Clément Goubault

Ulrich Jarry

Mégane Bostoën

Pierre-Antoine Éliat

Myrtil L Kahn

Rémy Pedeux

Thierry Guillaudeux

Fabienne Gauffre

Soizic Chevance

Stéphanie Dutertre

Xavier Pinson

Agnès Burel

Aurélien Dupont

Roselyne Viel

Alain Fautrel

R Hashizume

Radiosensitizing Fe-Au nanocapsules

Keywords: BBB, Blood Brain Barrier, GBM, Glioblastoma, H®, Hybridosome®, H(Fe), Iron oxide Hybridosome®, H(Fe, Au), Iron Oxide and Gold Hybridosome®, IR, Irradiation, MRI, Magnetic Resonance Imaging, NP, nanoparticle(s), NTA, Nanoparticle Tracking Analysis, ROS, Reactive Oxygen Species, SPION, iron oxide superparamagnetic nanoparticles, TEM, Transmission Electron Microscopy Glioblastoma, Nanoparticles, Hybridosomes®, Combined therapies, Radiotherapy, Chemotherapy, Mouse Models, MRI and Bioluminescence

Introduction

Glioblastoma multiforme (GBM: WHO grade IV), with an incidence of 5 per 100,000 people, is the most common type of brain tumor. It is highly aggressive and often deeply infiltrates brain tissues [START_REF] Aubry | From the core to beyond the margin: a genomic picture of glioblastoma intratumor heterogeneity[END_REF] . Today, the standard treatment, defined as the Stupp protocol, is based on surgery followed by radiotherapy (5 times 2 Gy per week for 6 weeks; total 60 Gy) with concomitant (75 mg per square meter of body-surface area per day, 7 days per week from the first to the last day of radiotherapy) chemotherapy with temozolomide as adjuvant (150 to 200 mg per square meter for 5 days during each 28-day cycle) [START_REF] Stupp | Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma[END_REF] . Despite this severe treatment, the median survival remains poor (< 18 months) with a rate of 5-year survival less than 5% [START_REF] Wang | A comparison between oral chemotherapy combined with radiotherapy and radiotherapy for newly diagnosed glioblastoma: A systematic review and meta-analysis[END_REF][START_REF] Weller | Standards of care for treatment of recurrent glioblastoma-are we there yet?[END_REF] . GBM is one of the few cancers for which there has been little increase in life expectancy over the past 30 years. In addition to the infiltrating nature of the tumor, which makes total resection of the tumor by surgery almost impossible, one of the major obstacles to the treatment of GBM is the Blood Brain Barrier (BBB). Indeed, the BBB severely limits the penetration of chemotherapeutic molecules and radiosensibilizing agents into brain tumor tissues. Brain tumor development partly disturbs the permeability of this BBB but often at it latest stage and not uniformly, which leads to an inefficient drug delivery [START_REF] Sarkaria | Is the blood-brain barrier really disrupted in all glioblastomas? A critical assessment of existing clinical data[END_REF] . To overcome this limitation, one strategy is the use of local administration [START_REF] Clavreul | Nanocarriers and nonviral methods for delivering antiangiogenic factors for glioblastoma therapy: the story so far[END_REF] . Thus, implantable polymer devices delivering a chemotherapy such as Gliadel® are presently used in the clinics. Direct intracranial delivery of drug-loaded vehicles, notably lipid nanocapsules, or of cellular vehicles such as stem cells producing growth factor inhibitors, has yielded promising results in orthotopic GBM models. [START_REF] Ashby | Gliadel wafer implantation combined with standard radiotherapy and concurrent followed by adjuvant temozolomide for treatment of newly diagnosed high-grade glioma: a systematic literature review[END_REF] Alternatively, intracranial infusion of drugs through convection-enhanced delivery devices enables the administration of drugs over longer period and has shown encouraging results in small animal models (see reference [START_REF] Séhédic | Locoregional Confinement and Major Clinical Benefit of 188Re-Loaded CXCR4-Targeted Nanocarriers in an Orthotopic Human to Mouse Model of Glioblastoma[END_REF] for review). Among the numerous therapeutic strategies which have been explored [START_REF] Zhang | Glioblastoma Treatment Modalities besides Surgery[END_REF]10 , an attractive lead with the promise of a breakthrough in cancer therapies is the improvement of radiotherapy through the use of radiosensitizing nanoparticles, in particular high-Z nanoparticles (Z: atomic number) [START_REF] Butterworth | Physical basis and biological mechanisms of gold nanoparticle radiosensitization[END_REF][START_REF] Coulter | Radiosensitising Nanoparticles as Novel Cancer Therapeutics -Pipe Dream or Realistic Prospect?[END_REF][START_REF] Rancoule | Nanoparticles in radiation oncology: From bench-side to bedside[END_REF][START_REF] Xie | Emerging Strategies of Nanomaterial-Mediated Tumor Radiosensitization[END_REF] . Indeed, the use of conventional radiotherapy is limited by the damages caused to healthy tissues in the path of irradiation. In the presence of high-Z nanoparticles, the energy is absorbed and "deposited" much more locally than in normal tissues, due both to the strong photon absorption and to the conversion of the initially high energy radiation into several low energy Auger electrons. First, photon-X are absorbed by atoms via the photoelectric effect, with an efficiency roughly proportional to Z [START_REF] Weller | Standards of care for treatment of recurrent glioblastoma-are we there yet?[END_REF] , thus favoring high-Z atoms in comparison to soft tissues. Following the absorption of a single photon of high energy, a high-Z atom may expel a dozen of Auger electrons of lower energy, hence of low penetration (~10 nm). Furthermore, the generated Auger electrons and secondary X-rays induce the production of hydroxyl radicals (HO . ) via water radiolysis. These, and other reactive oxygen species (ROS) that are further generated readily react with biological molecules, including DNA, proteins and lipids inducing cell death [START_REF] Hainfeld | Radiotherapy enhancement with gold nanoparticles[END_REF] . Gold (Z=79) is a material of choice, since it combines the advantages of biocompatibility and strong photoelectric effect [START_REF] Coulter | Radiosensitising Nanoparticles as Novel Cancer Therapeutics -Pipe Dream or Realistic Prospect?[END_REF] . The first in vivo experimental evidences of the radiosensitization effect of gold nanoparticles (AuNP) dates back to the 2000s [START_REF] Hainfeld | The use of gold nanoparticles to enhance radiotherapy in mice[END_REF][START_REF] Hainfeld | Radiotherapy enhancement with gold nanoparticles[END_REF] and the number of reports has kept increasing since then. The location of the gold nanoparticles at the tumor site can be verified by computed tomography (CT). Among the other metal-based materials that have been considered for radiosensitization, gadolinium and superparamagnetic iron oxide have the advantage of being easily tracked by MR-imaging (MR: magnetic resonance) [START_REF] Shariati | The Cancer therapy materialization by Theranostic nanoparticles based on gold doped Iron oxide under electromagnetic field amplification[END_REF] .

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Scheme: Schematic representation of a hybridosome® summarizing its main physicochemical characteristics and its multiple and general theranostic potentialities in terms of therapies, imaging and targeting. The potentialities used in the present work are highlighted in bold. Recently we have introduced a new type of multimodal nanocapsules, named hybridosomes® (H®), whose shell consists of inorganic nanoparticles (NP) crosslinked with a polymer [START_REF] Sciortino | Simple Engineering of Polymer-Nanoparticle Hybrid Nanocapsules[END_REF][START_REF] Gauffre | Assemblies of hydrophobic nanoparticles in an aqueous medium[END_REF] (Scheme). Interestingly, these nanocapsules are produced by a simple nanoprecipitation method, which allows at the same time the formation of the NP-shell and the encapsulation of a hydrophobic active ingredient. A previous study demonstrated that the storage capacity in the core of these nanocapsules is extremely high (over 170 g.L -1 ), the hydrophobic ingredient being condensed in a nanoprecipitated form 20 . Hybridosomes® containing iron oxide superparamagnetic nanoparticles (SPION), named hereafter H(Fe), can be used as MRI T2 contrast agents, with an efficiency comparable to commercial iron oxide based contrast agents such as Feraspin XXL TM 18 . In addition, a stealth-providing poly(ethylene glycol) block (PEG) can be added to the polymer holding the shell, to limit uptake by monocytes and delay their sequestration in the specialized organs of the immune system. Based on these results, hybridosomes® appear to be prime candidates for the treatment of cancers requiring multimodal therapies, such as glioblastoma.

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The main aim of the present work is to evaluate the radiosensitizing effect of H(Fe;Au) hybridosomes® composed of superparamagnetic iron oxide and a small amount of gold nanoparticles (10%) on GBM after intratumoral injection in mice implanted with the GL261 brain tumor model. We first evaluated the distribution of hybridosomes® in vitro and in vivo.

We took advantage of iron oxide NP to follow the in vivo biodistribution of H(Fe;Au) using MRI and to evaluate their presence in post-mortem tissues by histology (Perls staining). Then, we performed a survival study to evaluate the increased therapeutic effect of H(Fe;Au) in combination with irradiation. Six groups of mice were examined, including 3 groups not treated with radiotherapy (injected with H(Fe), H(Fe;Au) or none) and 3 similar groups receiving radiotherapy. Tumor growth was monitored in all groups by both bioluminescence and MRI.

