Roberto Gómez-Villarejo

Teresa Aguilar

Samah Hamze

Patrice Estellé

Javier Navas
email: javier.navas@uca.es

Experimental analysis of water-based nanofluids using boron nitride nanotubes with improved thermal properties

Keywords: Heat transfer, Nanofluids, Boron nitride nanotubes, Thermal conductivity, rheological properties

Nowadays, the use of nanofluids as alternative to commonly-used industrial heat transfer fluids is a topic of increasing interest. Analysing the improved efficiency of heat transfer processes according to advanced nanomaterials and obtaining stable nanofluids is one of the most interesting challenges. This paper presents a study of nanofluids based on boron nitride nanotubes and using an aqueous solution of Triton X-100 (which acts as a surfactant) as the base fluid. UV-vis spectroscopy, particle size measurements (size between 150-170 nm) and  potential (at about -25 mV) showed that stable nanofluids were obtained. Surface tension measurements were also performed. The surface tension of water was weakly affected by the presence of any amount of nanoparticles and was mainly governed by the presence of surfactant. The rheological properties of the fluids were also analysed, as were their isobaric specific heat and thermal conductivity values. A Newtonian behaviour was observed for the base fluid and the nanofluids, with no significant increase in viscosity. The isobaric specific heat increased by 8% and thermal conductivity by 10 % compared with the base fluid.

Thus, the results obtained are interesting because while thermal properties improved with nanoparticle content, rheological behaviour did not change. Consequently, the nanofluids studied in the current paper do not raise the pressure drop and pumping power significantly and may therefore be a good option for thermal system applications.

Introduction

Nanofluids are systems based on nano-sized materials suspended in a fluid [START_REF] Choi | Enhancing thermal conductivity of fluids with nanoparticles[END_REF]. They have been the subject of numerous scientific studies in recent years in the form of experiments, theoretical developments and numerical simulations [START_REF] Mahian | Recent Advances in Modeling and Simulation of Nanofluid Flows-Part I: Fundamental and Theory[END_REF][START_REF] Mahian | Recent Advances in Modeling and Simulation of Nanofluid Flows-Part II: Applications[END_REF]. Such a great effort is a result of nanofluids possessing enhanced properties that are of interest for applications such as engine cooling [START_REF] Sidik | A review on the application of nanofluids in vehicle engine cooling system[END_REF], electronic device cooling [START_REF] Kadri | A vertical magneto-convection in square cavity containing a al2o3+water nanofluid: cooling of electronic compounds[END_REF], concentrating solar energy [START_REF] Yasinskiy | Dramatically enhanced thermal properties for TiO2-based nanofluids for being used as heat transfer fluids in concentrating solar power plants[END_REF], nuclear reactors [START_REF] Wu | A review of nanofluid heat transfer and critical heat flux enhancement-Research gap to engineering application[END_REF], high voltage transformers [START_REF] Fal | Nanofluids in the Service of High Voltage Transformers: Breakdown Properties of Transformer Oils with Nanoparticles, a Review[END_REF], etc. The most interesting properties are their high isobaric specific heat [START_REF] Shin | Enhanced Specific Heat Capacity of Nanomaterials Synthesized by Dispersing Silica Nanoparticles in Eutectic Mixtures[END_REF] and thermal conductivity [START_REF] Choi | Enhancing thermal conductivity of fluids with nanoparticles[END_REF] values.

Furthermore, the analysis of their rheological properties is of great interest in many applications involving fluid flow. For example, Heris et al. [START_REF] Heris | Rheological Behavior of Zinc-Oxide Nanolubricants[END_REF] reported the rheological behaviour of ZnO-based nanofluids as lubricants, and also Yiamsawas et al. [START_REF] Yiamsawas | Measurement and Correlation of the Viscosity of Water-Based Al2O3 and TiO2 Nanofluids in High Temperatures and Comparisons with Literature Reports[END_REF] reported the analysis of nanofluids based on Al 2 O 3 and TiO 2 for high temperature applications. Thus, numerous studies in recent decades have analysed the enhancement of the thermal properties of the typical heat transfer fluids used, such as water [START_REF] Gao | Measurement and modeling of thermal conductivity of graphene nanoplatelet water and ethylene glycol base nanofluids[END_REF][START_REF] Ilhan | Experimental characterization of laminar forced convection of hBN-water nanofluid in circular pipe[END_REF], ethylene glycol [START_REF] Gao | Measurement and modeling of thermal conductivity of graphene nanoplatelet water and ethylene glycol base nanofluids[END_REF][START_REF] Zyla | Huge thermal conductivity enhancement in boron nitride -ethylene glycol nanofluids[END_REF] or a mixture of both [START_REF] Mahian | Dispersion of ZnO Nanoparticles in a Mixture of Ethylene Glycol-Water, Exploration of Temperature-Dependent Density, and Sensitivity Analysis[END_REF]. For example, Gao et al. [START_REF] Gao | Measurement and modeling of thermal conductivity of graphene nanoplatelet water and ethylene glycol base nanofluids[END_REF] reported increases in thermal conductivity of up to 4.6%, 18%, and 6.8% using graphene nanoplatelets in ethylene glycol, a 1:1 mixture of deionized water and ethylene glycol and deionized water, respectively. In addition, metal oxide [START_REF] Yasinskiy | Dramatically enhanced thermal properties for TiO2-based nanofluids for being used as heat transfer fluids in concentrating solar power plants[END_REF][START_REF] Yiamsawas | Measurement and Correlation of the Viscosity of Water-Based Al2O3 and TiO2 Nanofluids in High Temperatures and Comparisons with Literature Reports[END_REF][START_REF] Angayarkanni | Review on thermal properties of nanofluids: Recent developments[END_REF][START_REF] Lee | Measuring thermal conductivity of fluids containing oxide nanoparticles[END_REF][START_REF] Mahian | Natural convection of silica nanofluids in square and triangular enclosures: Theoretical and experimental study[END_REF] and metallic nanoparticles [START_REF] Gomez-Villarejo | Ag-based nanofluidic system to enhance heat transfer fluids for concentrating solar power: Nano-level insights[END_REF][START_REF] Navas | On the enhancement of heat transfer fluid for concentrating solar power using Cu and Ni nanofluids: An experimental and molecular dynamics study[END_REF] have been widely analysed for suspension in the base fluid.

Yasinskiy et al. [START_REF] Yasinskiy | Dramatically enhanced thermal properties for TiO2-based nanofluids for being used as heat transfer fluids in concentrating solar power plants[END_REF] reported an increase in thermal conductivity of up to 25.8% for TiO 2 -based nanofluids. In addition, enhancements have been reported of up to 6% and 13% for Ag and Cu-based nanofluids using a heat transfer fluid typically used in Concentrating Solar Power [START_REF] Gomez-Villarejo | Ag-based nanofluidic system to enhance heat transfer fluids for concentrating solar power: Nano-level insights[END_REF][START_REF] Navas | On the enhancement of heat transfer fluid for concentrating solar power using Cu and Ni nanofluids: An experimental and molecular dynamics study[END_REF]. Nowadays, advanced nanomaterials are being used in nanofluid technology. In this sense, the use of boron nitride could be of interest.

A C C E P T E D M A N U S C R I P T 4

The discovery of a new mono-dimensional material based on boron nitride structures and known as boron nitride whiskers was reported in 1981 by Ishii [START_REF] Ishii | Growth of Whiskers of Hexagonal Boron-Nitride[END_REF]. However, perfect tubular boron nitride structures were not synthesized until 1995 using an arcdischarge technique [22]. The next main challenge was the synthesis and characterization of boron nitride nanotubes. To this effect, many methods were invented or modified: laser ablation [START_REF] Golberg | Nanotubes in boron nitride laser heated at high pressure[END_REF], chemical vapour deposition (CVD) [START_REF] Lourie | CVD growth of boron nitride nanotubes[END_REF] or substitution reactions [START_REF] Han | Synthesis of boron nitride nanotubes from carbon nanotubes by a substitution reaction[END_REF]. In turn, applications such as polymeric and ceramic composites [START_REF] Huang | Enhancing superplasticity of engineering ceramics by introducing BN nanotubes[END_REF] or hydrogen storage [START_REF] Mpourmpakis | Why boron nitride nanotubes are preferable to carbon nanotubes for hydrogen storage? An ab initio theoretical study[END_REF] have been reported. Currently, boron nitride is known as "white graphene" [START_REF] Nag | Graphene Analogues of BN: Novel Synthesis and Properties[END_REF][START_REF] Zeng | White Graphenes": Boron Nitride Nanoribbons via Boron Nitride Nanotube Unwrapping[END_REF] and can be found in numerous shapes, including spheres [START_REF] Tang | Synthetic Routes and Formation Mechanisms of Spherical Boron Nitride Nanoparticles[END_REF], tubes [START_REF] Lee | Boron Nitride Nanotubes: Recent Advances in Their Synthesis, Functionalization, and Applications[END_REF] or ribbons [START_REF] Chen | Novel Boron Nitride Hollow Nanoribbons[END_REF]. Since it has similar structures and properties to carbon-based materials, predictably, the two have often been compared, in particular carbon nanotubes (CNTs) and boron nitride nanotubes (BNNTs). Both BNNTs and CNTs have similar mechanical properties and great thermal stability, meaning both can be applied to improve the thermal conductivity of matrix materials or fluids. The main difference between the two tube types is that CNTs are excellent electrical conductors that are normally used to improve the electrical conductivity of polymers [START_REF] Bauhofer | A review and analysis of electrical percolation in carbon nanotube polymer composites[END_REF][START_REF] Zhang | Conductive network formation in the melt of carbon nanotube/thermoplastic polyurethane composite[END_REF]. Meanwhile, BNNTS are basically electrically insulators and are appealing insulating materials with high thermal conductivity [START_REF] Yu | Vertically Aligned Boron Nitride Nanosheets: Chemical Vapor Synthesis, Ultraviolet Light Emission, and Superhydrophobicity[END_REF]. BN is also a highly stable dielectric ceramic material and interesting behaviour has been reported related to the electric and magnetic properties of nanofluids based on BN [START_REF] Abbasi | Hall effects on peristalsis of boron nitrideethylene glycol nanofluid with temperature dependent thermal conductivity[END_REF][START_REF] Fal | Dielectric Properties of Boron Nitride-Ethylene Glycol (BN-EG) Nanofluids[END_REF][START_REF] Ilhan | Experimental investigation of heat transfer enhancement and viscosity change of hBN nanofluids[END_REF].

