Munyque Mittelmann
email: munyque.mittelmann@ut-capitole.fr

Bastien Maubert
email: bastien.maubert@gmail.com

Aniello Murano
email: nello.murano@gmail.com

Laurent Perrussel
email: laurent.perrussel@irit.fr

Synthesis of Mechanisms with Strategy Logic (Short Paper)

Keywords: Mechanism Design, Logics for Multi-Agent Systems, Strategic Reasoning

Mechanism Design aims to design a game so that a desirable outcome is reached regardless of agents' self-interests. In this paper, we show how this problem can be rephrased as a synthesis problem, where mechanisms are automatically synthesized from a partial or complete specification in a high-level logical language. We show that Quantitative Strategy Logic is a perfect candidate for specifying mechanisms as it can express complex strategic and quantitative properties.

Introduction

Mechanism Design is focused on the designing of games that aggregate agents' preferences towards a single joint decision. Such games should ensure a preferable behavior of (rational) players as well as desirable features of the decision [START_REF] Nisan | Algorithmic Game Theory[END_REF]. Conitzer and Sandholm [START_REF] Sandholm | Automated mechanism design: A new application area for search algorithms[END_REF] introduced Automated Mechanism Design (AMD), whose goal is to automatically create mechanisms for solving a specific preference aggregation problem. AMD is usually tackled from an optimization and/or data-driven point of view (for instance, see [START_REF] Shen | Automated mechanism design via neural networks[END_REF][START_REF] Dütting | Optimal auctions through deep learning[END_REF][START_REF] Narasimhan | Automated mechanism design without money via machine learning[END_REF]).

In this paper we argue that Strategy Logic [START_REF] Chatterjee | Strategy logic[END_REF][START_REF] Mogavero | Reasoning about strategies: On the model-checking problem[END_REF] is a good candidate for a general-purpose logic for mechanism design. More precisely, we present a recently proposed approach to AMD, which consists in automating the process of verifying and designing new mechanisms using formal methods and strategic reasoning. This approach was inspired by [START_REF] Wooldridge | Logic for automated mechanism design-a progress report[END_REF] [START_REF] Wooldridge | Logic for automated mechanism design-a progress report[END_REF], who advocated the use of Alternating-time Temporal Logic (ATL) [START_REF] Alur | Alternating-time temporal logic[END_REF] to reason about mechanisms. ATL lacks the ability to reason about quantitative aspects such as preferences, as well as game-theoretic concepts such as equilibria, which are key features for modeling and evaluating mechanisms, more precisely the ones with monetary transfers. For addressing these aspects, we consider Quantitative Strategy Logic (SL[ℱ]) [START_REF] Bouyer | Reasoning about quality and fuzziness of strategic behaviours[END_REF]. SL[ℱ] is expressive enough to express complex solution concepts such as Nash equilibrium and properties about quantities.

First, we demonstrated how to represent and verify knowledge-based benchmarks and properties (such as efficiency and strategyproofness) in the newly proposed Epistemic SL[ℱ] (SLK[ℱ]) [START_REF] Maubert | Strategic reasoning in automated mechanism design[END_REF]. Previous extensions for imperfect information [START_REF] Belardinelli | Verification of multi-agent systems with public actions against strategy logic[END_REF][START_REF] Berthon | Strategy logic with imperfect information[END_REF][START_REF] Cermák | Practical verification of multi-agent systems against SLK specifications[END_REF] focused on the qualitative versions of SL, and SLK[ℱ] is the first logic for strategic reasoning that combines quantitative aspects, imperfect information, and the ability to express complex concepts from game theory.

In a second stage, we considered SL[ℱ] with Natural Strategies [START_REF] Jamroga | Natural strategic ability[END_REF] for reasoning with bounded recall [START_REF] Belardinelli | Reasoning about human-friendly strategies in repeated keyword auctions[END_REF]. This work offers a new perspective for reasoning about mechanisms based on the complexity of agents' strategies, which we illustrated by modeling the repeated keyword auction.

Finally, we reduced the design of deterministic mechanisms to SL[ℱ]-synthesis [START_REF] Mittelmann | Automated synthesis of mechanisms[END_REF]. In this work, mechanisms are synthesized from a partial or complete specification expressed in a high-level logical language. The quantitative semantics of SL[ℱ] allows us to investigate the constructions of mechanisms that approximate such properties, which is not possible with standard Strategy Logic (SL) [START_REF] Chatterjee | Strategy logic[END_REF][START_REF] Mogavero | Reasoning about strategies: On the model-checking problem[END_REF]. Our approach enables generating optimal mechanisms from a SL[ℱ] specification, which may include requirements over the strategic behaviour of participants and quality of the outcome. In this communication paper, we focus on the results obtained in relation to synthesis of action-bounded mechanisms [START_REF] Mittelmann | Automated synthesis of mechanisms[END_REF].

Quantitative Strategy Logic

Let us first present SL[ℱ] [START_REF] Bouyer | Reasoning about quality and fuzziness of strategic behaviours[END_REF] The intuitive reading of the operators is as follows: ∃𝑠. 𝜙 means that there exists a strategy such that 𝜙 holds; (i, 𝑠)𝜙 means that when strategy 𝑠 is assigned to agent i, 𝜙 holds; X and U are the usual temporal operators "next" and "until". The meaning of 𝑓 (𝜙 1 , ..., 𝜙 𝑛 ) depends on the function 𝑓 . We use ⊤, ∨, and ¬ to denote, respectively, function 1, function 𝑥, 𝑦 ↦ → max(𝑥, 𝑦) and function 𝑥 ↦ → -𝑥.

Definition 2. A weighted concurrent game structure (wCGS) is a tuple 𝒢 = (ℬ, 𝑉, 𝑣 𝜄 , 𝛿, ℓ) where (i) ℬ is a finite set of actions; (ii) 𝑉 is a finite set of positions; (iii) 𝑣 𝜄 ⊆ 𝑉 is an initial position; (iv) 𝛿 : 𝑉 × ℬ N → 𝑉 is a transition function; (v) ℓ : 𝑉 × AP → [-1, 1] is a weight function.
In a position 𝑣 ∈ 𝑉 , each player i chooses an action 𝑎 i ∈ ℬ, and the game proceeds to position 𝛿(𝑣, 𝑎) where 𝑎 is the action profile (𝑎 i ) i∈N . We write 𝑜 for a tuple of objects (𝑜 i ) i∈N , one for each agent, and such tuples are called profiles. Given a profile 𝑜 and i ∈ N, we let 𝑜 i be agent i's component, and 𝑜 -i is (𝑜 r ) r̸ =i . Similarly, we let N -i = N ∖ {i}.

A play 𝜋 = 𝑣 1 𝑣 2 ... is an infinite sequence of positions such that for every 𝑖 ≥ 1 there exists an action profile 𝑎 such that 𝛿(𝑣 𝑖 , 𝑎) = 𝑣 𝑖+1 . We write 𝜋 𝑖 = 𝑣 𝑖 for the position at index 𝑖 in play 𝜋. A history ℎ is a finite prefix of a play. A strategy is a function 𝜎 : Hist → ℬ that maps each history to an action. We let Str be the set of strategies. An assignment 𝒜 : N ∪ Var → Str is a function from players and variables to strategies. For an assignment 𝒜, an agent i and a strategy 𝜎 for i, 𝒜[𝑎 ↦ → 𝜎] is the assignment that maps 𝑎 to 𝜎 and is otherwise equal to 𝒜, and 𝒜[𝑠 ↦ → 𝜎] is defined similarly, where 𝑠 is a variable. For an assignment 𝒜 and a history ℎ, we let Out(𝒜, ℎ) be the unique play that continues ℎ following the strategies assigned by 𝒜. Definition 3. (Partial, see complete definition in [START_REF] Bouyer | Reasoning about quality and fuzziness of strategic behaviours[END_REF]) Let 𝒢 = (ℬ, 𝑉, 𝛿, ℓ, 𝑉 𝜄 ) be a wCGS, and 𝒜 an assignment. The satisfaction value 𝜙 𝒢 𝒜 (ℎ) ∈ [-1, 1] of an SL[ℱ] formula 𝜙 in a history ℎ is defined as follows, where 𝜋 denotes Out(𝒜, ℎ):

𝑝 𝒢 𝒜 (ℎ) = ℓ(last(ℎ), 𝑝) ∃𝑠. 𝜙 𝒢 𝒜 (ℎ) = max 𝜎∈Str 𝜙 𝒢 𝒜[𝑠↦ →𝜎] (ℎ) (i, 𝑠)𝜙 𝒢 𝒜 (ℎ) = 𝜙 𝒢 𝒜[i↦ →𝒜(𝑠)] (ℎ)
We write 𝜙 𝒢 (ℎ) when the satisfaction value of 𝜙 does not depend on the assignment. We also let 𝜙 𝒢 = 𝜙 𝒢 (𝑣 𝜄 ). We can define the classic abbreviations:

⊥= def ¬⊤, 𝜙 ∧ 𝜙 ′ = def ¬(¬𝜙 ∨ ¬𝜙 ′ ), 𝜙 → 𝜙 ′ = def ¬𝜙 ∨ 𝜙 ′ , F𝜓 = def ⊤U𝜓, G𝜓 = def ¬F¬𝜓
and ∀𝑠. 𝜙 = def ¬∃𝑠. ¬𝜙. We also use A𝜙 as a shorthand for a universal quantification on strategies and bindings for all agents.

Satisfiability and Synthesis of SL[ℱ]

The satisfiability of SL is undecidable in general [START_REF] Mogavero | Reasoning about strategies: on the satisfiability problem[END_REF], but it is decidable when restricted to systems with a bounded number of actions [START_REF] Laroussinie | Augmenting ATL with strategy contexts[END_REF], which we show to be also the case for SL[ℱ]. We restrict our attention to models in which atomic propositions take values in a given finite set of possible values. Given a finite set 𝒱 ⊂ [-1, 1] s.t. {-1, 1} ⊆ 𝒱, the 𝒱-satisfiability problem for SL[ℱ] is the restriction of the satisfiability problem to 𝒱-weighted wCGS. We have that: Theorem 1. Let 𝒱 be a finite set of values and ℬ a finite set of actions. Then 𝒱-satisfiability of SL[ℱ] over the wCGS 𝒢 = (ℬ, 𝑉, 𝑣 𝜄 , 𝛿, ℓ) is decidable.

The algorithm for SL[ℱ] satisfiability to synthesize mechanisms that optimally satisfy the specification, in the sense that they achieve the best possible satisfaction value for the specification. First, we note that the algorithm for the satisfiability problem of SL[ℱ] can actually return a satisfying wCGS when one exists. Second, it is proved in [START_REF] Bouyer | Reasoning about quality and fuzziness of strategic behaviours[END_REF] that given a finite set 𝒱 of possible values for atomic propositions and a formula 𝜙 ∈ SL[ℱ] there is only a finite number of possible satisfaction values 𝜙 can take in any wCGS, and we can compute an over-approximation ̃ Val 𝜙,𝒱 of this set.

