Fabian Pedregosa

Elodie Cauvet

Gaël Varoquaux

Christophe Pallier

Bertrand Thirion

Alexandre Gramfort

Improved brain pattern recovery through ranking approaches

Keywords: fMRI, supervised learning, decoding, ranking

Improved brain pattern recovery through ranking approaches

Fabian Pedregosa * † § , Elodie Cauvet ‡ † , Gaël Varoquaux * † , Christophe Pallier ‡ * † , Bertrand Thirion * † and Alexandre Gramfort * † ,

I. INTRODUCTION

The prediction of behavioral information or cognitive states from brain activation images such as those obtained with fMRI can be used to assess the specificity of several brain regions for certain cognitive or perceptual functions. This kind of analysis is implemented by learning a classifier or regression function that fits a given target variable given fMRI activations. The accuracy of this prediction depends on whether it uses the relevant variables i.e. the correct brain regions. Recovering the truly predictive pattern has proven to be challenging from a statistical point of view: the high dimensionality of the data together with the limited number of images makes the problem of brain pattern recovery an ill-posed problem.

So far, the approaches proposed to address this issue have relied on linear models, with univariate, i.e. voxel-based, Anova (analysis of variance) for hypothesis testing, or, for predictive modeling, with the choice of a regularizer using a priori domain-specific knowledge, such as the 1 -norm to promote sparsity [START_REF] Yamashita | Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns[END_REF], [START_REF] Ryali | Sparse logistic regression for whole-brain classification of fmri data[END_REF], total variation to promote spatial smoothness [START_REF] Michel | Total variation regularization for fMRI-based prediction of behaviour[END_REF]. Various data fit terms have been used, Logistic Regression (LR) [START_REF] Ryali | Sparse logistic regression for whole-brain classification of fmri data[END_REF], Linear SVM [START_REF] Mouro-Miranda | Classifying brain states and determining the discriminating activation patterns: Support vector machine on functional MRI data[END_REF], Lasso [START_REF] Yamashita | Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns[END_REF]. While Linear SVM and LR cannot address the recovery problem for multiclass problems, linear regression models assume a linear relationship between the quantity to predict and the amplitude of the fMRI signals. If the linear relationship does not hold in practice, then the estimation of the predictive patterns may suffer from a loss of statistical power. This can be particularly relevant with Blood Oxygen-Level Dependent (BOLD) signals observed in fMRI, where a saturation effect is expected as the level of signal increases.

When targets to predict consist of ordered values, as in a parametric design, such as clinical scores, pain levels or the complexity of a cognitive task, the response to these different conditions can reflect the non-linearities in the data. In such situation, we propose to use a data fit term, known as loss function, not relying on an assumption of linearity but only of increasing response. We show on simulations that this new formulation opens the door to capturing the non-linearity and leads to better recovery of the predictive brain patterns. On an fMRI dataset we show that the new formulation leads to models with better recovery properties.

a) Notations: We write vectors in bold, a ∈ R n , matrices with capital bold letters, A ∈ R n×p . The dot product between two vectors is denoted a, b . We denote by a = a, a the 2 norm of a vector.

II. LEARNING A LINEAR MODEL FROM FMRI DATA

Following standard statistical learning notations we denote by x i ∈ R p , 1 ≤ i ≤ n, the data and y i ∈ Y the target variables. In this paper, we aim at learning a weight vector w ∈ R p such that the prediction of y can be non-linearly related to the value of w T x. The vector w corresponds here to a brain map that can be represented in brain space as a volume for visualization of the predictive pattern of voxels. It is useful to rewrite these quantities in matrix form; more precisely, we denote by X ∈ R n×p the design matrix assembled from n fMRI volumes and by y ∈ R n the corresponding n targets. In other words, each row of X is a p-dimensional sample, i.e., an activation map of p voxels related to one stimulus presentation.

A standard approach to perform the estimation of w leads to the following minimization problem

ŵ = argmin w L(y, X, w) + λ Ω(w) , λ ≥ 0 (1)
where λ Ω(w) is the regularization term and L(y, X, w) is the loss function. The parameter λ balances the loss function and the penalty Ω(w).

If the explained variable is a linear combination of the images, y = Xw + , we can estimate ŵ using the mean squared error loss function L(y, X, w) = y -Xw 2 .

However, with fMRI the linearity assumption may not be valid. Instead, we model our explained variable as y = F (Xw) + , where F is a non-decreasing function.

We introduce the use of pairwise loss functions. These loss functions only assume the target values to be a non-decreasing function of the data. They have been widely used in ranking, a type of supervised machine learning problem whose goal is to automatically construct an order from the training data. A pairwise loss function operates on pairs of images: given a pair of images (x i , y i ) and (x j , y j ), y i = y j we build a model that predicts the sign of y i -y j .

Let I denote the index set of all considered pairs. Note that in some settings it might be important to restrict ourselves to a selected subgroup of all pairs, e.g. to the pairs of images of a single subject or to the pairs of images corresponding to a single session. For this purpose we define a ij ∈ R, (i, j) ∈ I to be a weight associated to each pair. We will now present the pairwise loss functions used in this article:

• Pairwise hinge loss [START_REF] Herbrich | Large margin rank boundaries for ordinal regression[END_REF]. This is a natural extension of the loss function used by Support Vector Machines and has been successfully used in information retrieval [START_REF] Cao | Adapting ranking svm to document retrieval[END_REF].

(i,j)∈I a ij [1 -w T (x i -x j )] + (2)
where [z] + = max{z, 0}. • Pairwise logistic loss [START_REF] Dekel | Log-linear models for label ranking[END_REF]. This is the pairwise extension of the logistic regression loss function.

(i,j)∈I

a ij log(1 + exp(w T (x i -x j ))) (3)
When noise is present in the model, the order of two samples might get inverted, a phenomenon known as label switching. Because this only affects labels that lie close, it is natural to penalize more the misclassification of distant labels. By setting the sample weights to a ij to a value that increases as labels become more separated, we become more robust to label switching. In the case of hinge loss functions, several strategies for choosing the appropriate weights are discussed in [START_REF] Cao | Adapting ranking svm to document retrieval[END_REF].

On the implementation side, both pairwise hinge loss and pairwise logistic loss can be implemented on top of existing SVM and Logistic Regression solvers, respectively, by taking the difference of pairs as input values. In practice, we used the liblinear [START_REF] Fan | Liblinear: A library for large linear classification[END_REF] library via the scikit-learn [START_REF] Pedregosa | Scikit-learn: Machine Learning in Python[END_REF] The target variable y l ∈ R n is simulated as a linear model:

y l = Xw + (4)
where the noise i ∈ [-σ 2 , σ 2 ] follows a uniform distribution. σ is chosen such that the signal-to-noise ratio verifies / Xw = 5%. We then define another target variable y nl to be a sigmoid function of y l , that is,

y nl = 1 1 + exp (-y l ) (5)
For each of the loss functions introduced earlier and mean squared error, we compute the correlation coefficient ρ(w, ŵ) = w, ŵ /( w ŵ ). This gives us the goodness of fit for the estimated ŵ. A method with correlation coefficient of 1 is able to recover perfectly the ground truth. Since we are interested in the estimation of w, we restricted ourselves to linear models, leaving out models such as kernel ridge or support vector regression with Gaussian kernel.

For all models we added 2 regularization in the form of λ w 2 and we cross-validated λ separately for each loss. In this setting, the model with mean squared error loss is equivalent to ridge regression. In order to focus on the effect of non-linearity, we first considered a noiseless simulation using trivial weights a ij = 1.

