A Bouttier

A A S Yeo

G Faye-Kette

Ponchel

K C N'

Guessan Gnaman

S Bouttier C

A Yeo D

A A S Aka Any-Grah

S Geiger

N Huang

V Nicolas

S Villebrun

H Faye-Kette

G Ponchel

A A Koffi

F Agnely

Characterization and in vitro evaluation of a

Keywords: Confocal laser scanning microscopy Gel Gonorrhea prevention Lactobacillus Probiotics Rheology Vaginal administration A, sodium alginate, ATCC, american type culture collection, BHIA, brain heart infusion agar, CDC, Center for disease control, CFU, colony forming unit, CLSM, confocal laser scanning microscopy, G′, elastic modulus, G″, viscous modulus, GC agar, chocolate agar, HIV, human immunodeficiency virus, L. crispatus, Lactobacillus crispatus, MRS, Man-Rogosa-Sharpe, N. gonorrhoeae, Neisseria gonorrhoeae, P, Poloxamer 407, PBS, phosphate buffered saline, pH i , initial pH, SVF, simulated vaginal fluid, T gel , gelation temperature, VNC, viable but nonculturable

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Introduction

Gonorrhea is a sexually transmitted infection that is caused by Neisseria gonorrhoeae. With 78 million new cases every year [START_REF] Who | WHO guidelines for the treatment of Neisseria gonorrhoeae[END_REF], it has become a major public health issue for many reasons. Indeed, this infection remains more often asymptomatic in women, which favors its spreading. It can induce severe damages such as infertility both in men and women, and blindness in newborns [START_REF] Grodstein | Relation of tubal infertility to history of sexually transmitted diseases[END_REF][START_REF] Laga | Epidemiology of ophthalmia neonatorum in Kenya[END_REF]. It also increases the risk of contracting human immunodeficiency virus HIV [START_REF] Cohen | HIV and sexually transmitted diseases: lethal synergy[END_REF][START_REF] Jarvis | Modulation of HIV transmission by Neisseria gonorrhoeae: molecular and immunological aspects[END_REF]. Resistance to several antibiotics even to the last intention treatments is currently emerging [START_REF] Lefebvre | Ceftriaxone-resistant Neisseria gonorrhoeae, Canada, 2017[END_REF]. Some untreatable strains that are insensitive to any known antimicrobial treatment are now circulating. Meanwhile, neither vaccines nor new drugs are emerging on the market. Condom which is the sole effective prevention mean is unfortunately either not well or insufficiently used. Thus, gonorrhea has become difficult to treat or to prevent. The main target of gonorrhea, as all sexually transmitted infections, is women because they are more vulnerable. A strategy giving women the control of their own protection could enable to achieve better results in the field of prevention [START_REF] Stein | HIV prevention: the need for methods women can use[END_REF]. Thus, recent studies are devoted to woman-controlled means intended for a vaginal administration [START_REF] Minnis | Effectiveness of female controlled barrier methods in preventing sexually transmitted infections and HIV: current evidence and future research directions[END_REF][START_REF] Traore | Current state of microbicide development[END_REF].

Promising approaches based on probiotics have been developed for the prevention of women urogenital tract infections (Bruce and Reid, microorganisms that, when administered in adequate amounts, confer a health benefit on the host" [START_REF] Hill | Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic[END_REF]. The most important probiotic genus studied for urogenital infections is Lactobacillus. The healthy vaginal flora is typically dominated by Lactobacillus (L.) species, such as L. iners, L. crispatus, L. jensenii and L. gasseri [START_REF] Pavlova | Genetic diversity of vaginal lactobacilli from women in different countries based on 16S rRNA gene sequences[END_REF][START_REF] Ravel | Vaginal microbiome of reproductiveage women[END_REF], but L. crispatus seems to largely prevail over the other Lactobacillus strains [START_REF] Antonio | The identification of vaginal Lactobacillus species and the demographic and microbiologic characteristics of women colonized by these species[END_REF][START_REF] Vasquez | Vaginal Lactobacillus flora of healthy Swedish women[END_REF]. Moreover, L. crispatus has been reported to promote the stability of the normal vaginal flora [START_REF] Verstraelen | Longitudinal analysis of the vaginal microflora in pregnancy suggests that L. crispatus promotes the stability of the normal vaginal microflora and that L. gasseri and/or L. iners are more conducive to the occurrence of abnormal vaginal microflora[END_REF]. Vaginal colonization with a human L. crispatus strain had been successful [START_REF] Antonio | DNA fingerprinting of Lactobacillus crispatus strain CTV-05 by repetitive element sequence-based PCR analysis in a pilot study of vaginal colonization[END_REF]. A L. crispatus strain was also used successfully as a vaginal suppository for healthy women with a history of recurrent urinary tract infections [START_REF] Czaja | Phase I trial of a Lactobacillus crispatus vaginal suppository for prevention of recurrent urinary tract infection in women[END_REF][START_REF] Stapleton | Randomized, placebocontrolled phase 2 trial of a lactobacillus crispatus probiotic given intravaginally for prevention of recurrent urinary tract infection[END_REF] and for the treatment of bacterial vaginoses [START_REF] Hemmerling | Phase 2a study assessing colonization efficiency, safety, and acceptability of Lactobacillus crispatus CTV-05 in women with bacterial vaginosis[END_REF]. Moreover, it was shown that L. crispatus inhibited the infectivity of N. gonorrhoeae in vitro [START_REF] Amant | Inhibition of Neisseria gonorrhoeae by Lactobacillus species that are commonly isolated from the female genital tract[END_REF] and ex vivo [START_REF] Breshears | Lactobacillus crispatus inhibits growth of Gardnerella vaginalis and Neisseria gonorrhoeae on a porcine vaginal mucosa model[END_REF]. Its use for a vaginal administration could be a valuable strategy for vaginal gonorrhea prevention. Therefore, L. crispatus was selected in the present study. As the health promoting effects of probiotics are usually strain specific, we report, in this work, on the ability of a reference vaginal L. crispatus strain ATCC 33197 to be used as a probiotic for the prevention of gonorrhea.