We have also characterized the transfer of an encapsulated charge from hybridosomes® to tumor cells, in vivo and in vitro, using a fluorescent dye BODIPY as a model. All these works and the good results obtained, allow us to consider the use of hybridosomes® as a unique theranostic nanoplatform to efficiently combine chemo-and radiotherapy, offering the possibility of a follow-up by imaging. stabilized) was purchased from VWR and used as received. Samples were made using MilliQ water (18.2 MΩ.cm -1 ). The fluorescent dye 4,4-difluoro-8-(4-trimethylsilylethynylphenyl)-1,3,5,7-tetramethyl-2,6-diethyl-4-bora-3a,4a-diaza-s-indacene (BODIPY, M = 476.2 g.mol -1 ) was kindly provided by Dr O. Mongin (Univ Rennes, CNRS, ISCR-UMR6226, F-35000 Rennes, France.) [START_REF] Ulrich | Convenient and Efficient Synthesis of Functionalized Oligopyridine Ligands Bearing Accessory Pyrromethene-BF2 Fluorophores[END_REF] .

Materials and methods

Elaboration and characterization of hybridosomes®

The iron oxide (-Fe2O3) nanoparticles (SPION) were synthesized following a reported procedure with slight modifications [START_REF] Casterou | Improved Transversal Relaxivity for Highly Crystalline Nanoparticles of Pure γ-Fe 2 O 3 Phase[END_REF] . Briefly, the SPION are obtained via hydrolysis of an organometallic Fe(II) precursor in the presence of a stabilizing ligand (here 2 eq. of octylamine and 1 eq. of oleic acid, relative to Fe), in the absence of any other solvent. Oleylamine-coated gold NP were synthesized following the procedure reported by Liu et al. [START_REF] Liu | Synthesis of Monodisperse Au, Ag, and Au-Ag Alloy Nanoparticles with Tunable Size and Surface Plasmon Resonance Frequency[END_REF] . Briefly, AuNP were synthesized in oleylamine, which acts both as a reductor of the gold salt (HAuCl4, 3 H2O) at 150°C and as a capping agent to stabilize the newly synthesized NP. After 1h30 of reaction, AuNP are readily dispersed in THF after precipitation in ethanol and centrifugation. Note that it is important for the elaboration of hybridosomes® to use alkyl-coated (hydrophobic) NP.

The magnetic hybridosomes® H(Fe) and H(Fe;Au) were prepared by rapidly adding water to a THF solution containing the iron oxide NP (plus the AuNP for H(Fe;Au)), in order to reach a water/THF composition of 75/25 v/v. Mixing was promptly followed by a very quick vortexing. After ca 7 h, PEG-PAA ([acrylic acid units] = 2.4 mmoles.L -1 ) was added to the mixture and the solvent was slowly evaporated overnight at 40°C. Two 24 h magnetic separations were performed using a permanent magnet, and the pellets were dispersed in fresh water to recover the purified hybridosomes®. To elaborate dye-loaded hybridosomes®, the BODIPY was dissolved in the THF solution in order to reach a final dye concentration in the water/THF mixture of 50 µmol.L -1 . After encapsulation, the BODIPY-loaded hybridosomes® can be excited at 488 nm, which is close to their maximum of absorbance, to produce a broad band emission around 550 nm 20 . The distribution of hydrodynamic diameters and H® concentration was determined by Nanoparticle Tracking Analysis (NTA), using a Nanosight LM10 device system (Malvern Panalytical) equipped with a 40 mW laser working at λ = 638 nm. Video sequences were recorded via a CCD camera operating at 30 frames per second and evaluated via the NANOSIGHT NTA 2.0 Analytical Software Suite. For each sample, 3 acquisitions with an acquisition time of 60 s were performed at 25°C. TEM analysis was performed using a Jeol 1400 electron microscope equipped with a Gatan Orius 1000 camera. The elemental concentrations of iron (18.7 µg/mL) and gold (2 μg/mL; in the case of H(Fe;Au)) in the purified H® suspensions were determined by atomic spectroscopy. Typically, the H® were dissolved in nitric acid for one week under heating at 40 °C. After appropriate dilution with milliQ water, ACCEPTED MANUSCRIPT / CLEAN COPY the concentrations were determined using an iCAP 7000Series ICP-OES spectrometer (Thermo Scientific) under an argon flow.

Tumoral cells, mice and brain implantation

GL261-Luc + cells were kindly provided by R. Hashizume (University of California, San Francisco, CA). [START_REF] Clark | Stable luciferase expression does not alter immunologic or in vivo growth properties of GL261 murine glioma cells[END_REF] Cells were cultured in DMEM medium (Dutscher, Brumath, France) supplemented with 10 % heat inactivated FBS (Dutscher) and 2 mM L-Glutamine (PanBiotech, Aidenbach, Bavaria, Germany). C57BL/6 (B6/Rj) and C57BL/6 albino (B6/Rj-Tyrc/c) mice were purchased from Janvier Labs (Saint Berthevin, France) and bred in the animal facility of the University of Rennes (ARCHE, Biosit, SFR UMS CNRS 3480-INSERM 018, Université de Rennes 1) under specific pathogenfree status. Mice were used at 6-12 weeks of age and manipulated according to institutional guidelines.

For stereotaxic implantation, mice were anesthetized with an intraperitoneal injection of ketamine (10 μg/g) and xylazine (1 μg/g) and were placed in a stereotactic frame (Stoelting, Dublin, Ireland). The animals underwent an injection (0.5 μL/min) of 10.10 3 GL261-Luc + cells in 2 μL sterile PBS with a Hamilton syringe, at the level of the bregma 3 mm on the right of the medial suture and at a depth of 2.5 mm. The syringe was held in place for an additional minute and was slowly removed to avoid backfilling of the solution.

The protocols were approved by the French Ministère de l'Enseignement Supérieur et de la Recherche and by the local Ethic Committee (Comité Rennais d'Ethique en matière d'Expérimentation Animale (CREEA) (France) (Agreement # 10972)). In particular, the number of animals per study group was validated and therefore allowing not to multiply the number of tumor models.

The mice were daily observed and were euthanized when showing specific clinical signs, following standard procedures. Among the conventional signs, those that were observed are the following:

Notable Clinical Signs (limit point reached if 3 simultaneous signs are detected): agitation/aggressiveness; hypomotility/hyporeactivity; moderate incoordination; stereotypes; generalized muscle flaccidity; abdominal swelling; arched back; weight loss less than 10 %, no food intake for less than 2 days.

Severe Clinical Signs (limit point reached if 1 sign is detected): akinesia; decubitus; difficulty/impossibility of mobilization; marked incoordination; generalized tremors; convulsions; weight loss more than 10%; no food intake for more than 2 days.

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Hybridosomes® injection and irradiation protocol

For in vivo distribution, dye-loaded H(Fe;Au) were injected in the brain tumor of mice 14 days after implantation of the GL261-Luc + tumor cells. For assessment of the irradiation procedure, H(Fe) were injected in the tumor to groups 2 & 5 and H(Fe;Au) to groups 3 & 6, at day 14 or 16 (albino mice) after tumor cells injection, and radiotherapy started the same day for groups 4, 5 & 6, as indicated in Table 1. The albino (a) and non-albino (na) mice were distributed within the groups as follows: group 1 = 6(a)/5(na); group 2 = 7(a); group 3 = 3(a)/6(na); group 4 = 6(a)/6(na); group 5 = 11(a); group 6 = 7(a)/6(na). The injected amount is 5 µL of a concentrated dispersion of hybridosomes® in PBS (500 µg.mL -1 Fe and 53 µg.mL -1 Au in the case of H(Fe;Au), i.e. ca 125 µg Fe & 13 µg Au/mouse kg. The intratumoral injection is performed as described above at the rate of 1 µL.min -1 at the exact same location as tumor implantation. For tumor irradiation mice were anesthetized with isoflurane. Irradiation was performed using an X-ray generator (CellRad, Faxitron Bioptics, Tucson, AZ)) on the head area at 2 Gy/day for 5 days.

Confocal microscopy

Images were acquired using a LSM 880 confocal microscope (Zeiss, Oberkochen, Deutschland) equipped with a 63X oil-immersion objective (NA 1.4) and driven by ZEN software. The beam excitation laser was 488 nm and the emission channel detector was set at 517-544 nm. Images were analyzed and processed with ImageJ. [START_REF] Schneider | NIH Image to ImageJ: 25 years of image analysis[END_REF]

Tissue isolation and Histology

After collection, brains, livers, cervical lymph nodes and spleens were frozen in isopentane (Sigma-Aldrich, St Louis, MO) and serially sectioned at 10 µm using a Leica cryostat (Leica, Solms, Germany) at -30 °C. Slides were firstly scanned using the NanoZoomer 2.0 HT (Hamamatsu Photonics K.K., Hamamatsu, Japan) for hybridosomes ® fluorescence acquisition.