Once we learned a vector ŵ for each method we compute the correlation coefficient with the ground truth for different sizes of the training data. The experiment is repeated 10 times with different initialization of the pseudorandom number generator. We compute errorbars and show the results in figure 1. As the number of samples increases, the linear model stalls and pairwise loss functions outperform MSE on both 5 × 5 × 5 and 7 × 7 × 7 dimension. As expected, the higher dimensionality of the second simulation makes the correlation coefficient decrease. However, unlike MSE, ranking tends to a perfect recovery as the number of samples increases. Both pairwise loss functions perform equivalently and have a significatively higher correlation coefficient than MSE. In the rest of the paper we will use pairwise logistic as loss function. As a result, pairwise loss functions should be preferred over MSE in situations where underlying model is non-linear. Notice that we fixed the non-linearity to be a sigmoid function, but the pairwise loss functions only assume that this function is non-decreasing. Unlike linear regression models, pairwise loss functions are indeed able to learn the structure on the non-linear transform F .

We now consider the model with noise as in ( 4) and use non-trivial weights a ij . To account for label switching, we set a ij to zero for pairs with too similar labels:

a ij = 0 if |y i -y j | < σ 1 otherwise . (6)
In the case of discrete values, this would be equivalent to zeroing weights for which the labels are adjacent. We now compute the correlation coefficient for weighted and unweighted pairwise logistic models and linear ridge regression model. The result can be seen in figure 2 for dimension 5 × 5 × 5. The unweighted logistic model breaks down in presence of noise and performs worse than linear ridge regression. On the other hand, appropriately setting the weights a ij has a major effect on robustness, where this model outperforms MSE in a noisy setting. Note also that weighted pairwise logistic has smaller variance than MSE.

IV. RESULTS ON FMRI DATA This dataset, described in [START_REF] Cauvet | Investigations of musical and linguistic structures using fMRI[END_REF], consists of 34 healthy volunteers scanned while listening to 16 words sentences with five different levels of complexity. These were 1 word constituent phrases (the simplest), 2 words, 4 words, 8 words and 16 words respectively, corresponding to 5 levels of complexity which was used as class label in our experiments. To clarify, a sentence with 16 words using 2 words constituents is formed by a series of 8 pairs of words. Words in each pair have a common meaning but there is no meaning between each pair. A sentence has therefore the highest complexity when all the 16 words form a meaningful sentence.

The dataset consists of 8 manually labeled ROIs, some informative and some not. For each ROI separately, we split the data into 60% training samples, 20% for parameter selection and 20% for validation. We trained a pairwise logistic model and set the 2 regularization by cross validation. We choose a ij to be zero if classes are adjacent, i.e. if |y i -y j | ≤ 1 and if x i and x j do not belong to the same subject, in order to consider exclusively non-adjacent pairs of images from the same subject. In all other cases, a ij was set to one. We computed the generalization score on the validation set as the mean number of inversions with respect to the order in labels, i.e. the sign flips sgn((X i -X j ) ŵ) = sgn(y i -y j ) for all pairs of images in the validation set.

We kept the four ROIs with highest scores (see figure 3). These are: Anterior Superior Temporal Sulcus (aSTS), Temporal Pole (TP), Inferior Frontal Gyrus Orbitalis (IFGorb) and Inferior Frontal Gyrus triangularis (IFG tri).

In order to inspect the properties of the estimated functions F for each ROI, we estimated ŵ using a pairwise logistic model. We then projected our data X along this vector ŵ and regularized the result using non parametric locally weighted scatterplot smoothing (LOWESS). Results in figure 4 show that the linearity varies in shape across ROIs which suggests that different regions exhibit different sensitivities to the complexity parameter under investigation. We see however a trend in the figures towards non-linear and non-decreasing functions with some saturation effect of the BOLD signal as in the temporal pole (TP).

In the case of the Temporal Pole (TP), which is the ROI revealing the highest saturation effect, an F-test on the data (X ŵ, y) reveals that the quadratic polynomial model fits better the data than a linear model (p-value < 0.03). As shown in the simulations, in this particular case pairwise loss functions are likely to improve the recovery of active brain regions.

V. CONCLUSION

In this paper, we investigated the use of pairwise loss functions to improve the problem of brain pattern recovery with supervised learning applied to fMRI data. Through simulations, we showed the benefit of such loss functions when the target to predict is non-linearly related to the voxel amplitudes. Experimental results on fMRI data confirmed the presence of such non-linear effects in the data which suggest that the pairwise approach should improve the identification of predictive brain patterns on experimental data.

This work shows that improvements in recovery of brain activation patterns should not only rely on the choice of a particular regularizer, but also on an appropriate loss function.

Here we have only considered 2 -penalized models, but a natural extension to work with full brain data would be to consider pairwise loss functions combined with sparse structured penalizations which incorporate domain-specific knowledge. This opens the path to further improvements and refinements in the recovery of brain pattern activation via supervised learning.

Fig. 1 .Fig. 2 .

 12 Fig.1. Correlation between the estimated vector ŵ and the ground truth w for different loss functions as the number of considered samples increases (higher is better) for dimensions 5×5×5 and 7×7×7 respectively. Pairwise loss functions outperform linear regression as the number of samples increases and tend to a perfect recovery.

Fig. 3 .

 3 Fig. 3. Scores obtained with the pairwise logistic on the 4 different ROIs. The regions with the best predictive power are the temporal pole the anterior superior temporal sulcus.

Fig. 4 .

 4 Fig.[START_REF] Mouro-Miranda | Classifying brain states and determining the discriminating activation patterns: Support vector machine on functional MRI data[END_REF]. Data projected along ŵ showing the non-linear effect in the 4 regions of interest. This projection gives an insight on the relationship between the BOLD signal and the explained variable. We observe that the the shape of the non-linearity varies across brain regions. Apart from IFG tri, all regions show a saturation effect in the BOLD response.

ACKNOWLEDGMENT

This work was supported by the ViMAGINE ANR-08-BLAN-0250-02, IRMGroup ANR-10-BLAN-0126-02 and Construct ANR grants.


Giuseppina Cantarella

Mimmo Scollo

Laurence Lempereur

Gloria Saccani-Jotti

Francesco Basile

Renato Bernardini
email: bernardi@unict.it

Prof Renato Bernardini

ENDOCANNABINOIDS INHIBIT RELEASE OF NERVE GROWTH FACTOR BY INFLAMMATION-ACTIVATED MAST CELLS

Keywords: Endocannabinoids, NGF-related inflammation, receptor, antagonist

Nerve growth factor (NGF) is a pleiotropic member of the neurotrophin family. Beside its neuronal effects, NGF plays a role in various processes, including angiogenesis. Mast cells release NGF and are among elements contributing to angiogenesis, a process regulated by arrays of factors, including the inhibitory cannabinoids. The possible inhibitory role of cannabinoids on mast cellrelated NGF mitogenic effect on endothelial cells was then investigated. Human mastocytic cells HMC-1, challenged with PMA to yield release of NGF, were preincubated with the endocannabinoid PEA. Then, conditioned media were added to HUVEC cultures. PMA-activated HMC-1 cells released substantial amounts of NGF, whereas PEA inhibited PMA-induced NGF release. HUVEC proliferation increased after treatment with media from activated HMC-1 cells, while was reduced with media from HMC-1 cells treated with PEA. To characterize receptors mediating such effects of PEA, RT-PCR and western blot analysis were performed on HMC-1 cells.

None of the two cannabinoid CB1 and CB2 receptors was expressed by HMC-1 cells, which on the other hand expressed the orphan receptor GPR55. PEA was ineffective in inhibiting NGF release from HMC-1 cells treated with PMA and transfected with positive GPR55 RNAi, whereas it induced significant reduction of NGF in cells transfected with the corresponding negative control RNAi. Results indicate that NGF released from inflammatory mast cells induces angiogenesis.

Cannabinoids attenuate such pro-angiogenic effects of NGF. Finally, cannabinoids could be considered for antiangiogenic treatment in disorders characterized by prominent inflammation.

