David Hamani
email: david.hamani@unilim.fr

Lyna Torzuoli

Assil Bouzid

Philippe Thomas

Olivier Masson

Bond valence parameters for Te 4+ and F -/S 2-/Se 2- New and refined bond valence parameters for Te 4+ -F -, Te 4+ -S 2-and Te 4+ -Se 2-ion pairs

Keywords: bond valence parameters, tellurium Te(IV), non-oxide anions

New and refined bond valence parameters related to ion pairs constituted of the tellurium Te 4+ cation and nonoxide X n-anions (X = F, S or Se) are proposed. After a selection of specific crystalline structures, the optimization of the bond valence parameters R and b with a cutoff distance is carried out by minimizing the root mean square deviation of the Te 4+ cation valence. The results are R = 1.728 Å and b = 0.622 Å with cutoff = 5.3 Å for the Te 4+ -F -pair and R = 2.444 Å and b = 0.387 Å with cutoff = 4.5 Å for the Te 4+ -S 2-pair. These parameters lead to a lower dispersion of the calculated valences around the formal valence compared to that obtained with the parameters available in the literature. As for the new set related to the Te 4+ -Se 2-pair, we find R = 2.578 Å and b = 0.296 Å with cutoff = 3.7 Å.

Short summary of max. 250 characters and a figure for the Table of Contents.

New and refined bond valence parameters for Te 4+ -X n-ion pairs are proposed (X = F, S or Se). The results are R = 1.728 Å and b = 0.622 Å with cutoff = 5.3 Å for the Te 4+ -F -pair ; R = 2.444 Å and b = 0.387 Å with cutoff = 4.5 Å for the Te 4+ -S 2-pair ; R = 2.578 Å and b = 0.296 Å with cutoff = 3.7 Å for the Te 4+ -Se 2-pair. Frequency Te 4+ valence (v.u.)

Brese & O'Keeffe [START_REF] Brese | Bond-valence parameters for solids[END_REF] This work with b fixed at 0.37 Å This work

Introduction

The bond valence sum rule is widely used in crystal chemistry as a verification and predictive tool for crystalline structures [START_REF] Brown | The Chemical Bond in Inorganic Chemistry: The Bond Valence Model[END_REF]. The valence of an ion i is calculated by adding up the bond valences Sij between i and its neighbouring ions j of opposite charge, by applying the Brown and Altermatt [START_REF] Brown | Bond-valence parameters obtained from a systematic analysis of the Inorganic Crystal Structure Database[END_REF][START_REF] Altermatt | The automatic searching for chemical bonds in inorganic crystal structures[END_REF] relation given by:

𝑆 𝑖𝑗 = 𝑒𝑥𝑝 ( 𝑅 𝑖𝑗 -𝑑 𝑖𝑗 𝑏 )
Where dij is the bond length and Rij is a parameter specific to the i-j pair whose value is the bond length corresponding to one valence unit. The parameter b is often considered as a universal constant equal to 0.37 Å so that Rij is expressed as follows:

𝑅 𝑖𝑗 = 𝑏 × 𝑙𝑛 ( 𝑉 𝑖 ∑ 𝑒𝑥𝑝 (- 𝑑 𝑖𝑗 𝑏 ) 𝑗 )
Where Vi is the valence of the ion i, i.e. its formal oxidation state. Rij is generally determined and used by dealing with a cutoff distance beyond which an anion is no longer considered to be bonded to a cation; in practice a cutoff value of about 3 Å is often used [START_REF] Brown | The Chemical Bond in Inorganic Chemistry: The Bond Valence Model[END_REF][START_REF] Brown | Recent developments in the methods and applications of the bond valence model[END_REF].

Several authors recommended to use different values for the parameter b [START_REF] Adams | Relationship between bond valence and bond softness of alkali halides and chalcogenides[END_REF][START_REF] Bv | version 0.96[END_REF][START_REF] Sidey | Alternative presentation of the Brown-Wu bond-valence parameters for some s 2 cation/O 2ion pairs[END_REF][START_REF] Krivovichev | Derivation of bond-valence parameters for some cation-oxygen pairs on the basis of empirical relationships between r0 and b[END_REF][START_REF] Gagné | Comprehensive derivation of bond-valence parameters for ion pairs involving oxygen[END_REF]. Adams [START_REF] Adams | Relationship between bond valence and bond softness of alkali halides and chalcogenides[END_REF] has shown that the value of b depends on the chosen cutoff distance. In particular, the parameters determined relying on the first and second coordination shells can differ significantly from those determined using only the first coordination shell while adding the third and fourth coordination shells does not modify the parameters. Chen and Adams [START_REF] Chen | Bond softness sensitive bond-valence parameters for crystal structure plausibility tests[END_REF] emphasized that the first coordination shell can be an effective quantity to improve the bond valence parameters of a cationanion pair by revising the parameter R while keeping the same parameter b value from Adams [START_REF] Adams | Relationship between bond valence and bond softness of alkali halides and chalcogenides[END_REF][START_REF] Bv | version 0.96[END_REF]. Other studies notably focused on structures that contain cations carrying lone electron pairs (see [START_REF] Krivovichev | Are the compressive effects of encapsulation an artifact of the bond valence parameters?[END_REF][START_REF] Locock | Revised Tl(I)-O bond valence parameters and the structures of thallous dichromate and thallous uranyl phosphate hydrate[END_REF][START_REF] Sidey | Accurate bond-valence parameters for the Bi 3+ /Brion pair[END_REF][START_REF] Hu | A new approach to bond valence parameters for Pb(II)-halide bonds[END_REF][START_REF] Mills | Revised values of the bond valence parameters for [6] Sb(V)-O and [3-11] Sb(III)-O[END_REF][START_REF] Christy | Effect of lone-pair stereoactivity on polyhedral volume and structural flexibility: application to Te IV O6 octahedra[END_REF][START_REF] Hamani | Localization and steric effect of the lone electron pair of the tellurium Te 4+ cation and other cations of the p-block elements. A systematic study[END_REF]). The Te 4+ cation belongs to this category and the determination of accurate bond valence parameters mainly focused on the most common Te 4+ -O 2-linkages [START_REF] Brown | Bond-valence parameters obtained from a systematic analysis of the Inorganic Crystal Structure Database[END_REF][START_REF] Bv | version 0.96[END_REF][START_REF] Sidey | Alternative presentation of the Brown-Wu bond-valence parameters for some s 2 cation/O 2ion pairs[END_REF][START_REF] Gagné | Comprehensive derivation of bond-valence parameters for ion pairs involving oxygen[END_REF][START_REF] Chen | Bond softness sensitive bond-valence parameters for crystal structure plausibility tests[END_REF][START_REF] Mills | Revised values of the bond-valence parameters for Te IV -O, Te VI -O and Te IV -Cl[END_REF] in addition to linkages with other anion types such as Cl - [START_REF] Bv | version 0.96[END_REF][START_REF] Chen | Bond softness sensitive bond-valence parameters for crystal structure plausibility tests[END_REF][START_REF] Mills | Revised values of the bond-valence parameters for Te IV -O, Te VI -O and Te IV -Cl[END_REF][START_REF] Brese | Bond-valence parameters for solids[END_REF], Br - [START_REF] Bv | version 0.96[END_REF][START_REF] Chen | Bond softness sensitive bond-valence parameters for crystal structure plausibility tests[END_REF][START_REF] Brown | Private communication[END_REF] or I - [START_REF] Bv | version 0.96[END_REF][START_REF] Chen | Bond softness sensitive bond-valence parameters for crystal structure plausibility tests[END_REF][START_REF] Sidey | X-ray Rietveld structure refinement and bond-valence analysis of Cs2TeI6[END_REF]. As outlined below, handling R, b and cutoff allows us to tend towards valences closer to those theoretically expected and to ensure the validity of structures previously considered questionable.

