Anja Olafsen

C Daniel

Y Schuurman

L B Råberg

Unni Olsbye

Claude Mirodatos
email: mirodatos@catalyse.cnrs.fr

L B Ra ˚berg C

Light alkanes CO2 reforming to synthesis gas over Ni based catalysts

Keywords: Methane, Propane, TEOM, TPH, Magnetic measurements, Dry reforming, Coke formation

Introduction

Crude natural gas may contain in addition to methane ca. 10 vol.% of light alkanes (C 2 -C 4 ) and up to 30 vol.% of CO 2 .In order to convert it into syngas via reforming reactions without prior separation [in view of a Gas To Liquid (GTL) process], an overall understanding of both CH 4 and higher alkanes dry reforming mechanisms is required for developing catalysts with a high activity and selectivity towards CO and H 2 , a high stability and a low selectivity to coke formation.

While numerous articles exist on the catalytic dry reforming of methane to synthesis gas, especially for nickel based catalysts [START_REF] Pinaeva | Environmental Challenges and Greenhouse Gas Control for Fossil Fuel Utilization in the 21st Century[END_REF], only few studies address the specificity of propane dry reforming, in general using supported noble metal catalysts (Rh, Ru) [START_REF] Solymosi | [END_REF]3]. Recently, we extended our prior studies of methane dry reforming over Ni based catalysts towards propane dry reforming [4]. In this work, it is attempted to compare methane and propane CO 2 reforming on two types of Ni based systems; one reference Ni/SiO 2 system and a Ni/Mg(Al)O hydrotalcite-derived catalyst, which was shown previously to display high catalytic stability for a long term reforming period [4].

After comparing the catalytic stability for the two systems toward the two feed gases (methane and propane), it is attempted to understand the carbon deposition processes and the specific role of each carbon deposit for the catalytic cycle as well as for the ageing process. The Tapered Element Oscillating Microbalance (TEOM) and Temperature Programmed Hydrogenation (TPH) under proper reaction conditions is used to quantify the various amounts of carbon deposits and Transmission Electron Microscopy (TEM) and magnetic measurements give indication on the state of the nickel phase along these processes. From these investigations, focussed on carbon deposits, the specificity of the hydrotalcite based system is outlined.

Experimental

Catalysts

The Ni/Mg(Al)O catalyst was prepared by synthesis of the corresponding hydrotalcite-like material with nominal composition Mg 5.88 Ni 0.12 Al 2 (OH) 16 CO 3 ÁnH 2 O and (Mg + Ni)/ Al = 3.0, followed by calcination and reduction in a flow of 10 vol.% H 2 /Ar, as reported in detail in ref. [4]. The BET surface area of the calcined material kept under inert conditions was 259 m 2 /g for sieved fraction of grain size 0.2-0.3 mm [4]. The metal loading of Ni/Mg(Al)O was determined to be 1.8 wt.%.

Ni/SiO 2 was synthesized by calcining SiO 2 -40 (Fluka, grain size 0.2-0.3 mm) at 825 8C for 10 h (giving a specific surface area of 164 m 2 /g) before impregnating it with an aqueous solution of nickel nitrate. After impregnation, the product was dried overnight at 100 8C and calcined at 750 8C for 8 h in air. The metal loading was determined to be 1.8 wt.%. Ni/SiO 2 used for the TEOM (TPH) and magnetic measurements was activated (and then passivated) by a second heating to 650 8C in a fluidized bed reactor for 14 h in an atmosphere of 10 vol.% H 2 /Ar, cooled to ambient temperature in the same atmosphere before the nickel metal surface finally was passivated by passing 2 vol.% O 2 /N 2 over the material for 1 h. The specific surface area of the passivated Ni/SiO 2 catalyst was 100 m 2 /g [5]. Ni/SiO 2 used in the stability tests were activated in a 10 vol.% H 2 /Ar flow in situ at 650 8C for 14 h.

Catalytic reforming conditions

Long term activity and stability tests were performed in a quartz tubular reactor (i.d. 6 mm). The test temperature was measured with a thermocouple placed axially in the reactor inside a quartz thermocouple well (o.d. 3 mm). For Ni/SiO 2 and Ni/Mg(Al)O the catalytic bed height was 2.7 and 3.8 cm, respectively. The temperature gradient over the bed under reforming conditions was less than 2 8C. Duration times of the ageing tests were 8000-10,000 min (130-170 h), with a total gas flow rate of 55 N ml/min and with 0.45 g catalyst (WHSV = 7300 ml/h g cat ). Gas compositions (in vol.%) were: CH 4 :CO 2 :N 2 = 10:10:80 and C 3 H 8 :CO 2 :H 2 :N 2 = 10:30:10:50. When using propane as fuel, hydrogen was added to the feed to maintain the degree of Ni reduction and improve the catalyst performances.

The reactor effluent was analyzed by on-line gas chromatographic (GC) analysis (Agilent micro-GC equipped with three columns).

TEOM studies

Reaction, coke deposition, and regeneration by temperature programmed hydrogenation were carried out in a Rupprecht & Patashnick TEOM 1500 pulse mass analyzer. It consists of a microreactor with a high-resolution microbalance that generates real-time measurements of mass changes during gassolid reactions [6][7][8]. The TEOM measures mass changes based on inertial forces, presenting key advantages over conventional gravimetric microbalances: (i) a well-defined flow profile, eliminating possible (heat and mass) diffusion and buoyancy phenomena, (ii) a very fast response time resolution (0.1 s), and (iii) a high mass resolution across the entire range of pressure and temperature.

The TEOM reactor was loaded with 72 mg of catalyst (sieve fraction 0.2-0.3 mm), firmly packed between two plugs of quartz wool. Prior to experiments the passivated catalysts were activated by a flow of 10 vol.% H 2 /Ar using a ramp of 10 8C/ min from room temperature up to 600 8C. When stable baseline was reached, Ar was replaced by the reaction mixture, and mass changes and product gases were continuously monitored. In addition to reaction mixture of 16 N ml/min, purge flow of 20 N ml/min (Ar) was used and the feed gases were preheated at 250 8C. The CH 4 and C 3 H 8 reforming by CO 2 were carried out at 600 8C at a total pressure of p = 1 atm and a weighthourly space velocity (WHSV) of 13,300 ml/h g cat . Gas compositions (vol.%) were CH 4 :CO 2 :Ar = 10:10:80 and C 3 H 8 :CO 2 :H 2 :Ar = 10:30:10:50. The coke content was determined from the mass change measured during reaction, accounting for the mass change caused by the change of the gas density in the tapered element when Ar was replaced by the C x H y (+H 2 )+CO 2 + Ar mixture.

The product gases were analysed by an on-line micro-GC (Quad SRA) equipped with a TCD, using Poraplot U and Molsieve 5A columns.

TPH experiments

TPH experiments were carried out on aged catalysts after cooling to room temperature under argon flow, then by ramping the temperature from 25 to 700 8Cat108C/min, under a flow of 5 vol.% H 2 /Ar (50 N ml/min), following the outlet gas composition by mass spectrometry (mostly methane formation arising from the hydrogenation of carbon deposits).

Magnetic measurements

The amount of ferromagnetic Ni (giving access to the degree of Ni reduction) and the average metal particle size were determined for both catalysts, when activated, using the Weiss extraction method [START_REF] Dalmon | Catalyst Characterization[END_REF]. The sample (about 200 mg) was loaded in a specially designed fixed-bed reactor suited as sample holder in the electro-magnet. The passivated catalysts were heated to 600 8C (10 8C/min) in a flow of 10 vol.% H 2 /Ar. Then the H 2 /Ar mixture was switched to Ar, the cell was cooled to ambient temperature and sealed under an Ar atmosphere before collecting the magnetisation isotherms. For methane dry reforming over Ni/SiO 2 (Fig. 1), a fast deactivation occurs during the first minutes on stream followed by a slow and linear decrease in activity. For Ni/Mg(Al)O, a much improved stability is noted together with a higher CH 4 and CO 2 conversion.

Results

Long term ageing tests

For propane dry reforming (Fig. 2) a lower conversion than for methane is observed for both catalysts [e.g. 10% versus 30% hydrocarbon conversion after 6000 min (100 h) over the reference catalyst]. For Ni/SiO 2 , an initial deactivation is observed followed by a stable conversion, while the Ni/ Mg(Al)O system remains perfectly stable over the run. In ref. [4], a stability test lasting for 34 days showed the same features.

Catalytic tests in the TEOM reactor

Methane and propane dry reforming experiments carried out in the TEOM reactor are reported in Fig. 3 (methane reforming) and Fig. 4 (propane reforming).

The deactivation curves recorded both for methane (Fig. 3A) and propane (Fig. 4A) in the TEOM reactor reflect well the trends reported above for long term ageing experiments in fixed bed reactor (Figs. 1 and2), even though slight differences in performances are noted, likely due to the difference in reactor configuration (WHSV, geometry, catalyst bed packing, etc.). Main findings are: (i) in all cases the CO 2 conversion is higher than that for methane or propane (due to RWGS), (ii) for both hydrocarbons, the deactivation is less pronounced for hydrotalcite based material, the difference being largest for methane dry reforming, and (iii) both for methane and propane dry reforming, the stabilized or pseudo stabilized conversion (after an initial deactivation within the first 2 h on stream) is about two times higher for the hydrotalcite based system than for the Ni/SiO 2 one.

Changes in mass

Mass changes observed in data presented in Figs. 3B and4B can unambiguously be assigned to carbon deposits, since the eventual contribution of the supports (e.g. hydroxylation and/or carbonatisation of silica or hydrotalcite Mg(Al)O materials) have been accounted for from blank experiments. The main trends observed are: (i) for both types of catalysts, a fast initial carbon uptake is noted either for methane or for propane dry reforming, which corresponds to the initial deactivation reported above. This carbon uptake during the initial period is about 2.5-4 times larger for Ni/SiO 2 than for Ni/Mg(Al)O and about 1.5-2 times larger for propane than for methane reforming (0.5 wt.% versus 0.13 wt.% for methane reforming and 0.8 wt.% versus 0.3 wt.% for propane reforming), (ii) after this initial period, the rate of carbon uptake (slope of the mass curve) remains about three times lower for Ni/Mg(Al)O than for Ni/SiO 2 (below 0.01 wt.% h À1 versus 0.03 wt.% h À1 both for methane and propane reforming). It was even noted that

TPH experiments

TPH experiments were carried out after various times on TEOM stream, as illustrated in Figs. 5 and6 for the hydrotalcite based system and in Fig. 7 for comparing Ni/SiO 2 and Ni/ Mg(Al)O systems after propane dry reforming.