Algorithm 1 synthesizes a wCGS that maximizes the satisfaction value of the given SL[ℱ] specification, in all cases where the satisfiability problem for SL[ℱ] can be solved and a witness produced. We now show how this can be used to solve automated mechanism design.

Algorithm 1 𝑠𝑦𝑛𝑡ℎ𝑒𝑠𝑖𝑠(Φ, 𝒱)

Input: a SL[ℱ]-formula Φ and a set of possible values for atomic propositions 𝒱.

Output: a wCGS 𝒢 such that Φ 𝒢 is maximal Solve 𝒱-satisfiability for Φ and 𝜀 = 𝜈 𝑖

5:

if there exists 𝒢 such that Φ 𝒢 ≥ 𝜈 𝑖 then return 𝒢

Synthesis for Mechanism Design

We first recall basic concepts used to formalize mechanisms, which determine how to choose one option among several alternatives, based on agents' strategies. We assume that each alternative is a tuple (𝑥, p) where 𝑥 ∈ 𝒳 is a choice from a finite set of choices 𝒳 ⊂ [-1, 1], p = (p i ) i∈N , and p i ∈ [-1, 1] is the payment for agent i. For each agent i ∈ N, let also Θ i ⊂ [-1, 1] be a finite set of possible types for i. We let Θ = ∏ i∈N Θ i , and we note 𝜃 = (𝜃 i ) i∈N ∈ Θ for a type profile, which assigns a type 𝜃 i to each agent i. The type 𝜃 i of an agent i determines how she values each choice 𝑥 ∈ 𝒳 ; this is represented by a valuation function

v i : 𝒳 × Θ i → [-1, 1].
A mechanism consists of a description of the agents' possible strategies, and a description of the alternatives that result from them. As shown in [START_REF] Maubert | Strategic reasoning in automated mechanism design[END_REF], we can represent mechanisms as wCGS and verify their equilibrium outcome.

SL[ℱ] can express a variety of important notions in mechanism design, such as strategyproofness, individual rationality, and efficiency [START_REF] Maubert | Strategic reasoning in automated mechanism design[END_REF]. We recall the formulas for some of these notions. Let 𝜃 = (𝜃 i ) i∈N be a type profile in Θ.

First the agent's utility is denoted by the SL[ℱ] formula util i (𝜃 i ) = def v i (choice, 𝜃 i ) -pay i . Efficiency can be expressed as follows: EF(𝜃) = def ∑ i∈N v i (choice, 𝜃 i ) = maxv 𝜃 , where maxv 𝜃 = max 𝑥∈𝒳 ∑ i∈N v i (𝑥, 𝜃 i ) is a constant in ℱ. We also recall the SL[ℱ]-formula that characterizes Nash equilibria:

NE(𝑠, 𝜃) = def ⋀ i∈N ∀𝑡. [ (N -i , 𝑠 -i )(i, 𝑡)F(term ∧ util i (𝜃 i )) ≤ (N, 𝑠)F(term ∧ util i (𝜃 i )) ]
where 𝑠 = (𝑠 i ) i∈N is a profile of strategy variables. We now illustrate the mechanism synthesis problem by considering rules based on the Japanese auction. We let wins i ∈ (-1, 1] be a constant value denoting the choice in which the agent i is the winner, with wins i ̸ = wins r for any r ̸ = i. We consider the choice set 𝒳 = {wins i : i ∈ N} ∪ {-1}, where -1 specifies the case where there is no winner at the end of the game.

Example 1. In the Japanese auction, the price is repeatedly raised by the auctioneer until only one bidder remains. The remaining bidder wins the item at the final price [START_REF] Klemperer | Auction theory: A guide to the literature[END_REF]. Let us fix a price increment inc > 0. There are only two possible actions, accept (acc) or decline (dec), so that the set ℬ = {acc, dec} is indeed bounded. Furthermore, we let Φ = {price, sold, initial, choice, bid i , pay i , term : i ∈ N}, where price denotes the current price, initial denotes whether the position is the initial one, sold specifies whether the item was sold, bid i specifies whether i is an active bidder, choice and pay i denote respec. the choice elected by the mechanism, and the payment of agent i. The proposition term specifies whether a position is terminal. The following SL[ℱ]-formulae are a partial description of a mechanism, inspired by the Japanese auction. The meaning of Rules J1-J8 is intuitive. Rule J9 specifies that for all type profiles there should exist a NE whose outcome is IR and EF.

J1. AG((initial

→ price = 0 ∧ ¬sold ∧ ¬term) ∧ (XG¬initial ∧ F term)) J2. AG(sold ↔ choice ̸ = -1) J3. AG((¬sold ∧ price + inc ≤ 1) → (price + inc = Xprice ∧ ¬Xterm)) J4. AG((sold ∨ price + inc > 1) → (price = Xprice ∧ Xterm)) J5. AG(choice = wins i ↔ bid i ∧ ⋀ r̸ =i ¬bid i ) J6. AG(choice = -1 ↔ ¬( ⋁ i∈N (bid i ∧ ⋀ r̸ =i ¬bid i ))) J7. AG ( ⋀ i∈N (choice = wins i → pay i = price) ) J8. AG ( ⋀ i∈N (choice ̸ = wins i → pay i = 0) ) J9. ⋀ 𝜃∈Θ (∃𝑠. NE(𝑠, 𝜃) ∧ F(term ∧ IR(𝜃) ∧ EF(𝜃)))
We denote by Σ jpn the conjunction of Rules J1-J9. Algorithm 1 constructs a wCGS that maximizes the satisfaction value of Σ jpn . We show that this value is 1, meaning that there exists a mechanism that is individually rational and efficient for some Nash equilibrium, for all type profiles [START_REF] Mittelmann | Automated synthesis of mechanisms[END_REF].

Conclusion

We present a novel approach for AMD based on Strategy Logic and formal methods, which builds an important bridge between logics for strategic reasoning in MAS and economic theory (in particular, computational social choice and mechanisms design). In the results presented here, in which mechanisms can be automatically generated from partial or complete specifications in a rich logical language. The great expressiveness of the specification language SL[ℱ] makes our approach of automated synthesis very general, unlike previous proposals. Another advantage is the use of formal methods, which are developed to guarantee their correctness by construction. While mechanism synthesis from SL[ℱ] specifications is undecidable, we solve it when the number of actions is bounded.

Definition 1 .

 1 syntax and semantics. The syntax of SL[ℱ] is defined by the grammar 𝜙 ::= 𝑝 | ∃𝑠. 𝜙 | (i, 𝑠)𝜙 | 𝑓 (𝜙, ..., 𝜙) | X𝜙 | 𝜙U𝜙 where 𝑝 ∈ AP is an atomic proposition, 𝑠 ∈ Var is a strategy variable, i ∈ N is an agent, and 𝑓 ∈ ℱ is a function over [-1, 1].

Acknowledgments

This work is part of a paper accepted at IJCAI-ECAI 22. This research is supported by the ANR project AGAPE ANR-18-CE23-0013, the PRIN project RIPER (No. 20203FFYLK), and the EU ICT-48 2020 project TAILOR (No. 952215).


Sébastien Picault
email: sebastien.picault@inrae.fr

Pauline Ezanno

Servane Bareille

Matthieu Mancini

Timothée Vergne

T Vergne Summary

Lessons learnt from the first modelling challenge in animal health: Improving preparedness to control African swine fever at the interface between livestock and wildlife

niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Raising livestock in a sustainable and welfare perspective requires to manage animal health, especially infectious diseases which spread at large scale between animal populations [START_REF] Ezanno | How mechanistic modelling supports decision making for the control of enzootic infectious diseases[END_REF]. Health crises highlight the need for robust epidemiological knowledge and predictive tools to better cope with uncertainty, especially at the livestock-wildlife interface [START_REF] Gortázar | Diseases shared between wildlife and livestock: a European perspective[END_REF]. Developing models that forecast disease spread is pivotal to better understand epidemics and to assess ex ante the efficacy of control measures [START_REF] Grassly | Mathematical models of infectious disease transmission[END_REF], but doing so during an epidemic is extremely difficult. Modelling challenges, which are relatively short competitions, enhance cooperation between actors and modellers' ability to timely advise policy makers, improve the accuracy of model predictions and modellers' readiness when facing emerging threats, and promote international collaborations. After the first modelling challenge on seasonal influenza [START_REF] Friedberg | Ten Simple Rules for a Community Computational Challenge[END_REF], annually renewed [START_REF] Reich | A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States[END_REF][START_REF] Viboud | The future of influenza forecasts[END_REF], others were organized on Ebola [START_REF] Viboud | The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt[END_REF], Chikungunya [START_REF] Valle | Summary results of the 2014-2015 DARPA Chikungunya challenge[END_REF] and Dengue [START_REF] Johansson | An[END_REF]. However, none concerned an animal disease so far, while animal epidemiology has specific features which may induce different conclusions on the most suitable approaches and also require specific preparedness.

African swine fever (ASF) is an emerging disease currently spreading at the interface between wild boar and pig farms in Europe and Asia [START_REF] Sánchez-Cordón | African Swine Fever: Disease Dynamics in Wild Boar Experimentally Infected with ASFV Isolates Belonging to Genotype I and II[END_REF]. This viral disease is associated to a tremendous impact on swine production, livestock economy and international trade and neither a vaccine nor a treatment is available [START_REF] Dixon | African Swine Fever Epidemiology and Control[END_REF]. It is one of the most major livestock infectious disease threats for most countries as the virus can spread internationally via geographical proximity or due to movements of persons, swine and swine products [START_REF] Vergne | Pig empire under infectious threat: risk of African swine fever introduction into the People's Republic of China[END_REF]. To enhance the global preparedness to better face ASF epidemics, there is a need to consider explicitly the interface between livestock and wildlife, and to be able to assess various and combined control measures.

The objective of this paper is to present ASF Challenge, the first modelling challenge in animal health, the comparison of approaches mobilised by the five international teams involved, and to discuss lessons learnt throughout this process.

MATERIALS AND METHODS

Challenge organization

During the preparation step (July 2019-August 2020), a source model (called "M0") was built to generate the synthetic data mimicking a ASF-like outbreak in a realistic west-European context. The challenge itself took place between August 27, 2020 and January 13, 2021. Three situation reports and synthetic epidemiological data corresponding to days 50, 80 and 110 after the detection of a first case, were released successively to the participants. These data were produced by the original model described below and represented detection events on pig farms or wild boar, with the location and cause of detection. Finally, the predictions of the participants' models were compared and analysed.

Model M0 and simulated epidemics

The simulated outbreak was located on a hypothetical island built by aggregating the two French regions Auvergne-Rhône-Alpes and Occitanie, using three types of land use based on public GIS data † (agricultural, forest and urban) to define the location of individual wild boar and domestic pig farms. Assuming that a the wild boar population was reduced by half during a hunting season, we used hunting bags per department provided by the Office Français de la Biodiversité (OFB) to determine the initial wild boar population (500,366) and distributed the centres of their home range randomly (80% in forest areas, 18% in agricultural areas, 2% in urban areas). The coordinates of the 4,775 pig farms registered in the two French regions were also randomly distributed as follows: 33% in Auvergne-Rhône-Alpes and 67% in Occitanie, and within each region 85% in agricultural areas, 10% in forests, 5% in urban areas. Besides, we endowed each farm with variable characteristics (size; commercial or backyard status; farrow, finisher, or farrow-to-finish; access to an outdoor area) which were used to generate a biosecurity score and simulate commercial movements between farms.