In this paper, we propose bond valence parameters for the Te 4+ -F -, Te 4+ -S 2-and Te 4+ -Se 2-ion pairs. For Te 4+ -F -, we aim at improving the parameters with respect to the only set established by Brese & O'Keeffe back in 1991 [START_REF] Brese | Bond-valence parameters for solids[END_REF]. For Te 4+ -S 2-, the unique parameter set available to us is from a private communication from Brown that should be used with caution according to the author himself [START_REF] Brown | Private communication[END_REF]. For Te 4+ -Se 2-, to the best of our knowledge no valence parameters exist in the literature.

In section 2, we present the method used to determine these three parameter sets. In section 3, we discuss the results following the application of these new parameters to structures of inventoried crystalline phases.

Methodology

The crystalline structures were selected from the Inorganic Crystal Structure Database (ICSD [START_REF]Inorganic Crystal Structure Database (ICSD)[END_REF]) using the following criteria: a) Entry from experimental inorganic structures; b) Data of high quality according to the ICSD, i.e. temperature factors given, standard deviation given for cell parameters, R-value specified, no unusual difference between calculated and measured densities; c) No hydrogen element; d) Only one anion type per structure so that the Te 4+ valence is only influenced by the bonds with one anion type (F -, Se 2-or S 2-); e) Only one ion type per site with full occupation; f) Crystal structure determined at temperature in between 278 and 308 K and at ambient pressure; g) No interatomic distances shorter than 70% of the sum of the ionic radii (using the Shannon effective ionic radii [START_REF] Shannon | Revised effective ionic radii and systematic studies of interatomic distances in halides and chalcogenides[END_REF]). Cation-cation, cation-anion and anion-anion distances were checked. The bond valence parameters were determined by minimising the root mean square deviation (RMSD) of the valence (see [START_REF] Brown | The Chemical Bond in Inorganic Chemistry: The Bond Valence Model[END_REF][START_REF] Gagné | Comprehensive derivation of bond-valence parameters for ion pairs involving oxygen[END_REF][START_REF] Locock | Revised Tl(I)-O bond valence parameters and the structures of thallous dichromate and thallous uranyl phosphate hydrate[END_REF][START_REF] Mills | Revised values of the bond valence parameters for [6] Sb(V)-O and [3-11] Sb(III)-O[END_REF]):

𝑅𝑀𝑆𝐷 = √ ∑ (∑ 𝑆 𝑖𝑗 𝑗 -𝑉 𝑖 ) 2 𝑚 𝑚
With m the number of non-equivalent positions of cation i in the whole selected structures. In the present work, given the very small number of structures containing only one cation type and one anion type, the bond valence sum rule is applied on Te 4+ only, not on the anion. Thereby, the obtained bond valence parameters remain independent of other bond valence parameters involving the anion type considered and another cation type different from Te 4+ .

Results and discussion

We present below the results of the bond valence parameters obtained for the three Te 4+ -F -, Te 4+ -S 2-and Te 4+ -Se 2-pairs. The details for the anion valences are gathered in the Appendix.

The case of Te 4+ -F -

The bond valence parameters were adjusted using 13 non-equivalent Te 4+ positions from 11 structures and 2448 Te 4+ -F -distances up to 10 Å (see Table 1, Table 2 and Figure 1). The application of the procedure reaches a minimal RMSD value of 0.086 for R = 1.724 Å, b = 0.625 Å and cutoff = 5.6 Å. These parameters lead to an average valence of 3.998 v.u. for Te 4+ . As reported by Adams [START_REF] Adams | Relationship between bond valence and bond softness of alkali halides and chalcogenides[END_REF], the parameters R and b depend on each other, i.e. for a short cutoff (2.6 Å), a minimal R value is found so the b value increases in order to maintain valences close to 4 v.u. (see Figure 2). The optimized parameters are found when their values converge beyond a cutoff distance of 5.6 Å in that case, this value encompassing the first and second coordination shells (see Figure 1). Frequency Te 4+ -F -distances (Å)

Comparison with former bond valence parameters

Our results are compared to those calculated with two other parameter sets. The unique set identified in the literature for the Te 4+ -F -pair was proposed by Brese and O'Keeffe [START_REF] Brese | Bond-valence parameters for solids[END_REF] with R = 1.87 Å and b = 0.37 Å but for which the cutoff distance was not specified. First, we optimized this set following our methodology so that the results are compared in the most relevant way possible with results from other sets. For that, we carried out the optimization of the cutoff distance by reaching a minimal RMSD of 0.245 for the 11 structures with only one anion type. In that case, a cutoff of 3.7 Å is obtained. These parameters entail average Te 4+ and F -valences of 4.108 v.u. (RMSD = 0.229) and 1.018 v.u. (RMSD = 0.108), respectively. For the overall 33 structures, the average Te 4+ valence is 3.970 v.u. (RMSD = 0.245).

For comparison, we also used another parameter set in which R and cutoff were optimized while b was fixed at 0.37 Å. This led to R = 1.861 Å and cutoff = 3.3 Å for an optimization carried out from the 11 structures with one anion type. In that case the average Te 4+ and F -valences are equal to 3.991 v.u. (RMSD = 0.198) and 0.998 v.u.

