Douwe Kamsma

Pascal Bochet

Felix Oswald

Nander Ablas

Sophie Goyard

J L Gijs

Wuite

Erwin J G Peterman
email: e.j.g.peterman@vu.nl

Thierry Rose
email: rose@pasteur.fr

Single-Cell Acoustic Force Spectroscopy (scAFS): Resolving kinetics and strength of T-cell adhesion to fibronectin

Keywords: scAFS, single-cell, acoustic force spectroscopy, adhesion strength, adhesion kinetics, CD4, T-lymphocytes, fibronectin, integrin, ECM, extracellular matrix, rupture force, mechanobiology

Assessing strength and kinetics of molecular interactions of cells with the extracellular matrix is fundamental to understand cell-adhesion processes. Given the relevance of these processes, there is a strong need for physical methods to quantitatively assess the mechanism of cell adhesion at the singlecell level, allowing discrimination of cells with different behaviours. Here we introduce single-cell Acoustic Force Spectroscopy (scAFS), an approach that makes use of acoustic waves to exert controlled forces, up to 1 nN, to hundreds of individual cells in parallel. We demonstrate the potential of scAFS by measuring adhesion forces and kinetics of CD4 + T-lymphocytes (CD4) to fibronectin. We determined that CD4 adhesion is accelerated by interleukin-7, their main regulatory cytokine, while CD4 binding strength remains the same. Activation of these cells likely increases their chance to bind to the vessel wall in the blood flow to infiltrate inflamed tissues and locally coordinate the immune response.

INTRODUCTION

Cell adhesion to the extracellular matrix (ECM) is not only central to tissue assembly and repair, but also to immune surveillance and response [START_REF] Ley | Getting to the site of inflammation: the leukocyte adhesion cascade updated[END_REF]. Adhesion kinetics and strength are currently measured with atomic force microscopy (AFM) [START_REF] Benoit | Discrete interactions in cell adhesion measured by single-molecule force spectroscopy[END_REF][START_REF] Lehenkari | Single integrin molecule adhesion forces in intact cells measured by atomic force microscopy[END_REF][START_REF] Li | Force measurements of the alpha5beta1 integrinfibronectin interaction[END_REF], surface plasmon resonance technology (SPR) [START_REF] Kim | Study of cell-matrix adhesion dynamics using surface plasmon resonance imaging ellipsometry[END_REF], fluid-flow devices [START_REF] Lu | Microfluidic shear devices for quantitative analysis of cell adhesion[END_REF], shear-spinning disks [START_REF] Boettiger | Quantitative measurements of integrin-mediated adhesion to extracellular matrix[END_REF][START_REF] Friedland | Mechanically activated integrin switch controls alpha5beta1 function[END_REF][START_REF] Garcia | Force required to break alpha5beta1 integrin-fibronectin bonds in intact adherent cells is sensitive to integrin activation state[END_REF], centrifugation methods [START_REF] Reyes | A centrifugation cell adhesion assay for high-throughput screening of biomaterial surfaces[END_REF] or micropipette aspiration [START_REF] Hogan | Characterizing cell adhesion by using micropipette aspiration[END_REF] . Accurate measurements of celladhesion kinetics and strength absolutely require large and well-defined datasets, in order to grasp the heterogeneity in cell behavior of cell subsets and to capture rare events. Here we present a massively Manuscript 2 parallel approach that allows such accurate force control while continuously monitoring many cells using optical microscopy.

It has been shown that acoustic forces can be applied directly to manipulate cells [START_REF] Marx | Biophysics: using sound to move cells[END_REF] or for flowsorting purposes according to their density [START_REF] Laurell | Chip integrated strategies for acoustic separation and manipulation of cells and particles[END_REF] or their size [START_REF] Petersson | Free flow acoustophoresis: microfluidic-based mode of particle and cell separation[END_REF]. Recently, we presented acoustic force spectroscopy (AFS) as a new single-molecule method to apply wellcontrolled forces up to hundreds of pN to single (bio)molecules with standing acoustics waves, using microspheres as force transducers [START_REF] Sitters | Acoustic force spectroscopy[END_REF]. Here we show that cells have by themselves enough acoustic contrast such that forces on the order of nN can be applied to them directly, allowing accurate determination of their interactions with the ECM. We call this method single-cell acoustic force spectroscopy (scAFS).

scAFS is performed in a transparent microfluidic flow chamber that can be combined with any optical microscope (Figure S1). Well-controlled high forces in the nN range can be applied to hundreds of cells in parallel with scAFS, while tracking their positions in three dimensions in real time. We demonstrate the potential of scAFS by measuring the adhesion process of human primary CD4 + T-lymphocytes (CD4). In the human body, CD4 escape the blood stream upon activation, bind to the blood-vessel endothelial cells near inflamed areas, migrate through the endothelium and infiltrate inflamed or infected tissues as illustrated in Figure 1 [START_REF] Butcher | Leukocyte-endothelial cell recognition: three (or more) steps to specificity and diversity[END_REF][START_REF] Ley | Getting to the site of inflammation: the leukocyte adhesion cascade updated[END_REF][START_REF] Schnoor | Crossing the Vascular Wall: Common and Unique Mechanisms Exploited by Different Leukocyte Subsets during Extravasation[END_REF][START_REF] Springer | Traffic signals for lymphocyte recirculation and leukocyte emigration: the multistep paradigm[END_REF]. Integrins expressed on CD4 are inactive in their resting state and numerous studies describe their increased adhesion upon stimulation with various antigens, chemokines and cytokines [START_REF] Dustin | T-cell receptor cross-linking transiently stimulates adhesiveness through LFA-1[END_REF][START_REF] Kinashi | Overview of integrin signaling in the immune system[END_REF]. Here, we quantify the effect of Interleukin-7 (IL7) activation [START_REF] Cimbro | IL-7 induces expression and activation of integrin alpha4beta7 promoting naive Tcell homing to the intestinal mucosa[END_REF][START_REF] Kondrack | Interleukin 7 regulates the survival and generation of memory CD4 cells[END_REF][START_REF] Mazzucchelli | Interleukin-7 receptor expression: intelligent design[END_REF][START_REF] Tamarit | Membrane microdomains and cytoskeleton organization shape and regulate the IL-7 receptor signalosome in human CD4 T-cells[END_REF] on the binding kinetics and strength of CD4 to fibronectin, a major component of the ECM targeted by integrins [START_REF] Garcia | Force required to break alpha5beta1 integrin-fibronectin bonds in intact adherent cells is sensitive to integrin activation state[END_REF][START_REF] Li | Force measurements of the alpha5beta1 integrinfibronectin interaction[END_REF]. This simplified model of CD4 adhesion serves as a testbed to demonstrate the capabilities of scAFS in quantitative studies of cell adhesion.

RESULTS

Manipulating cells with acoustic forces

In our scAFS experiments, the flow chamber is coated with fibronectin, commonly used to mimic the ECM or integrin targets lining the endothelium of blood vessels (Figure S1). CD4, purified from healthy donor blood samples, are injected into the AFS chamber and allowed to settle down on the fibronectinfunctionalized bottom surface (Figure 2A,B). Subsequently, a standing acoustic wave is generated in the flow chamber. The acoustic frequency defines the position of the nodal plane, while the amplitude determines the magnitude of the acoustic force. When acoustic force is applied, unbound cells move towards the nodal plane, while adherent cells remain attached to the surface (Figure 2C,D). Unbound and adherent cells can be discriminated on the basis of their diffraction patterns in a bright-field microscopy image, which changes when a cell moves away from the optical focal plane (Figure 2D,E). The position of each cell can be determined from its diffraction pattern in real time in three dimensions, using quadrant interpolation (van Loenhout et al., 2012) and a look-up table [START_REF] Sitters | Acoustic force spectroscopy[END_REF], with an accuracy of 2.0 nm in x and y, and 72 nm in z (Figure S2). Given that only μm-scale observations are required for the experiments presented here, this accuracy provides a large margin for inaccuracies due to changes in cell shape. In a typical experiment, an acoustic force of ~10 pN is applied for ~2 s, the minimal force required to push unbound cells upward to the nodal plane. Subsequently, the force is switched off and the cells sediment back to the bottom glass surface (Figure 2G). For unbound cells, substantial movements are observed in the xy-plane (Figure 2F), due to free diffusion and weak acoustic pressure deviations in this plane [START_REF] Spengler | Microstreaming effects on particle concentration in an ultrasonic standing wave[END_REF], as can be observed in Figure S3A. In contrast, the xy-and z-positions of bound cells remain unchanged. These results demonstrate that, with scAFS, force can be applied to the cells, while tracking their individual positions in the field of view (in our instrument: 1.8 mm 2 ), allowing detailed investigation of their adhesion to the fibronectin-functionalized surface.