The synthetic epidemiological data were simulated using a stochastic, spatially-explicit agent-based model, with three kinds of agents: pig herds (compartmental sub-model), individual wild boar, and the whole island (as a metapopulation). A recent modelling software, EMULSION [START_REF] Picault | EMULSION: Transparent and flexible multiscale stochastic models in human, animal and plant epidemiology[END_REF], was used for making model components explicit and more revisable.

In pig farms, we neglected natural mortality, thus driving the population only by precalculated commercial movements, sold animals being replaced with new ones. Wild boar were subject to hunting and natural mortality only. As the epidemic was taking place during the hunting season (8 months), we indeed assumed no birth during the simulated period [START_REF] Vetter | How climate change and wildlife management affect population structure in wild boars[END_REF].

Pigs and wild boar were categorised into mutually exclusive health states: susceptible (S), exposed i.e. asymptomatic but starting being infectious (E), fully infectious and symptomatic (I). All infected animals were assumed to die, resulting in an infectious carcass (C). Wild boar dying from natural causes produced either an infectious (C) or a healthy (D) carcass when E/I or S at death, respectively. In pig farms, carcasses were removed the next day, whereas wild boar carcasses could stay in the environment up to several months until fully decayed or removed by humans. The force of infection in pig farms was assumed density-dependent, with a higher transmission rate in backyard farms than in commercial farms.

We modelled several transmission pathways between epidemiological units. For pig farms, we considered: the movement of an infected pig from an infected farm, the contact with an infectious wild boar, and indirect contacts with infectious farms in the neighbourhood. For wild boar, we assumed contacts with infectious wild boar, with infectious carcasses, or with an infectious pig farm. Apart from pre-computed trade movements, all other transmission pathways were spatially explicit (based on transmission kernels) and, when farms were involved, depended on their biosecurity level and outdoor access.

Detection of ASF cases initially relied on passive surveillance: wild boar carcasses could be found and tested each day with a low probability, whereas each pig could be detected and tested each day and at death, with a probability that depended on the farm type (high in commercial farms, low in backyard farms). The detection of the primary outbreak resulted in increased detection probabilities. Current European regulatory measures were triggered immediately after the first detection, and applied to all confirmed pig farms: 1) the slaughter of all animals, 2) the installation of protection and surveillance zones subject to trade ban and increased vigilance, 3) the tracing of farms with recent trade contacts (same effect). Culled farms were repopulated after several weeks. Any infected wild boar carcass found was removed without delay and triggered an active search in the immediate neighbourhood, with a higher probability to find new carcasses. Also, a proportion of hunted wild boar were tested.

Several additional control measures were implemented successively in the simulation. First, assuming the forest near the primary case was a major threat, 300 km of fences were installed and became operational 60 days after the first detection. An increased hunting pressure started in the fenced area and in a buffer area around the fences, with systematic tests on hunted wild boar, the suspension of active search, and an increased probability of finding carcasses by passive surveillance. Then, 90 days after the first case, the detection of dead or alive infected wild boar led to the preventive culling (and testing) of all pigs from nearby farms.

Selection of synthetic data for the challenge An exposed wild boar was introduced near a forest at the center of the island, a few weeks before the start of the hunting season. We ran 500 stochastic repetitions of the model to identify trajectories that were realistic enough and well suited for the challenge. After discarding those without any detection or detections later than 200 days after ASF introduction, we chose at random one of the trajectories that met five selection criteria: more than 250 infected wild boar before primary case detection to ensure disease installation in wildlife; primary case found in pig farm; less than 500 wild boar infected outside the fences at installation; more than 250 infected wild boar 110 days after primary case; and less than 30 infected wild boar 230 days after primary case (Fig. 1).

Figure 1. Temporal dynamics of the number of live infected wild boars (exposed + infectious) for the selected trajectory (black) and the stochastic repetitions where detection occurred before 200 days (gray), with the three prediction phases that followed the initial situation report. Vertical dashed lines: changes in control interventions.

Participants and their methods

Five modeller teams participated in the whole challenge (see Acknowledgements). In the narrative of the synthetic epidemics, phase 1 started 50 days after the dectection of a first case in a pig farm near a forest. Participants were provided with a first situation reports and asked 1) to predict the number and location of wild boar and pig farm cases expected in the following 30 days, 2) to assess the effectiveness of surrounding the infected zone with fences, and 3) to advise on increasing hunting pressure in the fenced zone. At the end of phase 2 (110 days after first case), they were asked 1) to update their predictions on fences, now including a buffer zone and an increased hunting pressure, and 2) to advise on the effectiveness of five alternative control measures: culling all pigs from farms a) located within 3 km of a positive wild boar carcass, b) located in the protection zone, c) with a trade contact with an infected farm in the three preceding weeks; d) increasing the size of active search area around wild boar carcasses (from 1 km to 2 km); e) increasing the surveillance zone (from 10 to 15 km). At end of phase 3, teams were asked to update their predictions and estimate the fade-out probability for the next four months. Six weeks were left to the participants for answering each phase.

The participants were free to choose their own approach, hence developed either one single model or two separate models for wild boar/pig farm interactions, with a diversity of modelling paradigms and granularity regarding both the epidemiological and spatial units. Stochastic compartmental models were used almost for all epidemiological units (except "CIRAD" team which built a probabilistic model for pig farms). Wild boar were mostly modelled at individual scale (except "WUR" team which used a spatial area) and pigs at farm scale (except for "UK" team which used individual scale). Predictions were made at several spatial scales (discretized in squares, rectangles or hexagons) ranging from 1 to 195 km 2 . We compared their predictions regarding the temporal dynamics of ASF spread in pig farms and wild boar with the possible outcomes of model M0 in the same conditions, i.e. keeping the challenge trajectory up to the beginning of the prediction period, then simulating M0 from that point with the appropriate settings and new random seeds. For spatial predictions, we compared 1) the predicted probability for each pig farm to be infected with the locations of positive farms in model M0 with the same conditions, 2) the probability that each spatial unit contained an infected and detected wild boar with the locations of wild boar cases in M0.

RESULTS

Temporal model predictions

The temporal forecasts for pig farm cases were very good in most teams (Fig. 2A), whereas wild boar dynamics appeared much more difficult to capture (Fig. 2B). The installation of fences and increased hunting pressure was highlighted by most teams as difficult to integrate in their models.

Spatial model predictions

Spatial predictions for pig farms (Fig. 3) were quite good (including one team, CIRAD, which successfully predicted the occurrence of a distant case due to trade contacts). Besides, the regulatory measures based on protection and surveillance zones do not require to predict the exact location of infected farms, since an increased vigilance may be sufficient to ensure reactivity on detection and culling. Spatial predictions regarding wild boar cases were much more heterogeneous, both in their granularity (e.g. from 1 km 2 to 195 km 2 tiles) and in the spread patterns (Fig. 4), reflecting the diversity of assumptions made by each team on wildlife and making the comparisons quite difficult.

DISCUSSION

Modelling challenges organized in human health over the last decade demonstrated their considerable value for the development and assessment of modelling and forecasting methods [START_REF] Ajelli | The RAPIDD Ebola forecasting challenge: Model description and synthetic data generation[END_REF]. The ASF Challenge, that ran between August 2020 and January 2021, was the first modelling challenge in animal health. Using a new mechanistic and stochastic metapopulation and multi-host model of ASF spread, we generated synthetic data mimicking an ASF-like epidemic detected at the interface between pig farms and wild boar in a typical European context. Land use, size and location of farms, as well as wild boar hunting bags per administrative units were derived from real data in the southern quarter of France. ASF incidence data (detected cases) were provided to the modelling teams while the epidemic developed. The objectives for the teams involved in the challenge were to reproduce the synthetic epidemic assuming a set of control strategies, predict its expansion and prioritize a finite number of alternative interventions. We compared 5 independent modelling approaches and their qualitative and quantitative spatio-temporal predictions over the three one-month periods of the challenge.

To make this challenge interesting and useful, the model that generated the synthetic epidemiological data needed to be more detailed than the different models that could be developed by participants to make their predictions. Hence, data generation were computationally intensive and calibrating the model to generate interesting and realistic "ASFlike" epidemic trajectories was extremely time-consuming, especially because of the lack of data on wild boar population dynamics and mobility patterns and their expected impact on fences' efficacy.

The context of ASF provided an opportunity to address the specificities of infectious livestock diseases at the interface between wildlife and domestic farms. Still poorly observed (Vicente et al., 2021), this interface is key to increasing our effectiveness in controlling emerging animal diseases. All participants acknowledged the interest of explicitly modelling interactions at the interface between domestic and wild fauna to accurately predict the course and extent of the epidemics and account for the impact of control measures. The temporal and spatial predictions on domestic pigs were more accurate than for wild boar, which highlights the diversity on assumptions made on wild boar population dynamics and contact patterns due to the lack of knowledge on wildlife. Also, intensive hunting, a key control measure against ASF, was one of the most problematic feature to introduce in models (for participants and organisers), and their potential impact on wild boar ecology, possibly including increased contacts [START_REF] Lange | Alternative control strategies against ASF in wild boar populations[END_REF], was not modelled.

No specific modelling approach was better than all others on every prediction, and the added-value of their complementarity for policy makers will be addressed in further studies through ensemble models both for the temporal and spatial dynamics. This diversity, which was intentional in the challenge, also led to heterogeneous output formats, which made comparisons difficult and suggested stricter specifications for further challenges.

The choice of producing fictitious data as in the Ebola challenge [START_REF] Viboud | The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt[END_REF], rather than using historical records, required much work but provided the organisers with a total control and knowledge on the situation, on the noise level in the synthetic data (e.g. a proportion of small farms were not known from the beginning and discovered by participants as they became infected), and on the "representativity" of the selected trajectory compared to possible model outcomes. Such open international challenges are a privileged framework to anticipate emerging infectious diseases, including zoonotic threats at the interface between wildlife, livestock and human activity, and to improve the readiness of modelling teams to face future epidemics.

Figure 2 .

 2 Figure 2. Median of the predicted numbers of detected pig farms (A) and detected wild boar (B) by each team during the second period of the challenge (days 80 to 110). Acceptable range of output variations is shown (10 th to 90 th percentiles obtained when running model M0 during the prediction period).

Figure 3 .

 3 Figure 3. Detected pig farms between days 50 and 80 as predicted by each team (black circles: farms that would have been detected in model M0 with the selected trajectory in the absence of additional control measures). A: CIRAD; B: UK; C: Massey Univ.; D: WUR.

Figure 4 .

