Assessment of Inter-Specific Diversity of the \u3cem\u3eHedysarum\u3c/em\u3e Genus in Tunisia

In Tunisia, many grassland and pasture species were menaced by genetic erosion. Thus, we were interested in the Hedysarum species which constitute a very important phytogenetic patrimony able to produce forage and restore destroyed pasture land especially in arid and semi-arid areas. In order to facilitate fodder improvement, we investigated the phenetic relationships among Hedysarum species using rDNA intergenic spacer (IGS) polymorphism

A Classification Table for Achondrites

Classifying chondrites is relatively easy and the criteria are well documented. It is based on mineral compositions, textural characteristics and more recently, magnetic susceptibility. It can be more difficult to classify achondrites, especially those that are very similar to terrestrial igneous rocks, because mineralogical, textural and compositional properties can be quite variable. Achondrites contain essentially olivine, pyroxenes, plagioclases, oxides, sulphides and accessory minerals. Their origin is attributed to differentiated parents bodies: large asteroids (Vesta); planets (Mars); a satellite (the Moon); and numerous asteroids of unknown size. In most cases, achondrites are not eye witnessed falls and some do not have fusion crust. Because of the mineralogical and magnetic susceptibility similarity with terrestrial igneous rocks for some achondrites, it can be difficult for classifiers to confirm their extra-terrestrial origin. We -as classifiers of meteorites- are confronted with this problem with every suspected achondrite we receive for identification. We are developing a "grid" of classification to provide an easier approach for initial classification. We use simple but reproducible criteria based on mineralogical, petrological and geochemical studies. We presented the classes: acapulcoites, lodranites, winonaites and Martian meteorites (shergottite, chassignites, nakhlites). In this work we are completing the classification table by including the groups: angrites, aubrites, brachinites, ureilites, HED (howardites, eucrites, and diogenites), lunar meteorites, pallasites and mesosiderites. Iron meteorites are not presented in this abstract

LANDSLIDE SUSCEPTIBILITY MAPPING IN THE MUNICIPALITY OF OUDKA, NORTHERN MOROCCO: A COMPARISON BETWEEN LOGISTIC REGRESSION AND ARTIFICIAL NEURAL NETWORKS MODELS

The Rif is among the areas of Morocco most susceptible to landslides, because of the existence of relatively young reliefs marked by a very important dynamics compared to other regions. These landslides are one of the most serious problems on many levels: social, economic and environmental. The increase in the frequency and impact of landslides over the past decade has demonstrated the need for an in-depth study of these phenomena, allowing the identification of areas susceptible to landslides. The main objective of this study is to identify the optimal method for the mapping of the area susceptible to landslides in municipality of Oudka. This area has been marked by the largest landslide in the region, caused by heavy rainfall in 2013. Two Statistical Methods i) Regression Logistics (LR) ii) Artificial Neural Networks (ANN), were used to create a landslide susceptibility map. The realization of this susceptibility map required, first, the mapping of old landslides by the aerial photography, the data of the geological map and by the data obtained using field surveys using GPS. A total of 105 landslides were mapped from these various sources. 50% of this database was used for model building and 50% for validation. Eight independent landslide factors are exploited to detect the most sensitive areas: altitude, slope, aspect, distance of faults, distance streams, distance from roads, lithology and vegetation index (NDVI). The results of the landslide susceptibility analysis were verified using success and prediction rates. The success rate (AUC&thinsp;=&thinsp;0.918) and the prediction rate (AUC&thinsp;=&thinsp;0.901) of the LR model is higher than that of the ANN model (success rate (AUC&thinsp;=&thinsp;0.886) and prediction rate (AUC&thinsp;=&thinsp;0.877). These results indicate that the Regression Logistic (LR) model is the best model for determining landslide susceptibility in the study area.</p

Hypothalamic inflammation is reversed by endurance training in anorectic-cachectic rats

<p>Abstract</p> <p>Aim</p> <p>We tested the effects of a cancer cachexia-anorexia sydrome upon the balance of anti and pro-inflammatory cytokines in the hypothalamus of sedentary or trained tumour-bearing (Walker-256 carcinosarcoma) rats.</p> <p>Methods</p> <p>Animals were randomly assigned to a sedentary control (SC), sedentary tumour-bearing (ST), and sedentary pair-fed (SPF) groups or, exercised control (EC), exercised tumour-bearing (ET) and exercised pair-fed (EPF) groups. Trained rats ran on a treadmill (60%VO_2max) for 60 min/d, 5 days/wk, for 8 wks. We evaluated food intake, leptin and cytokine (TNF-α, IL1β) levels in the hypothalamus.</p> <p>Results</p> <p>The cumulative food intake and serum leptin concentration were reduced in ST compared to SC. Leptin gene expression in the retroperitoneal adipose tissue (RPAT) was increased in SPF in comparison with SC and ST, and in the mesenteric adipose tissue (MEAT) the same parameter was decreased in ST in relation to SC. Leptin levels in RPAT and MEAT were decreased in ST, when compared with SC. Exercise training was also able to reduce tumour weight when compared to ST group. In the hypothalamus, IL-1β and IL-10 gene expression was higher in ST than in SC and SPF. Cytokine concentration in hypothalamus was higher in ST (TNF-α and IL-1β, p < 0.05), compared with SC and SPF. These pro-inflammatory cytokines concentrations were restored to control values (p < 0.05), when the animals were submitted to endurance training.</p> <p>Conclusion</p> <p>Cancer-induced anorexia leads towards a pro-inflammatory state in the hypothalamus, which is prevented by endurance training which induces an anti-inflammatory state, with concomitant decrease of tumour weight.</p