A c c e p t e d M a n u s c r i p t

INTRODUCTION

Nerve growth factor (NGF) is the prototype molecule for the family of neurotrophins [START_REF] Thoenen | The changing scene of the neurotrophic factors[END_REF], of primary relevance to neurogenesis [START_REF] Jiang | Expression of human p140trk receptors in p140trkdeficient, PC12/endhotelial cells resulting nerve growth factor-induced signal transduction and DNA synthesis[END_REF], neuronal repair processes [START_REF] Tabakman | Interactions between the cells of the immune and nervous system:neurotrophins as neuroprotection mediators in CNS injury[END_REF], as well as neuronal plasticity [START_REF] Glebova | Heterogeneous requirement of NGF for sympathetic target innervation in vivo[END_REF] and survival.

Although neurotrophins are thought to exert their actions predominantly on neural cells [START_REF] Levi-Montalcini | The nerve growth factor 35 years later[END_REF], indeed some of them possess pleiotropic properties [START_REF] Tuveri | NGF, a useful tool in the treatment of chronic vasculitic ulcers in rheumatoid arthritis[END_REF]. For example, NGF is able to exert proinflammatory effects [START_REF] Raychaudhuri | Effect of nerve growth factor on endothelial cell biology: proliferation and adherence molecule expression on human dermal microvascular endothelial cells[END_REF] and displays prominent pro-angiogenic properties in vitro and in vivo [START_REF] Cantarella | Nerve growth factor-endothelial cell interaction leads to angiogenesis in vitro and in vivo[END_REF].

Moreover, NGF can influence development and activation of an array of haematopoietic cell types, including basophiles and mast cells [START_REF] Crivellato | Mast Cells and Basophils: A Potential Link in Promoting Angiogenesis during Allergic Inflammation[END_REF]. Interestingly, the latter can release substantial amounts of NGF stored in their granules [START_REF] Nilsson | Human mast cells express functional TrkA and area source of nerve growth factor[END_REF]. Mast cells are derived from their haematopoietic precursors and represent critical effectors cells in allergic disorders and other IgE-dependent immune responses [START_REF] Nadler | Signal transduction by the high-affinity immunoglobulin E receptor FceRI: coupling form to function[END_REF]. More recently, it has been shown that mast cells are also involved in the regulation of angiogenesis [START_REF] Maltby | Mast cells in tumor growth: Angiogenesis, tissue remodelling and immune-modulation[END_REF], the process leading to formation of new vessels starting from preexisting ones [START_REF] Folkman | Angiogenesis in cancer, vascular, rheumatoid and other disease[END_REF].

From the biologic point of view, angiogenesis is the result of the concerted, balanced action of an array of stimulatory factors, such as, for instance, VEGF or FGF [START_REF] Ferrara | Molecular and biological properties of the vascular endothelial growthfactor family of proteins[END_REF], or inhibitory factors of various nature, including angiostatin [START_REF] Ribatti | Endogenous inhibitors of angiogenesis: a historical review[END_REF], endostatin [START_REF] O'reilly | Endostatin: anendogenous inhibitor of angiogenesis and tumor growth[END_REF], and the family of ubiquitary lipid mediators known as endocannabinoids [START_REF] Bifulco | Endocannabinoids as emerging suppressors of angiogenesis and tumor invasion[END_REF][START_REF] Marzo | Targeting the endocannabinoid system: to enhance or reduce?[END_REF].

Endocannabinoids usually induce inhibitory responses in different tissues and organs [START_REF] Marzo | Targeting the endocannabinoid system: to enhance or reduce?[END_REF], their effects being mediated by specific membrane receptors, such as those belonging to the CB1/CB2 system [START_REF] Matsuda | Structure of a cannabinoid receptor and functional expression of the cloned cDNA[END_REF][START_REF] Munro | Molecular characterization of a peripheral receptor for cannabinoids[END_REF], vanilloid receptors [START_REF] De Petrocellis | Plant-Derived Cannabinoids Modulate theActivity of Transient Receptor Potential Channels of Ankyrin Type-1and Melastatin Type-8[END_REF], and the TRPV1 receptor. Recently, a novel receptor, which is able to bind endocannabinoids, GPR55, has been identified and cloned [START_REF] Ryberg | The orphan receptor GPR55 is a novel cannabinoid receptor[END_REF].

In this paper, we describe the role of NGF released by noxious stimuli-activated mast cells in fuelling angiogenesis and, eventually, the modulating effects of the endocannabinoid PEA, an Nacylamidic molecule that negatively influences mast cell functions sustaining an inflammatory response [START_REF] Mazzari | N-(2-hydroxyethyl)hexadecanamide is orally active in reducing edema formation and inflammatory hyperalgesia by down-modulating mast cell activation[END_REF].

A c c e p t e d M a n u s c r i p t 4

To demonstrate the hypothesized angiogenic potential of mast cells, we first challenged the one-of-a kind human cell line, derived from a patient with mast cell leukaemia, mastocytic cells HMC-1 [START_REF] Butterfield | Purification of tryptase from a human mast cell line[END_REF] with inflammatory stimuli and then measured NGF released in the media. Subsequently, human umbilical cord vascular endothelial cells (HUVEC) underwent challenge with conditioned media from activated mast cells.

Finally, in light of the described inhibitory effects of cannabinoids upon inflammation [START_REF] Marzo | Targeting the endocannabinoid system: to enhance or reduce?[END_REF], we evaluated possible inhibitory effects of PEA on mast cells-related NGF release.

A c c e p t e d M a n u s c r i p t 5

MATERIALS AND METHODS

Cell cultures and reagents.

HMC-1 cells (kindly provided by Dr. Butterfield, Rochester, MN), which are immature human leukemic mast cells, were cultured in Iscove's medium, supplemented with 10% fetal calf serum (FCS) (Invitrogen Srl, San Giuliano Milanese, Italy), 10 mM monothiolglycerol (Sigma-Aldrich, Milano, Italy), and antibiotics (streptomycin and penicillin) (Sigma-Aldrich, Milano, Italy).

Stimulation of HMC-1 cells was performed in 24-multiwell plates (Falcon, Lincoln Park, NJ).

Before stimulation, cells were cultured for 24 h in medium without FCS. After this time, 2x10 6 cells were incubated for the times indicated in medium without FCS containing different concentration of PMA (Sigma-Aldrich, Milano, Italy), or PEA (kindly provided by Dr. Della Valle, Epitech, Italy) or combination of both substance.

HUVECs were obtained from human umbilical cords from healthy women underwent uncomplicated term pregnancies, as described elsewhere [START_REF] Jaffe | Culture of human endothelial cells derived from umbilical veins. Identification by morphologic and immunologic criteria[END_REF].

Cells were grown in gelatin coated plastic in medium M199 (Invitrogen Srl, San Giuliano Milanese, Italy) (Invitrogen Srl, San Giuliano Milanese, Italy) supplemented with endothelial cell growth supplement (ECGS; 20 g/ml) (Sigma-Aldrich, Milano, Italy), heparin (1625 UI/ml) (Sigma-Aldrich, Milano, Italy) and 20 % fetal calf serum (FCS) (Invitrogen Srl, San Giuliano Milanese, Italy) .

ELISA

The secretion of NGF in the culture media after different treatments was measured with growth factor specific ELISA kits (Quantikine, RD Systems Inc. Minneapolis, MN, USA), according to the instructions of the manufacturer. The lower detection limit for NGF was 5 pg/ml. Concentrations of NGF in the samples were calculated by interpolation from the standard curve.

Western blot analysis

Proteins obtained after different treatments, according to the experiment, were separated in acrylamide gels and electrotransferred to nitrocellulose blots (Amersham Italia S.r.l., Milan, Italy).