 4 Figure 4. Predicted probability to detect infected wild boars between days 80 and 110, without additional control measures after day 80, as calculated by two teams: INRAE (A, 195 km² tiles), Massey Univ. (B, 1 km² tiles), and CIRAD (C, 86.8 km 2 tiles) compared to wild boar cases found in model M0 (D, 25 km 2 tiles).

† https://www.diva-gis.org/

ACKNOWLEDGEMENTS

This work was supported by the animal health division of INRAE [PPApred grant]. We are grateful to C. Belloc & C. Peroz (Oniris), E. Gilot-Fromont (VetAgroSup), E. Baubet & E. Marboutin (OFB) for their expertise on ASF, pig herd management, and wild boar population dynamics, which greatly helped us to define the model and associated scenarios. We also warmly thank all participants to the ASF Challenge for their enthusiastic involvement: F. Jori, F. Munoz, D. Pleydell ("Cirad team"), E. Dankwa, C. Donnelly, S. Hayes, S. Lambert, R. N. Thompson ("UK team"), G. Beaunée, E. Vergu, F. Deslandes ("INRAE team"), M. Vignes ("Massey team"), G. J. Boender, T. J. Hagenaars ("WUR team"). We are most grateful to the Bioinformatics Core Facility of Nantes BiRD, member of Biogenouest, Institut Français de Bioinformatique (IFB) , and to the INRAE MIGALE bioinformatics facility (MIGALE, INRAE, 2020. Migale bioinformatics Facility, doi: 10.15454/1.5572390655343293E12), for the use of their computing resources.


INTRODUCTION

Handwriting recognition is a challenging, already wellstudied topic. However, most research focus on adult handwriting recognition. Few are interested on children handwriting and to provide a character segmentation associate with the recognition. Moreover, children handwriting is a more difficult context because children are in an early stage of learning. Their handwriting is deformed and contain spelling mistakes.

The goal of this work is to design an efficient model to do recognition and segmentation of children handwriting for an education purpose.

METHOD

The first step is to select a model which can do recognition and provide an accurate segmentation. We chose an object based detection architecture : Mask R CNN. The main steps of this model are :

Extract features from input image with a

Convolutional Neural Network (CNN).

Compute coarse regions to analyze with a Region

Proposal Network (RPN). Because the network do not know the size of object to detect, it uses a lot of regions with different scales, ratios and positions. For each region, RPN predict an objectness score and bounding box position.

Extract features for each region

DATASET

The dataset is composed of children words annotated on letter level. The handwriting is encoded with online format. There are converted to image resize at 128px height and pad at 1280px width.

Data augmentation is performed on train part on 375 words to obtain 12 000 words with:

• Offline transformations :

• Rotation, inclination, stretching. • Online transformation :

• Curvature, stroke stretching. Split

PRELIMINARY RESULTS

Evaluation metrics :

• Character Error Rate (CER) : evaluate the recognition aspect • Intersection Over Union (IoU) : evaluate the segmentation aspect

The use of segmentation lattice improve the CER by 1,4% and decreases slightly the IoU by 0,5%. The preliminary results are encouraging, but the recognition performance is not acceptable for a real application use. More experiments on how to use the lattice are in progress.

CONCLUSION AND PERSPECTIVES

The contribution of this work is to use a segmentation lattice with a Mask R CNN. The first results show the potential of this approach, although the recognition still not efficient enough for a real application.

Another idea is to use a hybridization of a model that is great in recognition and approximate in segmentation (Seq2Seq) and of a model that is approximate in recognition and efficient in segmentation (Mask R CNN).

Recognition and segmentation of children handwriting

  and predict the label, bounding boxes and segmentation mask. Here, the bounding boxes prediction makes it possible to refine the delimitation proposed by the RPN.4. Non-maximum Suppression (NMS) is applied toselect the best predictions. The next step is to improve the model with expert knowledge. The handwriting is encoded with an online signal converted to an image as input of Mask R CNN. Using knowledge relative to handwriting, the online signal can be segmented into different hypotheses of letter regroup in a segmentation lattice. The goal is to use the lattice to focus the model on precise regions of the image in RPN.

corbille@irisa.fr Use segmentation lattice to focus Mask R CNN:

	Simon Corbillé, Élisa Fromont, Éric Anquetil,
	Univ Rennes, IRISA lab 35000 Rennes France
	Contact : simon.Train	Validation Test
	12000	128	1032
	Methods	CER (%)	IoU (%)
	Baseline	14,4	78,1
	With lattice	13,0	77,6


Marie-Claude F Jaurand
email: jaurand@cephb.fr

Annie Renier

Julien Daubriac

Mesothelioma: Do asbestos and carbon nanotubes pose the same health risk?

Carbon nanotubes (CNTs), the product of new technology, may be used in a wide range of applications. Because they present similarities to asbestos fibres in terms of their shape and size, it is legitimate to raise the question of their safety for human health. Recent animal and cellular studies suggest that CNTs elicit tissue and cell responses similar to those observed with asbestos fibres, which increases concern about the adverse biological effects of CNTs. While asbestos fibres' mechanisms of action are not fully understood, sufficient results are available to develop hypotheses about the significant factors underlying their damaging effects. This review will summarize the current state of knowledge about the biological effects of CNTs and will discuss to what extent they present similarities to those of asbestos fibres. Finally, the characteristics of asbestos known to be associated with toxicity will be analyzed to address the possible impact of CNTs.

Introduction

Carbon nanotubes (CNTs) have unique chemical and physical characteristics as a result of their nanostructure. CNTs may be used in a wide range of applications, in fields as diverse as electronics and medicine [START_REF] Shvedova | Mechanisms of pulmonary toxicity and medical applications of carbon nanotubes: Two faces of janus?[END_REF][START_REF] Helland | Reviewing the environmental and human health knowledge base of carbon nanotubes[END_REF]. Due to their widespread use, it is important to determine the safety of CNTs for the protection of ecological systems and human health. Research to investigate the biological effects of CNTs is advancing today in order to foresee and prevent their potentially harmful effects. CNTs have fibre-like characteristics in terms of their elongated shape, dimensions and aspect ratio. As particles with at least one dimension of less than 100 nm, they correspond to High Aspect Ratio Nanoparticles (HARN) [START_REF] Tran | An outline scoping study to determine whether high aspect ratio nanoparticles (harn) should raise the same concerns as do asbestos fibres[END_REF]. In light of the health impact of mineral fibres, especially the fibrogenic and carcinogenic potency of asbestos fibres, and the health and socio-economical tragedies caused by unregulated asbestos utilization, the increasing development and uses of CNTs have triggered concern about their potential toxicity [START_REF] Stern | Nanotechnology safety concerns revisited[END_REF][START_REF] Kolosnjaj | Toxicity studies of carbon nanotubes[END_REF][START_REF] Boczkowski | Potential uses of carbon nanotubes in the medical field: How worried should patients be?[END_REF][START_REF] Donaldson | Carbon nanotubes: A review of their properties in relation to pulmonary toxicology and workplace safety[END_REF][START_REF] Bergamaschi | Nanomaterials and lung toxicity: Interactions with airways cells and relevance for occupational health risk assessment[END_REF]. In recent years, several publications have reported the effects of CNTs. Most studies have concerned animal and cell responses, focusing primarily on respiratory diseases, especially the inflammatory effects in the lung. However, while inhalation is one important probable route of contamination, it must be kept in mind that there are other relevant routes of exposure. A severe primary cancer, malignant mesothelioma (MM), has been closely linked to asbestos exposure [START_REF] Bianchi | Malignant mesothelioma: Global incidence and relationship with asbestos[END_REF][START_REF] Wagner | Diffuse pleural mesothelioma and asbestos exposure in the north western cape province[END_REF]. Epidemiological and animal studies have shown that asbestos fibres are not the only fibres to be associated with a risk of MM development. Epidemiological studies have demonstrated a higher incidence of MM in populations exposed to asbestiform and non-asbestos fibres [START_REF] Whitehouse | Environmental exposure to libby asbestos and mesotheliomas[END_REF][START_REF] Dikensoy | Mesothelioma due to environmental exposure to erionite in turkey[END_REF][START_REF] Comba | Pleural mesothelioma cases in biancavilla are related to a new fluoro-edenite fibrous amphibole[END_REF][START_REF] Baris | Epidemiological and environmental evidence of the health effects of exposure to erionite fibres: A four-year study in the cappadocian region of turkey[END_REF]. Some manmade vitreous fibres have caused MM in animal experiments [START_REF]IARC: Man-made mineral fibres[END_REF]. The question of whether CNTs might potentially be linked to MM development justifies further research in this area. Moreover, on the basis of the literature, CNTs have already shown effects in animals and in cell systems that are similar to those observed with asbestos fibres [START_REF] Shvedova | Mechanisms of pulmonary toxicity and medical applications of carbon nanotubes: Two faces of janus?[END_REF][START_REF] Helland | Reviewing the environmental and human health knowledge base of carbon nanotubes[END_REF][START_REF] Kolosnjaj | Toxicity studies of carbon nanotubes[END_REF][START_REF] Donaldson | Carbon nanotubes: A review of their properties in relation to pulmonary toxicology and workplace safety[END_REF]. Two recent studies showed the occurrence of MM in genetically-modified cancer-sensitized mice and in conventional Fischer 344 rats exposed to CNTs by intraperitoneal or intrascrotal administration respectively [START_REF] Sakamoto | Induction of mesothelioma by a single intrascrotal administration of multi-wall carbon nanotube in intact male fischer 344 rats[END_REF][START_REF] Takagi | Induction of mesothelioma in p53+/-mouse by intraperitoneal application of multi-wall carbon nanotube[END_REF]. These initial results underline the urgent need for information to further our knowledge about CNTs' potential to cause MM. MM is a primary tumour of the serosas caused by the neoplastic transformation of mesothelial cells. In populations exposed to asbestos fibres, MM mainly occurs in the pleura, and to a lesser extent in the peritoneum and pericardium. MM is considered to be highly specific to asbestos exposure, and is found in from 60% to over 80% of cases [START_REF] Albin | Asbestos and cancer: An overview of current trends in europe[END_REF][START_REF] Kishimoto | Cancer due to asbestos exposure[END_REF][START_REF] Kishimoto | Malignant pleural mesothelioma in parts of japan in relationship to asbestos exposure[END_REF][START_REF] Mowe | Occupational exposure and regional variation of malignant mesothelioma in norway, 1970-79[END_REF][START_REF] Park | Asbestosrelated occupational lung diseases in nsw, australia and potential exposure of the general population[END_REF][START_REF] Yeung | An occupation-industry matrix analysis of mesothelioma cases in australia 1980-1985[END_REF]. In France, the calculated risk of MM attributable to occupational asbestos exposure was estimated at 83.2% (95% CI 76.8 to 89.6) in men, and 38.4% (95% CI 26.8 to 50.0) in women [START_REF] Goldberg | The french national mesothelioma surveillance program[END_REF]. Many studies carried out to investigate pleural and mesothelial cell response to asbestos fibres have made it possible to reach sound hypotheses about the mechanism of action of asbestos fibres in neoplastic mesothelial cell transformation. The aim of the present review is to explore whether our knowledge of the mechanism of action of asbestos fibres could offer a useful paradigm to provide a warning or predict the risk of CNTs, to interpret data on animal and cellular responses, and to evaluate their potential health effects. For the purposes of our discussion, we consider three points: (i) the fate of asbestos fibres following exposure; (ii) their effects on mesothelial cells and the biological mechanism associated with the cell response; (iii) the nature of the fibre parameters involved in the harmful effects, and their similarities with CNT characteristics. We begin with a summary of current knowledge on the toxicology of CNTs, then look at asbestos fibres' mechanisms of action, focusing on carcinogenic effects at the pleural level. Finally, we address the similarities between asbestos and CNTs.

