Etude des paramètres zootechniques de la race Ndama en milieu traditionnel villageois en Gambie

Une enquête épidémiologique sur la trypanosomose bovine a été réalisée en Gambie de novembre 1987 à octobre 1989. Elle a concerné la race trypanotolérante Ndama en zone de faible et forte pression glossinienne et visait la connaissance des paramètres de production de cette race en élevage traditionnel villageois et l'étude des facteurs les influençant. Naissances et mortalités, changements de poids des animaux, expulsion d'oeufs de strongles, fréquences des infections annuelles et mensuelles de la trypanosomose sont présentés ainsi que les variations de l'hématocrite. Les auteurs concluent que la production bovine de race Ndama en zone infestée par la trypanosomose est rentable mais conditionnée par la disponibilité en nourriture et la gestion du troupeau au sens large (contrôle des feux, sélection, traitement anthelminthique régulier, complémentation

Attenuation of doxorubicin-induced cardiotoxicity by mdivi-1: a mitochondrial division/mitophagy inhibitor

Doxorubicin is one of the most effective anti-cancer agents. However, its use is associated with adverse cardiac effects, including cardiomyopathy and progressive heart failure. Given the multiple beneficial effects of the mitochondrial division inhibitor (mdivi-1) in a variety of pathological conditions including heart failure and ischaemia and reperfusion injury, we investigated the effects of mdivi-1 on doxorubicin-induced cardiac dysfunction in naïve and stressed conditions using Langendorff perfused heart models and a model of oxidative stress was used to assess the effects of drug treatments on the mitochondrial depolarisation and hypercontracture of cardiac myocytes. Western blot analysis was used to measure the levels of p-Akt and p-Erk 1/2 and flow cytometry analysis was used to measure the levels p-Drp1 and p-p53 upon drug treatment. The HL60 leukaemia cell line was used to evaluate the effects of pharmacological inhibition of mitochondrial division on the cytotoxicity of doxorubicin in a cancer cell line. Doxorubicin caused a significant impairment of cardiac function and increased the infarct size to risk ratio in both naïve conditions and during ischaemia/reperfusion injury. Interestingly, co-treatment of doxorubicin with mdivi-1 attenuated these detrimental effects of doxorubicin. Doxorubicin also caused a reduction in the time taken to depolarisation and hypercontracture of cardiac myocytes, which were reversed with mdivi-1. Finally, doxorubicin caused a significant elevation in the levels of signalling proteins p-Akt, p-Erk 1/2, p-Drp1 and p-p53. Co-incubation of mdivi-1 with doxorubicin did not reduce the cytotoxicity of doxorubicin against HL-60 cells. These data suggest that the inhibition of mitochondrial fission protects the heart against doxorubicin-induced cardiac injury and identify mitochondrial fission as a new therapeutic target in ameliorating doxorubicin-induced cardiotoxicity without affecting its anti-cancer properties

The Role of Transporters in the Pharmacokinetics of Orally Administered Drugs

Drug transporters are recognized as key players in the processes of drug absorption, distribution, metabolism, and elimination. The localization of uptake and efflux transporters in organs responsible for drug biotransformation and excretion gives transporter proteins a unique gatekeeper function in controlling drug access to metabolizing enzymes and excretory pathways. This review seeks to discuss the influence intestinal and hepatic drug transporters have on pharmacokinetic parameters, including bioavailability, exposure, clearance, volume of distribution, and half-life, for orally dosed drugs. This review also describes in detail the Biopharmaceutics Drug Disposition Classification System (BDDCS) and explains how many of the effects drug transporters exert on oral drug pharmacokinetic parameters can be predicted by this classification scheme

Consumption of legal and illegal cigarettes in the Gambia

BackgroundThe prevalence of cigarette smoking in the Gambia is relatively high, compared with most African countries. Little is known about the characteristics of the smokers and their habits, particularly with regard to tobacco tax avoidance and tax evasion.MethodsA nationally representative survey of 1211 smokers conducted in November/December 2017 employed a three-stage stratified sampling method and resulted in 1205 complete observations. The sociodemographic characteristics and smoking behaviours were analysed, including smoking intensity and brand preferences. Information on the physical features of cigarette packs that smokers had, observed by enumerators, and self-reported cigarette prices were used to estimate the proportion of illegal cigarettes on the market.FindingsAs in many African countries, most smokers were male, between the ages of 25 and 54 years living primarily in urban areas. The three most popular cigarette brands are Piccadilly, Royal Business and Bond Street, which account for over three-quarters of all cigarette purchases. Price information suggests that about 7.3% of smokers purchased an illicit cigarette at their last purchase. When smoking intensity was taken into account, 8.6% of the total cigarette market was estimated to be illicit. Using an alternative method of evaluating pack’s features revealed that only 0.9% of last purchases were illicit.ConclusionDespite recent excise tobacco tax increases, the use of illicit cigarettes in the Gambia is low and does not represent a significant obstacle to reaching both the public health and fiscal goals of higher tobacco taxes.</jats:sec

Deep learning-based hybrid feature selection for the semantic segmentation of crops and weeds

Deep convolution neural networks are the recent algorithms used for robotic vision. However, the complex crop–weed vegetation and the background interferences required a robust feature representation. Therefore, we proposed a Dual-branch Deep neural network for the semantic segmentation of crops and weeds. The branches utilized distinct feature extraction algorithms that extract essential semantic cues, and a decoder combined these features to improve the global contextual information. Finally, the hybrid feature selection module(HSFM) utilized the decoder features to complement one another. Experimental results show the proposed method obtained mean intersection of union scores of 0.8613 and 0.9099 on CWFID and BoniRob datasets, respectively

Multi-level feature re-weighted fusion for the semantic segmentation of crops and weeds

Intelligent farm robots empowered by proper vision algorithms are the new agricultural machinery that eases weed control with speed and accuracy. Based on the farmland substantial similarity between the crops, and weeds, or other background interference objects, an improved deep convolutional neural network (DCNN) algorithms is proposed for the pixel semantic segmentation of crop and weed. First, a lightweight backbone is proposed to balance the features map textual and shape signals, which are essential cues for better crop and weed prediction. Second, a multi-level feature re-weighted fusion (MFRWF) module is suggested to combine only the relevant information from every backbone layer output to improve the contextual maps of crops and weeds. Finally, a decoder is designed based on convolutional weighted fusion (CWF) to preserve the relevant crop and weed context information by reducing the possible feature context distortion. Experimental results show that our improved neural network obtained the mean intersection of union (MIOU) scores of 0.8646, 0.9164, and 0.8459 on the carrot/weed field image (CWFID), sugar beet (BoniRob), and Rice seedling datasets, respectively. Therefore, the results have not only outperformed the commonly used architectures but can precisely identify crops/weeds and substantially improve the robot inference speed with minimal memory overhead. The code is available at:https://github.com/jannehlamin/MFRWF