Robert Castellana

Elisabeth Tabone

Mathilde Capelli

Catherine Gigleux

M Cristofaro

Hervé Pietra

Predictive diffusion of palms pests Rhynchophorus ferrugineus & Paysandisia archon and perspectives about biological control

come   L'archive ouverte pluridisciplinaire

Predictive diffusion of palms pests

To contact us: robert.castellana@laposte.net

  species of palms are actually infested by Rhynchophorus ferrugineus & Paysandisia Archon, according to the observations of our network of French & Italian Botanical Collections of ca 100 ornamental palm species. Predictive diffusion of these pests may also concern in the future the 2500 species of wild populations of palms in Asia, South America and Africa. The adaptation of these pests to new environments and climatic conditions, and the difficulties to detect early symptoms of infestation, were determining a failure of all eradication and suppression conventional control programs like Integrated Pest Management, based mainly upon the use of chemical or agronomic approaches. Our French & Italian Network is associated with the researches about biological control by Inra (France) & Enea (Italy).

PA: 35 SPECIES Our observations about infestation concerning ca 100 ornemental palms Paysandisia archon (PA) versus Rhynchophorus ferrugineus (RPW)

	Acoelorraphe wrightii
	Arenga engleri
	Brahea aculeata, armata, dulcis, edulis	Brahea armata & edulis
	Chamaerops humilis	Butia capitata & yatay
	Howea fosteriana	Chamaerops humilis
	Jubaea chilensis	Howea fosteriana
	Livistona australis, chinensis, decora	Jubaea chilensis
	(decipiens), saribus	Livistona chinensis
	Nannorrohops arabica	Nannorrohops arabica
	Phoenix dactylifera, reclinata, robellini,	Phoenix dactylifera, canariensis,
	theophrasti	sylvestris
	Sabal bermudana, mauritiiformis, minor,	Sabal mexicana
	palmetto	Serenao repens
	Serenao repens	Syagrus romanzoffiana
	Syagrus romanzoffiana	Trachycarpus fortunei
	Trachycarpus sp: 10 sp/15	Trithrinax campestris
	Trithrinax acanthocoma	Washingtonia filifera & robusta
	TOTAL	TOTAL RPW: 19 SPECIES


Robert Castellana

Elisabeth Tabone

Catherine Gigleux

M Cristofaro

Hervé Pietra

Predictive diffusion of palms pests Rhynchophorus ferrugineus & Paysandisia archon and perspectives about biological control

come

EUNOPS 2019 :

 2019 MENACES SUR LES PALMIERS Notre réseau rassemble plusieurs instituts de recherche, jardins botaniques et associations, en France et en Italie, lesquels alertent sur la menace représentée par deux ravageurs actuellement diffusés suite à un commerce incontrôlé de palmiers ornementaux, Rhynchophorus ferrugineus & Paysandisia archon. Un tiers des espèces de la centaine de palmiers ornementaux cultivés dans nos régions sont actuellement menacés selon nos observations. Certains d'entre eux commencent à être menacés dans leur habitat naturel. Il existe 2500 espèces de palmiers. Ils constituent une biodiversité remontant à des temps préhistoriques et sont par ailleurs à la base de l'économie de nombreuses régions parmi les plus pauvres de la planète. Au-delà du fait d'alerter la communauté scientifique sur les menaces à venir, nous présenterons brièvement lors de ce Congrès nos initiatives en réseau relatives au soutien à la recherche sur le bio-contrôle de ces ravageurs : *Biocontrôle de Paysandisia archon : en France, l'Inra (Antibes & Versailles) travaille sur les Antagonistes (parasitoïdes oophages) & sur la Confusion Sexuelle (phéromones d'agrégation) *Biocontrôle de Rhynchophorus ferrugineus : Snp & Fredon Corse cherchent de leur côté à développer le piégeage de masse. Snp soutient par ailleurs la mise sur le marché des souches de champignons entomopathogènes du type Beauveria bassiana. Notre partenaire italien, l'Enea, est quant à lui en train de finaliser la technique dite de l'insecte stérile (SIT). Castellana R. (Phoenix Project), Tabone E. (Inra Antibes), Gigleux C. (Fredon Corse), Cristofaro M. (Enea Italy) & Pietra H. (Sauvons Nos Palmiers -France). Predictive diffusion of palms pests Rhynchophorus ferrugineus & Paysandisia archon and perspectives about biological control. Key words: Rhynchophorus ferrugineus, Paysandisia archon, biological control, palms pests EUNOPS 2019 : RIVIERA BOTANICAL GARDENS More than 35 species of palms are actually infested by Rhynchophorus ferrugineus & Paysandisia Archon, according to the observations of our network of French & Italian Botanical Collections of ca 100 ornamental palm species. Predictive diffusion of these pests begin to concern wild populations of these palms, and may concern in the future others species in Asia, South America and Africa. The adaptation of these pests to new environments and climatic conditions, and the difficulties to detect early symptoms of infestation, were determining a failure of all eradication and suppression conventional control programs like Integrated Pest Management, based mainly upon the use of chemical or agronomic approaches. We will present at Eunops 2019 the researches about biological control by the French & Italian partners of our network: *Biological Control of Paysandisia archon: Inra France (Antibes & Versailles) are working on Antagonists (Oophages parasitoids) & Sexual Confusion (Aggregative pheromones) *Biological Control of Rhynchophorus ferrugineus : Snp & Fredon Corse (France) are working about Mass trapping & Snp also about researches concerning Entomopathogenic fungi (like Beauveria bassiana). Enea (Italy) is working about the Sterile Insect Technic (SIT).


domain: sdv shs

text:
A fraction is protected as PDO

• Obviously, most of these types are just local specialty products without large commercial ambition.

• But, in 2018, the main French cheeses are often recognized at European level, -45 as Protected Designation of Origin (PDO) -and 7 as Protected Geographical Indication (PGI). • Second country in EU after Italy (50 registered) out of the 189 cheeses (see DOOR). • From Roquefort (a ewe cheese) in 1925 (very first protected cheese in the world) up to the last one (till now), a goat cheese named Charolais (registered in 2014)

Rennes 4 -6 April 2018

The French PDO cheese platter

Rennes 4 -6 April 2018

PDO cheeses in France : Value production

• This production of PDO cheeses represents yearly more than 200 Ktons so almost 10% of the total amount of cheeses produced in France.