In this study, nanofluids based on BNNTs were prepared and characterized. An aqueous solution of Triton X-100, which acts as the surfactant, was used as the base fluid. The stability of the nanofluids was analysed by means of UV-vis spectroscopy, and particle size and  potential measurements. The surface tension and rheological properties of the fluids were also measured and analysed according to the temperature and concentration

A C C E P T E D M A N U S C R I P T

of BNNTs. Finally, thermal properties, such as isobaric specific heat and thermal conductivity were measured and also analysed with regard to the concentration of BNNTs and temperature.

Materials and Methods

Nanofluid preparation

Reagents. Triton X-100 and boron nitride nanotubes (BNNTs) were purchased from Sigma Aldrich (Saint-Quentin-Fallavier; France). Triton X-100

(C 14 H 22 O(C 2 H 4 O) n ) is a
non-ionic surfactant that has a hydrophilic polyethylene oxide chain and an aromatic hydrocarbon lipophilic or hydrophobic group. It is available in liquid form and has average molecular weight of 625 and a density of 1.07 g/cm 3 .

As indicated by manufacturer data [39], BNNTs content is higher than 50% and elemental B free lower than 25%. The average nanotube diameter is about 52 nm.

Surface area (BET) of BNNTs is higher 100 m 2 /g. It should also be noted that the BNNTs presently used are produced from inductively coupled plasma synthesis without metal catalysis [39]. In the absence of a density value for BNNTs in the manufacturer's specification, it was measured by gas pycnometry as explained the in following section.

Preparation. Nanofluids were prepared following the two-step method [START_REF] Li | A review on development of nanofluid preparation and characterization[END_REF]

Nanomaterial characterization

The BNNTs were characterized by Scanning Electron Microscopy (SEM) and X-Ray Diffraction (XRD). The SEM of the BNNTs was performed with a JEOL-JSM-7100F Finally, the true density of the BNNTs was measured using an Ultrapic 1200e gas pycnometer (Quantachrome Instruments, USA) using nitrogen. The experiments were performed in replicate at room temperature with two different sample masses, which were carefully weighed with a precision balance. For each replicate, density was the average of 6 measurements.

A C C E P T E D M A N U S C R I P T

Nanofluid characterization

The nanofluids prepared were characterized for both stability and efficiency for comparison with the base fluid.

The improved efficiency of nanofluids results from significantly enhancing their thermal properties. However, this efficiency also depends on their stability. Thus, several techniques were used to analyse the chemical and physical stability of the nanofluids over time. UV-Vis spectroscopy makes it possible to assess the sedimentation process and therefore the stability of the nanofluids [START_REF] Sarsam | Stability and thermophysical properties of water-based nanofluids containing triethanolamine-treated graphene nanoplatelets with different specific surface areas[END_REF]. To this end, UV-Vis spectra were recorded in the wavelength range from 350 to 880 nm to analyse the presence of BNNTs in suspension. The system used consisted of a DH-2000-BAL halogen supplied by Ocean Optics© (Ocean Optics, United Kingdom) as the light source, and a USB200+ spectrometer supplied by Ocean Optics©. The particle size and size distribution were measured by dynamic light scattering (DLS), a common technique for analysing colloidal systems [START_REF] Angayarkanni | Review on thermal properties of nanofluids: Recent developments[END_REF][START_REF] Murdock | Characterization of nanomaterial dispersion in solution prior to In vitro exposure using dynamic light scattering technique[END_REF]. Furthermore,  potential measurements were performed to evaluate and understand the interactions between the particles in suspension and therefore the agglomeration process. A zetasizer Nano ZS system supplied by Malvern© (Malvern, United Kingdom) was used to perform both measurements. The UV-vis spectra, and particle size and  potential measurements were performed for 25-30 days, recording several measurements each day.

The efficiency of the nanofluids can also be evaluated from the heat transfer coefficient, which depends on all their thermophysical properties, such as thermal conductivity, density, isobaric specific heat, dynamic viscosity and surface tension [START_REF] Chandrasekar | Mechanisms proposed through experimental investigations on thermophysical properties and forced convective heat transfer characteristics of various nanofluids -A review[END_REF].

Consequently, the nanofluids were characterized for these properties.

The surface tension (ST) of the nanofluids was measured because this property plays an important role in many heat transfer processes and configurations, as recently

A C C E P T E D M A N U S C R I P T 8
emphasized by Estellé et al. [START_REF] Estelle | Current trends in surface tension and wetting behavior of nanofluids[END_REF]. This paper also reported that in most cases a decrease in surface tension leads to an increase in heat transfer properties. Thus, surface tension was measured at the interface between air and both the base fluid and nanofluids in the 10-50 ºC temperature range with a DSA-30 Drop Shape Analyzer from KRÜSS GmBH (Hamburg, Germany) based on the pendant drop technique. Temperature regulation within temperature chamber was achieved using a Peltier system and the temperature was monitored with a PT100 probe inserted into the temperature chamber. The experimental equipment is described in Figure 1a. Measurements at room condition were also performed and compared to the measurements under controlled conditions.

The experimental procedure consists of using a 15-gauge needle with an outer diameter of 1.835 mm to produce drops with controlled flow rate and volume, as reported previously [START_REF] Cabaleiro | Dynamic viscosity and surface tension of stable graphene oxide and reduced graphene oxide aqueous nanofluids[END_REF]. Then, the instrument records and digitally analyses the shape of the sample drops formed at the end of a syringe just at the moment when the drop snaps from the apex of the needle. Finally, surface tension is obtained from a drop shape analysis through a balance of internal and external forces acting on the drop and based on the Young-Laplace equation, as shown in Figure 1b. Thus, the reported ST values are the average of at least 10 measurements and no observable deviation between measurements was shown from the replicates. The needle remains within the chamber at least 10 mins at the required temperature before producing the drop. and the number of points per decades was adjusted to avoid sample evaporation at the geometry edge during measurement. Evaporation cannot be controlled at temperatures higher than 50 °C. Additional information about this measurement procedure and uncertainty evaluation in viscosity measurement, reported to be less than 4%, can be found in [START_REF] Halelfadl | Viscosity of carbon nanotubes water-based nanofluids: Influence of concentration and temperature[END_REF]. Water alone, the base fluid (aqueous solution of Triton X-100) and all the nanofluid samples were tested to verify the uncertainty in viscosity measurement, evaluate the influence of the surfactant on water viscosity and the effect of nanoparticle content respectively. Finally, the experiments were performed in two or three replicates with no observable differences.

A C C E P T E D M A N U S C R I P T

In turn, thermal properties such as isobaric specific heat and thermal conductivity were measured to analyse the efficiency of the nanofluids prepared. The isobaric specific heat measurements were performed using a temperature modulated differential scanning calorimeter (TMDSC), model DSC214 Polyma, supplied by Netzsch© (Netzsch, Germany). To perform the measurements, a program was created that can be summed up as: the temperature was equilibrated at 341 K to remove contaminants and kept isothermal for 10 minutes; then the samples were equilibrated at 288 K and then ramped to 373 K at a rate of 1 K/min. A modulation was programmed around the studied temperatures with an amplitude of ± 1 K and a period of 120 s. Finally, cooling was performed at 1 K/min. The isobaric specific heat of the base fluid was measured for

𝑘(𝑇) = 𝐷(𝑇) • 𝐶 𝑃 (𝑇) • 𝜌(𝑇) (1)
where k is the thermal conductivity, D is the thermal diffusivity, C P is the isobaric specific heat and  is the density.

Results and discussion

Nanomaterial characterization

The BNNTs used to prepare the nanofluids were characterized to determine their intrinsic properties by means of techniques such as SEM, XRD and density measurements. Figure 2a shows the growth direction parallel to the BNNT fibrils. At increased magnification, Figures 2b and2c show that the BNNTs appear predominantly in bundles rather than individually and that these bundles mainly form an entangled network. Figure 2c shows that the diameter of the BNNT bundles is about 30 nm. This is larger than the average nanotube diameter expected and reported by the manufacturer.

It can also be observed that some impurities, such as spherical particles, are present in the BN sample. was obtained, which agrees well with data previously reported [START_REF] Zhi | Specific heat capacity and density of multi-walled boron nitride nanotubes by chemical vapor deposition[END_REF].

Nanofluid characterization

Nanofluid stability

Preparing stable nanofluids is the key to most nanofluid applications since their thermal properties are determined by the quality of the colloidal dispersion achieved. In this sense, nanofluid systems are considered to be stable when the concentration of nanoparticles in suspension and/or their size remain constant over time [START_REF] Yu | A Review on Nanofluids: Preparation, Stability Mechanisms, and Applications[END_REF]. Nanofluids are dynamic systems, meaning nanomaterial in suspension tends to agglomerate due to attraction forces, while sedimentation can also occur. This has a negative effect on the stability and thermal properties of nanofluids [START_REF] Chakraborty | Synthesis of Cu-Al layered double hydroxide nanofluid and characterization of its thermal properties[END_REF]. Consequently, the analysis of the physical stability of nanofluids is of great interest and was therefore analysed using The sedimentation process in the five nanofluids was determined using UV-vis spectroscopy and by analysing the evolution of the extinction coefficient with time.

