Rémy Boyer
email: remy.boyer@lss.supelec.fr

Guillaume Bouleux
email: guillaume.bouleux@lss.supelec.fr

Karim Abed-Meraim

COMMON POLE ESTIMATION WITH AN ORTHOGONAL VECTOR METHOD

In some applications as in biomedical analysis, we encounter the problem of estimating the common poles (angularfrequency and damping-factor) in a multi-channel set-up composed as the sum of Exponentially Damped Sinusoids. In this contribution, we propose a new subspace algorithm belonging to the family of the Orthogonal Vector Methods which solves the considered estimation problem. In particular, we expose a root-MUSIC algorithm which deals with damped components for an algorithmic cost comparable to the root-MUSIC for constant modulus components. Finally, we show by means of an example, that the proposed method is efficient, especially for low SNRs.

INTRODUCTION

Common poles estimation in a multi-channel Exponentially Damped Sinusoids (EDS) signal is an open problem since this problematic has been treated rarely. We can find some work for the two channels case [START_REF] Golub | Matrix Computations[END_REF][START_REF] Trefethen | Numerical linear algebra[END_REF][START_REF] Morren | Detection of autoregulation in the brain of premature infants using a novel subspace-based technique[END_REF] but, to our best knowledge, only a single method has been proposed so far for the case of more than two channels. This method, named MUS-CLE [START_REF] Papy | Common pole estimation in the multi-channel exponential data modelling[END_REF] for MUlti-channel Subspace-based Common poLe Estimation, has been applied to the biomedical signal analysis and is based on shift-invariance of the signal subspace and Total-Least-Squares [START_REF] Golub | Matrix Computations[END_REF] technique. In this paper, we propose a new solution to the common poles estimation problem which is based on the orthogonality of the signal and noise subspaces. Thus, the proposed method belongs to the family of the Orthogonal Vector Methods [START_REF] Van Der Veen | Subspace-based signal analysis using singular value decomposition[END_REF]. In addition, we propose an improved version of the DMUSIC algorithm [START_REF] Geoffrey) Li | A high-resolution technique for multi-dimensional NMR spectroscopy[END_REF] which is the MUSIC algorithm for damped sinusoids. This algorithm has been introduced in the context of the biomedical analysis processing and is based on a costly multidimensional search. In this paper, we propose a "root" version of the DMUSIC algorithm, called root-DMUSIC. More specifically, we avoid the costly multidimensional search by zeroing a polynomial form and by inspecting the orthogonality condition for preselected zeros. This is an efficient way to decrease the complexity burden of the method without addi-tional assumptions on the damping-factor values. Finally, the overall complexity cost of the proposed method is comparable to the root-MUSIC [START_REF] Rao | Performance analysis of Root-Music[END_REF] for constant modulus components. Consequently, this new algorithm allows the comparison with shift-invariant techniques as the MUSCLE algorithm. Moreover, we show on noisy multi-channel EDS signal example that in some situations, it is preferable, in terms of estimation accuracy and even w.r.t the computational cost, to use the root-DMUSIC algorithm instead of the MUSCLE algorithm.

COMMON POLE ESTIMATION FOR THE MULTI-CHANNEL EDS MODEL

The multi-channel EDS model is given

for k = 1, • • • , K and t = 0, • • • , N/2 -1 by: x k (t) = Z c a k (t) + Z k b k (t) ∈ C N/2 , ( 1
)
where K is the number of channels, N is the sample size,

a k (t) = [α k (1)z t 1,c , • • • , α k (M c )z t M c ,c ] T b k (t) = [β k (1)z t 1,k , • • • , β k (M k )z t M k ,k ] T and α k = [α k (1), • • • , α k (M c )] T , β k = [β k (1), • • • , β k (M k )] T are two vectors of complex am- plitude, Z c =    1 1 . . . 1 . . . . . . . . . z N/2-1 1,c z N/2-1 2,c . . . z N/2-1 M c ,c    N/2×M c (2)
contains the common poles z m,c = e dm,c+iωm,c and:

Z k =    1 1 . . . 1 . . . . . . . . . z N/2-1 1,k z N/2-1 2,k . . . z N/2-1 M k ,k    N/2×M k (3)
is associated to the non-common poles z m,k = e d m,k +iω m,k of the k-th channel. The processing window is chosen equal to N/2 as its optimal value belongs to the range [N/3, 2N/3] as shown in [START_REF] Van Der Veen | Subspace-based signal analysis using singular value decomposition[END_REF][START_REF] Hua | Matrix pencil method for estimating parameters of exponentially damped/undamped sinusoids in noise[END_REF]. The common pole estimation problem can be algebraically described according to:

K k=1 R Z c Z k = R (Z c ) . ( 4
)
where R(A) denotes the column range space of matrix A. So, we look for the intersection of K spaces.

