Performance evaluation of IEEE 802.15.6 CSMA/CA-based CANet WBAN

International audienceIn the recent few years, Wireless Body Area networks (WBANs) showed what can be done remotely to greatly improve healthcare systems and facilitate the life to elderly. One of the recent ehealth projects is CANet which aims at embedding a WBAN into a cane to monitor elderly/patients. Our main goal in this paper is to evaluate the performances of the emerging standard IEEE 802.15.6 when applied on different sensors from CANet eHealth project. At this end, we defined a small scenario extracted from CANet, and we assigned IEEE 802.15.6 priorities to the selected cane sensors according to their inherent characteristics. We considered further the mandatory RAP period of IEEE 802.15.6 superframe under the beacon period with superframes mode since it supports both normal and urgent traffic. Our results showed that the contention access behavior of this considered model of simulation depends on several constraints (including the nature of the studied application and the traffic types and frequency). This would be necessarily taken into account to get the most advantage of all features offered by WBANs standard IEEE 802.15.6. Keywords—Medium Access Control (MAC), wireless body area networks (WBANs), E-health, CANet project, wireless sensor networks (WSN), IEEE 802.15.6

Comparative study of IEEE 802.15.4 and IEEE 802.15.6 for WBAN-based CANet

International audienceIn this paper, we present an overview of IEEE 802.15.4 and 802.15.6 standards. Thereafter, in view of their various strengths and many similarities, we study the possibility of using one of these two norms to implement the body area network (WBAN) of CANet (an innovative ehealth project) scenario according to the nature of the studied sensors. To do so, we considered an hybrid differentiation layer, previously proposed, based on 802.15.4 and we made a classification of CANet ehealth sensors based on IEEE 802.15.6 native superframe periods and priority and service differentiation systems. Each choice between them has its advantages and disadvantages. Thus, it will be necessary to analyse in detail the simulation and prototyping results of 802.15.4 and 802.15.6 norms once implemented in CANet context in order to decide about the standard providing the optimal QoS

Dosimetric impact on changes in target volumes during intensity-modulated radiotherapy for nasopharyngeal carcinoma

Background and purposeTo assess anatomic changes during intensity modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC) and to determine its dosimetric impact.Patients and methodsTwenty patients treated with IMRT for NPC were enrolled in this study. A second CT was performed at 38Gy. Manual contouring of the macroscopic tumor volumes (GTV) and the planning target volumes (PTV) were done on the second CT. We recorded the volumes of the different structures, D98 %, the conformity, and the homogeneity indexes for each PTV. Volume percent changes were calculated.ResultsWe observed a significant reduction in tumor volumes (58.56 % for the GTV N and 29.52 % for the GTV T). It was accompanied by a significant decrease in the D98 % for the 3 PTV (1.4Gy for PTV H, p=0.007; 0.3Gy for PTV I, p=0.03 and 1.15Gy for PTV L, p=0 0.0066). In addition, we observed a significant reduction in the conformity index in the order of 0.02 (p=0.001) and 0.01 (p=0.007) for PTV H and PTV I, respectively. The conformity variation was not significant for PTV L. Moreover, results showed a significant increase of the homogeneity index for PTV H (+ 0.03, p=0.04) and PTV L (+ 0.04, p=0.01).ConclusionTumor volume reduction during the IMRT of NPC was accompanied by deterioration of the dosimetric coverage for the different target volumes. It is essential that a careful adaptation of the treatment plan be considered during therapy for selected patients

HLA Class III: A susceptibility region to systemic lupus erythematosus in Tunisian population

<div><p>Background and objectives</p><p>Short tandem repeats (STR) are usually used as informative polymorphic markers for genetic mapping and for disease susceptibility analysis. The involvement of these microsatellite markers localized in the MHC region was reported in many auto-immune diseases.</p><p>In this study we analyzed for the first time eight polymorphisms of microsatellite loci at the HLA region: D6S291, D6S273, TNFa, b and c, MICA, D6S265 and D6S276, in Tunisian systemic lupus erythematosus (SLE) patients.</p><p>Materials and methods</p><p>We performed a case control study in which the microsatellite loci were amplified using specific primers labeled with NED, VIC, PET or 6-FAM and analyzed using GeneScan software 3.7. For the statistical analysis, we used SPSS software and we performed a sub-haplotype scoring test using the haplo.stats software developed in the R language.</p><p>Results</p><p>We found that two mean associated regions existed; the most statistically significant encompassed the 3 TNF markers (p = 0.0003, OR = 19.34); the latter covered the DR region. In fact, when scoring haplotypes in 3 marker- sliding windows, the p value increased as we moved away from the TNF region and decreased again when we approached the DRB1 locus. We also established for the first time the negative association between alleles of D6S291 and SLE. The majority of clinical and serological correlations were noted with TNF alleles.</p><p>Conclusion</p><p>Our results confirm the association between TNF and DRB1 polymorphisms and SLE. The association between alleles of D6S291 and SLE needs however to be verified by the analysis of other markers beyond this region.</p></div

Clinical and serological associations with STR markers.

<p>Clinical and serological associations with STR markers.</p

Characteristics of studied STR.

<p>Characteristics of studied STR.</p

Clinical and immunological manifestations in our patients.

<p>Clinical and immunological manifestations in our patients.</p

Three-marker window haplotype analysis.

<p>Three-marker window haplotype analysis.</p

Allelic distribution of STR markers.

<p>Allelic distribution of STR markers.</p