Figure 4a shows the evolution of the extinction coefficient measured at =400 nm for at least 25 days. For the measurements, the nanofluid with the highest concentration was diluted at a ratio of 1:5 (nanofluid:base fluid). At =400 nm, photonic absorption and light scattering processes occurred due to the presence of BNNTs in suspension, so the evolution of the extinction coefficient at this wavelength gives information about the presence of nanomaterial in the base fluid. The extinction coefficient of all the nanofluids decreased during the first few days, after which time it remained stable.

Therefore, all the nanofluids became stable and could be promising for use as heat transfer fluids. Figure 4b shows the plot of the extinction coefficient when the nanofluids reached physical stability versus the nominal mass concentration of BNNTs.

A linear relationship is observed, indicating that the amount of nanomaterial incorporated into the base fluid leads to stable nanofluids and that the sedimentation process does not occur to a greater extent in any of the nanofluids. In turn, physical stability was also analysed from particle size measurements using the DLS technique.

Figure 4c shows how the size of the particles in the nanofluids evolved over 25 days or more. Particle size measurements showed a unimodal distribution and all the values obtained were between 150 and 180 nm. These values are higher than the nominal value reported from SEM, but agglomeration can occur in colloidal suspensions. Thus, these values show that all the nanofluids were highly stable, which is coherent with the results obtained from UV-vis spectroscopy. Moreover, the nanofluid with the lowest mass concentration showed the smallest particle size, while no differences were observed

A C C E P T E D M A N U S C R I P T 16

The density of nanofluids has been shown to affect the efficiency of the heat transfer fluid, studies reporting an increase in efficiency when density increases [START_REF] Chandrasekar | Mechanisms proposed through experimental investigations on thermophysical properties and forced convective heat transfer characteristics of various nanofluids -A review[END_REF].

Consequently, density was measured when the nanofluids were stable. These values were also used to calculate the volume fraction of the nanofluids according to 𝜙 = (𝜌 𝑛𝑓 -𝜌 𝑏𝑓 ) (𝜌 𝑛𝑡 -𝜌 𝑏𝑓 ) ⁄

, where  is the density and the subscripts nf, bf and nt refer to the nanofluid, base fluid and BN nanotubes. In this study, as noted above, the solution of Triton-X in water in the proportion defined in the Experimental section is considered the base fluid. The density of the nanofluids and base fluid was measured by pycnometry. The density of the BNNTs was measured using gas pycnometry with a value of 1396.5 kg m -3 obtained, as described above. Table 1 shows density and volume fraction values for the nanofluids, a slight increase in density with nanoparticle content being observed, as expected.

Surface tension measurements

The surface tension (ST) of the base fluid and nanofluids was measured as described above. Knowing this property is of great importance in heat transfer systems, in particular those involving boiling heat transfer and condensation. The experimental uncertainty of measurements performed with this device was previously reported to be less than 1 % [START_REF] Zyla | Thermophysical and dielectric profiles of ethylene glycol based titanium nitride (TiN-EG) nanofluids with various size of particles[END_REF]. Calibration of the device was also checked at 20°C with two pendant drop calibration gauges provided by the device manufacturer and a maximum relative deviation of 0.1% was obtained. In addition, the ST of distilled water (DW) was first measured in the same temperature range and the values were compared to Equation ( 2

where  is ST in mN/m and T the temperature in Kelvin.

As mentioned above, the experimental equipment and procedure was first evaluated from the ST measurement of DW. The results are shown in Figure 5a. The figure shows that the ST of DW decreases with temperature as expected and that a very good agreement is achieved between experimental data and equation ( 1), with an absolute average deviation AAD=1.08%. In addition, the experimental conditions at 20°C are not significantly affected when the drop is produced at ambient condition or within the temperature chamber. The ST of the base fluid is also reported in Figure 5a. It shows that the surface tension of DW is drastically reduced with the presence of surfactant, indicating that the surface tension of the base fluid is mainly governed by surfactant.

This decrease in ST was about 44.5% and was not dependent on temperature.

Consequently, the ST reduction rate of the base fluid with temperature was similar to that of water. Again, the ST of the base fluid was not modified by the experimental conditions at 20°C.

The evolution of the ST of the nanofluids with both nanoparticle content and temperature is reported in Figure 5b. It shows that the nanofluid ST was weakly affected by the presence of any amount of nanoparticles, within the experimental uncertainty, and was mainly governed by the presence of surfactant. This is probably due to the low content considered in this study. As expected, the ST of the nanofluids also decreased with temperature with a trend similar that of the base fluid. Finally, as the ST of the

Rheological properties

Rheological measurements were performed in to determine how the nanoparticles affected the rheological behaviour of the base fluid. As expected, a Newtonian behaviour was reported for water for all tested temperatures and it was clear to see that water viscosity decreased with temperature, as shown in Figure 6. The viscosity data for water were favourably compared to values reported by [START_REF] Vargaftik | International Tables of the Surface-Tension of Water[END_REF] with an absolute average deviation (AAD)=4.3% in the 10-50°C range. Flow curves of water at 10 and 40°C are also reported in Figure 7 to show the Newtonian behaviour. The shear flow behaviour of the base fluid at the same temperature is also reported. The results indicate that the base fluid also behaved in a Newtonian manner within the shear rate range investigated.

Similar results were also obtained for other temperatures. It is also observed that the viscosity of base fluid was slightly higher than that of water, with an absolute average increase of 6.9% in the 10-40°C range, as illustrated by both Figures 6 and7. Viscosity also decreased with temperature following a similar trend to water. Finally, Figure 7 shows that the base fluid was only slightly affected by nanoparticle content as mainly Newtonian behaviour is maintained in the shear rate range investigated, within experimental uncertainty, with no significant increase in viscosity. This is evidenced by Figure 8

Thermal properties

The nanofluids were analysed to determine their isobaric specific heat and thermal conductivity. Isobaric specific heat has a vital role in the performance of heat transfer

A C C E P T E D M A N U S C R I P T

21 fluids and therefore the values of this property for the nanofluids prepared was measured between room temperature and 70 ºC. Figure 9 shows the values obtained for the nanofluids and also for the base fluid and for water with regard to temperature and volume fraction. The isobaric specific heat increased for all the nanofluids with regard to the base fluid and water, the nanofluids with higher volume fractions presenting the greatest increases. At 70 ºC the isobaric specific heat increased by 8.3% and 8.0% with regard to water and the base fluid, respectively. The isobaric specific heat of solids is usually lower than that of fluids; thus, taking into account the "simple mixture rule", the values expected for nanofluids would be lower than those for the base fluid, as reported previously [START_REF] Chandrasekar | Mechanisms proposed through experimental investigations on thermophysical properties and forced convective heat transfer characteristics of various nanofluids -A review[END_REF][START_REF] Cabaleiro | Specific heat of metal oxide nanofluids at high concentrations for heat transfer[END_REF][START_REF] Mousavi | Effective heat capacity of ferrofluids -Analytical approach[END_REF]. This model can be represented by a simple equation given as

𝐶 𝑃,𝑛𝑓 = 𝜙 • 𝐶 𝑃,𝑛𝑝 + (1 -𝜙) • 𝐶 𝑃,𝑏𝑓 (3)
where  is the volume fraction and C P is the isobaric specific heat, and the subscripts nf, np and bf refer to the nanofluids, nanoparticles and base fluid, respectively [START_REF] Cabaleiro | Specific heat of metal oxide nanofluids at high concentrations for heat transfer[END_REF]. The thermal equilibrium model is used to predict the values of isobaric specific heat, and usually fits the experimental values better. However, this model also predicts lower isobaric specific heat values for nanofluids due to the lower values for solids with regard to fluids [START_REF] Cabaleiro | Specific heat of metal oxide nanofluids at high concentrations for heat transfer[END_REF]. Figure 9b shows the values obtained for the nanofluids and the plot of the values generated using equation ( 3) and, as expected, the model did not give a good fit to the experimental values. However, some studies have reported different behaviour of isobaric specific heat; that is, an increase in the isobaric specific heat values for nanofluids with regard to the base fluid [START_REF] Shin | Enhanced Specific Heat Capacity of Nanomaterials Synthesized by Dispersing Silica Nanoparticles in Eutectic Mixtures[END_REF][START_REF] Navas | On the enhancement of heat transfer fluid for concentrating solar power using Cu and Ni nanofluids: An experimental and molecular dynamics study[END_REF][START_REF] Shin | Specific heat of nanofluids synthesized by dispersing alumina nanoparticles in alkali salt eutectic[END_REF][START_REF] Nelson | Flow Loop Experiments Using Polyalphaolefin Nanofluids[END_REF][START_REF] Vajjha | Specific Heat Measurement of Three Nanofluids and Development of New Correlations[END_REF]; and nanofluids with higher isobaric specific heat values with regard to the base fluid but showing a wavelike behaviour with regard to the volume fraction [START_REF] Sonawane | An experimental investigation of thermo-physical properties and heat transfer performance of Al2O3-Aviation Turbine Fuel nanofluids[END_REF]; or nanofluids showing isobaric

A C C E P T E D M A N U S C R I P T

22 specific heat values greater than the base fluid, but which decreases with the increase in volume fraction [START_REF] Kumaresan | Experimental investigation of the thermo-physical properties of water-ethylene glycol mixture based CNT nanofluids[END_REF]. Furthermore, the interfacial free energy of solid-liquid is altered with suspended nanomaterials. Due to the higher specific surface area of nanomaterials, which depends on their morphology, their surface free energy has a greater proportion of the capacity of the system, which affects the isobaric specific heat. The surface free energy depends on the nature of the components of the system, their properties and the interactions between them, and therefore on the molecular-level structure. Thus, we feel it is very complicated to rationalize the behaviour of the C P for nanofluids at the present time. Therefore, the behaviour found in this study can be attributed to an internal structure forming inside the nanofluid that depends on the nature of the components [START_REF] Shin | Enhanced Specific Heat Capacity of Nanomaterials Synthesized by Dispersing Silica Nanoparticles in Eutectic Mixtures[END_REF][START_REF] Shin | Specific heat of nanofluids synthesized by dispersing alumina nanoparticles in alkali salt eutectic[END_REF]. This structure is one of the heat storage modes related to the layers of liquid and surfactant molecules around the nanomaterial that constitute a solid-like layer with higher specific heat than the bulk liquid. Thus, an internal structure involving the water and surfactant molecules around the BNNTs may have been formed in the nanofluids, giving high isobaric specific heat values and making the nanofluids very stable, as shown above.