Three binding stages of adhering cells

In order to quantify the kinetics of CD4 adhesion to fibronectin, we apply a minimal acoustic pulse every two minutes, 9 times in a row, while continuously imaging the cells. From the images, cells are identified and selected automatically. Clustered cells are excluded after visual inspection. Using this approach, we typically track several hundreds of cells simultaneously in three dimensions. Three populations of cells are distinguished based on their xyz-trajectories (Figure 3): "unbound", "binding" and "bound" cells. Unbound cells move upward each time an acoustic force is applied, indicating that they are not bound to fibronectin. These cells move substantially in x and y when elevated by the acoustic force and some can shift more than others due to the weak local lateral acoustic pressure deviations. Binding cells show substantial shifts in the xy-plane along the bottom surface (1-3 m), without moving in the z-direction. These cells appeared to be crawling, in the process of adhering, but not completely immobilized yet. Bound cells do not move upward upon acoustic-force application and shift only minimally in the xy-plane (<1 m). Based on these observations, we use xy-shifts of 1 and 3 μm as boundary values to classify the cells in the three categories.

IL7 accelerates CD4 adhesion

To further assess the progression from unbound to bound cells, we measure the adhesion status of cells with a minimal acoustic pulse at 5, 20, 40 and 60 minutes after cell injection in the AFS chamber. Applying only four acoustic pulses minimizes the perturbation of the cell-adhesion process. Figure 4A shows superimposed image pairs before and after the acoustic pulse for non-activated and IL7-activated CD4 after 20 minutes of incubation (see Figure S3 for 5, 40 and 60 min). Whisker plots in Figure 4B display the xy shifts of these cells 20 minutes after injection under different conditions. Addition of peptide inhibitors, which targeting the integrins binding fibronectin through its RGD motif [START_REF] Bernhagen | High-Affinity RGD-Knottin Peptide as a New Tool for Rapid Evaluation of the Binding Strength of Unlabeled RGD-Peptides to alphavbeta3, alphavbeta5, and alpha5beta1 Integrin Receptors[END_REF], results in substantially decreased binding of cells to the fibronectin surface (Figure 4D). In the absence of fibronectin no adhesion of cells is observed (Figure 4B). These observations confirm that adhesion is mediated by integrin-fibronectin interactions. In the presence of fibronectin, IL7 activation increases by 44% the fraction of immobilized cells from 27% to 39% (Figure 4B). To illustrate the progression of cell binding, the shifts in xy-position of the cells are plotted as a cumulative distribution function (CDF) (Figure 4C). CDFs show the three cell subsets described above: bound, binding and unbound cells. The percentages of cells in the bound state are plotted at different time points, in the presence or absence of IL7 activation (Figure 4E). These results show that the fraction of bound cells increases with incubation time. While two thirds of the cells are bound after 60 minutes independently of their activation status, the adhesion process is substantially faster for IL7-activated CD4.

Calibration of the acoustic force acting on the cells

Determining the binding strength of CD4 to fibronectin-functionalized surface requires calibration of the acoustic forces acting on the cells. Since cells vary substantially in size, density and stiffness, it is imperative to calibrate the forces acting on a representative number of cells. To this end, we measured the Stokes' drag force from the upward velocity (in the z direction) of each CD4 when pushed towards the acoustic nodal plane. Buoyancy and gravity acting on the cells can be calculated independently based on their size and weight. The acoustic force is in balance with these three forces and can thus be determined for each individual cell [START_REF] Kamsma | Tuning the Music: Acoustic Force Spectroscopy (AFS) 2.0[END_REF] (Figure S4). Cell velocities are measured during application of successive acoustic pulses of increasing amplitude, spaced by ~1 minute to allow the cells to sediment back to the bottom of the AFS chamber (Figure 5A). The cells' upward velocity (slope at the inflexion point) during acoustic pulses increases with the acoustic amplitude, while the cell sedimentation velocity stays the same (Figure 5B). From these data, we calculated the force acting on each cell as a function of the amplitude of the electric voltage (Vpp) applied to the piezoelectric element and obtained quadratic scaling in accordance with theory [START_REF] Settnes | Forces acting on a small particle in an acoustical field in a viscous fluid[END_REF]. We compared the calibration for IL7-activated and non-activated cells from different donors and found that the calibration is indeed similar (Figure 5C).

Binding strength of unbound, binding and bound CD4

In order to measure the adhesion strengths to fibronectin of CD4, we applied a voltage ramp. We calibrated the forces acting on each cell during the ramp using calibration parameters obtained from separated measurements on a subset of cells (Figure 5C). In such an experiment we observe that most bound cells show an elevation in two steps (Figure 5D). In the first step, the cells are elevated by less than 2 m without moving in the xy-plane. In the second step, these cells are elevated to the acoustic node and also move substantially in the xy-plane (Figure S5D,F). We interpret the first step as either an extension of fibronectin fiber or a deformation of the cells which remain bound to the fibronectin-coated surface, and the second step as the actual rupture of fibronectin-integrin bonds (Figure 5D). This method to measure the force causing bond rupture is detailed in Figure S5. We note that rupture force is defined here as the force at which the last interaction between cell and fibronectin breaks and the cell moves up from the surface. In order to demonstrate that the fibronectin is not detaching from the surface during the application of acoustic force, we covalently attach microspheres to the fibronectin and observe that all microspheres remain attached after applying 500 pN (Figure 5E). The maximal observed extension of glassadsorbed fibronectin is 150 nm, with a resolution of 72 nm in the z direction.

Before measuring CD4 rupture forces, we determined whether cells were unbound, binding or bound by repeatedly applying minimal force pulses. Then we applied a linear force ramp and determined at what force each cell ruptures from the fibronectin-coated surface (Figure S5F). Box plots of the rupture forces are clearly different for the three classes of cells (Figure 6A), with median values of 9, 39 and 100 pN (unbound, binding and bound, respectively) for non-activated and 15, 39 and 112 pN for IL7-activated cells. The distributions of rupture forces show clear overlap for the three subsets (Figure 6C) and are similar from one blood donor to another (Figure S6). The binding strength is not affected by IL7-activation, while, as a result of the faster binding kinetics (Figure 4E), the proportion of bound cells is increased (Figure 6B).

DISCUSSION

We have resolved the adhesion strength and kinetics of individual CD4 binding to fibronectin. Three classes of cells could be distinguished: unbound, binding and bound. Interaction strengths were below 30 pN for unbound cells, below 55 pN for transient binding and crawling cells, and from 55 to hundreds of pN for bound cells. In AFM experiments the average rupture force of a single integrin-fibronectin bond has been shown to be ~40 pN at a loading rate of 20 pN/s [START_REF] Li | Force measurements of the alpha5beta1 integrinfibronectin interaction[END_REF]. This single-bond rupture force suggests that the unbound, binding, or bound cells that we characterized were held by zero, one, or several integrin bonds, respectively. The adhesion strength was not affected by IL7-activation, but adhesion kinetics was. This accelerated kinetics could be necessary for the cells to resist the shear force (~150 pN) due to the blood flow challenging cell adhesion. The shear force is about four times the strength of a single integrinfibronectin bond, which suggests that IL7 triggers the inside-out integrin activation pathway, resulting in faster binding kinetics. Nevertheless, the slower, but same-strength outside-in integrin activation pathway is still available for non-activated cells not experiencing shear stress. In capillaries, 1800-2000 CD4 per microliter of blood are carried by a flow speed of 2 mm/s. CD4 roll over endothelial cells held by selectinligand interactions with a rate of 10 m/s. The relatively small differences in kinetics we observed here, might be enough to favor the binding of IL7-activated cells with integrins activated by inside-out pathways. On the contrary, stochastic contacts with the ECM might be too short-lived in non-activated cells for the first integrin to activate the outside-in pathway [START_REF] Hynes | Integrins: versatility, modulation, and signaling in cell adhesion[END_REF][START_REF] Hynes | Integrins: bidirectional, allosteric signaling machines[END_REF].

With these measurements, we demonstrate that scAFS can be used to study the adhesion process of hundreds of cells in parallel in real time using well-controlled forces. Because the parameters that influence the acoustic force experienced by cells, i.e. size, shape and density, are very homogeneous in CD4 (see online methods) [START_REF] Laurell | Chip integrated strategies for acoustic separation and manipulation of cells and particles[END_REF][START_REF] Petersson | Free flow acoustophoresis: microfluidic-based mode of particle and cell separation[END_REF], we could calibrate a subset of cells and use the calibration parameters obtained for the whole population. Calibration of all cells individually would, however, increase the accuracy of the rupture force determination and may be required for cell types with more heterogeneity. Here, we have applied forces up to 500 pN to adherent CD4. Since the maximum output voltage that can be applied (42 Vpp) to the piezo element with our current system, we can estimate that forces as high as 1 nN can be reached for these cells. Such forces are high enough to rupture multiple integrin-fibronectin bonds as shown here, or other cell adhesion systems in the early steps of adhesion such as integrins with CAM, VCAM and MADCAM ligands [START_REF] Ley | Getting to the site of inflammation: the leukocyte adhesion cascade updated[END_REF] or T-cell receptors with peptide-MHC complexes [START_REF] Liu | Accumulation of dynamic catch bonds between TCR and agonist peptide-MHC triggers T cell signaling[END_REF]. However 1 nN will not be enough force to detach completely spread-out cells from a surface.