The vaginal route has been selected instead of the oral route to obtain a maximal local effect while avoiding interferences with the gastrointestinal tract. Different strains of L. crispatus are already administered as capsules, vaginal suppositories or tablets [START_REF] Nader-Macias | Profiles and technological requirements of urogenital probiotics[END_REF]. However, these conventional dosage forms are associated to an inhomogeneous repartition in the vagina (Palmeira- [START_REF] Palmeira-De-Oliveira | New strategies for local treatment of vaginal infections[END_REF]. In this study, we focused on the design of a gel form intended for the administration of this L. crispatus strain. Hydrogels are already used and well accepted for vaginal administration. They can easily spread over the vaginal mucosa, they are easy to be prepared and have a low cost of production [START_REF] Cook | Polymeric gels for intravaginal drug delivery[END_REF]Brown, 2018, Pilcher, 2004). Besides, they can be self-administered without partner knowledge. Several studies have been focused on the formulation of viscoelastic and temperature-sensitive hydrogels based on poloxamer 407, with remanence capacity at the vaginal mucosa and sufficient resistance to dilution in presence of vaginal fluids (Aka- [START_REF] Aka-Any-Grah | Formulation of mucoadhesive vaginal hydrogels insensitive to dilution with vaginal fluids[END_REF][START_REF] Huang | Thermo-sensitive composite hydrogels based on poloxamer 407 and alginate and their therapeutic effect in embolization in rabbit VX2 liver tumors[END_REF][START_REF] Liu | Effect of carrageenan on poloxamer-based in situ gel for vaginal use: improved in vitro and in vivo sustained-release properties[END_REF]. In aqueous solution, this synthetic poly(ethylene oxide)-poly(propylene oxide)poly(ethylene oxide) triblock copolymer forms micelles above a critical micelle concentration or temperature. If the polymer concentration is high enough and above a critical temperature called gelation temperature (T gel ), these micelles organize themselves into a cubic liquid crystalline structure forming a gel [START_REF] Dumortier | A review of poloxamer 407 pharmaceutical and pharmacological characteristics[END_REF]. Poloxamer 407 can be mixed with mucoadhesive polymers such as cellulosic derivatives, polyacrylates or polysaccharides to reinforce remanence at the mucosal surface [START_REF] Caramella | Mucoadhesive and thermogelling systems for vaginal drug delivery[END_REF][START_REF] Rençber | Mucoadhesive in situ gel formulation for vaginal delivery of clotrimazole: formulation, preparation, and in vitro/in vivo evaluation[END_REF][START_REF] Giuliano | Mucosal applications of Poloxamer 407-based hydrogels: an overview[END_REF][START_REF] Vigani | Development of a mucoadhesive in situ gelling formulation for the delivery of Lactobacillus gasseri into vaginal cavity[END_REF]. A clinical study conducted on 104 women investigated the vaginal administration of thermosentitive gels (polaxamer 407, 17% w/w, or poloxamer 407, 15% w/w, combined with hydroxyethyl cellose, 1% w/w) containing sildenafil citrate [START_REF] Soliman | Thermosensitive bioadhesive gels for the vaginal delivery of sildenafil citrate: in vitro characterization and clinical evaluation in women using clomiphene citrate for induction of ovulation[END_REF]. Neither gel leakage nor side effects were reported. Among mucoadhesive polymers, sodium alginate is particularly attractive. Indeed, it is a natural polymer derived from brown algae that is commonly and widely used for drug delivery, cell encapsulation and immobilization (including Lactobacillus), wound dressing and enzymes immobilization (Chaluvadi et al. 2012, Lee and[START_REF] Lee | Alginate: properties and biomedical applications[END_REF][START_REF] Lin | In situ gelling of alginate/pluronic solutions for ophthalmic delivery of pilocarpine[END_REF][START_REF] Szekalska | Alginate: current use and future perspectives in pharmaceutical and biomedical applications[END_REF][START_REF] Tønnesen | Alginate in drug delivery systems[END_REF]. Poloxamer 407 and alginate are compatible [START_REF] Grassi | Rheological properties of aqueous Pluronic-alginate systems containing liposomes[END_REF]. Their mixture can be liquid at low or room temperature to allow easy administration and spreading on the vaginal surface, and then can undergo gelation at body temperature [START_REF] Lin | In situ gelling of alginate/pluronic solutions for ophthalmic delivery of pilocarpine[END_REF]. Moreover, good tolerance and biocompatibility are expected. Indeed, a recent study showed that sodium alginate in oil-poloxamer organogels intended for vaginal administration of voriconazole were non-cytotoxic towards HeLa and Vero cell lines [START_REF] Querobino | Sodium alginate in oil-poloxamer organogels for intravaginal drug delivery: Influence on structural parameters, drug release machanisms, cytotoxicity and in vitro antifungal activity[END_REF]. [START_REF] Huang | Thermo-sensitive composite hydrogels based on poloxamer 407 and alginate and their therapeutic effect in embolization in rabbit VX2 liver tumors[END_REF] also reported an absence of cytotoxicity in mouse fibroblast (L929) cell line of thermosensitive composite hydrogels based on poloxamer 407 and alginate used in transarterial embolization therapy. To the best of our knowledge, there is only one published study reporting the use of a gel for the administration of Lactobacilli into the vagina [START_REF] Vigani | Development of a mucoadhesive in situ gelling formulation for the delivery of Lactobacillus gasseri into vaginal cavity[END_REF]. These authors developed two mixtures based on poloxamer 407 and methylcellulose loaded with Lactobacillus gasseri for preventing candidosis recurrences and they studied the viability of the probiotic over 24 h.

In the present study, the mixture of poloxamer 407 and sodium alginate was assessed as a matrix for L. crispatus in order to obtain a temperature-sensitive vaginal gel with adequate mechanical properties and capable to inhibit N. gonorrhoeae. The probiotic properties of the selected L. crispatus strain were first assessed. In a second step, the influence of L. crispatus on the thermogelling and viscoelastic properties of the mixture of poloxamer 407 and alginate was investigated by rheology at 25 °C, i.e. in administration conditions, and at 37 °C after dilution by simulated vaginal fluid (SVF) to mimic in vivo conditions after administration. The efficacy of the gel on N. gonorrhoeae was evaluated in vitro as well as the viability of the L. crispatus in the gel over a six-month period.

Materials and methods

Materials

L. crispatus, a reference strain, isolated from human vagina with collection numbers CIP 103603 (ATCC 33197; NCTC 4505; NCIMB 4505), and a reference strain N. gonorrhoeae with collection number CIP 107031 (ATCC 49226; CCM 4500; CCUG 26213; CDC 10.001; CNCTC 5194; DSM 9189) were purchased from Institut Pasteur (Paris). The strains were stored at -80 °C in cryovials with the appropriate broth supplemented with 20% (v/v) glycerol. Streptococcus pneumoniae ATCC 49619 and Streptococcus pyogenes ATCC 12344 were obtained from Institut Pasteur (Abidjan). BD-Difco™ Lactobacilli of Man-Rogosa-Sharpe (MRS) broth or MRS agar, brain heart infusion agar and Columbia agar base were obtained from Fisher Scientific (France). Poloxamer 407 (P) (Lutrol® F127) of pharmaceutical grade was purchased from BASF (Germany). According to the supplier, the average molecular weight was 11774 g•mol -1 (9840-14600 g•mol -1 ). Sodium alginate (A) was purchased from Roth (France), batch N° 351172083. Its weight-average molecular weight determined by size exclusion chromatography coupled to multi-angle light scattering was 300 000 g•mol -1 . The M:G (β-D-mannuronic acid:α -L-guluronic acid) ratio determined by 1 H NMR was 1.24 ± 0.04. Bovine serum albumin and all other reagents were supplied by Sigma-Aldrich (France) and were of analytical grade. Live/ dead® bacLight TM bacterial viability kit was purchased from Fisher Scientific (France). Sterile ultrapure water (resistivity 18.2 MΩ, MilliQ, Millipore, France) was used. All the antibiotic discs were from BIO-RAD (France) and the E-test from Biomérieux (France).

Study of Lactobacillus crispatus

Growth kinetic

L. crispatus (1/1000 v/v) in MRS broth was incubated at 37 °C, 5% CO 2 to determine its stationary growth phase. Then, the number of colony-forming units was determined at the beginning (t 0 ) and every three hours for 24 h, using a MRS agar plate. This test was performed in triplicate in one experiment.

Acid production and growth at different pH

The evaluation of the acidification ability of L. crispatus and of the effects of low pH on its growth was achieved according to [START_REF] Boskey | Acid production by vaginal flora in vitro is consistent with the rate and extent of vaginal acidification[END_REF], with slight modifications. MRS broth was prepared and adjusted to specific initial pH (pH i ) ranging from 4 to 7 with either HCl or NaOH before autoclaving. L. crispatus was inoculated (1% v/v) into 10 mL of each MRS broth giving a starting concentration of about 10 7 cells/mL. These suspensions were incubated for 24 h at 37 °C under 5% CO 2 . The amount of acid produced by L. crispatus was indirectly determined by measuring the pH immediately after preparation (t 0 ) and after a 24 h incubation (t 24h ) with a pH meter (Metter Toledo equipped with an electrode Seven2GO, France). To assess the sensitivity of L. crispatus to the pH, the numbers of CFU/mL of each MRS broth were quantified at the beginning (t 0 ) and after 24 h (t 24h ). This assay was performed in two separate experiments constituted of three replicates each.

Auto-aggregation and co-aggregation assays

This test was conducted to appreciate the ability of L. crispatus to auto-aggregate and co-aggregate N. gonorrhoeae. It was performed according to [START_REF] Verdenelli | Evaluation of antipathogenic activity and adherence properties of human Lactobacillus strains for vaginal formulations[END_REF] with slight modifications. The cultures were harvested by centrifugation (2800 g, 10 min, 4 °C), and washed twice with sterile water (pH7). Bacterial suspensions in water of L. crispatus and N. gonorrhoeae were adjusted to 0.5 McFarland. Equal volumes (1 mL) of each suspension were mixed for 20 s using a vortex and left for 4 h at 37 °C. A droplet of the single suspensions and the mixture was then put on a glass slide immediately and after four hours. After Gram-staining, aggregates, defined as visible clumps of bacteria, were observed using a B-290 TB Optika microscope (Italy). This experiment was performed in triplicate.

