A Bioinformatic Study on the Potential Anti-Vitiligo Activity of a Carpobrotus edulis Compound.

The plant Carpobrotus edulis has traditionally been known for its wide applications in diseases, especially vitiligo, which is characterized by patches and white macules caused by the loss of melanocytes. One of the chemical treatments for vitiligo consists mainly of skin repigmentation and usually leads to a non-durable effect by inhibiting the Janus kinase (JAK) signal transduction (STAT pathway). JAK inhibitors generally block multiple JAK tyrosine kinases, which leads to secondary effects. In this study, natural molecules from Carpobrotus edulis were extracted and tested using a structure-based drug-design approach and pharmacophore modeling. The best-fit candidate from the extracted molecules was compared to the chemical molecules used. The results indicated a similarity between the chemical and natural ligands which suggested the potential use of the natural product against vitiligo. The main finding of this research work was the discovery of a new molecule extracted from a natural plant and the detection of its anti-vitiligo activity using an in-silico approach. This method can significantly reduce the cost of searching for potential medicinal molecules.

A SIR-Poisson Model for COVID-19: Evolution and Transmission Inference in the Maghreb Central Regions.

2019-nCoV is a virulent virus belonging to the coronavirus family that caused the new pneumonia (COVID-19) which has spread internationally very rapidly and has become pandemic. In this research paper, we set forward a statistical model called SIR-Poisson that predicts the evolution and the global spread of infectious diseases. The proposed SIR-Poisson model is able to predict the range of the infected cases in a future period. More precisely, it is used to infer the transmission of the COVID-19 in the three Maghreb Central countries (Tunisia, Algeria, and Morocco). Using the SIR-Poisson model and based on daily reported disease data, since its emergence until end April 2020, we attempted to predict the future disease period over 60 days. The estimated average number of contacts by an infected individual with others was around 2 for Tunisia and 3 for Algeria and Morocco. Relying on inferred scenarios, although the pandemic situation would tend to decline, it has not ended. From this perspective, the risk of COVID-19 spreading still exists after the deconfinement act. It is necessary, therefore, to carry on the containment until the estimated infected number achieves 0.

Genetic Markers Analyses and Bioinformatic Approaches to Distinguish Between Olive Tree (Olea europaea L.) Cultivars.

The genetic diversity of 22 olive tree cultivars (Olea europaea L.) sampled from different Mediterranean countries was assessed using 5 SNP markers (FAD2.1; FAD2.3; CALC; SOD and ANTHO3) located in four different genes. The genotyping analysis of the 22 cultivars with 5 SNP loci revealed 11 alleles (average 2.2 per allele). The dendrogram based on cultivar genotypes revealed three clusters consistent with the cultivars classification. Besides, the results obtained with the five SNPs were compared to those obtained with the SSR markers using bioinformatic analyses and by computing a cophenetic correlation coefficient, indicating the usefulness of the UPGMA method for clustering plant genotypes. Based on principal coordinate analysis using a similarity matrix, the first two coordinates, revealed 54.94 % of the total variance. This work provides a more comprehensive explanation of the diversity available in Tunisia olive cultivars, and an important contribution for olive breeding and olive oil authenticity.

OGDD (Olive Genetic Diversity Database): a microsatellite markers' genotypes database of worldwide olive trees for cultivar identification and virgin olive oil traceability.