As can be seen for the hydrotalcite based system, either for methane (Fig. 5) or propane (Fig. 6) dry reforming, two main types of carbon are formed upon time on stream; (i) a small amount accumulating within the first 0.1 h on stream, which can be hydrogenated between 200 and 500 8C, and which does not further evolve for longer ageing period, and (ii) a more abundant and stable carbon, which can be hydrogenated only at around 600 8C, and which slowly and regularly accumulates with time on stream. It can be noted also in Fig. 6 that the amount of stable carbon accumulating with time on stream is higher for propane than for methane reforming, in agreement with the TEOM results. For Ni/SiO 2 reference catalysts, similar trends were already reported for methane dry reforming [START_REF] Pinaeva | Environmental Challenges and Greenhouse Gas Control for Fossil Fuel Utilization in the 21st Century[END_REF]. For propane dry reforming over Ni/SiO 2 (Fig. 7), it can be noted that the more reactive carbon can be hydrogenated at lower temperature than for the hydrotalcite based material.

TEM analyses

From TEM analyses reported in ref. [START_REF] Pinaeva | Environmental Challenges and Greenhouse Gas Control for Fossil Fuel Utilization in the 21st Century[END_REF] it was observed for Ni/SiO 2 that most of the Ni particles after reduction had a size comprised between 4 and 8 nm. For Ni/Mg(Al)O [4], most of the particles were below 5 nm, while some large particles were observed in the range 20-40 nm. After methane dry reforming tests, it was noted that for Ni/SiO 2 , both two-dimensional carbon veils and whiskers accumulate upon time on stream, with a large number of Ni particles being located on top or at the intersection of carbon whiskers. In contrast, whiskers growth was only scarcely observed for the hydrotalcite based system.

Only bidimensional carbon layers or veils around the Ni particles and on the support were observed, and the Ni particles remaining embedded into the support, as depicted for a large particle in Fig. 8 [4]. Note that the main fraction of small particles (below 5 nm) was still on the support, though the presence of carbon hindered a precise evaluation of their mean size [4].

State of the nickel phase from magnetic measurements

Table 1 summarizes data obtained from magnetic measurements after the reduction. As can be seen, the hydrotalcite based material is much less reduced than Ni/SiO 2 , with a better dispersion of the metallic phase (in agreement with the above TEM data), as expected from the strong metal support interaction typical of this material [4]. Some magnetic measurements, not reported here [START_REF] Raaberg | [END_REF], were also recorded after catalytic tests. They indicate a trend to some decrease in the ferromagnetic content, especially for the Ni/SiO 2 system. Such a trend may indicate a transformation of part of the metallic Ni phase (ferromagnetic) into nickel carbide (nonferromagnetic) or with interstitial carbon within the Ni phase (less ferromagnetic). For the hydrotalcite system, it was even observed in some cases a slight increase of the ferromagnetic content, which here could suggest a further reduction of the Ni phase under reforming conditions.

Discussion

Nature of the ageing process

By checking that the degree of Ni reduction and the mean particle sizes do not change in a significant way along the reforming runs (either for methane or propane) [START_REF] Raaberg | [END_REF], it can be deduced that for the present investigation, most of the catalyst ageing, reflected by the loss of activity, is due to carbon deposits. Note however that in the presence of real natural gas feed, other sources of poisoning such as sulphur deposits should be accounted for, in addition to coke poisoning.

Nature of carbon deposits

From TEOM, TPH and TEM experiments, it was observed that at least two types of carbon deposits are formed during the dry reforming processes: (i) carbon deposits accumulating within the first minutes on stream, which can be hydrogenated between 200 and 500 8C, and which does not further evolve for longer ageing period (denoted as low temperature carbon, C LT ), and (ii) a more abundant and stable carbon, which can be hydrogenated at around 600 8C, but which slowly and regularly accumulates with time on stream (denoted as high temperature carbon, C HT ).

(i) C LT cannot be considered as long term deactivating carbon, since it is rapidly accumulating and stabilizing as soon as the reduced catalysts are contacted with the reacting feed. It was already assigned, for the case of methane dry reforming on Ni catalysts, to a combination of Ni surface and bulk carbon species, which play a direct role in the reforming mechanism. Its concentration was shown to depend on the reaction conditions and the reactivity of the Ni phase, as a function of metal loading, addition of dopants like alkali or alkaline earth elements, nature of the support, etc. [START_REF] Pinaeva | Environmental Challenges and Greenhouse Gas Control for Fossil Fuel Utilization in the 21st Century[END_REF]. By dividing the molar amount of these active carbon deposits by the molar amount of surface nickel (deduced from the mean Ni particle size), the ratio C LT /Ni surface can be evaluated, as reported in Table 2 for the various studied cases.

Within the uncertainties in the experimental methods for calculating this ratio, it could be first underlined that the concentration of this active carbon leading to CO formation seems to be slightly more abundant for Ni/Mg(Al)O than for Ni/ SiO 2 , and for methane than for propane reforming. On a more quantitative point of view, by considering these C LT /Ni surface values in Table 2, it can be speculated that this active carbon C LT would correspond to NiC, Ni 2 Co rN i 3 C surface carbon (nickel carbide like), as already reported in the literature for methane steam or dry reforming [START_REF] Pinaeva | Environmental Challenges and Greenhouse Gas Control for Fossil Fuel Utilization in the 21st Century[END_REF].

(ii) At variance with C LT ,C HT seems to directly control the long term deactivation process. Thus, for Ni/SiO 2 , the regular rate of deactivation appears to correspond to the regular accumulation of C HT , while for Ni/Mg(Al)O, the low rate of stable carbon uptake seems to ensure the long term catalyst stability. However, from the TEM analyses, it is concluded that this C HT comprises most likely at least two forms of graphitic carbon; the whiskers observed only for Ni/SiO 2 and the bidimensional carbon observed both for Ni/SiO 2 and Ni/ Mg(Al)O.

Specificities of the hydrotalcite based system as compared to the reference Ni/SiO 2 catalyst: From the above observations, it was shown that on both catalytic systems, the dry reforming of methane or propane is likely to proceed via similar active surface carbide like intermediates, though the ratio C LT /Ni revealed some slight differences depending on the catalyst and on the reformed hydrocarbon.

In contrast, major differences were revealed for the two studied catalytic systems concerning the stable and accumulating carbon and the kinetics of accumulation:

On the reference silica based system, the carbon deposition has been well described elsewhere [START_REF] Pinaeva | Environmental Challenges and Greenhouse Gas Control for Fossil Fuel Utilization in the 21st Century[END_REF]. It combines (i) the formation of carbon nanotubes by carbon extrusion from dense planes, favoured by the fact that the Ni particle are not fixed on the silica and can be transported by the nanotubes and (ii) encapsulating carbon which progressively limits the access of the reacting gases to the active surface. The carbon whiskers cannot be considered as participating to the catalyst ageing, unless random and side phenomena like particle fragmentation take place (due to surface and bulk constraints (Ni carbide) and further on to pores and reactor plugging). In contrast, the bidimensional form of encapsulating carbon, rather favoured by the free access to all sides of the particles, unambiguously leads to catalysts deactivation. From this analysis, the curves of carbon uptake for Ni/SiO 2 (Fig. 4B) can be interpreted as such: initial fast surface carbide buildup followed by the regular accumulation of both carbon nanotubes (not toxic unless large amounts deposited) and encapsulating deactivating carbon. For the hydrotalcite based system, the strong metal/support interaction which embeds the Ni particles onto the support hinders the formation of carbon nanotubes, since only part of the particles' surface is accessible to the reacting gases, which prevents any extrusion from the other side. Such a configuration also hinders the formation of encapsulating layers around the particles, which is proved by the low amount of C HT detected by TPH. Though outside the scope of the present paper, a full investigation comparing the mechanism of methane and propane dry reforming (to be published) also indicates that the hydrotalcite support plays another major role which is to provide continuously oxygen to the Ni surface and which obviously limits the formation of any toxic carbon around the particles. The source of oxygen is ensured by a pool of carbonates around the Ni particles (well identified from in situ DRIFT spectra not reported here) able to decompose into CO and surface oxygen.

Specificities of methane and propane dry reforming

As seen by comparing Figs. 3B and 4B and in Table 2,itis concluded that methane dry reforming tends to produce significantly less surface and out-of-surface carbon than propane dry reforming. This trend should still be reinforced by performing the propane dry reforming experiments in the absence of added hydrogen in the feed. For surface carbon, it can easily be understood that the cracking of methane into surface carbon as a preliminary step involves only C-H bond breaking, while C-C bonds are also involved for propane reforming. Therefore, it can be speculated that: (i) for methane reforming, the probability to form C-C bonds as coke precursors from the atomic carbon species (easily formed from methane cracking) is low due to the fast competitive oxidation by surface oxygen provided by CO 2 dissociation, and (ii) for propane reforming, the probability to form coke precursors is much higher since C 3 partially dehydrogenated adspecies may easily form and polymerise into polyaromatics, in competition with the CO formation. This process might involve a transient formation of propylene as assumed in ref. [START_REF] Solymosi | [END_REF]. Further differences between the two reforming mechanisms will be reported in a forthcoming study.

Conclusions

From the preliminary data presented in this paper, combined with data already published or still to be published, major differences were observed by comparing two nickel based catalysts for the dry reforming of methane and propane. The much higher stability of the hydrotalcite based system was assigned (i) to the morphology and structure of the nickel phase, remaining in strong interaction with the support under reaction conditions, while the Ni particles are easily extracted from the silica surface, and (ii) to an active role of the hydrotalcite support which is to provide continuously oxygen to the nickel surface. It was also demonstrated that methane reforming generates less surface and out-of-surface carbon than propane reforming. This might be related to the competition between the initial steps of cracking, polymerization and carbon oxidation, highly sensitive to the nature and structure of the molecules to be reformed.

Figs. 1

 1 Figs. 1 and 2 report the activity/stability tests carried out over the Ni/SiO 2 reference catalyst and the Ni/Mg(Al)O hydrotalcite-derived catalyst both for dry methane and propane reforming to syngas at 600 8C and 1 atm.For methane dry reforming over Ni/SiO 2 (Fig.1), a fast deactivation occurs during the first minutes on stream followed by a slow and linear decrease in activity. For Ni/Mg(Al)O, a much improved stability is noted together with a higher CH 4 and CO 2 conversion.For propane dry reforming (Fig.2) a lower conversion than for methane is observed for both catalysts [e.g. 10% versus 30%

Fig. 1 .

 1 Fig. 1. Activity/stability tests at 600 8C for 8000-10,000 min (130-170 h) under a CH 4 :CO 2 :N 2 = 10:10:80 stream. (a) Ni/SiO 2 and (b) Ni/Mg(Al)O.

Fig. 2 .

 2 Fig. 2. Activity/stability tests at 600 8C for 10,000 min (170 h) under a C 3 H 8 :CO 2 :H 2 :N 2 = 10:30:10:50 stream. (a) Ni/SiO 2 and (b) Ni/Mg(Al)O.

Fig. 3 .

 3 Fig. 3. (A) Changes in methane [(*) (c), (&) (d)] and carbon dioxide [(*) (a), (&) (b)] conversion vs. time on stream (min) in the TEOM reactor over Ni/SiO 2 [(&) (b), (&) (d)] and Ni/Mg(Al)O [(*) (a), (*) (c)]; (B) Mass uptake (expressed as carbon wt.% referring to the catalyst) vs. time on stream (min) for methane dry reforming in the TEOM reactor for Ni/SiO 2 and Ni/Mg(Al)O.