A C C E P T E D M A N U S C R I P T 23

An increase in thermal conductivity is known to lead to more efficient heat transfer [START_REF] Timofeeva | Nanofluids for heat transfer: an engineering approach[END_REF], and the suspension of nanomaterials in a fluid increases its thermal conductivity [START_REF] Lee | Measuring thermal conductivity of fluids containing oxide nanoparticles[END_REF][START_REF] Gomez-Villarejo | Ag-based nanofluidic system to enhance heat transfer fluids for concentrating solar power: Nano-level insights[END_REF][START_REF] Navas | On the enhancement of heat transfer fluid for concentrating solar power using Cu and Ni nanofluids: An experimental and molecular dynamics study[END_REF][START_REF] Aguilar | Investigation of enhanced thermal properties in NiO-based nanofluids for concentrating solar power applications: A molecular dynamics and experimental analysis[END_REF]. Thus, the thermal conductivity of the nanofluids was measured at 30, 50 and 70 ºC following the procedure described above. Figure 10a shows the values obtained with regard to temperature and volume fraction. In all cases, thermal conductivity is seen to increase with temperature, meaning the nanofluids follow the same trend as the base fluid. Furthermore, the values for the nanofluids were higher than those of the base fluid and water. Figure 10b shows the k nf /k bf ratio with regard to temperature and the volume fraction. An increase of about 10% is observed for the two nanofluids with the highest volume fractions. In turn, it is of interest to analyse the increase in thermal conductivity values using models that relate thermal conductivity with volume fraction. The first model reported with this aim was presented by Maxwell [START_REF] Maxwell | A treatise on electricity and magnetism[END_REF]:

A C C E P T E D M A N U S C
where n is the shape factor, usually defined as n = 3/,  being the sphericity, which can be calculated from the dimensions of the nanomaterial. However, as the dimensions of the BNNTs were not well-known in this case, the H-C model cannot be used.

Moreover, many models to predict the thermal conductivity of spherical nanoparticles can be found in the literature, but there are few specific models for nanofluids based on nanotubes. One of these is the Xue model [START_REF] Xue | Model for thermal conductivity of carbon nanotube-based composites[END_REF]:

𝑘 𝑛𝑓 𝑘 𝑏𝑓 = 1 -
where all the variables have been previously defined. the models because they do not consider the interaction between the components of the nanofluid system. At high temperatures, the deviation is higher because the number of interactions increases. For example, the motion of particles in suspension can enhance the heat transport within the base fluid [START_REF] Gao | Measurement and modeling of thermal conductivity of graphene nanoplatelet water and ethylene glycol base nanofluids[END_REF][START_REF] Xuan | Aggregation structure and thermal conductivity of nanofluids[END_REF]. One of the reasons for the increase in heat transport and thermal conductivity postulated is the stochastic motions of the

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nanomaterial in suspension and the interactions between particles and the fluid molecules; that is, Brownian motion. Thus, assuming that this mechanism can be considered separately, the total effective thermal conductivity can be considered as the sum of the terms related to static conductivity and Brownian motion; that is, 𝑘 𝑛𝑓 = 𝑘 𝑠𝑡𝑎𝑡𝑖𝑐 + 𝑘 𝑏𝑟𝑜𝑤𝑛𝑖𝑎𝑛 . Thus, to take into account dynamic transport, Xuan et al. reported a model that includes the influence of viscosity, temperature and other properties of the base fluid and the nanoparticles, given by [START_REF] Xuan | Aggregation structure and thermal conductivity of nanofluids[END_REF] 𝑘 𝑏𝑟𝑜𝑤𝑛𝑖𝑎𝑛,𝑋𝑢𝑎𝑛 = 𝜌 𝑝 𝜙𝐶 𝑃,𝑏𝑓 2 √ 𝜅𝑇 3𝜋𝜇𝑟 𝑐 [START_REF] Wu | A review of nanofluid heat transfer and critical heat flux enhancement-Research gap to engineering application[END_REF] where  p is the density of BNNTs (1396.6 kg m -3 ), C P,bf is the isobaric specific heat of the base fluid,  is the Boltzmann constant,  the viscosity and r c is the mean gyration radius of the cluster. This value is estimated from the DLS measurements shown above when the nanofluids are considered stable. Also, Koo and Kleinstreuer introduced a new model considering the H-C model and a contribution of Brownian motion [START_REF] Koo | A new thermal conductivity model for nanofluids[END_REF]. This Brownian contribution is given by [START_REF] Koo | A new thermal conductivity model for nanofluids[END_REF] 𝑘 𝑏𝑟𝑜𝑤𝑛𝑖𝑎𝑛,𝐾𝑜𝑜-𝐾𝑙𝑒𝑖𝑛𝑠𝑡𝑟𝑒𝑢𝑒𝑟 = 5𝑥10

where d p is the diameter of the cluster, also obtained from DLS measurements, as previously [START_REF] Vajjha | Experimental determination of thermal conductivity of three nanofluids and development of new correlations[END_REF]. It can also be observed that  does not change, which is coherent because, as stated above,  depends on the kind of nanomaterial and the same type was used in all the nanofluids. In turn, f(T,) increased linearly with temperature, as the models predict [START_REF] Vajjha | A review and analysis on influence of temperature and concentration of nanofluids on thermophysical properties, heat transfer and pumping power[END_REF]. The values of  and f(T,) are shown in Figure 11d. Thus, the contribution of Brownian motion is clearly observed, and this contribution increases with temperature.

Conclusions

This study presents an analysis of nanofluids based on BNNTs. An aqueous solution of Triton X-100, which acts as a surfactant, was used as a base fluid. The stability, surface tension, rheological and thermal properties of the nanofluids were studied.

For all nanofluids prepared, the extinction coefficient obtained from UV-vis spectroscopy decreased during the first few days, after which it remained stable. Particle size measurements showed a characteristic unimodal distribution, all values ranging between 150 and 180 nm and presenting high stability in all cases. Moreover, the  potential values, which were stable over time, were coherent with those obtained from

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UV-vis spectroscopy and particle size measurements. Therefore, all the nanofluids prepared reached a stable condition and may be promising for use as heat transfer fluids.

Furthermore, the evolution of the surface tension of the nanofluids according to their nanoparticle content and temperature was analysed. Water surface tension was weakly affected by the presence of nanoparticles whatever the content and was mainly governed by the presence of Triton X-100 as the surfactant. This is probably due to the low nanotube content considered in this study. As expected, the surface tension of the nanofluids also decreased with temperature following a trend similar to that of the base fluid because the values are governed by the surfactant.

In addition, rheological properties were measured. The results indicated that the base fluid behaved in Newtonian manner within the shear range investigated. In turn, the nanofluids showed a mainly Newtonian behaviour with no significant increase in viscosity.

Furthermore, thermal properties, such as isobaric specific heat and thermal conductivity,

  whereby the nanomaterial is first synthesized and then dispersed in a base fluid. In this study, boron nitride nanotubes were used as the nanomaterial. The base fluid used was a 0.35 vol% aqueous solution of Triton X-100, which was used as stabilizing agent. Five nanofluids were prepared with different concentrations of BNNTS in the base fluid: 0.1 • 10 -2 , 0.3 • 10 -2 , 0.5 • 10 -2 , 1.0 • 10 -2 , 3.0 • 10 -2 wt%. In each case, the amount of Triton X-100 for 0.35 vol% solution was mixed in water (100 mL) under magnetic stirring for 30 minutes. Then, BNNTs were added to the solution in the right amounts to obtain the A C C E P T E D M A N U S C R I P T concentrations given above. The nanofluids were kept in a sonication bath (80 Hz, Elmasonic P by Elma®) for 2 hours at a temperature below 30ºC. Moreover, a solution of the base fluid, Triton X-100 with the same concentration noted before, was prepared for comparison purposes.

Figure 1 .

 1 Figure 1. (a) Experimental equipment for ST measurements, and (b) example of

A

  C C E P T E D M A N U S C R I P T 11 comparison purposes. Moreover, thermal conductivity was measured by the laser flash technique (LFA) using LFA467 HyperFlash technology supplied by Netzsch© (Netzsch, Germany). To be precise, this technique measures thermal diffusivity, a thermophysical property that defines the speed of heat propagation by conduction during changes of temperature, or how quickly a material reacts to a change in temperature. According to Standard ASTM E 1461-01, thermal conductivity may be calculated by the equation:

Figure 2 .

 2 Figure 2. SEM pictures of BNNTs.

Figure 3 .

 3 Figure 3. Powder XRD of BNNTs.

A

  C C E P T E D M A N U S C R I P T 14 techniques such as UV-vis spectroscopy, dynamic light scattering to obtain the particle size, and  potential.

A

  C C E P T E D M A N U S C R I P T15 among the remaining nanofluids. The difference with regard to the nanofluid with lowest concentration was very slight. Finally,  potential of the nanofluids was measured, Figure4dshowing the values obtained. These are also coherent with the results from UV-vis spectroscopy and particle size measurements; that is, the values remain stable over time. After the first few days, all the values obtained were between -25 and -20 mV.