(RMSD = 0.101), respectively, expressing that the latter set is of lower quality than the set with optimized R, b and cutoff but of better quality than that with the parameters from Brese and O'Keeffe. However, the results diverge from the ideal valence when considering the structures with more than one anion type, leading to an average Te 4+ valence of 3.920 v.u. for the overall 33 structures. The distributions of the Te 4+ valences are gathered in Figure 3 and one can notice the smaller dispersion for the proposed set with optimized R, b and cutoff, the sidelined valences (assuming values inferior or superior to 0.5 v.u. from the ideal valence) being found for sets in which b is fixed at 0.37 Å.

The case of Te 4+ -S 2-

Considering the methodology described above, the refinement of the bond valence parameters was carried out for the Te 4+ -S 2-pair dealing with 7 non-equivalent Te 4+ positions in 6 structures with one anion type and 561 Te 4+ -S 2- distances up to 10 Å (see Table 3 and Table 4). This led to a minimal RMSD value of 0.070 for R = 2.444 Å, b = 0.387 Å and cutoff = 4.6 Å. The corresponding average Te 4+ and S 2-valences are equal to 3.998 v.u. and 2.056 v.u. respectively. This set applied to a unique additional structure with more than one anion type led to a Te 4+ valence equal to 3.962 v.u. for the overall 7 structures. Brown [START_REF] Brown | Private communication[END_REF] proposed a parameter set with R = 2.44 Å and b = 0.37 Å for which, as above, we optimized the cutoff value and obtained 4.5 Å. We also determined a parameter set by b at 0.37 Å and found values close to those of Brown with R = 2.442 Å and cutoff = 4.5 Å. The values of R, b and cutoff for these three sets are alike, the set proposed in the present work slightly improving the Te 4+ valence only mostly because of a procedure with a precision of three decimal digits. Following the same procedure, the bond valence parameters for the Te 4+ -Se 2-pair are R = 2.579 Å and b = 0.304 Å with a cutoff distance of 4.6 Å (see Table 5 andTable 6). A minimal RMSD value of 0.029 was reached by considering 4 non-equivalent Te 4+ positions within 4 structures containing 301 Te 4+ -Se 2-distances up to 10 Å. An additional parameter set with b fixed at 0.37 Å was also determined but the resulting RMSD is larger with a value of 0.070. One can note that no additional structure with more than one anion type fulfils the above selection criteria in that case.

Conclusion

The bond valence parameters R and b with a cutoff distance are revised from a procedure using the root mean square deviation of the Te 4+ valence for the Te 4+ -F -(R = 1.728 Å and b = 0.622 Å with cutoff = 5.3 Å) and Te 4+ -S 2-(R = 2.444 Å and b = 0.387 Å with cutoff = 4.5 Å) ion pairs. The new parameters lead to a lower dispersion of the calculated valences compared to that obtained with the parameters of the literature. The new ones also remove the ambiguity related to the validity of some crystalline structures that apparently do not present structural singularities. Following the same procedure, new parameter set is proposed for the Te 4+ -Se

Figure 2 :

 2 Figure 2: Influence of the cutoff value (a, b) on the bond valence parameters b and R and (c) on the root mean square deviation (RMSD) for 11 structures containing one anion type, F -.The parameters R, b and cutoff were also used to check the bond valence sums for all the anions F -, corresponding to 62 non-equivalent positions in the 11 structures. Note that for those calculations, the bond valence parameters associated to the M x+ -F -pairs (M x+ = cation different from Te 4+ ) were extracted from the Adams' database[START_REF] Bv | version 0.96[END_REF]. The average F -valence is equal to 1.001 v.u. (RMSD = 0.062), very close to the formal value of 1 v.u.. Then we extended the application of this refined parameter set to structures containing more than one anion type, still considering the above selection criteria (except point d)). This corresponds to 31 additional non-equivalent Te 4+ positions from 22 structures. The average calculated Te 4+ valence is equal to 4.064 v.u. (with RMSD = 0.181) in the overall 44 positions from 33 structures.

Figure 3 :

 3 Figure 3: Distribution of the Te 4+ valence calculated with different bond valence parameter sets of the Te 4+ -F -pair for 33 structures.

Table 1 :

 1 Comparison of the Te 4+ and F -valences obtained from different parameter sets for the Te 4+ -F -pair.

	Brese & O'Keeffe [19]	This work with b fixed at 0.37 Å	This work
	R, b, cutoff (Å)
	1.87, 0.37, 3.7	1.861, 0.37, 3.3	1.724, 0.625, 5.6

Table 2 :

 2 Comparison of the Te 4+ valences obtained from different parameter sets for the Te 4+ -F -pair for 11 structures containing one anion type, F -(colourless) and 22 structures containing several anion types (in grey).

	ICSD #	Structure	Non-equivalent Te 4+ position #	Brese & O'Keeffe [19]	Te 4+ valence (v.u.) This work with b fixed at 0.37 Å	This work
	16108	Sb2TeF14	1	3.794	3.692	3.882
	81862	BaTe2F10	1	4.136	4.020	4.141
	81865	PbTeF6	1	3.750	3.660	3.980
	84364	KTe2F9	1	4.032	3.935	4.004
	84364	KTeF5	1	4.230	4.128	3.933
			2	4.118	4.003	3.965

Table 3 :

 3 Comparison of the average Te 4+ and S 2-valences obtained from different parameter sets for the Te 4+ -S 2-pair.

	Brown [20]	This work with b fixed at 0.37 Å	This work
	R, b, cutoff (Å)
	2.44, 0.37, 4.5	2.442, 0.37, 4.5	2.444, 0.387, 4.6

Table 4 :

 4 Comparison of the Te 4+ valences obtained from different parameter sets for the Te 4+ -S 2-pair for 6 structures containing one anion type, S 2-(colourless) and 1 structure containing several anion types (in grey).

	ICSD #	Structure	Non-equivalent Te 4+ position #	Brown [20]	Te 4+ valence (v.u.) This work with b fixed at 0.37 Å	This work

The case of Te 4+ -Se 2-

Table 5 :

 5 Comparison of the average Te 4+ and Se 2-valences obtained from different parameter sets for the Te 4+ -Se 2-pair.

	This work with b fixed at 0.37 Å	This work
	R, b, cutoff (Å)
	2.587, 0.37, 4.7	2.579, 0.304, 4.6

Table 6 :

 6 Comparison of the Te 4+ valences obtained from different parameter sets for the Te 4+ -Se 2-pair for 4 structures containing one anion type, Se 2-(no structure containing several anion types).