A c c e p t e d

M a n u s c r i p t 6 Membranes were incubated with 5% fat-free milk, 0.1% Tween-20 (Sigma-Aldrich, Milano, Italy) in PBS (Sigma-Aldrich, Milano, Italy) and incubated with the following antibodies: rabbit polyclonal anti NGF (Santa Cruz Biotechnology, Santa Cruz, CA, USA) rabbit polyclonal anti CB1 (Cayman chemical Ann Arbor, MI, USA), rabbit polyclonal anti CB2 (Cayman chemical Ann Arbor, MI, USA), rabbit polyclonal anti GPR55 (Abcam, Cambridge, UK), or rabbit polyclonal anti -tubulin (Santa Cruz Biotechnology, Santa Cruz, CA, USA) . Peroxidase-labeled secondary antibodies and an enhanced chemiluminescence kit (Amersham Italia S.r.l., Milan, Italy) were used for immunodetection. For validation of blot data, densitometric analysis was performed on immunoblots by using ImageJ analysis software.

Immunofluorescence.

HCM-1 cells grown on tissue culture chamber slides after different treatments were fixed with 4% paraformaldehyde (Sigma-Aldrich, Milano, Italy) for 15 min, followed by permeabilization with 0.1% Triton X-100 (Sigma-Aldrich, Milano, Italy) and blocking for 45 min with PBS-BSA 1% (Sigma-Aldrich, Milano, Italy). The cells were consecutively processed with rabbit polyclonal anti NGF (Santa Cruz Biotechnology, Santa Cruz, CA, USA) or rabbit polyclonal anti GPR55 (Abcam, Cambridge, UK) or isotype control antibody, and anti-rabbit antibody-fluorescein isothiocyanate (FITC) conjugate (Serotec Ltd., Oxford, England). Cells were observed under fluorescence light microscope (DMIRB, Leica, Germany) and photographed.

HUVEC proliferation assay

For human umbilical endothelial cell (HUVEC) proliferation studies the conditioned medium (CM) of unstimulated and PMA 50ng/ml (Sigma-Aldrich, Milano, Italy) stimulated cells was used alone.

For this purpose, HMC-1 cells were cultured for 24 h under the same conditions as described above.

CM was concentrated 10-fold by ultrafiltration in Centriprep-10 filter units (Amicon, Beverly, MA), and supernatants were stored frozen at -80°C. HUVEC were seeded at 1 x 10 3 cells/well into 96-multiwell plates in M199 with ECGS, 20 % FCS and heparin. After 24 h, medium was replaced with fresh complete medium containing graded concentrations of CM (10, 20, 40 and At the end of experiments cells were stained with 0.5% crystal violet solution for 30 min, washed with bidistilled water and lysed in 10% acetic acid for 15 min. Optical density was read at 570 nm.

Reverse transcriptase-PCR.

Total RNA was extracted from cells grown to 80% confluence using TRIzol (Invitrogen Srl, San Giuliano Milanese, Italy), according to the manufacturer's instructions. For first strand cDNA synthesis, 1 µg of total RNA was reverse-transcribed using 25 µg ml-1 oligo (dT)12-18 primer (Invitrogen Srl, San Giuliano Milanese, Italy) in a final volume of 20 µl, in the presence of 200 units of M-MLV reverse (Invitrogen Srl, San Giuliano Milanese, Italy). The reaction was carried out at 37 °C for 1 h and heated at 95 °C for 10 min, and subsequently for 5 min at 4 °C. The reaction program for (a) human CB1 and human CB2 primers consisted of 35 runs of denaturation at 95 °C for 45 sec, annealing at 62 °C for 45 sec and elongation at 72 °C for 1 min.; (b) human GPR55 primers consisted of denaturation at 95° C for 45 sec, annealing at 56°C for 45 sec and elongation at 72°C for 1 min. The cycle program was preceded by an initial denaturation at 95 °C for 3 min and followed by a final extension at 72 °C for 7 min. PCR products were analyzed by 1.0% agarose gel electrophoresis and visualized with ethidium bromide. The following RNA transcripts were detected via amplification of the corresponding cDNAs: the human CB1 using a primer pair composed of the sense primer 5'-CATCATCACACGTCTG-3' and the antisense primer 5'-ATGCTGTTATCCAGAGGCTGC-3'; the human CB2 using a primer pair composed of the sense primer 5'-TTTCCCACTGATCCCCAATG-3' and the antisense primer 5'-AGTTGATGAGGCACAGCATG-3'; the human GPR55 using a primer pair composed of the sense primer 5'-GAGTCAGCAAAACACCAGTGGGGAC -3' and the antisense primer 5'- GPR55-expressing HMC1 cells were transfected with duplex small interfering RNA (siRNA) (Invitrogen Srl, San Giuliano Milanese, Italy) for GPR55 using Lipofectamine RNAiMAX (Invitrogen Srl, San Giuliano Milanese, Italy) reagent according to the manufacturer's instructions.

Following transfection, the cells were incubated at 37 °C for 24 h. The sequences of the siRNA used were as follows; sense, 5'-AGGUGUUUGGCUUCCUCCUUCCCAU-3'; antisense, 5'-AUG GGAAGGAGGAAGCCAAACACCU-3'. The stealth RNAi negative control duplex, whose GC content is similar to that of the duplex siRNA, was used as a negative control.

Statistical analysis

All experiments were perfomed in triplicate. Results were analyzed by the one-way ANOVA,

Nerve growth factor is substantially released by human mast cells challenged with inflammatory stimuli

In order to assess the ability of the human mast cell line HMC-1, cultures were incubated 24 h with graded concentrations of the pro-inflammatory compound phorbol myristate acetate (PMA), an activator of protein kinase C. PMA induced robust release of NGF by HMC-1 cells in a concentration-dependent manner. The most effective NGF releasing concentration of PMA was 50 ng/ml (fig. 1, panel A). The release induced by PMA (50 ng/ml) was also time dependent, as incubation of HMC-1 cells resulted in significantly increased levels of tissue culture media NGF after 8h, reaching a maximum after 24h incubation as assessed by ELISA assay of the tissue culture media. The expression of NGF was also assessed by western blot at identical time points in respective cell lysates; data obtained indicated that NGF content of HMC-1 cell was partially depleted after 8h incubation, and totally after 24 h incubation, in a way inversely proportional to the amounts of NGF released into the tissue culture media (Fig. 2, panels A and B).

Endocannabinoids modulate NGF release by HMC-1 cells.

In view of the pro-inflammatory role of NGF contained in mast cells, as well as of the inhibitory effects of endocannabinoids upon various inflammatory parameters, the effects of the endocannabinoid derivative PEA was assessed in the model of PMA-induced NGF release, in cultured HMC-1 cells. Incubation of HMC-1 cells with graded concentrations of the cannabinoid related molecule palmithoylethanolamide (PEA) prevented the increase of NGF release in the tissue culture media determined by phorbol myristate acetate (PMA), as assessed by ELISA assay (Fig. 3).

The most effective concentration of PEA was 50 g/ml. In the same line, previous results inverse pattern of NGF expression was found in HMC-1 cell lysates undergone western blot analysis (Fig.

4, panel A and B)

In addition to ELISA and western blot data, HMC-1 cells were incubated with PEA 50 g/ml, and then challenged with a specific anti-NGF fluorescent antibody. Data obtained indicate that, whereas PEA resulted in substantial prevention of NGF depletion from HMC-1 cells (Fig. 5).

NGF release by activated mast cells is associated with proliferation of endothelial cells.

Considering the role of mast cells in inflammatory phenomena of various origins [START_REF] Gribaldeston | Effector and potential immunoreg-ulatory roles of mast cells in IgE-associated acquired immune responses[END_REF], and that NGF contributes to angiogenesis processes [START_REF] Cantarella | Nerve growth factor-endothelial cell interaction leads to angiogenesis in vitro and in vivo[END_REF], we attempted to establish a role for mast cellreleased NGF in relation to different parameters related to endothelial cell biology.

To do so, HMC-1 cells were first treated with PMA to allow de-granulation and consequent NGF release. Then, graded concentrations of supernatants were added to the usual incubation media of HUVEC cells.