Figure 4 .

 4 Figure 4. (a) Evolution of the extinction coefficient measured at =400 nm with time.

A

  C C E P T E D M A N U S C R I P T18 nanofluids mainly decreased in the presence of surfactant, this could lead to increased heat flux in real systems[START_REF] Estelle | Current trends in surface tension and wetting behavior of nanofluids[END_REF].

Figure 5 .

 5 Figure 5. (a) Surface tension of DW and base fluid -Influence of temperature. (b)

Figure 6 .

 6 Figure 6. Viscosity data of water and base fluid.

Figure 7 .

 7 Figure 7. Viscosity data of water, base fluid and nanofluids in accordance with shear

  where the relative viscosity deviation of the nanofluids compared to the base fluid is plotted according to the nanoparticle content for all temperatures. The figure shows that the evolution of relative viscosity was within experimental uncertainty whatever the nanoparticle loading and temperatures (taking into consideration uncertainty of base fluid and nanofluid measurement).

Figure 8 .

 8 Figure 8. Relative viscosity deviation of nanofluids compared to base fluid according to

Figure 9 .

 9 Figure 9. (a) Isobaric specific values of the nanofluids; (b) comparison with a simple

Figure 10 .

 10 Figure 10. (a) Thermal conductivity values of the nanofluids; (b) thermal conductivity

  Figure 11 shows the plot of the Maxwell model and the Xue model and the experimental results for comparison purposes at several temperatures. At 30 ºC and low volume fraction values, both models show values close to the experimental ones, but neither model predicts the experimental values very well. Typically, the experimental values are higher than those predicted by

  Figure 11 shows the results of the application of the Maxwell and Xue models

Figure 11 .

 11 Figure 11. Thermal conductivity values for the nanofluids prepared and the plots of

  were measured. The isobaric specific heat increased by 8.3% and 8.0% at 70 ºC with regard to water and the base fluid, respectively. Also, the thermal conductivity of the nanofluids increased with regard to the base fluid and water, this increase reaching about 10% for the two nanofluids with the highest volume fraction. In order to understand the heat transport mechanism, several models of thermal conductivity were analysed. The contribution of Brownian motion was clearly observed, this contribution increasing with temperature. So, from a practical perspective, the results obtained are interesting because while the thermal properties of the fluids improved with nanoparticle content, their rheological behaviour did not change. Consequently, use of nanofluids cannot modify pressure drop A C C E P T E D M A N U S C R I P T 29 and pumping power in real situations. Therefore, the nanofluids prepared could be a promising alternative to the typical HTF used. A C C E P T E D M A N U S C R I P T A C C E P T E D M A N U S C R I P T

Table 1 .

 1 Density and volume fraction values for the nanofluids prepared.

	wt.% BNNTs	 / kg m -3	 / vol%
	0.0 (H 2 O + Triton-X)	998.4	0.000
	0.001	998.7	0.080
	0.003	998.9	0.126
	0.005	999.0	0.151
	0.01	999.2	0.206
	0.03	999.4	0.254

Acknowledgements

Roberto Gómez-Villarejo acknowledges EU COST for the STSM grant ref. COST-STSM-CA15119-37968 linked to the Cost Action "Overcoming Barriers To Nanofluids Market Uptake (NANOUPTAKE)". P. Estellé acknowledges the European Union through the European Regional Development Fund (ERDF), the Ministry of Higher Education and Research, the French region of Brittany and Rennes Métropole for the financial support related to surface tension and gas pycnometer devices used in this study. He also acknowledges Francis Gouttefangeas from CMEBA, Université Rennes 1 and Mathieu Pasturel from the Institut des Sciences Chimiques de Rennes, Université Rennes 1 for performing respectively the SEM and XRD characterization. J. Navas acknowledges the Ministerio de Economia y Competitividad (MINECO) of the Spanish Government for funding under Grant No. ENE2014-58085-R, for the financial support related to the isobaric specific heat and thermal conductivity measurements, which were performed using equipment acquired under Grant No. UNCA15-CE-2945.

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Graphical abstract

ACCEPTED MANUSCRIPT

A C C E P T E D M A N U S C R I P T 36

Highlights

Stable nanofluids based on boron nitride nanotubes were prepared and analysed Isobaric specific heat increased by 8% and thermal conductivity by 10 % Newtonian behaviour was found for nanofluids with no significant increase in viscosity Surface tension was mainly governed by the presence of Triton X-100 as surfactant Rheological behaviour is not changed with nanoparticle content


Stéphane Jouneau

Mallorie Kerjouan

Chloé Rousseau

Mathieu Lederlin

Francisco Llamas-Guttierez

Bertrand De Latour

Stéphanie Guillot

Laurent Vernhet

Benoit Desrues

Ronan Thibault
email: ronan.thibault@chu-rennes.fr

Prof Thibault Ronan

What are the best indicators to assess malnutrition in idiopathic pulmonary fibrosis patients? A cross-sectional study in a referral centre

Keywords: malnutrition, lean body mass, food intake, bioelectrical impedance analysis, interstitial lung disease

Background & aims: Little is known about the indicators to assess malnutrition in patients with idiopathic pulmonary fibrosis (IPF). This study aimed to determine: i) the prevalence of malnutrition in IPF patients, ii) the nutritional indicators predictive of low fat-free mass (FFM) as measured by bioimpedance analysis; iii) the IPF patients' characteristics associated with low FFM. Methods: The IPF patients were consecutively recruited in a referral centre for Rare Pulmonary Diseases. Malnutrition was defined as a fat-free mass index (FFMI) = FFM (kg)/(height (m) 2 ) <17 (men) or <15 (women). Nutritional assessment included body mass index (BMI), mid-arm circumference (MAC), triceps skinfold thickness, analogue food intake scale, and serum albumin and transthyretin. Primary endpoint: FFMI. Statistics: area under the receiver operating characteristic curve (AUC) assessed low FFMI prediction from nutritional indicators. Multivariable logistic regression: variables associated with low FFMI. Results: Eighty-one patients were consecutively recruited. Low FFMI prevalence was 28% (23/81). BMI AUC was 0.91 [95% CI, 0.84-0.97] and MAC AUC was 0.85 [0.76-0.94]. Multivariable analysis associated BMI (Odds ratio (OR) 0.26 [95% confidence interval (CI) 0.12 -0.54], P=0.0003), male gender (OR 0.02 [0.00 -0.33], P=0.005), and smoking (OR 0.10 [0.01 -0.75], P=0.024) with a lower risk of malnutrition. Conclusion: Malnutrition occurred in nearly one third of IPF patients. Malnutrition screening should become systematic, based on BMI and MAC that are good clinical indicators of low FFMI. We propose a practical approach to screen malnutrition in IPF patients.

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INTRODUCTION

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and irreversible lung disease with a poor prognosis and a median survival after diagnosis of 3-5 years [START_REF] Ley | Clinical course and prediction of survival in idiopathic pulmonary fibrosis[END_REF][START_REF] Raghu | An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management[END_REF][START_REF] Strand | Pulmonary function and survival in idiopathic vs secondary usual interstitial pneumonia[END_REF]. IPF is the first aetiology of chronic idiopathic interstitial pneumonia in adults, and is associated with several comorbidities [START_REF] Raghu | Comorbidities in idiopathic pulmonary fibrosis patients: a systematic literature review[END_REF]. Malnutrition, defined as low body mass index (BMI) or low fat-free mass (FFM) [START_REF] Chailleux | Prognostic value of nutritional depletion in patients with COPD treated by long-term oxygen therapy: data from the ANTADIR observatory[END_REF][START_REF] Landbo | Prognostic value of nutritional status in chronic obstructive pulmonary disease[END_REF][START_REF] Schols | Body composition and mortality in chronic obstructive pulmonary disease[END_REF][START_REF] Vestbo | Body mass, fat-free body mass, and prognosis in patients with chronic obstructive pulmonary disease from a random population sample: findings from the Copenhagen City Heart Study[END_REF], is an independent predictor of mortality in patients with chronic obstructive pulmonary disease (COPD), another chronic, progressive, and irreversible lung disease. FFM is the nutritional indicator the best correlated with COPD patient's survival [START_REF] Schols | Body composition and mortality in chronic obstructive pulmonary disease[END_REF]. Although BMI is widely used to assess nutritional status, it is an insensitive detector of impaired FFM in COPD patients [START_REF] Schols | Body composition and mortality in chronic obstructive pulmonary disease[END_REF][START_REF] Thibault | Assessment of nutritional status and body composition in patients with COPD: comparison of several methods[END_REF]. Bioelectrical impedance analysis (BIA) is the simplest and most accurate method for assessing body composition in clinical practice [START_REF] Thibault | Assessment of nutritional status and body composition in patients with COPD: comparison of several methods[END_REF][START_REF] Kyle | Bioelectrical impedance analysis--part I: review of principles and methods[END_REF][START_REF] Kyle | Bioelectrical impedance analysis-part II: utilization in clinical practice[END_REF][START_REF] Thibault | Body composition: why, when and for who?[END_REF]. Pulmonary rehabilitation improves the FFM of COPD patients [START_REF] Disease | Global strategy for the diagnosis, management and prevention of chronic obstructive lung disease[END_REF]. The prognosis for IPF patients with a low BMI [START_REF] Alakhras | Body mass index and mortality in patients with idiopathic pulmonary fibrosis[END_REF] or low BMI plus respiratory parameters [START_REF] Kishaba | Body mass index-percent forced vital capacity-respiratory hospitalization: new staging for idiopathic pulmonary fibrosis patients[END_REF], and low FFM [START_REF] Nishiyama | Fatfree mass index predicts survival in patients with idiopathic pulmonary fibrosis[END_REF] is poor. However, to our knowledge, little is known regarding the nutritional assessment of IPF patients. The IPF management guidelines do not cover nutritional status assessment [START_REF] Raghu | An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management[END_REF][START_REF] Cottin | Diagnosis and management of idiopathic pulmonary fibrosis: French practical guidelines[END_REF] or the nutritional criteria for assessing disease stage and prognosis [START_REF] Raghu | An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management[END_REF]. Therefore it is needed to determine the best indicators for assessing IPF patients' nutritional status. In this crosssectional study in consecutive IPF patients, we aim to assess the prevalence of malnutrition; to identify the most reliable clinical and biochemical nutritional indicators (BMI, weight loss, low energy intake, mid-arm circumference, triceps skinfold, serum albumin and transthyretin) for predicting low FFM diagnosed by BIA; and, using multivariate analysis, to identify the demographic, respiratory, and nutritional variables associated with low FFM. Our results should provide practical advice for detecting early stage malnutrition in IPF patients, form the basis for future prospective randomized controlled trials on IPF patient nutrition, and, at best, should contribute to elaborate nutritional recommendations in future IPF guidelines.