Hemolytic activity

To evaluate the ability of L. crispatus to induce hemolysis, the hemolytic activity of L. crispatus was determined according to [START_REF] Maragkoudakis | In vitro and in vivo safety evaluation of the bacteriocin producer Streptococcus macedonicus ACA-DC 198[END_REF] with slight modifications. In short, the subculture of L. crispatus of 16 h in MRS broth was streaked onto Columbia agar base plates supplemented with 5% (v/v) whole sheep blood. The plates were incubated at 37 °C under 5% CO 2 for 24 h and 48 h in anaerobic conditions. Then, the clear zones and the color of hemolysis around the growth colonies were observed. Streptococcus pneumoniae ATCC 49619 and Streptococcus pyogenes ATCC 12344 were used as controls for respectively α-and β-hemolysis. This experiment was performed thrice.

Antibiotic susceptibility profile

L. crispatus susceptibility to different classes of antibiotics was evaluated by disc (6 mm diameter) method. At least two independent sets of experiments were performed. As a control to the disc method, susceptibility to azithromycin, cefixime, ceftriaxone, ciprofloxacin, gentamicin, penicillin G and tetracycline was also evaluated by the Etest method according to the manufacturer's instructions. This method provides a convenient and quantitative test of antibiotic resistance. All the plates were incubated for 24 and 48 h. MRS agar was used in order to favor the growth of L. crispatus.

Purity control and counting of L. crispatus

Purity was assessed by macroscopic observation of colonies and microscopic observation after Gram staining. The serial decimal dilution method, by plating onto MRS agar medium, was used for counting total Lactobacilli in every suspensions and gels. Dilutions were made in PBS and after vortexing each dilution for 5 s, 100 µL of the previous dilution were inoculated in 900 µL of the next dilution. Then, 100 µL of the chosen dilutions were poured on the MRS agar plates.

Hydrogel preparation

A concentrated mixture of polymers was prepared. Polymer solubilization was performed by using a mixer equipped with a turbine adapted to the mixing of viscous preparations (Rayneri-turbotest, Rayneri, France) under an agitation of 1000 rpm as described by Aka-Any-Grah et al. ( 2010). The alginate powder (1.250 g) was gradually added under agitation at room temperature to ultrapure water (71.875 g). After complete dissolution of alginate, the poloxamer powder (26.875 g) was gradually added at 4 °C under the same agitation. After complete dissolution, this mixture was equilibrated 48 h at 4 °C to eliminate air bubbles and was autoclaved at 121 °C, 15 min before its mixing with the Lactobacilli suspension.

Meanwhile, frozen L. crispatus (-80 °C) was isolated on MRS agar for 48-72 h. Then, it was subcultured twice, first for 24 h and second for 16 h (37 °C, 5% CO 2 ). This second subculture was centrifuged (2800 g, 10 min, 4 °C) and washed twice with sterile water before being suspended in sterile water. L. crispatus homogenization was achieved by vortexing. L. crispatus suspension was enumerated by plating serial dilutions onto MRS agar.

Final gels with or without L. crispatus were obtained by mixing respectively 1 mL of sterile water or 1 mL of the L. crispatus suspension to 4 g of the concentrated polymer mixture. This allowed obtaining two types of gels (P21.5A1 and P21.5A1L) whose final compositions are presented in Table 1. P21.5A1L contained 9 log 10 CFU of L. crispatus per gel sample (5 g).

Preparation of hydrogels diluted by simulated vaginal fluid

Previous studies showed that 5 mL of gels were able to properly cover the human vaginal epithelium, immediately after insertion, within the first 30 min and without sexual intercourse [START_REF] Barnhart | In vivo distribution of a vaginal gel: MRI evaluation of the effects of gel volume, time and simulated intercourse[END_REF]. The volume of ambient fluid present in the vagina at any time is approximately 0.5-0.75 mL [START_REF] Owen | A vaginal fluid simulant[END_REF]. Therefore, to mimic the maximum dilution likely to occur in the vagina after the gel administration, 5 mL of each formulation were diluted with 0.75 mL of simulated vaginal fluid (SVF). SVF containing sodium chloride, potassium hydroxide, calcium hydroxide, bovine serum albumin, lactic acid, acetic acid, glycerol, urea and glucose was prepared according to [START_REF] Owen | A vaginal fluid simulant[END_REF]. It simulates the vaginal fluid from healthy, nonpregnant, premenopausal women and can be used to study vaginal formulations in vitro. P21.5A1 + SVF and P21.5A1L + SVF denoted respectively P21.5A1 and P21.5A1L samples diluted with SVF. The aim of this test was to assess the influence of the dilution by SVF on the thermogelling and the rheological properties of the formulations.

Rheological characterization of the hydrogels

The rheological properties of the gels were assessed at 25 °C, at 37 °C and after dilution of the gels by SVF at 37 °C. Experiments were conducted on a rotational rheometer ARG2 (TA instruments, New Castle, USA) equipped with an aluminum cone/plate geometry (diameter 40 mm, angle 1° and cone truncation 28 µm) and with a solvent trap to limit evaporation during measurement. Peltier diodes, placed in the lower plate, allowed controlling the temperature. The samples were equilibrated 3 min before starting the experiments. In flow measurements, the viscosity (η) was recorded as a function of the shear rate. The shear rate was increased gradually from 0.01 s -1 to 1000 s -1 over 3 min, maintained at 1000 s -1 for 1 min and then decreased gradually from 1000 s -1 to 0.01 s -1 over 3 min. In oscillatory measurements, linear viscoelastic regions, where the moduli remained constant as the shear stress increased, were determined. The gelation temperature (T gel ) and viscoelastic properties of the gels were assessed under a stress value belonging to their viscoelastic linear regime. A temperature sweep from 5 to 45 °C at a rate of 1 °C/min was performed at a frequency of 1 Hz, and the elastic modulus (G′) as well as the viscous modulus (G″) were recorded as a function of the temperature. The gelation temperature (T gel ) was determined as the temperature of the crossover of G′ and G″. G′ and G″ were also recorded during frequency sweeps from 0.01 to 50 Hz. These experiments were performed in triplicate.

pH measurement of the gels

pH of the gels was measured at room temperature with a pH-meter Mettler Toledo Seven2Go, suited for measurements in viscous aqueous media. This experiment was performed in triplicate.

Assessment of the distribution of L. crispatus within the gel

The distribution and viability of L. crispatus within the gels were assessed by using Syto9 that stained both living and dead bacteria in green and propidium iodide that stained only dead bacteria in red. When used simultaneously, Syto9 seemed to allow the observation of living bacteria in green, and propidium iodide the observation in red of the dead ones [START_REF] Moore | Development of a viability standard curve for microencapsulated probiotic bacteria using confocal microscopy and image analysis software[END_REF]. These fluorescent stains were introduced at 1/1000 (v/w) in the gels. In short, they were introduced in the 1-mL L. crispatus suspension before mixing it with the gels in the liquid state. Then, they were immediately observed by microscope. This study was performed with an inverted confocal laser scanning microscope LSM 510-Meta (Carl Zeiss, Germany) using a Plan-Apochromat 63X/1.4 objective lens, equipped with an argon (488 nm excitation wavelength) and a helium neon laser (543 nm excitation wavelength). The green and the red fluorescence emissions were collected with a 505-550 nm band-pass and a 560 nm long pass emission filter respectively, under a sequential mode. The pinhole was set at 1.0 Airy unit. For each condition, single 2D images were collected as well as 3D images with an image every 0.9 µm along the z axis to reach a thickness of 32 µm taken arbitrarily. 12 bit numerical images were acquired with LSM 510 software version 3.2.

Stability studies of the gel P21.5A1L

P21.5A1L was stored over six months at 4 and 25 °C, respectively below and above the gelation temperature, in order to assess its stability. The gel viscosity at a shear rate of 125 s -1 and pH were measured as previously described. Counting on MRS agar plate was performed to investigate the culturability of cells. In brief, after serial decimal dilutions, three dilutions were plated on MRS agar. Plates were incubated at 37 °C for 48 h before counting the colony forming units. Otherwise, L. crispatus distribution and viability were evaluated by confocal laser scanning microscopy. Briefly, the fluorescent stains (Syto9 and propidium iodide) were introduced at 1/1000 (v/w) in the liquid gels containing L. crispatus, vortexed and immediately observed by confocal microscopy as previously described in Section 2.8.

Inhibition of the growth of N. gonorrhoeae

For the preparation of N. gonorrhoeae suspension, the frozen stock was isolated on Thayer-Martin medium plate and incubated for 18 h at 37 °C in a moist atmosphere enriched with 5% CO 2 . These conditions were used because autolysis may occur during prolonged incubation, and it may be difficult to obtain a suspension from growth on agar plates. Then, colonies were suspended in NaCl 0.85% to a turbidity equivalent to 0.5 McFarland standard. These suspensions contained 10 6 N. gonorrhoeae cells/mL. They were mixed thoroughly using a vortex mixer to break up clumps of growth.