Toxicology of CNTs

Context of toxicological studies on CNT

Various kinds of CNTS have been the focus of toxicological studies. CNTs are heterogeneous in terms of their structure, impurities and physico-chemical properties. Both single-walled (SWCNTs) and multi-walled (MWCNTs) CNTs have been examined in toxicological studies, including commercial and laboratory-made CNTs, whether purified or used as produced. The effects of CNTs have been investigated following in vivo exposure of rodents, and on several types of cells in culture. Most studies concerned pulmonary toxicity [START_REF] Shvedova | Mechanisms of pulmonary toxicity and medical applications of carbon nanotubes: Two faces of janus?[END_REF][START_REF] Helland | Reviewing the environmental and human health knowledge base of carbon nanotubes[END_REF][START_REF] Kolosnjaj | Toxicity studies of carbon nanotubes[END_REF]. Animal experiments mainly focused on inflammatory responses after exposure by intratracheal instillation or aspiration, or intraperitoneal injection. In vitro cell systems with several types of mammalian cells have been used to study inflammatory responses and genotoxicity. A few in vivo and in vitro studies were related to dermal toxicity, and some in vitro studies focused on neurons [START_REF] Helland | Reviewing the environmental and human health knowledge base of carbon nanotubes[END_REF]. Toxicity test systems on procaryotes were also used to assess genotoxicity. Here our focus will be on respiratory effects. Biodistribution of CNTs after deposition in the lung or via other routes has been poorly investigated. A translocation of SWCNTs in various organs has been reported by several authors [START_REF] Mcdevitt | Tumor targeting with antibodyfunctionalized, radiolabeled carbon nanotubes[END_REF][START_REF] Cherukuri | Mammalian pharmacokinetics of carbon nanotubes using intrinsic nearinfrared fluorescence[END_REF][START_REF] Singh | Tissue biodistribution and blood clearance rates of intravenously administered carbon nanotube radiotracers[END_REF][START_REF] Wang | Biodistribution of carbon single-wall carbon nanotubes in mice[END_REF][START_REF] Elgrabli | Biodistribution and clearance of instilled carbon nanotubes in rat lung[END_REF]. In a recent study, MWCNTs deposited by intratracheal instillation in rats revealed clearance due to macrophage uptake and the lymphatic system without evidence of crossing the pulmonary barrier, six months after instillation [START_REF] Elgrabli | Biodistribution and clearance of instilled carbon nanotubes in rat lung[END_REF]. It can be noted that macrophage and lymphatic clearance was also demonstrated following administration or exposure to asbestos fibres [START_REF] Erdely | Cross-talk between lung and systemic circulation during carbon nanotube respiratory exposure. Potential biomarkers[END_REF][START_REF] Oberdörster | Size dependent lymphatic short term clearance of amosite fibers in the lung[END_REF][START_REF] Trosic | Pathways and quantification of insoluble particles in the lung compartments of the rat[END_REF][START_REF] Dodson | Asbestos content of lung tissue, lymph nodes, and pleural plaques from former shipyard workers[END_REF]. Erdely et al. [START_REF] Erdely | Cross-talk between lung and systemic circulation during carbon nanotube respiratory exposure. Potential biomarkers[END_REF] suggest that the release of soluble inflammatory factors could circulate to the vascular blood compartment after lung deposition of CNTs. The release of circulating factors must be taken into consideration to account for fibre effects. While asbestos fibres have been detected in the pleura, soluble molecules could also account for the pleural response [START_REF] Adamson | Kgf and hgf are growth factors for mesothelial cells in pleural lavage fluid after intratracheal asbestos[END_REF], and genotoxicity may be due to clastogenic factors [START_REF] Brooks | Evidence for 'bystander effects' in vivo[END_REF][START_REF] Emerit | Reactive oxygen species, chromosome mutation, and cancer -possible role of clastogenic factors in carcinogenesis[END_REF]. Additional studies are needed to determine the pharmacokinetics of CNTs. Regarding the numerous varieties of CNTs associated with a broad scale of physical and physico-chemical properties, fundamental studies will be necessary to establish the parameters leading the translocation process.

Biological effects on mesothelial cells

In vivo effects on mesothelial cells Six recently-published studies concerned CNTs' effects on mesothelial cells. Three reported findings from animal experiments and three from cell system studies. One animal experiment concerned the mesothelial cell inflammatory response and pathological changes after intra-peritoneal injection [START_REF] Poland | Carbon nanotubes introduced into the abdominal cavity of mice show asbestos-like pathogenicity in a pilot study[END_REF]. The authors exposed C57Bl/6 mice to four samples of MWCNTs of different sizes and aggregation states. There was one sample of "short" MWCNTs (from NanoLab, Inc; mean diameter: 14.8 ± 0.5 nm; mean length: 1-5 µm); two samples of "long" MWCNTs (Long1, from Mitsui & Co.; mean diameter: 84.9 ± 1.9 nm; mean length: 40-50 µm [24% > 15 µm of length]; Long2 from Univ. Manchester; mean diameter: 165 ± 4.7 nm; mean length: 20-100 µm [84% > 15 µm of length]); and one sample of more tangled MWCNTs (from NanoLab, Inc.; mean diameter: 10.4 ± 0.3 nm; mean length: 5-20 µm), as well as carbon black. At the same time, two samples of amosite fibres were tested; these were short fibres (4.5% > 15 µm of length) and long fibres (50.4% > 15 µm of length) known to be differently pathogenic in rodents. In prior experiments, inhalation and intraperitoneal exposure in rats to long amosite fibres revealed greater pathogenicity than short fibres in terms of fibrosis and cancer [START_REF] Donaldson | Inflammation generating potential of long and short fibre amosite asbestos samples[END_REF][START_REF] Davis | The pathogenicity of long versus short fibre samples of amosite asbestos administered to rats by inahlation and intraperitoneal injection[END_REF]. In the study reported by Poland et al. [START_REF] Poland | Carbon nanotubes introduced into the abdominal cavity of mice show asbestos-like pathogenicity in a pilot study[END_REF], inflammation was assessed after injection of 50 µg of MWCNTs/mouse, after 24h and seven days. The end points were quantification of inflammation in peritoneal lavage and histology of diaphragm. Only long samples of MWCNTs and of amosite produced inflammation and granulomas. Histological analyses revealed the occurrence of "frustrated phagocytosis" by macrophages. These results thus demonstrated some similarities between the responses to the long forms of amosite and MWCNTs. Several of the effects of asbestos were also found with CNTs. There were higher inflammatory responses with samples of long fibres. Only the samples that contained long fibres caused granulomas and "frustrated phagocytosis." A long-term study was performed by Takagi et al. [START_REF] Takagi | Induction of mesothelioma in p53+/-mouse by intraperitoneal application of multi-wall carbon nanotube[END_REF] who inoculated MWCNTs (MWCNTs-7 from Mitsui; diameter: 100 nm; length: 27% > 5µm) in the peritoneal cavity of C57Bl/6 p53 +/-mice. Because these mice have a mutation in one allele of the Trp53 gene, they are prone to develop cancer. Crocidolite fibres were inoculated as positive control. Mesotheliomas were found after exposure to both MWCNTs and crocidolite. This study has been discussed on several points, including concern about the type of mice, inappropriate exposure methods, high exposure dose, underestimation of the number of particles of MWCNTs and poorly-illustrated histology [START_REF] Ichihara | Re: Induction of mesothelioma in p53+/-mouse by intraperitoneal application of multi-wall carbon nanotube[END_REF][START_REF] Donaldson | Re: Induction of mesothelioma in p53+/-mouse by intraperitoneal application of multi-wall carbon nanotube[END_REF]. Details can be found in the different papers but some of the authors' replies can be summarized here. It is recognized that Trp53 +/-mice are more prone to develop cancers, and that the response using high doses by the intraperitoneal route of exposure provides different information regarding hazard potency. However, spontaneous excess of mesotheliomas has not been reported in this type of mice, and the injection method is applicable to the hazard approach for mesothelial cells in the absence of human data. Concerning the dose, the authors mentioned that other experiments using lower doses are in progress, giving similar responses [START_REF] Ichihara | Re: Induction of mesothelioma in p53+/-mouse by intraperitoneal application of multi-wall carbon nanotube[END_REF]. More recently, MWCNTs-7 were administered by a single intrascrotal injection in 7 Fischer 344 rats (240 µg/rat) maintained for an observation period of 52 weeks [START_REF] Sakamoto | Induction of mesothelioma by a single intrascrotal administration of multi-wall carbon nanotube in intact male fischer 344 rats[END_REF]. Dimensions were 82% of the MWCNTs with a diameter between 70-110 nm, and 72.5% between 1-4 µm in length. Five vehicle-treated controls and 7 UICC crocidolite-treated rats (470 µg/rat) were also studied. The overall incidence of mesotheliomas was 86% in MWCNT-treated rats while no mesothelioma was found in vehicle-or crocidolite-treated rats. This method of exposure of mesothelial cells is not usually used to assess a carcinogenic potency of fibres. However, injury at the scrotal mesothelium is used as a method to investigate the repair mechanism of peritoneal mesothelium [START_REF] Foley-Comer | Evidence for incorporation of free-floating mesothelial cells as a mechanism of serosal healing[END_REF][START_REF] Mutsaers | Mesothelial regeneration is not dependent on subserosal cells[END_REF]. Further data are clearly needed to improve our knowledge of the effects of these MWCNTs on mesothelial cells in vivo.