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M A N U S C R I P T 6

PATIENTS AND METHODS

Study design

This single-centre cross-sectional study used prospective data collection. Patients were recruited from several general hospitals and private physicians, and assessed at Rennes University Hospital (CHU Rennes).

Study population

The patients were recruited between May and December 2016 at a French tertiary referral centre for IPF: the Competence Centre for Rare Pulmonary Diseases ('Centre de Compétences Maladies Pulmonaires Rares'), Department of Respiratory Medicine, Rennes University Hospital (CHU Rennes), Rennes, France. We collected data from all consecutive patients with stable IPF, as defined in multidisciplinary discussions [START_REF] Raghu | An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management[END_REF][START_REF] Cottin | Diagnosis and management of idiopathic pulmonary fibrosis: French practical guidelines[END_REF] who had been without infection or exacerbation in the eight weeks preceding their first appointment. This study was approved by the hospital Ethic Committee (n°17.53).

Clinical and biological assessment of nutritional status

The nutritional status of all patients was assessed by a single pulmonologist physician (SJ). This initial medical consultation included assessment of weight, height, mid-arm circumference (MAC; tape measure) and triceps skinfold thickness (TSF; adipometer). Body mass index was calculated as: weight (kg) / (height (m) 2 . Mid-arm muscular circumference (MAMC) (cm) was calculated as: MAC (cm)-( x TSF (cm)). Food intake was systematically assessed with the ten-point analogue visual scale of the Simplified Evaluation of Food Intake® (SEFI®), as previously described [START_REF] Thibault | Use of 10point analogue scales to estimate dietary intake: a prospective study in patients nutritionally at-risk[END_REF]. Patients moved the cursor on the scale to answer the question: 'How much do you presently eat, ranging from 'nothing at all' (far left

A C C E P T E D M A N U S C R I P T 7
of the scale) to 'as usual' (far right side of the scale)?' Results were expressed as a number between 0 and 10. Nutritional biological parameters of all patients (serum albumin and transthyretin) and CRP were also measured.

Bioelectrical impedance analysis (BIA)

Body composition, including FFM, fat mass, total body water, extracellular and intracellular water, and 50-kHz phase angle, were measured with a multifrequency bioimpedance generator/analyser (Quadscan 4000, Bodystat Ltd, Isle of Man, UK). Briefly, patients lay supine with the palms of their hands facing inwards and areas of skin on the backs of their left hand, left wrist, left foot, and left ankle were cleaned with 70 % ethanol and four adhesive electrodes (3M Red Dot T; 3M Health Care, Borken, Germany) were placed on them. An 0.8 mA electrical current at frequencies of 5, 50, 100, and 200 kHz produced by the bioimpedance generator/analyser was used to measure whole-body resistance (R) and reactance (Xc) [START_REF] Kyle | Bioelectrical impedance analysis--part I: review of principles and methods[END_REF]. Phase angles were calculated from: phase angle (°) = arctan(Xc/R) × (180/π). Fat-free mass index (FFMI) was calculated as: fat-free mass (kg) / (height (m) 2 .

FFMI was considered to be low if it was below 17 in men or below 15 in women, as in COPD patients [START_REF] Vestbo | Body mass, fat-free body mass, and prognosis in patients with chronic obstructive pulmonary disease from a random population sample: findings from the Copenhagen City Heart Study[END_REF][START_REF] Schols | Prevalence and characteristics of nutritional depletion in patients with stable COPD eligible for pulmonary rehabilitation[END_REF]. The body fat mass index (BFMI) was calculated as: fat mass (kg)/(height (m) 2 .

Respiratory and other data collection

Demographic (gender, age) and clinical data (disease duration, comorbidities, current drug use, tobacco use, performance of surgical lung biopsy), pulmonary function test (PFT) and six-minute walk test (6MWT) parameters, were collected from the hospital electronic medical database. Dyspnoea was assessed using the New York Health Association (NYHA) scale.

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A N U S C R I P T 8 PFT and 6MWT were performed according to international guidelines [START_REF] Miller | Standardisation of spirometry[END_REF][START_REF] Committee | ATS statement: guidelines for the six-minute walk test[END_REF]. The gender, age and physiology (GAP) index was calculated as proposed by Ley et al. [START_REF] Ley | A multidimensional index and staging system for idiopathic pulmonary fibrosis[END_REF].

Statistical analysis

Descriptive statistics are expressed as means ± standard deviations (SD) or medians and interquartile ranges for continuous data, according to their distribution, and as the number of patients (with the percentage in parenthesis, followed immediately by the counts for the numerator/denominator) for categorical data. ROC curves were used to analyse the association of each nutritional variable with low FFM and to find the best cut-off associated with low FFM by the Youden method. ROC curves were analysed with their AUCs and 95 % confidence intervals (CIs). The discriminative power of the AUC was defined as: 0.90 ≤ AUC ≤ 1.0, excellent; 0.80 ≤ AUC < 0.90, good; 0.70 ≤ AUC < 0.80, fair; 0.60<AUC< 0.70, poor; 0.50 ≤ AUC < 0.60, failure [START_REF] Swets | Measuring the accuracy of diagnostic systems[END_REF]. We analysed the FFM with χ2 tests (or Fisher's exact test when appropriate) for categorical data, and Student's t-test (or Mann-Whitney-Wilcoxon / Kruskall Wallis test when appropriate) for continuous data. Multivariable logistic regression analysis adjusted for factors with P values of <0.2 in univariate analysis was performed with backward stepwise elimination of all variables that did not contribute (P value ≥0.05). The adjusted Odds ratio of continuous variables was expressed for 1-point increases. Sensitivity, specificity, positive predictive value and negative predictive value, and their 95 % CIs were calculated according to the Youden method. Statistics were computed with SAS software V9.4 (SAS Institute Inc., Cary, NC, USA), and two-tailed P values of <0.05 were considered statistically significant.

RESULTS

Patients' clinical and demographics characteristics

A C C E P T E D M A N U S C R I P T

The study included 81 patients (72 (88%) men) with IPF whose clinical characteristics are shown in Table 1. The mean age was 74.4 ± 8.6 years. Of these, 41 were taking antifibrotic medication at inclusion: 18 (32%) patients with nintedanib (mean duration -597 ± 635 days; range 54 -1765 days) and 23 (28%) with pirfenidone (mean duration -449 ± 267 days; range 20 -1049 days. The remaining 40 patients (49%) were either taking no antifibrotic medication because they were newly diagnosed (n=20 (25%)), did not tolerate or refuse antifibrotic medication, or their disease was too severe to be treated (i.e. FVC < 50% pred and/or TLCO < 30% pred).

Prevalence of malnutrition in IPF patients

In the 81 IPF patients the prevalence of malnutrition based on BIA, i.e. low FFM, was 28% (23/81) (Table 2). This prevalence was lower using other definitions: 4% (3/81) based on BMI<21, 5% (4/81) based on MAC (<250 mm in women and <260 mm in men), and 9% (7/81) based on MMAC (<190 mm in women and <240 mm in men).

Relationship between fat-free mass and clinical and biological nutrition assessment parameters

Low FFMI was significantly associated with lower values for BMI, MAC, TSF, and hence MAMC (Table 2). The sensitivity, specificity, positive predictive value, and negative predictive value, defining the capacity of BMI<21 for predicting low FFMI were respectively: 13%, 100%, 100%, and 74%. Lower FFMI was associated with a lower 50 kHz phase angle (25) and a higher percentage of fat mass. Patients with low FFMIs were older, more frequently women, non-smokers, had a lower TLCO, and were less likely to be diagnosed using surgical lung biopsy (Table 1). Symptoms (dyspnoea, cough, digital clubbing) or IPF drug therapy were not associated with a low FFMI. Neither were changes in serum albumin 4). MAMC (AUC = 0.79, 95% CI, 0.69-0.90) and phase angle (AUC = 0.72, 0.61-0.84) were both fair predictors of FFMI loss.

Relationship between food intake, nutritional parameters, and IPF drug use

As reduced food intake is a well-known indicator of malnutrition, we assessed the factors associated with decreased food intake as indicated by the SEFI®. Patients with an SEFI® analogue score of <7 had a lower TLCO (34.4±13.6%) than those with a SEFI® score ≥7 (46.0±14.9%, P=0.0028), suggesting a link between decreased food intake and disease severity. Patients with a SEFI® analogue score <7 had lower values for MAC (28.3±2.7 vs. 29.9±2.5 cm, P=0.01), MAMC (26.3 ±2.6 vs. 27.6 ±2.3 cm, P=0.025), and phase angle (4.6±1.0 vs. 5.2±0.9 degrees, P=0.012) than those with a SEFI® score ≥7, suggesting a more impaired nutritional status when energy intake is decreased. However, FFMI (17.7 ± 3.3 vs.

