Phytochemical characterization, antioxidant and antibacterial activity of Salvia officinalis (L.) extracts from the Tiaret region

This work aims the valorization of a medicinal plant known by its traditional use, Salvia officinalis L. (Lamiaceae), by phytochemical characterization and evaluation of the antioxidant and antibacterial activity of their extracts. The antioxidant activity was assessed by the DPPH method and the antibacterial potential was determined by the diffusion method. The quantitative determination revealed that the ethanolic extract has a content of 8.04% for polyphenolic content and 17.4 % for flavonoids. The DPPH radical scavenging activity of S. officinalis showed that the ethanolic extract of S. officinalis presented the higher antiradical effect manifested with IC50 of 0.106±0.001 mg/ml. In addition, the antibacterial activity showed the strong capacity of S. officinalis methanolic extract to inhibit B. subtilis, M. luteus, E. coli and S. aureus with a diameter inhibition zone of 27.06±1.49; 15.43±2.23; 11.6±0.52 and 11.5±2.17 mm respectively. While the activity of the ethanolic extract was 26.62±2.97 mm against B. subtilis, 16.51±2.36 mm against M. luteus, 13.62±0.55 mm for S. aureus, P. aeruginosa (12.30±1.59 mm). The macrodilution method (MIC) showed a range of 625 to >5000 µg/ml. The study of the antioxidant and antibacterial activity of extracts of S. officinalis suggested that this plant represented a natural source of bioactive molecules with very important biological activities. DOI: http://dx.doi.org/10.5281/zenodo.512932

Ongoing diphtheria outbreak in Yemen: a cross-sectional and genomic epidemiology study.

BACKGROUND: An outbreak of diphtheria, declared in Yemen in October, 2017, is ongoing. We did a cross-sectional study to investigate the epidemiological, clinical, and microbiological features of the outbreak. METHODS: Probable cases of diphtheria that were defined clinically and recorded through a weekly electronic diseases early warning system (from 2017, week 22, to 2020, week 17) were used to identify trends of the outbreak (we divided the epidemic into three time periods: May 29, 2017, to June 10, 2018; June 11, 2018, to June 3, 2019; and June 4, 2019, to April 26, 2020). We used the line list of diphtheria reports for governorate-level descriptions. Vaccination coverage was estimated using the 2017 and 2018 annual reports by the national Expanded Programme on Immunization. To confirm cases biologically, Corynebacterium diphtheriae was isolated and identified from throat swabs using standard microbiological culture and identification procedures. We assessed differences in the temporal and geographical distributions of cases, including between different age groups. For in-depth microbiological analysis, tox gene and species-specific rpoB real-time PCR, Illumina genomic sequencing, antimicrobial susceptibility analysis (disk diffusion, E-test), and the Elek diphtheria toxin production test were done on confirmed cases. We used genomic data for phylogenetic analyses and to estimate the nucleotide substitution rate. FINDINGS: The Yemen diphtheria outbreak affected almost all governorates (provinces), with 5701 probable cases and 330 deaths recorded up to April 26, 2020. We collected clinical data for 888 probable cases with throat swab samples referred for biological confirmation, and genomic data for 42 positive cases, corresponding to 43 isolates (two isolates from one culture were included due to distinct colony morphologies). The median age of patients was 12 years (range 0·2-80). The proportion of cases in children aged 0-4 years was reduced during the second time period, after a vaccination campaign, compared with the first period (19% [95% CI 18-21] in the first period vs 14% [12-15] in the second period, p<0·0001). Among 43 tested isolates, 39 (91%) produced the diphtheria toxin and two had low level (0·25 mg/L) antimicrobial resistance to penicillin. We identified six C diphtheriae phylogenetic sublineages, four of which are genetically related to isolates from Saudi Arabia, Eritrea, and Somalia. Inter-sublineage genomic variations in genes associated with antimicrobial resistance, iron acquisition, and adhesion were observed. The predominant sublineage (30 [70%] of 43 isolates) was resistant to trimethoprim and was associated with unique genomic features, more frequent neck swelling (p=0·0029) and a younger age of patients (p=0·060) compared with the other sublineages. Its evolutionary rate was estimated at 1·67 × 10-6 substitutions per site per year, placing its most recent common ancestor in 2015, and indicating silent circulation of C diphtheriae in Yemen before the outbreak was declared. INTERPRETATION: In the Yemen outbreak, C diphtheriae shows high phylogenetic, genomic, and phenotypic variation. Laboratory capacity and real-time microbiological monitoring of diphtheria outbreaks need to be scaled up to inform case management and transmission control of diphtheria. Catch-up vaccination might have provided some protection to the targeted population (children aged 0-4 years). FUNDING: National Centre of the Public Health Laboratories (Yemen), Institut Pasteur, and the French Government Investissement d'Avenir Programme. TRANSLATION: For the Arabic translation of the abstract see Supplementary Materials section