• But the total of estimations of domestic consumption and export reaches 28.5 % of the total turnover (for cheeses) of the firms concerned.

• Source : Chiffres-clés 2016 -Des produits sous signe de la qualité et de l'origine -Produits laitiers AOP et IGP INAO -CNAOL (2017) Rennes 4 -6 April 2018

The GI landscape of French milk products

• GI includes also the PGI / Milk products includes also butter and creams : Add 3 butters and 2 creams PDO + 7 PGI (6 cheeses and 1 cream).

• In 2016, all GI milk products gathered 255 424 tons and 13,5% of the turnover.

19 343 milk producers, 1 281 on-farm processors and 423 cheese-makers A great proportion of dairy farms involved

• The dairy farms involved in this activity gather in the country :

• 10% of cow milk for 24% of dairy cattle farms (and 28 PDO cheeses),

• 13.5% of goat milk for 34% of dairy goat farms (and 14 PDO cheeses),

• up to 41% of ewe milk for 88% of dairy ewe farms (and 3 PDO cheeses).

Source : Joint report INAO -CNAOL ( 2017)

Rennes 4 -6 April 2018

Different types of cheese French consumers of PDO cheeses

• French cheese consumption : 2 d in the world (after Greece) with 26 Kg / y, 96% of people (47% every day).

• French PDO cheese consumption : some specificities Income criterion : High and medium income (but light effect)

Age : higher for seniors

Family composition : higher for couples and for families with children (increasing with the age of the children)

Rennes 4 -6 April 2018

Connecting food to place : The concept of « terroir »

• In the French tradition, to be recognized as origin product implies a strong link to the local ecosystem referred to the concept of "terroir".

• Impossible to translate (Barham, 2003) • This concept shapes the content of the specifications making mandatory the use of certain resources and know-how.

Rennes 4 -6 April 2018

Definition of « Terroir »

• A terroir is (1) a delimited geographical area (2) where a human community (3) over the course of history generates and accumulates a collective body of production knowledge (4) based on a system of interactions between biophysical and human factors.

(5) The sequence of socio-technical steps involved (6) reveals originality, (7) confers typicity (8) and earns a reputation (9) on a good originating in the geographical area in question. Feeding methods as source of specificity

• Great diversity in the PDO specifications.

According to the local resources.

• Grass and hay are dominant.

Studies on the effects of types of pasture and hays (See Martin B.)

• Silage are increasingly prohibited. With transition periods.

Camembert [of / made in] Normandy ?

• The raw milk inside a major crisis in the French PDO cheese world. Traditional and artisan cheese-makers

• The size of the cheese processing units is also an important issue as artisan, small scale and on-farm processors are part of a lot of PDO systems.

• A particular pattern : the « fruitières » in Alps, Jura and Franche-Comté (influence of Swiss tradition) Traditionnally, every breeder has few cows and for making a cheese, needs to mix his milk with the neighbors. The group creates a Fruitière and hire a cheese-maker. Ancient setting remaining till now.

  Rennes 4 -6 April 2018 Biodiversity : the use of local breeds • Several PDO cheese specifications includes local breeds as mandatory Northern Alps (Beaufort and Tome des Beauges) with Tarentaise and Abondance breeds Comté with Montbéliarde and Simmental breeds • Local breed with increasing proportion in specification revision Camembert de Normandie with Normande breed Abondance with Abondance breed • Mention of the breed if 100% of the herd Munster with Vosgienne breed Salers and Cantal with Salers breed (mention « Tradition Salers ») Rennes 4 -6 April 2018 Milking a herd of Salers cows in mountain Rennes 4 -6 April 2018 An example in Savoie PDO cheeses Rennes 4 -6 April 2018 a local breed in PDO specification Impact on the collective management and the individual uses Rennes 4 -6 April 2018 (Lambert-Derkimba et al, 2010 Animal)

•

  A great firm decided to quit the PDO Camembert de Normandie for sanitary reasons (officially). But using the sourcing denomination « fabriqué en Normandie ». • Conflict between both types of cheeses on the use of the protected name. PDO with raw milk, with more pasture and increasing porportion of Normande breed. • Presently, a new negociation for solving the conflict… Rennes 4 -6 April 2018

•

  When comparing 2016 with 2006, the total volume is quite stable : + 2.7 %

	Rennes 4 -6 April 2018

Rennes 4 -6 April 2018

On-farm processors : « fromage fermier »

• More than 20% of the French on-farm processors are producing PDO cheeses.

• Even if people in [short chains + direct selling] have no real utility for PDO / they manage their reputation through inter-personal relationships (« domestic city »). • On-farm PDO cheeses represent 8,25 % of the total PDO cheeses.

This proportion is increasing every year.

The most frequent units are in Saint-Nectaire, Reblochon, Salers (mandatory), Abondance and Munster. • For Saint-Nectaire and Reblochon, they benefit of a distinction (green casein pastilla) within the surface of the cheese.

Rennes 4 -6 April 2018

Rooting the processing activity

• The spatial distribution of the 400 units and 1250 on-farm processors within all the rural areas concerned confers to this production a major role in terms of sustainable development.

• A unique case in the French PDO cheeses :

The « fruitières » of Comté. • Limit of transportation of the milk for making the Comté PDO cheese, up to 25 km from the processing unit.

Avoids the concentration in huge units, enhances the effects of location (the « crus »), protects the employment in the rural areas. Main stakes for knowledge production strategy

• New tools for traceability of milk and cheese / location and production methods

• Interactions genotypes x environment (including practices) / specification evolvments

• Native flora of raw milks, local starters/ sources and roles in the process / providing microbiota for humans

• Links with cheese aromas and flavours / learning processes with young people

• Relevant markets and access conditions / Distribution of value added within the chain

• Governance of the PDO system (local democracy) / Relationships with the territory Sustainability, agro-ecology, heritage management, « basket of goods » at territorial level.

