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Institution

Tunis University

EducationTunis, Tunisia
About: Tunis University is a education organization based out in Tunis, Tunisia. It is known for research contribution in the topics: Population & Thin film. The organization has 11745 authors who have published 15400 publications receiving 154900 citations. The organization is also known as: University of Tunis & UT.


Papers
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Journal ArticleDOI
TL;DR: A clinal distribution of certain haplogroups, some of them more frequent in Western or Eastern populations that might be the result of human migrations from the Middle East, sub-Saharan Africa, and Europe are shown.
Abstract: Human population movements in North Africa have been mostly restricted to an east-west direc- tion due to the geographical barriers imposed by the Sahara Desert and the Mediterranean Sea. Although these barriers have not completely impeded human migrations, genetic studies have shown that an east- west genetic gradient exists. However, the lack of genetic information of certain geographical areas and the focus of some studies in parts of the North African landscape have limited the global view of the genetic pool of North African populations. To provide a global view of the North African genetic landscape and population struc- ture, we have analyzed � 2,300 North African mitochon- drial DNA lineages (including 269 new sequences from Libya, in the first mtDNA study of the general Libyan population). Our results show a clinal distribution of certain haplogroups, some of them more frequent in Western (H, HV0, L1b, L3b, U6) or Eastern populations (L0a, R0a, N1b, I, J) that might be the result of human migrations from the Middle East, sub-Saharan Africa, and Europe. Despite this clinal pattern, a genetic discon- tinuity is found in the Libyan/Egyptian border, suggest- ing a differential gene flow in the Nile River Valley. Finally, frequency of the post-LGM subclades H1 and H3 is predominant in Libya within the H sequences, high- lighting the magnitude of the LGM expansion in North Africa. Am J Phys Anthropol 000:000-000, 2011. V C 2011 Wiley-Liss, Inc.

45 citations

Journal ArticleDOI
TL;DR: These findings demonstrate that PpSP32 is the immunodominant target of the antibody response to P. papatasi bites and represents a good candidate for large scale testing of human exposure to the vector and perhaps for assessing the risk of contracting the disease.
Abstract: Background Zoonotic cutaneous leishmaniasis (ZCL) due to Leishmania major is highly prevalent in Tunisia and is transmitted by a hematophagous vector Phlebotomus papatasi (P. papatasi). While probing for a blood meal, the sand fly injects saliva into the host's skin, which contains a variety of compounds that are highly immunogenic. We recently showed that the presence of anti-saliva antibodies was associated with an enhanced risk for leishmaniasis and identified the immunodominant salivary protein of Phlebotomus papatasi as a protein of approximately 30 kDa.

45 citations

Journal ArticleDOI
TL;DR: The occurrence of the prevalent plasmid pattern in both epidemic strains and unrelated isolates indicated that diffusion and endemic persistence of the bla(SHV-ESBL) genes in the ward were due to concomitant spread of epidemic strain and plasmids dissemination among unrelated strains.
Abstract: Previous genotypic investigations of extended-spectrum beta-lactamase (ESBL)-producing Klebsiella pneumoniae recovered in a Tunisian neonatal ward revealed the spread of two epidemic strains and a high number of genetically unrelated isolates. The aim of the present study was to determine the role of the dissemination of self-transferrable plasmids harboring bla genes in the outbreaks experienced by the ward. The 49 previously identified clinical isolates of ESBL-producing K. pneumoniae were examined for relationships between their enzymes and plasmids. Analysis of crude extracts by isoelectric focusing showed four beta-lactamase-activities at pI 8.2, 7.6, 6, and 5.4. Clinical isolates contained large plasmids that could be transferred by conjugation and transformation conferring resistance to expanded-spectrum cephalosporins. DNA amplification and sequencing were performed to confirm the identities of transferred beta-lactamases. Nucleotide sequence analysis of SHV-specific PCR products from six isolates identified two bla(SHV) genes corresponding to SHV derived ESBLs, SHV-12 and SHV-2a. PstI digestion of plasmid DNA from transformants revealed six restriction patterns. The occurrence of the prevalent plasmid pattern in both epidemic strains and unrelated isolates indicated that diffusion and endemic persistence of the bla(SHV-ESBL) genes in the ward were due to concomitant spread of epidemic strains and plasmid dissemination among unrelated strains.

45 citations

Proceedings ArticleDOI
01 Jan 2017
TL;DR: A predictive modeling approach is proposed to detect robot manipulator accuracy errors based on robot's current data analysis for predictive maintenance purposes and the feasibility of building a data-driven condition monitoring of robot manipulators using the electrical power time-series data analysis is proved.
Abstract: The predictive maintenance of industrial machines is one of the challenging applications in the new era of Industry 4.0. Thanks to the predictive capabilities offered by the emerging smart data analytics, data-driven approaches for condition monitoring are becoming widely used for early detection of anomalies on production machines. The aim of this paper is to provide insights on the predictive maintenance of industrial robots and the possibility of building a condition-monitoring system based on the data analysis of robot's power measurements. A predictive modeling approach is proposed to detect robot manipulator accuracy errors based on robot's current data analysis for predictive maintenance purposes. An experimental procedure is also carried out to oversee the correlation between the robot accuracy error and a set of extracted features from current time-series, and to evaluate the proposed predictive modeling. The obtained results are satisfactory and prove the feasibility of building a data-driven condition monitoring of robot manipulators using the electrical power time-series data analysis.

45 citations

Journal ArticleDOI
TL;DR: This review provides a comprehensive understanding of sarc Openia in various autoimmune diseases and highlights the need for a consistent definition of sarcopenia.
Abstract: Sarcopenia refers to a decrease in skeletal muscle mass and function. Because sarcopenia affects mortality, and causes significant disability, the clinical importance of sarcopenia is emerging. At first, sarcopenia was recognized as an age-related disease but, recently, it has been reported to be prevalent also in younger patients with autoimmune diseases. Specifically, the association of sarcopenia and autoimmune diseases such as rheumatoid arthritis has been studied in detail. Although the pathogenesis of sarcopenia in autoimmune diseases has not been elucidated, chronic inflammation is believed to contribute to sarcopenia, and moreover the pathogenesis seems to be different depending on the respective underlying disease. The definition of sarcopenia differs among studies, which limits direct comparisons. Therefore, in this review, we cover various definitions of sarcopenia used in previous studies and highlight the prevalence of sarcopenia in diverse autoimmune diseases including rheumatoid arthritis, spondyloarthritis, systemic sclerosis, inflammatory bowel disease, and autoimmune diabetes. In addition, we cover the pathogenesis and treatment of sarcopenia in autoimmune and rheumatic diseases. This review provides a comprehensive understanding of sarcopenia in various autoimmune diseases and highlights the need for a consistent definition of sarcopenia.

45 citations


Authors

Showing all 11809 results

NameH-indexPapersCitations
Walid Saad8574930499
Alexandre Mebazaa8371639967
Albert Y. Zomaya7594624637
Anis Larbi6725915984
Carmen Torres6446115416
Chedly Abdelly6042914181
Hans R. Kricheldorf5782518670
Mohamed Benbouzid5149212164
Enrique Monte481187868
Fayçal Hentati4715310376
A. D. Roses4512024719
Laurent Nahon452056252
Bessem Samet453087151
Maxim Avdeev425268673
Abdellatif Boudabous401745605
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202316
2022130
20211,621
20201,599
20191,685
20181,689