Then, slices were stained either with DAPI (SouthernBiotech, Birmingham, AL), Hematoxylin and eosin (H&S) and/or Perls (specific iron staining) before second acquisition.

In vivo Bioluminescence assays

Mice received an intraperitoneal injection of 150 µL of 15 µg.µL -1 D-Luciferin K + solution, (Interchim, Montluçon, France) while anesthetized via inhaled isoflurane and monitored using a Photon imager (Biospace Lab, Nesles la Vallée, France) equipped with a highly sensitive ACCEPTED MANUSCRIPT / CLEAN COPY cooled CCD camera. Data were analyzed using the cpm (count per minutes) per cm² focused on the head.

In vivo Magnetic Resonance Imaging

In vivo Magnetic Resonance Imaging (MRI) experiments were carried out at 4.7 Tesla with a horizontal Biospec 47/40 imaging system (Bruker Biospin, Wissembourg, France). After prior anesthesia with isoflurane, mice were placed in a prone position and held in a contention system equipped with a face mask for anesthesia with 1-2.5% isoflurane in air. Breathing was monitored with a pneumatic probe. The body temperature was maintained at 36.5-37.5°C by a feedback-regulated heating pad throughout the imaging protocol. Tumor size was monitored using axial and coronal T2-weighted images obtained using a Rapid Acquisition with Relaxation Enhancement (RARE) sequence [START_REF] Hennig | Rapid nontomographic approach to MR myelography without contrast agents[END_REF] . Acquisition parameters were as follows: TR = 3500 ms; TE/TEeff = 9.35/28.5 ms; RARE factor = 8; 2 averages, in plane resolution = 100 µm x 100 µm, slices thickness = 1 mm. Acquisition time was 2 min 20 s for each acquisition.

Tumor volumes V (mm 3 ) were calculated according to the formula, V = (L x l x h) x /6, with L, l and h the lengths of the 3 main axes of the tumor measured on axial and coronal MR Images.

Statistical analysis

To avoid tumor size bias, the mice were distributed into 6 groups such that each mice group contains tumors of all sizes, based on MRI measurements at days 9/10 after tumor implantation (see Figure SI-1). Two mice (out of 54) with tumor size exceeding 30 mm 3 were excluded from the cohort, after which the mean diameter size was 4.8  1.12 mm 3 . Data are expressed as median survival and were analyzed using GraphPad Prism 7.0 (GraphPad Software, Inc., San Diego, CA) or Origin softwares. The P-values were calculated using the Logrank (Mantel-Cox) test (*p<0.05).

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Results

Characterization of the gold containing hybridosomes® H(Fe;Au).

As already described in detail previously elswhere [START_REF] Sciortino | Simple Engineering of Polymer-Nanoparticle Hybrid Nanocapsules[END_REF][START_REF] Sciortino | Structure and elasticity of composite nanoparticle/polymer nanoshells (hybridosomes®)[END_REF] , our hybridosomes® are very original types of nanocapsules (Scheme). They are original both in i) their synthesis (simple and fast), ii) their composition (inorganic NP, organic polymer) and iii) their multifunctionality, coming from the NP shell (imaging, therapy) as well as from the core allowing the loading of a large number of molecules (efficient drug delivery). In this work, we have optimized the shell of our magnetic iron-oxide hybridosomes(R), usually only made of SPION, by adding a small number of gold nanoparticles (AuNP) in order to confer a radiosensitization property to our nanocapsules. The designed mixed iron-gold hybridosomes® H(Fe;Au) were characterized by transmission electron microscopy (TEM) and single Nanoparticle Tracking Analysis (NTA) (Figure 1A). In a recent study, we developed the process of encapsulation in hybridosomes®, using a fluorescent model dye (BODIPY) and iron oxide hybridosomes® 20 . The dye is encapsulated in a solid form (nanoprecipitate) with two main emission bands centered at 560 nm (green) and 625 nm (red). Here, we investigated the release of the encapsulated dye from the gold containing H(Fe;Au) into GBM cells. To this aim, GL261-Luc + cells were incubated for 2 hours with BODIPY-loaded H(Fe;Au) and then analyzed by confocal microscopy. As seen in Figure 2, the green fluorescence of the dye was detected in the cytosol of incubated cells, but not in the nucleus.

Intracellular delivery of encapsulated payload.

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Biodistribution of the hybridosomes® and of their cargo

We next sought to evaluate the in vivo biodistribution of the capsule and cargo (i.e. encapsulated load) after intra-tumoral injection of dye-loaded hybridosomes®. To this aim, BODIPY-loaded H(Fe), were injected in the brain tumors of 10 mice, 14 days after implantation of the GL261 -Luc + tumor cells. Two mice were sacrificed 30 min after injection, and then every day to study their main organs. The presence of iron (more precisely Fe 3+ ions) from the shells of the hybridosomes® was assessed by optical microscopy following Perls staining on slices of brains and livers at day 5 (Figure 3A). In brain slices, iron is irregularly present near the edges of the tumor. No significant accumulation of exogeneous iron could be detected in the liver.

The BODIPY fluorescence (green + red) from slices of brain, liver, spleen and cervical lymph nodes is displayed in Figure 3B lymph nodes). No signal was detected for non-injected mice (upper pictures). For injected mice, 30 min after injection, the fluorescence of the BODIPY remains localized in a limited area, most probably surrounding the site of injection (Figure 3B). Then, it spreads spatially over the 5 days of monitoring. Interestingly, the fluorescence signal seems to co-localize with the tumor (with the exception of the individual analyzed at 48 h). Some diffuse fluorescence also appears in the liver, but with a delay of a few days. A low amount of fluorescence is also significant in the cervical lymph nodes after a few days but remains non-significant in the spleen (

Survival

We sought to assess whether hybridosomes® containing a small amount of AuNP (H 90% Fe; 10% Au) could potentiate the therapeutic effect of radiations on GL261-Luc + brain tumor model. To this aim, GL261-Luc+ brain tumor-bearing mice were divided into six groups with similar tumor size distributions (Figure SI-1), as measured by MRI 9 or 10 days after tumor implantation. The mice received intratumoral injection of either H(Fe;Au), H(Fe) or none, depending on their group, as shown in Table 1. The same day, radiotherapy started for the groups concerned. Radiotherapy was applied for 5 days with 2 Gy / day. Figure 4 shows the Kaplan-Meier survival curves for all groups. The Figure 4 shows that the group of mice treated with H(Fe;Au) combined with irradiation (red full line) exhibit the longest median survival (28 days), far ahead of other groups which have a median survival in between 21 days (untreated mice) and 24 days (radiotherapy only).

More precisely, survival was significantly increased in the H(Fe;Au) + irradiation group compared to untreated mice (*p = 0.0115, logrank). In contrast, even if the number of mice used was almost the same (12 and 13 respectively), treatment with irradiation showed no significant benefit (p=0.1123). The groups treated with H(Fe), H(Fe;Au) and even H(Fe)+irradiation showed no significant difference with the control group receiving no treatment.

Monitoring of the tumoral growth by Bioluminescence and MRI

The first bioluminescence measurement was achieved on day 9 after tumor cells implantation, individuals exhibited a reduction in signal intensity after the irradiation period. This is particularly true in group 6 (H(Fe;Au) + irradiation) where 3 out of 7 mice showed a significant decrease of bioluminescence after irradiation. The case of one particular mouse who survived for 78 days is detailed in the following section. In the control group 4, irradiated but receiving no hybridosomes®, only 1 out of 6 mice underwent such signal decrease. Two mice in the group irradiated in the presence of H(Fe) (group 5) had a temporary stop of tumor growth, but no decrease in size was observed. ACCEPTED MANUSCRIPT / CLEAN COPY Case study of a long term survivor treated by radiotherapy combined with H(Fe;Au)

Of note, one mouse (#1082) treated with H(Fe;Au) combined with irradiation survived until day 78 after tumor implantation (Figure 4). Its tumor size was monitored over all this period by both bioluminescence and MRI. The bioluminescence signal (Figure 6A) from the GL261-Luc+ implanted tumor clearly decreased after the irradiation treatment, over a period of almost three weeks (from day 21 to day 39). The decrease in intensity over this period is more than a factor of 20. From day 40, the bioluminescence increased again, first slowly, then abruptly. The tumor size was also monitored using MRI (Figure 6B). From day 24 to day 62 the tumor remained extremely small and hindered by the hypointense signal of the iron-oxide NP. A sudden burst of the tumor growth occurred in-between days 70 and 78.

To go further, the brain of the mouse # 1082 was collected after death, serially sectioned (every 100 µm) and analyzed by optical microscopy after HES and Perls staining (

Discussion

ACCEPTED MANUSCRIPT / CLEAN COPY The results presented here suggest that the H(Fe;Au) efficiently potentialize the radiosensitization of GBM.