• RMT Fromages de terroir / GIS Filières fromagères sous indication géographique Thank you for your attention


→→

  A2 hydrolyses for instance fatty acid in position sn-2, releasing R2 FFA and a lysophospholipid. This lysophospholipid is a powerful detergent able to break cellular membranes. Snake and bee venoms are very rich in PLA2. Get rid of FFA under the form of soap or «neutralization pastes» : crucial unitary operation of refining. Pastes: soaps of sodium, soda, water, salts, sodium phosphates, mucilages, neutral oil can be retained, coloring constituants, oxydation products and diverse contaminants. → Reactions taking place during this process are:  neutralization of exces of phosphoric acid added to degum oils (1)  neutralization of FFA under the form of sodic soaps: R-COOH + NaOH -> R-COONa +H 2 O (2) → As weak acids, reaction in exces of alkali displaces equilibrium towards soaps formation, ↓ residual acidity. Excess ~ 0,01 et 0,05 % for degummed soya oil → AVOID «side saponification» (3), i.e. partial saponification of triglycerides => glycerol and sodium soaps. ↑ losses. Get rid of alkalines substances (soaps and soda in excess) present at the outlet of neutralization turbine, + last traces of metals, phospholipids and other impurities. Objectives: < 30 ppm of soap.→ Good separation of raw oil/degumming otherwise → important emulsions are being formed, difficult elimination of soaps.→ Washing more effective if done in two steps, water washing must be as hot as possible (90°C).→ Post-stream Drying: humidity removal if still present in washed oil before decoloring operation → risk of filter clogging specially in the presence of soaps. FA in refined oils (colza oils, combined oils) -Source ITERG

Influence of temperature and quality of catalyst on AG trans formation Trans FA content in several food products

  Applications : raw matter for margarine, pastry, frying oils, …. physical fractionation, IE (chimical ou enzymatic) … INTERESTERIFICATION Principle : rearrangement of FA on glycerol  modif. Of melting behavior of oil without modification of the oil global FA composition

	REFINED FATS ADAPTATION OF FATS to FOOD APPLICATIONS FRACTIONATION FRACTIONATION OF FATS FRACTIONATION OF FATS FRACTIONATION OF PALM OIL HYDROGENATION PRINCIPE SCHÉMATIQUE DE L'HYDROGÉNATION
	Teneur en AGT En % des AG Totaux HUILE TAG P.lipides AG Libres AG trans Stérols Tocophérol Pr. d'ox. Cires Pigments Métaux Contaminants OIL TAG P. Lipids FFA Trans FA Sterols tocopherol Pr. Ox Waxes Pigments Metals Contaminants Moyenne 0.8 Results BRUTE 85 -89% 0,1 -1,5% 0,5 -5% < 0.1% 0 -2% (soja) 0,15% Variable  100 mg/kg  10 mg/kg  1 mg/kg  10 mg/t RAW Objectives :  stability  technological, organoleptic and nutritionnal properties Minimum Maximum 0.3 1.9 RAFFINEE 98 -99% < 50 mg/kg < 0,1% 0.3 -1.9% < 1% 0,1% Variable < 5 mg/kg < 0,02 mg/kg  1 mg/t  1 mg/t REFINED Physical Levers : Kinetics control of cooling (size and nature of fat cristals) Fractionation (increase in FA with high or low melting points) Chemical Levers Hydrogenation (melting profile modif. [nature of FA] +  stability) Interesterification (modif. Of melting profile [position of FA]) Enzymatic levers Interesterification => structuration of TAG glycerolysis => emulsifying power Authorized treatments (arrêté du 12/02/73) FAT Controlled cooling HIGH melting point Fraction Melting separation Composition Equipments : Cooling system Parameters : Cooling speed overcooling. Agitation speed Cristallisation time 24 25 temperature decanting centrifugation filtration (retentate) Post raffinage 36 LOW melting point Fraction 28 -Continuous Filtration -Vapor Stearin Olein Inlet Vacuum Recycling pump stearin cake Recycling Aspiration Olein (permeate) press vapor Stearin Inlet (partially cristallized fat) Press Filter Stearin cake -Press Filter -Stéarine (20%) Oléine (80%) PPP 30% 0% PPO, POP 26% 51% OOP, OPO 44% 44% OOO 0% 5% Composition moyenne Trisaturés (PPP) PALM  CH = CH  + H 2   CH 2  CH 2  + catalysts [Ni, Cr, Cu, Mn] Huiles neutres sèches Huiles brutes Raffinage TRANS FA Catalyseur neuf (Ni, Cu) • Negative health effects of industrial trans: effect on 6% Disaturés monoinsaturés (PPO, POP) 50% Monosaturés diinsaturés (POO, OPO) 40% Triinsaturés (OOO) 4% Cristallisation (28°) Filtration Oléine Palme Stéarine Indice d'iode 56/58 50/55 32/36 Pt fusion 19/21 36/38 50/55 %S à 15° 18/22 38/42 76/82 %S à 20° 5/7 28/32 67/73 %S à 25° 2 23/27 58/62 plasmatic lipoproteines and prostaglandines - melting point - stability (rapeseed -soya) TOTAL or PARTIAL Hydrogenation, selective or not: selectivity = f([catalysts], temperature : k 3 /k 2 ; k 2 /k 1 ) k 3 k 2 k 1 C18:3 C18:2 C18:1 C18:0 (linolenic) (linoleic) (oleic) (stearic)  Apparition of trans forms (15 -40% depending on conditions) ex: elaïdic acid (trans-Δ⁹ 18:1)  Apparition position isomers ( 40%), conjugaison ( 2%) Filtration H 2 Paramètres : Température Pression Agitation Catalyseur (%, type, activité) Huiles hydrogénées brutes Catalyseur usagé Recyclage REACTEUR Hydrogenation degree Total Partial Elevated T° Used catalyst AG Trans Teneur Mini (% AG Totaux) Teneur Maxi synthesis S I (% AG Totaux) Pain de mie 3.7 Sandwich bread • Compulsory labelling of trans FA S + I 21.2 Viennoiserie 24.5 34.8 S I Pastry 50% solid 50% liquid trans Pâtes feuilletés, pizza 16.6 61 Puff pastry, pizza S S S I I I AG Low T° New Catalyst Soupes deshydratées 4.3 27 Viande bovine 1.0 2.8 agneau 3.6 Dehydrated soups Bovine meat Lamb S I S I S I Increase / optimizing of fat processing S S I S I I • New definition of process parameters (desodorisation, 12.5% 12.5% 25% 25% 12.5% 12.5% desacidification) 5.4 Beurre 4 11 Lait (vache/chèvre/brebis) 1.8 5.6 -lower temperature, shorter time, intense vacuum Butter  Modification of melting profile Milk (cow/goat/ewe) • Alternatives to partial hydrogenation :  Non directed : T > Tmelting of FA  Directed : T intermediate