Fig. 4 .Fig. 5 .

 45 Fig. 4. (A) Changes in propane [(*) (b), (&) (d)] and carbon dioxide [(*) (a), (&) (c)] conversion vs. time on stream (min) in the TEOM reactor over Ni/SiO 2 [(&) (c), (&) (d)] and Ni/Mg(Al)O [(*) (a), (*) (b)] catalysts; (B) Mass uptake (expressed as carbon wt.% referring to the catalyst) vs. time on stream (min) for propane dry reforming in the TEOM reactor for Ni/SiO 2 and Ni/ Mg(Al)O.

Fig. 6 .

 6 Fig. 6. Amount of carbon hydrogenated into methane during TPH experiments after TEOM propane dry reforming over Ni/Mg(Al)O for 0.1 h (b) and 24 h (a).For comparison, curve (c) is similar to one curve in Fig.5(related to methane dry reforming). Heating rate during the TPH experiment was 10 8C/min.

Fig. 7 .

 7 Fig. 7. Normalized amount of carbon hydrogenated into methane during TPH experiments after TEOM propane dry reforming for approximately 0.1 h over Ni/Mg(Al)O (a) and Ni/SiO 2 (b). Heating rate during the TPH experiment was 10 8C/min.

Fig. 8 .

 8 Fig. 8. TEM image of a large Ni particle after 12 h under propane dry reforming stream over 1.9 wt.% Ni/Mg(Al)O [4].

  ) Ni/SiO 2 Ni/Mg(Al)O Ni/SiO 2 Ni/Mg(Al)O After reduction at 600 8C %95 %20 8 5-6 aa This mean value, due to the very low amount of ferromagnetic signal, does not exclude that large particles may also coexist, like the one observed by TEM in Fig.8.

Table 2

 2 Values of the C LT /Ni surface as deduced from TPH and TEOM measurements

	Catalysts	Ni/SiO 2	Ni/Mg(Al)O
	Methane dry reforming	0.3 a	1.8
	Propane dry reforming	0.2	1.1

a From ref.

[START_REF] Pinaeva | Environmental Challenges and Greenhouse Gas Control for Fossil Fuel Utilization in the 21st Century[END_REF]

.


François Lamoureux

Gaelle Picarda

Julie Rousseau

Clothilde Gourden

Séverine Battaglia

Céline Charrier

Bruno Pitard

Dominique Heymann

Françoise Redini
email: ç<francoise.redini@univ-nantes.fr>

Lamoureux Fran

Picarda Gaelle

Gourden Clothilde

Pitard Bruno

Heymann Dominique

Redini Fran

Fran Oise Redini

Therapeutic efficacy of soluble receptor activator of nuclear factor-kappaB-Fc delivered by nonviral gene transfer in a mouse

Keywords: Animals, Apoptosis, Cell Line, Tumor, Cell Movement, Cell Proliferation, Disease Models, Animal, Disease Progression, Gene Expression Regulation, Neoplastic, Gene Therapy, Gene Transfer Techniques, Humans, Immunoglobulin Fc Fragments, genetics, Lung, pathology, Mice, Osteolysis, complications, genetics, pathology, therapy, Osteosarcoma, complications, genetics, pathology, therapy, Receptor Activator of Nuclear Factor-kappa B, genetics, therapeutic use, Reproducibility of Results, Solubility, Survival Analysis, Transgenes, Treatment Outcome

Introduction

With an estimated incidence of 2 cases per million people per year, osteosarcoma is the most frequent primary bone malignant tumor excluding hematopoietic intraosseous tumors. Osteosarcoma generally affects young patients with a peak incidence at 18 years old. The unifying histologic feature found in all types and subtypes of osteosarcomas is the presence of osteoid tissue produced by the neoplasic cells . As these tumors frequently penetrate and destroy the cortical substance of the bone and extend into the surrounding tissues, a

The final effector molecules that ultimately control osteolysis associated with tumor development in bone site are Receptor Activator of NF-kB Ligand (RANKL) and osteoprotegerin (OPG) . RANKL directly stimulates osteoclastic differenciation and osteoclast [START_REF] Baud Huin ' M | osteoprotegerin: key partners of osteoimmunology and vascular diseases[END_REF] activation and survival by signalling through its membrane receptor RANK, expressed on the osteoclast precursor surface. Physiologically, RANKL signalling is negatively regulated by the soluble antagonist receptor protein OPG which induces osteoclast apoptosis. Targeting RANKL signalling with OPG inhibits tumor associated osteolysis in several experimental bone tumor models including mouse colon adenocarcinoma, myeloma, breast, lung, prostate cancer and osteosarcoma . However, OPG has been shown to bind the TNF receptor [START_REF] Morony | Osteoprotegerin inhibits osteolysis and decreases skeletal tumor burden in syngeneic and nude mouse models of experimental bone metastasis[END_REF][START_REF] Croucher | Osteoprotegerin inhibits the development of osteolytic bone disease in multiple myeloma[END_REF][START_REF] Yonou | Osteoprotegerin/osteoclastogenesis inhibitory factor decreases human prostate cancer burden in human adult bone implanted into nonobese diabetic/severe combined immunodeficient mice[END_REF][START_REF] Capparelli | Osteoprotegerin prevents and reverses hypercalcemia in a murine model of humoral hypercalcemia of malignancy[END_REF][START_REF] Zhang | Qi Y Osteoprotegerin inhibits prostate cancer-induced osteoclastogenesis and prevents prostate tumor growth in the bone[END_REF][START_REF] Lamoureux | Therapeutic relevance of osteoprotegerin gene therapy in osteosarcoma: prevention of bone resorption, inhibition of tumor progression, increase of animal survival[END_REF] TRAIL (TNF Related Apoptosis Inducing Ligand), and to block TRAIL-mediated apoptosis in cancer cells . Thus, alternative [START_REF] Holen | Shipman CM Role of osteoprotegerin (OPG) in cancer[END_REF][START_REF] Holen | Eaton CL Osteoprotegerin (OPG) is a survival factor for human prostate cancer cells[END_REF][START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF][START_REF] Kapoor | Osteoprotegerin and the bone homing and colonization potential of breast cancer[END_REF] agents such as soluble RANK-Fc that block RANKL mediated bone resorption but that do not interact with TRAIL, may provide useful therapies to prevent tumor development in bone. RANK-Fc is a chimeric protein formed by fusing the four cysteine-rich pseudorepeats of RANK that are responsible for RANK-L binding with the Fc portion of human immunoglobulin G1 (IgG1). Moreover, RANK-Fc has the potential advantage over OPG of greater specificity for RANKL. Fusion of the four Cystein Rich Domains (CRD) of RANK to the constant region of hIgG1 dictates homodimerization which probably increases its avidity for RANKL. The sRANK differs from OPG because in addition to containing four CRDs, OPG also contains two death domains and a heparin binding domain . Accordingly, [START_REF] Yamaguchi | Goto M Characterization of Structural Domains of Human Osteoclastogenesis Inhibitory Factor[END_REF] RANK-Fc has been recently shown to cause a marked reduction in tumor burden in two SCID-hu-multiple myeloma models , and also [START_REF] Sordillo | RANK-Fc: a therapeutic antagonist for RANK-L in myeloma[END_REF] an inhibition of prostate cancer progression in bone . However, no study was performed on RANK-Fc effects in primary bone tumors. [START_REF] Zhang | Soluble Receptor Activator of Nuclear Factor kB diminishes prostate cancer progression in bone[END_REF] Previous data showed that it is feasible to provide long-lasting expression of RANK-Fc at bone-protective levels using a retroviral gene therapy approach . However, the toxicity associated with the use of viral vectors is extremely complex involving both the innate [START_REF] Kim | Her SJ Retrovirus-mediated gene transfer of receptor activator of nuclear factor-kappaB-Fc prevents bone loss in ovariectomized mice[END_REF] and adaptative immune responses. Recently, a new class of synthetic vectors has been reported for gene transfer in various organs in vivo including skeletal and cardiac muscles , and in lungs . These new synthetic vectors result from the association of plasmid DNA [18 19] [20] with amphiphilic polymers consisting in blocks of poly(ethylene oxide) and of poly(propylene oxide). Intramuscular injections of these synthetic vectors lead to the synthesis of proteins for local benefit such as dystrophin or for systemic use such as erythropoietin .

[21]

The aim of this study was to determine the therapeutic relevance of RANK-Fc in a murine osteolytic osteosarcoma model by using a non-viral gene transfer approach.

Material & Methods

Cell lines

-The osteosarcoma cell line POS-1, derived from mouse spontaneous osteosarcoma , was cultured in RPMI 1640 medium (Bio [START_REF] Kamijo | Inhibition of lung metastasis of osteosarcoma cell line POS-1 transplanted into mice by thigh ligation[END_REF] Whittaker, Verviers, Belgium) supplemented with 10 fetal bovine serum (FBS, Hyclone, Perbio, France) and 2 mmol/L L-glutamine.

%

-The osteoclast precursor RAW 264.7 cells from the monocyte macrophage lineage were obtained from the American Tissue and Cell Collection (ATCC) and grown in MEM (Invitrogen, Cergy-Pontoise, France) supplemented with 10 FBS (Hyclone) and 1 non α % % essential amino acids (Invitrogen).

-The human osteosarcoma MG63 cell line was purchased from the ATCC and used for assay of TRAIL biological activity and in vitro cultured in Dulbecco s Modified Eagle s Medium (DMEM, BioWhittaker) supplemented by 10 FBS (Hyclone) and 2 mmol/L of ' ' % L-glutamine.

experimentations In vitro

Plasmid constructions

The pcDNA3.1-RANK-Fc construction (kindly provided by Dr Choi Y., Philadelphia, USA) contains a DNA sequence encoding the extracellular domain of murine RANK (0.7 kb) fused to the coding sequences of the constant portion of human IgG1 (0.5 kb)

. The [START_REF] Guilloneau | The role of TNF-related activation-induced cytokine-receptor activating NF-kappa B interaction in acute allograft rejection and CD40L-independent chronic allograft rejection[END_REF] soluble RANK-Fc cDNA is inserted in the pcDNA3.1 plasmid between XbaI and XhoI under the control of the CMV promoter. For the in and studies, the empty pcDNA3.1 was used as a control.

vivo in vitro

Cell transfection

To assess the cellular expression of RANK-Fc, 2 g of pcDNA3.

Osteoclasts differentiation

The biological activity of the transgene was compared between pcDNA3. Amgen Inc, Thousand Oaks, USA). After five days of culture, multinucleated cells (> 3 nuclei) were counted after a May Gr nwald ü Giemsa staining.

Cell proliferation

Replicate subconfluent cell cultures of POS-1 cells in 96-well plates were treated for 24 to 72 hours with increasing concentrations of murine RANK-Fc (R&D systems, Abingdon, UK) (0, 25, 50 and 100 ng/ml). Cell viability was determined by the sodium 3′[ 1-(phenylaminocarbonyl)-3,4-tetrazolium -bis(4-methoxy-6-nitro)benzene sulfonic acid hydrate (XTT) cell proliferation reagent assay kit ] (Roche Molecular Biomedicals).