MUSIC-LIKE CRITERION

First criterion

The N/2 × N/2 Hankel matrix associated to the k-th channel admits a Vandermonde-type decomposition according to:

X k = [x k (0), • • • , x k (N/2 -1)] = Z c Z k A k 0 0 B k Z H c Z H k ( 5
)
where

A k = diag(α k ) and B k = diag(β k ). Now, consider K projectors on the noise subspace of X 1 , • • • , X K , denoted, respectively by {P ⊥ 1 , . . . , P ⊥ K }, i.e. P ⊥ i = I -P i where P i is the orthogonal projector on R([Z c Z i ]).
We can give the following result:

Theorem 1 The MUSIC-like criterion defined by:

f (z) = d(z) H K k=1 P ⊥ k d(z) ( 6
)
where

d(z) = [1, z, • • • , z N/2-1 ] T is zero (minimum) if and only if z ∈ {z 1,c , • • • , z Mc,c }, i.e. iff z is a common pole.
Proof: First note that:

d(z) H P ⊥ k d(z) = 0 ⇐⇒ d(z) ∈ R([Z c Z k ]), and
d(z) H P ⊥ k d(z) > 0 otherwise. Hence d(z) H K k=1 P ⊥ k d(z) = 0 is equivalent to d(z) ∈ K k=1 R Z c Z k = R (Z c ) .

Another criterion

Now assume that we know that several poles are common in several channels (but not in all channels), in that case we can exploit this knowledge to reduce the complexity burden of the proposed method. The new algebraic problem is given by:

T i=1 k∈Q i R ([Z c Z k ]) = R(Z c ). ( 7
)
where T is the number of partition of set {1, . . . , K}.

The expression below means that we associate channels for which we know that there is common poles with constraint

T i=1 Q i = {1, . . . , K} and Q i = ∅.
In that case, we can consider the following modified criterion:

g(z) = d(z) H T i=1 Π ⊥ i d(z). ( 8
)
where Π ⊥ i is the orthogonal projector on the noise subspace of matrix:

[X k1 , • • • , X ki ], with Q i = {k 1 , • • • , k i }. (9) or equivalently matrix k∈Qi X k X H k , for i ∈ [1 : T ]. (10)
So, we have to estimate T projectors Π ⊥ i in comparison with K projectors P ⊥ k in the general case, ie., without additional knowledge. As T ≤ K, we reduce the algorithmic burden.

For instance, we can give the following example. Consider three channels according to:

channel 1 z 1 z 2 z 3 channel 2 z 1 z 2 z 4 z 5 channel 3 z 1 z 2 z 5 z 6
The common pole set is {z 1 , z 2 } and if we assume that we know that z 5 belongs to channel 2 and 3. So, we associate channels 2 and 3 according to

Q 1 = {1} and Q 2 = {2, 3}.
As, we have two partitions (T = 2), we need only two projectors Π ⊥ 2 associated to [X 2 X 3 ] and Π ⊥ 1 associated to X 1 . This approach reduces the algorithmic burden since we have to consider only two SVDs in comparison to three in the general case.

Another situation of interest is when the common poles for any pair of channels are only those desired poles

{z 1,c , • • • , z M c ,c }.
In that case, one can partition the set of channels according to Q 1 = {1} and Q 2 = {2, • • • , K} which leads again to 2 SVD computations instead of K.

Estimation of the projectors

The estimation of the noise projectors P ⊥ k is classically obtained by the SVD [START_REF] Golub | Matrix Computations[END_REF] according to:

X k = [ U (S) k Mc+M k U (N ) k N/2-M c -M k ]Σ k V H k (11)
where

U (S) k (respectively U (N ) k
) is the signal (respectively noise) part of the left singular basis. Then, the noise projector

is P ⊥ k = U (N ) k U (N ) k H = I -U (S) k U (S) k H .
Note, that we use the same procedure for projector Π⊥ k but we replace a single Hankel matrix by a sum of Hankel matrices.

ROOT-MUSIC ALGORITHM FOR DAMPED SINUSOIDS

The search procedure associated to the MUSIC criterion for damped sinusoids is multidimensional and therefore is a very costly operation. A MUSIC algorithm, called DMUSIC, has been presented in [START_REF] Geoffrey) Li | A high-resolution technique for multi-dimensional NMR spectroscopy[END_REF] for damped sinusoids. So in this section, we expose the "root" version of the DMUSIC algorithm which essentially consists of zeroing a polynomial form and next by inspecting the orthogonality condition for the preselected zeros. Thus, the overall complexity cost of the algorithm is comparable to the complexity cost of the root-MUSIC algorithm for undamped components.

The criterion of the root-MUSIC is given by f (z) defined in expression [START_REF] Golub | Matrix Computations[END_REF] where we replace d(z) H by d(z -1 ). All z, which are in the generator set of matrix Z c , are zeros of the polynomial form f (z). Due to the Vandermonde structure of vectors d (.), the estimation of the poles can be formulated in term of finding the zeros of the following polynomial:

f (z) = z N 2 -1 N 2 -1 =-N 2 +1
q z with q = q * -.