Effects on mesothelial cells in vitro

To the best of our knowledge, four studies have reported in vitro effects on mesothelial cells. DNA breakage and DNA repair were found in both human normal and malignant mesothelial cells exposed to SWCNTs, as well as cell activation via AP-1, NF-κB and Akt [44]. Another study concluded that there was alteration of cell viability and decreased cell proliferation in human mesothelioma cells exposed to SWCNTs [START_REF] Kaiser | Single walled carbon nanotubes (swcnt) affect cell physiology and cell architecture[END_REF]. Three studies reported cytotoxicity on human normal mesothelial cells, malignant mesothelioma cell line, and on large T SV40-transformed mesothelial cells (Met-5A) [44,46,[START_REF] Wick | The degree and kind of agglomeration affect carbon nanotube cytotoxicity[END_REF]. It is noteworthy that the same raw CNT material with different degrees of dispersion exerted different cytotoxicity on a human mesothelioma cell line [START_REF] Wick | The degree and kind of agglomeration affect carbon nanotube cytotoxicity[END_REF]. In this study, the toxicity of CNT-bundles (well-dispersed material with a bundle diameter of around 20 nm) was less than that of CNTagglomerates (densely roped aggregates with a rope diameter in the micron-range). CNTs appear to be taken up by different cell types and diverse in vitro effects have been associated with CNTs uptake [START_REF] Helland | Reviewing the environmental and human health knowledge base of carbon nanotubes[END_REF][START_REF] Kaiser | Single walled carbon nanotubes (swcnt) affect cell physiology and cell architecture[END_REF]. However, the cellular uptake of CNTs is controversial. Both absence and significant uptake have been reported, as recently discussed [START_REF] Shvedova | Mechanisms of pulmonary toxicity and medical applications of carbon nanotubes: Two faces of janus?[END_REF]. Uptake is likely dependent on interactions between cellular receptors and cell surface functions, and CNTs surface reactivity. A variety of cell surface functions may be found, depending on the cell type. CNTs may also carry diverse reactive groups. Different sorts of chemicals and biological molecules are currently used to disperse CNTs that may modify the CNTs surface. Hence cell-CNT interactions are dependent on a number of intrinsic and extrinsic parameters. It should be recalled that modification of the surface of asbestos fibres modulates the cell responses [START_REF] Wu | Vitronectin adsorption to chrysotile asbestos increases fiber phagocytosis and toxicity for mesothelial cells[END_REF][START_REF] Donaldson | Superoxide anion release by alveolar macrophages exposed to respirable industrial fibres: Modifying effect of fibre opsonisation[END_REF][START_REF] Boylan | Vitronectin enhances internalization of crocidolite asbestos by rabbit pleural mesothelial cells via the integrin avb5[END_REF][START_REF] Lu | In vitro genotoxicity studies of chrysotile asbestos fibers dispersed in simulated pulmonary surfactant[END_REF][START_REF] Jaurand | Chemical and photoelectron spectrometry analysis of the adsorption of phospholipid model membranes and red blood cell membranes on to chrysotile fibres[END_REF]. In macrophages, the scavenger receptor with collagenous structure (MARCO) seems to play an important role in pulmonary damage induced by inorganic particles [START_REF] Thakur | Differential binding of inorganic particles to marco[END_REF] and may be involved in interaction between MWCNTs and plasma membrane of macrophages [START_REF] Hirano | Multi-walled carbon nanotubes injure the plasma membrane of macrophages[END_REF]. In mesothelial cells, integrin receptors were reported to interact with asbestos fibres [START_REF] Boylan | Vitronectin enhances internalization of crocidolite asbestos by rabbit pleural mesothelial cells via the integrin avb5[END_REF][START_REF] Pande | Role of alphavbeta5 integrin receptor in endocytosis of crocidolite and its effect on intracellular glutathione levels in human lung epithelial (a549) cells[END_REF]. Recently, no particle internalisation was evidenced in large T SV40-transformed mesothelial cells (MeT-5A) exposed to MWCNTs, despite cytotoxicity [46]. Further studies are necessary to clarify these controversial results, as fibre internalisation is an important process accounting for the adverse cellular effects of particles, and more data are needed to determine the interactions of CNT with mesothelial cells.

Biological effects in other systems

Inflammation

Several studies have investigated the inflammatory response provoked by CNT exposure, conducted on mice or rats exposed via intratracheal instillation or inhalation. Several reviews may be consulted for more details [START_REF] Shvedova | Mechanisms of pulmonary toxicity and medical applications of carbon nanotubes: Two faces of janus?[END_REF][START_REF] Helland | Reviewing the environmental and human health knowledge base of carbon nanotubes[END_REF][START_REF] Stern | Nanotechnology safety concerns revisited[END_REF][START_REF] Kolosnjaj | Toxicity studies of carbon nanotubes[END_REF][START_REF] Boczkowski | Potential uses of carbon nanotubes in the medical field: How worried should patients be?[END_REF][START_REF] Donaldson | Carbon nanotubes: A review of their properties in relation to pulmonary toxicology and workplace safety[END_REF][START_REF] Bergamaschi | Nanomaterials and lung toxicity: Interactions with airways cells and relevance for occupational health risk assessment[END_REF]. Some recent data are summarized in Table 1 [START_REF] Erdely | Cross-talk between lung and systemic circulation during carbon nanotube respiratory exposure. Potential biomarkers[END_REF][START_REF] Liu | Toxicological effects of multi-wall carbon nanotubes in rats[END_REF][57][START_REF] Shvedova | Inhalation vs. Aspiration of single-walled carbon nanotubes in c57bl/6 mice: Inflammation, fibrosis, oxidative stress, and mutagenesis[END_REF][START_REF] Li | Comparative study of pathological lesions induced by multiwalled carbon nanotubes in lungs of mice by intratracheal instillation and inhalation[END_REF]. Regarding the large applications of CNTs and the known adverse effects of fine particulate matter, the potential effects of CNTs have also been investigated on systems other than respiratory [START_REF] Shvedova | Mechanisms of pulmonary toxicity and medical applications of carbon nanotubes: Two faces of janus?[END_REF][START_REF] Helland | Reviewing the environmental and human health knowledge base of carbon nanotubes[END_REF]. A recent study suggests that deposition of both SWCNTs and MWCNTs produce a systemic response, which may affect the cardiovascular system [START_REF] Erdely | Cross-talk between lung and systemic circulation during carbon nanotube respiratory exposure. Potential biomarkers[END_REF].

Genotoxicity

Both in vivo and in vitro effects of CNTs suggest a possible genotoxic effect, related to inflammatory responses and production of reactive oxygen species, as persistent inflammation is considered to increase the carcinogenic risk [START_REF] Federico | Chronic inflammation and oxidative stress in human carcinogenesis[END_REF].

In vivo, a mutation of the K-ras oncogene was observed in mice exposed to SWCNTs by inhalation, and chromosomal aberrations were detected in type II pneumocytes after intratracheal deposition of MWCNTs in mice [START_REF] Shvedova | Inhalation vs. Aspiration of single-walled carbon nanotubes in c57bl/6 mice: Inflammation, fibrosis, oxidative stress, and mutagenesis[END_REF]61]. Several in vitro studies have reported a genotoxic potency using different cell types (Table 2) [44,46,[START_REF] Hirano | Multi-walled carbon nanotubes injure the plasma membrane of macrophages[END_REF]57,[61][62][63][64][START_REF] Herzog | Swcnt suppress inflammatory mediator responses in human lung epithelium in vitro[END_REF][66][67][START_REF] Karlsson | Copper oxide nanoparticles are highly toxic: A comparison between metal oxide nanoparticles and carbon nanotubes[END_REF][69][START_REF] Simon-Deckers | In vitro investigation of oxide nanoparticle and carbon nanotube toxicity and intracellular accumulation in a549 human pneumocytes[END_REF]. Activation of DNA repair processes and mutagenesis of the adenine phosphoribosyl transferase gene was found in mouse embryonic stem cells [69]. Genotoxicity as assessed by the cytokinesis-block micronucleus test, was found in rat lung epithelial cells exposed to MWCNTs [57]. Micronuclei formation occurred in human epithelial cells (MCF-7) treated with MWCNTs, and a pancentrometric probe analysis demonstrated both chromosome breakage and chromosome loss [61]. DNA damage was also reported in SWCNT-treated mouse embryo fibroblasts and in CNT-treated bronchial epithelial BEAS 2B cells [63,67]. No mutation or DNA breakage was found in a FE1-Mutatrade markMouse lung epithelial cell line exposed to SWCNTs but purine oxidation was detected with the Comet assay [START_REF] Jacobsen | Genotoxicity, cytotoxicity, and reactive oxygen species induced by single-walled carbon nanotubes and c(60) fullerenes in the fe1-mutatrade markmouse lung epithelial cells[END_REF]. Investigations of the mutagenic potency of MWCNTs using bacterial test systems did not reveal mutagenic activity [START_REF] Sotto | Multi-walled carbon nanotubes: Lack of mutagenic activity in the bacterial reverse mutation assay[END_REF][START_REF] Wirnitzer | Studies on the in vitro genotoxicity of baytubes((r)), agglomerates of engineered multi-walled carbon-nanotubes (mwcnt)[END_REF]. These bacterial assays may not be fully relevant to evaluate genotoxicity of particles. Previous results with bacterial cells were generally not or only moderately positive with asbestos fibres [START_REF] Autho | Use of in-vitro genotoxicity and cell transformation assays to evaluate potential carcinogenicity of fibres[END_REF].

Asbestos fibres' mechanism of action 3.1. The asbestos legacy

Numerous publications on the mechanism of action of asbestos fibres have emphasized several responses associated with the mechanism of toxicity at the serosal level. They make it clear that two aspects must be considered: the biological response and the particle status. The first depends on several factors that include the fate of asbestos fibres following inhalation, i.e., their ability to reach the pleura. It is well know that deposition, clearance and translocation of fibres are dependent on biological mechanisms and partners (mucociliary transport, phagocytic cells), but also on fibre parameters, especially fibre dimensions. Short fibres are more easily internalised by macrophages than long fibres, and long fibres possibly involve "frustrated phagocytosis." The biopersistence of fibres is linked to both their dimensions and stability in the biological milieu.