Caspase activity

POS-1 cells (2 10 per well) cultured in 24-well plates were treated with 100 ng/ml RANK-Fc for 24 to 72 hours, washed and lysed

× 4
with 50 l of RIPA buffer for 30 min. in the presence of protease inhibitors. The cells were then scraped off and the protein amount was Cells treated with 1 M staurosporin 6 hours before harvesting were used as a positive control for caspase activity.

μ

Cell cycle analysis

Confluent POS-1 cells treated with increasing concentrations of RANK-Fc (0, 50 and 100 ng/ml) for 24, 48 and 72 hours were removed from culture dishes by trypsinization, washed twice in PBS and incubated in PBS containing 0.12 Triton X-100, 0.12 mM

TRAIL biological activity

Replicate subconfluent cell cultures of human osteosarcoma MG63 cells in 96-well plates were treated for 72 hours with increasing concentrations of human TRAIL (R&D systems) (0, 50 and 100 ng/ml) in the presence or absence of 100 ng/ml RANK-Fc. Cell viability was determined by the XTT cell proliferation reagent assay kit as described above.

experimentations In vivo

: four-week-old male C3H/He mice (Elevages Janvier, Le Genest St Isle, France) were housed under Mouse osteosarcoma models pathogen-free conditions at the Experimental Therapy Unit (Faculty of Medicine, Nantes, France) in accordance with the institutional guidelines of the French Ethical Committee and under the supervision of authorized investigators. The mice were anaesthetized by inhalation of a combination isoflurane/air (1.5 , 1 L/min) associated with an intramuscular injection of buprenorphine (0.05 mg/kg; % Temgesic , Schering-Plough, Levallois-Perret, France) prior to subcutaneous inoculation of POS-1 cell suspension containing 2 10 ® × 6 cells in 50 l PBS in the hind footpad of the mice. Under these conditions, mice develop a primary tumor at the site of injection in three μ weeks that can be transplanted to mice of the same strain as a small fragment (2 2 2 mm ) in close contact with the tibia. For this purpose, × × 3 the periostum of the diaphysis was opened and resected along a length of 5 mm, underlying bone was intact. The osteosarcoma fragment was placed contiguous to the exposed bone surface without periostum, and the cutaneous and muscular wounds were sutured. Tumors appeared at the graft site approximately 8 days later associated with the development of pulmonary metastases in a 3 week-period. The tumor that develops in contact to the tibia induces osteolytic lesions that reproduce the osteolytic form of human osteosarcoma . The [START_REF] Kamijo | Inhibition of lung metastasis of osteosarcoma cell line POS-1 transplanted into mice by thigh ligation[END_REF] tumor volume (V) was calculated from the measurement of two perpendicular diameters using a calliper, according to the following formula: V 0.5 L (S) , where L and S are respectively the largest and smallest perpendicular tumor diameters. A model of pulmonary

= × × 2
metastases was developed to study RANK-Fc effect independent of bone environment, where mice were anaesthetized by inhalation of a mixture of isoflurane/air combined with an intramuscular injection of buprenorphine as described above prior to i.v. injection of 50 l of μ POS-1 cell suspension containing 1.5 10 cells. In these conditions, pulmonary metastases developed rapidly, leading to the death of the

× 5
animals in three weeks after POS-1 cell injection.

: for intramuscular injections, mice were anaesthetized with a combination isoflurane/air. Fifty microliters of Formulation preparations block copolymers/DNA formulations were injected into shaved tibial anterior muscles at one site using a microfine syringe (U100, Becton Dickinson, Rungis, France). Lutrol , a block copolymer consisting of poly(ethyleneoxide) -poly(propyleneoxide) -poly(ethyleneoxide) : to determine the effect of RANK-Fc delivered by synthetic vectors on osteosarcoma development, the mice Experimental protocols were transplanted with POS-1 osteosarcoma fragments as described above. Groups of 8 mice were assigned respectively as controls (no injection), control vectors (Lutrol /pcDNA3.1 alone) and RANK-Fc (Lutrol /pcDNA3.1-RANK-Fc). Preliminary results from the ® ® laboratory have already shown that the vector Lutrol alone does not affect tumor development in the same mouse osteosarcoma model

® [9]
. A preventive treatment was applied, where the Lutrol /DNA formulations were injected into both tibial anterior muscles once a week, ® beginning 7 days before osteosarcoma implantation up to 21 days post-implantation. The tumor volume was calculated as described above.

Treatment continued until each animal showed signs of morbidity, which included cachexia or respiratory distress, at which point they were sacrificed by cervical dislocation. Lung tumor dissemination was assessed at necropsy.

Radiographs on animals anaesthetized with 50 mg/kg Nesdonal (Merial, Lyon, France) were taken every week and at the time of necropsy with a mammography PLANMED Sophie apparatus (SN RAH 40710, Helsinki, Finland). Analysis of architectural parameters was performed using the high resolution X-ray micro-CT system for small animal imaging SkyScan-1072 (SkyScan, Aartselaar, Belgium).

Relative volume (BV/TV) of the tibia total bone (cortical trabecular) or trabecular bone was quantified at necropsy in the osteosarcoma

[ + ]
groups that received RANK-Fc compared to that of control mice. The results of one representative experiment out of 3 are shown.

Gene and protein expression analysis

To assess RANK-Fc transgene expression at the mRNA and protein levels, pcDNA3.1-and in vitro pcDNA3.1-RANK-Fc-nucleofected RAW 264.7 cells were cultured in 6-well plates (2 10 per well) under standard conditions during 48

× 6 hours.
, blood was drawn intermittently from the retro-orbital vein to monitor serum RANK-Fc level (day 7, 10 or 15 post-injection). In vivo At necropsy, the tumor and muscle tissues were lysed in Reporter Lysis Buffer 1X (Promega, Madison, USA) supplemented with protease inhibitor cocktail (Roche Molecular Biomedicals, Manheim, Germany), broyed during 30 sec using Ultraturax , centrifuged at 10 000 rpm ® during 5 min at 4 C and were processed for RANK-Fc detection using the ELISA test described below.

°RNA extraction and semi-quantitative Reverse Transcription-Polymerase Chain Reaction (RT-PCR) analysis

RANK-Fc mRNA expression was determined by RT-PCR after total RNA extraction using Trizol reagent (Invitrogen). First, RNA was reversed-transcribed (RT) using 400 U MMLV-RT from Invitrogen, then two microliters of the RT reaction mixture were subjected to PCR using upstream (5 -GCTGGCTACCACTGGAACTC-3 ) and downstream (5 -GTGGGCATGTGTGAGTTTTG-3 ) primers (30

′ ′ ′ ′
pmoles each) of sRANK-Fc and Taq polymerase (1.25 U, Eurobio, Les Ulis, France). The effect of RANK-Fc was assessed on tumor cell phenotype by studying the expression of several bone markers by RT-PCR.

RANK-Fc

Results

In vitro analysis of transgene expression mRANK-Fc overexpression was investigated at the mRNA and protein levels by RT-PCR and ELISA analyses performed on RAW 264.7 cells which were transfected with pcDNA3.1 or pcDNA3.1-RANK-Fc using the AMAXA nucleofector system. RT-PCR analysis showed a major expression of RANK-Fc mRNA in pcDNA3.1-RANK-Fc transfected cells whereas no expression was observed in the corresponding pcDNA3.1 transfected cells ( ). This result was confirmed at the protein level by ELISA analysis, as supernatant from Fig. 1a pcDNA3.1-RANK-Fc transfected cells showed a high level of murine RANK-Fc protein (101.6 15.88 ng/ml) after 48 hours, when ± compared to pcDNA3.1 transfected cells which showed no protein expression ( ).

Fig. 1b

In vivo validation of transgene expression

After injection of the DNA-Lutrol complexes into the tibial anterior muscles, an overexpression of the RANK-Fc transgene was ® measured both at systemic (serum) and local (muscle) levels in mice treated with pcDNA3.1-RANK-Fc. The production varied from 0.053 to 0.499 ng/ml in the serum and from 0.09 to 22.57 ng/ml in the muscle, being significantly higher to the pcDNA3.1 or control groups where no RANK-Fc expression could be detected, either in serum or in muscle (

). No correlation could be established between Fig. 1c RANK-Fc concentration (either systemic or local) and its therapeutic efficacy. The immunogenicity of the human Fc part of RANK-Fc was checked previously in a immunocompetent rat model of osteosarcoma, and no antibodies were detected up to 3 weeks (not shown).

In vitro validation of transgene biological activity

To confirm that RANK-Fc expressed by non viral gene transfer was biologically active, we investigated its ability to block RANKL induced multinucleated cell formation in the osteoclast precursor RAW 264. To ensure that RANK-Fc does not block TRAIL-mediated apoptosis, the effect of RANK-Fc was assessed on the human osteosarcoma cell line MG63 treated with increasing concentrations of TRAIL. To dispose of great amount of protein for dose and time-dependant analysis , a recombinant RANK-Fc corresponding to the same sequence as the transgene used in the study was chosen. No in vitro in vivo effect of RANK-Fc treatment could be demonstrated on TRAIL induced apoptosis of MG63 cells (

). Similar results were obtained Fig. 1e with other TRAIL sensitive cell lines, such as the A673 human Ewing sarcoma cell line.

These results demonstrate that RANK-Fc protein is expressed after non viral gene transfer both and and that it exerts in vitro in vivo, an anti-resorption activity (against RANKL) and not a pro-tumoral one (unable to block TRAIL induced apoptosis) in vivo

Protective effect of mRANK-Fc transgene expression on bone resorption associated to osteosarcoma development

The mouse osteosarcoma POS-1 model used in this study has been previously associated with osteolytic lesions by micro-CT analysis . To demonstrate the inhibitory effect of RANK-Fc on the development of osteolytic lesions, mice transplanted with osteosarcoma [START_REF] Kamijo | Inhibition of lung metastasis of osteosarcoma cell line POS-1 transplanted into mice by thigh ligation[END_REF] were treated with pcDNA3.1-RANK-Fc or pcDNA3.1 alone (control vector) using the amphiphile block copolymer Lutrol which had ® previously demonstrated the best transfection efficiency , . Because control tumors and pcDNA3.1 (control vector) treated in vivo [20 21] mice exhibit similar bone alterations , only pcDNA3.1 treated mice tibiae radiographs and micro-CT analyses were shown. Important [START_REF] Lamoureux | Therapeutic relevance of osteoprotegerin gene therapy in osteosarcoma: prevention of bone resorption, inhibition of tumor progression, increase of animal survival[END_REF] osteolytic lesions were observed on the tibia of POS-1 osteosarcoma bearing mice treated with pcDNA3.1 alone as compared to the pcDNA3.1-RANK-Fc group that exhibit minor lesions (

). These results were confirmed by the bone microarchitecture analysis, as Fig 2a the quantification of the specific bone volume revealed a reduced trabecular bone loss in RANK-Fc treated mice as compared to the pcDNA3.1 group: 24.01 versus 44.7 respectively (

). The anti-bone resorption activity of the RANK-Fc transgene was thus

mRANK-Fc transgene expression limits osteosarcoma progression and increases animal survival

Mice received a preventive treatment with DNA-Lutrol complexes, the first injections being realized 7 days before osteosarcoma ® implantation. This strategy was chosen because in vivo transgene production is optimal 7 days after the construct injection, this timepoint corresponding to the day of tumor transplantation. The tumor volume was calculated twice a week following the measure of the two perpendicular diameters. The results show that the tumor volume of each animal was smaller in the RANK-Fc treated group compared to the pcDNA3.1 or the control groups (

). As a result, the mean tumor volume 21 days after tumor implantation was significantly lower Fig 3a in the group receiving RANK-Fc compared to the pcDNA3.1 group or the control group (p<0.05), reaching respectively 1652.7 1055 mm ). These results enabled us to calculate the relative tumor progression between day 12 and 21 which was significantly Fig. 3a decreased by 62.7 (p<0.05) and 64.3 (p<0.01) in the RANK-Fc treated group as compared respectively to the pcDNA3.1 and untreated % %

group (

). As a consequence, a significant increase (p<0.02) of animal survival was observed with 57.1 of survival at day 28 in the Fig. 3b % RANK-Fc treated group versus 0 in the pcDNA3.1 group and 14.3 in the untreated group (

). Animals died of respiratory distress % %

Fig 3c

because of lung metastasis or were sacrificed due to huge tumor development. Animals treated with RANK-Fc showed no pulmonary metastases at day 26.