We performed measurements at room temperature and only fibronectin was used to mimic the ECM, a simplification in order to demonstrate the potential of the scAFS method. In vivo, the blood vessel wall is composed of endothelium cells, which express integrin ligands or ECM induced while activated, and in future experiments endothelium cells could be grown inside the flow chamber at 37 °C, providing a more realistic model for the vessel wall. When endothelium cells spread out, they cannot be detached by the acoustic force. T-cells could be flushed in such a prepared flow chamber, allowing one to investigate the full complexity of these cell-cell interactions using scAFS.

CONCLUSION

scAFS is a novel method that can be used to obtain insight into the cell adhesion process, it is performed in a closed fluidics system, allowing precise control of parameters such as temperature, flow rate and gases dissolved in the medium, which allows keeping the sample sterile and the operator safe. Given the volume of the AFS chamber (5.4 L) measurements can be performed on small biological sample volumes, obtained for example from patients or small animals. This approach should be instrumental in the measurement of T-cell adhesion alteration associated with pathologies in diagnosis development or in drug screening [START_REF] Ley | Integrin-based therapeutics: biological basis, clinical use and new drugs[END_REF]. Finally, the relative simplicity and compactness of the system allows straightforward integration in advanced fluorescence microscopes. Taken together, this illustrates that acoustic forces can be applied directly to cells in order to assess quantitatively their interactions with their environment, opening up a wide range of potential applications in research and the clinic.

Methods

Blood sampling and cell preparation

Blood samples from healthy donors were provided by a blood center (Etablissement Français du Sang, Centre Necker-Cabanel, Paris). CD4 were separated by negative selection (RosetteSep Kit, StemCell) as described previously [START_REF] Tamarit | Membrane microdomains and cytoskeleton organization shape and regulate the IL-7 receptor signalosome in human CD4 T-cells[END_REF]. CD4 were equilibrated for 18 hours in RPMI 1640 medium (Lonza) supplemented with Hepes (10 mM, Sigma-Aldrich), penicillin 50 U/mL, streptomycin 50 g/mL (Sigma) and heat-inactivated fetal bovine serum (FBS 10%, Lonza, uncomplemented at 53 °C during 45 min, containing 50mg of proteins per mL from which 40 mg/mL of BSA) and placed in an incubator at 37 °C, 5% CO2 in a humidified atmosphere. CD4 were activated with 2 nM of recombinant glycosylated human IL7 expressed from HEK cells (Abcys) at 37 °C, 5% CO2 for 15 minutes prior to injection in the scAFS flow chamber at room temperature.

Experimental setup, cell imaging

The AFS chip itself consists of a flow chamber and a piezoelectric element (LUMICKS b.v., AFS module). The fluid chamber surface area was 54 mm 2 , 12 mm 2 under each of the two piezos (Figure S1). The functionalization of the flow chamber was performed by injecting 30L of bovine fibronectin solution (5 g/mL diluted in PBS, Sigma-Aldrich) incubated for 30 min at room temperature as described previously [START_REF] Boettiger | Quantitative measurements of integrin-mediated adhesion to extracellular matrix[END_REF]. The chamber was saturated with 30 L of RPMI medium completed with 1% FBS for 15 min then washed with 200L of the same medium (40 volumes of the chamber). For assessment of CD4 adhesion, 30 L of non-activated or IL7-activated CD4 suspensions in RPMI medium, completed with Hepes (10 mM final) and 1% FBS (0.5 mg of proteins /mL final), was injected in the chamber and incubated at room temperature. The piezoelectric element attached to the flow chamber was driven with a function generator (Siglent, SDG830) providing oscillating current amplified by a RF-amplifier (SCD, ARS 2_30_30, 50 Ω impedance, 10 W maximum output power). A maximum driving voltage of 42 Vpp was applied in these experiments at 14.3 MHz for not more than a few seconds, this did not lead to sample heating of more than two degrees. Part of the data was acquired using a LUMICKS AFS Stand-alone instrument. Images were acquired with a bright field inverted microscope (Nikon Eclipse Ti). Here, an LED light source (Thorlabs, M660L4) was used in combination with an air objective lens (Nikon, CFI Plan Fluor 10X/0.30 NA, field of view 1.8 mm 2 ). To regulate the sample z-position, a piezo translation stage (PI, P-517.2CL) was mounted on the microscope and driven by a digital piezo-controller (PI, E-710.4CL). Images were taken with a CMOS camera (Thorlabs, DCC1545M, 1280x1024 pixels) with a full-frame rate of 60 Hz.

Cell tracking

Acquired images were processed in real time to extract the cell positions in three dimensions. To determine the xy-positions, a quadrant interpolation algorithm was used (van Loenhout et al., 2012). A look-up table (LUT) was used to determine the z-position [START_REF] Gosse | Magnetic tweezers: micromanipulation and force measurement at the molecular level[END_REF]. The LUT was built from image series of cells seating on the glass surface in the absence of acoustic force for cell individually. Images of seated cells were acquired starting from the cells completely in focus up to 30 µm above the focus, with 100 nm steps. The diffraction rings of CD4 were used to interpolate the xyz-positions of the cell centers. The precision of the tracking was determined by calculating the standard deviation of a bound cell during 8 seconds at 60 Hz, resulting in an accuracy of 2.0 nm x and y, and 72 nm in z (Figure S2). The tracking software is available at http://figshare.com/articles/AFS_software/1195874. For the real-time tracking of 300 cells in parallel, a fast PC (including two Xeon E5 2643v2 processors) running National Instruments LabView is used. Additionally, a moving ROI was implemented to adjust all the ROIs, frameto-frame, bases to the previously determined xy-position. Separate calibration of cells takes only a few minutes, including data processing.

Validation of the integrin-fibronectin bonds

The specificity of the CD4 adhesion to fibronectin-functionalized glass through integrins has been validated using competitive peptide inhibitors: Arg-Gly-Asp and Gly-Arg-Gly-Asp-Ser (Sigma-Aldrich) [START_REF] Bernhagen | High-Affinity RGD-Knottin Peptide as a New Tool for Rapid Evaluation of the Binding Strength of Unlabeled RGD-Peptides to alphavbeta3, alphavbeta5, and alpha5beta1 Integrin Receptors[END_REF]. Peptide solutions were added to non-activated or IL7-activated CD4 + T-cell suspensions in RPMI medium completed with 1% fetal bovine serum (containing 40mg/mL of BSA, 0.4mg/mL final) and 50mM Hepes. Peptide/cell solutions of 10 -7 , 10 -6 , 10 -5 , 10 -4 , 10 -3 or 10 -2 M of RGD or GRGDS were prepared. Peptide/cell samples were injected in the chamber and incubated at room temperature. Measurements have been performed in duplicate using CD4 isolated from three blood donors.

Acoustic force calibration on cells

The acoustic radiation force Frad has been calibrated using the method previously described by Kamsma et al. [START_REF] Kamsma | Tuning the Music: Acoustic Force Spectroscopy (AFS) 2.0[END_REF] . Here the acoustic force was determined by writing down the force balance during the uplift of unbound cells. Acceleration was neglected, because the measurements were performed in the low Reynolds number regime:

Frad -Fgravity + Fbuoyancy -Fdrag = 0

(1)

Fgravity, Fbuoyancy and Fdrag are the gravitation, buoyancy and drag forces, respectively. The radiation force resulted from the calculation of the other forces:

Fgravity = 4/3  r 3 cell g (2) Fbuoyancy = 4/3  r 3 medium g (3) Fdrag = vcell faxen (4)
The CD4 are nearly perfect spheres with a radius rcell of 4.01 ± 0.13 m (n = 463). Radii were computed from optical microscopy from the 2D projection surface area of individual cell using ImageJ assuming perfect spheres. The density cell of CD4 is 1030 ± 20 kg•m -3 , determined from isopycnic sedimentation.

The gravitational acceleration g is 9.81 m•s -2 . The density of medium medium (RPMI/10% FBS) is 1008.4 kg•m -3 , as determined using a gauged flask at 23 °C. Faxen's drag coefficient faxen [START_REF] Schaffer | Surface forces and drag coefficients of microspheres near a plane surface measured with optical tweezers[END_REF] was used to determine the drag force on the cells; this takes into account the hydrodynamic surface effect.