- Cristallisation of high melting point TAG (displacement of equilibriums)

Few oils monographies

FEW CONCLUSIONS

2 series or PUFA very important: n-6 serie (or omega 6) and n-3 serie (or omega 3) with first double bond located respectively at 6 or 3 carbons from the methul extremity of the molecule. Precursor of omega 6 and omega 3 series are linoleic acid (LA, 18:2 n-6) and alpha-linolenic acid (ALA, 18:3 n-3). These two acids are said « essential » because they can not be synthesized by animal organism and must be brought by diet.

FA Profile very specific and determine with FA position on TAG => oil properties Chemical and enzymatic process help refig oil and modulated their functionnal properties

Development of enzymatic method for biomodifications

Complex socio economical context: competition for ressources (biofuels), high pressure on agricultural lands linked to emergents markets and increasing demand of ois, complexity of some supply chain (palm), strong image of lipids/fat in collective conscience and complex reltionship with health.


F Ould-Kaddour

D Levesque

Diffusion of nanoparticles in dense fluids

Keywords: numbers: 05, 10, -a, 61, 25, -f

The diffusion process of a single spherical nanoparticle immersed in a fluid solvent is studied by molecular dynamics simulations. When the nanoparticle mass stays constant, it is shown that, at short times, the decay of the nanoparticle velocity autocorrelation function is strongly modified when the particle diameter increases. It is also shown that, at large times, the characteristic algebraic decay induced by the hydrodynamic correlations between the solvated particle and the solvent presents a scaling behavior depending on the particle diameter.

INTRODUCTION

The determination of transport properties of particles with a nanometric size immersed in a solvent is of large interest for the present researches in the domain of nanotechnologies [START_REF] Hamley | Introduction to Soft Matter[END_REF] .

When the nanoparticles have a diameter larger than 100 nm and, hence, a mass larger by several orders of magnitude than that of the solvent particles, they can be considered in practical applications as brownian particles [START_REF] Cukier | [END_REF] . However when the size and mass of nanoparticles differ from those of the solvent particles only by a factor ∼ 10, the transport properties of such particles could differ from those expected for brownian particles. Examples of this type of nanoparticles are the fullerenes, the carbon nanotubes of short length, ... etc ... . Numerous theoretical works have been published in the literature on this subject by using molecular dynamics simulations. Many of these studies [3][4][5][6][7][8][9] have been devoted to determine the size and mass of solvated particles at which, in the low concentration limit, the diffusion coefficient D is well estimated by the Stokes-Einstein relation D = k B T /(α h πηR) where k B , T, η and R are the Boltzmann constant, the solvent temperature, the solvent viscosity and the radius of the solvated particle, respectively. α h is a numerical coefficient determined by the choice of the hydrodynamic limit condition at the interface between the fluid solvent and the solvated particle. An unambiguous conclusion on this point is not easy to achieve, because the Stokes-Einstein relation derives from the Einstein relation D = k B T /ξ, where ξ, the friction coefficient, is well defined only in the brownian limit as the integration of the time autocorrelation function of the force acting on the brownian particle 6,10,11 . Then, the use of the Stokes-Einstein relation a priori should suppose that two conditions are fulfilled : brownian limit and validity of a hydrodynamic estimate of ξ 2,12 .

Briefly summarized, the conclusions of these works are that the Stokes-Einstein relation can give a qualitatively acceptable estimate of the diffusion coefficient even if the two conditions are not satisfied. But when a quantitative estimate is required, α h must be considered as a free parameter and, for instance, adjusted between the values of 4 (slip boundary condition) and 6 (stick boundary condition). Such an adjustment of α h values is obviously needed to take into account the approximate character of the Stokes-Einstein and Einstein relations when the size and mass of the tracer particles are insufficiently large with respect to those of the solvent particles.

In order to investigate the specific case where the mass and size ratios between solvated and solvent particles are smaller than 100, we will consider a model in which the mass ratio m t /m s is equal to 60 (m t and m s : mass of the solvated and solvent particles, respectively) and the size ratio varies between 1 and 17. Such a model where the mass m t of solvated particles is kept constant while their size varies, is chosen in order to determine the qualitative changes on the nanoparticle diffusion only induced by the increase of the nanoparticle diameter. We study the case of the low concentration limit of the solvated nanoparticles, i.e. concentrations smaller than 0.5 10 -4 . Our aim is to obtain by molecular dynamics (MD) simulations at constant energy (microcanonical ensemble) a detailed description of the diffusion process, in particular, as mentioned above, how this process varies with the size of the solvated particle, through the computation of the velocity autocorrelation function (VAF)

c(t), c(t) = 1 t m -t tm-t 0 dτ v(τ ).v(τ + t) = c(0) z(t) = 3k B T m t z(t) , (1)
where v(t) is the nanoparticle velocity, z(t) the normalized VAF and t m the total integration time of the motion equations in a simulation run.

In Sec. II, the studied system and simulation procedure are described and the simulations data are presented. Sec. III is devoted to the analysis of the results and the discussion of proposed corrections to take into account the finite size effects inherent to simulation data.

In the last section, the conclusions of the analysis will be summarized with a special mention of the scaling behavior of the VAF long-time tail with the solvated particle diameter.

II. SYSTEMS AND SIMULATIONS

Similarly to models used in our previous works 9,10 or works published in the literature, the studied system is composed of N solvent particles and one solvated particle. The solvent particles and, also the solvated particle with the solvent particles, interact by a truncated soft repulsive Lennard-Jones (LJ) pair potential :

v(r ij ) = v LJ (r ij ) + ǫ = 4ǫ[( σ α β r ij ) 12 -( σ α β r ij ) 6 ] + ǫ for r ij ≤ 2 1 6 σ α β = 0 for r ij > 2 1 6 σ α β , α, β = 0 or 1 , (2)
where r ij is the distance between solvent or tracer particles i and j. σ 1 1 is the LJ size parameter of the solvent particles, σ 0 0 that of the solvated particle and, for the cross LJ pair potential, σ 0 1 is given by σ 0 1 = 0.5(σ 1 1 + σ 0 0 ). The choice of these spherical, repulsive and short ranged LJ potentials is suitable for the main purpose of our study (cf. Introduction).