All these results show that RANK-Fc not only exerts a protective effect on osteosarcoma associated bone lesions but also diminishes the tumor progression in bone, increasing the animal survival in an osteolytic model of osteosarcoma.

Expression of mRANK-Fc inhibits osteosarcoma progression by preventing bone resorption

Complementary to radiographic and micro-CT analyses, TRAP staining was performed on osteosarcoma sections from mice treated or not with RANK-Fc to determine whether this cytokine could inhibit osteosarcoma-induced osteoclast formation. The development of large osteosarcoma tumors in this model is accompanied by increased osteoclastic bone resorption and increased recruitment of osteoclasts to the tumor-bone interface ( , arrows). The presence of TRAP positive osteoclasts was abrogated in the sRANK-Fc group ( ), Fig. 4a Fig. 4a,b confirming at the cellular level the inhibitory effect of RANK-Fc on osteosarcoma associated osteolysis.

In vitro, RANK-Fc has no effect on tumor cell proliferation, apoptosis, migration and gene expression

To determine whether RANK-Fc inhibitory effect on tumor progression is direct on tumor cells or not, several in vivo in vitro experiments were performed on osteosarcoma cell proliferation, apoptosis, cell migration, gene expression and cell cycle, using the POS-1 mouse osteosarcoma cell line corresponding to the model. in vivo

The viability of POS-1 cells treated with increasing concentrations of RANK-Fc was analyzed from 24 to 72 hours using a XTT based method. No significant effect was noticed even after 72 hours of treatment with 100 ng/ml of RANK-Fc (

), nor on POS-1 cell Fig 5a

apoptosis as analyzed by caspase activity assay ( ). Similarly, RANK-Fc treatment had no effect on POS-1 cells migration (data not Fig 5b shown) and on the cell cycle phase distribution (

). RT-PCR analysis demonstrates that a 100 ng/ml treatment during 72 hours with Fig 5c

RANK-Fc does not induce gene expression modulation of POS-1 cells (data not shown).

These data demonstrate that the inhibitory effects observed on tumor progression for the RANK-Fc treated group are not due to in vivo a direct effect on POS-1 tumor cells.

RANK-Fc treatment does not affect tumor nodule development in lungs

As RANK-Fc exerts no direct effect on tumor cells, we hypothesize that the inhibitory effect observed in osteosarcoma development is the indirect consequence of bone resorption inhibition, thus depending on bone microenvironment. To demonstrate this hypothesis, another set of experiments was performed in mice developing tumor lesions in lungs. This model was induced after POS-1 cell injection in the retro-orbital vein. The results presented in show no significant differences between the different groups in the overall mouse Figure 6 survival rate, indicating that RANK-Fc exerts no inhibitory effect on tumor development outside the bone micro-environment.

Discussion

The mouse model of osteosarcoma used in this study is characterized by the presence of osteolytic lesions . The release of latent [START_REF] Wittrant | RANKL directly induces bone morphogenetic protein-2 expression in RANK-expressing POS-1 osteosarcoma cells[END_REF] growth factors (such as insulin growth factor, TGF-, BMP, PDGF and VEGF) stored in the bone matrix during osteolysis stimulates the β tumor growth in a vicious cycle that leads to tumor cell proliferation and tumor progression in bone sites , . Bone resorption [ 25 26] inhibitors thus appear as one of the most promising tools to manage osteolytic lesions associated to primary or secondary bone tumors. The OPG/RANKL/RANK pathway offers multiple molecular checkpoints for therapeutic targeting in osteolytic tumors. Inhibition of this axis has demonstrated therapeutic efficacy in restricting tumor-mediated osteolysis as well as in animal models of both bone metastasis in vitro , and osteosarcoma . Indeed, previous results obtained in our laboratory in the same mouse osteosarcoma model with OPG [16 [START_REF] Wittrant | RANKL/RANK/OPG: new therapeutic targets in bone tumours and associated osteolysis[END_REF][START_REF] Whang | The effects of RANK blockade and osteoclast depletion in a model of pure osteoblastic prostate cancer metastasis in bone[END_REF][START_REF] Feeley | Conduah AH Mixed metastatic lung cancer lesions in bone are inhibited by noggin overexpression and Rank:Fc administration[END_REF] [9] gene transfer demonstrated the relevance of using such anti-resorptive factors as promising therapeutic approaches for primitive osteolytic tumors. However, the ability of OPG to block the TRAIL apoptosis pathway in cancer cells was noticed and there were concerns that this could lead to a burst in tumor growth . Denosumab is a fully human mAb directed against RANKL and is currently under investigation [START_REF] Hl | Eaton CL Osteoprotegerin (OPG) produced by bone marrow stromal cells protects breast cancer cells from TRAIL-induced apoptosis[END_REF] in phase III clinical trials , . Denosumab was generated by immunizing the XenoMouse with full-length human RANKL protein, [31 32] [START_REF] Green | Antibody engineering via genetic engineering of the mouse: XenoMouse strains are a vehicle for the facile generation of therapeutic human monoclonal antibodies[END_REF] producing a fully human IgG1 mAb which recognizes an epitope with a single amino acid difference between the mouse and the human sequences. Because human IgG1 can induce complement-dependent cytotoxicity or antibody-dependent cell cytotoxicity to target cells [START_REF] Scallon | Ghrayeb J Chimeric anti-TNF-alpha monoclonal antibody cA2 binds recombinant transmembrane TNF-alpha and activates immune effector functions[END_REF] , it was converted to a noncytotoxic IgG2 mAb, known as Denosumab which has an extremely high affinity (Kd approximately 10 M)

12

for human RANKL. The fact that Denosumab does not recognize rodent RANKL has complicated preclinical development, with only one relevant animal study conducted in cynomolgus monkeys . Therefore, as these anti-RANKL antibodies cannot be used in our mouse [START_REF] Kostenuik | Osteoprotegerin and RANKL regulate bone resorption, density, geometry and strength[END_REF] model of osteosarcoma, RANK-Fc, another member of the TNF receptor family was used in the present study. Indeed, RANK-Fc, the fusion of the extracellular domain of RANK (amino acids with the constant region of human immunoglobulin G1 (IgG1) has the potential advantage over OPG of greater specificity for RANKL . Delivery of RANK-Fc as a recombinant protein has shown [START_REF] Sordillo | RANK-Fc: a therapeutic antagonist for RANK-L in myeloma[END_REF] promising results as a potential therapy through experiments in animal models, in that RANK-Fc limits hypercalcemia and osteolysis induced by myeloma or prostate cancer and reduces bone tumor establishment in these models , , , . Moreover, a recent study [15 [START_REF] Zhang | Soluble Receptor Activator of Nuclear Factor kB diminishes prostate cancer progression in bone[END_REF] 29 36] reported that RANK-Fc inhibition of RANKL has an anti-osteoclast activity at doses that have no detectable immunoregulatory activity [ . Even if long-lasting expression of RANK-Fc could be provided at bone-protective levels using a retrovirus-mediated gene transfer 37] approach by the use of genetically modified mesenchymal stem cells , the toxicity associated with the use of such viral vectors is [START_REF] Kim | Her SJ Retrovirus-mediated gene transfer of receptor activator of nuclear factor-kappaB-Fc prevents bone loss in ovariectomized mice[END_REF] extremely complex.

The results from the present study validate the non viral gene transfer method and the therapeutic interest of RANK-Fc in osteosarcoma. This methodology has previously proved its efficacy to deliver and express therapeutic gene in the same mouse model of osteosarcoma . In the present study, we demonstrate that when injected every week, the DNA-Lutrol complexes can induce RANK-Fc [START_REF] Lamoureux | Therapeutic relevance of osteoprotegerin gene therapy in osteosarcoma: prevention of bone resorption, inhibition of tumor progression, increase of animal survival[END_REF] ® over-expression both at local (muscle) and systemic levels in sufficient quantities to induce anti-bone resorption activity. The overproduction reached its maximum 7 days after injection and lasted for 15 days at the systemic level. The intra-muscular injection of the RANK-Fc/Lutrol complexes induces a local RANK-Fc transgene production that blocks bone resorption, as confirmed by radiography, ® histology, and quantified by micro-CT analysis in an osteolytic model of osteosarcoma. Moreover, the same inhibitory effect on bone osteolytic lesions has been obtained by adenoviral delivery of RANK-Fc in a rat osteocondensant osteosarcoma (data already published; ,

Given its role in osteoclastogenesis, it is likely that inhibition of osteosarcoma progression by RANK-Fc reflects, at least in part, its ability to inhibit bone resorption. Indeed, RANK-Fc has no direct activity on osteosarcoma cells, as demonstrated by studies on in vitro proliferation, migration, apoptosis, cell cycle or phenotype analysis. Furthermore, the observation that RANK-Fc did not diminish development of non osseous tumors (pulmonary tumor lesions induced by the same osteosarcoma POS-1 cells injected i.v.) suggests that the ability of RANK-Fc to inhibit osteosarcoma development was not caused by a direct effect on tumor but rather specific to factors in the bone microenvironment. Given that RANKL expression has been shown previously in the POS-1 tumor by immunohistochemical analyses , the present data suggest that inhibition of RANKL activity diminishes the osteosarcoma progression. Moreover, other experiments [START_REF] Lamoureux | Therapeutic relevance of osteoprotegerin gene therapy in osteosarcoma: prevention of bone resorption, inhibition of tumor progression, increase of animal survival[END_REF] performed in our laboratory have shown that osteosarcoma cells express RANK, and that RANKL is able to induce modulation of gene expression in these cells , , . Targeting RANKL is therefore a promising approach in bone tumor therapy. It has been demonstrated [24 38 39] that RANKL is implicated in the pathogenesis of bone metastasis at several levels: increased bone resorption as a result of excess RANKL results in the release of growth factors that facilitate tumor cell division and survival, and a recent study suggested a role for RANKL as a chemoattractant for certain cancer cells metastatic to bone . Furthermore, RANKL can stimulate both angiogenesis and endothelial

[40] [41]
cell survival , suggesting a role for RANKL in supporting vascularization of bone metastases. This role could also be extended to

[42]
osteosarcoma, which is a naturally highly vascularized tumor. As RANKL participates to the regulation of Treg function, it could also interfere in tumor response at this level , .