For these investigations, we used the GL261 model in immunocompetent mice considered as the standard model for glioblastoma research [START_REF] Maes | Experimental immunotherapy for malignant glioma: lessons from two decades of research in the GL261 model[END_REF] . Indeed, despite some distinct features from spontaneous glioblastoma, notably the lack of characteristic histological vascularity, it shows rapid development and excellent reproducibility [START_REF] Maes | Experimental immunotherapy for malignant glioma: lessons from two decades of research in the GL261 model[END_REF] . The nano-objects that are under investigation here have the potential to provide radiosensitization and encapsulate a chemotherapy at the same time.

Hybridosome® should be considered for the release of a chemotherapy.

The standard treatment for glioblastoma is a combination of chemotherapy and external radiation therapy. In this context, we are interested in developing and characterizing the capacity of hybridosomes to combine concomitant radiotherapy and chemotherapy. Thus, in the work presented here, we wanted to characterize the ability of our hybridosomes to deliver a molecule of interest to the tumor site of injection and to evaluate its fate (residence time, circulation). For this proof of concept, we have first used hybridosomes® loaded with a fluorescent dye to model the release of a drug in the tumor environment. [START_REF] Ferrer-Font | Metronomic treatment in immunocompetent preclinical GL261 glioblastoma: effects of cyclophosphamide and temozolomide[END_REF] The in vivo fluorescence analysis of the brain shows that the dye-loaded hybridosomes® release their payload throughout the tumor area after intratumoral injection. The dye is present at least for 5 days after injection. The model dye also accumulates into the liver, with some delay. A possible explanation for the emission observed in the liver, is that a fraction of dye-loaded hybridosomes® extravasate from the tumor site into the vascular system, where they are takenup by the monocytes and conveyed to the liver. Indeed, since the hybridosomes® are ca 90 nm in diameter, they ought to be rapidly sequestered by the mononuclear phagocyte system (MPS) if they enter the bloodstream. Over this period of time, some dye also reaches the spleen and possibly the cervical lymph nodes. At the cellular level, we observed in vitro that the dye is able to diffuse into the cytosol of GL261 cells after incubation with dye-loaded H(Fe;Au), but also in vivo in the brain tumor area (cf. Figure 3D). The diffusion of the fluorescent BODIPY in the cytosol but not in the nucleus is consistent with previous fluorescence microscopy observations using a variety of encapsulated BODIPY dyes 30 . Since the capsule shell remains out of the cell 20,30 , the subcellular repartition of the encapsulated cargo depends only on its molecular properties. Thus, a specific drug may be able to enter the nucleus whereas our model dye does not. Altogether, these results are consistent with previous results, both in vitro and in ACCEPTED MANUSCRIPT / CLEAN COPY shows a significantly prolonged survival (28 days compared to 21 for the control group, *p=0.0115), whereas all other groups did not. In addition, it is also the only group for which bioluminescence intensity show a clear decay, for 3 mice over 7. One mouse of this group even showed a 78-days survival. This shows that the presence of gold is indispensable to achieve a beneficial effect.

Interestingly enough, the increase in survival rate was achieved here with very low amounts of gold. An early work [START_REF] Cho | Estimation of tumour dose enhancement due to gold nanoparticles during typical radiation treatments: a preliminary Monte Carlo study[END_REF] , based on numerical simulations, reported that an intratumoral concentration of 0.7% by weight wt/wt (i.e. 7 mg Au/g tumor) is required for a twofold dose enhancement using 140 kVp X-rays. Another numerical study suggested that a gold nanoparticle concentration of at least 0.1% is necessary to generate radiosensitization using low-energy X-rays (~100 keV) [START_REF] Roeske | Characterization of the Theorectical Radiation Dose Enhancement from Nanoparticles[END_REF] . Most in vivo experimental studies obtained significant improvements in the survival of animals using gold nanoparticles in the range of 0.1-75 mg/g tumor [START_REF] Butterworth | Physical basis and biological mechanisms of gold nanoparticle radiosensitization[END_REF][START_REF] Hainfeld | Radiotherapy enhancement with gold nanoparticles[END_REF][START_REF] Cho | Estimation of tumour dose enhancement due to gold nanoparticles during typical radiation treatments: a preliminary Monte Carlo study[END_REF] . It is important to note that in the case of intravenous injection, these quantities are determined by postmortem gold titration in the tissues. However, the proportion of nanoparticles having reached the tumor is generally less than 1%, which may lead to injecting doses that are beyond reasonable for clinical translation [START_REF] Wilhelm | Analysis of nanoparticle delivery to tumours[END_REF] . Roux et al. estimated that an injection of 8 µg/g (body weight) or less is relevant for clinical translation. Since then, some significant radiosensitizing effects were observed with gold nanoparticles at less than 5 µg/g 34- 36 . In the present study, mice were injected 0.25 µg of Au, or approximately 0.01 µg/g (body weight) associated with irradiation in the range ~ 10-100 keV, as in most reported preclinical studies. Therefore, there is an opportunity to increase the amount of gold to increase the radiotherapeutic benefit. This can be easily achieved without increasing the total amount of hybridosomes® by increasing the ratio of gold to iron oxide NP in their shell or even using pure gold hybridosomes®. Indeed, iron oxide was used here as a mean to assess the presence of the hybridosomes® at the site of injection. However, in the case of surgical application, this might ACCEPTED MANUSCRIPT / CLEAN COPY not be necessary. Note that despite the fact that the radiation enhancement is expected to be much lower at clinical radiation energies (MeV), many reports show that high-Z materials such as gold and gadolinium still have a significant dose deposition effect [START_REF] Butterworth | Physical basis and biological mechanisms of gold nanoparticle radiosensitization[END_REF][START_REF] Rancoule | Nanoparticles in radiation oncology: From bench-side to bedside[END_REF][START_REF] Mowat | In Vitro Radiosensitizing Effects of Ultrasmall Gadolinium Based Particles on Tumour Cells[END_REF] .

Iron oxide show no radiosensitization effect. It is important to note that H(Fe) did not potentiate the radiotherapy, and even possibly induced a slight deleterious effect compared to radiotherapy alone. Indeed, it contrasts with a few previous studies reporting a radiosensitization effect of iron oxide nanoparticles. [START_REF] Kirakli | Superparamagnetic iron oxide nanoparticle (SPION) mediated in vitro radiosensitization at megavoltage radiation energies[END_REF]39 This effect is not primarily related to the increase in dose deposition, as in the case of gold, but results from the iron-catalyzed production of reactive oxygen species (ROS) via the Femton or Haber-Weiss reactions [START_REF] Xie | Emerging Strategies of Nanomaterial-Mediated Tumor Radiosensitization[END_REF] . More recently, it has been demonstrated that irradiated SPION target the immunosuppressive tumor environment, and reactivate the immune defense at the tumor site [START_REF] Wu | Repolarization of myeloid derived suppressor cells via magnetic nanoparticles to promote radiotherapy for glioma treatment[END_REF] . Even if iron oxide alone shows no effect, a synergy may occur between gold and iron by combining the effect of strong dose deposition and ROS catalysis. This was observed before in the case of particles made of gold and manganese oxide [START_REF] Chen | Nanochemistry and Nanomedicine for Nanoparticle-based Diagnostics and Therapy[END_REF] . are present and visible in vivo at the tumor site for at least two months, allowing enough time for one or even several cycles of radiotherapy. In addition, we demonstrate that an encapsulated cargo could be delivered from the hybridosomes® specifically to the tumor cells.

H(Fe

MRI vs bioluminescence. In the clinic, the diagnosis is made by MRI. For preclinical studies, bioluminescence is much more convenient, provided that a Luciferase-expressing tumor model is at hand. Importantly, our comparative results show that both techniques are reasonably correlated. Some discrepancy may arise from the highly scattering nature of the brain tissues, resulting in intensity loss at the detector for the more profound tumors. In addition, when present, the SPION hinders the measurements of small tumors. The position of the mouse relatively to the bioluminescence detector is also an important factor [START_REF] Keyaerts | 16 -Bioluminescence Imaging[END_REF] . In addition, in contrast to bioluminescence, MRI may not account for isolated tumor cells which in the case of GBM, may extend several centimeters away from the main tumor.

Conclusion

The current study demonstrates that mixed goldiron oxide hybridosomes® have a real potentiating effect on radiotherapy treatment of GBM, with a significant increase of survival even for a very low amount of gold. Numerous studies (especially simulations and theoretical calculations) tend to show that the potentiating effect of radiosensitizing nanoparticles is drastically impacted by their state of aggregation and organization. [START_REF] Retif | Nanoparticles for Radiation Therapy Enhancement: the Key Parameters[END_REF][START_REF] Retif | Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles[END_REF] In hybridosomes®, the assembly of gold nanoparticles into a robust nanocapsule is certainly the key to their performance in terms of potentiating applied radiation. We are currently investigating this hypothesis in the laboratory. The decrease of tumoral activity observed for a number of mice well-responding to this treatment is extremely encouraging, as well as the long-term survival (78 days) of one individual. Since nanoparticles were still at the tumor site at this time, additional radiotherapy cycles can be considered for an improved benefit.

Moreover, while iron oxide nanoparticles were not effective to enhance the radiotherapy, they enabled particle tracking and could further be used in the clinics for image-guided radiotherapy.