The inhibition of N. gonorrhoeae was evaluated by using a modified version of the agar overlay technique of [START_REF] Amant | Inhibition of Neisseria gonorrhoeae by Lactobacillus species that are commonly isolated from the female genital tract[END_REF]. Fig. 1 presents the method schematically. Brain heart infusion agars (BHIA) with pH adjusted either to 5 or 6.5 were prepared before being autoclaved at 121 °C over 15 min. Gels or suspensions containing L. crispatus were inoculated onto BHIA plates (60 mm diameter), using respectively a sterile handle or a micropipette to obtain spots of 0.5 g for the gels or of 50 µL for the suspensions. After 24 h of incubation, 4 mL of chocolate agar (containing proteose peptone, dextrose, sodium chloride, disodium phosphate, agar, hemoglobin) were poured onto the BHIA plates and allowed to solidify. Then, 500 µL of N. gonorrhoeae suspension were spread onto the agar overlay and incubated for 24 h. The presence of a zone of growth inhibition was considered as positive for inhibition. Control experiments were performed by using the same protocol without the step of spot formation. Moreover, the effect of a gel without L. crispatus was also assessed. For all experiments, the number of L. crispatus in the suspensions or the gels was confirmed by standard serial dilution and culture. The thickness of each agar layer was about 2 mm.

Results and discussion

In this study, a well identified and characterized reference strain that originated from a human vagina and that had already shown its efficacy on N. gonorrhoeae [START_REF] Amant | Inhibition of Neisseria gonorrhoeae by Lactobacillus species that are commonly isolated from the female genital tract[END_REF][START_REF] Breshears | Lactobacillus crispatus inhibits growth of Gardnerella vaginalis and Neisseria gonorrhoeae on a porcine vaginal mucosa model[END_REF] was selected. Its probiotic benefits such as its acidification ability and its capacity to auto-aggregate or co-aggregate N. gonorrhoeae were first confirmed before formulation development and in vitro efficacy studies.

Characterization of L. crispatus

Based on published data, L. crispatus suspensions containing 9 log 10 CFU/mL were selected. [START_REF] Amant | Inhibition of Neisseria gonorrhoeae by Lactobacillus species that are commonly isolated from the female genital tract[END_REF] showed the effectiveness of different dilutions of 10 8 L. crispatus on N. gonorrhoeae and [START_REF] Reid | Probiotic Lactobacillus dose required to restore and maintain a normal vaginal flora[END_REF] showed the effectiveness of over 10 8 viable probiotic per day to restore and maintain a normal vaginal flora. An expert consensus document stated that the minimal number of viable cells should be 1 × 10 9 CFU administered per day [START_REF] Hill | Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic[END_REF].

L. crispatus growth kinetic test allowed determining its stationary phase that began after 9 h of culture. Based on this result, for all the tests, cultures of 16 h of incubation were used to ensure reproducible physiological and metabolic states of the strain.

As regards L. crispatus acidification ability, this strain was grown in either standard growth medium (pH i 6.5) or in modified pH growth medium (4, 5, 6, 7). The use of these pH values was based on the fact that vaginal pH varies between 3.5 and 5.5 and increases up to 7 in the presence of seminal fluid [START_REF] O'hanlon | Vaginal pH and microbicidal lactic acid when Lactobacilli dominate the microbiota[END_REF][START_REF] Owen | A vaginal fluid simulant[END_REF]. Therefore, the growth and the acid production of L. crispatus were simultaneously evaluated in MRS at pH ranging from 4 to 7 to mimic this vaginal pH. In MRS, the Lactobacilli had the nutrients they needed to grow and pH was the only modified parameter in order to assess its influence. The growth of L. crispatus was favored at pH ranging from 6 to 7 (Table 2). This pH range corresponded to the pH of the mixture of polymers, which should thus be favorable for L. crispatus addition. Otherwise, whatever the pH i of MRS, a decrease in pH values was observed after 24 h of incubation at 37 °C and 5% CO 2 , mimicking the vaginal conditions. The variations of pH are given in Table 2. They were also higher at pH varying between 6 and 7, suggesting a correlation between L. crispatus viability and acid production. A reduction of pH by L. crispatus indicated indirectly an acidification due to lactic acid production. Thus, this result suggested higher lactic acid production at pH higher than 6. Both pH and lactic acid concentration of a media may inactivate pathogens individually or in combination. [START_REF] O'hanlon | Vaginal pH and microbicidal lactic acid when Lactobacilli dominate the microbiota[END_REF] showed that as the alkaline pH of the vagina due to seminal fluid reduced the protective action of vaginal acidity against pathogens, the level of vaginal lactic acid was likely to reduce the transmission of vaginal acid-sensitive pathogens. As only protonated lactic acid might have microbicidal activity, it would be better to have a pH below the pKa of lactic acid (3.90) [START_REF] Tachedjian | The role of lactic acid production by probiotic Lactobacillus species in vaginal health[END_REF]. In this study, the quantity of protonated lactic acid was not measured, but as the final pH in each sample was between 3.1 and 3.9, it can be supposed that lactic acid was in its protonated state favorable for its antibacterial activity. The final pH in each sample was comparable to the pH of healthy vagina dominated by Lactobacilli as described by O' Hanlon et al. (2013).

Moreover, [START_REF] Graver | The role of acidification in the inhibition of Neisseria gonorrhoeae by vaginal Lactobacilli during anaerobic growth[END_REF] showed the important role of acidification in the inhibition of N. gonorrhoeae. [START_REF] Foschi | Vaginal Lactobacilli reduce Neisseria gonorrhoeae viability through multiple strategies: an in vitro study[END_REF], the presence of lactate seemed to be crucial for the anti-gonococcal activity, especially for pH values ranging from 4.4 to 5.3, indicating that the presence of hydrogen ions was necessary but not sufficient to inhibit gonococci. In our study, results of the acid production and the growth of L. crispatus in the pH range of 4 to 7 predicted a favorable growth in the vagina containing natural nutrients and favorable conditions for the inhibition of N. gonorrhoeae (see Section 3.5). [START_REF] Amant | Inhibition of Neisseria gonorrhoeae by Lactobacillus species that are commonly isolated from the female genital tract[END_REF] also showed the ability of this Lactobacillus strain to inhibit N. gonorrhoeae both at acid and neutral pH. Based on these studies, the higher reduction in pH related to higher lactic acid production was considered as more interesting.

The auto-aggregation and co-aggregation with N. gonorrhoeae properties of L. crispatus were investigated. Fig. 2 shows their organization in suspension after a 4 h-incubation time in suspension. L. crispatus formed large and dense visible clumps (Fig. 2A) whereas N. gonorrhoeae formed a clump similar to that observed by [START_REF] Anderson | Seminal plasma promotes Neisseria gonorrhoeae aggregation and biofilm formation[END_REF] (Fig. 2C), with an aspect different than that of L. crispatus (Fig. 2A). Small and widely distributed aggregates were observed in the mixtures of L. crispatus and N. gonorrhoeae (Fig. 2B). They were arranged as microcolonies similar to the ones observed by [START_REF] Foschi | Vaginal Lactobacilli reduce Neisseria gonorrhoeae viability through multiple strategies: an in vitro study[END_REF]. L. crispatus can change its organization in the presence of pathogens to co-aggregate with them. [START_REF] Reid | Coaggregation of urogenital bacteria in vitro and in vivo[END_REF] showed that when Lactobacilli formed co-aggregates and bound to pathogens, this resulted in returns to homeostasis, because co-aggregation created a hostile biochemical micro-environment around the pathogen and prevented it from continuation of growth and domination of the niche.