[43 44] To inhibit RANKL activity, three candidates are potentially promising: the decoy receptor OPG, the soluble receptor RANK-Fc constructed as the fusion of RANK extracellular domain with the constant region of the human IgG1, and antibodies directed against human RANKL. The advantage of using anti-RANKL antibodies is that they do not inhibit the TRAIL apoptosis pathway. In a recent randomized, double-blind, double dummy, active-controlled multicenter phase I clinical study, Body demonstrated the efficacy of et al [45] denosumab, A single subcutaneous dose of denosumab given to patients with multiple myeloma or bone metastasis from breast cancer yielded a dose dependent and sustained reduction in bone resorption. However, as this therapeutic agent cannot be used in immuno-competent models of bone tumors in rodents, RANK-Fc which is more specific of RANKL binding than OPG seems therefore a better therapeutic tool for these pathologies.

In conclusion, these data demonstrate that RANK-Fc delivered by non viral gene transfer is a promising therapeutic approach for osteolytic bone tumors such as osteosarcoma by targeting RANKL in the bone microenvironment.

Ackowledgements:

This study was financially supported by the Institut National du Cancer (INCa), the Fondation pour l Avenir de la Financial support: The same protocol was applied as in . The tumor volume (V) was calculated from the measurement of two perpendicular diameters, Figure 2 according to the following formula: V 0.5 L (S) , where L and S are respectively the largest and smallest perpendicular tumor diameters. the three groups over a 56 day-period.

  1 and pcDNA3.1-RANK-Fc were transfected by nucleofection into μ RAW 264.7 cells using the cell Line nucleofector Kit V program D-032 (AMAXA biosystems, K ln, Germany) following the ® ö manufacturer s recommendations. The transfection efficacy is controlled by quantification of 2 g of pmaxGFP transfected cells by ' μ ™ fluorescence microscopy (AMAXA biosystems).

μ

  quantified using the BCA (bicinchominic acid Copper II sulfate) test (Pierce Chemical Co., Rockford, IL, USA). Caspase-3 activity was + assessed on 10 l of cell lysate with the CaspACE assay kit (Promega, Madison, USA) following the manufacturer s recommendations.μ ™ '

  7 cells. Inhibition of osteoclast formation was analyzed by multinucleated cell counting after May Gr nwald Giemsa staining of pcDNA3.1 and pcDNA3.1-RANK-Fc transfected RAW 264.7 cells ü cultured in the presence of soluble RANKL. The results presented in show that RAW 264.7 cells transfected with Figure 1d pcDNA3.1-RANK-Fc induced a significant inhibition of multinucleated cell formation in the presence of RANKL as compared to cells transfected with pcDNA3.1 respectively 84.7 4 and 148.3 39.1 multinucleated cells (p 0.048) in the presence of 75 ng/ml RANKL, and [ ± ± = 62.7 7.4 and 272.7 30.3 (p 0.003) for 100 ng/ml RANKL .

  Fig 2b,c confirmed as RANK-Fc treatment induces a decrease of osteolytic lesions in the POS-1 model of osteosarcoma as compared to the in vivo control group (CT: without tumor).

± 3 , 3 ±

 33 4272.7 712.8 mm and 4504.1 2162.2 mm ( ). In addition, the incidence of animals bearing progressive tumors (tumor volume > ± 2000 mm ) is significantly lower at day 21 in the RANK-Fc treated animals (2/6) as compared to controls or pcDNA3.1 treated mice (

  Appliqu e (study n ET 6-418, Paris, France), the Ligue Contre le Cancer (Comit des Pays de la Loire) and the é » °é INSERM -R gion Pays de la Loire (grant for JR). FL was financially supported by the Association de Recherche sur le Cancer, GP by the é INCa. The authors wish to thank Christelle Bailly, Marie-No lle Herv and Cyril Le Corre from the Experimental Therapy Unit and Paul Pilet ë é (INSERM U791) from the microscopy platforms of the IFR26 (Nantes, France) for their technical assistance. We thank G. Odri for critical review of this manuscript.

Figure 1 Figure 2 Figure 3

 123 Figure 1 and validation of RANK-Fc transgene overexpression and biological activity In vitro in vivo Murine RANK-Fc (mRANK-Fc) transgene expression was assessed 48 hours after transfection in murine RAW 264.7 cells using a AMAXA nucleofector/pcDNA3-mRANK-Fc formulation at the transcript level by RT-PCR (a) and at the protein level by ELISA in the culture medium (b). formulations of pcDNA3-mRANK-Fc with Lutrol block copolymers were assessed. The formulations were prepared by In vivo, ® equivolumetric mixing block copolymers in water and DNA solution at the desired concentration (50 g/muscle). The DNA-Lutrol μ ® formulation was administrated in the tibial anterior muscle of both legs at weekly intervals. Murine RANK-Fc expression was analyzed 7 days post-injection by ELISA test in the muscle and in the serum (c). The biological activity of the mRANK-Fc transgene was assessed by its ability to block the RANKL induced multinucleated cell formation in RAW 264.7 cells (d). RAW 264.7 cells transfected by nucleofection with pcDNA3.1 or pcDNA3.1-mRANK-Fc (RANK-Fc) were cultured in the presence of 50, 75 and 100 ng/ml RANKL during 5 days to assess multinucleated cell formation. : p 0.048, pcDNA3.1/RANK-Fc vs pcDNA3.1 transfected RAW cells cultured with 75 ng/ml of * = RANKL. : p 0.003, pcDNA3.1-mRANK-Fc vs pcDNA3.1 transfected RAW cells cultured with 100 ng/ml of RANKL. Viability assay ** = using XTT test of MG63 cells cultured in the presence of 50 or 100 ng/ml of hTRAIL were realized with recombinant human RANK-Fc (100 ng/ml) which exhibits the same sequence than the RANK-Fc transgene produced (e). in vivo

3 - 1 3 -Figure 4

 3134 Figure 4 mRANK-Fc gene transfer inhibits osteosarcoma progression by preventing bone resorption TRAP staining was realized on 6 m-sections of tibias and tumors from pcDNA3.1 and RANK-Fc treated mice (a). Numerous TRAP positive μ osteoclasts were observed in POS-1 osteosarcoma bearing mice treated by pcDNA3.1 (arrows). Magnification: x320. Osteoclast numbers at the tumor-bone interface surface (OcS/TBIS; b).

Figure 5

 5 Figure 5 murine RANK-Fc exerts no direct effect on osteosarcoma cells in vitro The effects were assessed on POS-1 cell proliferation using an XTT assay as described in the Material & Methods section. POS-1 cells were treated for 24 to 72 hours with increasing concentrations of recombinant murine RANK-Fc (50 and 100 ng/ml), that exhibits the same sequence as the mRANK-Fc transgene used for experiments (a). To determine the RANK influence on tumor cell apoptosis, the in vivo caspase-3 activity was analysed in the cell lysate of POS-1 cells treated with 100 ng/ml mRANK-Fc for 24, 48 and 72 hours (b), CT : + staurosporin (1 M, 6 hours) was used as positive control; CT : POS-1 cells alone. Paralleled experiments were performed on cell cycle μ distribution by FACS analysis in the absence or the presence of 100 ng/ml mRANK-Fc during 24, 48 and 72 hours (c: as no effect could be detected, only the results obtained after 72 hours of incubation are shown).

Figure 6

 6 Figure 6 mRANK-Fc exerts no therapeutic effect in a model of tumor lesions that develop in lungs A model of pulmonary tumor lesions was induced in C3H/HeN mice by the intraveinous injection of 200 000 POS-1 cells in the retro-orbital vein. The Lutrol /DNA formulations were injected into both tibial anterior muscles once a week, beginning at 7 days before POS-1 cells ® injection up to 21 days post-implantation. The mice were separated into 3 groups (n 8) treated as follows: control mice received vehicle = (PBS) alone (CT), pcDNA3.1/Lutrol (pcDNA3.1) or pcDNA3.1-mRANK-Fc/Lutrol (RANK-Fc). The overall survival rate was compared ® ®

  39. Mori K , Berreur M , Blanchard F Receptor activator of nuclear factor-kappaB ligand (RANKL) directly modulates the gene expression profile of RANK-positive Saos-2 human osteosarcoma cells. Oncol Rep. 2007; 18: 1365-71 40. Jones DH , Nakashima T , Sanchez OH Regulation of cancer cell migration and bone metastasis by RANKL. Nature. 2006; 440: 692-6 41. Min JK , Kim YM , Kim YM Vascular endothelial growth factor up-regulates expression of receptor activator of NF-kappa B (RANK) in endothelial cells. Concomitant increase of angiogenic responses to RANK ligand. J Biol Chem. 2003; 278: 39548-57 42. Kim YM , Kim YM , Lee YM TNF-related activation-induced cytokine (TRANCE) induces angiogenesis through the activation of Src and phospholipase C (PLC) in human endothelial cells. J Biol Chem. 2002; 277: 6799-805 43. Antony PA , Restifo NP Do CD4 CD25 immunoregulatory T cells hinder tumor immunotherapy ?

	+	+	. J Immunother. 1997; 25: 202-6
	44. Curotto de Lafaille MA , Lafaille JJ CD4( ) regulatory T cells in autoimmunity and allergy +	. Curr Opin Immunol. 2002; 14: 771-8
	45. Body JJ Breast cancer: bisphosphonate therapy for metastatic bone disease. Clin Cancer Res. 2006; 12: 6258s-6263s

[START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF]

[START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF]

[START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF]

[START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF]

[START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF]

[START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF]

[START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF]

[START_REF] Shipman | Croucher PI Osteoprotegerin is a soluble decoy receptor for tumor necrosis factor-related apoptosis-inducing ligand/Apo2 ligand and can function as a paracrine survival factor for human myeloma cells[END_REF]


Omar Hamdoun

Fabien Moutarde

Bogdan Stanciulescu

Bruno Steux

PERSON RE-IDENTIFICATION IN MULTI-CAMERA SYSTEM BY SIGNATURE BASED ON INTEREST POINT DESCRIPTORS COLLECTED ON SHORT VIDEO SEQUENCES

Keywords: Video-surveillance, camera networks, person identification and tracking, re-identification, interest points

We present and evaluate a person re-identification scheme for multi-camera surveillance system. Our approach uses matching of signatures based on interest-points descriptors collected on short video sequences. One of the originalities of our method is to accumulate interest points on several sufficiently time-spaced images during person tracking within each camera, in order to capture appearance variability. A first experimental evaluation conducted on a publicly available set of low-resolution videos in a commercial mall shows very promising inter-camera person re-identification performances (a precision of 82% for a recall of 78%). It should also be noted that our matching method is very fast: ~ 1/8s for re-identification of one target person among 10 previously seen persons, and a logarithmic dependence with the number of stored person models, making reidentification among hundreds of persons computationally feasible in less than ~ 1/5 second.