In addition, cellular and in vivo studies have shown that a molecule of interest, concentrated under its nanoprecipitated form in hybridosomes®, is internalized by the cells and remains durably in the tumor.

Based on these results, we believe that gold-containing hybridosomes® have a great potential for treatments requiring combined-modality therapy, including surgery, radiotherapy and chemotherapy, as it is the case for glioblastoma. Few objects present such potentialities.

ACCEPTED MANUSCRIPT / CLEAN COPY Optimization of the gold content and combination with an encapsulated chemotherapy should further improve the benefits and enable translation of this innovative strategy into the clinics.

  Poly(ethylene glycol)-b-Poly(acrylic acid) (PEG-PAA) (MPEG = 2 kg.mol -1 ; MPAA = 7.2 kg.mol -1 ) was kindly provided by Dr G. Casterou. Tetrahydrofuran (THF, GPR Rectapur ≥99% ACCEPTED MANUSCRIPT / CLEAN COPY

  The size distribution measured by NTA in aqueous suspensions shows a main mode of the hydrodynamic diameter at 94  13 nm. The TEM analysis of the suspensions dried on a TEM grid confirms the formation of capsules of ~100 nm, containing both gold and iron oxide NP. Single AuNP (diameter 9.8  2.3 nm) are larger than single iron oxide NP (diameter 4.2  1.7 nm) and appear with a darker contrast, since TEM contrast increases with electron density (ZAu = 79, ZFe = 26, ZO = 8). A final Fe:Au composition of ca 10:1 was determined using ICP-EOS titration.

Figure 1 :

 1 Figure 1 : Hybridosomes® characterization. (A) Single Nanoparticle Tracking Analysis of a watersuspension of H(Fe;Au). (B) Transmission electron micrographs of H(Fe;Au) with arrows indicating AuNP (black) and Fe2O3 NP (grey). The mass ratio Fe:Au is ca 10:1.

Figure 2 -

 2 Figure 2 -Left: Bright-field image and confocal fluorescence microscopy of unstained GL261 cells after incubation with dye-loaded H(Fe;Au), showing diffusion of the dye in the cytosol but not in the nucleus. Right: enlargement and Z-scan. Imaged for the BODIPY green fluorescence.

  & 3C (brain and liver) and Figure SI-2 (spleen and cervical ACCEPTED MANUSCRIPT / CLEAN COPY

Figure 3 -

 3 Figure 3 -Presence of iron in the tumor, and release of encapsulated dye (BODIPY), emitting in the red and green, in the brain and liver after intratumoral injection of BODIPY-loaded H(Fe) in mice with

  GL261 brain tumor. (A) Optical microscopy images with HES/Perls stained sections of tumoral brain 5 days after the injection, showing distribution of the iron from the hybridosomes® shell. Pictures show representative results (left: non-injected; right: injection of BODIPY loaded-H(Fe)). The blue arrow indicates the localization of iron (blue staining). (B) & (C) Fluorescence imaging: brain and liver slices were stained with DAPI and imaged for DAPI (blue) and BODIPY (green+red) fluorescence. Dash lines: tumor area. (D) & (E) Enlargements of (B) and (C), respectively, at day 5. The images show that the dye is released in the cytosol.

Figure 4 -

 4 Figure 4 -Kaplan-Meier curves (left) and box plot representation (right) of mice survival with GL261 gliomas after treatment with radiotherapy and/or hybridosomes®. Intratumoral injection of H(Fe) (blue), H(Fe;Au) (red) or none (black) was achieved two weeks after the implantation of GL261-Luc+ cells, and irradiation started immediately with 2 Gy per day for 5 days (full lines: irradiated; dashed lines: non-irradiated). P values were calculated by the log-rank test. IR=irradiation.

and days 10 or 11

 11 for MRI. No measurements were achieved during the irradiation period (until day 21) to avoid repetitive anesthesia. Then, measurements were acquired every 4-5 days until death. Only albino mice could be followed by bioluminescence. All measurements are presented in Figure SI-4. Whereas the survival of mice belonging to the 3 non-irradiated groups (#1-3) rarely exceeded the irradiation period (only 2 mice out of 18), it is clear from bioluminescence measurements that in the groups receiving irradiation (groups 4-6) several ACCEPTED MANUSCRIPT / CLEAN COPY

Figure 5 -

 5 Figure 5 -Log-Log representation of the bioluminescence intensity vs MRI measurement of tumor volume, for albino mice over the survey.Bioluminescence and MRI are complementary techniques for the monitoring of tumor growth.Bioluminescence provides a measurement of the activity of the tumoral cells. It is rapid and cost-effective, but cannot be applied in the clinics. MRI is an imaging technique giving detailed morphological information on the tumor. However, the distinction between inflammation and tumor itself is not always straightforward. Since few studies present MRI and bioluminescence data simultaneously, we took advantage of this large set of data to check the correlation between MRI and bioluminescence measurements. Figure5shows a Log-Log representation of bioluminescence intensity vs tumor volume measured from MRI. It appears that the data follow roughly a straight line of slope 1, which indicates that the volume (from MRI) is positively correlated to bioluminescence intensity. The discrepancy is more important for small tumor volumes (< 10 mm 3 ). This might be due to the hyposignal of the iron oxide NP, masking the tumor contrast.

  Figure SI-3). A large tumor is clearly visible on HES stained slices, consistently with MRI and bioluminescence observations. Moreover, at day 78, Perls staining confirms the localization of iron at the upper edge of the tumor, as seen by MRI. It also confirms that iron from the H(Fe;Au) is still present even two months after intratumoral injection.

Figure 6 -

 6 Figure 6 -Case study. At day 14 after brain implantation of GL261-Luc+ cells, the mouse 1082 underwent intratumoral injection of H(Fe;Au) and was treated by irradiation for one week. (A) Bioluminescence signal from the GL261-Luc+ tumor. (B) MRI of the brain. Day 10 is before injection of hybridosomes®, all other images are after injection of the hybridosomes® and show the hypointense signal from the magnetic iron-oxyde NP.

  Goubault et al., Nanomedicine : NBM 40 (2022) 102499 Accepted October 30, 2021. https://doi.org/10.1016/j.nano.2021.102499 Submitted version available herein 4

  Goubault et al., Nanomedicine : NBM 40 (2022) 102499 Accepted October 30, 2021. https://doi.org/10.1016/j.nano.2021.102499 Submitted version available herein 8

  Goubault et al., Nanomedicine : NBM 40 (2022) 102499 Accepted October 30, 2021. https://doi.org/10.1016/j.nano.2021.102499 Submitted version available herein 11

Table 1 -

 1 Description of the different mice groups and the associated treatments.

	Group treatment	Number of mice
	Group 1: tumor -no treatment (control)	12
	Group 2: tumor + H(Fe)	8
	Group 3: tumor + H(Fe;Au)	9
	Group 4: tumor + radiotherapy	12
	Group 5: tumor + H(Fe) + radiotherapy	11
	Group 6: tumor + H(Fe;Au) + radiotherapy	13

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Goubault et al., Nanomedicine : NBM 40 (2022) 102499 Accepted October 30, 2021. https://doi.org/10.1016/j.nano.2021.102499 Submitted version available herein 14

  Goubault et al., Nanomedicine : NBM 40 (2022) 102499 Accepted October 30, 2021. https://doi.org/10.1016/j.nano.2021.102499 Submitted version available herein 20

	Intratumoral administration after surgery is appropriate for hybridosomes®-based therapy of
	GBM. We believe that these results are encouraging in the context of postoperative radiotherapy
	combined with chemotherapy, which is the case for standard of care for GBM. Indeed, the blood
	brain barrier (BBB) has remained an impassable obstacle for most chemotherapies and
	radiosensitizing agents. Therefore, alternative options are convection assisted delivery (CVD)

;Au) associated with irradiation can induce long-term survival of brain tumor-bearing mice: a case study. A careful investigation of the long-term surviving mouse treated with both radiotherapy and H(Fe;Au) was particularly interesting. After radiotherapy, the bioluminescence intensity decreased continuously during 20 days. Then, from day 39, it started increasing again, first slowly then bursting, leading finally to the death on day 78. One can reasonably hope that an additional radiotherapy approximately at day 40, that is 20 days after the end of the first treatment, would have further improved the survival of this individual. This would have not required a new injection of radiosensitizing materials, since MRI observations confirmed by histology show that the hybridosomes® were still at the tumor site. and local administration of sustained released chemotherapy, embedded in polymer matrixes such as Gliadel®. Deposition of a radiosensitization agent during surgery is a particularly advantageous option. Our results show that the nanoparticles constituting the nanocapsule shell ACCEPTED MANUSCRIPT / CLEAN COPY

  Goubault et al., Nanomedicine : NBM 40 (2022) 102499 Accepted October 30, 2021. https://doi.org/10.1016/j.nano.2021.102499 Submitted version available herein 21

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Supplemental Figures

Figure SI-1 -Initial tumor size distribution (day 9/10) within the 6 groups of mice. The inner walls in the boxes represent the median. The lower and upper walls of the boxes represent respectively the 1 st and 3 rd quartiles. Lower and upper ticks represent the 1 st and 9 th deciles.