HUVEC treated with concentrated supernatants from PMA-challenged HMC-1 responded with increased proliferation (Fig. 6, panel A). The addition to the tissue culture media of either a NGF monoclonal antibody, or PEA prevented the increased mitogenesis of HUVEC cells observed after addition of activated HMC-1 cell-conditioned medium (Fig. 6, respectively panels B and C).

3.4

The blunting effects of PEA on mast cell NGF release are mostly mediated by the GPR55 orphan receptor.

In order to unravel molecular mediators and mechanisms underlying the effects of PEA on mast cell-dependent NGF release, investigation continued focusing on cannabinoid-related receptors pattern in HMC-1 cells.

RT-PCR mRNA analysis for CB1 and CB2 receptors revealed that the human mast cell line HMC-1 lacks both receptors, as compared to the control human neuronal cell line HNC (human neuronal cells)(Fig. 7, panel A) mRNA data corresponded with western blot analysis, which indicated the absence of both receptor protein in HMC-1 cells (Fig. 7, panel B). To answer the question whether or not the GPR55 orphan receptor could play a functionally relevant role in mediating the inhibiting effects of PEA, we then investigated consequences of GPR55 receptor blockade on mast cell-related NGF release in HMC-1 cells. To do so, cells were first transfected either with the positive GPR55 RNAi + , or with its corresponding negative GPR55

RNAi -.

Incubation of HMC-1 cells with GPR55 RNAi + , resulted in time dependent decrease of GPR55 receptor protein expression. Western blot analysis of HMC-1 cell lysates revealed maximal effect of GPR55 RNAi + occurred after 48 h incubation, whereas GPR55 protein expression returned to basal values after 72 h of incubation with the positive GPR55 RNAi + (Fig. 8, upper and lower blots).

Similar results were obtained by using immunofluorescence methods, using a specific GPR55 monoclonal antibody (data not shown).

Moreover, to provide the proof of concept that GPR55 orphan receptor is functionally enrolled in mast cell-dependent NGF release, the latter was assayed in the tissue culture media of HMC-1 cells that had been transfected with either GPR55 RNAi + , or GPR55 RNAi -, in various experimental conditions. In fact, PEA was ineffective in lowering amounts of NGF released into the media in HMC-1 cells treated with PMA, transfected with GPR55 RNAi + , whereas it was able to induce significant reduction of NGF in those transfected with the negative GPR55 RNAi -(Fig. 9).

A c c e p t e d

M a n u s c r i p t 12

DISCUSSION

In this paper, we demonstrate that nerve growth factor release from mast cells activated by inflammatory stimuli is inhibited in the presence of PEA, a lipid molecule belonging to the endocannabinoid family.

It is known that NGF is released by activated immunocytes and may mediate inflammatory reactions [START_REF] Aloe | The expanding role of nerve growth factor: from neurotrophic activity to immunologic diseases[END_REF]. In this line, an increased number of polymorphonucleate cells are observed in animal models of inflammation [START_REF] Metcalfe | Mast cells[END_REF], and the neurotrophin possesses hyperalgesic properties as assessed by various tests for pain score in laboratory species, as well as in humans. [START_REF] Dmitrieva | Sensitisation of visceral afferents by nerve growth factor in the adult rat[END_REF][START_REF] Farquhar-Smith | A novel neuroimmune mechanism in cannabinoid-mediated attenuation of nerve growth factor-induced hyperalgesia[END_REF]. In addition, NGF has been shown to fuel the inflammatory angiogenic process through its mitogenic effects upon endothelial cells [START_REF] Cantarella | Nerve growth factor-endothelial cell interaction leads to angiogenesis in vitro and in vivo[END_REF].

In line with these current literature reports, the application of the pro-inflammatory molecule PMA to cultured human mastocytic cells HMC-1 induces time-related release of NGF. Maximal release was observed after 24 h incubation with PMA. Now, evidence shows that inflammatory processes may be delayed after the occurrence of a noxious stimulus [START_REF] Williams | The diverse potential effector and immunoregulatory roles of mast cells in allergic disease[END_REF]. For example, mast cells increase their number and are activated following allergen or bacterial lipopolysaccharide challenge [START_REF] Li | The role of mast cells in endotoxin-induced uveitis[END_REF], as well as in increasing post-traumatic or post-ischemic inflammatory events [START_REF] Costa | Therapeutic effect of the endogenous fatty acid amide, palmitoylethanolamide, in rat acute inflammation: inhibition of nitric oxide and cyclooxygenase systems[END_REF]. It is in fact common notion that a quantitative evaluation of the real damage consequent to application of noxious stimuli is reasonable after one day or more from damage [START_REF] Rosa | Studies on the mediators of the acute inflammatory response induced in rats in different sites by carrageenan and turpentine[END_REF]. For example, in nervous trauma, this is the consequence of the progressive recruiting of neurons to apoptotic phenomena, which are triggered with the traumatic event and eventually progress in following hours [START_REF] Costa | Therapeutic effect of the endogenous fatty acid amide, palmitoylethanolamide, in rat acute inflammation: inhibition of nitric oxide and cyclooxygenase systems[END_REF]. Thus, it is plausible to hypothesize that mast cells activated by aspecific inflammatory stimuli release mediators of inflammation, including NGF, with a delayed schedule if compared to other cells, such as neutrophils that are instead promptly recruited to the inflammatory site shortly after application of noxae [START_REF] Chen | Neutrophil-derived leukotriene B4 is required for inflammatory arthritis[END_REF]. In our hands, immunofluorescence experiments indicated that granules of HMC-1 cells were depleted of NGF concomitantly with increased levels of the neurotrophin into the culture media.

A c c e p t e d M a n u s c r i p t 13 Thus, as endocannabinoids have been proven to physiologically exert anti-inflammatory effects [START_REF] Costa | Therapeutic effect of the endogenous fatty acid amide, palmitoylethanolamide, in rat acute inflammation: inhibition of nitric oxide and cyclooxygenase systems[END_REF], it appears plausible that incubation of PMA-challenged HMC-1 cells with the endocannabinoid-related lipid molecule PEA, resulted in decreased release of NGF into the culture media and, in parallel, in decreased degranulation of mast cells, thus preventing detrimental effects of NGF and other mediators released abundantly following their activation during inflammatory processes [START_REF] Dmitrieva | Sensitisation of visceral afferents by nerve growth factor in the adult rat[END_REF].

Post-traumatic or -ischemic inflammation may be associated with progressive cell loss and proliferation of non-specific cell elements, such as fibroblasts [START_REF] Badid | Role of myofibroblasts during normal tissue repair and excessive scarring: interest of their assessment in nephropathies[END_REF], as well as with neoangiogenesis [START_REF] Emanueli | Nerve growth factor promotes angiogenesis and arteriogenesis in ischemic hind limbs[END_REF]. The latter would either take place in response to vasoactive stimuli which occur in the inflammatory process, or by hypoxia and is nevertheless fuelled by overproduction of proangiogenic molecules, such as NGF [START_REF] Emanueli | Nerve growth factor promotes angiogenesis and arteriogenesis in ischemic hind limbs[END_REF].

In this line, tissue culture media conditioned by mast cells activated with PMA were able to promote endothelial cell proliferation. The mitogenic potential of conditioned media was however blunted when endothelial cells had been pre-treated with a specific NGF monoclonal antibody, thus corroborating the NGF hypothesis of angiogenesis promotion. In fact, it has been reported that HUVEC express the NGF specific tyrosine kinase receptor trk140, which mediates mitogenesis of endothelial cells in vitro and formation of new vessels in vivo [START_REF] Jiang | Expression of human p140trk receptors in p140trkdeficient, PC12/endhotelial cells resulting nerve growth factor-induced signal transduction and DNA synthesis[END_REF][START_REF] Cantarella | Nerve growth factor-endothelial cell interaction leads to angiogenesis in vitro and in vivo[END_REF].