INTRODUCTION AND RELATED WORKS

In many video-surveillance applications, it is desirable to determine if a presently visible person has already been observed somewhere else in the network of cameras. This kind of problematic is commonly known as "person reidentification", and a general presentation of this field can be found for instance in §7 of [START_REF] Tu | An intelligent video framework for homeland protection[END_REF]. Re-identification algorithms have to be robust even in challenging situations caused by differences in camera viewpoints and orientations, varying lighting conditions, pose variability of persons, and rapid change in clothes appearance.

A first category of person re-identification methods rely on biometric techniques (such as face or gait recognition), but in this paper we focus on the second group of methods, which use only global appearance. Among these, various approaches have been proposed: signature based on color histograms (such as in [START_REF] Park | ViSE: Visual Search Engine Using Multiple Networked Cameras[END_REF] or [START_REF] Pham | A multi-camera visual surveillance system for tracking reoccurrences of people[END_REF]), texture characteristics (see eg [START_REF] Lantagne | VIP : Vision tool for comparing Images of People[END_REF]), or panoramic model from multi-view [START_REF] Gandhi | Person Tracking and Reidentification: Introducing Panoramic Appearance Map (PAM) for Feature Representation[END_REF]. A more extensive survey of various kinds of object signatures can be found in [START_REF] Yilmaz | Object Tracking: A Survey[END_REF]. More recently some works have proposed the use of matching of interest points for establishing correspondance between objects, like cars in [START_REF] Arth | Object Reacquisition and Tracking in Large-Scale Smart Camera Networks[END_REF], and also for person re-identification as for instance in [START_REF] Gheissari | Person Reidentification Using Spatiotemporal Appearance[END_REF]. We here propose and evaluate a person re-identification scheme using matching of interest points collected in several images during short video sequences. The central point of our algorithm lies in the exploitation of image sequences, contrary to the method proposed in [START_REF] Gheissari | Person Reidentification Using Spatiotemporal Appearance[END_REF] where matches are done on image-to-image basis. This allows to get a more "dynamic" and multi-view descriptor than when using single image, and is a bit similar in spirit to the "averaging of interest-point descriptors throughout time sequence" used in the work by Sivic and Zisserman in [START_REF] Sivic | Video Google: A text retrieval approach to object matching in videos[END_REF], or the use (for content-based video matching) of interest point descriptors found in "video volumes" in [START_REF] Basharat | Content Based Video Matching Using Spatiotemporal Volumes[END_REF]. However, contrary to both of them, we do not use SIFT [START_REF] Lowe | Distinctive Image Features from Scale-Invariant Keypoints[END_REF] detector and descriptor, but a locally-developped (see §2) and particularly efficient variant of SURF [START_REF] Bay | SURF:Speeded Up Robust Features[END_REF]. This is also in contrast with Gheissari et al. in [START_REF] Gheissari | Person Reidentification Using Spatiotemporal Appearance[END_REF] who use a color-histogram of the region around interest points for their matching. Note also that we do not use a "vocabulary" approach as in [START_REF] Arth | Object Reacquisition and Tracking in Large-Scale Smart Camera Networks[END_REF] or [START_REF] Sivic | Video Google: A text retrieval approach to object matching in videos[END_REF], nor a "cluster" representation of descriptors as in [START_REF] Basharat | Content Based Video Matching Using Spatiotemporal Volumes[END_REF], but perform a direct very efficient matching between interest point descriptors.

DESCRIPTION OF OUR PERSON RE-IDENTIFICATION SCHEME

In this section we detail the algorithmic choices made in our person re-identification approach. Our method follows the classical scheme of Detection-Recognition-Identification (DRI) algorithms. It can be separated in two main stages: a learning phase, and a recognition phase, as illustrated on figure 2a and2b. The learning consists in taking advantage of tracking of a given person in a sequence from one camera, in order to extract interest points and their descriptors necessary to build the model consisting of a signature for each person.

The interest point detection and descriptor computation is done using "key-points" functions available in the Camellia image processing library developed in our lab (http://camellia.sourceforge.net).

These

Camellia key-points detection and characterization functions, which shall be described elsewhere in more details, are implementing a very quick variant inspired from SURF [START_REF] Bay | SURF:Speeded Up Robust Features[END_REF] but even faster. SURF itself is a recently proposed and extremely efficient alternative to the more classic and widely used interest point detector and descriptor SIFT [START_REF] Lowe | Distinctive Image Features from Scale-Invariant Keypoints[END_REF]. In Camellia "key-points" as in SURF, the detection of points is Hessian-based (rather than Laplacian-based) and uses integral image for a very efficient computation. The point descriptors, whose computation also takes advantage of integral image, are 64D vectors coarsely describing distribution of Haar-wavelet responses in 4x4 sub-regions around the interest point (see [START_REF] Bay | SURF:Speeded Up Robust Features[END_REF] for more details). Camellia key-points are an optimized implementation of a variant of SURF, using integer-only computations, which makes it particularly well-suited for embedding in camera hardware.

Our recognition step uses tracking of the to-beidentified-person, and models built during learning stage, in order to determine if the signature of the currently analyzed person is similar enough to one of those already "registered" for which signatures have been stored from other cameras. Our method can be detailed in the following 5 steps:

Model building

A signature is built for each detected and tracked person. In order to maximize the quantity of nonredundant information, we do not use every successive frame, but instead images sampled every half-second. The person's signature is obtained as the accumulation of interest point descriptors obtained on those images.

Query building

The query for the target persons is built on several evenly time-spaced images, exactly in the same way as the models, but with a smaller number of images (therefore collected in a shorter time interval).

Descriptor comparison

The metric used for measuring the similarity of interest point descriptors is the Sum of Absolute Differences (SAD).

Robust fast matching

A robust and very fast matching between descriptors is done by the employed Camellia function, which implements a Best Bin First (BBF) search in a KD-tree [START_REF] Beis | Shape indexing using approximate nearest-neighbour search in high-dimensional spaces[END_REF] containing all models.

Identification

The association of the query to one of the models is done by a voting approach: every interest point extracted from the query is compared to all models points stored in the KD-tree, and a vote is added for each model containing a close enough descriptor; finally the identification is made with the highest voted-for model.

EXPERIMENTAL EVALUATION

Direct comparison with other existing approaches is not easy, as to our knowledge there is no available benchmark for evaluation of person re-identification. We therefore decided to conduct a first experimental evaluation of our proposed method on a publicly available series of videos (http://homepages.inf.ed.ac.uk/rbf/CAVIAR) showing persons recorded in corridors of a commercial mall. These videos (collected in the context of European project CAVIAR [IST 2001 37540]) are of relatively low resolution, and include images of the same 10 persons seen by two cameras with very different viewpoints (see figure 3).

The model for each person was built with 21 evenly timespaced images (separated by half-second interval), and each query was built with 6 images representing a 3 second video sequence (see figure 4). Camera color potential variability is avoided by working in grayscale. Illumination invariance is ensured by histogram equalization of each person's bounding-box. The resulting performance, computed on a total of 760 query video sequences of 3 seconds, is presented in table 1, and illustrated on a precision-recall curve on figure 5. The main tuning parameter of our method is the "score threshold", which is the minimum number of matched points between query and model required to validate a re-identification. As expected, it can be seen that increasing the matching score threshold, increases the precision but at the same time lowers the recall. Taking into account the relatively low image resolution, our person re-identification performances are good, with for instance 82% precision and 78% recall when the score threshold is set to a minimum of 15 matching interest points between query and model. Note that we here consider only the best match (if matching score over threshold).

For comparison, the best result reported in [START_REF] Gheissari | Person Reidentification Using Spatiotemporal Appearance[END_REF] on a set of videos including 44 different persons is 60% correct best match (and they achieve 80% only when considering if true match is included in the 4 best matches). It is of course difficult to draw any strong conclusion from that, as the video sets are completely different, and ours contain only 10 different persons v.s. 44 in work presented in [START_REF] Gheissari | Person Reidentification Using Spatiotemporal Appearance[END_REF]. The high execution speed of our re-identification method should also be emphasized: the computing time is less than 1/8 s per query, which is negligible compared to the 3 seconds necessary to collect the six images separated by ½ s.

Score

More importantly, due to the logarithmic complexity of the KD-tree search with respect to the number of stored descriptors, the query processing time should remain very low even when large number of person models are stored. In order to verify this, we compared the re-identification computation time when varying the number of images used in model sequences, as reported in table 2. Indeed figure 6 shows that the re-identification computation time scales logarithmically with number of stored descriptors. Since the number of stored descriptors is roughly proportional to the number of images used, if 100 to 1000 person models were stored instead of 10 (with ~ 20 images for each), the KDtree would contain 10 to 100 times more key-points, i.e. ~ 0.25 to 2.5 millions of descriptors. Extrapolating a little from figure 6, we therefore expect a query computation time < 1/5 s for a re-identification query among hundreds of registered person models. However, the reliability of reidentification among such a high number of persons remains to be verified.

Number of images used in model sequences

CONCLUSIONS AND PERSPECTIVES

We have presented a new person re-identification approach based on matching of interest-points collected in query short video sequence with those collected in longer model videos used for each previously seen person.

Our first experiments on low-resolution videos have shown very promising inter-camera person re-identification performances (a precision of 82% for a recall of 78%).

It should be noted that our matching method is very fast, with typical computation time of 1/8s for re-identification of one target person among 10 stored signatures for previously seen persons in other cameras. Moreover, this reidentification time scales logarithmically with the number of stored person models, so that the computation time would remain below 1/5 second for a real-world-sized system potentially involving tracking of hundreds of persons.

More thorough evaluations have to be done and are currently under progress, including on other video corpus, and especially with more registered persons, in order to assess re-identification reliability among large number of persons. Also, our re-identification scheme will soon be integrated in the global video-surveillance processing, which will allow to restrict interest points inside the person area, therefore excluding most background key-points, which should improve significantly the performance of our system. Finally, we also hope to further increase performances, either by exploiting relative positions of matched interest points, and/or by applying a machine-learning to the set of "models" built for respective registered persons.

Figure 1 :

 1 Figure 1: examples of successful matching of interest points for a given person seen under 2 different viewpoints and scales(left), with pose change (middle), and with clothe appearance and illumination change (right).

Figure 2a :

 2a Figure 2a: Schematic view of model building. For each tracked person, interest points are collected every 10 frames, and the person's signature is the union of all these key-points stored in a global KD-tree.

Figure 2b :

 2b Figure 2b: Schematic view of re-identification of a query.Interest points are collected similarly during tracking of a person to be re-identified, appearing in another camera, and a vote is made according to the respective identifications associated to all matching key-points.