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Sabri Khssibi
email: khssibi@irit.fr

Adrien Van Den Bossche

Thierry Val
email: val@irit.fr

Hanen Idoudi
email: hanen.idoudi@ensi.rnu.tn

Leila Azzouz Saidane
email: leila.saidane@ensi.rnu.tn

Leila Azouz Saïdane

Optimization of IEEE 802.15.4: Overview, Theoretical Study and Simulation

Keywords: Wireless Sensor Networks, IEEE 802.15.4, QoS algorithms, MAC protocols, CANet project

In this paper we study, through theoretical analysis and simulation, the impact of Beacon Order (BO) and Superframe Order (SO) parameters of IEEE 802.15.4 on the networks performance and we investigate their optimal values for different classes of traffic. The traffic is dimensioned according to the requirements of the CANet project in which a cane becomes a mean of communication and a surveillance system embedding several sensors to monitor the elderly health and environment(voice, pressure, temperature, etc.). The cane's sensors impose different QoS constraints. Depending on the expected throughput, a sensor's traffic will fall within one of three classes that we defined. Therefore, in order to ease the understanding of our optimization, we introduce a classification scheme which applies to the existing quality of service algorithms. We derive by theoretical study the optimal values of BO and SO that should be used to fit each traffic class QoS requirements and we validate our results by simulation.

University of Toulouse, where he currently teaches networks and computing systems. He obtained his HDR in 2002.He is now a professor for the University of Toulouse at the Blagnac Institute of Technology. He was assistant director of the LATTIS laboratory, where he managed a research activity on wireless local networks and related protocols. He is now a member of IRIT-CNRS laboratory of Toulouse in IRT team. His research focuses on wireless networks.

Hanen Idoudi earned her engineering and master degrees in computer science at the National School of Computer Science, University of Manouba, Tunisia in

Introduction

Wireless Sensor Networks (WSNs) are composed of autonomous sensors to monitor physical or environmental conditions. They can be used in many applications such as health care monitoring, forest fire detection, environment surveillance and monitoring, etc.

Traditional applications of WSNs rely often on homogeneous sensors, having the same characteristics and requirements and performing the same tasks which leads also to common traffic characteristics. Health care applications came with new requirements and new architectures. Various types of sensors can be used within the same application to monitor several physical parameters. For instance, sensors can be embedded on a same patient's body to monitor his blood pressure, cardiac rhythm, movements, fall detection, etc. All these sensors compose the same wireless network but generate different traffics at different rates and periodicity.

Many WSN applications need to ensure that the detected information successfully arrive to their destinations and that it is delivered in a timely manner. In health care applications, the information collected by sensor nodes can be critical when reporting on serious situations, thus, these applications do not tolerate any packets loss or important transmission delays [START_REF] Yigitel | QoS-aware MAC protocols for wireless sensor networks: A survey[END_REF].

For this kind of constrained communications, protocols supporting Quality of Service (QoS) algorithms are required. In order to evaluate the QoS requirements of WSNs, authors of [START_REF] Yigitel | QoS-aware MAC protocols for wireless sensor networks: A survey[END_REF][START_REF] Chen | QoS support in wireless sensor networks: a survey[END_REF] define some metrics such as access delay, collision rate, etc. that can be measured at MAC layer.

CANet [START_REF] Bougeois | Le projet CANet : une activité pluridisciplinaire liant recherche et pédagogie[END_REF] is one of the innovative health care projects which aimed at designing an intelligent cane to monitor, in a non-intrusive way, the environment and health of the elderly in their everyday life. The cane embeds different types of sensors, such as for localization, temperature, movement tracking, or monitoring of different vital signs of old persons. All these sensors have to be implanted on the same cane, which communicates with an access point that plays the role of the network coordinator. The cane is equipped with a single wireless interface that has to serve all types of traffic generated from the embedded sensors.

The choice of a MAC protocol that satisfies a certain level of QoS and that can be flexible and adjustable to the cane requirements (regarding the heterogeneity of the generated traffic) is fundamental. In addition to these QoS requirements, ensuring low energy consumption is important since the cane will operate on battery.

As IEEE 802.15.4 is a widely used standard for WSN, we considered its application within the CANet project. To cope with the different constraints (delay, throughput, etc) of the cane-embedded sensors, we perform in this paper a theoretical and experimental study of different IEEE 802.15.4 parameters that can influence the length of the superframe period and the inter-beacon period in IEEE 802.15.4 protocol within the beacon enabled mode and the star topology.

First, we will present an overview of IEEE 802.15.4, where we explain the important parameters to calculate the length of superframe and the CSMA algorithm for the slotted period. Second, we will propose a classification for the existing QoS mechanisms in WSNs. Third, we will define a classification of traffic types that can exist in WSN, especially in CANet project. After that, we will present a theoretical study of the parameters used to vary the duration of the superframe (SO: Superframe Order) and the duration between two beacons (BO: Beacon Order) and we will finish by presenting some results of simulations.

2 Theoretical choice of BO and SO parameters 2.1 Overview of IEEE 802.15.4 standard IEEE 802.15.4 standard (Kim et al., 2007) defines the specifications of the MAC sub-layer and the PHY layer for Low-Rate Wireless Personal Area Networks (LR-WPANs). It defines two types of nodes: Reduce Function Device (RFD) and Full Function Device (FFD). RFD nodes do not implement the entire stack of IEEE 802.15.4 and have limited functionalities. On the other hand, the FFD nodes implement all the IEEE 802.15.4 specification and they can be networks coordinators.

In IEEE 802.15.4, two types of architecture are defined: Star or Peer to Peer. In the star topologies, all nodes are connected to one coordinator, which is responsible for synchronizing all nodes, allocating the Guaranteed Time Slots (GTS) and the beacon transmission. The star topology is the one chosen for our application.

Two different modes of transmission are possible: non-beacon-enabled and beaconenabled modes. In non-enabled-beacon mode, all nodes in the network use CSMA/CA access mechanism without any synchronization superframe. In the rest of the paper, we will focus only to the enabled-beacon mode, because it is used with star topologies. In this mode, a beacon is transmitted, by the coordinator, at the beginning of each superframe to synchronize all nodes. This superframe is divided into two periods: active and inactive period. The active period consists of 16 slots having an equal duration and it is composed into two parts: Contention Access Periods (CAP) and Contention Free Periods (CFP). In the CAP, the nodes use CSMA/CA access mechanism. In the CFP, only GTS are defined and has to be reserved in advance. If a node needs to reserve GTS in the CFP part, it has to send a request to the coordinator. When the coordinator receives the request, it verifies if there are free GTS in the CFP period and then it satisfies accordingly the requesting node. Therefore, the node can transmit its messages in the reserved slots by using TDMA (Time Division Multiple Access). The interval between two beacons is named Beacon Interval (BI) and represents the total duration of the superframe (figure 1). This parameter is calculated by:

BI = aBaseSuperf rameDuration × 2 BO [Symbols] (1)
With aBaseSuperframeDuration is equal to 960 symbols and BO is the Beacon Order and it is 0 ≤ BO < 15. The active period is named Superframe Duration (SD) and it is calculated by :

SO = aBaseSuperf rameDuration × 2 SO [Symbols] (2)
With 0 ≤ SO ≤ BO ≤ 14 Now, we will describe how the CSMA/CA operates in the enabled-beacon mode. In the first step, the parameters NB (represents the number of attempts to access to the channel) is set to 0 and CW is set to 2. If the node operates with the battery power, the backoff exponent is set to a min (2, MacMinBE). In the other cases, the backoff is set to MacMinBE (the default value of MacMinBE is 3). After that, the algorithm locates the backoff period boundary.

In the second step, the algorithm generates a random period between 0 and 2 BE-1 . This random value represents the waiting delay before attempting to transmit packets.

After the expiration of the waiting period, the MAC sub-layer performs a Clear Channel Assessment (CCA) procedure (step 3). After this step, the Mac sub-layer verifies the state of the channel:

• If the channel is idle, the algorithm decreases the value of CW by 1. Then the CSMA/CA algorithm verifies if the value of CW is equal to 0, the node can transmit its packets.

In the other cases, the algorithm returns to the step 3.

• If the channel is used, CSMA/CA algorithm would set CW to 2 and increase NB by 1 (step 4). If the value of NB is greater than macMaxCSMABackoff , the packet cannot be transmitted. In the other case, the algorithm returns to the step 2 and tries again.

In an IEEE 802.15.4 WSN, the coordinator ensures some QoS by allocating GTS in the CFP part of the superframe. The coordinator cannot provide more than 7 GTS which is not sufficient for dense WSN. For this reason, many existing work tried to propose QoS mechanisms in enabled-beacon mode by using CSMA/CA. In another hand, other researches try to improve the GTS reservation method.