When σ 00 , defining the size of the solvated particle varies the solvent thermodynamic state and m t staying identical, the modifications of the solvated particle diffusion clearly depend unambiguously on this only parameter. σ 1 1 and ǫ being chosen as the units of length and energy, the time unit τ 0 is m s σ 2 1 1 /ǫ. The computation of the asymptotic behavior of the tracer VAF requires to perform the simulations with systems large enough to allow the existence of a time domain where this behavior is not affected by the coupling between the hydrodynamic diffusive and sound modes, resulting from the periodic boundary conditions of the simulation cell [START_REF] Erpenbeck | [END_REF] . In addition, the system size having to be sufficient to accomodate a large solvated particle, the simulations are realized for N = 55296 when σ 00 is equal to 1, 4 and 7 and N = 87808 when σ 00 is equal to 11 and 17. The solvent density in reduced units is ρ s σ 3 11 = 0.2, so that the sides L c /σ 11 of the simulation cubic cells are equal to 65.15 (N = 55296) or 76.13 (N = 87808). With these L c values, at a temperature T * = k B T /ǫ = 2.01 where the sound velocity c s is equal to 2.68 14 , it is expected that the VAF asymptotic behavior can be computed until t c = L c /c s equal to 24.3τ 0 and 28.6τ 0 for the systems with N = 55296 and N = 87808, respectively.

It is probably more realistic to take into account the size of the solvated particle and to compute t c from t c = (L c -σ 00 )/c s , giving t c ≃ 21.0 τ 0 and ≃ 22.0 τ 0 for the small (σ 00 = 4 and 7) and large (σ 00 = 11 and 17) sizes of the tracer particle.

The computation of the VAF of one isolated particle in a solvent needs very extensive simulations, peculiarly when an accuracy of ∼ 10% is required on the values of the VAF asymptotic behavior which is expected to vary with t as α s t -3/2 15, 16 . In order to achieve such an accuracy, 67 runs of 10 5 integration time steps (∆t = 0.005τ 0 ) have been realized for computing the nanoparticle VAF for σ 00 = 1, 1020 runs of 10 5 ∆t for σ 00 = 4, 1790 runs of 50 ×10 3 ∆t for σ 00 = 7, 2900 runs of 50 ×10 3 ∆t for σ 00 = 11 and 2050 runs of 50 ×10 3 ∆t for σ 00 = 17. c(t) was computed up to 30.0τ 0 in order to determine the time domain where its long-time behavior becomes proportional to t -3/2 . The statistical error on the VAF was obtained by calculating a standard error from the estimates of c(t) computed after each period of 3000 time steps during the MD runs.

The results of these simulations are presented in Fig. 1 in the time domain where the function z(t) = c(t)/c(0) is expected to be without bias induced by the coupling with the hydrodynamic sound modes. For t/τ 0 < 2.0, the estimated statistical error is about 1-2% for all particles diameters but it increases from 1-2% up to 10-15% at t/τ 0 > 5.0 when σ 00 varies from 1 to 17.

III. ANALYSIS AND DISCUSSIONS

At short times, defined as t/τ 0 < 5.0, z(t) varies from an exponential or quasi-exponential decrease for σ 00 = 1, to a more complex variation involving two disctinct rates of decrease, clearly visible at σ 00 = 11, and, finally, to an oscillatory behavior at σ 00 = 17 (cf. Fig. 1).

For σ 00 = 1, within the statistical error, a simple exponential c exp(-α z t) gives an excellent curve fitting of z(t) on the time domain from 0.2 to 5.0 with α z = 0.030, (cf. Fig. 2). This exponential decay continues up to t = 22.0τ 0 , but differs from that expected if the diffusion of the particle was of brownian type satisfying to the Stokes-Einstein relation. In this case, α z would be given by α h πm s ρ s νR/m t 17 , with ν = η/m s ρ s and m t the mass of the solvated particle, and would be equal to 0.035 (α h = 4) or 0.053 (α h = 6), ν being equal to 1.71 in reduced units 14 . These quantitative differences are typical of those found in the test of the validity of the Stokes-Einstein relation (cf. above), if it is supposed that c(t) keeps for t larger than t = 22.0τ 0 the exponential behavior determined from its short-time values for t/τ 0 < 5.

When the solvated particle has a diameter σ 00 = 4, 7 or 11, a fit of z(t) by a single exponential in the time domain 0 < t/τ 0 < 5.0 is not possible within the estimated statistical errors. Fits realized with a linear combination of two exponentials allow to show that the fast decrease for t/τ 0 < 2.0, is followed by a more slow decrease 18 . But in contrast with the result obtained for σ 00 = 1 with one exponential, the values of the parameters are very sensitive to the upper bound of the time interval chosen to realize the fits so that the identification of two well characterized regimes of exponential decrease in the range 0 < t/τ 0 < 10 is precluded. A fortiori, a similar result is obtained at σ 00 = 17, where z(t) presents an oscillatory behavior, indicating an effect of backscattering on the solvated particle due to the solvent, followed by a slow monotonic decrease. From the previous discussion, it appears that, at short times, the diffusion process differs strongly with the σ 00 values. In this time range, z(t) goes from an exponential decrease similar to that of brownian particle to a damped oscillatory decrease similar to that obtained for particles in a dense fluid.

For the time domain (12 < t/τ 0 < 18) where the sound mode should be without influence on the diffusion process and excluding the case σ 00 = 1 where, for these t values, the z(t)

decrease stays exponential, it is seen in Fig. 3 that z(t) is fitted within the statistical error by the expected analytic form α s t -3/2 . The fits are very accurate for σ 00 = 4, 7 and 11, for σ 00 = 17 the fit stays acceptable, but the MD data are affected by an important statistical noise. The fits, realized with a two-parameter form α s t -a 0 , give values of a 0 close of 3/2 :

1.48, 1.52 and 1.58 for σ 00 equal to 4, 7 and 11, respectively, while the α s values differ by 10-15% from the values obtained when a 0 is equal to 3/2. For σ 00 = 17, the large statistical errors make the variations on α s and a 0 much larger, i.e. of the order of 30%.