Regarding the security aspect associated with the use of this L. crispatus strain, two parameters were studied, its hemolytic activity and its antimicrobial resistance. Hemolytic activity test showed that the Columbia sheep blood agar aspect around the colonies was unchanged, meaning L. crispatus did not exhibit hemolysis. It is a non-hemolytic bacterium. This result was in accordance with many reports [START_REF] Ambalam | Safety assessment of potential probiotic strains Lactobacillus rhamnosus 231 and Lactobacillus rhamnosus v92 in mouse model[END_REF][START_REF] Kassaa | Identification of vaginal Lactobacilli with potential probiotic properties isolated from women in north Lebanon[END_REF][START_REF] Maragkoudakis | Probiotic potential of Lactobacillus strains isolated from dairy products[END_REF]. The antibiotic resistance is another key factor for probiotics as the level of susceptibility to the antimicrobial agents is species-dependent. Table 3 presents the results of the disc method. The E-test and the disc method gave similar results for the antibiotics studied by both methods. The resistance to gentamicin and ciprofloxacin was observed both by E-test and disc diffusion methods. Results showed that L. crispatus was resistant to an aminoglycoside (gentamicin), quinolones (ciprofloxacin, nalidixic acid, pefloxacin) and a lincosamide (clindamycin) (Table 3). Several studies have reported intrinsic resistance of Lactobacilli to quinolones, gentamicin, and other antibiotics [START_REF] Danielsen | Susceptibility of Lactobacillus spp. to antimicrobial agents[END_REF]; [START_REF] Štšepetova | Assessment of phenotypic and genotypic antibiotic susceptibility of vaginal Lactobacillus sp[END_REF][START_REF] Temmerman | Identification and antibiotic susceptibility of bacterial isolates from probiotic products[END_REF]. According to the European Food Safety Authority (EFSA) guidance on the assessment of bacterial susceptibility to antimicrobials of human and veterinary importance, bacterial strains carrying intrinsic resistance present a minimal risk for horizontal spread and thus, may be used as a food additive. Based on these in vitro tests, L. crispatus is an interesting probiotic candidate. However, further studies should be performed to search for pathogenicity genes, as well as in vivo studies to confirm that this L. crispatus strain would not induce any pathogenicity and could be regarded as a safe microorganism for a vaginal administration.

Preparation and rheological characterization of gels

In a second step of our study, L. crispatus was incorporated in an aqueous mixture of poloxamer 407 and sodium alginate in order to develop a formulation with characteristics that were suitable for a vaginal administration. In a preliminary optimization step, the concentration of poloxamer 407 (21.5%) and sodium alginate (1%) were selected in order to obtain a formulation that remained in gel state at 37 °C, even after dilution with SVF, with minimal polymer concentrations. Thereafter, the study focused on this gel denoted P21.5A1 and on its corresponding gel (P21.5A1L) containing L. crispatus at 9 log 10 CFU per gel sample (5 g). The counting of Lactobacilli in both suspensions and gels after their preparation showed that, in the gel, it represented 1/5 of the number in the suspension. That corresponded to the dilution ratio of L. crispatus suspension (1 mL) with the gel (4 g). This result suggested that the fabrication process was not deleterious for the Lactobacilli.

Both gels were characterized by rheology (Fig. 3, Table 4). The gel without L. crispatus, P21.5A1, showed a shear-thinning behavior (Fig. 3A,B). This behavior should allow an easy administration. This formulation was also non-thixotropic even after dilution by the simulated vaginal fluid (Fig. 3A,B). Therefore, as soon as the shear was removed, the viscosity returned to its initial high value, which should be favorable to maintain the gel at the administration site and to increase the residence time of the formulation in the vagina. P21.5A1 also had a thermogelling behavior (Fig. 3C). Below T gel , the elastic modulus (G′) was lower than the viscous modulus (G″) revealing a dominant viscous behavior. Above T gel , G′ was higher than G″ showing a dominant elastic behavior. P21.5A1 gelation temperature was 19 ± 1 °C. After dilution with SVF, T gel was increased (Fig. 3C,D,Table 4) whereas the viscoelastic moduli values decreased due to the diminution of the concentration of poloxamer (Fig. 3C versus D and E versus F, Table 4). Aka-Any-Grah et al. ( 2010) also observed this phenomenon. Interestingly, when L. crispatus was introduced into the gel (P21.5A1L), the rheological properties were similar to those of P21.5A1 (Fig. 3, Table 4). Thus, L. crispatus did not significantly affect the rheological properties of this mixture of poloxamer 407 and sodium alginate, even after dilution with SVF.

Table 3

Antibiotics susceptibility of L. crispatus by disc diffusion method as a mean of at least two repetitions, showing highlighted in gray the antibiotics to which L. crispatus was resistant. Teicoplanin (TEC, 30 μg) 15

Antibiotic discs (dose

Distribution of L. crispatus within the gel

For further characterization of the gel containing L. crispatus, the distribution of L. crispatus immediately after the gel preparation was studied by confocal fluorescence microscopy (CLSM), using both Syto9 and propidium iodide (Fig. 4). [START_REF] Zotta | A comparison of fluorescent stains for the assessment of viability and metabolic activity of lactic acid bacteria[END_REF] showed the usefulness of two stain indicators for optimal results in the evaluation of cells viability. In the present study, Syto9 was used to stain live bacteria in green whereas propidium iodide was used to stain dead cells. Almost all the L. crispatus cells were green stained confirming their viability after their introduction into the gel. The distribution seemed to be similar at all the observed points, from two different wells of the same gel. Thus, CLSM showed a homogeneous distribution of L. crispatus in the gel along the x, y and z axes (Fig. 4). This distribution of L. crispatus was repeatable and reproducible, showing the reproducibility of the method of gel preparation. This homogeneous distribution of L. crispatus in the gel should be favorable to a homogeneous distribution of L. crispatus in the vagina after administration.

Influence of the storage conditions

The stability of the gel P21.5A1L was examined for 6 months at two different storage conditions: 4 and 25 °C. Viscosity of the gel (Fig. 5A,B) as well as its pH (Fig. 5C,D) remained unchanged over these 6 months of storage at both temperatures (Fig. 5A, C and Fig. 5B,D). However, the viability and the culturability of formulated L. crispatus were modified (Figs. 6 and7). The number of L. crispatus assessed by counting on MRS agar plate decreased drastically after 14 days of storage at 4 °C (Fig. 6) and after 2 days at 25 °C (Fig. 7). The number of L. crispatus was assessed by confocal microscopy using Syto9 and propidium iodide (Fig. 6). Samples were analysed by two types of acquisition, the z-stack acquisition of two different areas and the single stack of

Table 4

Influence of L. crispatus on the rheological properties of the gel containing poloxamer 407 at 21.5% and sodium alginate at 1% at three different conditions: 25 °C, 37 °C and 37 °C after dilution with SVF. eight different areas. The coefficient of correlation between the two types of image acquisition was 0.93. Despite the observation of greenlabeled bacteria on the images of the confocal microscopy, there was no bacterial count by agar count method on MRS plate at D180 (storage at 4 °C) and at D14 and D180 (storage at 25 °C). This result suggested the development of viable but nonculturable (VNC) bacteria in the gel during storage at both 4 °C and 25 °C. This can be due to the absence of nutrient inducing a stress of L. crispatus in the gel. Indeed, the enumeration by agar plate method often leads to an underestimation of bacterial total number due to the formation of cells chains and clumps or to the induction of VNC state after an exposure to stress or starvation [START_REF] Léonard | Preservation of viability and anti-Listeria activity of lactic acid bacteria, Lactococcus lactis and Lactobacillus paracasei, entrapped in gelling matrices of alginate or alginate/caseinate[END_REF][START_REF] Rault | Multiparametric flow cytometry allows rapid assessment and comparison of lactic acid bacteria viability after freezing and during frozen storage[END_REF][START_REF] Zotta | Viability staining and detection of metabolic activity of sourdough lactic acid bacteria under stress conditions[END_REF]. These results are in accordance with several studies which showed that cell viability estimated by microscopy was higher than viability assessed by plate counts. VNC cells can not be cultured using standard microbiological media because they are incapable of undergoing the sustained cellular division required to form a colony on regular agar media but they often maintain a potential for metabolic activity at the single cell level [START_REF] Zotta | Viability staining and detection of metabolic activity of sourdough lactic acid bacteria under stress conditions[END_REF].

As the number of viable L. crispatus decreased in gel during storage, further studies are needed to preserve its viability over time. In this respect, hydrogel lyophilization, addition of prebiotics in the formulation, or extemporaneous mixing of gel and L. crispatus might be interesting strategies.