When inflammatory angiogenesis is triggered, formation of new vessels is however the result of the balanced action of multiple factors of either stimulatory or inhibitory nature [START_REF] Folkman | Angiogenesis in cancer, vascular, rheumatoid and other disease[END_REF]. Thus, besides VEGF, FGF [START_REF] Ferrara | Molecular and biological properties of the vascular endothelial growthfactor family of proteins[END_REF], or NGF [START_REF] Cantarella | Nerve growth factor-endothelial cell interaction leads to angiogenesis in vitro and in vivo[END_REF], endothelial cells are under the influence of angiostatin [START_REF] Ribatti | Endogenous inhibitors of angiogenesis: a historical review[END_REF], endostatin [START_REF] O'reilly | Endostatin: anendogenous inhibitor of angiogenesis and tumor growth[END_REF], or endocannabinoids [START_REF] Bifulco | Endocannabinoids as emerging suppressors of angiogenesis and tumor invasion[END_REF].

We observed that the pharmacological endocannabinoid compound PEA eventually slowered HUVEC cell proliferation in a fashion similar to the anti-NGF monoclonal antibody.

These data not only suggest that endocannabinoids exert antinflammatory effects [START_REF] Lambert | The palmitoylethanolamide family: a new class of anti-inflammatory agents?[END_REF], but that these molecules also restrain angiogenic processes eventually occurring during an inflammatory process.

In addition, as cannabinoid derivative have been suggested and/or approved for clinical use in A c c e p t e d M a n u s c r i p t 14 various pathological conditions, such as multiple sclerosis (MS) [START_REF] Rog | Cannabis-based medicines in multiple sclerosis-a review of clinical studies[END_REF] and gastrointestinal and liver diseases [START_REF] Izzo | Emerging role of cannabinoids in gastrointestinal and liver diseases: basic and clinical aspects[END_REF], one could envision their use as anti-mast cell/NGF component of inflammation.

Now one reasons that anti-inflammatory effects of cannabinoids are mostly mediated by the CB1/CB2 family of cannabinoid receptors [START_REF] Bolognini | The plant cannabinoid Delta9-tetrahydrocannabivarin can decrease signs of inflammation and inflammatory pain in mice[END_REF]. However, no expression of these two receptors was detected in HMC-1 cells [START_REF] Maccarrone | Human mast cells take up and hydrolyze anandamide under the control of 5-lipoxygenase and do not express cannabinoid receptors[END_REF]. Thus, in line with the hypothesis that some effects of endocannabinoids are mediated by the GPR55 receptor [START_REF] Ryberg | The orphan receptor GPR55 is a novel cannabinoid receptor[END_REF], either GPR55 mRNA and protein were detected in HMC-1 cells. These finding are in accordance with other work, describing GPR55 expression in other cell type of the immune system, such as microglia [START_REF] Pietr | Differential changes in GPR55 during microglial cell activation[END_REF], and led to the hypothesis that they could indeed play a functional role.

Results showed that inhibition of GPR55 protein synthesis occurs in HMC-1 cells transfected with the GPR55 RNAi + , and that PEA is very ineffective in blunting NGF levels in the media from cells bearing the GPR55 RNAi + transfection. These data strongly suggest that the GPR55 orphan receptor is responsible for the majority of the inhibiting effects of PEA on PMA induced release of NGF from activated mast cells.

In synthesis, these data are suggestive for a substantial contribution of NGF to the inflammatory activity of mast cells in the human cell line HMC-1 and that, in particular, it also exerts a potent proliferative effect upon human endothelial cells, the first phase of angiogenesis.

Cannabinoids, such as PEA, effectively inhibit NGF release from mast cells and consequent endothelial cell proliferation, an effect mediated by the orphan receptor GPR55.

In conclusion, we hypothesize that inhibition of the GPR55 receptor might be envisioned as a novel candidate mode for treatment of human inflammatory disorders of various origins, by restraining the angiogenic component.

  96 h. In other experiment NGF neutralizing antibodies (1 g/ml) (R&D Systems, Inc. Minneapolis, MN, USA) were added together with (10, 20, 40 and 80 % of CM) to HUVECs and incubated along the entire experiment. In other experiments HUVEC were treated with PEA 50 g/ml, or PMA 50 ng/ml or with the combination of both substance.

A c c e p t e d M a n u s c r i p t 8 2. 7

 87 RNA interference (RNAi) analysis.

  followed by the least significance Duncan's test. Vertical bars in figures are means + S.E of at least three separate experiments was set at a p-value <0.05.

A c c e p t e d M a n u s c r i p t 10 treatment

 10 of cells with PMA depletes intracellular NGF from mast cells, pre-treatment of cells with

Thus, with the

  aim to elucidate the possible mechanisms responsible for PEA effects in PMA stimulated HMC-1 cells, a new member of the cannabinoid receptor family, the orphan receptor GPR55, was analyzed in HMC-1 cells. Either GPR55 mRNA (RT-PCR; fig. 7, panel C) or protein (western blot; fig. 7, panel D) were detected in HMC-1 cells.

A c c e p t e d M a n u s c r i p t 11 3. 5

 115 The GPR55 orphan receptor is specifically relevant to pharmacological modulation of mast cell-dependent NGF release.

Figure 1 .

 1 Figure 1. Nerve growth factor (NGF) amounts measured in the tissue culture media of

Figure 2 .Figure 3 .

 23 Figure 2. Panel A: Time-dependent effect of the phorbol esther phorbol myristate acetate

Figure 4 .A c c e p t e d M a n u s c r i p t 21 *

 421 Figure 4. Panel A: Effect of the cannabinoid palmytoyl-ethanolamide (PEA; 50 g/ml) on

Figure 5 .

 5 Figure 5. Immunoflorescence analysis of NGF content in HMC-1 cells in culture, untreated

Figure 6 .

 6 Figure 6. Panel A: Proliferation tests on human umbilical vein endothelial cells (HUVEC)

A c c e p t e d M a n u s c r i p t 22 Figure 7 .

 227 Figure 7. Upper panels: Reverse transcriptase polymerase chain reaction of the mRNA,

Figure 8 .Figure 9 .

 89 Figure 8. Upper panels: Time course of the effect of the transfection of human mastocytic

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Figure 9 A

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  80 % of CM)

ACKNOWLEDGEMENTS

This work was accomplished thanks to generous contribution of the Epitech group inc., Abano Terme, and, in part, with the funds granted by MIUR to the PhD school in Preclinical and Clinical Pharmacology, University of Catania School of Medicine.


K Vekey

Ron M A Heeren

Oscar F Van Den Brink
email: oscar.vandenbrink@akzonobel.com

Junkan Song

Antony Memboeuf

Károly Vékey

Discrimination between Charge-Catalyzed and Charge-Independent Fragmentation Processes of Cationized Poly (n-Butyl Acrylate)

When performing structural investigation of macromolecular systems using tandem mass spectrometry, an important matter is the choice of the cation and how that does affect the tandem mass spectra. Moreover, when studying mechanistic aspects, the role of the adduct ions in the mechanism of the fragmentation processes is often discussed: Is the process charge-induced (more accurately described as charge-catalyzed) or charge-remote (more accurately described as charge-independent). In a previous study [START_REF] Memboeuf | Energetics of fragmentation for cationized poly(ethylene glycol) oligomers[END_REF], we shed light on the catalytic effect of lithium in the case of cationized poly(ethylene glycols) (PEGs). The activation energy of the main fragmentation process for the trimer was shown, by means of Density Functional Theory calculations, to decrease by as much as 0.3 eV in the presence of lithium.

To further sketch our picture of the role of cation adducts on the fragmentation of even electron ions, we present in this communication the results obtained on the fragmentation of poly (n-butyl acrylate), PBA, with different alkali ions and various degrees of polymerization. Thus, we present a method to clarify the role of the charge on the fragmentation processes.