The coefficient α s of the VAF long-time tail of tagged particles in a solvent, is expected to write in the low concentration limit 19

α s = 2 3(ρ t + ρ s m s /m t )(4π(D 0 t + ν)) 3/2 (3)
where ρ t is the density of the solvated particles such as ρ t ρ s ≃ 0 and D 0 t their diffusion coefficient, estimated in excluding the long-time tail contribution δD t to the time integral of z(t) defining the full diffusion coefficient :

D t = k B T ∞ 0 dt z(t)/m t 13 . This contribution is of the order of δD t = k B T α s /(2 m t t 1/2 c
). Since in our simulations ρ t < 10 -4 , α s is given by

α s = 2 m t 3ρ s m s (4π(D 0 t + ν)) 3/2 . (4)
From this relation, it is seen that α s depends on the solvated particle diameter only through D 0 t . The D 0 t values are, in reduced units, 0.22, 0.112, 0.060 and 0.032 for σ 00 = 4, 7, 11 and 17, respectively. Since ν = 1.71, the α s values are weakly depending on D 0 t and, so, on σ 00 . They are equal to 1.68, 1.83, 1.91 and 1.95 ; these values must be compared to the estimates α f s of α s , obtained from the fits of z(t) (cf. above and Fig. 3) on the time domain 12-18 τ 0 , equal to 8.0 ± 0.2, 3.0 ± 0.3, 1.7 ± 0.3 and 0.9 ± 0.4.

The large discrepancy between the α s and α f s values does not seem to result from a biased estimate of D t due to finite size effects inherent to simulation data. The finite size effects affecting the D t values have been well studied in the literature 3,20,21 . From these works, it was concluded that a realistic estimate of the difference between the diffusion coefficient D N t for a system of N solvent particles and its value D ∞ t in the infinite system limit is given by

D ∞ t = D N t + k B T ξ c 6πm s ρ s νL , (5)
where ξ c is a constant equal to ∼ 2.84. This finite size correction is positive, independent of the solvated particle diameter and for the considered systems in our simulations has the typical value 0.005 in reduced units. So, the finite size corrections to the D t values computed by simulation cannot explain the difference between the two sets of α s estimates.

In order to overcome the discrepancy between the estimates α s and α f s , we suppose that α f s scales inversely proportionaly to the nanoparticle diameter and then, that the appropriate time scale τ n associated to the VAF long-time behavior of nanoparticles is not τ 0 but is depending on the the solvated particle diameter and has the form τ n = σ 00 τ 0 /(c α σ 11 ), c α being constant for a given thermodynamic state of the solvent. With this hypothesis, the long-time tail of the nanoparticle VAF writes α f s /t 3/2 = α s /(τ n t/τ 0 ) 3/2 . This relation is satisfied in taking into account the estimated errors on the values of α f s and α s for c α = 10.5 ± 1.0. Fig. 4 shows that, at large times in agreement with the previous hypothesis, the VAF of nanoparticles of diameter σ 00 = 4, 7 and 17 collapse within the statistical errors on the VAF of the nanoparticle with the diameter σ r 00 = 11, when time is scaled proportionally to σ 00 /σ r 00 .

IV. CONCLUSIONS

The computation by MD simulations of the nanoparticle VAF demonstrates that this latter exhibits at short times a decrease which varies qualitatively when the size ratio between the nanoparticle and solvent particles increases. In addition, at large times the expected algebraic decrease proportional to t -3/2 seems to be characterized by a time scale depending on the particle diameter. This last conjecture is reasonably verified by our MD data but, obviously depends on the reliability of our MD estimates of the asymptotic behavior of the nanoparticle VAF which presents clearly noticeable statistical errors as it is seen in Fig. 4.

Figure captions

Figure 1 .

 1 Figure 1. Normalized VAF of a solvated particle with m t /m s = 60 and diameter : σ 00 = 1, (solid line and filled circle), 4 (solid line and filled square), 7 (solid line and filled diamond), 11 (solid line and filled triangle up) and 17 (solid line and filled triangle down). The statistical error is of the order of the symbol size.

Figure 2 .

 2 Figure 2. Fit of z(t) for σ 00 = 1 by an exponential. MD data : filled circle with error bars, fit : dashed line.

Figure 3 .

 3 Figure 3. From left to right and top to bottom, fits of z(t) for σ 00 = 4, 7, 11, and 17 for the t/τ 0 values between 12 and 18. MD data : filled circle with error bars. Fits of the MD data with α/t -3/2 : solid line and with α/t -a 0 : dashed line.

Figure 4 .

 4 Figure 4. Collapse of functions z(t) in the time domain 10τ 0 < t < 18τ 0 onto z(t) for σ 00 = 11 : solid and filled square σ 00 = 4, solid line and filled diamond σ 00 = 7, solid line and triangle up σ 00 = 11 solid line triangle down σ 00 = 17. Top : unscaled functions z(t), bottom : scaled functions z(t). The typical statistical error on the z(t) values in this time domain is ±0.003.


B Lymphocytes Plasmocytes

Immune memory

Antigen « clearance »

Systemic inflammatory response

What means a protective immune system ? .036

Conclusion (3)

 AA may be used for their physiological role

• Antiinflammatory and antioxidant • To limit the negative consequences of inflammation  May require AA be supplied far above current nutritional recommandations • Safety issue : side effects? toxicity?

• Economic issue • Regulation issue : health allegation, drugs or nutrients?