QoS in Wireless Sensor Networks

Many applications in WSNs require a minimum level of transmissions reliability. To satisfy this requirement, many QoS algorithms were proposed. In this section, we classify existing QoS algorithms then we define traffic types in CANet project based on their QoS needs. • Priority based differentiation: priorities may be assigned to nodes according to the importance of the information they handle or to classify the generated traffic (Shin, 2013;[START_REF] Severino | A Traffic Differentiation Add-On to the IEEE 802.15.4 Protocol: implementation and experimental validation over a real-time operating system[END_REF][START_REF] Saxena | Dynamic duty cycle and adaptive contention window based QoS-MAC protocol for wireless multimedia sensor networks[END_REF][START_REF] Firoze | PR-MAC a priority reservation MAC protocol for wireless sensor networks[END_REF].

Classification of QoS algorithms

• Access parameters differentiation: different MAC layer parameters like CW, backoffexponet and SIFS are tuned for different levels of priority. The aim is to expedite the transmission of packets that have a high priority [START_REF] Xia | Service Differentiated and Adaptive CSMA/CA over IEEE 802.15.4 for Cyber-Physical Systems[END_REF][START_REF] Severino | A Traffic Differentiation Add-On to the IEEE 802.15.4 Protocol: implementation and experimental validation over a real-time operating system[END_REF]Kim et al., 2007;Youn et al., 2007;[START_REF] Koubaa | Improving the IEEE[END_REF][START_REF] Tae | Priority-based delay mitigation for event-monitoring ieee 802.15.4 lr-wpans[END_REF].

• Controls parameters differentiation: This class contains the QoS mechanisms that use parameters such as hop count, life-time of a packet and power control to manage the transfer of packets in the network. In this proposals, these parameters are used to differentiate between the existing traffics and to assign priorities [START_REF] Yigitel | QoS-aware MAC protocols for wireless sensor networks: A survey[END_REF][START_REF] Nguyen | A prioritized MAC protocol for multi-hop, event-driven wireless sensor networks[END_REF][START_REF] Liu | An energy-efficient QoS-aware media access control protocol for wireless sensor networks[END_REF].

GTS sub-class includes algorithms which are proposed to resolve the problem of GTSs reservation in IEEE 802.15.4. This sub-class is divided into 3 parts :

• Allocation based on requests order : The coordinator reserves slots times to the nodes according to the order of their requests reception. If a node wants to reserve GTSs, it has to send a request to the coordinator, which contains the number of desired slots and the direction of the exchange (reception or transmission). Upon a request reception, the coordinator compares the number of requested GTSs with the number of available slots in the CFP period. If the number of requested slots is lower or equal to the number of available slots, the coordinator allocates the necessary slots to this node. In the other case, the coordinator rejects the request.

• Allocation based on the dynamic priority of nodes : GTS reservation depends to the priority assigned to each node. In [START_REF] Huang | An Adaptive GTS Allocation Scheme for IEEE 802.15.4[END_REF], this priority changes dynamically according to the use of last reserved GTS. The priority change is followed by the reallocation of GTS in the network. The algorithm in [START_REF] Huang | An Adaptive GTS Allocation Scheme for IEEE 802.15.4[END_REF] does not support any traffic differentiation. To meet this need, other protocols such as D-SeDGAM (Villarverde et al., 2010) allow the differentiation between services.

This class suffers from several limits. For instance, if many nodes have a strong priority, they will monopolize the bandwidth. Also, this class does not take into account realtime traffics.

• Allocation based on traffic priority : In this third class, GTS allocation is adapted to real-time traffics. In the initial structure of IEEE 802.15.4 superframe, when a node wants to transmit data during CFP, it must send a GTS request and wait for the beacon. If the request was accepted, the node will transmit the packets only in the allocated period, which makes the current structure of the superframe inadequate to support the transmission of real-time data. In (Kim et al., 2007), the authors propose a new reservation algorithm based on an extension of the IEEE 802.15.4 GTS concept. They suggest to eliminate the inactive period, then SD becomes equal to BI. Other modifications are proposed in the superframe structure. Therefore, it supports the concept of multi-user at the time of communication.

This class does not take into account the energy consumption and allows the treatment of only one type of traffic.

Algorithms proposed in this classification do not use the length of the information that will be sent in the GTS period. Therefore, the authors of [START_REF] Khssibi | Study and proposal of an optimized scheduling guaranteed time slots in WPAN 802[END_REF]; [START_REF] Khssibi | Classification des techniques d'allocation de GTS de la norme IEEE 802[END_REF]) defined 3 algorithms that use the number of requested GTS in the reservation process :

• FGA (FIFO GTS Allocation) : In this algorithm, the GTS reservation is performed according to the reception order of the GTS requests.

• MFGA (Min First GTS Allocation: MFGA) : This algorithm is an enhancement of FGA algorithm. In this algorithm, the highest priority is assigned to the packet that has requested the lowest number of slots.

• MWGA (Mean Weighted GTS Allocation) : In this algorithm, authors propose to balance the access to the channel between nodes by reserving a number of slots that is proportional to their needs.

We focus on the differentiation between existing traffics in the network which should be based on the type and the importance of the transmitted information. For that, we will analyze the characteristics of the generated traffics in CANet project.

Traffic types in CANet

In CANet project, there are many types of sensors used to collect information from the human body and the environment such as heart bit, skin temperature, accelerometer, localization, velocity sensors also a microphone for voice transmission in case of emergency. These sensors generate data with different characteristics (bit rate, priority and periodicity). The bit rate represents the number of bits transmitted from the node to the coordinator. It can be divided into Low and High bit rate. The traffics priority, in CANet project, depends on the type of information. For that, we define 3 priority levels. At last, the detected information can be sent periodically or randomly. The transmission frequency depends on the characteristics of the detected information.

A sensor in the monitoring applications like CANet project can generate and transmit information that belongs to one of the flowing classes :

• Class 1 : In this class, traffics have low priority and low bit rate and they are generated periodically or randomly. The detected information is transmitted using CSMA/CA in the CAP period. This class represents the traffic generated by sensors like skin temperature, heart rate, etc.

• Class 2 : This class contains all traffics characterized by high bit rate and high priority. These traffics will be transmitted continuously. This class represents the real-time traffics generated by the microphone embedded on the cane.

• Class 3 : this class contains all traffics characterized by low flow, very high priority and generated randomly. The detected information is very important because it represents an urgent case. Therefore, it should be sent as soon as possible. The traffics in this class are generated by heart rate, skin temperature sensors in emergency cases to report on critical health states.

To comply with the requirements of each type of traffic, using the optimal values of IEEE 802.15.4 parameters is necessary. BO and SO are the most significant parameters that can affect both bit rate and delays constraints. However, there are no former works that have focused on studying the impact of these parameters on the performances of IEEE 802.15.4 and its ability to meet QoS needs of various types of traffic.

Hence, our goal is to perform a study on the BO and SO parameters in order to determine the optimal values that can characterize different types of CANet traffics.

Analysis of BO and SO

In this section, we will investigate the impact of BO and SO on the network performances such as theoretical throughput, superframe duration, etc. Our goal is to find the optimal values of BO and SO parameters. For that, we use the star topology with enabled-beacon mode of IEEE 802.15.4. The selected values will allow the classification of traffics and satisfy the requirement of all types of traffic.

We calculate the Theoretical Instantaneous Flow (TIF) by:

T IF = SD BI Symbols = 1 2 BO -SO × 250Kbit/s (3)
The figure 3 is created by the use of the equation (3). It represents the theoretical instantaneous flow variation for different BO and SO values. If BO and SO are equal to 14 the theoretical instantaneous flow is equal to 250Kbit/s, in this case, the maximal value of flow can be achieved. If the values of BO and SO increase, the theoretical instantaneous flow increases. Vice versa, if BO and SO decrease the value of theoretical instantaneous flow decreases. In the figure 4, the superframe has the largest duration and the highest theoretical instantaneous flow as BO = SO = 14. In addition, if the values of BO and SO are equal and different of 14, the superframe has lowest duration and the highest theoretical instantaneous flow. In the other cases, when the BO -SO is larger, the superframe duration and the theoretical instantaneous flow are shorter (Figure 5) and an inactive period appears. The length of the inactive period is calculated by:

InactiveP eriod = BI -SD = 960 × (2 BO -2 SO ) × 16 × 10 -6
(4)

Figure 6 represents the variation of inactive period in terms of BO -SO and BO. The SO value is varying from 0 to BO. If SO value is equal to 0, the inactive period length is equal to the length of the beacon interval. In other cases, the length of the inactive period decreases when the value of BO -SO increases. Then the length of the inactive period depends essentially on the value of SO.

We derive from the previous figures the theoretical optimized values of BO and SO for the different traffic classes presented in the section 3. These values are represented in Table 1. For class 1 traffics, the choice of BO and SO values is not important because the nodes can send their information at any time in the CAP. The period length between two frames successively transmitted by the same node is very large. For that, we intend to maximize the inactive period length and minimize the active period length. In the same time, we should ensure to have the necessary period for transmission. If BO and SO values are less than 7, the inactive and the active period are very short. For BO = 6 and SO = 0, the inactive period is equal to 0,967s and the active period is equal to 15,36ms, and for BO = SO = 6 the active period is equal to 0,983s. For these reasons, we should fix 7 as the lowest value for BO = SO to have the shortest length of the active period equal to 1,966s. 0,1 ,2 , 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 In class 2, the length of packets is between 20ms and 30ms. For the real-time traffics, the end-to-end delay has an important influence on the QoS. For that, we will remove the inactive period to minimize the delays (BO = SO). This class requests a minimum level of QoS, its traffics will be transmitted in CFP. The length of active period will be very small and does not exceed the length of packets generation.