	ICSD #	Structure	Non-equivalent Te 4+ position #	Te 4+ valence (v.u.) This work with b fixed at 0.37 Å This work
	63011	Na2TeSe3 (mC48)	1	3.957	3.955
	63012	K2TeSe3	1	3.945	4.026
	415121	Li2TeSe3	1	4.121	4.025
	430313	Na2TeSe3 (mP24)	1	3.992	3.995

Appendix

Comparison of the F -, S 2-and Se 2-valences obtained from different bond valence parameter sets for structures containing one anion type [START_REF] Krivovichev | Are the compressive effects of encapsulation an artifact of the bond valence parameters?[END_REF]


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text:
Dmitrii Y Travin

Dmitry Sutormin

Peter Mergaert

Konstantin Severinov

Complete genome sequences of two Rhizobium strains producing azol(in)emodified antibiotics

Rhizobia are known for their ability to establish symbiotic relationships with plants. Specialized metabolism of these bacteria remains understudied. Here, we report whole-genome sequences of two rhizobia producing narrow-spectrum antirhizobial azol(in)e-modified peptides: that of Rhizobium sp. Pop5, a phazolicin producer, and another of Rhizobium anhuiense T24, a trifolitoxin producer.

ANNOUNCEMENT

Symbiotic nitrogen-fixing rhizobia compete for the host plants nodulation using a variety of mechanisms including the production of antimicrobial compounds [START_REF] Mendoza-Suárez | Competition, Nodule Occupancy, and Persistence of Inoculant Strains: Key Factors in the Rhizobium-Legume Symbioses[END_REF]. Phazolicin [START_REF] Travin | Structure of ribosome-bound azole-modified peptide phazolicin rationalizes its species-specific mode of bacterial translation inhibition[END_REF] and trifolitoxin [START_REF] Triplett | Trifolitoxin Production and Nodulation Are Necessary for the Expression of Superior Nodulation Competitiveness by Rhizobium leguminosarum bv. trifolii Strain T24 on Clover[END_REF] are antirhizobial azol(in)e-containing antibiotics belonging to ribosomally synthesized and post-translationally modified peptides (RiPPs). The genome of the trifolitoxin producer, isolated from the nodules of Trifolium dubium and originally classified as Rhizobium trifolii T24 (4) was not sequenced to date except for two small, 7.1 and 7.3 kbp, regions [START_REF] Breil | DNA sequence and mutational analysis of genes involved in the production and resistance of the antibiotic peptide trifolitoxin[END_REF][START_REF] Breil | A newly discovered gene, tfuA, involved in the production of the ribosomally synthesized peptide antibiotic trifolitoxin[END_REF].

The genome of phazolicin-producing Rhizobium sp. Pop5, isolated from the nodules of Phaseolus vulgaris, was available in contigs only (GCA_000295895.1).

Rhizobium sp. Pop5 was provided by Prof. Esperanza Martinez-Romero, and R. anhuiense T24 was obtained from USDA-ARS Culture Collection (USDA2124). Both strains were maintained on YM medium. Genomic DNA was extracted from overnight cultures grown at 28°C using GeneJET Genomic DNA purification kit (ThermoFisher). Pop5 DNA was sequenced using Oxford Nanopore Technologies (ONT) sequencing, while a combination of ONT and Illumina sequencing was performed for T24 DNA. For Nanopore sequencing, libraries were prepared with non-sheared DNA using the Ligation Sequencing Kit 1D (SQK-LSK109, ONT) and EXP-NBD104 native barcoding expansion according to standard protocols. Genomic DNA was subjected to End Repair and A tailing by NEBNext FFPE DNA Repair mix and NEBNext Ultra II End repair/dA-tailing module (NEB). Sequencing adaptors were ligated using NEBNext Ultra II DNA Ligation module (NEB) after AMPure XP (Beckman Coulter) purification. The final product was cleaned using LFB buffer. MinION sequencing was performed using R9.4 flow cell (FLO-MIN106D, ONT). Base calling was performed using Guppy 6.0.1 [START_REF] Wick | Performance of neural network basecalling tools for Oxford Nanopore sequencing[END_REF] with the "sup" mode. For Illumina sequencing, DNA was sheared using Covaris sonicator and 200-400 bp fragments were size-selected with AMPure XP beads. Library was prepared using NEBNext Ultra II DNA Library Prep kit (NEB). Sequencing was performed on MiSeq with the 250+250 bp paired-end protocol.

Illumina reads were filtered and trimmed with Trimmomatic v 0.39 [START_REF] Bolger | Trimmomatic: a flexible trimmer for Illumina sequence data[END_REF]. For T24, a draft genome was assembled with Unicycler (v 0.5.0) (9) using ONT reads. The assembly was subsequently polished with medaka (v 1.5.0), Polypolish (v 0.5.0) [START_REF] Wick | Polypolish: Short-read polishing of long-read bacterial genome assemblies[END_REF], and POLCA (v 4.0.8) (11) using ONT and Illumina reads. For Pop5, a draft genome was assembled with Unicycler (v 0.5.0), and the assembly was polished with medaka (v 1.5.0). Default parameters were used for all software unless otherwise specified. Replicons were circulated and rotated automatically using Unicycler and annotated using PGAP 6.1.

Both genomes contain multiple replicons including the chromosome and several plasmids (Table 1). An antiSMASH [START_REF] Blin | antiSMASH 6.0: improving cluster detection and comparison capabilities[END_REF] search revealed 12 biosynthetic gene clusters per genome (Fig. 1A). The trifolitoxin tfxABCDEFG cluster is located on the chromosome, while the phazolicin cluster phzEACBDR is encoded on the smallest plasmid (Fig. 1A). According to average nucleotide identity (ANI) analysis by JSpeciesWS [START_REF] Richter | JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison[END_REF], the genome of R. leguminosarum T24 is 99.08% identical (89.78% aligned nucleotides) to that of R. anhuiense CCBAU 23252 T (GCA_003985145.1) (14) (Fig. 1B). Accordingly, the strain is reclassified as R. anhuiense bv. trifolii T24.

Figure 1 .

 1 Figure 1. (A) Genome organization of the two sequenced Rhizobium strains visualized using Proksee (https://proksee.ca/). The chromosomes and plasmids are shown not to scale. Colored arrowheads indicate the locations of biosynthetic gene clusters identified by antiSMASH. Schematic representation of phz and tfx clusters is shown below with the functions of encoded proteins listed. CDS, coding sequence; HSL, homoserine lactone; T3PKS, type III polyketide synthase; NRPS, non-ribosomal peptide synthetase; LAP, linear azol(in)e-containing peptide; RiPP, ribosomally synthesized posttranslationally-modified peptide. (B) Alignment of the whole genome of R. anhuiense T24 and the draft genome of R. anhuiense CCBAU 23252 T (GCA_003985145.1) (14) generated with Mauve (15).