The dynamic viscosity medium of the medium is 0.999 ± 0.007 mPa•s, as measured with an Ostwald's u-tube viscosimeter at 23 °C. The velocity of the cell vcell was calculated by taking the derivative of the cell zposition versus time.

The cell sedimentation velocity, after acoustic elevation, was measured to verify the parameters used. Cells had a constant velocity of sedimentation for about 10 seconds, until they slowed down in close proximity of the glass surface due to the increase of the viscosity, as described by Faxen's law [START_REF] Schaffer | Surface forces and drag coefficients of microspheres near a plane surface measured with optical tweezers[END_REF]. The sedimentation apparent velocity of cells in the absence of acoustic pressure is given by: vsedimentation = 4/3r 3 g (cell -medium) / (6r) = 2 (cell -medium) rcell 2 g / (9 )

(5)

The sedimentation velocities of the individual CD4 were measured till the cell was reaching one diameter above the glass surface (8 m), resulting vsedimentation = 1094 ± 33 nm•s -1 (n =10, Figure 2G). Considering that rcell = 4.0 m, it follows that the CD4 have a cell = 1038.7 ± 0.9 kg•m -3 at 23 °C.

The force on the CD4 was calibrated using Expression 1. The elevation velocity of the cells was used to determine the force for each time step (Figure S4A,B). A sine function (the theoretical shape of the force field) was fitted to the force versus cell height plot (Figure S4C). The force Frad was then extrapolated for the cells seated on the bottom surface. The curve fitting was repeated for several acquisitions on multiple cells (n = 14 and 37 for non-activated and IL7-activated cells, respectively) with increasing voltage from 2.1 to 10.5 Vpp. The extrapolated forces Frad versus voltage were plotted in order to verify the quadratic dependence of the force with the amplitude.

In order to quantify the homogeneity of the acoustic field of view, the force per square voltage of ~1500 silica microspheres (6.84 µm in diameter) are calibrated with the same method as described above. The calibration results in a ~30 % standard deviation of the acoustic force over the whole field of view (Figure S4D), this includes the error due to variations in microsphere size (~5% in radius, which will result in ~15% variation in applied force).

Investigating the strength of glass-adsorbed fibronectin

We test if cell detachment is caused by breaking of the cell-fibronectin bonds and not by breaking of the interaction of fibronectin with the glass surface. The glass surface inside the AFS chamber was functionalized with fibronectin (10 g/mL in PBS, 30 min, room temperature) then washed with PBS. Carboxylic acid groups from glass-adsorbed fibronectin were activated by adding a solution of EDC (N-3dimethylaminopropyl-N'-ethylcarbodiimide, 15 L, 2 mM, Sigma-Aldrich) and NHS (N-hydroxysuccinimide, 15 L, 5 mM, Sigma-Aldrich) diluted in PBS and incubated for 15 min at room temperature. Polystyrene microspheres functionalized with amine groups (2-aminoethylated beads, 5 m in diameter, Sigma-Aldrich) were suspended in PBS and then injected in the chamber and incubated for 2 hours. Unbound microspheres were washed away with 200 L of PBS. Forces were calibrated as described above, but using free microspheres in the absence of fibronectin (rbead = 2.5 m, bead = 1500 kg/m 3 ).

Determination of rupture forces

To measure the rupture force of a bound cell, a square-root amplitude ramp was applied, while the cell height is measured. The rupture force Fr was calculated by determining the voltage at rupture. Using the force/(voltage) 2 ratio, the rupture force is given by: Fr = 0.554 10 -12 Ur 2 (tr) (7)

During the force ramp, some cells showed small deformations before rupture, as shown in Figure S5E. These deformations affected the determination of the cell's z-position and exact determination of the rupture event was less evident. We considered a rupture event when the elevation of the cell was larger than one diameter of the cell (8 m). This definition resulted in a time delay between the "real" rupture event time tr and the "considered" rupture time t8 (when reaching 8 m above the glass bottom surface, at amplitude U8) (Figure S5B). The real rupture time as a function of the t8 and the amplitude U8, is given by: tr = t8 -(0.0386 e -(0.372 U 8 ) ) (8)

The time delay (t8 -tr) is shown in (Figure S5B), where the amplitude Ur driving the rupture of the CD4 from the fibronectin-functionalized surface is given by: 𝑈 𝑟 = 𝑈 8 √(

FIGURE LEGENDS

Figure 1: CD4-adhesion mechanism

Three-step mechanism of leukocytes adhering to blood-vessel endothelium while infiltrating inflamed or infected tissues [START_REF] Butcher | Leukocyte-endothelial cell recognition: three (or more) steps to specificity and diversity[END_REF][START_REF] Ley | Getting to the site of inflammation: the leukocyte adhesion cascade updated[END_REF][START_REF] Schnoor | Crossing the Vascular Wall: Common and Unique Mechanisms Exploited by Different Leukocyte Subsets during Extravasation[END_REF][START_REF] Springer | Traffic signals for lymphocyte recirculation and leukocyte emigration: the multistep paradigm[END_REF].

Step 1: unbound CD4 (pink) carried by the blood flow in end-vessels, rolling along the vascular endothelium (brown rectangles), while P-selectin glycoprotein ligand-1 at the CD4 surface bind transiently to endothelial cell adhesion molecules, first to L-selectins (brown sticks), later, upon inflammation to P-selectins (green sticks).

Step 2: chemokines or cytokines (black diamonds) expressed or presented by inflamed endothelial cells, bind their cognate receptors at the surface of CD4 and trigger intracellular signals that activate different kinds of integrin dimers  (pink lollipops) targeting the ECM (41, 51 and 61)and ligands such as ICAM (L2), VCAM (41) and MADCAM (47) (brown baskets) [START_REF] Ley | Getting to the site of inflammation: the leukocyte adhesion cascade updated[END_REF]. CD4 slow down and crawl along the surface.

Step 3: CD4 are immobilized by the formation of multiple integrin-ligand bonds. Subsequently, the CD4 cross the endothelium, and infiltrate the tissue.

SUPLEMENTAL DATA

Supplemental movie:

As shown in Figure 5D, human primary CD4 + T-cells are imaged (60 images/s) when they are subjected during 20 seconds to an acoustic force ramp from 0 to 10.5 Vpp corresponding to forces of 0-55 pN. Weakly bound cells are lifted off the fibronectin-functionalized glass. (A) As described in the experimental setup in Methods, the AFS chip consists of two glass plates (thickness 1 mm (top) and 0.17 mm (bottom)) with a fluid chamber (30 mm long, 1.8 mm wide, 0.1 mm thick, 5.4 mL volume, colored in pink) in between. Two independent transparent piezoelectric elements (7x7 mm) are glued to the upper glass slide. (B) Schematic illustration of the scAFS bright-field imaging method, using a LED, condenser lens, microscope objective and CMOS camera. The z-position of the AFS chip is controlled by a piezoelectric translation stage. (C) Schematic illustration of the transverse plane of the AFS chip (not to scale). An acoustic force gradient is shown (grey scale), with high force at the glass bottom plane and no force at the level of the acoustic node plane. Bound cells stay on the fibronectin, whereas unbound cells are pushed upward to the node. (D) A diagram of the hardware connected electronically to the piezo. A computer controls the function generator that feeds an alternating voltage via the amplifier to the piezoelectric element. (E) A digital camera acquires the images of CD4 in the field of view. (F-I) Images of field of views and zoom in showing CD4 injected in the FN-functionalized fluid chamber of the AFS chip (left) and schematic illustration (right). The objective is focused on the cells seated on the glass bottom surface; (F) no acoustic force is applied. (G, H) A linear acoustic amplitude ramp applies a quadratic force ramp to the cells (14.3 MHz, 0-10.5 Vpp, 20 s), lifting up first unbound cells (G, ~4.2 Vpp) and next binding cells (H, ~10.5 Vpp). Cells cluster together in lines, due to weak acoustic pressure deviations within the xy-plane [START_REF] Spengler | Microstreaming effects on particle concentration in an ultrasonic standing wave[END_REF]. (I) When the acoustic forces are off, all the cells sediment (~20 s), back to the focal plan. This data is also presented in Supplementary Movie. x-position (nm)

Supplemental Text and Figures

x-position (nm)

x-position (nm)

  and equipment funding (Center for Innovation and Technical Research), and by the Pasteur-Weizmann Foundation.AUTHOR CONTRIBUTIONSD.K., F.O., N.A., T.R. acquired scAFS data; S.G. and T.R. have purified, grown and prepared the CD4; D.K., F.O., N.A., P.B. and T.R. have analyzed data; D.K., P.B., G.W., E.P. and T.R. wrote the manuscript. G.W., E.P., and T.R. supervised the project.COMPETING FINANCIAL INTERESTSD.K., G.J.L.W. and E.J.G.P. have filed a patent application (PCT/NL2014/050377) covering the acoustic force spectroscopy method. G.J.L.W. and E.J.G.P. are co-owners of LUMICKS B.V.