LE

  Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017 Common response to many diseases (infectious or not), stressful events, management … BRAIN .010 Amino Acid Academy, Paris, September 28-29, 2017

 017 LELE•LE

 017 Val deficiency (4 vs 15 g/kg) upregulated the expression of gene coding for inflammatory response (TNF, IL-8 and NFkB) while downregulated antiinflammatory response (IL-10) in the gut in carps  Thr deficiency (70% of the Control) in primiparous sows reduced plasma Gut explants from birds fed a Thr deficient diet had no response (mucin, IgA and IL-8 mRNA) to ex vivo LPS treatment Amino Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017 Zhang et al 2017 Le Floc'h et al 2008  Pigs fed a moderate Trp deficient diet had higher inflammatory response (haptoglobin, fever)  Pigs fed a moderate Thr deficient diet had lower serum specific anti BSA and swine fever Ig G component of glycoproteins : mucins and immunoglobulins Mucins  420 % Fogg et al. 1997  Thr confers specific properties to these proteins : posttraductional glycosylation Thr/Lys : Immunoglobulins 150 % Basset et al. 1965 Le Floc'h et al 2014  Postprandial plasma [Thr] are lower in co infected pigs (Mh+H 1 N 1 ) Plasma total Ig G content 8-8.3 g/L 2.8 g/L µM Amino Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017 Carcass  54 % Bikker et al. 1997  .Threonine supply above recommendations Mao et al 2014 Trevisi et al 2015 Threonine supplementation enhances immunoglobulins  total IgG and  inflammatory response (sera cytokine concentrations, tissue expression of TLR) induced by pseudorabies vaccination, but depressed FCR  IgM in ETEC challenged pigs susceptible to ETEC Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017 Dietary Gln supplementation preserves lymphocyte proliferation capacity in infected pigs Piglets weaned at 21d, fed a diet supplemented with 4% of Gln, inoculated with E coli at 26 d  Gln supplementation restored lymphocyte proliferation capacity in infected pigs  but did not modify growth rate and hyperthermia Gln dietary supplementation (1% of the diet) during 3 wks resulted in higher intestinal Ig A and blood IgG (+ better growth rate) but 4% of Gln did not Bartell & Batal 2007 With contrasted results in broilers  Gln+Glu dietary supplementation (0,5% of the diet) during 3 or 6 wks had no beneficial effect on growth performance, intestinal morphology, and inflammatory response of broiler chickens raised under hot and humid tropical environment Shakeri et al 2014 Amino Acid Academy, Paris, September 28-29, 2017 80% of recommended daily feed intake L-Cys 60% of recommended daily feed intake  less severe diarheas .023 Amino Acid Academy, Paris, September 28-29, 2017 Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017 The question of the nutritional cost of immunity 2 ways to get and provide energy and nutrients for immune functions acquisition (= feed intake) allocation (= metabolism) Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017The question of the nutritional cost of immunity• If the cost of IS is small compared to the other functions  the animal could increase nutrient acquisition or/and change nutrient allocation towards immune functions• If the cost of IS is (very) high compared to other functions the animal won't be able to maintain its immune functions no growth restoration with  Trp• greater response of growth to additional TrpIn pigs suffering from inflammation :.032Amino Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017 Do dietary AA (as exogenous supply) may help to support immune system in livestock species? But the question should be … Do dietary AA (as exogenous supply) mays help to support HEALTH in livestock species? .033 Arg supplementation (up to 0.8%) in a milk based diet enhanced spleen weigh, blood granulocytes and IgG and IL-8 in piglets Amino Acid Academy, Paris, September 28-29, 2017 The nutritional cost of maintaining the immune system is probably not so high (# AA)  BUT « basal »immune functions are affected by AA deficiency Amino Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017  Does it really impact on health?  Evidences showing that immune capacities compromised by AA deficiency may affect health are still scarce in livestock The metabolic effort for mounting an immune response is high +++ for inflammatory response  Not all but some AA support immune functions and limit the negative effect on performance  Two major limits for efficacy of nutritional adjusments reduced feed intake catabolic state associated with inflammation Amino Acid Academy, Paris, September 28-29, 2017 LE FLOC'H/ Paris 2017

integrity Less harmful as possible cooperation efficacy efficacy .012

Amino Acid Academy, Paris, September 28-29,

2017 LE FLOC'H/ Paris 2017 Outline A brief introduction of immune system AA dietary supplies and immune system maintenance and functioning Does maintening a protective immune system require nutritional adjustments? .013

Amino Acid Academy, Paris, September 28-29,

2017 LE FLOC'H/ Paris 2017 Which AA and for what purposes ?

	 AA as contituent of immune proteins  BCAA deficiency (50% of the Control) reduced lymphoid organ
	Thr, Val weights (spleen, BF, thymus) in broilers Immunoglobulins, Acute phase proteins
	Trp, Phe
	 AA as nutrients for immune cells
	Energy, cell proliferation	Ala, Gln
	 AA as bioactive molecules (or precursor)
	Cytotoxic and antioxidant compounds	Arg, Cys, Trp
		.014

Amino Acid Academy, Paris, September

[28][29] 2017


K Eversole

Marc Buée

Corinne Vacher

Christophe Mougel

] 2 Leaders from our PhytoMic network

Muriel Vayssier Animal Sc Div.