Table 1 . Accession numbers, assembly and run statistics for the two Rhizobium genomes

 1

		Rhizobium sp. Pop5	Rhizobium anhuiense T24
	BioSample accession no.	SAMN28987821	SAMN28987535
	BioProject accession no.	PRJNA848232	PRJNA848223
	GenBank accession no.	CP099398	CP098801
		CP099399	CP098802
		CP099400	CP098803
		CP099401	CP098804
		CP099402
	Illumina sequencing reads	-	SRR20001171
	ONT sequencing reads	SRR20000763	SRR20001172
	Total reads length (Illumina), bp -	463 844 988
	Total reads length (ONT), bp	338 208 140	185 875 667
	Number of reads (Illumina)	-	923994
	Number of reads (ONT)	41698	25553
	N50 (ONT), bp	16641	13212
	Genome size, bp	6 742 135	7 327 117
	GC content, %	60.93	60.97
	Number of replicons	5	4
	Replicon sizes, bp	4 430 159	4 746 307
		951 562	1 441 560
		503 518	767 332
		454 824	371 918
		402 072

ACKNOWLEDGEMENTS We thank Prof. Esperanza Martinez-Romero (Universidad Nacional Autónoma de México) and USDA-ARS Culture Collection for providing the strains Rhizobium sp. Pop5 and R. anhuiense bv. trifolii T24 (USDA2124) respectively. NGS library preparation and sequencing were performed at Skoltech Sequencing Core Facilities. The work was supported by a grant from the Ministry of Science and Higher Education of the Russian Federation (agreement No. 075-10-2021-114 from 11 October 2021).

Data availability.

The genome sequences reported were deposited in DDBJ/ENA/GenBank databases; the raw reads were deposited in the NCBI Sequence Read Archive. Accession numbers are provided in Table 1.


MD Anthony Le Bras

Fakhreddine

MD Kevin Janot

MD Jean-Christophe Ferre

MD Jean-Yves Gauvrit

MD François Eugene

Rehearsals using patient-specific 3d-printed aneurysm models for simulation of endovascular embolization of complex intracranial aneurysms: 3D SIM Study. AUTHORS

Keywords: interventional neuroradiology, simulation, intracranial aneurysm, 3D-printed

 Challenging embolization of complex intracranial aneurysms, with advanced devices (WEB, flow diverters)  Pre-operative rehearsals could be helpful for advanced device selection  Patient-specific 3D-printed models bring haptic feedback and reliable model  Implantation failure of advanced device and radiation dose of procedure could be reduced by EVIAS solution rehearsals Graphical abstract REHEARSALS USING PATIENT-SPECIFIC 3D-PRINTED ANEURYSM MODELS FOR SIMULATION OF ENDOVASCULAR EMBOLIZATION OF COMPLEX INTRACRANIAL ANEURYSMS: 3D SIM STUDY

INTRODUCTION

Endovascular device strategy for embolization of complex intracranial aneurysms including device selection, sizing and positioning is very dependent on the neurointerventionalist's experience and facilitated using 2D conventional measurements based on 3D rotational angiography. A family of endovascular devices based on flow diversion [START_REF] Fiorella | CURATIVE RECONSTRUCTION OF A GIANT MIDBASILAR TRUNK ANEURYSM WITH THE PIPELINE EMBOLIZATION DEVICE[END_REF] or disruption [3,[START_REF] Asnafi | Efficacy and Safety of the Woven EndoBridge (WEB) Device for the Treatment of Intracranial Aneurysms: A Systematic Review and Meta-Analysis[END_REF] have been developed to address the difficulty of giant or wide-neck aneurysm embolization. These endovascular devices are challenging to use and need accurate preoperative planning to optimize sizing and landing areas and avoid corrective intervention as well as procedural and peri-procedural complications.

Computed preoperative simulations incorporating some finite elements [START_REF] Ma | High Fidelity Virtual Stenting (HiFiVS) for Intracranial Aneurysm Flow Diversion: In Vitro and In Silico[END_REF] can help a neurointerventionalist in this purpose, and recent publications [START_REF] Bouillot | Virtual-versus-Real Implantation of Flow Diverters: Clinical Potential and Influence of Vascular Geometry[END_REF][START_REF] Ospel | Comparison of Pipeline Embolization Device Sizing Based on Conventional 2D Measurements and Virtual Simulation Using the Sim&Size Software: An Agreement Study[END_REF][START_REF] Cagnazzo | Comparison of Woven EndoBridge device sizing with conventional measurements and virtual simulation using the Sim&Size software: a multicenter experience[END_REF] emphasize the value of these computed simulation tools for flow diverter or disrupter endovascular devices.

However, computed simulation software does not address an important criterion of endovascular embolization which is haptic feedback linked to the handling of endovascular devices during challenging navigation, due to anatomy or to arterial rigidity, as well as during the intra-arterial or intrasaccular device delivery.

With advances in materials and technologies, in vitro simulation based on patient-specific models continues to improve, incorporating fluid dynamics or biomechanical data [START_REF] Khan | Prototyping of cerebral vasculature physical models[END_REF][START_REF] Chivukula | Reconstructing patient-specific cerebral aneurysm vasculature for in vitro investigations and treatment efficacy assessments[END_REF][START_REF] Anderson | Three-dimensional printing of anatomically accurate, patient specific intracranial aneurysm models[END_REF][START_REF] Kaneko | A patient-specific intracranial aneurysm model with endothelial lining: a novel in vitro approach to bridge the gap between biology and flow dynamics[END_REF].

The use of 3D-printed patient-specific models of intracranial aneurysms enable the neurointerventionalist to plan and perform in vitro the endovascular embolization with the possibility to test different strategies with different sizes and landing zones for the embolization devices [START_REF] Ishibashi | Tailor-made shaping of microcatheters using threedimensional printed vessel models for endovascular coil embolization[END_REF][START_REF] Kono | Preoperative Simulations of Endovascular Treatment for a Cerebral Aneurysm Using a Patient-Specific Vascular Silicone Model[END_REF][START_REF] Nawka | Feasibility of a customizable training environment for neurointerventional skills assessment[END_REF]. The patient can thus benefit from the increased confidence of the neurointerventionalist who will have already performed the in vitro endovascular intervention and integrated each step.