Efficacy of inhibition of N. gonorrhoeae

The ability of L. crispatus to inhibit the growth of N. gonorrhoeae in vitro, was asssed at two different pH (5, 6.5) (Table 5). In the absence of L. crispatus, N. gonorrhoeae grew onto chocolate agar at pH 6.5 but did not grow onto this media at pH 5.0. The inhibition of N. gonorrhoeae was due to the acidic environment. After deposition of spots of L. crispatus suspension onto BHIA at pH 6.5, an inhibition zone of N. gonorrhoeae was clearly observed. These results were in accordance with those of [START_REF] Foschi | Vaginal Lactobacilli reduce Neisseria gonorrhoeae viability through multiple strategies: an in vitro study[END_REF], who demonstrated that the L. crispatus strains they studied were also able to counteract N. gonorrhoeae viability through multiple mechanisms (acidic environment creation, lactate production, biosurfactant production and co-aggregation), and could represent a new potential probiotic strategy for the prevention of gonorrhea in women.

The gel P21.5A1 alone had no effect on N. gonorrhoeae growth. Conversely, at pH 6.5, the P21.5A1L gel containing L. crispatus inhibited the growth of pathogens (Table 5) with an efficacy depending on L. crispatus load. L. crispatus was thus responsible of the inhibition by the gel at pH 6.5. When using BHIA pH 6.5, the inhibition zone of the suspension containing 8 log 10 L. crispatus was similar to the inhibition zone of the gel containing 9 log 10 L. crispatus. The gel, due to its viscosity, could slow down the diffusion of substances that are produced by L. crispatus and are involved in the inhibition mechanisms. Despite this lower in vitro efficacy compared to a simple L. crispatus suspension, gels remain interesting formulations. Indeed, liquid suspensions are known to lead to a rapid flow and clearance after vaginal administration whereas the gel will have a higher residence time due to its viscosity and mucoadhesive properties. Otherwise, the method used to assess the inhibition of N. gonorrhoeae only explored the influence of the pH and the diffusion of inhibitory molecules through the agar layer (~2 mm). Further studies by direct contact with N. gonorrhoeae should be performed to determine if L. crispatus, when incorporated in gel formulations, preserves all its inhibition properties on N. gonorrhoeae under the conditions prevailing in the vaginal cavity in vivo.

Table 5

Inhibition of the growth of N. gonorrhoeae in vitro by agar overlayed method, after 24 h of incubation at 37 °C, 5% CO 2 . Comparative study of L. crispatus suspension and of gels P21.5A1 and P21.5A1L. Four different experiments (tests).

Conclusion

This study showed the probiotic potential of L. crispatus ATCC 33197 and its ability to inhibit N. gonorrhoeae. L. crispatus can be considered as a good candidate to be used in the development of vaginal formulations for the prevention of gonorrhea. Gels containing poloxamer 407 at 21.5% and alginate at 1% with or without L. crispatus ATCC 33197 showed rheological properties favorable for a vaginal administration. Their process of preparation was not deleterious for the Lactobacilli cells. L. crispatus was able to inhibit N. gonorrhoeae even when incorporated in the gel. Therefore, this vaginal gel could be promising as a single-dose system intended to be administered to women at risk due to a history of vaginal infections and to women having naturally a deficiciency of lactobacilli in their vaginal flora. Such treatment might limit gonorrhoea transmission in women that do not have the possibility to negotiate the use of condom during sexual intercourses. Yet, L. crispatus viability should be optimized by lyophilization or the addition of some nutrients in the formulation and in vivo studies should also be conducted to evaluate the efficacy and the safety of the gel. The number, frequency and timing of administration, as well as the effect of sexual intercourses, are important parameters to assess in further clinical studies.

Fig. 1 .

 1 Fig. 1. Schematic depiction of the inhibition of N gonorrhoeae test: ① brain heart infusion agar at pH 5 or 6.5, ② spots of gels or suspensions containing L. crispatus after incubation 24 h, 37 °C, ③ chocolate agar medium, ④ spreading of N. gonorrhoeae, ⑤ inhibition zones.

Fig. 2 .

 2 Fig. 2. Aspects of clumps in aggregation tests after 4 h of incubation (×100). A: L. crispatus; B: mixture of L. crispatus and N. gonorrhoeae; C: N. gonorrhoeae. Scale bars correspond to 10 μm.

Fig. 3 .

 3 Fig. 3. Comparison of the rheological properties of P21.5A1 and P21.5A1L: flow properties (A, B), temperature sweep displaying one data point out of ten (C, D), and viscoelastic properties at 1 Hz (E, F), for gels without SVF (A, C, E) and with SVF (B, D, F). For P21.5A1: ( ) η, (■) G′, (□) G″, and for P21.5A1L: (♦) η, (♦) G′, (♢) G″. Note that P21.5A1 and P21.5A1L curves are superimposed.

Fig. 4 .Fig. 6 .Fig. 7 .

 467 Fig. 4. Representative confocal microscopy image of the distribution of L. crispatus within the P21.5A1L hydrogel immediately after their preparation, showing a large majority of L. crispatus in green (living bacteria). Dead bacteria appear in red. Images correspond to the stacking of 37 images collected along the z-axis. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Table 1

 1 Hydrogels containing alginate (A), poloxamer (P) with or without L. crispatus (L).

	Acronyms Poloxamer (% w/w) Alginate (% w/w) L. crispatus (log 10 CFU/5 g of gel)
	P21.5A1	21.5	1	-
	P21.5A1L 21.5	1	9

Table 2

 2 Growth of L. crispatus and reduction in pH values due to L. crispatus acid production obained with different initial pH values. Mean of three replicates on two separate experiments.

	Initial pH

International Journal of Pharmaceutics 588 (2020) 119733

Acknowledgements

This work was supported by Institut de recherche et de développement (IRD), Franco-Ivorian cooperation, Campus France, AMRUGE-CI/C2D grant (support to the modernization and reform of universities and colleges of Côte d'Ivoire). The authors thank the region île-de-France for the purchase of the confocal microscope and are grateful to Luc Picton and Christophe Rihouey from Laboratoire Polymères, Biopolymères, Surfaces, UMR 6270 CNRS, Université de Rouen, for the determination of alginate molecular weight and Charles Konan Kouassi from Université Abobo-Adjamé for his technical help during optical microscopy observations. Clémence N'Guessan acknowledges Université Paris-Saclay for her international dual degree PhD grant.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Paul Tourniaire
email: paul.tourniaire@inria.fr

Marius Ilie
email: ilie.m@chu-nice.fr

Paul Hofman
email: hofman.p@chu-nice.fr

Nicholas Ayache
email: nicholas.ayache@inria.fr

Hervé Delingette
email: herve.delingette@inria.fr

Attention-based Multiple Instance Learning with Mixed Supervision on the Camelyon16 Dataset

Keywords: Attention Mechanism, Mixed Supervision, Histopathology

Since the standardization of Whole Slide Images (WSIs) digitization, the use of deep learning methods for the analysis of histological images has shown much potential. However, the sheer size of WSIs is a real challenge, as they are often up to 100,000 pixels wide and high at the highest resolution, and therefore cannot be processed directly by any model. Moreover, as the manual delineation of structures within WSIs is tedious, histological datasets often only contain slide-level labels, or a limited amount of delineated slides. In this context, multiple-instance learning (MIL) approaches have been proposed, considering WSIs as bags of smaller images, designated as tiles or patches. Among these methods, the attention-based MIL aims at learning the importance of each tile for the slide final classification while at the same time performing a clustering of those tiles. In this paper, we introduce the concept of mixed supervision within this framework, by exploiting tile-level labels in addition to slide-level labels to improve the classification of slides. More precisely, we show on the Camelyon16 dataset that even a small proportion of slides with pixel-wise annotations can improve their classification but also the localization of tumorous regions. This improves the consistency of the results between the tile and slide levels and the interpretability of the algorithm.

Introduction

In terms of tumor assessment, histopathology is currently the clinical gold-standard diagnosis technique. Nonetheless, pathologists face multiple challenges when confronted to Whole Slide Images (WSIs), and often require careful and time-intensive efforts. WSIs are usually stained with Hematoxylin and Eosin (H&E) and scrutinized through a microscope by the pathologist in order to detect cancerous tissue. Given the size of tissue samples, and the potential artifacts that may occur, such as tissue folds or tears, the diagnosis is often tedious. Since the digitization of pathological slides, machine and deep learning algorithms have offered automated solutions for the diagnosis of tumors [START_REF] Babak | Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer[END_REF][START_REF] Wang | Weakly supervised deep learning for whole slide lung cancer image analysis[END_REF]. However, pixel-level annotations such as tumor segmentation are usually unavailable, since the annotation process requires both time and medical expertise: datasets often only display slide-level labels. Among deep learning algorithms for weakly-supervised learning, some of the most popular are based on the multiple instance learning assumption (MIL). As such, the WSI is divided into tiles or patches of smaller size (e.g. 512 x 512 pixels 2 ) and the slide is considered normal if all instances (tiles) are normal, and tumorous if at least one tile contains tumor. The tile-level predictions are then aggregated following various mechanisms to provide the slide-level or patient-level label [START_REF] Campanella | Clinical-grade computational pathology using weakly supervised deep learning on whole slide images[END_REF][START_REF] Courtiol | Classification and disease localization in histopathology using only global labels: A weakly-supervised approach[END_REF].