Class 3 covers high priority traffics that must be transmitted in the CFP or CAP periods. The choice of BO and SO values is not important if a packet is timely transmitted.

Table 1 presents the different values of BO (Column 1) and SO (Column 2) that should be used for different classes. These values are the result of our theoretical analysis. We propose in the next section to assess these results by simulation and refine the theoretical proposition.

Simulations and Results

In this section, we present the simulations of GTSs allocation in IEEE 802.15.4 while varying the values of BO and SO. These simulations aim at validating the results derived from our previous theoretical analysis.

Two scenarios were simulated with different BO and SO values and different number of nodes. We used the implementation of IEEE 802.15.4 in the OMNeT simulator (OMNet++, 2010) with star topology containing one coordinator and several nodes. The BO and SO values vary between 0 and 14. The number of nodes is equal to 1, 5 and 10. The application packet inter-arrival time is equal to 30ms or 60s and the application payload size is equal to 70 or 10 Bytes.

In the first scenario, we will try to observe the influence of BO and SO variation on the number of transmitted messages in the second class traffics. The number of slots that a node can reserve depends on the length of the first message to transmit. The number of reserved slots is maintained until the end of the simulation. Parameters used for the first scenario are presented in Table 2.

Figure 9 presents the number of successfully transmitted messages in the CFP with GTSs. We note that the number of transmitted messages decreases when BO and SO values increase. The maximal number of transmitted messages is reached when BO = SO = 0 for 1 node and BO = SO = 1 for 5 nodes.

The raise of the number of successfully transmitted messages in BO = SO = 1 for 5 nodes is the result of the slots length increases. Figure 7 illustrates the change of the slots number reserved by each node. For BO = SO = 0 the slots number which is necessary for the transmission is equal to 4 slots for each node. For that, only two nodes can transmit their messages. Vice versa, when BO = SO = 1, the slots length becomes larger. For that, the necessary slots numbers decreased by 2 for each node and by 2 for the minimal CAP length. The unused slots are reserved to other nodes (figure 7 (a) and (b)). If the superframe duration increases, the waiting time for the next transmission period increases for each node. For example, if BO = SO = 14, SD becomes equal to 251,66s. Therefore, all nodes must wait 251,66s to achieve their transmission period (figure 8 and figure 7 (c)). From the beginning of the superframe, nodes have generated 8367 messages, but only 10 first packets are conserved and 8357 were dropped. For that, the number of successfully transmitted messages decreases when SD increases. We note in the figure 9 that we have a similar number of transmitted messages for BO = SO = 2, 3, 4, and 5, the superframe length for these values is successively equal to 61,44ms, 122,88ms, 245,76ms and 491,52ms. In one superframe, the node generates 1, 4, 8 and 16 messages and the slots´length is equal to 3,84ms, 7,68ms, 15,36ms and 30,72ms, For these BO and SO values, nodes can transmit only half of generated messages. After some time the buffer will be filled and starts to reject messages.

Finally, the BO and SO optimal values for this class are BO = SO = 0 for 1 node and BO = SO = 1 for 5 nodes.

In the second simulation, we changed the parameters to adapt them to the characteristics of the first class. The parameters for the second simulation are given in Table 3.

With this configuration, if BO = SO, the number of successfully transmitted messages is equal to 100%. It is not influenced by the BO and SO variation because traffics are not heavy.

Parameters

Values Application packet inter-arrival time 60s BO 0, 1,2,3,4,5,6,7,8,9,10,11,12,13 and 14 SO 0,1,2,3,4,5,6,7,8,9,10,11,12,13 In this class, the sensors have a message to transmit every 60s. For this reason, the use of small BO and SO values is not a good solution. If we use the high BO and low SO values, we can enlarge the inactive period to minimize the energy consumption for each node. In one hand, the maximal superframe duration is equal to 251,65s for BO = SO = 14 and the maximal inactive period length is equal to 251,64s for BO = 14 and SO = 0. On the other hand, a compromise between the number of successfully transmitted messages and energy saving must be found. In figure 10, the number of successfully transmitted messages without acknowledgement (ACK) for SO = 2 is greater than the number of successfully transmitted messages with ACK because when a node transmits a message requiring an ACK, it has to wait to receive this ACK for a fixed delay. If the node does not receive the ACK, it will retransmit the message. In this case, the same message is sent at least for 2 times while the SD length is not very large, then the node cannot manage to retransmit the old one and transmit new messages in the same SD. If the use of ACK is deactivated, nodes transmit their messages and do not wait the reception of the ACK.

When SO = 3, the ratio of successfully transmitted messages with ACK is greater than the ratio of successfully transmitted messages without the ACK. This is explained by the fact that for BO ≥ 3, the number of collisions is reduced and nodes have a sufficient period for retransmitting and transmitting the messages. If the SD length increases, nodes have more chance to transmit their messages. Also, if the number of nodes increases, the ratio of successful messages decreases because of the collisions. For that, if the number of nodes increases, the SD length must increase then the SO value must increase as well.

In our theoretical study, we fixed the minimum SO value at 7 to ensure that we have a minimum length of active and inactive periods. Our goal is to find the optimal BO and SO values that increase the number of successfully transmitted messages and help nodes to save energy. After these simulations, we can deduce that any values in the interval [7,14] with requirement of ACK can be used.

Finally, we do not simulate the last class for two reasons. The first reason, nodes do not need to transmit their messages periodically. Therefore, the generated traffic is low and do not have an important influence on the network performances. Secondly, in the classical case, only one node can trigger the emergency phase, in CANet project.

In this part, we simulated transmissions in different periods: CFP and CAP. We configured the network with parameters adapted to each class of CANet traffics. We validated, by simulation, the different values of BO and SO that we derived in our theoretical study. Finally, we can recommend these values to use in WSN applications where generated traffics comply with the classes defined in this paper.

Conclusion

The technological advances allowed the application of sensor networks to e-health innovative solutions. In these solutions, several QoS constraints have to be tackled. Within the CANet project, we deal with the problem of combining several types of sensors generating different traffic patterns. In this paper, we investigated the use of IEEE 802.15.4 MAC protocol in this context and its ability to adapt to different traffic types by tuning its BO and SO parameters.

In the first part, we presented an overview of IEEE802.15.4 and its main parameters. After that, we presented our classification of existing QoS mechanisms. At the end of this part, we have classified the different types of generated traffic in CANet project into 3 classes based on their priority. In next parts, our main goal was to conduct a theoretical and experimental study to determine the optimal values that we should use to meet the requirements of each type of traffic generated by the sensors cane.

Our study demonstrated that the first class does not have any QoS constraints and the transmitted messages number is not important. For that, we aimed to find a configuration that ensures the successful reception of an acceptable rate of transmitted messages and that reduces energy consumption by increasing the inactive period. After our simulation and theoretical study, we noticed that the optimal values of BO and SO should be in the interval [7][8][9][10][11][12][13][14].

Moreover, the second class covers real time traffics, thus, we had to look for optimal values that ensure a maximum number of successfully transmitted messages. Two steps were necessary to find the optimal values. Firstly, we removed the inactive period by setting BO = SO. Secondly, we have studied theoretically and by simulation the variation of the number of successfully transmitted messages for different BO and SO values. In the theoretical study, we found that the optimal value must be in the interval [0-1]. This result was verified and refined by simulation. The optimal values are: BO = SO = 0 for one node with 100% of successfully transmitted messages and BO=SO=1 for 5 nodes with 97% of successfully transmitted messages.

In our future work, we aim to define a new mechanism for traffic differentiation in CANet project. This mechanism should adapt dynamically the BO and SO parameters according to the traffic characteristics. We will also analyze the effect of BO and SO variation and the necessary period to return to the stable state as defined by the requirements of CANet project.

Figure 1

 1 Figure 1 Superframe structure in IEEE802.15.4

Figure 2

 2 Figure 2 Classification of QoS algorithms

Figure 3 Figure 4

 34 Figure 3 Instantaneous throughput in terms of BO and SO

Figure 5 14 Figure 6

 5146 Figure 5 Variation of superframe duration in terms of SO and the instantaneous throughput with BO = 14

Figure 7

 7 Figure 7 Transmission for BO = SO = 0, 1 and 14

Figure 8 Figure 9

 89 Figure 8 Periodic transmission time for BO = SO = 14

Figure 10

 10 Figure 10 Successfully transmitted messages in CAP with BO = 14

Table 1

 1 Different values of BO and SO for the different classes

	Parameters	Values
	Application packet inter-arrival time	30ms
	BO = SO

Table 2

 2 Simulation parameters for the second class

	and 14

Table 3

 3 Parameters of the second simulation

Sabri Khssibi is currently