The experiments were performed on a Bruker Esquire 3000plus ion trap mass spectrometer with PBA from 4 up to 12 monomeric units (polymerization degree varies with different cations). The experimental setting is identical to the one described in the previous study [START_REF] Memboeuf | Size Effect on Fragmentation in Tandem Mass Spectrometry[END_REF] and the structure of PBA selected can be found in the supporting information. PBA oligomers with positively charged alkali ion adducts including Li + , Na + , K + or Cs + were studied in the system. The main fragmentation processes observed are the loss of 56 Da and 130 Da in the cases of lithium and sodium adducts. Using high resolution and high accuracy mass spectrometry, the elemental compositions of these losses were identified to be C 4 H 8 and C 8 H 16 O. Backbone cleavage was not observed for PBA; all neutral losses originate from side chain cleavages. The PBA used here (i.e. with a butylmethyl carboxylate and a hydrogen end group) was specifically selected this work in order to avoid any end group fragmentation.

When potassium and caesium were used for adduct formation, no significant fragmentation was observed. This is most probably due to cation detachment, which was shown, e.g. in the case of cationized PEGs, to become preferential as the size of the cation increases [START_REF] Memboeuf | Structure and energetics of poly(ethylene glycol) cationized by Li(+), Na(+), K(+) and Cs(+): a first-principles study[END_REF]. This observation supports previous studies claiming the value of low mass cations for structural investigation of oligomers using tandem MS: stable complexes are formed with Li + and Na + cations that enable the macromolecule to dissociate into various fragments carrying specific structural information.

To study the energetics of polymer fragmentation, the survival yield (SY) [START_REF] Memboeuf | Size Effect on Fragmentation in Tandem Mass Spectrometry[END_REF][START_REF] Derwa | New basis for a method for the estimation fo seconary ion internal energy distribution in 'soft' ionization techniques[END_REF][START_REF] Heeren | A novel method to determine collisional energy transfer efficiency by Fourier transform ion cyclotron resonance mass spectrometry[END_REF][START_REF] Collette | Comparison of the internal energy distributions of ions produced by different electrospray sources[END_REF][START_REF] Guo | Manipulating internal energy of protonated biomolecules in electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry[END_REF] is a convenient quantitative measure. It is defined according to Eq.1:

M M F I SY I I = + (Eq.1)
in which I M is the intensity of the cationized molecule and ΣI F is the sum of all product ion intensities.

The survival yield curve is typically of the sigmoid-type (continuously decreasing from 1, at low energy, to 0 at high energy). Similarly the intensity of the individual product ions can be used as numerator in Eq1 and the corresponding curves can then be plotted. This way, a breakdown diagram is obtained. These diagrams were plotted in the case of lithium and sodium cationized PBA with 10 monomeric units and are shown in Figure 1. Only two of the most intense fragmentation processes (i.e. neutral loss of 56 and loss of 130 Da) are shown here for the sake of clarity and as they represent altogether between 80-90% of the product ions observed. An example of the spectra underlying the data presented in Figure 1 is shown in the supporting information. In the case of the lithium adduct, the two curves of the product ions are running closer and more parallel to each other, while they are much more separated in the case of the sodium adduct. Hence, the relative importance of the respective fragmentation pathways (loss of 56 and 130Da) changes significantly with the adduct cations [START_REF] Cooks | Thermochemical determinations by the kinetic method[END_REF]. To further investigate this effect, the relative intensities of the two reaction channels were compared as a function of polymer size. For a given oligomer the ratio changes significantly with collision energy, as shown in Figure . 1. At high energy the abundance ratio of the two fragmentation process becomes fairly constant; so this was measured corresponding to ca. 95% fragmentation (SY=0.05). The abundance ratio measured for the two processes, -56/-130, was measured as a function of molecular size, and this is shown in Figure . 2; both for lithium and sodium cationized polymers. The figure shows that the relative intensities of the two main fragmentation processes are approximately independent of the degree of polymerization; especially for hexamers and above. The asymptotic values calculated are 1.27±0.11 for PBA oligomers with Li + adduct and 1.99±0.12 with Na + adduct. (The method of error estimation is presented in supporting information). Figure 1 shows that the breakdown curve changes when the cation is changed from Li + to Na + . This clearly suggests that at least one of the two (major) fragmentation processes is charge-catalyzed. There are two possibilities; only one of the processes is charge-catalyzed (and the other is charge independent) or both processes are charge-catalyzed. As mentioned above, both fragmentation channels involve side chain losses. If the process is charge-catalyzed, there is only one possible reaction channel in the cationized molecule (i.e. that close to the charged site). If the process is independent of the charge; the number of possible reaction channels will increase with the degree of polymerization (possibly linearly with polymerization degree). As a consequence, the abundance of charge independent processes should increase with molecular size. The abundance of a charge-catalyzed process, however, will not be affected by varying the molecular size. Therefore, under conditions of similar degrees of fragmentation, a combination of a charge-catalyzed and a charge-independent process will lead to a change in the intensity ratio of product ions when the mass of the precursor ions is changed. If both processes are charge-catalyzed the intensity ratio will not be affected on change of the precursor ion's mass. Figure 2 clearly demonstrates that the ratio of the two processes reaches a constant value at n=6. Therefore, both of the fragmentation processes, viz. the loss of 56 Da and the loss of 130 Da, are charge-catalyzed.

The flow chart shown in Scheme 1 can be used to formalise the above reasoning in a procedure for determining whether processes are charge-catalyzed or charge-independent. The validity of this procedure is, at this stage, limited to polymers with a periodic structural pattern that show two (main) fragmentation products. There are two critical steps in the procedure: The first one is drawing breakdown diagrams with different cations, which reveals whether there is at least one charge-catalyzed fragmentation process. The second one is performing a size-dependence analysis, which provides information about the similarity of the nature of the fragmentation processes. This paper demonstrated that changing the size of the adduct ions can be used to increase the degree of fragmentation of polymers in tandem mass spectrometry. In fact similar to the case of PEG oligomers, tandem MS spectra of PBA oligomers ionised with Li + and Na + provide more structural information than those of PBA oligomers ionised with larger cations [START_REF] Memboeuf | Structure and energetics of poly(ethylene glycol) cationized by Li(+), Na(+), K(+) and Cs(+): a first-principles study[END_REF]. Although the cation doesn't qualitatively change the fragmentation pattern (the same product ions are observed), the nature of the cation changes the relative abundance of the respective fragmentation processes. This illustrates well the catalytic effect the cation can exert on the fragmentation processes observed [START_REF] Naray-Szabo | It was prepared by radical polymerization using tert-butyl peroxy-3,5,5-trimethylhexanoate as initiator at 140 o C in xylene. The number average molecular weight is 2,800[END_REF]. Moreover, we have also shown that performing a simple size-dependence analysis using breakdown diagrams with at least two different cations, the catalytic influence of the cation on the fragmentation processes observed can be clearly demonstrated. We have also delineated a simple procedure for determination on the presence of an effect of the cation on the fragmentation (charge-catalyzed or charge-independent). This is important information for investigations by means of quantum chemical modelling. Although the MS/MS spectra obtained for PBA on ion trap instrument are rather simple (only two product ion peaks are observed), this procedure should also be generally applicable to homopolymers (or alternating copolymers). The limitation is however that there should be more than one product ion. The applicability of the method to tandem MS experiments that produce more than two different product ions should be investigated. A particularly interesting subject of research would be fragmentations in which the backbone of the polymer is cleaved in two ways, producing a multitude of product ions that can be grouped as two types.

Two examples of tandem MS/MS spectra underlying the data presented in Figure 1

Figure 1 .

 1 Figure 1. Breakdown diagrams of (a) lithium and (b) sodium cationized poly (n-butyl acrylate) with 10 monomeric units.

Figure 2 .