DISCUSSION

In this cross-sectional study, nearly one third (28%) of the IPF patients were malnourished, as defined by a low FFMI based on BIA. Decreased BMI and MAC, female gender, and neversmoking were strong predictors of low FFM. As a low FFMI has been suggested to affect IPF prognosis [START_REF] Nishiyama | Fatfree mass index predicts survival in patients with idiopathic pulmonary fibrosis[END_REF], a systematic nutritional assessment should be routinely recommended for IPF patients.

To our knowledge, this is the first study to determine, in IPF patients, if usual nutritional indicators could predict low FFMI measured by BIA. Measuring BMI with a cut-off of <21, as recommended for COPD patients [START_REF] Vestbo | Body mass, fat-free body mass, and prognosis in patients with chronic obstructive pulmonary disease from a random population sample: findings from the Copenhagen City Heart Study[END_REF][START_REF] Disease | Global strategy for the diagnosis, management and prevention of chronic obstructive lung disease[END_REF][START_REF] Schols | Prevalence and characteristics of nutritional depletion in patients with stable COPD eligible for pulmonary rehabilitation[END_REF], is an insensitive method for diagnosing malnutrition, and largely underestimates the problem. It indicated that only 4% were malnourished, while a low FFMI derived from BIA diagnoses 28%, indicating that 87% of patients with low FFMI having BMI ≥21 were false negatives. This poor sensitivity of BMI <21 has been reported for COPD patients, for whom BIA is the most sensitive method for diagnosing malnutrition [START_REF] Thibault | Assessment of nutritional status and body composition in patients with COPD: comparison of several methods[END_REF][START_REF] Schols | Prevalence and characteristics of nutritional depletion in patients with stable COPD eligible for pulmonary rehabilitation[END_REF]. However, when choosing the right cut-offs, BMI is excellent, and MAC good, at predicting low FFMI. The most discriminative cut-off for BMI was 25.4 with excellent sensitivity and negative predictive value, but the specificity and positive predictive values were poor because it produced many false positives. MAC<295 mm and a combination of BMI and MAC gave similar predictive profiles. We believe that these results will prove useful in daily clinical practice.

Our data indicate that malnutrition is common in IPF patients: nearly one third of them were malnourished. This is important because some studies on IPF patients suggested that a low BMI, alone [START_REF] Alakhras | Body mass index and mortality in patients with idiopathic pulmonary fibrosis[END_REF] or combined with respiratory parameters [START_REF] Kishaba | Body mass index-percent forced vital capacity-respiratory hospitalization: new staging for idiopathic pulmonary fibrosis patients[END_REF], and low FFM derived from [START_REF] Alakhras | Body mass index and mortality in patients with idiopathic pulmonary fibrosis[END_REF]. Patients with a BMI ≥ 30 had a better survival rate than those with BMIs < 25 and 25-30. A retrospective Japanese study on 65 patients with IPF found that a one-point increase in BMI over 12 months was associated with 10% fewer deaths [START_REF] Kishaba | Body mass index-percent forced vital capacity-respiratory hospitalization: new staging for idiopathic pulmonary fibrosis patients[END_REF]. A recent study of 44 Japanese IPF patients (17) evaluated the prognosis value of FFMI. The FFMI (hazard ratio (HR): 0.64, 95% CI: 0.43-0.94, P=0.02) and percentage predicted FVC (HR: 0.96, 95% CI: 0.93-0.99, P=0.008) were significant predictors of survival. Nutritional status was not correlated with respiratory parameters such as percentage predicted FVC, percentage predicted TLCO, or 6MWT [START_REF] Alakhras | Body mass index and mortality in patients with idiopathic pulmonary fibrosis[END_REF][START_REF] Nishiyama | Fatfree mass index predicts survival in patients with idiopathic pulmonary fibrosis[END_REF]. We found that the percentage predicted TLCO was significantly lower in IPF patients with a low FFMI. It is now clearly needed to determine whether the prognostic prediction could be improved by combining nutritional and respiratory parameters. A low serum albumin was independently associated with increased mortality in 1269 patients with idiopathic interstitial pneumonia on the waiting list for lung transplantation in the US [START_REF] Zisman | Serum albumin concentration and waiting list mortality in idiopathic interstitial pneumonia[END_REF]. The clinical profiles of the patients included in these studies differed from those of our patients. In Kishaba et al. study, most of the patients (74%) were treated with prednisone alone or prednisone plus ciclosporin [START_REF] Kishaba | Body mass index-percent forced vital capacity-respiratory hospitalization: new staging for idiopathic pulmonary fibrosis patients[END_REF]. In Nishiyama et al. study, the patients had lower BMIs, only one had been diagnosed as IPF with a surgical lung biopsy, a lower TLCO, but young patients and those treated with anti-fibrotics ( pirfenidone or nintedanib), or on long-term oxygen therapy were excluded [START_REF] Nishiyama | Fatfree mass index predicts survival in patients with idiopathic pulmonary fibrosis[END_REF]. All those diagnosed with idiopathic interstitial pneumonia before the 2011 guidelines for IPF were published (2) had more severe disease and were eligible to lung transplant [START_REF] Zisman | Serum albumin concentration and waiting list mortality in idiopathic interstitial pneumonia[END_REF]. Our cross-sectional study did not assess the relationship between FFMI and prognosis. A longitudinal study is needed to assess the impact of FFMI on survival according to disease severity, and therapy (oxygen supplements or anti-

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A N U S C R I P T 13 fibrotic medications), in normal clinical practice. Nevertheless, the link between the loss of FFM and prognosis and illness severity emphasises the value of using BIA for managing patients with chronic diseases like IPF.

As expected, those patients with decreased FFMI were relatively old. The fact that patients diagnosed by surgical lung biopsy were less likely to have a low FFMI could be explained by their early diagnosis as they did not have to wait for there to be honeycombing on the chest CT-scan [START_REF] Lee | Clinical findings and outcomes in patients with possible usual interstitial pneumonia[END_REF][START_REF] Yamauchi | Clinical Course and Changes in High-Resolution Computed Tomography Findings in Patients with Idiopathic Pulmonary Fibrosis without Honeycombing[END_REF], indicating more severe disease at the time of nutritional screening. We have no clear explanation why women and non-smokers are so likely to lose FFMI. The mechanisms underlying malnutrition in IPF patients remain unclear. As reported in COPD patients [START_REF] Eid | Inflammatory response and body composition in chronic obstructive pulmonary disease[END_REF][START_REF] Evans | Cachexia: a new definition[END_REF], anorexia, insulin resistance, inflammation, and hypogonadism could all be involved. However, we found no link between food intake or C-reactive protein (CRP) concentration and FFMI. Nevertheless, the mean CRP concentration in our IPF patients (8.2 ± 12.1 mg/L) was higher than those of COPD patients (3-4 mg/L), who are known to suffer from systemic inflammation [START_REF] Agusti | Persistent systemic inflammation is associated with poor clinical outcomes in COPD: a novel phenotype[END_REF][START_REF] Groenewegen | Increased systemic inflammation is a risk factor for COPD exacerbations[END_REF].

We focussed specifically on antifibrotic therapy, but found no difference in the nutritional status of untreated patients and those treated with pirfenidone or nintedanib. However, patients on pirfenidone reported a slight decrease in food intake; this needs to be confirmed.

BIA was chosen as the reference method for assessing FFM because it is easy to use for measuring body composition at the bedside or in outpatients [START_REF] Kyle | Bioelectrical impedance analysis--part I: review of principles and methods[END_REF][START_REF] Kyle | Bioelectrical impedance analysis-part II: utilization in clinical practice[END_REF][START_REF] Thibault | Body composition: why, when and for who?[END_REF], and has been well validated as an accurate measure of FFM and prognosis assessment in COPD patients [START_REF] Disease | Global strategy for the diagnosis, management and prevention of chronic obstructive lung disease[END_REF].

Our experience in this study confirmed the ease-of-use of BIA; all the measurements on all patients were obtained by a single physician (SJ) who had never used BIA before.

Finally, this study has some limitations. Weight loss was not taken into account as a nutritional parameter, because many data were missing. They were all based on patients' recall and so could be not considered as precise objective data. A longitudinal study is needed Stéphane Jouneau has received fees, funding or reimbursement for national and international conferences, boards, expert or opinion groups, research projects over the past 5 years from Actelion, AIRB, Astra Zeneca, BMS, Boehringer, Chiesi, Gilead, GSK, LVL, Mundipharma, Novartis, Pfizer, Roche, Savara-Serendex. Ronan Thibault designed the Simplified Evaluation of Food Intake® (SEFI®) (Knoë, le Kremlin Bicêtre, France) tool, and received royalties.

