ABSTRACT
Background: Until now, there has been limited information on the prevalence and the phylogeny of Borrelia burgdorferi sensu lato in Ixodes ticks in Tunisia, particularly in Ixodes inopinatus. Methods: The present study aimed to determine the prevalence and the phylogeny of B. burgdorferi s.l., in coexisted I. ricinus and I. inopinatus ticks collected from Northern Tunisia. One hundred questig ticks were collected during winter 2020 by tick-dragging method in Beja gouvernorate located in the north of Tunisia. Real-time PCR panel targeting B. burgdorferi s.l. 23S rRNA gene were performed. Positive DNA samples were subjected to conventional PCRs targeting 457 bp fragment of the Borrelia sp. flagellin (fla) gene using primers FlaF/FlaR. The identified Borrelia sp. isolate underwent partial sequence analysis to determine genospecies and evaluate their phylogenetic position. Results: The study revealed a prevalence rate of 28% (28/100) for B. burgdorferi sensu lato in the Ixodes ticks. The prevalence rates across tick species and genders did not show significant variations (p > 0.05). Interestingly, the study underlines the coexistence of I. inopinatus and I. ricinus sharing the same geographic areas in Northern Tunisia. Furthermore, DNA of B. lusitaniae was detected in I. inopinatus ticks for the first time in Tunisia. Revealed B. lusitaniae bacterium is similar to previously identified strains in Mediterranean region, but distinct from those isolated exclusively from countries of Eastern and Central Europe, such as Serbia, Romania, and Poland. This study highlights the prevalence of B. burgdorferi s.l. in I. ricinus/I. inopinatus ticks, and reveals B. lusitaniae in I. inopinatus ticks for the first time in Tunisia. Conclusion: These findings suggest the involvement of I. inopinatus as a potential vector of this pathogenic genospeciess in Tunisia. This may help understanding the ecology of Ixodes ticks, the natural infection and the transmission dynamics of Borrelia species in this country.
ABSTRACT
Diffuse low-grade gliomas (DLGG) are brain tumors of young adults. They affect the quality of life of the inflicted patients and, if untreated, they evolve into higher grade tumors where the patient's life is at risk. Therapeutic management of DLGGs includes chemotherapy, and tumor diameter is particularly important for the follow-up of DLGG evolution. In fact, the main clinical basis for deciding whether to continue chemotherapy is tumor diameter growth rate. In order to reliably assist the doctors in selecting the most appropriate time to stop treatment, we propose a novel clinical decision support system. Based on two mathematical models, one linear and one exponential, we are able to predict the evolution of tumor diameter under Temozolomide chemotherapy as a first treatment and thus offer a prognosis on when to end it. We present the results of an implementation of these models on a database of 42 patients from Nancy and Montpellier University Hospitals. In this database, 38 patients followed the linear model and four patients followed the exponential model. From a training data set of a minimal size of five, we are able to predict the next tumor diameter with high accuracy. Thanks to the corresponding prediction interval, it is possible to check if the new observation corresponds to the predicted diameter. If the observed diameter is within the prediction interval, the clinician is notified that the trend is within a normal range. Otherwise, the practitioner is alerted of a significant change in tumor diameter.