Fate of asbestos fibres

Regarding industrial uses and commercial applications of asbestos fibres, the main risk of contamination is linked to the inhalation route. In general, particle deposition depends on aerodynamic considerations. Several authors have studied the mechanism of fibre deposition and retention in the lungs [START_REF] Oberdorster | Toxicokinetics and effects of fibrous and nonfibrous particles[END_REF][START_REF] Lippmann | Deposition, retention and clearance of inhaled particles[END_REF][START_REF] Morgan | Deposition of inhaled asbestos and man-made mineral fibres in the respiratory tract[END_REF][START_REF] Morgan | Studies on the deposition of inhaled fibrous material in the respiratory tract of the rat and its subsequent clearance using radioactive tracer techniques. Ii. Deposition of the uicc standard reference samples of asbestos[END_REF]. Once deposited in the lung, asbestos fibres may be translocated into different organs and tissues, including the pleura. This was demonstrated in animals following inhalation or intratracheal deposition [START_REF] Lippmann | Deposition and retention of inhaled fibres: Effects on incidence of lung cancer and mesothelioma[END_REF], and in humans by investigation of fibre retention in different body compartments including the pleura [START_REF] Paoletti | Characterization of asbestos fibers in pleural tissue from 21 cases of mesothelioma[END_REF][START_REF] Boutin | Black spots concentrate oncogenic asbestos fibers in the parietal pleura: Thoracoscopic and mineralogic study[END_REF][START_REF] Tossavainen | Retention of asbestos fibers in the human body[END_REF]. A recent paper discusses the translocation pathways of asbestos fibres to the pleura [START_REF] Miserocchi | Translocation pathways for inhaled asbestos fibers[END_REF]. Translocation appears to be due to trans-cell migration and lymphatic circulation. These authors propose that fibres deposited in the alveolar space can be translocated to the interstitium, down the gradient of physiological water absorption. This transfer is facilitated when the epithelial layer is damaged. Once in the interstitium, fibres can be distributed to different organs. Fibres can be cleared from the interstitium via the lymphatic system and enter the capillaries as inflammation increases the interstitial pressure, allowing the fibres to migrate and be distributed throughout the whole body. Therefore, fibres can reach the pleura via the capillary system and transfer through the visceral pleura. The parietal pleural has pores of relatively large diameter (about 150-200 nm), and the pleural fluid drainage goes through stomatas where particles are found to be concentrated. Translocation of CNTs to the pleura can be assumed, as asbestos fibres are not the only particles to be translocated to this site. Migration was observed after inhalation of refractory ceramic fibres and NMVF10a fibreglass in hamsters and rats, and anthracotic areas ("black spots") containing particulate matter are present in human pleura [START_REF] Boutin | Black spots concentrate oncogenic asbestos fibers in the parietal pleura: Thoracoscopic and mineralogic study[END_REF][START_REF] Bermudez | Pleural dosimetry and pathobiological responses in rats and hamsters exposed subchronically to mmvf 10a fiberglass[END_REF][START_REF] Gelzleichter | Comparison of pulmonary and pleural responses of rats and hamsters to inhales refractory ceramic fibers[END_REF][START_REF] Everitt | Comparison of pleural responses of rats and hamsters to subchronic inhalation of refractory ceramic fibers[END_REF][START_REF] Mitchev | black spots' and hyaline pleural plaques on the parietal pleura of 150 urban necropsy cases[END_REF]. One important point for the study of CNT toxicity is therefore to determine their ability to be distributed in the body and to reach the pleura. It is likely that the CNT aggregation state will modulate the rate of translocation. Recent experiments comparing inhalation and tracheal or pharyngeal deposition of CNTs concluded that the different effects were likely related to a difference in the dispersion and aggregation state of the CNTs [START_REF] Shvedova | Inhalation vs. Aspiration of single-walled carbon nanotubes in c57bl/6 mice: Inflammation, fibrosis, oxidative stress, and mutagenesis[END_REF][START_REF] Li | Comparative study of pathological lesions induced by multiwalled carbon nanotubes in lungs of mice by intratracheal instillation and inhalation[END_REF]. It can also be assumed that the CNT pretreatments used for particle dispersion will also influence the biodistribution of these particles. Moreover, it must be kept in mind that CNT exposure takes place via routes other than inhalation, which ought to be investigated.

Biological and genomic effects of asbestos fibres on mesothelial cells

Inflammation and mesothelial cell activation

Many authors have described the inflammatory processes occurring in the lung and in the pleura, and shown that fibres can interact with mesothelial cells in culture conditions. Fibre deposition in the lung is followed by the recruitment of inflammatory cells, which produce several factors: ROS (reactive oxygen species), RNS (reactive nitrogen species), clastogenic factors and cytokines that may stimulate and/or damage neighbouring mesothelial cells. Fibres also may produce ROS. Moreover, mesothelial cells respond by fibre internalisation according to a phagocytic process associated with oxidative reactions [START_REF] Adamson | Kgf and hgf are growth factors for mesothelial cells in pleural lavage fluid after intratracheal asbestos[END_REF][START_REF] Manning | Diseases caused by asbestos: Mechanisms of injury and disease development[END_REF][START_REF] Vallyathan | Enhanced generation of free radicals from phagocytes induced by mineral dusts[END_REF][START_REF] Antony | Pleural cell biology in health and disease[END_REF][START_REF] Autho | Mechanisms of mineral fibre carcinogenesis[END_REF][START_REF] Shukla | Multiple roles of oxidants in the pathogenesis of asbestos-induced diseases[END_REF][START_REF] Bhattacharya | Biomarkers in risk assessment of asbestos exposure[END_REF]. In this situation, mesothelial cells adapt to the oxidative environment by oxidative stress, increasing oxidant defences and decreasing natural ROS and RNS production. At the same time, several regulatory pathways are activated: signalling pathways (MAPKs) associated with cell proliferation and apoptosis, and DNA repair and control of cell cycle progression in response to DNA damage [START_REF] Upadhyay | Asbestos-induced pulmonary toxicity: Role of DNA damage and apoptosis[END_REF][START_REF] Jaurand | Mechanisms of fiber-induced genotoxicity[END_REF]. These different reactions are the consequence of 2 types of interactions: between cells (inflammatory cells/mesothelial cells) and between cells and fibres. As neoplastic transformation is linked to genetic damage and requires proliferation steps, comparison between the genotoxic effects of asbestos and CNTs might provide clues making it possible to develop hypotheses about the potential effects of CNTs.

Genotoxicity

Many investigations have focused on DNA damage provoked by asbestos fibres in mesothelial cells. Several studies have demonstrated different types of DNA damage (DNA breakage, base oxidation), and perturbation of the mitotic process [START_REF] Upadhyay | Asbestos-induced pulmonary toxicity: Role of DNA damage and apoptosis[END_REF][START_REF] Jaurand | Mechanisms of fiber-induced genotoxicity[END_REF], showing that base oxidation and DNA breakage (single strand and double strand breaks) were detected in asbestos-treated mesothelial cells [START_REF] Jaurand | Mechanisms of fiber-induced genotoxicity[END_REF][START_REF] Nygren | DNA damage in bronchial epithelial and mesothelial cells with and without associated crocidolite asbestos fibers[END_REF][START_REF] Unfried | Distinct spectrum of mutations induced by crocidolite asbestos : Clue for 8-hydroxydeoxyguanosine-dependent mutagenesis in vivo[END_REF][START_REF] Burmeister | Effects of asbestos on initiation of DNA damage, induction of DNA-strand breaks, p53-expression and apoptosis in primary, sv40-transformed and malignant human mesothelial cells[END_REF][START_REF] Liu | Phagocytosis of crocidolite asbestos induces oxidative stress, DNA damage, and apoptosis in mesothelial cells[END_REF][100]. These may be due to ROS / RNS production and to the mesothelial cells' ability to phagocytise asbestos fibres. Fibre uptake does not abolish the mitotic process as some fibres are found in dividing mesothelial cells. Moreover, extensive chromosome damage was described. A list of chromosome abnormalities has been reported by different authors. Asbestos fibres produce structural chromosome alterations; significant enhancement of aneuploid cells, abnormal anaphases and telophases [101-105]. Induction of micronuclei by all types of asbestos in primary cultures of human mesothelial cells has been reported by Poser et al. [106]. Other studies have shown genomic alterations in asbestos-treated human mesothelial cells. Loss of heterozygosity was detected as asbestos-induced mutations in a human mesothelioma cell line [107]. Using 3D reconstruction, Cortez et al. recently reported mitotic abnormalities, centrosome amplification and aneuploid cell formation in lung carcinoma cells, even with long periods of recovery post-treatment [108]. These findings are similar to earlier reports concerning rat pleural mesothelial cells and using less powerful methods.

Gene expression in asbestos-treated mesothelial cells

A few studies have investigated gene expression in asbestos-treated mesothelial cells using microarray analysis (Table 3) [109-111]. They confirmed results obtained in studies focusing on given types of damages. Modulation of several biological processes were observed. They were associated with inflammatory, proliferation, DNA repair and cell adhesion pathways. Further studies comparing the cell response to CNTs and to the different types of asbestos fibres are likely to be informative in order to approach the possible effects of CNTs.

Gene alterations in mesothelioma

Epidemiological studies have shown that MM is a consequence of asbestos exposure in a majority of cases [START_REF] Albin | Asbestos and cancer: An overview of current trends in europe[END_REF][START_REF] Kishimoto | Cancer due to asbestos exposure[END_REF][START_REF] Kishimoto | Malignant pleural mesothelioma in parts of japan in relationship to asbestos exposure[END_REF][START_REF] Mowe | Occupational exposure and regional variation of malignant mesothelioma in norway, 1970-79[END_REF][START_REF] Park | Asbestosrelated occupational lung diseases in nsw, australia and potential exposure of the general population[END_REF][START_REF] Yeung | An occupation-industry matrix analysis of mesothelioma cases in australia 1980-1985[END_REF][START_REF] Goldberg | The french national mesothelioma surveillance program[END_REF]. This led us to assume that genomic alterations found in MM could be linked to the effect of asbestos fibres. The identification of these changes can provide insight into the molecular mechanism of action of asbestos on mesothelial cells. MM cells exhibit frequent alterations in tumour suppressor genes found at the INK4 locus, and often the type of alteration is deletions. NF2 is another frequently inactivated tumour suppressor gene in MM cells. Germinal mutations in NF2 are responsible for type 2 neurofibromatosis, but NF2 patients are not prone to develop mesothelioma. TP53 is mutated less often in MM cells. To investigate whether genetic alterations in mesothelioma might be relevant to the effect of asbestos fibres, animal models of human MM are developed. Mesotheliomas develop following exposure, by intraperitoneal injection, of hemizygous NF2 mice to asbestos fibres [112,113]. This made it possible to compare characteristics of mouse and human mesotheliomas. Histologically, very similar tumours were observed, and the genomic alterations in the tumour suppressor genes investigated were very close to those observed in human MM. These gene are involved in the control of cell cycle and junction stability. Regarding the function of the gene, it might be of interest to determine the consequences of CNT exposure on cell cycle progression and cell architecture.

Asbestos fibre characteristics related to disease

If one looks at fibre parameters, several features appear to be shared by CNTs and asbestos fibres. To compare CNTs and asbestos fibres in relation to toxic potential, we should focus on the asbestos characteristics modulating asbestos toxicity. Shape, size, chemistry and surface reactivity are all related to cell and tissue responses to asbestos fibres.

Shape

CNTs have a thin and elongated shape compatible with a fibre, according to the WHO fibre definition of a particle with parallel edges and an aspect ratio (length/diameter) greater than three. It seems that CNTs are prone to form aggregates, ropes and clumps, a feature that is not fully similar to asbestos, which forms bundles of rather well-organized structures. The length of CNTs may vary, reaching up to several micrometers or longer [START_REF] Donaldson | Carbon nanotubes: A review of their properties in relation to pulmonary toxicology and workplace safety[END_REF]114]. Accordingly, "frustrated phagocytosis" was observed in cells engulfing long CNTs [START_REF] Poland | Carbon nanotubes introduced into the abdominal cavity of mice show asbestos-like pathogenicity in a pilot study[END_REF].

Size

The diameters of asbestos fibres fall in the nanosize range. If one refers to the dimensions of the UICC samples, which have been used in a number of animal and cell studies, the diameter of chrysotile fibres was less than about 100 nm, and 200 nm for crocidolite. Length depended on the sample, but generally averaged several micrometers. However, there was a significant range in length and a small percentage of fibres longer than 10 µm were generally present.