Acknowledgements:

The authors thank the 'Association pour l'aide aux insuffisants respiratoires de Bretagne (AIRB)' for providing the bioelectrical impedance analyser, and Dr Owen Parkes for the English language editing of the manuscript. Fat-free mass index (FFMI) was determined by bioimpedance analysis, calculated as: fat-free mass (kg)/(height (m) 2 , and considered to be low or impaired (< 17 in men) and (<15 in women) as for COPD patients [START_REF] Vestbo | Body mass, fat-free body mass, and prognosis in patients with chronic obstructive pulmonary disease from a random population sample: findings from the Copenhagen City Heart Study[END_REF][START_REF] Schols | Prevalence and characteristics of nutritional depletion in patients with stable COPD eligible for pulmonary rehabilitation[END_REF]. Sensitivity was 100 % for a BMI < 25 and/or CMB <

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  A C C E P T E D M A N U S C R I P T 10 and serum transthyretin. The variables significantly associated with a reduced risk of low FFMI in multivariable logistic regression were BMI, male gender, and smoking. The capacity of MAC to predict low FFMI was assessed by replacing BMI with MAC in the multivariable model. Two variables were then significantly associated with less risk of low FFMI: MAC (OR 0.48 [0.32 -0.70], P=0.0002), and male gender (OR 0.06 [0.01 -0.46], P=0.0062). We further tested the predictive values of BMI and MAC for low FFMI. The area under the receiver operating characteristic curve assessing low fat-free mass index (FFMI) prediction by BMI was: 0.91 [95% CI, 0.84-0.97] (Figure 1), and the area for MAC was 0.85 [0.76-0.94] (Figure 2), indicating their excellent (BMI) and good (MAC) discriminative powers for low FFMI. An IPF patient with a BMI≥25 and a MAC ≥30 cm was 100% likely to have a normal FFMI (Table

18. 2 ± 2 . 3 )

 223 and the percentage of patients with low FFMI (8/27 (30%) vs. 15/54 (28 %)) were not statistically different in patients with SEFI® score <7 or ≥7. Patients on pirfenidone (6.9 ±A C C E P T E D MA N U S C R I P T 11 2.4) tended to report a lower SEFI® analogue score than patients on nintedanib (7.4 ± 2.7) or who were untreated (8.2 ± 2.3) (P=0.0516).

12 BIA ( 17 )

 1217 , are associated with a poor prognosis. But none of them assessed the prevalence of malnutrition, even based on BMI<21 or low FFMI. Alakhras et al. carried out a retrospective analysis of a US cohort of IPF patients and reported the relationship between BMI and mortality

4 *

 4 Cardiovascular comorbidities included high blood pressure, history of stroke, myocardial infarction, atherosclerosis, etc… A C C E P T E D M A N U S C R I P T

28 Table 4 -

 284 Value of body mass index (BMI) and mid-arm circumference (MAC) for predicting low fat-free mass index (FFMI) in idiopathic pulmonary fibrosis (IPF) patients (n=81).

30, ( 23 /

 23 [START_REF] Ley | A multidimensional index and staging system for idiopathic pulmonary fibrosis[END_REF]; 95 % confidence interval (CI) 88-100%), while specificity was 57 % (33/58; 95 % CI 43-70 %), positive predictive value was 48 % (23/48; 95 % CI 33-63 %) and the negative predictive value was 100 % (33/33; 95 % CI 91-100 %). The BMI and MAC cutoffs associated with low FFMI were assessed by the Youden method.

Figure 1 -

 1 Figure 1-Area under the receiver operating characteristic curve (AUC) assessing body

Figure 2 -

 2 Figure 2-Area under the receiver operating characteristic curve (AUC) assessing mid-

Table 1 -Clinical and demographic characteristics of patients with idiopathic pulmonary fibrosis (IPF).

 1 FVC, forced vital capacity; GAP index, the gender, age and physiology index; TLCO, carbon monoxide diffusion; % pred; percentage of

	1
		All patients	Low FFMI	Normal FFMI	Odds ratio [95%
	Variable	(n=81)	(n=23)	(n=58)	confidence interval]	P value
	Age (years)	74.4 ± 8.6	77.5 ± 6.8	73.1 ± 9.0	1.07 [1.00 -1.15]	0.0375
		(42.0; 68.0; 76.0; 80.0;	(59.0; 74.0; 78.0; 83.0;	(42.0; 68.0; 75.0;
		89.0)	86.0)	79.0; 89.0)
	Gender
	Female	10 (12.3%)	8 (34.8%)	2 (3.4%)	Reference	0.0005
	Male	71 (87.7%)	15 (65.2%)	56 (96.6%)	0.07 [0.01 -0.35]
	Smoking status
	Never	31 (38.3%)	13 (56.5%)	18 (31.0%)	Reference	0.0333
	Yes	50 (61.7%)	10 (43.5%)	40 (69.0%)	0.35 [0.13 -0.94]
	Cough
	No	25 (30.9%)	6 (26.1%)	19 (32.8%)	Reference	0.5578
	Yes	56 (69.1%)	17 (73.9%)	39 (67.2%)	1.38 [0.47 -4.07]
	Dyspnea
	(NYHA stages)
	I	7 (8.6%)	3 (13.0%)	4 (6.9%)	Reference	0.5224
	II	16 (19.8%)	3 (13.0%)	13 (22.4%)	0.31 [0.04 -2.17]
	III	43 (53.1%)	14 (60.9%)	29 (50.0%)	0.64 [0.13 -3.28]
	IV	15 (18.5%)	3 (13.0%)	12 (20.7%)	0.33 [0.05 -2.37]
	Digital clubbing
	No	53 (65.4%)	13 (56.5%)	40 (69.0%)	Reference	0.2883
	Yes	28 (34.6%)	10 (43.5%)	18 (31.0%)	1.71 [0.63 -4.62]

2

Table 2 -Nutritional assessment of patients with idiopathic pulmonary fibrosis (IPF) (n=81).

 2

	7
		All patients	Low FFMI	Normal FFMI	Odds ratio [95%
	Variable	(n=81)	(n=23)	(n=58)	confidence interval] P value
	Clinical parameters
	Weight (kg)	73.5 ± 11.4	60.7 ± 6.5	78.6 ± 8.6	0.69 [0.58 -0.82]	<0.0001
		(41.6 ; 64.0 ; 73.0	(41.6 ; 57.4 ; 61.0	(61.0 ; 73.0 ; 77.0 ; 86.0 ;
		; 82.0 ; 95.0)	; 65.0 ; 72.0)	95.0)
	Body mass index	26.3 ± 3.3	23.2 ± 2.0	27.6 ± 2.9	0.42 [0.27 -0.64]	<0.0001
		(17.3 ; 23.9 ; 26.0	(17.3 ; 21.9 ; 23.5	(22.2 ; 25.7 ; 27.5 ; 29.7 ;
		; 29.0 ; 35.3)	; 24.5 ; 27.2)	35.3)
	Body mass index < 21
	No	78 (96.3%)	20 (87.0%)	58 (100.0%)	Reference
	Yes	3 (3.7%)	3 (13.0%)	0 (0.0%)	19.98 [0.63 -635.32] 0.0208
	SEFI® score	7.7 ± 2.5	7.8 ± 2.8	7.6 ± 2.4	1.03 [0.85 -1.26]	0.4560
		(1.0 ; 5.1 ; 8.6 ;	(1.0 ; 5.0 ; 9.5 ;	(2.5 ; 5.1 ; 8.0 ; 10.0 ;
		10.0 ; 10.0)	10.0 ; 10.0)	10.0)
	SEFI® score < 7
	No	54 (66.7%)	15 (65.2%)	39 (67.2%)	Reference
	Yes	27 (33.3%)	8 (34.8%)	19 (32.8%)	1.09 [0.40 -3.03]	0.8617
	Mid-arm circumference	29.4 ± 2.7	27.2 ± 2.0	30.3 ± 2.4	0.50 [0.35 -0.70]	<0.0001
	(cm)	(21.0 ; 27.5 ; 29.0	(21.0 ; 26.0 ; 27.0	(24.5 ; 29.0 ; 30.0 ; 32.0 ;
		; 31.0 ; 35.0)	; 28.5 ; 31.0)	35.0)
	TSF (mm)	7.1 ± 2.3	5.9 ± 2.0	7.6 ± 2.2	0.66 [0.51 -0.87]	0.0017

Table 3 -Logistic regression multivariable analysis of factors associated with malnutrition, defined by low fat-free mass index (n = 81).

 3 The Odds ratio for continuous variables (body mass index) is given for 1-point increases.

		Odds Ratio [95%
	Variables	confidence interval] P value
	Body mass index 0.26 [0.12 -0.54]	0.0003
	Male gender	0.02 [0.00 -0.33]	0.0055
	Tobacco use	0.10 [0.01 -0.75]	0.0243
	Fat-free mass index was calculated as: fat-free mass (kg)/(height (m) 2 ; below 17 was
	considered to be low or impaired for men and below 15 for women, as for COPD patients (8,
	20).

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A N U S C R I P T 14 to assess the predictive value of weight loss for assessing FFMI loss and disease prognosis. We used the FFMI cut-off values recommended for COPD patients. Nishiyama et al. used the median of FFMI to split their 44 IPF patients [START_REF] Nishiyama | Fatfree mass index predicts survival in patients with idiopathic pulmonary fibrosis[END_REF]. The cut-off was 16.6 kg/m² for both genders, which is quite similar to the COPD cut-offs we used: women <15 and men <17.

However, more studies are needed to determine the optimal cut-off for defining malnutrition in IPF patients. We conclude that malnutrition (i.e. low FFMI measured by BIA) is highly prevalent (nearly one third) in IPF patients. Therefore, malnutrition screening should become systematic, based on BMI and MAC that are good clinical indicators of low FFMI. Based on these indicators sensitivity, specificity, positive predictive value, and negative predictive value (Figures 1 and2, and Table 4), we propose a two-step assessment for malnutrition in IPF patients: 1) first step: measure BMI and MAC; if BMI ≥ 25 and MAC ≥ 300 mm, patient is likely not malnourished; if BMI<21 or MAC <295 mm, the patient is likely malnourished: dietician intervention is needed. 2) For all other situations, go to the second step: FFMI measurement by BIA: malnutrition if FFMI <15 (women) or <17 (men). Future studies should assess whether nutritional intervention targeted to FFM, e.g. pulmonary rehabilitation, could change IPF patient outcome.

Statement of authorship

All authors should have made substantial contributions: SJ and RT conceived, and designed the study, analysed, interpreted the data, and drafted the article; SJ, MK, ML, SG, and LV collected the data; CR analysed the data; BD conceived and designed the study; all authors approved the final version to be submitted. Qualitative variables: number (%). Quantitative variables: mean ± standard deviation (min; Q1; median ; Q3; max). FFMI, fat-free mass index ;

Conflict of interest statement