Figure 3 :

 3 Figure 3: Typical low resolution views of the persons used as part of the models (top-line), and typical views of the same person in the other camera from which we try to re-identify.

Figure 4 :Figure 5 :

 45 Figure 4:Visualization of detected key-points on 15 of the 21 images for one person's model (top line), and on the 6 images of a successfully matched re-identification query for the same person (bottom-line).

threshold for query-model matching (number of matched points)

		Precision	Recall
		(%)	(%)
	40	99	49
	35	97	56
	30	95	64
	25	90	71
	20	85	75
	15	82	78
	10	80	79
	5	80	80
	Table 1: precision and recall, as a function of the score
	threshold for query-model matching
	(ie minimum number of similar interest points).

identification computation time when varying number of images in models

	Computation time (ms)	190 Re-120 130 140 150 160 170 180
		1000	10000	100000	1000000
			Number of stored keypoints
	Figure 6:Re-identification computation time as a
		function of stored key-point descriptors;
		the dependence is clearly logarithmic
					Total number	Computation time
					of stored	for
					interest points	re-identification
					(ms)
					1	1117	123
					2	2315	132
					4	5154	141
					8	11100	149
					16	22419	157
					24	32854	161
					Table 2: total number of interest points, and
					re-identification computation time when varying the number
					of images used for the model for each stored person


Omar Hamdoun

Alexandre Bargeton
email: alexandre.bargeton@ensmp.fr

Fabien Moutarde
email: fabien.moutarde@ensmp.fr

Benazouz Bradai
email: benazouz.bradai@valeo.com

Lowik Chanussot

DETECTION AND RECOGNITION OF END-OF-SPEED-LIMIT AND SUPPLEMENTARY SIGNS FOR IMPROVED EUROPEAN SPEED LIMIT SUPPORT

Keywords: Advanced Driving Assistance System (ADAS), Traffic Sign Recognition, Speed Limit

We present two new features for our prototype of European Speed Limit Support system: detection and recognition of end-of-speed-limit signs, as well as a framework for detection and recognition of supplementary signs located below main signs and modifying their scope (particular lane, class of vehicle, etc…). The end-of-speed-limit signs are globallyrecognized by a Multi-Layer Perceptron (MLP) neural network. The supplementary signs are detected by applying a rectangle-detection in a region below recognized speed-limit signs, followed by a MLP neural network recognition. A common French+German end-of-speed-limit signs recognition has been designed and successfully tested, yielding 82% detection+recognition. Results for detection and recognition of a first kind of supplementary sign (French exit-lane) are already satisfactory (78% correct detection rate), and our framework can easily be extended to handle other types of supplementary signs. To our knowledge, we are the first team presenting results on detection and recognition of supplementary signs below speed signs, which is a crucial feature for a reliable Speed Limit Support.

INTRODUCTION AND RELATED WORKS

An assistant constantly informing the driver of the current speed limit, or a smart Adaptive Cruise Control (ACC) ensuring the respect of this speed limit, are some of the currently emerging important driving assistance functions. Most current GPS navigators now include a function to inform the driver of the supposed current speed-limit. However speed-limit information extracted from GPS cartographic data is neither always complete nor systematically up-to-date. Moreover, temporary speed limits for road works, and variable speed limits, are by definition not included in pre-defined digital cartographic data. And when a roadwork temporary speed-limit is visually detected, it is then essential to also correctly detect the end-of-speed-limit sign generally posted at the roadwork end. Also some traffic signs along roads provide specific speed limits that are applicable, for instance, only to a particular lane or only to certain vehicle categories, those specificities being mentioned on "supplementary signs" (sometimes also called "complementary" or "supplemental" signs) located below the main sign. For all these reasons, a visual real-time speed-limit sign detection and recognition system is a mandatory complement to GPS systems for designing high-level advanced driving assistance systems such as Speed Limit Support (SLS) and smart ACC. And this visual sign recognition should take into account end-of-speed-limit signs and supplementary signs as well. Traffic Signs detection and Recognition (TSR) usually involves two main steps: 1/ detection of potential traffic signs in the image, based on the common shape/color design of sought traffic signs; 2/ classification of the selected regions of interest (ROI) for identifying the exact type of sign, or rejecting the ROI. Many TSR systems (e.g. [START_REF] Bahlmann | A System for Traffic Sign Detection, Tracking, and Recognition Using Color, Shape, and Motion Information[END_REF], [START_REF] Broggi | Real Time Road Signs Recognition[END_REF]) use color information to make detection step easier. But as noted and advocated in [START_REF] Gavrila | Traffic sign recognition revisited[END_REF] and [START_REF] Barnes | Real-time radial symmetry for speed sign detection[END_REF], using only shape information in grayscale improves robustness for operation in dark or night condition. This is what we do in our Speed Limit Support (SLS) prototype, already presented in [START_REF] Moutarde | Robust on-vehicle real-time visual detection of American and European speed limit signs, with a modular Traffic Signs Recognition system[END_REF] and [START_REF] Moutarde | Modular Traffic Sign Recognition applied to on-vehicle real-time visual detection of American and European speed limit signs[END_REF], which relies on digit extraction and identification for recognition step (contrary to most TSR systems which use global recognition as in [START_REF] Bahlmann | A System for Traffic Sign Detection, Tracking, and Recognition Using Color, Shape, and Motion Information[END_REF] [START_REF] Zhang | Traffic sign recognition using Discriminant analysis based Algorithms[END_REF]). Our current SLS system is quite robust and fast for detecting and recognizing signs for beginning of speed-limit [5][7]. It should be noted that, thanks to our digit-recognition-based approach as well as to our efficient (patented) rectangle detection, we were probably, to our knowledge, the first research team reporting satisfying results on U.S. speed sign recognition (see [START_REF] Moutarde | Robust on-vehicle real-time visual detection of American and European speed limit signs, with a modular Traffic Signs Recognition system[END_REF], a year before more recent work by [START_REF] Keller | Real-time Recognition of U.S. Speed Signs[END_REF] which still have unacceptably high false alarm rate). We also have recently significantly improved our European speed sign recognition by using a global number segmentation before applying digit recognition [START_REF] Bargeton | Improving pan-European speed-limit signs recognition with a new "global number segmentation" before digit recognition[END_REF]. However, in order to design a complete Speed Limit Support system, we need to include proper recognition of end of speed limits as well, and also detection and recognition of potential complementary signs under speed-limit signs, as presented in this paper.

[2] [3] [4]

END OF SPEED LIMIT SIGNS DETECTION AND RECOGNITION

The potential end-of-speed-limit signs are detected by the same Hough-based circle detection as the one we use for speed-limit signs. The main challenge is the recognition step, because there are many subtypes of end-of-speed-limit signs in each country, and their designs can be quite different in various E.U. countries. Another potential difficulty arises from the need to avoid confusion with similar signs such as end-of-no-passing. Finally it is difficult (and nearly impossible) to collect a large number of examples properly covering, for each sign class, the potential variability in size, orientation, etc… We therefore created a database of synthetic examples. Positive examples were generated from each end-of-speed-limit sign prototype by randomized controlled transformations covering as much as possible the various expected appearances, and negative examples were either synthetically generated (for potentially confusing signs) or extracted from videos. The example were all histogram-equalized and normalized to a standard 16x16 size, as illustrated in figure 1. Table 1. First evaluation of European end-of-speedlimit sign detection and recognition on French+German roads.

Fig. 2 Illustration of correct recognition of end-of-speed-limit signs in Germany (left) and in France (right)

A first systematic evaluation was done on a small set of recorded French and German videos (see figure 2) containing 22 end-of-speed-limit signs. The quantitative results obtained, given in table 1, are not perfect (82% global recognition rate) but already quite satisfactory.

SUPPLEMENTARY SIGNS DETECTION AND RECOGNITION

One of the main difficulties is that the supplementary signs may have various positions, width/height ratios, and even relative size. We therefore decided to define a relatively wide "search region" below each recognized speed-limit sign. These searched regions are histogram-equalized before we apply inside them our original (and Valeo-patented) rectangledetection developed for American speed-limit rectangular signs detection (see [START_REF] Moutarde | Robust on-vehicle real-time visual detection of American and European speed limit signs, with a modular Traffic Signs Recognition system[END_REF] or [START_REF] Moutarde | Modular Traffic Sign Recognition applied to on-vehicle real-time visual detection of American and European speed limit signs[END_REF]).

Rectangle detection results are illustrated on figure 3. There are indeed some spurious detected rectangles, but they shall be efficiently filtered by the posterior classification step. As a first test, we focused on French exit-lane supplementary signs, which exist in various "flavours", some of them square, and others with rectangular shape. We decided that the most convenient way to deal with that was to systematically resize the potential supplementary sign to a common (experimentally chosen) 12x12 square size. The classifier itself is a MLP neural network with 12x12=144 inputs, and only 1 output neurons designed to output +1 for all positive examples of exit-lane supplementary signs and -1 for any other image. The hidden layer size was set to 10 neurons, by comparing, on validation set, correct classification rates for several hidden layer sizes. A first evaluation was done on a set of recorded French videos containing 50 speed-limit signs, among which 18 with an exit-lane supplementary sign below.

The results obtained are illustrated on figure 4, and quantified in table 2. The correct detection rate of 78% is already quite satisfactory for a first implementation, and further improvement to increase precision by collecting more negative examples is underway.

Fig. 1 .

 1 Fig. 1. Some synthetic examples (top line), and their normalized to 16x16 version (bottom line)

Fig. 3 .Table 2 .Fig. 4 .

 324 Fig. 3. Illustration of research zone below recognized speed-limit signs, and of rectangle-detection inside: on the left, a supplementary sign is detected, on the right spurious rectangles are detected but shall be eliminated by recognition step

Acknowledgements: This work is part of a research project that has received the "Jeune Chercheur -ITS Bretagne" prize, attributed in 2008 to PhD student Alexandre Bargeton.

CONCLUSIONS AND PERPECTIVES

We have presented the successful introduction in our prototype Speed Limit Support system of 2 new important features: recognition of end-of-speed-limit signs, and detection and recognition of a first type of supplementary sign modifying the scope of its above speed-limit sign. The performance of our first version of detection and recognition of end-of-speed-limit signs is already good (82%), but can certainly be improved, which we are currently working on. Also, the current version of this feature has been developed and tested only on French and German signs. Evaluation of pan-European generalization of this feature is currently under way, with promising results in Italy. Regarding supplementary sign, our prototype currently handles (with 78% correct detection rate) only the French "exit-lane" sub-sign. However, our framework and methodology presented here for detection and recognition of supplementary sign could easily be extended to handle more kinds of supplementary signs. To our knowledge, we are the first team presenting results on detection and recognition of supplementary signs below speed signs, which is a crucial feature for a reliable Speed Limit Support. The final correct handling of detected speed signs taking supplementary signs into account will most probably require to know if the vehicle does or not drive on the outgoing exit-lane, which should be easy to do by fusion of vision information with GPS information, a technique for which we have already promising results [START_REF] Lauffenburger | Navigation and Speed Signs Recognition Fusion for Enhanced Vehicle Location[END_REF].