Olive (Olea europaea), whose importance is mainly due to nutritional and health features, is one of the most economically significant oil-producing trees in the Mediterranean region. Unfortunately, the increasing market demand towards virgin olive oil could often result in its adulteration with less expensive oils, which is a serious problem for the public and quality control evaluators of virgin olive oil. Therefore, to avoid frauds, olive cultivar identification and virgin olive oil authentication have become a major issue for the producers and consumers of quality control in the olive chain. Presently, genetic traceability using SSR is the cost effective and powerful marker technique that can be employed to resolve such problems. However, to identify an unknown monovarietal virgin olive oil cultivar, a reference system has become necessary. Thus, an Olive Genetic Diversity Database (OGDD) (http://www.bioinfo-cbs.org/ogdd/) is presented in this work. It is a genetic, morphologic and chemical database of worldwide olive tree and oil having a double function. In fact, besides being a reference system generated for the identification of unkown olive or virgin olive oil cultivars based on their microsatellite allele size(s), it provides users additional morphological and chemical information for each identified cultivar. Currently, OGDD is designed to enable users to easily retrieve and visualize biologically important information (SSR markers, and olive tree and oil characteristics of about 200 cultivars worldwide) using a set of efficient query interfaces and analysis tools. It can be accessed through a web service from any modern programming language using a simple hypertext transfer protocol call. The web site is implemented in java, JavaScript, PHP, HTML and Apache with all major browsers supported. Database URL: http://www.bioinfo-cbs.org/ogdd/.

Clarification of purple carrot juice: analysis of the fouling mechanisms and evaluation of the juice quality.

Purple carrot juice was clarified by microfiltration. Two modes of filtration, batch concentration and total recycle were tested and the effect of microfiltration process on permeate flux and membrane fouling was studied. Intrinsic membrane resistance was negligible compared with the fouling resistances, which was less than 5 % of total resistance. Determination of membrane hydraulic permeability showed that water cleaning could permit a recovery of about 7 % of initial hydraulic flux. The analysis of color parameters of feed, permeate and concentrate juice during filtration shows that the a* and b* values decrease for the permeate corresponding respectively to changes from green to red and from blue to yellow. The total sugar and reducing sugars increase in permeate and decrease in concentrate. This work showed that it was possible to clarify the purple carrot juice by microfiltration with a real amelioration of the juice appearance.

Purification and characterization of an amylase from Opuntiaficus-indica seeds.

BACKGROUND: In Tunisia, prickly pear fruit grow spontaneously; it is consumed as fresh fruit, juice or jam. When the fruit is used for juice production, the seeds are discarded and go to waste. Our study aimed to extract biomolecules from seeds by producing value-added products from the fruits. RESULTS: An amylase from Opuntia ficus-indica seeds was extracted and purified to homogeneity. An increase in specific activity of 113-fold was observed. The apparent molecular mass of the enzyme is 64 kDa. The optimum pH and temperature for enzyme activity were pH 5 and 60 °C, respectively. Under these conditions, the specific activity is 245.5 U mg(-1) . The enzyme was activated by Co(2+) and Mg(2+) (relative activity 117% and 113% respectively) at lower ion concentrations. It was strongly inhibited by Mn(2+) and Fe(2+) . Cu(2+) inhibited totally the activity of this enzyme, but Ca(2+) has an inhibitory effect which increases with ion concentration. CONCLUSION: The extracted enzyme belongs to the exo type of amylases and is classified as a ß-cyclodextrin glycosyltransferase since it generates mainly ß-cyclodextrin from starch. It exhibits high thermal stability and a broad range of pH stability, making it a promising prospect for industrial and food applications.

Causal inference in biomolecular pathways using a Bayesian network approach and an Implicit method.

We introduce here the concept of Implicit networks which provide, like Bayesian networks, a graphical modelling framework that encodes the joint probability distribution for a set of random variables within a directed acyclic graph. We show that Implicit networks, when used in conjunction with appropriate statistical techniques, are very attractive for their ability to understand and analyze biological data. Particularly, we consider here the use of Implicit networks for causal inference in biomolecular pathways. In such pathways, an Implicit network encodes dependencies among variables (proteins, genes), can be trained to learn causal relationships (regulation, interaction) between them and then used to predict the biological response given the status of some key proteins or genes in the network. We show that Implicit networks offer efficient methodologies for learning from observations without prior knowledge and thus provide a good alternative to classical inference in Bayesian networks when priors are missing. We illustrate our approach by an application to simulated data for a simplified signal transduction pathway of the epidermal growth factor receptor (EGFR) protein.