Figure 2 :

 2 Figure 2: scAFS on single CD4: manipulation and high-resolution tracking.(A) Sketch showing CD4 (pink) in culture medium (light pink) in the AFS flow chamber, and sedimented on glass (blue) functionalized with fibronectin (FN, orange). (B) Digital image of CD4 on FN-functionalized glass in AFS flow chamber. (C) A standing acoustic wave induces a pressure force field (gray gradient) pushing the unbound cells (blue square) upward (dark, high pressure) to the acoustic node (light pink, low pressure). (D) Same cropped frame as in panel B, after the application of an acoustic wave (14.3 MHz, 4.2 Vpp, 5 s). Bound cells are immobile (orange square, the diffraction pattern is unchanged) and unbound cells have moved up towards the acoustic node, out of focus (blue square, the diffraction pattern has changed). For full fields of view see FigureS1E-H. Image series of a bound and an unbound cell, demonstrating the diffraction pattern of the cells upon application of acoustic force (F and G) xy-and z-position graphs as a function of time of unbound (blue) and bound (orange) CD4. Gray zones indicate the period of application of acoustic waves; black plots the amplitude of the acoustic wave(14.3MHz, 4.2Vpp, 5s). The center positions of CD4 at bottom surface and acoustic node are indicated by horizontal dashed black lines.

Figure 3 :

 3 Figure 3: Deciphering unbound, binding and bound cells from their xy-trajectories and z-elevation. Trajectories of CD4 z-(left) and xy-positions (right) have been plotted for representative cells from free (A), binding (B) and bound (C) subsets. CD4 are subjected to a series of nine acoustic pulses (14.3 MHz, 4.2 Vpp, 2 s), spaced by ~2 minutes as indicated in the plot (A, left). Color coding of the trajectories is used to indicate time correspondence between left and right plots. Purple and orange zones indicate whether cells are in the binding (adhesion process) or bound (immobilization) state, respectively.

Figure 4 :

 4 Figure 4: CD4 adhere faster to fibronectin and get immobilized when activated by IL7. (A, B) CD4 are activated by IL7 (+IL7, n = 666) or not (NA, n = 463) and subsequently injected in nonfunctionalized (-FN) or fibronectin-functionalized (+FN) chambers. The non-activated (NA, green) and IL7activated cells (+IL7, red) are pushed upwards with a minimal force (14.3 MHz, 4.2 Vpp, 2 s) after 5, 20, 40 and 60 minutes of incubation. (A) Images of CD4 before (red) and after (green) acoustic wave application are superimposed (20 minutes of incubation). Immobile cells appear in yellow (superposition of red + green). Bound fractions (xy-shift < 1m) are indicated. Bottom images show zooms of regions indicated by squares in top images. (B) Box plot of shifts in xy-plane of non-activated (green) and IL7-activated (red)

Figure 5 :

 5 Figure 5: CD4 rupture-force calibration and measurement.(A) z-position of a representative unbound CD4 plotted with the voltage of the applied acoustic pulses(2.1, 4.2, 6.3, 8.4, 10.5 Vpp, <2 seconds). (B) Acoustic-pressure induced upward motion of the cell in panel A. Trajectories of different acoustic pulses are superimposed by adjusting time offset. Acoustic pulse is indicated by grey zone. The inset shows trajectories at a different time scale (from 0 to 30 seconds), focusing on sedimentation of cells after application of acoustic pulse (grey vertical line). (C) Force acting on the cell close to the bottom surface, as calibrated from the velocity in panel B, for cells from a representative donor (data are means ± s.d., n = 14 for not-activated and n = 37 for IL7-activated cells). Quadratic fits yield quadratic constants of 0.55 ± 0.25 and 0.54 ± 0.32 pN/Vpp 2 (fit value ± s.d.) for nonactivated and IL7-activated cells, respectively. (D) Application of a linear (Vpp) ramp to a cell to determine rupture force (blue, 14.3 MHz, 0 to 10.5 Vpp). Corresponding complete field of view: see FigureS1E-Hand Supplemental Movie. Most bound cells experience small upward movements (up to 3 m) before rupture occurs. t0 (vertical blue dashed line) indicates the start of acoustic force application, tr (vertical red dashed line) the time of rupture identified here by a displacement of a cell larger than its diameter (8 m). Amplitude of acoustic wave is indicated at bottom (black line). (E-I) The resistance of glass-adsorbed fibronectin to traction has been performed using polystyrene microspheres (5 µm in diameter) covalently bound to the fibronectin-functionalized glass. An upward acoustic force is applied to the beads from 0 to 500 pN in 2 seconds. (G) A representative part of the field of view is shown, boxes indicate the beads selected for xyz-position tracking. Images before (F) and after (G) force application of the same region are superposed (H) and show no detectable lateral shifts of any beads (<200nm; red+green=yellow). (I) The z-position of a representative bead is plotted versus time. The force ramp is indicated by a gray zone. Maximal elevation is 150 nm from the starting position.

Figure 6 :

 6 Figure 6: CD4 rupture-force distribution, effect of IL7. (A) Rupture force distribution of the CD4 from the fibronectin-functionalized surface (for underlying data analyses see Figure S5). Whiskers are maximum and minimum, boxes indicate second and third quartiles framing the median. Medians for unbound, binding and bound are 8.8 (n = 127), 39.8 (n = 41), 99.7 (n = 51) pN for non-activated and 14.8 (n = 160), 39.3 (n = 74), 111.7 (n = 107) pN for IL7-activated cells. Data separated for two representative blood donors are shown in Figure S6. (B) Bar plots of fractions of unbound, binding and bound cells out of non-activated and activated CD4 after 19 minutes of incubation (error bars are s.e.m.). (C) Cumulative probability distribution plot of the rupture forces is shown for unbound, bonding, and bound cell, IL7-activated and non-activated. The horizontal black dashed line indicates 50% of the cell subset. The vertical black dashed line indicates the change of force scale in abscise from 0-55 pN to 55-500pN.

Figure S1 :

 S1 Figure1

Figure S1 :

 S1 Figure S1: Description of the single-cell AFS system to assess cell-adhesion strength, related to Figure 2.

FFigure S2 :

 S2 Figure S2: x, y and z-position tracking analysis and resolution, related to Figure 2. (A, B) xyz-position trajectories an unbound (left) CD4 and a bound (right) CD4. Same data as Figure 2 F,G, split in four panels. cells are seated on the surface of the flow cell (green zone); after 10 seconds, the acoustic force is applied (14.3 MHz, 4.2 V pp , yellow zone); finally, the force is switched off (purple zone). (C, D) xy plot of the data shown in a and b, colors correspond to zones indicated in A and B. (E, F) xy plot of green zone, standard deviations are 36.3 and 1.6 nm for the unbound and bound CD4, respectively. (G, H) trajectories of z-position in the absence of force; standard deviations are 84 nm and 72 nm for the unbound and bound CD4, respectively.

Figure S3 :

 S3 Figure S3: CD4 adhesion kinetics to fibronectin assessed by scAFS, related to Figure 4.

Figure S5 :

 S5 Figure S5: Determination of the exact rupture force of CD4, related to Figure 5.(A) Force calibration was performed by applying increasing acoustic pulses(2.1, 4.2, 6.3, 8.4, 10.5 V pp as indicated for each curve) for ~1 second to CD4 as shown in Figure5A,B. Trajectories of the z-position of a representative cell are plotted. The horizontal green and red dash lines represent 0 and 8 mm elevation, respectively. The time t 0 is the moment of acoustic force application (vertical blue dashed line) and the time t 8 is the moment when the elevation of the cell is 8 mm higher (vertical red dashed line). (B) The time delay t 8 -t 0 is plotted versus the amplitude U 8 and fitted with the Expression 8 in Methods. The five data points obtained from panel A are plotted as open circles. Standard deviation of U 8 and time delay are indicated as error bars (n = 8). (C) The amplitude U 8 is plotted as a function of U 0 for non-activated and IL7-activated CD4 from two donors. The extrapolation of U 8 is plotted as a black line according to the Expression 9 in Methods. Three of the data points from panel A are displayed as open circles, colors are used for the different subsets of cells (not-activated and IL7-activated cells of two different donors). The interpretation of the contributions of cell deformation and bond rupture to the z elevation are indicated as dashed arrows as an example for a single cell. Unbound (D) and bound (E) CD4 are pushed up from the glass surface (horizontal green dashed line, z 0 ) to the node plane (horizontal black dashed line) as shown in the plot of z-position as function of time (lower panels). Vertical cyan and red dashed lines indicate the start of the elevation (t 0 ) and the time of reaching a height of 8 µm (t 8 ), respectively. The dark blue line indicates the linear ramp of the acoustic amplitude. Most bound cells show mild elevation (2-3 mm) after t 0 under the acoustic pressure and only minimal xy-shifts. After bond rupture, cells move swiftly up to the node, while large xy-shifts are observed. The black dashed line indicates the threshold height above which a cell is considered unbound (z 0 + 8 µm). (F) z-position trajectories of an unbound, a binding and a bound CD4 during a typical bond-rupture measurement, with applied voltage indicated. The first 19 minutes are used to identify the cell state, also shown in Figure2A. Subsequently a square-root amplitude ramp (14.3 MHz, 0-42 Vpp, 18 s) is performed, resulting in a linear force ramp (0-970 pN, 53.88 pN/s). The right panel is a zoom in of the amplitude ramp (indicated by the grey zone on the left), providing insight into the elevation of the cells, their residence in the acoustic node and their sedimentation to the bottom glass surface after switching of the acoustic waves.