A recent publication reported results from 8 patients with intracranial aneurysms using patient-specific 3D aneurysm models before intervention with novel flow diverter stents (FDS) [START_REF] Yamaki | Biomodex patient-specific brain aneurysm models: the value of simulation for first in-human experiences using new devices and robotics[END_REF]. Aneurysm structures and features were found to be similar between the 3D models and patients. In addition, simulation was postulated to potentially increase operator confidence and enhance patient outcomes.

In this multicenter open prospective study of patients with wide-neck intracranial aneurysms, we compared the concordance in device selection for adequate wall-apposition/aneurysm neck closure for patients having an in vitro simulation prior to the real procedure. Accuracy of 3D-printed models, embolization outcomes, including wall-apposition/aneurysm neck closure status, per and peri-procedural complications, procedure time and radiation dose, were also investigated.

METHODS

Patient selection: For inclusion in the study, a patient must have presented with a complex wide-neck intracranial aneurysm (neck > 4mm or ratio < 2) requiring intervention to manage risk of rupture. A multidisciplinary meeting including neurosurgeons, neurointerventionalists and neurologists validated the indication of endovascular preventive treatment. Informed consent for participation in the study was obtained from each patient. The study design was reviewed and approved by the Institutional Ethics Committees of our institutions.

Visit 3D rotational angiography (3DRA): Prior to the endovascular embolization procedure, a diagnostic cerebral angiography of the patient aneurysm, including a 3DRA (voxel = 235 µm3matrix = 384), was performed, with 18mL of iodine contrast at 3mL/s, without saline dilution. The 3D volume rendering model (VR) obtained from this visit 3DRA was used first to provide the reference 3D patient-specific model for the metrology assessment (first ten patients) and secondly to print the patient-specific 3D-printed aneurysm model (see paragraph below) for in-vitro simulation.

Metrology: The purpose of metrology was to provide a geometric evaluation of the accuracy of the patient-specific 3D-printed model of the first ten patients. The comparison was performed between the reference 3D VR model obtained from the visit 3DRA and the 3D VR model obtained from the 3DRA of the patient-specific 3D-printed model, with same patients'3DRA injection properties. This comparison consisted in registration of the two models using an iterative closest point algorithm (ICP) with a least-square matching method. After registration of meshes, each point of the model (obtained from the 3D-model printed 3DRA) was projected on the surface defined by the reference (obtained from the visit 3DRA) in order to calculate the point-tosurface distances [START_REF] Mitton | 3D reconstruction method from biplanar radiography using non-stereocorresponding points and elastic deformable meshes[END_REF][START_REF] Bras | 3D reconstruction of the proximal femur with low-dose digital stereoradiography[END_REF]. This comparison was processed for the first ten patients on the entire set of 5000 points per aneurysm model. The mean, 95% confidence interval (CI), minimum, and maximum were calculated. These data were secondarily separated in two anatomical areas: 1) saccular aneurysm 2) parent and daughter arteries.

Following the registration of the 3DRA VR models, 3D specific points were manually selected on adequate incidences for both models (registered in the same referential) in order to calculate aneurysm-specific geometrical characteristics: maximum dome height, aneurysm neck width as well as the diameters of the parent artery and daughter arteries at the bifurcation (Figure 1). Distance shifts between these measurements for both models were then calculated (mean, standard deviation, absolute maximum).

Patient-specific 3D-printed aneurysm models: Based on images acquired from visit 3DRA, a 3D-printed patient-specific model was produced for the EVIAS system (Biomodex, Paris, France). The segmentation of visit 3DRA was performed with an FDA-cleared and CEmarked system. The printing process merged soft and rigid materials to produce a realistic mechanical behavior of the 3D-printed models. 3D-printed anatomies are made with various flexible photopolymers which allow control of the pliability of the target area, providing precise haptic feedback. The accuracy of the printer was up to 200 µm [START_REF] Yamaki | Biomodex patient-specific brain aneurysm models: the value of simulation for first in-human experiences using new devices and robotics[END_REF]. Patient-specific 3D models were printed with a Stratatys Multijet printer allowing to lay down material with different biomechanical data including Young modulus. These models were printed according to a patented technology that optimize material distribution in order to fit with biomechanical datas as kinematic constraint and loading conditions according to physiologic values of a healthy artery based on literature [START_REF] Riley | Ultrasonic measurement of the elastic modulus of the common carotid artery. The Atherosclerosis Risk in Communities (ARIC) Study[END_REF]. For example, in the intra-petrous carotid segment of the models, the allocated local deformation was null.

Moreover, a blood-mimicking fluid is designed, in combination with a hydraulic system, to simulate blood flow dynamics and to replicate real-world density, viscosity, and body temperature.

Simulation : In vitro simulations were performed by 3 senior neurointerventionalists with 5 to 10 years' experience each with intrasaccular flow disrupter device [Woven EndoBridge (WEB), Microvention, Tustin, CA] or FDS [Pipeline; Medtronic, Dublin, Ireland] procedures. The same practitioner performed both simulation and procedure for a given aneurysm. Device sizes were estimated based on the 3D VR acquired from the patient-models during the simulations. For each simulation the neurointerventionalist had a full portfolio of sizes of WEB and FDS available, to test different sizes or landing zones, if necessary. Once all the simulations were performed, the neurointerventionalist had to select the appropriate device in terms of wall-apposition/aneurysm neck closure and without device overhanging.

All simulations and procedures were performed on biplane Allura (Philips, Eindhoven, Netherlands). (Figure 2)

Procedure : As the EVIAS in vitro simulation system is not approved for endovascular device selection, the study was designed to allow the neurointerventionalist, according to his experience, to choose a different strategy or a different size of device during the real procedure compared to the one selected at the end of the in vitro simulation. Moreover, if the simulation failed with a WEB or a FDS, the neurointerventionalist was allowed to attempt with this type of device during the real procedure according to his experience. Similarly to the simulation the appropriate device was selected according to an optimal wall-apposition/neck closure without device overhanging.

Data collection : Data was collected on demographic (age, sex, smoking status, pre procedural modified Ranking Score) and aneurysm characteristics (location, dome width and height, neck width, dome / neck ratio) (Table 1).

The following measurements were collected: times between visit angiography, in vitro simulation, and real procedure, in vitro simulation and real procedure duration, fluoroscopy time, radiation dose, embolization strategy, number of devices tested / implantation failure rate, immediate complication rate after the procedure (e.g., ischemic stroke, neck embolus, aneurysm perforation), embolization efficiency as measured by wall-apposition (correct or incorrect) for FDS or aneurysmal neck closure (complete, incomplete, residual neck) for WEB, morbidity (mRS > 2 at 3 months), and mortality.