@gr_pathobiome 2 international meetings 2015, march 2018

•oü•ü

  Agriculture : production and environment o Soil, plants, trees microbiomes for production, health & mitigation of climate change o Animals microbiomes for production, health and decrease of antimicrobialuse and greenhouse gaz o Depollution, recycling, improved sustainability • Food chain: safety and sustainability o Food quality, preservation and safety o Sustainability, waste reduction and conversion • Human: health o Health & disease (chronic non transmissible and infectious ones) o Nutrition & preservation of health Provide services linked to agriculture, environment, nutrition and health 2005 Technological breakthrough: New generation sequencing The Human microbiome & INRA 2005 Paris meeting (INRA sponsored): C. Fraser, E. Rubin, J. Weissenbach, J. Doré, S. D. Ehrlich 2007 Rockville meeting (co-sponsored by NIH & EU) => creation of IHMC 2007-2008 NIH Human Microbiome Project-NIH Jump start ; EU MetaHIT project 2008: Data analysis & coordination center (HMP) 2009: Canadian Human Microbiome Initiative (CIHR); Australian Jumpstart Human Microbiome Project 2010: Korean Microbiome Diversity using Korean Twin Cohort (NRFK) 2011: International Human Microbiome Standards (EU) … "Participants agreed that a consortium should be formed with membership to include funding agencies and Principal Investigators of projects that have an interest in the comprehensive assessment of the human microbiome and its impact on health and disease." => share with other studied biotopes issues -International Microbial Ecosystems and Meta-omics (MEM) • A multidisciplinary program built on the strength in microbiology and involving mathematics • To understand functioning of the microbial ecosystems of agronomic interest, from soils to humans, using meta-omics • And to optimize their services through prediction and engineering International SAB MEM governance & priorities 1. Create an interdisciplinary scientific community sharing thoughts, knowledge, resources and working on projects based on both biology & mathematics; 2. Develop common & accessible pipelines & analytic methods (for biology & math); 3. Go gradually beyond descriptive approaches (who is there) toward functional understanding (what do they do, which interactions within & with the environment), modeling, engineering to optimize the ecosystems' services; 4. Encourage and support integrated INRA projects; 5. Enhance visibility and international positioning of INRA in these fields of research. MEM steering committee Thematic groups • MEM budget is based on o Permanent staff salaries (main budget, often forgotten) o Functioning: 1M€ to 700 000 € /year o 2 cofunded PhD fellowships / year (covering 50% of the PhD salary) o Recommendation for permanent positions MEM budget and means Projects : Calls, Key actions, integrated projects (incubated by MEM) o Meetings & think-tanks, conferences o Training o Visits or short stays abroad (started 2017) o Management => Examples of achievements… • Involves o 70 laboratories /teams from 11 INRA research divisions o ~135 scientists annual RCAM workshop 1. Enable easy access to sequencing facilities: SOPs, advices & low cost (20 €/sample) 2. Development of an analysis pipeline in a biologist friendly-environment o Benchmarking of bioinformatics tools for metabarcoding o Pipeline development in a Galaxy environment: FROGS* o Training sessions from raw reads to (basic) statistical analyses and result interpretation. More than 12 3-days sessions of 10-12 persons. 3. Expand the choice of microbial barcodes : understudied phyla and development of functional markers => ongoing project Example 1, organize & ease metabarcoding * Escudié et al. (2018) Bioinformatics --frogs.toulouse.inra.fr Example 1, barcodes for understudied species in Agri-systems IAM unit (Nancy): Dikarya and Oomycota ü IRHS units (Angers): phytopathogens ü CARRTEL unit (Thonon): eukaryotic microplankton ü BioGer Unit, (Versailles): Fusarium strains ü IGEPP (Rennes), LEM (Lyon), Agroecologie (Dijon): bacteria ü Agroecology (Dijon): Glomeromycotina ü BIOGECO(Bordeaux): leaf yeasts ü MaIAGE unit (Jouy): bioinformatics ü GetPlaGe (Toulouse): sequencing platform Mock communities (10 to 12 barcodes and associated primer pairs tested) • about 250 strains for Fungi/Oomycota (genomic DNA) • 54 bacterial strains (gDNA) • 38 gDNA of EuK plankton Extension to food systems : 10 additional laboratories involved Example 2, boosting metagenomic studies q Animals; all but one with international consortia þ Humans: MetaHIT, Chinese and HMP studies Latent Block Model for Overdispersed Count Data with Application in Microbial Ecology. Aubert, Schbath and Robin. Under revision for JRSS Ü a biclustering model-based method allowing to study the interaction between the structure of microorganism communities and environnemental samples from an abundance matrix. Ü cobiclust R package available at https://github.com/julieaubert/cobiclust and on CRAN • Variational inference for probabilistic Poisson PCA. Chiquet, Mariadassou and Robin Ann. Appl. Stat., 2018. Ü a probabilistic PCA adapted to multivariate Poisson-log normal count data and allowing to account for covariates and offsets. Ü PLNModels R package available at https://github.com/jchiquet/PLNmodels Example 4, Use of text-mining Extraction of information from publications thanks to knowledge modelling, ontologies and text-mining approaches : • Microbes • Habitat • Phenotype Ü Ontology : http://agroportal.lirmm.fr/ontologies/ONTOBIOTOPE Ü Florilege DB and web application http://migale.jouy.inra.fr/Florilege ○ Taxon ↔ Habitat : 820 000 relations ○ Taxon ↔ Phenotype : 86 000 relations ○ Direct links with external public DB (PubMed, DSMZ, GenBank ...) Chaix, Deléger, Bossy & Nédellec (2018). Text mining tools for extracting information about microbial biodiversity in food. Food Microbiology. Changes mind and work practices (Maths:Bio; 75% MEM project with international partners) ü Increased % of INRA publications on MEM topics, more collaborative publications, 68% in journals of exceptional & excellent reputations ü 28 patents, 5 start-ups • Assessment of INRA's metaprograms Feb 2018 • 2018: institutional reflexion to launch new metaprograms à from MEM to « Holobiont, the host and its microbiota » • No national strategic agenda on Microbiomes … European Commission Food security, sustainable agriculture and forestry, marine, maritime and inland water research and the bioeconomy • International Bioeconomy Forum (launched on Nov 2017) Flexible multilateral platform whereby European and global R&I partners would gather to discuss and act on common challenges in the bioeconomy, such as the microbiome… the IBF will be used as a platform to share ideas and experiences on bioeconomy policies, strategies and actions, fostering collaboration and joint activities that will promote innovation in key sectors. Ü Feb 2018: submission of Coordination Support Action projects ó Microbiome working group "Towards a coordinated microbiome R&I activities in the food system to support (EU and) international bioeconomy goals" Conclusion, a time of opportunities þ INRA's metaprogramm on microbial ecosystems -Create an internal scientific dynamic and …. -… foster a pluri-disciplinary community -Will shift to the more focus holobiont concept for next generation of MP þ European Commission level -International Bioeconomy Forum / WG microbiome / Microbiome Support o Common strategic agenda o Work on standards o Recommandations for future actions þ European & international initiatives -EPSO & International phytobiomes Alliance -ERA-Net INTIMIC : Diet-microbiota-health => 11 projects, knowledge PF Example 4, Pathobiome concept 2013 Think tank => multidiscipline to address animal and plant health taking into account the biotic environment of pathogens (pathologists, infectiologists, microbial ecologists, mathematics, etc).

Microbiome Support

Ü Exchange knowledge across the scientific and political community and ensure an efficient use of the available resources Ü Improve coherence between national and EU microbiome research and facilitate alignment of international research agendas Ü Establish international agreed microbiome definition, best pratices and standards Ü Improve the international cooperation, creating the basis for joint international partnerships