Bm

  Figure S5: Determination of the exact rupture force of CD4, related to Figure 5.

  Loenhout, M.T.,Kerssemakers, J.W., De Vlaminck, I., and Dekker, C. (2012). Non-bias-limited tracking of spherical particles, enabling nanometer resolution at low magnification. Biophys J 102, 2362-2371.

	(𝑡 8 -𝑡 𝑟 ) 𝑡 𝑚𝑎𝑥	)	(9)
	As shown in Figure S5F, cells were first subjected to a series of nine acoustic pulses (14.3 MHz, 4.2 Vpp, 2
	s) spaced by 2 minutes (blue line) to determine whether they were unbound, binding or bound cells.
	Subsequently, in order to determine the cells' adhesion strength, a square root amplitude ramp (14.3 MHz,
	0-42 Vpp, 18 s) was applied after 19 min providing a linear force ramp (0 -970 pN, 53.88 pN/s).

van

ACKNOWLEDGMENTS

The authors thank Andrea Candelli for helpful discussions (LUMICKS B.V.) and Jenneke Klein Nuland for providing lab facilities needed for cell culture (ACTA, Amsterdam). This work is part of the research program of Future & Emerging Technologies (FET) (E.J.G.P. and G.J.L.W.), which is part of the EU Horizon 2020 program, and supported by the Institut Pasteur through its Transversal Research Program (PTR 424)

The histogram is fitted with a Gaussian function resulting in ~30 % standard deviation of the acoustic force, this includes the error due to the microsphere (~5% in radius, which will result in ~15% variation in applied force).

Click here to access/download Supplemental Videos and Spreadsheets 20171031Cell_SupMovie_SCAFS_Kamsma.avi


Charalampos Saitis

Claudia Fritz

Gary P Scavone

Sounds like melted chocolate: How musicians conceptualize violin sound richness

Keywords: Violin, Semantics, Perception, Acoustics

Results from a previous study on the perceptual evaluation of violins that involved playing-based semantic ratings showed that preference for a violin was strongly associated with its perceived sound richness. However, both preference and richness ratings varied widely between individual violinists, likely because musicians conceptualize the same attribute in different ways. To better understand how richness is conceptualized by violinists and how it contributes to the perceived quality of a violin, we analyzed free verbal descriptions collected during a carefully controlled playing task (involving 16 violinists) and in an online survey where no sound examples or other contextual information was present (involving 34 violinists). The analysis was based on a psycholinguistic method, whereby semantic categories are inferred from the verbal data itself through syntactic context and linguistic markers. The main sensory property related to violin sound richness was expressed through words such as full, complex, and dense versus thin and small, referring to the perceived number of partials present in the sound. Another sensory property was expressed through words such as warm, velvety, and smooth versus strident, harsh, and tinny, alluding to spectral energy distribution cues. Haptic cues were also implicated in the conceptualization of violin sound richness.

INTRODUCTION

The overall goal of the research presented here is to better understand how musicians evaluate violins within the wider context of finding relationships between measurable vibrational properties of instruments and their perceived qualities. Contrary to the typical approach of beginning with a physical hypothesis based on structural dynamics measurements [START_REF] Bissinger | Structural acoustics of good and bad violins[END_REF][START_REF] Fritz | Perceptual thresholds for detecting modifications applied to the acoustical properties of a violin[END_REF] or audio feature extraction [START_REF] Stȇpánek | Rustle as an attribute of timbre of stationary violin tones[END_REF][START_REF] Łukasik | Matching violins in terms of timbral features[END_REF], a method that relies on theoretical assumptions about cognitive-semantic categories and how they relate to natural language [START_REF] Dubois | Categories as acts of meaning: The case of categories in olfaction and audition[END_REF][START_REF] Saitis | Perceptual evaluation of violins: A psycholinguistic analysis of preference verbal descriptions by experienced musicians[END_REF] was used to identify and categorize concepts of violin sound richness emerging in spontaneous verbal descriptions. These were collected during a carefully controlled playing experiment [START_REF] Saitis | Effect of task constraints on the perceptual evaluation of violins[END_REF] and in an online survey where no sound examples or other contextual information was present.

Using the same method in earlier violin playing experiments, whereby skilled string players ranked a set of instruments based on preference and described their criteria through free verbalization tasks [START_REF] Saitis | Perceptual evaluation of violins: A quantitative analysis of preference judgments by experienced players[END_REF], we previously explored how violin quality in general is conceptualised by the musician [START_REF] Saitis | Conceptualization of violin quality by experienced performers[END_REF][START_REF] Saitis | Perceptual evaluation of violins: A psycholinguistic analysis of preference verbal descriptions by experienced musicians[END_REF]. Specifically, eight semantic categories (concepts or meta-criteria) were identified: 1) TEXTURE (distribution of spectral content); 2) RESO-NANCE (intensity "under the ear" and via "felt" vibrations); 3) PROJECTION (intensity "at a distance"); 4) RE-SPONSE (ease of playing and responsiveness); 5) CLARITY (lack of audible artifacts in the sound); 6) BALANCE (of sound and response across strings and registers); 7) INTEREST (affective-hedonic reactions); 8) RICHNESS (amount of spectral content). The latter emerged as a key perceptual factor in assessing violin quality. A statistical analysis of the preference judgments collected in the same and subsequent experiments corroborated that violin preference is strongly associated with perceived richness in the sound [START_REF] Saitis | Investigating the origin of inter-individual differences in the preference for violins[END_REF][START_REF] Saitis | Perceptual evaluation of violins: A quantitative analysis of preference judgments by experienced players[END_REF][START_REF] Saitis | Evaluating violin quality: A comparison of player reliability in constrained vs. unconstrained tasks[END_REF][START_REF] Saitis | Perceptual evaluation of violins: A comparison of intra-individual agreement in playing vs. listening tasks for the case of richness[END_REF][START_REF] Saitis | Effect of task constraints on the perceptual evaluation of violins[END_REF].

Importantly, it was shown that while perceived variations in violin quality rely on variations in style and the expertise of different musicians, the broader semantic categories emerging from verbal descriptions remain common across diverse musical profiles, thus reflecting a shared perception of acoustic information. This allowed us to develop a musician-driven framework for understanding how the dynamic behavior of a violin might relate to its perceived quality [START_REF] Saitis | Perceptual evaluation of violins: A psycholinguistic analysis of preference verbal descriptions by experienced musicians[END_REF]. Furthermore, the verbal data revealed that vibrations from the violin body and the bowed string (via the bow) are used as extra-auditory cues that not only help to better control the played sound but also contribute to its perceived qualities. Indeed, recent research on the evaluation of violin and piano quality has revealed that an increase in the vibrations felt at the left hand of violinists and the fingertips of pianists can lead to an increase in the perceived richness as well as loudness of the sound [START_REF] Saitis | The role of haptic cues in musical instrument quality perception[END_REF].

Here we further investigated the perceptual and cognitive processes involved when violinists evaluate violins by focusing on how they describe perceptions of sound richness. Verbalizations were analyzed on the basis of semantic proximities in order to identify emerging concepts that could be coded under broader categories acting as psychologically relevant descriptors of violin sound richness. Semantic proximities were inferred from syntactic context and linguistic markers (e.g., reformulation, explanation, comparison, negation). The coding process was based on the inductive principle of Grounded Theory, where a system of ideas is constructed not starting from a hypothesis (or a set of hypotheses) but from the data itself [START_REF] Strauss | Basics of qualitative research: Techniques and procedures for developing grounded theory[END_REF].

METHOD

Online survey

Taking into account the lingual diversity of Québec, where this research took place, bilingual questions in English and French were compiled, and participants were invited to respond in the language they felt most comfortable with. Similarly to our previous work [START_REF] Saitis | Perceptual evaluation of violins: A psycholinguistic analysis of preference verbal descriptions by experienced musicians[END_REF], very general open-ended questions were formed to avoid confining the responses into pre-existing categories. Two respondents chose to reply in French and it was decided not to translate their responses but include them in the analysis directly.