A modified π rough k-means algorithm for web page recommendation system

Web page recommendation system is an application of Web Usage Mining (WUM) approach, which specializes in predicting the user next browsing activity in real-time Web for personalized recommendations. To date, many works have been addressed in investigating the use of data mining techniques (e.g., Clustering) in Web page application. Most of the research efforts are utilized partitional clustering algorithms to discover user profiles in order to obtain a better quality of recommendations. However, the quality of current solutions has only managed to achieve accuracy within the range of 60-70%. This happens due to the weaknesses of partitive algorithm criterion in Web page recommendation system to overcome the overlapping profiles, which require more attention. In order to tackle above problem, a modified algorithm for Web page recommendation is proposed. The ultimate goal is to improve the recommendation quality which leads to increase the prediction accuracy. Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. Secondly, a modified πRKM algorithm is proposed to partition the user session data. The modified πRKM is able to perform better partition by identifying the overlapping objects between the correct clusters and also capable to do a re-partition using the indiscernibility relation function. Thirdly, the local and global similarity algorithm is proposed to classify the current user pages request to produce recommendations. There are different datasets used to carry out extensive experiments which are described as follows; firstly, Iris and Vowel datasets were used to assess the effectiveness of proposed modified πRKM, where rough classifier assessment strategies used to measure the quality of overlapping classes. The experimental results revealed that the modified πRKM algorithm performed better than the previous version in terms of the correct identification of overlapping objects between positive clusters. Secondly, the CTI dataset, which has been proven by the existing research work as a more suitable Web server logs in the term of Web page recommendation quality, is used for measuring the performance of the proposed modified algorithm for Web page recommendation system. The experiment is divided into three interdependent stages of usage mining process, namely: data preparation, pattern discovery, and recommendation. In data preparation stage, the quality of prepared data is measured by Local Outlier Factor (LOF) method. The experimental results revealed that the degree of user sessions outliers reduced than the previous method while in pattern discovery stage, the results of user sessions partition with the modified πRKM algorithm are measured by the Davies Bouldin Index (DBI). The experimental results revealed that the modified πRKM algorithm significantly affected the partitions quality of the cluster obtained. In the third stage, the results of recommendation engine are measured using three accuracy parameters, namely Precision, Coverage, and Fmeasure. The results of the proposed modified algorithm for Web page recommendation system achieve an accuracy of 76-82% which is significantly outperforming than the previous work

A simple potentiometric sensor for rhodamine B

The construction and performance characteristics of PVC electrodes for Rhodamine B (RB) are described. Different methods for electrode fabrication (modified with the ion-pair, ion pairing agent or soaking the plain electrode in the ion-pair suspension) have been used. Matrix compositions were optimized on the basis of effects of type and content of the modifier as well as influence of the plasticizers. The fabricated electrodes worked satisfactorily in the concentration range from 1×10-6 to 0.001 M with Nernstian cationic slopes, depending on the method of electrode fabrication. The ion-pair modified electrode showed the best performance (slope 56.3±2.0 mV decade-1) compared with the plain electrodes or modified with sodium tetraphenylborate (NaTPB) and fast response time of about 8 sec and adequate lifetime (4 weeks). The developed electrodes have been successfully applied as well as end point indicator electrode for the potentiometric titration of RB with high accuracy and precision. The solubility products of different RB ion-pair were determined conductometrically