In vitro simulation/procedure duration was measured from the time between the first and last series. The first series was acquired after the positioning of the long sheath and the intermediate catheters in the internal carotid or the vertebral arteries. The end of the procedure was considered the final control run. This calculation was intended to eliminate the time required for access, from the femoral to the internal carotid/vertebral artery, on which the application of the simulation does not have an impact.

Cohort data : Fluoroscopy time, radiation dose and implantation failure rate were collected retrospectively (unpublished raw data) from 2012 and 2018 from 55 previous WEB cases without simulation at one center using the same imaging equipment (biplane ALLURA, Philips, Eindhoven, Netherlands).

Outcomes evaluated: The primary endpoint was evaluation of agreement between simulation and procedure as assessed by choice of implantable devices (size, positioning). Secondary endpoints included rate of complications, mortality rate, procedure times, irradiation dose, and effectiveness of procedure. The concordance between visit angiography, in vitro simulation and real procedure was examined as described below :

1. Concordance between the device selected following the in vitro simulation and the device implanted during the real procedure 2. The concordance between wall-apposition/aneurysm neck closure at post-simulation and post-procedure. 3. The concordance between device (WEB only) selection from conventional measurements planned after visit angiography and implanted during procedure 4. The concordance between device selection (WEB only) from conventional measurements planned after visit angiography and post-simulation.

Statistical analysis:

To describe the data, quantitative results were expressed as mean ± standard deviation (SD) or median and interquartile range (IQR) and qualitative results were expressed in numbers (%). The concordance between in vitro simulation and real procedure was assessed using Cohen's Kappa coefficient with a confidence interval of 95%, with coding variables : device selected (concordances 1,3,4) or wall-apposition/aneurysm neck closure (concordance 2).

All statistical tests had a significance level of 0.05. The statistical analyses were performed using SAS software, v.9.4® (SAS Institute, Cary, NC, USA).

RESULTS

Patients were enrolled in this unblinded, multicenter, non-randomized, prospective study from November 2018 through December 2020, in two university hospitals. Of the 22 patients screened, 21 patients met the study criteria and were treated, and 1 subject was not treated due to a pre-implantation endovascular complication. The mean age (SD) was 56 (10) years, and most patients were women (67%) (Table 1). Half of the patients were current smokers, and 81% had an mRS of 0.

Aneurysms were localized mainly at the internal carotid artery (50%) and at the basilar tip (23%). Aneurysms were predominantly of the saccular morphology. At the diagnostic patient angiography the mean (SD) dome width was 7.59 (1.44) mm, neck width was 5.25 (1.16) mm and dome to neck ratio was 1.63 (0.56). Notes: Qualitative results are expressed as: total number (missing data) and number (%) for each modality.

Quantitative results are expressed as : mean ± standard deviation (median).

Metrology

For the aneurysm, point-surfaces calculation showed a mean absolute shift of 0.11 mm; 95% of shifts were between -0.22 and 0.36 mm. The absolute maximum shift was 0.75 mm for the aneurysm and 1.04 mm for parent artery and daughter arteries.

For aneurysm-specific geometrical characteristics, shifts between 3D VR models are presented in Table 2. An example of data obtained for patient 008 after registration of the models by ICP algorithm is shown in Fig 1. For the WEB devices:

-K between the device selected from conventional measurement at visit diagnostic angiography and the device implanted during the real procedure was 0.62 [0.15 -1.00]. -K between the device selected from conventional measurement at visit diagnostic angiography and the device selected post-simulation was 0.47 [0.22 -0.72].

The percentage of implant failure during the real procedure, whereas in vitro simulation was possible, was reported for 9.5% of the cases (2 patients). For the first case, the neurointerventionalist failed to pass the intermediate catheter through the origin of the ophthalmic artery during the real procedure whereas this issue was considered as not relevant before the simulation and the ophthalmic artery was not printed on the model. For the second case, there was a true mismatch between the device selected following simulation (WEB SL 7x4 mmcomplete aneurysm neck closure) and the device chosen during the real procedure (overhanging of the simulation selected device during the real procedure with decision to downsize for a WEB SL 6x4 mm resulting in a residual neck closure).

It must be noted that for one patient, there was a strategy failure during the simulation (failure of positioning of 3 different sizes of WEB), but the neuroradiologist, based on his personal experience, decided to try to implant two different sizes of WEB during the real procedure resulting in implant failure for both and strategy conversion for coiling with remodeling.

The mean number of devices tested was 2.2 per simulation and 1.2 per procedure. The mean (SD) X-ray dose (mGy.cm2) and the mean (SD) X-ray duration (min) were reported for simulation, real procedure and historic cohort (55 patients) in Table 3. Mean (SD) delay (days) between simulation and procedure was 17 (51) days.

Safety

The mean mRS post-procedure was identical to the mean mRS pre-procedure. Complications included: 1 post-procedure minor stroke of a top basilar aneurysm with no clinical significance; and 1 peri-procedure ruptured aneurysm with no clinical significance (minor SAH).

DISCUSSION

This study on a small number of patients underlines the potential of in vitro patient-specific simulations with the EVIAS system for optimal preoperative planning. The results showed a potential improvement in term of implantation failure (9.5% post-simulation vs 25.5 in the historic cohort, p = 0,34) adequate device selection, radiation dose and cumulative fluoroscopy duration compared to an historic cohort in which device selection was based on conventional measurements.

In this study, concordance was considered high in device selection and wallapposition/aneurysm neck closure efficiency between post-simulation and real procedure which indicated that the 3D models reliably reproduced the aneurysm environment allowing device selection consistent with patient anatomy. As in previous studies ( [START_REF] Anderson | Three-dimensional printing of anatomically accurate, patient specific intracranial aneurysm models[END_REF] - [START_REF] Frölich | 3D Printing of Intracranial Aneurysms Using Fused Deposition Modeling Offers Highly Accurate Replications[END_REF]), we evaluated the anatomical accuracy of EVIAS 3D patient-specific printed models (integrating biomechanical data), regarding aneurysm and parent vessels geometric characteristics, validating that they can be used safely for preoperative planning.

Furthermore, low concordance between WEB device selection pre-simulation (based on conventional measurements) and post-simulation indicated that experienced interventionalists derived benefit from simulation prior to performing a complex endovascular intracranial intervention. Other recent studies report the necessity of new technologies to optimize FDS or WEB selection by using software based on biomechanical data or aneurysm volume calculation ([21] - [START_REF] Ospel | Comparison of Pipeline Embolization Device Sizing Based on Conventional 2D Measurements and Virtual Simulation Using the Sim&Size Software: An Agreement Study[END_REF]) compared to device selection based only on operator experience with conventional measurements.