Thirty-four violinists (20 female; average age = 42 yrs, SD = 17 yrs, range = 19-73 yrs) provided written responses to the questions (French version is given in parentheses) Q1: What does richness mean for you? (Qu'est-ce que la richesse signifie pour vous?) and Q2: How would you evaluate a violin in terms of richness? (Comment évalueriez-vous un violon en termes de richesse?). Respondents had at least 14 years of violin experience (average years of violin training = 31 yrs, SD = 15 yrs, range = 14-65 yrs), with 13 describing themselves as professional musicians. Musical profile information for each violinist is reported in Table 1.

Playing experiment 2.2.1 Musicians, violins and controls

Sixteen violinists participated in the playing experiment (8 female; average age = 32 yrs, SD = 8 yrs, range = 21-55 yrs). They had at least 15 years of violin experience (average years of violin training = 25 yrs, SD = 8 yrs, range = 17-48 yrs) and were remunerated for their participation. Eleven participants described themselves as professional musicians. Musical profile information for each violinist is reported in Table 2. Musicians #10 and #11 had previously participated in the online survey (respondents #25 and #23 in Table 1, respectively).

Five violins of different make (Europe, North America, China), year of fabrication (1914-2011) and price ($2.7k-$71k) were chosen from two luthier workshops in Montreal, Canada, in order to form, as much as possible, a set of instruments with a wide range of characteristics [START_REF] Saitis | Effect of task constraints on the perceptual evaluation of violins[END_REF]. The respective luthiers provided the price estimates and tuned the instruments for optimal playing condition based on their own criteria. Participants' own violins were not included in the set of instruments in order to avoid possible preference biases caused by the mere exposure effect [START_REF] Zajonc | Attitudinal effects of mere exposure[END_REF] by which familiarity with a stimulus object increases preference toward it.

Low light conditions and dark sunglasses were used to help hide the identity of the instruments as much as possible and thus circumvent the potential impact of visual information on judgment while ensuring a certain level of comfort for the musicians, as well as safety for the violins. To avoid the potential problems of using a common bow across all participants (e.g., musicians being uncomfortable with a bow they are not familiar with, bow quality), each violinist used their own bow. Furthermore, violinists were given the option to either use a provided shoulder rest (Kun Original model), or use their own, or use no shoulder rest. Sessions took place in acoustically dry rooms to help minimize the effects of room reflections on the direct sound from the violins.

Tasks and procedure

In the playing experiment, musicians were asked to "rank-rate" the five violins in terms of richness in two tasks.

In each task, violinists simultaneously rated each of the violins using separate, identical on-screen sliders, thus providing a ranking of the instruments at the same time. They were instructed to always rate their top choice as 1 and their lowest as 0, and were not allowed to assign the same rank-rating to two or more instruments. Musicians were instructed to maximise evaluation speed and accuracy, and were encouraged to play their own violin whenever they needed a reference point during the experiment. To minimise fatigue, violinists were encouraged to take breaks between trials whenever needed. The first task involved playing the eight notes of the chromatic scale G2 → D3 détaché, first without vibrato The particular excerpt was chosen because it incorporates the whole range of the instrument (as opposed to the first task) as well as a variety of techniques and dynamics. Violinists were instructed to follow the temporal and expressive markings as much as possible (i.e., a certain degree of personal interpretation was expected). Upon completing the second task, participants provided written responses to the same two questions as in the online survey. Two violinists chose to reply in French and it was decided not to translate their responses but include them in the analysis directly.

Analysis

Following the data coding steps that form the constant comparison method within the Grounded Theory framework [START_REF] Strauss | Basics of qualitative research: Techniques and procedures for developing grounded theory[END_REF][START_REF] Saitis | Perceptual evaluation of violins: A psycholinguistic analysis of preference verbal descriptions by experienced musicians[END_REF], our analysis started from the verbalizations collected in the online survey. First, groups of words indicating a concept of violin sound richness, henceforth called verbal units, were extracted from musicians' responses to the first question and classified in semantic categories. Inter-categorical associations were then established, at which point a tentative core for our conceptual framework had been formed. We next scanned the verbal responses to the second question. New concepts were identified and the core was updated to fit with the new data. The analysis was then extended to the verbal responses collected in the playing experiment on the basis of the updated core, wherein no further concepts emerged. Consequently coding was stopped as theoretical saturation had been reached.

Each verbal unit corresponded to a semantically distinct violin quality characteristic. Semantic proximities were assessed through syntactic context and linguistic markers such as the use of apposition, opposition, reformulation, explanation, comparison, or negation. For example, the phrase "a complex and pleasant sound" contained two verbal units, namely "complex" and "pleasant," whereas the phrase "resonant sound that is not weak" constituted a single unit which, however, comprised two manifestations of the same quality characteristic with opposite meanings, namely "resonant" (positive connotation or desirable quality) and "weak" (negative connotation or undesirable quality).

RESULTS

Semantic categories

In total, 211 verbal units were extracted from the responses collected in the online survey (34 violinists, 6 units per respondent on average) and 75 units in the playing experiment (16 violinists, 5 units per respondent on average), and were classified in eight distinct semantic categories, revealing a common framework for semantic features given to "rich" as a qualifier of violin timbre and sound quality:

1. A strong consensus was observed with the use of full (plein in French), describing a certain sensory property referring to the perceived amount of spectral content as in the perceived number of partial frequencies present in a violin note. This sensory property was also described, with some approximation, by other semantically related sensory adjectives such as deep, dark (sombre in French), dense, complex, big (ample in French), wide (large in French), and thick, or semantic opposites like thin, narrow, small, light, and nasal. Some musicians described this characteristic of a rich violin sound in acoustical (i.e., technical) terms-lots of /an abundance/variety of harmonics/overtones/dynamics)-while others tried to qualify a rich violin sound by referring to the ease/flexibility of the instrument to produce a variety/palette of colours/timbres and to react a lot in terms of sound changes, colours, thus enabling a violinist to create appropriate sounds for the chosen repertoire and having a shimmering quality whereby the sound changes constantly as one draws the bow. Along the same line of conceptualization, one violinist described a rich sound as being generous (généraux in French).

2. Another sensory property was expressed through words such as warm, velvety, smooth, round, sweet, and mellow, versus strident, harsh, tinny, brassy, squeaky, metallic, and bright-borrowed from the semantic field of texture. Also referring to spectral content, such conceptualizations direct to the distribution of spectral energy between the bass, midde, and treble registers in a played note; undesirable qualities are associated with disproportionately more treble or not enough bass frequencies (mellow tone on lower strings, no stridency on upper ones). This sensory property of a rich violin sound was also described in acoustical terms by some performers: evenness of projection across the frequency range; the sound has to contain a particular amount of energy in the different range of frequencies; combined with a good dose of lower frequencies for warmth.

3. Strong consensus was also observed with the use of resonant, strong, ringing, powerful, sonorous, sustained, lively, and projective, versus weak, muffled, and closed. The semantic field summarizing these verbalizations can be described as action-presence [START_REF] Saitis | Perceptual evaluation of violins: A psycholinguistic analysis of preference verbal descriptions by experienced musicians[END_REF] and suggests an evaluation of "how much sound" comes out of the violin based on estimated intensity and spatial attributes (a rich sound has to vibrate naturally and to go far without forcing), but also on the "amount of felt vibrations" from the body-bow system (how much you feel the sound in your body when you hear it) [START_REF] Saitis | The role of haptic cues in musical instrument quality perception[END_REF].

4. Yet another sensory property associated with a rich violin sound was expressed through words and phrases such as clarity, pure, precise, focus, speakability or how freely each string speaks, the sound can take a lot of pressure without cracking, lack of grainy tonality, and direction (as in focus). Here violinists tried to describe a violin tone perceived as having more distinct and well-defined spectral components, especially in the low register where different notes may be heard as "blending into each other" or "unfocused" due to overlapping overtones. Some violinists specifically referred to a clear sound as lacking audible artifacts such as a wolf tones (oscillating beat when note frequency too close to the resonance frequency of the violin body).

5. Some musicians tried to qualify a rich violin sound as varying with/responding to vibrato and offering lots/nuances of vibrato or un vibrato nerveux, ample, leger ou inexistant (a vibrato that is nervous, full, light or non-existent).

Table 3. Distribution of categories within and across responses to questions (N = total units; # = coded units; % = proportion).

Online survey Playing experiment 6. Some violinists qualified a rich violin sound by referring to the responsiveness of the instrument (i.e., how quickly the violin responds to different bowing gestures): if the violin answers tenderly to the bow; pay attention to reactions to different strokes; it is important that [the violin] responds quickly and evenly; the sensitivity/response of the violin is helpful; it is important that it responds quickly and evenly; il faut sentir la sensibilité jusqu'au bout des doigts (you have to feel the sensitivity right down to your fingertips.