The attention mechanism was recently proposed as the tile pooling function [START_REF] Ilse | Attention-based deep multiple instance learning[END_REF]. The authors propose to extract tile-level features with a convolutional network [START_REF] Sirinukunwattana | Locality sensitive deep learning for detection and classification of nuclei in routine colon cancer histology images[END_REF], and use a two-layered neural network to calculate a weighted average and select key instances for the slide-level prediction. A recent improvement of the attention-based MIL was proposed in the CLAM (Clustering-constrained Attention Multiple instance learning) algorithm [START_REF] Lu | Data-efficient and weakly supervised computational pathology on whole-slide images[END_REF]: the introduction of instance-level clustering during training, where instances given the highest (resp. lowest) attention scores were considered positive (resp. negative) evidence of the slide class. A smooth SVM loss [START_REF] Berrada | Smooth loss functions for deep top-k classification[END_REF] calculated on the instance-level prediction using an instance classifier is then added to the overall slide-level cross-entropy. For the tile-level feature extraction, a frozen ImageNet pre-trained ResNet50 [START_REF] He | Deep residual learning for image recognition[END_REF] is used, so as to accelerate the training procedure. This, however, was identified as a major caveat by [START_REF] Dehaene | Self-supervision closes the gap between weak and strong supervision in histology[END_REF], who decided to replace the backbone with a self-supervised deep neural network, trained on histological images using contrastive loss [START_REF] He | Momentum contrast for unsupervised visual representation learning[END_REF]. On the Camelyon16 dataset [START_REF] Babak | Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer[END_REF], they showed performance close to the best performing fullysupervised method [START_REF] Wang | Deep learning for identifying metastatic breast cancer[END_REF], but at the cost of heavy and long GPU training.

When pixel-level labels are available, the combined use of pixel-level and image-level labels is coined mixed supervision. It is especially useful when the amount of pixel-level annotated images is low, in regards to the total amount of available images. [START_REF] Mlynarski | Deep learning with mixed supervision for brain tumor segmentation[END_REF] showed that using weakly and fully annotated data to train a deep learning model for brain tumor segmentation improved the segmentation performance compared to the baseline trained only on fully annotated data. [START_REF] Ciga | Learning to segment images with classification labels[END_REF] simultaneously trained a ResNet18 model on classification and segmentation tasks, leveraging only a part of available fully annotated data, to obtain the same performance as models trained on the entire fully labeled dataset. However, both classification and segmentation tasks relied on tile-level information, the authors having devised a strategy to select tiles suited for either task.

In this work, starting from the CLAM framework, we propose the first mixed supervision approach within the attention-based MIL framework. Our main goal is not only to improve the slide-level classification, but also the localization performance of the model. Our contributions are listed as follows:

• First, we introduce mixed supervision for the MIL framework inside the CLAM algorithm. • Second, we propose an improvement of the instance-level clustering method in the case of non-pathological slides.

• Finally, we show that we can improve the model's classification performance and the localization of tumorous tiles by adding a small amount of ground-truth tile-level labels along with slide-level labels.

Methods

Data preprocessing

For the preprocessing of the WSIs, we first transform a downsampled version of the image to the HSV space and apply Otsu thresholding [START_REF] Otsu | A threshold selection method from gray-level histograms[END_REF] on the hue and saturation channels to detect tissue. Then, we extract 256 x 256 non-overlapping tiles from the tissue region, at the highest magnification level. For the tiles feature extraction, we use the same model as [START_REF] Lu | Data-efficient and weakly supervised computational pathology on whole-slide images[END_REF], i.e. a ResNet50 architecture without the final classification layer, and an output dimension of 1024.

CLAM Algorithm

Description of the original model

Slide-level classification. The overview of the model can be seen in Figure 1. We consider a classification problem with n classes, and detail only the "multiple branches" version of CLAM (CLAM MB). A slide is represented as a feature matrix z, of size 1024 x N, where N is the number of tiles in the slide. A first fully-connected layer W 1 transforms each 1024-dimensional feature vector z k into a 512-dimensional feature vector h k , where k is the tile index. Then a gated-attention module computes the attention weights from h for each of the n classes, following:

a k,m = W a,m (tanh(V a h k ) sigm(U a h k )) N i=1 exp{W a,m (tanh(V a h i ) sigm(U a h i ))} (1)
where m is the class index, and V a , U a , and W a are fully-connected layers. The attention weights are represented by the matrix A ∈ R N×n . Before the final binary classification layers W c,m , each feature vector h k is multiplied by its corresponding attention weight. This operation is represented by the matrix M = A h. Finally, each column of M (representing one of the n classes) is independently processed by one of the n classifiers to obtain the slide-level score for each class. A softmax activation function is eventually applied on the logits, and a cross-entropy loss L slide is computed on the obtained scores.

Instance-level clustering. Based on the attention scores a k,m , the tiles with the highest (resp. lowest) scores are retrieved for each class, and assigned a positive (resp. negative) pseudo-label. The assumption is that high-attention tiles are positive evidences of the class, whereas the low-attention tiles are negative evidences. For each class, a binary classifier W inst,m classifies the gathered instances, and computes a tile-level smooth top-1 SVM loss L patch which is added to L slide to give the global loss term: L = c 1 L slide + c 2 L patch where c 1 and c 2 are hyperparameters.

The instance-level clustering does not directly affect the slide-level classification, rather, it encourages the learning of discriminative features by the model layer W 1 to better separate classes. Note that the inference of slide-level classification does not use the instance level clustering.

Instance-level clustering for non-pathological slides

Given a tumor diagnosis task on a histopathological dataset, where some slides contain tumors, and others not, there is a caveat with the current formulation of the instance-level clustering: indeed, when assigning negative pseudo-labels to low-attention tiles, the model is actually learning that these tiles are not normal, and should therefore be classified as such. However, it is one of the hypotheses of MIL to consider all instances of a non-tumorous slide to be tumor-free. Therefore, all tiles originating from a non-tumorous slide should be classified as non-tumorous too. As a result, we decide to ignore the instance classifier W inst,normal , and instead use the tumor instance classifier W inst,tumor to classify the B patches with the highest attention scores in normal slides as negative evidence of tumors. That way, we expect to reduce the number of false positives in the final classification. Furthermore, we also ignore W inst,normal to classify the patches from tumorous slides, and use only W inst,tumor . Indeed, without the need for histological subtyping, only a single binary classifier is required to perform the distinction between tumorous and non tumorous images. W inst,normal remains therefore unused in our model.

Mixed supervision: Instance-level classification with ground-truth labels

Instead of selecting the tiles based on the highest and lowest attention scores, we introduce a mixed supervision formulation of the instance-level clustering which is now qualified as instance-level classification. On slides where tumorous regions were delineated by expert annotators, we propose to select tiles based on whether they belong to those tumorous regions. In doing so, we are sure that the instance-level classification layer learns with instances truly representative of two classes which is not the case when they are selected based on their attention score. This selection is only performed on slides for which annotations are available, which may be a small proportion of the histological training set. In fact, we hope to improve the model performance in classification and tumor localization (i.e. the tile-level classification of the slide) even with a small ratio of tile-level labels.

The training stage is therefore divided into two parts: first, only the subset of slides with pixel-wise annotations along with a subset of normal slides is used to train the model. This is to train the instance level classifier on true classes without the noise generated by the original pseudo-labeling procedure. We use various subset proportions (10, 50, 80% of the training slides) to measure the impact of the annotations on the results. For a tumorous slide containing N tiles such that N = N tumor + N normal , we randomly sample min(K, N tumor ) tiles from the tumorous ones, and min(K, N normal ) among the normal ones, where K is a hyperparameter. Then, positive and negative labels are generated for the two sets of tiles, and a score is assigned to each tile t following: l t = W inst,tumor h t . Second, the entire training set is used, this time without using any instance-level label, leveraging only slide-level labels. This procedure is summarized by Algorithm 1.