 2 Figure 2. Ratios of signal intensities for the two main fragmentation processes (losses of 56 Da / 130 Da) observed at 95-100% fragmentation of the precursor ion, plotted versus m/z for lithium and sodium cationized PBAs. Full lines are asymptotic values obtained after averaging the last 8 values for Li + and the last 6 values for Na + .

Scheme 1 .

 1 Scheme 1. Determination of the cation influence on two fragmentation processes (charge-catalyzed/independent).

  are shown in S2 and S3. /MS spectrum of m/z 1403 (PBA 10 +Li + ) at excitation voltage of 0.64 V /MS spectrum of m/z 1419 (PBA 10 +Na + ) at excitation voltage of 0.64 V The error bar value s presented in Figure 2 is the standard deviation of the ratio of the -56 and -130 product ion peaks. It is calculated according to SEq.1. -is the mean value of the intensities of the product ion peak (-x), ( ) I x s -corresponds to the standard deviation of the ion peak (-x) intensities.

Acknowledgements

We gratefully acknowledge the financial support of the Sixth Framework Program of the European Community for funding the POLY-MS project (MEST-CT-2005-021029). Leo van der Ven, Marco Koenraadt and Ber Yebio from AkzoNobel Car Refinishes, Sassenheim, The Netherlands are acknowledged for the preparation of the acrylic resins.


Sylvie Szulman

Nathalie Aussenac-Gilles

Adeline Nazarenko

Henri V Teguiak

Eric Sardet

Jean Charlet
email: jean.charlet@spim.jussieu.fr

Henry Valéry Teguiak

DAFOE: A Platform for Building Ontologies from Texts

Keywords: D.2.11 [Software Architectures], I.2.4 [Knowledge Representation Formalisms and Methods], H.2.1 [Database Management]: Logical DesignData models Ontology Building, Ontology Editor, Meta-Modelization, Data Model

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

INTRODUCTION

DAFOE 1 is a new platform for building ontologies using different types of linguistic entries (text corpora, results of natural language processing tools, terminologies or thesauri). DAFOE supports knowledge structuring and conceptual modelling from these linguistic entries as well as ontology formalization. DAFOE outputs models with two main original features: an ontology articulated with a lexical component and a connection with the text or linguistic entry that motivated their definition. The requirements of the platfom and its development focus 1) on integrating various kinds of tools currently used within a single modelling platform, 2) on guaranteeing persistence and traceability of the whole ontology building process, and 3) on developing the platform in an open source paradigm with possible plugin extensions.

TEXT-BASED ONTOLOGY ENGINEER-ING

There is a growing interest for ontologies and related tools, including Ontology Engineering Environments. Many of them are pure ontology editors that support the development of formal ontologies but do not assist the tasks of knowledge acquisition or structuring. Knowledge engineers are supposed to have a first of ontology draft before using such tools. Since 2003, a significant shift occurred. Firstly, a parallel has been established between ontology population from text and semantic (textual) annotation. Secondly, many projects have proved the benefit brought by Human Language Technologies (HLT), including NLP, Information Extraction, Knowledge Discovery or Text Miming, for complementarity activities such as ontology learning from text and ontology population. The diversity and richness of existing HLT tools as well as the complexity of the ontology development tasks underlined the need for tool suites and platforms where the knowledge engineer can define its modelling strategy.This challenge is also one major motivation of the DAFOE project but the platform targets more ambitious goals: a better interoperability, a higher robustness and an easier combination of HLT and ontology technologies.

The goal of DAFOE is both to extend the variety of HLT that can be used and to support scalable ontology engineering. It claims that there are several ways to get an ontology, and that tools and processes must be selected according to each ontology case-study. DAFOE will propose tools similar to those of Text2Onto, but human supervision will play a major role for selecting tools, validating their results and conceptualizing. Knowledge conceptualization requires that a human selects and organizes properly concepts and relations, but this process can be guided. The result of DAFOE will typically be a termino-ontological resource where the ontology is connected to a lexical component.

DATA MODEL

DAFOE data model has to take into account various ontology building strategies, whatever information source (texts, terminologies, thesauri or human expertise) is used.

Overall Architecture

The data model is based on a valid methodology for building ontologies from texts, which has inspired tools such as Terminae [START_REF] Aussenac-Gilles | The Terminae method and platform for ontology engineering from texts[END_REF] or Text2Onto [START_REF] Cimiano | Text2onto -a framework for ontology learning and data-driven change discovery[END_REF]. This methodology takes into account the whole process of "transforming" textual data into ontologies and split it into different phases, which correspond to various input levels if one wants to start with a thesauri rather than text, for instance. This methodologies relies on two main ideas: 1/ textual data are an important information source to build ontologies, especially if the ontology is to be used to annotate textual documents but 2/ textual data cannot be mapped directly into an ontology and the transformation must be mediated.

Corpora Layer

The corpora layer is useful for the knowledge engineer willing to build an ontology from text. He/she can build a working corpus by selecting different source documents and browse that corpus, either as plain documents or as segmented ones. In the data model the corpus is represented as a sequence of sentences, each one having a unique identifier.

Terminological Layer

The terminological layer gives a view over the domain specific lexicon of the corpus. It gathers the terms of the domain and their relationships. Terminological knowledge is traditionally produced by NLP tools such as term extractors applied on the working corpus. The underlying assumption is threefold: text analysis can extract term candidates that are relevant for a given domain, those terms are likely to be turned into ontology concepts and the distribution of these terms reflects their semantics [START_REF] Harris | Mathematical Structures of Language[END_REF]. DAFOE visualizes results of NLP tools such as YaTeA term extractor [START_REF] Aubin | Improving term extraction with terminological resources[END_REF]. NLP results are given to DAFOE through an API. The data model is extensible and may be adapted to different NLP tools.

Termino-Conceptual Layer

This layer represents a semantic structure of unambiguous termino-concepts (TC) and termino-conceptual relations (RTC). The knowledge engineer may build that layer by importing a preexisting termino-conceptual resource such as a thesaurus or out of the analysis of the terminological layer. In that case, he/she analyses the meaning of terms and relations that appear at the terminological layer with respect to each other and by looking at their occurrences. The termino-conceptual layer is pivotal for transforming linguistic elements into conceptual ones and tracing the ontology back to the linguistics.

Ontology Layer

The ontology data model allows to formalize TCs and RTCs in a formal language equivalent at OWL-DL. Concepts are described as classes, individuals as instances of classes, properties between classes as object properties and properties between a class and a value as data properties or attributes. An automatic process will translate TCs and RTCs into formal concepts in a hierarchy with inherited properties as usual subsumption in description language. This translation exploits the structure of the semantic network represented in the termino-conteptual layer and the differential criteria associated with TCs and RTCs.

CONCLUSION

A prototype of the DAFOE platform has been implemented. DAFOE is intended to provide a variety of ontology engineering methods. As such a diversity can not be managed in a unique and static model, we adopted an extended Ontology-Based Database (OntoDB) architecture that supports model management and plugins. The strength of DAFOE approach is i) a precise definition of the various steps by which one can design a formal ontology; ii) a data model guaranteeing persistence and traceability of the whole ontologie building process; iii) the supply of flexible methodological guidelines that support the knowledge engineer without constraint; iv) an architecture based on the MOF model and plugins adaptability to ensure extensibility of the model and processes around a core tool; v) the specification of various modelling strategies based on different input/output of the platform; vi) the final production of an ontology which is associated to a terminological component.

Figure 1 :

 1 Figure 1: Data model architecture.

  The data model is therefore structured into four layers as represented in Figure 1. Each one corresponds to a specific methodological step.

		API for NLP
		tools
		Imports
	Entry	Layer 0 (corpora) Text visualization
	Entry	Layer 1 (terminological) Linguistic study
	Entry	Layer 2 (terminolo-conceptual) Semantic network building	SKOS export
	Entry	Layer 3 (ontological) Formal ontology building	OWL export