. Thus, these fish species are good sources of proteins and, minerals that can be used for managing mineral deficiencies in humans and animals.

In order to improve therapeutic compliance and prevent antimalarial drug resistance, we conducted this study to evaluate the knowledge of physicians and pharmacists in Kayes on the management of adverse effects of antimalarial drugs. Methods: A cross-sectional study was conducted from July to November 2017 among physicians and pharmacists selected by simple random sampling and practicing in the Kayes region for more than one year. The survey was based on a questionnaire proposed by the national pharmacovigilance center. In addition to a descriptive analysis of the results, a logistic regression analysis was performed to assess potential factors that could be associated with knowledge. Results: Among 151 physicians and pharmacists participated in the study, less than 40% had better knowledge about the management of antimalarial drug adverse events. Physicians and pharmacists working in government facilities were more likely to have better knowledge compared with those working in other facilities (OR=8.38; 95% CI: 2.48-28.30). In addition, pharmacists were more likely to have better knowledge than physicians (OR=3.48; 95% CI: 1.21-12.19). Conclusions: The frequency of good knowledge of the management of adverse drug reactions to antimalarials is insufficient, although membership in government structures and profession seem likely to improve it.

To improve adherence to treatment, quality of life of patients on anti-tuberculosis drugs, and prevent antibiotic resistance, we conducted this systematic review to support risk minimization actions. Methods: Medline, Scopus, and Web of Science were searched with a focus on adverse drug reactions. Two independent reviewers assessed the methodological quality of the included studies using criteria defined by the Newcastle Ottawa Scale. Results: Seven studies were included, and four risk management strategies were identified (psychological intervention, drug dose reduction with or without prescription of adjunctive drugs, drug switching, permanent or temporary drug discontinuation). The strategies adopted were dependent on the nature and severity of the adverse events. All drugs responsible for serious adverse effects were changed or discontinued. Conclusions: The results highlight the relatively low frequency of adverse events leading to permanent discontinuation of 1st-line anti-tuberculosis drugs, but also emphasize the high incidence of adverse events leading to permanent discontinuation of cycloserine.

For the protection of endangered species and successful wildlife population monitoring, wild animal recognition is essential. While deep learning models like YOLOv5 have shown promise in real-time object recognition, their practical applicability may be constrained by their high processing requirements. In this paper, we suggest a faster and lighter version of YOLOv5s for wild animal recognition. To lower computational costs for model parameters and floating-point operations (FLOPs) for the backbone, our suggested model includes Mobile Bottleneck Block modules and an improved StemBlock. We also use Focal-EIoU as a loss function to gauge the accuracy of the predicted bounding boxes during inference and employ a BiFPN-based neck. We tested our technique on three datasets, including Wild Animal Facing Extinction, Fishmarket, and MS COCO 2017. Additionally, our technique is compared with state-of-the-art deep learning models, and from the baseline model we recorded a 17.65% increase in FPS, 28.55% model parameters reduction, and 50.92% in FLOPs reduction. Furthermore, our model has a faster model loading time, which is critical for deployment in remote areas. This enables real-time species recognition on basic hardware, aiding conservation efforts through rapid analysis. The model advances deep learning in ecology by balancing efficiency with performance. • Introducing a new, lightweight, and efficient animal recognition model. • Combines modified Stem Block, DWConv, and MBBlock for enhanced speed and accuracy. • Feature fusion enhanced with BiFPN for better accuracy. • CIoU loss was replaced with Focal-EIoU for class balance. • WildARe-YOLO – New approach in the limited infrastructure environment. [ABSTRACT FROM AUTHOR]

Diagnosis of Campylobacter fetus venerealis infection on bulls in the Shaba region (Zaire). The presence of Campylobacter fetus subsp. venerealis infection has been investigated in 3 ranches of the Shaba region. A total of 275 sexually active buIls has been examined using the direct immunofluorescence technique on preputial washings. From these 275 buIls 67 (24.3 %) were found to be infected. The technique of direct immunofluorescence proved to be very usefull under tropical conditions because smears could be prepared from the preputial washings in the field, fixed and stored for months before being examined in a specialized laboratory. Suggestions for prevention and treatment are briefly discussed.