Implementation details

During training, we used a batch size of 1. We used the Adam optimizer (Kingma and Ba, 2014) with β 1 = 0.9 and β 2 = 0.99, and a learning rate of 2.10 -4 . All models were trained on a single NVIDIA GeForce GTX 1080 GPU. We used 70 epochs with early stopping after 20 epochs without improvement on the slide-level cross-entropy loss in the validation set.

During the first part of the training, we set c 1 = c 2 = 0.5 (when using tile-level labels) so that both loss terms L slide and L patch are weighted equally, and c 1 = 0.7 and c 2 = 0.3 during the second part, for these were the values used by [START_REF] Lu | Data-efficient and weakly supervised computational pathology on whole-slide images[END_REF] in their article. For hyperparameter K, we tested several increasing values (128,256,512,1024,5000), and we used the value K = 1024, for which we reached the best performance. The value B = 8 was kept from the original model.

Results

Data description and experiments

The Camelyon16 dataset

The Camelyon16 challenge [START_REF] Babak | Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer[END_REF] aimed at detecting metastases in H&Estained WSIs of lymph node sections. The dataset contains 399 slides, split between a training set of 270 slides, and a test set of 129 slides. The slides were prepared and stained in two different medical centers. All slides that contain metastases (111 slides in the training set, 49 in the test set) have been exhaustively annotated (except for 20 of them in the training set, partially) by a group of expert pathologists. Annotations are available as XML files and can be converted to binary masks using the Automated Slide Analysis Platform (ASAP) open source software (https://github.com/computationalpathologygroup/ASAP). All slides were scanned at 40x magnification ( 0.25µm/pixel).

Algorithm 1: Instance-level classification using tile-level labels Data:

(h 1 , ..., h N ), Y (the slide label), K, B Result: l Y l Y ← {} if Y = "tumor" then K tumor = min(K, N tumor ) K normal = min(K, N normal ) Select t 1 , ...,

Experimental setup

To measure the classification performance of our models, we decided to use the area under the receiver operating characteristic curve (AUC), as it was the metric used for the challenge, along with the F1-score. All models were evaluated on the challenge test set. The training set was further split into a training and a validation set. We used 5-fold cross validation to perform these splits in order to select the best performing model. In the training set, we randomly sampled k% (k ∈ {10, 50, 80}) of the slides to use with tile-level labels outside of the 20 with only partial annotations.

For the localization performance, we computed slide binary masks based on the outputs of the instance-clustering layer W inst,tumor after having applied a threshold of 0.5. The masks were computed at the 5 th resolution level. Furthermore, we used two different metrics for normal and tumorous slides: in the former, we computed the tile-wise specificity, i.e. the amount of tiles erroneously classified as tumor divided by the total amount of tiles. In the latter, we computed the Dice score in reference to the ground-truth mask. This metric was computed on 46 slides from the test set, as 3 metastatic slides out of the 49 were unavailable (one because the annotation file is absent from the dataset, the other two because of an error when computing the reference masks from the annotation file in ASAP).

Evaluation

The test set classification results are shown in Table 1. For all models, we report the performance from the best fold, as it is usually done in challenges. We can see that the models with tile-level labels all outperform the CLAM algorithm in terms of slide-level classification, even when only 10% of the annotated slides were used. Moreover, we can see that the models trained with tile-level labels have also higher scores on localization tasks, both for tumorous (mean dice scores) and normal slides (mean specificity). In particular, models trained with tile-level labels tend to detect less falsely tumorous tiles than the reference model. Figure 2 shows an example of a tumorous slide from the test set and the masks computed using CLAM and two other annotation-based models. We can see that although the tumorous region is quite well detected in CLAM, there are many false positive tiles. When using tile-level labels however, these false positives tend to disappear, and the detected region is closer to the ground truth. Figure 3 is another example from the test set of the difference between CLAM and annotation-based models. Figure 4 shows an example of a normal slide (also taken from the test set): here again, we can see that there are many more false positives when using CLAM. Using only 10% (resp. 80%) of the annotated slides, our method would have ranked 6 th (resp. 4 th ) on the challenge open leaderboard.

Discussion & Conclusion

In this work, we presented a mixed supervision approach for attention-based MIL. We proposed to add strong supervision in the tile classification branch of the CLAM algorithm for a subset of the training slides. We showed that even with a small amount (10%) of slides with pixel-wise annotations of tumors, we were able to obtain improved classification of slides and above all a better localization of the tiles with tumour tissue. In particular, we witnessed a sharp decrease in the number of false positive tiles, i.e. a better discrimination between tiles with normal and tumorous tissue. This better localization of tumors is crucial for WSI with only slide-level labels, since machine learning algorithms may provide the correct classification at the slide level but not necessarily with correct classifications at the tile level. This work shows that even with fairly limited pixel-wise annotation, it is possible to obtain more consistent and robust results at both local (tile) and global (slide) levels. Finally, the better localization of tumorous tiles and reduced rate of false positives in non-pathological slides also improves the interpretability of the provided slide classification algorithm which is key for the adoption of those algorithms in clinical practice. The proposed approach may be improved in several ways. We have noticed that on the original CLAM and on our mixed supervised version, the localization performance of tumorous tiles may vary from one fold to the next. For our method, one or two folds (out of five) have significantly worse results than the other folds. This may be due to the lack of stain normalization performed since the slides originate from two distinct centers with different acquisition equipment. Considering that only two centers were involved in the acquisition of the challenge data, we originally did not consider that stain normalization was essential. Moreover, in the method that won the challenge [START_REF] Wang | Deep learning for identifying metastatic breast cancer[END_REF], some post-processing steps were applied to improve the localization accuracy. In our case, no post-processing was performed, and only a coarse localization map was computed, which could be refined for improved accuracy. Finally, the original CLAM paper considered the attention weights a k,m rather than the instance-level clustering as the source of information to localize pathologies. Therefore, it may also be interesting to supervise the attention mechanism with pixel-wise annotation similarly to what we proposed in this paper on the tile classification.

Figure 1 :

 1 Figure 1: Overview of the CLAM model. Activation functions are not detailed in the interest of clarity. The original instance selection approach appears in blue (based on the attention scores), whereas our annotation-based instance selection approach appears in red.

Figure 2 :

 2 Figure 2: Metastatic slide test 016 from Camelyon16 (the metastasis region is delineated in black), next to binary masks computed using the different models. (b) displays the results of the CLAM algorithm, (c) and (d) show the results obtained using 10% and 80% of tile-level labels.

Figure 3 :

 3 Figure 3: Metastatic slide test 068 from Camelyon16 (the metastasis region is delineated in black), next to binary masks computed using CLAM, and the model with 10% of tile-level labels.

Figure 4 :

 4 Figure 4: Slide test 042 from Camelyon16 without tumor, next to binary masks computed using CLAM, and the model with 10% of tile-level labels.

  t Ktumor // tumor tiles indexes Select t 1 , ..., t K normal // normal tiles indexes for t ← t 1 , ..., t Ktumor do generate positive label y t = 1 l t = W inst,tumor h t end l Y ← l Y ∪ {l t } for t ← t 1 , ..., t K normal do generate negative label y t = 0 l t = W inst,tumor h t end l Y ← l Y ∪ {l t } else Select t 1 , ..., t B for t ← t 1 , ..., t B do generate negative label y t = 0 l t = W inst,tumor h t end l Y ← l Y ∪ {l t } end

Table 1 :

 1 Classification and localization metrics for the different methods.

	Method	AUC F1-score Mean Dice score (std) Mean tile-level Specificity (std)
	CLAM	0.895	0.8	0.215(0.28)	0.864(0.1)
	CLAM w/ 10% annot. 0.924	0.835	0.35(0.263)	0.999(0.001)
	CLAM w/ 50% annot. 0.939	0.878	0.375(0.279)	0.999(0.001)
	CLAM w/ 80% annot. 0.949	0.873	0.405(0.282)	0.999(0.002)

Acknowledgments

The authors are grateful to the OPAL infrastructure from Université Côte d'Azur for providing resources and support. This work has been supported by the French government, through the 3IA Côte d'Azur Investments in the Future project managed by the National Research Agency (ANR) with the reference number ANR-19-P3IA-0002