For example, virtual simulation software, e.g., Sim&Size (Sim&Cure, France) can be utilized to suggest optimal sizing and display the potential degree of wall apposition. In a retrospective study of 189 patients, interventions with the Pipeline Flex Embolization Device using software assistance were associated with fewer corrective procedures, shorter procedure duration, and lower radiation dose [START_REF] Piergallini | Virtual simulation with Sim&Size software for Pipeline Flex Embolization: evaluation of the technical and clinical impact[END_REF]. A multicenter study of the same simulation software with the WEB in 186 aneurysms found similar results [START_REF] Cagnazzo | Comparison of Woven EndoBridge device sizing with conventional measurements and virtual simulation using the Sim&Size software: a multicenter experience[END_REF] with an improvement in implantation failure (33% vs 7%). These results are quite similar to ours where an implantation failure rate of 9.5% vs 25% was found.

In vitro simulation using EVIAS technology, in contrast, allow multiple rehearsals of the whole procedure simulation (even access catheter navigability and stability) on an accurate patient-specific anatomy as well as haptic feedback similar to the real procedure.

Our study has several limitations. First, the design of this study does not allow an adequate evaluation of clinical outcome for benefit from multiple rehearsals in vitro-simulation. Indeed, the occurrence of complications during embolization procedure is quite low and the number of patients to include to prove this hypothesis with sufficient power would have been too high in the first patient evaluation of this technology. Second, our study was based in only 2 centers with a small number of practitioners and patients, suggesting that our results have to be interpreted with caution and confirmed by a larger randomized study.

One other limitation of our study was the absence of coiling embolization strategies; however even if 3D in vitro simulation had been studied for microcatheter shaping in coiling embolization technique ([13]- [START_REF] Namba | Microcatheter Shaping for Intracranial Aneurysm Coiling Using the 3-Dimensional Printing Rapid Prototyping Technology: Preliminary Result in the First 10 Consecutive Cases[END_REF]), we decided to evaluate only FDS and WEB devices over coils because device deployment was less operator dependent. The ability of the EVIAS system to properly plan coiling embolization strategy needs to be evaluated. We also choose to evaluated the wall-apposition/aneurysm neck closure instead of Roy Raymond score [START_REF] Roy | Endovascular Treatment of Unruptured Aneurysms[END_REF] and Web Occlusion Score [START_REF] Fiorella | Interobserver variability in the assessment of aneurysm occlusion with the WEB aneurysm embolization system[END_REF] in absence of spontaneous thrombosis in simulation and absence of immediate complete occlusion by the end of FDS procedures.

One of the drawbacks of ex-vitro endovascular simulations remains the availabilities of the angiography suite and the neuroradiologist to perform the rehearsals before the real procedure. Indeed, even if the EVIAS system allows a rapid installation with the possibility to quickly change 3D patient-specific cartridges, the whole simulation procedure is time consuming, necessitating integration of this pre-operative planning in the angiography suite workflow. For each complex case, the benefits of realistic rehearsal and training versus cost and time to procedure could be assessed as part of the intervention strategy.

Another drawbacks considerer the medico-economic impact : the cost of patients' specific cartridges were supported by hospitals innovation funds. WEB portfolio for simulations were obtained by combination of devices from our hospital expired, non-human use devices from laboratories, and re-sterilize after patients implantation failure. FDS were obtained with laboratory partnership. Finally, our study didn't demonstrate the ability to reduce the number of devices attempted to implant in procedure, and the cost of its.

CONCLUSION

In summary, this prospective study found that rehearsal using a patient-specific 3D aneurysm simulation prior to endovascular embolization of complex unruptured intracranial aneurysms enabled optimization of treatment device and approach, resulting in reduced procedure duration and thus lower radiation exposure for the patient.

Table 1 .

 1 Baseline patient and aneurysm characteristics

	Characteristic

Table 2 : Shifts (mm) between geometrical aneurysmal dimension from VR models obtained from 3DRA visit and 3DRA of the 3D-printed patient-specific model.

 2

	3DRA visit/	Dome	Aneurysm	Neck	Parent	Daughter	Daughter
	3DRA printed	height	width	Width	artery	artery 1	artery 2
	model	(mm)	(mm)	(mm)	(mm)	(mm)	(mm)
	Mean	-0.05	-0.05	-0.09	0.09	0.08	0.12
	SD	0.25	0.21	0.18	0.16	0.27	0.16
	Absolute	0.37	0.5	0.40	0.39	0.53	0.32
	Maximum
	Procedural and clinical outcomes
	At the visit patient angiography, 16 (76.2%) of cases were selected for treatment by WEB,
	and 5 (23.8%) by FDS.
	The concordance, defined by the kappa coefficient (K [95% CI]), between post-simulation
	and device implanted during the real procedure was 0.85 [0.69 -1.00] and 0.93 [0.79 -1.00]
	for the device selection and the wall-apposition/aneurysm neck closure, respectively (Table -
	supplementary material)

Table 3 . Procedural and Clinical Outcomes

 3

		In Vitro Simulation	Procedure	R WEB Cohort Procedure
	Radiation dose, mGy.cm2	5459.0 ± 10412	150 423 ± 64 590	180 090 ± 75 008
	Cumulative fluoroscopy time, min	16.95 ± 10.07	23.05 ± 11.34	30.5 ± 20.4
	Number of devices tested, mean	2.2 (Per simulation)	1.2 (Per procedure)	1.3 (Per procedure)
	% of implantation	1/21	2/21	14/55
	failure	(4,8%)	(9,5%)	(25,4%)
	Time
	Duration between time
	guide catheter
	appropriately positioned
	and time microcatheter appropriately positioned	11.62 ± 7.79	18.57 ± 10.25	N/A
	(i.e., time of
	catheterization of
	aneurysm), min
	Duration between time
	microcatheter
	appropriately positioned and time procedure	37.71 ± 21.33	29.43 ± 13.53	N/A
	ended (i.e., implantation
	of devices), min
	Total procedure duration, min	56.52 ± 24.52	64.86 ± 19.77	N/A
	simulation, days Delay between visit and	60.14 ± 52.77	N/A
	procedure, days Delay between visit and	76.67 ± 73.57	N/A
	Delay between			N/A
	simulation and	16.52 ± 51.67
	procedure, days

GLOSSARY