Chemistry

Metals are considered to be important elements to account for fibre toxicity. Iron content, either structural or as contaminant, may be linked to the formation of ROS and RNS. Depending on the method of production, CNTs may contain metals as contaminants; moreover, they can be functionalized to acquire specific properties. Data in the literature show a wide qualitative and quantitative diversity of metal contaminants in the chemical composition of CNT samples, emphasizing the importance of using well-defined samples for toxicological analyses [START_REF] Donaldson | Carbon nanotubes: A review of their properties in relation to pulmonary toxicology and workplace safety[END_REF].

Surface reactivity

Surface reactivity is an important parameter in asbestos-related effects. The production of ROS and RNS was mentioned above. It is interesting to note that some studies indicate that, in contrast to asbestos, CNTs quench ROS in an acellular system generating hydroxyl radicals [115]. While asbestos fibres are hydrophilic, CNTs, unless functionalized, are hydrophobic. As a result, CNTs are often treated with dispersing agents prior to exposing cells or animals to CNTs suspended in aqueous medium.

Asbestos fibres' ability to adsorb biological molecules is another fibre parameter to take into consideration. Asbestos adsorbs proteins and phospholipids, which has consequences on cell-fibre interactions. An enhancement of biological effects can be observed (particle internalisation, cytotoxicity), as well as a reduction of toxicity [116][117][118][119]. Asbestos bodies are structures found in the lung of asbestos-exposed subjects. They consist of an asbestos fibre core surrounded by a complex coat produced by the cell and tissue reaction; they are made of apatite mineralization and protein aggregation (hemosiderin, ferritin). These structures are more likely formed on amphiboles rather than on chrysotile. They are not specific to asbestos, as they have been reported in other fibrous and non-fibrous particles. It would be of interest to know whether these structures could be formed on CNTs [120-122].

Biopersistence

While biopersistence is not an intrinsic particle parameter, it has received attention for the evaluation of the carcinogenic potency of manmade vitreous fibres (MMVFs) [123,124]. Biopersistence in the lung is the result of a clearance mechanism and the behaviour of fibres in the biological medium. Clearance depends on particle uptake by scavenger cells; it is then modulated by the fibre size and toxicity (short particles are eliminated following uptake by macrophages; cytotoxic particles impair the process). The behaviour of the fibres is also size-dependent (fibre dimensions govern the mechanism and site of deposition in the lung), as well as dependent on the fibre structure and chemistry (these parameters modulate the stability of the particles in the biological medium). Some chemical elements may dissolve and reduce fibre strength, breaking the fibres into smaller fragments. Finally, biopersistence modulates the amount of fibre retained in the lung and the time it remains in the lung. To date, CNTs have been considered biopersistent, but further studies are needed to determine the relevance of this parameter in the context of human exposure to CNTs [57].

Discussion

CNTs are valuable industrial products with multiple applications in the field of nanotechnologies, yet legitimate concerns about their potential adverse effects on human health need to be addressed. The risk of MM, a primary pleural carcinoma linked to asbestos exposure, must be examined in light of the physical nature of CNTs, which are elongated and ultrafine, and the fact that human beings may be exposed to CNTs through inhalation.

While not yet definitive, data are now available providing information on the pulmonary and cellular effects of CNTs, which may be compared to those of asbestos fibres. Moreover, the asbestos fibre characteristics involved in the toxic processes may be compared to those of CNTs to determine their similarities. These comparisons make it possible to develop hypotheses about common and different mechanisms of action. A summary of comparisons between CNTs and asbestos is provided in Tables 4 and5. A paradigm for the health effects of HARN has emerged from toxicology studies of industrial fibres, including asbestos. A recent report reviewed state-of-the-art knowledge of the toxicity of asbestos and HARN [START_REF] Tran | An outline scoping study to determine whether high aspect ratio nanoparticles (harn) should raise the same concerns as do asbestos fibres[END_REF]. This clearly suggest a community of toxicological features and concern between HARN of different origin and composition. The reader will find in this quoted review additional information on other HARN (nanowires, nanorods) and the proposal for a research strategy to determine the potential toxicity of HARN.

Shape, structure and chemistry

Both CNTs and asbestos particles share fibrous morphology, and their dimensions are in the same range. CNTs are manufactured in two main forms, SWCNTs and MWCNTs. A SWCNT is a single-layer graphene sheet rolled up in a cylindrical shape, whereas a MWCNT contains several layers [125]. The structure of chrysotile presents similarities with MWCNT. CNT samples may have much higher length than asbestos fibrils and form clumps resulting in different presentation and tissue penetration. One role of CNT sample dispersion to modulate biological effects is suggested by the results reported from in vivo experiments studying inhalation and intratracheal deposition.

Biodistribution

Similarly to asbestos fibres, CNTs may be deposited and retained in the lung after inhalation. So far, there is no definitive data on their migration and long-term retention, and on their translocation to the pleura. Interaction with mesothelial cells is likely important to account for asbestos pathogenicity; however, distant effects after deposition in the lung have been reported. As already mentioned, CNTs are the subject of scientific interest for a large number of already mature or potential applications. One paradox is that biological studies with CNTs are designed to investigate both adverse (exposure to toxic dust) and beneficial (nanomedicine) effects. These different types of studies show that MWCNTs are concentrated in the lymph nodes after deposition in the lung, and that functionalized MWCNTs also accumulate in lymph nodes after subcutaneous injection [START_REF] Elgrabli | Biodistribution and clearance of instilled carbon nanotubes in rat lung[END_REF]126]. CNT biodistribution has been studied following intraperitoneal or intravenous injection in mice. CNTs are distributed throughout the entire body and cleared via urine excretion. McDevitt et al. found an accumulation of labelled SWCNTs in the kidney, liver, spleen and, to a lesser extent, in bone [127]. There is to date no reason to exclude the possibility of CNT translocation to the serosa. In a recent paper, Hankin et al. [128] summarized the research required into the mechanism of translocation of nanoparticles across the respiratory epithelium, and the resulting possible effects in and beyond the lung. The authors provide recommendations to develop research on translocation and penetration of nanoparticles that take into consideration the parameters allowing a robust interpretation of the data.

The relationship between structure and biological effects

Based on our present knowledge, a comparison between cell responses to SWCNTs and MWCNTs cannot be established. This is partly due to the limited number of investigations carried out with both types of nanotubes in the same assays. Nevertheless, both types are able to induce biological responses in one or several cell types, and in the lung. While studying the biodistribution of MWCNTs following intraperitoneal injection, Guo et al. compared different results obtained with both SWCNTs and MWCNTs [129]. These authors suggest that toxic responses observed in the kidney in some studies may depend on whether CNTs are functionalized, a procedure that may improve the biocompatibility. Surface functionalization, purity and treatment of CNTs appear to modulate the biological response, as found in different studies [115,130,131]. The surface modifications of CNTs developed in the field of nanomedicine studies are of interest to learn about interactions between CNTs and cells or organelles. It is already known that surface changes influences cell responses. Viability of neuroblastoma cells was not affected by pure MWCNTs (99% purity). Viability and proliferation were reduced after acid treatment or when MWCNTs of lower purity were used (97%) [131]. Acute pulmonary toxicity and genotoxicity of MWCNTs were reduced upon heating but restored upon grinding, in relation with surface defects [57] Studies carried out with asbestos have demonstrated that long and thin fibres are more toxic than short fibres, without excluding potential toxicity for short fibres. Limits of 4 µm or 8 µm in length have been proposed, mainly based on in vivo experiments. CNTs can fulfil these length criteria, and similarly to asbestos, long CNTs were more active than short CNTs [START_REF] Poland | Carbon nanotubes introduced into the abdominal cavity of mice show asbestos-like pathogenicity in a pilot study[END_REF]. More data on size-dependent biological effects of CNTs will be of great interest. Surface reactivity of asbestos fibres has been largely advanced as a key parameter accounting for their toxicity in terms of ROS production and sorptive abilities. ROS production is associated with cytotoxicity, cell activation, and chromosome and DNA damage. Conflicting data are found with CNTs, as both production and scavenging of ROS were described. CNTs are a large family regarding their method of generation, treatment and functionalization. Hence the surface reactivity of CNTs towards biological systems will be largely dependent on the type of nanotubes. This may be maximized by treatments to disperse CNTs prior to use for biological studies. Different CNTs samples may have more heterogeneous surface activities than asbestos.

Biological effects

Available data in the literature concerning the effects of CNTs on mesothelial cells remain limited. Several effects of asbestos fibres, especially genetic damage, are related to fibre internalisation. While asbestos fibres are clearly internalized by mesothelial cells, there is no definitive data on CNT uptake by these cells. The physico-chemical properties of CNTs are likely to take into consideration in the occurrence of this physiological process.

Animals and cell systems exposed to CNTs appear to develop several responses similar to those observed with asbestos. There is some evidence that CNTs produce inflammation and mesothelioma when inoculated in the peritoneal cavity of mice. This result is consistent with inflammatory potency after inhalation or intratracheal instillation. Several CNT-exposed mammalian cells respond in culture conditions by inflammatory reactions and oxidative stress. Genotoxic potency has been reported in different cell types, including mesothelial cells, as well as in studies conducted in vivo. Hence CNTs used in experimental systems fulfil several criteria to elicit tissue injury, including the mesothelium.

Conclusions

The link between asbestos effects and mesothelioma has been attributed to several mechanisms. This link has been investigated using different animal models and cell types, and substantial similarities exist in the responses of the different cell types.

Several fibre properties have been linked to adverse effects. Shape, dimension and surface reactivity are all important parameters. Reactive species may produce DNA lesions (base oxidation, breaks); their origin is related both to fibre surface reactivity and phagocytosis. Inflammation contributes to the production of ROS/RNS. Chromosome damage appears to be of major importance to account for the significant effects of asbestos. Gene deletions and recombinations might result from these effects.

Integrity of some cell processes may be critical in the response to asbestos: dynamics of the cell membrane (fibre uptake, cell division) and control of cell division (check points, chromosome segregation processes, repair of DNA breakage, cytokinesis). In view of findings of a much less hazard of short than some long/non-biopersistent HARN, more information is needed on the CNTs' characteristics and conditions to which we may be exposed. Based on available data in the literature and knowledge of the mechanisms of action of asbestos fibres, it appears that CNTs may elicit responses that are similar to those caused by asbestos fibres. In this review, for the sake of brevity, CNTs have been considered as a single entity. However, there is a large degree of heterogeneity within the CNT family. The legacy of our knowledge on the mechanism of action of asbestos prompts us to recognize some similarities between these two types of particles. Nevertheless, in view of the diverse uses of CNTs, toxicological studies should be carried out in the context of the respective applications, taking into consideration the possible interactions between the target tissue and the nanotubes, and their possible biodistribution. An evaluation of the conditions and type of exposure to CNTs thus appears mandatory to focus clearly on the safety and health issues. Exposure by inhalation for aerosolized CNTs must take into consideration both lung and pleural diseases.

Acknowledgements

The authors would like to thank Audrey Saint-Albin for her help in editing the manuscript.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions MCJ contributed to the design and drafting of the manuscript. AR participated in the acquisition of data on asbestos on mesothelial cells and the genetics of mesothelioma cells. JD analysed the data in the literature on gene expression. Effects of heated CNTs lower than unheated.

Grinding restored the effects.