Q1 (N = 132) Q2 (N = 79) ALL (N = 211) Q1 (N = 46) Q2 (N = 29) ALL (N = 75) # % # % # % # % # % #
7. Some violinists qualified a rich violin sound as being well-balanced for both low and high notes or stable (if the sound is good in all the ranges), or having equal resonance on all strings. . . thus making the richness of tone consistent throughout. In particular, some musicians explicitly referred to the responsiveness of the violin in higher positions on the lower strings (G and D). As one violinist put it, I often find a rich sounding violin starts to get a weak sound as I strain the string by going higher.

8. Finally, many musicians referred to global affective-hedonic qualities that do not reflect the perception of certain physical parameters and could thus qualify any sensory property irrespective of modality: beautiful; pleasant/not irritating; has personality; unmusical tonality; the heart-melting sound; richness is the difference between butter and margarine; richness is indulgence; the instrument blooms. . . has the sensation that you can sink in to it. Or as one violinist said: I judge richness based on how much the sound reminds of melted chocolate.

Table 1 reports the musical profile of each respondent in the online survey along with information on whether they used verbal expressions within a given category (Fu = fullness; Wa = warmth; Reso = resonance; Cl = clarity; Vi = vibrato; Resp = responsiveness; Ba = balance; In = interest). Corresponding information for the musicians in the playing experiment is reported in Table 2. No obvious relationship between having a certain style and/or level of experience and attending to particular attributes was observed. Consequently, Table 3 summarizes the across-musicians distribution of semantic categories within each and over all responses to the different questions. Occurrences were further summarized across questions due to similar trends.

Discussion

In order to identify how the definitions of violin sound richness proposed by the experts (i.e., the violinists) position themselves in relation to dictionary definitions of the adjective rich in English, we have noted definitions and synonyms from two sources:

• Oxford English Dictionary (OED; 2nd Edition): 1) Of things: Powerful, strong. 2) Wealthy in, having abundance of, amply provided with, some form of property or valuable possessions. 3) Of choice or superior quality; esp. of articles of food or drink with reference to their stimulative or nourishing effects. 4) Of a full, ample, or unstinted nature; highly developed or cultivated. 5) Of colour: Strong, deep, warm. 6) Of musical sounds: Full and mellow in tone. 7) Of odours: Full of fragrance.

• WordNet (www.wordnet.princeton.edu; a large network of semantic relations between words based on psycholinguistic and computational theories of human lexical memory [START_REF] Miller | WordNet: A lexical database for English[END_REF]): 1) Having an abundant supply of desirable qualities or substances. 2) Fat, fertile, productive (marked by great fruitfulness). 3) Deep (strong; intense). 4) [Of wine, food, etc.] full-bodied, racy, robust (marked by richness and fullness of flavor). 5) [Of sound] pleasantly full and mellow. 6) Ample, copious, plenteous, plentiful (affording an abundant supply).

It appears that rich is conceptualized in a highly similar fashion across sensory modalities (taste, smell, vision, audition) but also in more abstract nonsensory domains (wealth, strength, abundance). Central to all conceptualizations of rich is the idea of "affording an abundant supply" of one or more "desirable qualities," which is reflected in the first semantic category identified in the experts discourse (full sound; lots of harmonics/overtones). Furthermore, qualifying a rich violin sound as resonant/powerful/strong (third semantic category) and as offering lots/nuances of vibrato (fifth semantic category) can be regarded in the same light as the global "lots of" definition of rich. The agreement of OED and WordNet in how rich is defined for sounds suggests that its qualification as both full and mellow (second semantic category) is considered beyond violin sound to any auditory scenario.

The semantic categories of clear/focused and balanced are more specific to musical sound and to the violin in particular, where tones in the middle and low registers should not be "muddy" or "blurry", and those in the high register should not be "thinner" or "weaker" (cf. [START_REF] Saitis | Perceptual evaluation of violins: A psycholinguistic analysis of preference verbal descriptions by experienced musicians[END_REF]). Characterizations of a rich violin sound as beautiful, pleasant, heart-melting, and reminding of melted chocolate assume a cognitive evaluation of the subjective-affective state of the musician in response to their imaginary (online survey) or physical (playing experiment) interaction with the violin and its sound.

Descriptions of responsiveness (of the instrument) were the least recurrent in both the imaginary and physical situations. In fact, this semantic category did not emerge at all in the playing experiment, while in the online survey it emerged only in responses to the question How would you evaluate a violin in terms of richness? (Q2). It is plausible that, for the violinists who responded to the online survey, the type of question at hand may have affected how different facets of rich are negotiated. That is, the use of the word "evaluate" in Q2 could have evoked notions of musician-instrument interaction and playability, whereas the formulation of Q1 led to a prioritization of primarily sound attributes. Similarly, the violinists who took part in the playing experiment were asked to first respond to the question How and based on which criteria did you make your preference ranking? before answering Q1 and Q2. A look at those responses, which is beyond the scope of the present analysis, indeed reveals descriptions of responsiveness.

CONCLUSIONS

The present analysis provides further evidence that metaphorical linguistic structures such as rich sound are central to the process of conceptualizing timbre by allowing the musician to meaningfully perceive and communicate subtle acoustic variations in terms of other, more commonly shared experiences [START_REF] Saitis | The semantics of timbre[END_REF].

While individual conceptualizations of violin sound richness are very subtle and can overlap, the broader semantic categories emerging from the collected verbalizations reflect a shared representation of what a rich violin sound may mean. This can be seen as a first step in translating the semantics of violinists' expressions into perceptually meaningful descriptors of violin sound quality. Importantly, it demonstrates that violin players with different levels of experience and expertise share a common framework for differentiating the sensory meanings of auditory cues.

We expect that there are variations of the language (i.e., the specific lexicon and its meaning) used by musicians from place to place (sometimes resulting from a strong influence by one or more particular teachers in an area). The present analysis might thus be biased toward a verbal tradition specific to the Montreal region. Nevertheless, this research provides a resource that should be consulted by any researchers planning to conduct perceptual studies of violin quality (i.e., when designing the language used in their experiments).

Table 1 .

 1 Musical profile of online survey respondents and semantic categories they used.

			Musical profile	Semantic categories
		Practice (yrs)	Skill	Style of music	Fu Wa Reso Cl Vi Resp Ba In
	1	17	Amateur	Classical, Folk
	2	16	Amateur	Classical
	3	14	Amateur	Classical
	4	16	Amateur	Classical
	5	18	Amateur	Classical, Jazz, Folk
	6	23	Professional	Classical, Jazz
	7	44	Professional	Classical, Contemporary
	8	23	Amateur	Classical, Baroque
	9	20	Amateur	Classical, Jazz, Folk
	10	17	Professional	Classical, Contemporary
	11	20	Professional	Classical, Baroque, Contemporary
	12	39	Professional	Classical, Contemporary
	13	45	Amateur	Classical
	14	50	Professional	Classical, Contemporary
	15	34	Amateur	Classical
	16	35	Amateur	Classical
	17	25	Amateur	Classical
	18	56	Amateur	Classical, Contemporary
	19	19	Professional	Classical, Jazz
	20	15	Amateur	Classical, Jazz
	21	15	Amateur	Classical, Folk
	22	27	Professional	Classical, Baroque
	23	25	Professional	Jazz, Folk
	24	31	Professional	Classical, Baroque
	25	48	Professional	Classical, Folk
	26	18	Professional	Classical, Baroque
	27	44	Professional	Classical
	28	30	Amateur	Classical
	29	65	Amateur	Classical, Baroque
	30	40	Amateur	Classical, Contemporary
	31	50	Amateur	Classical, Baroque
	32	60	(not reported)	Classical, Baroque
	33	38	Amateur	Classical, Folk
	34	22	Amateur	Classical

Table 2 .

 2 Musical profile of playing test participants and semantic categories they used.

			Musical profile				Semantic categories
		Practice (yrs)	Skill	Style of music	Fu	Wa	Reso	Cl	Vi	Resp	Ba	In
	1	21	Professional	Classical
	2	23	Professional	Classical
	3	21	Professional	Classical
	4	18	Professional	Contemporary
	5	17	Amateur	Classical
	6	30	Professional	Classical
	7	26	Professional	Classical
	8	20	Amateur	Classical
	9	25	Amateur	Jazz
	10	48	Professional	Classical
	11	22	Amateur	Classical
	12	34	Professional	Classical
	13	17	Professional	Folk
	14	20	Amateur	Classical
	15	32	Professional	Classical, Folk
	16	28	Professional	Classical

followed by a repetition with vibrato. Violinists were instructed to follow a 50 bpm tempo and use the whole bow. The second task involved playing the opening solo passage from Max Bruch's Violin Concerto No. 1 in G Minor, Op. 26 (Movement I: Prelude).