(

) 12
The above polynomial is of degree N -2 and its explicit computation is given by summing along the diagonals of matrix k P ⊥ k . As a consequence of the Hermitian character of k P ⊥ k , f (z) is a conjugate centro-symmetry polynomial. In addition, q 0 is real and equals to Tr( k

P ⊥ k ) = 2N -(KM c + k M k ).
According to formulation (12), we can simply verify that:

f (z) = z N -2 f * 1 z * . ( 13
)
This property implies that if z m is a zeros then 1/z * m is also a zero and therefore (z m , 1/z * m ) occur in pairs. Note that for the M c desired poles, we have not constraint |z m | = 1, ie., the zeros are inside, outside or on the unit circle. The factorized form of f (z) is then:

f (z) = N -2 m=1 (z -z m ) z - 1 z m * . ( 14
)
At this stage, we assume that all the zeros {z 1 , . . . , z N -2 } of f (z) are possible poles. To further reduce the number of zeros to M c , we evaluate the orthogonality condition:

arg max m∈[1:N -2] 1 d(z m ) H T i=1 Π⊥ i d(z m ) . ( 15
)
for the preselected zeros. The M c pics in the above criterion provide the common poles. Note also, that in most practical situation, the damping factor is non-positive and hence the desired poles are inside the unit circle. This means that one can limit the above selection only to halh of the zeros (only those inside the unit circle).

NUMERICAL SIMULATIONS

In this section, we compare the proposed method, called root-DMUSIC, with the one presented in [START_REF] Papy | Common pole estimation in the multi-channel exponential data modelling[END_REF] by means of 300 Monte-Carlo runs. The latter, named MUSCLE, is based on shift-invariance of the signal subspace. The considered test signal is a 4 channels with two EDS in each where one is common. In Fig. 1, we have drawn the zero locations of the different sinusoidal component. We can see that only the common pole is estimated. As a brief comparison, we have reported on Fig. 2 and3, the Mean Square Error (MSE) of the common angular-frequency and the damping-factorestimates with respect to the SNR for two situations: (1) four channels with spaced EDS and (2) two channels with closely-spaced EDS.

Four channels case

As we can see on Fig. 2, the proposed method shows an interesting gain (compared to MUSCLE) for the angular-frequency and has a similar accuracy for the damping-factor estimation.

Two channels case with closely-spaced sinusoids

In this part, we deal with closely-spaced sinusoids. This situation is difficult since the components of each channel can potentially disturb the estimation of the component of interest. On Fig. 3, we can see that in this scenario the root-DMUSIC can sligntly improve the estimation accuracy of the desired parameters.

CONCLUSION

In this paper, we have proposed a new orthogonal vector method for the common pole estimation of a multi-channel Exponentially Damped Sinusoidal (EDS) model. Our method is an evolution of the DMUSIC algorithm which is the MU-SIC algorithm for damped sinusoids. In our solution, we avoid the costly multidimensional search by zeroing a polynomial form and by inspecting the orthogonality condition only for the preselected zeros. This is an efficient way to decrease the complexity burden of the method which allows possible

Fig. 1 .

 1 Fig. 1. Zero locations

Fig. 2 .

 2 Fig. 2. MSE Vs. SNR, N = 20 (a) angular-frequency ω c = 0.6, ω 1,1 = 1.2, ω 1,2 = 1.5 and ω 1,3 = 0.9, (b) dampingfactor d c = -0.1, d 1,1 = -0.1, d 1,2 = -0.3 and d 1,3 = -0.25.

Fig. 3 .

 3 Fig. 3. MSE Vs. SNR, MSE Vs. SNR, N = 20 (a) angularfrequency ω 1,c = 0.6, ω 1,1 = 0.5 and ω 1,2 = 0.55 (b) damping-factor d 1,c = -0.2, d 1,1 = -0.01 and d 1,1 = -0.2 .

14th European Signal Processing Conference (EUSIPCO 2006), Florence, Italy, September 4-8, 2006, copyright by EURASIP


Ida Storm

Drejer

Have Rasmussen

; Strobel

; Hansen

Hans Christian Bruun

Ergot alkaloids in rye flour determined by solid phase cation-exchange and high pressure liquid chromatography with fluorescence detection

Keywords: ergot alkaloids, HPLC, cereals, rye flour, survey

Ergot alkaloids in rye flour determined by solid phase cation-exchange and high pressure liquid

Introduction

Ergot alkaloids (EAs) are mycotoxins produced by fungi of the genus Claviceps. The fungus infects flowers of cereals and grasses and replaces the developing grain or seed with an alkaloid containing a wintering body, known as the ergot body or sclerotium. The sclerotia are harvested with grain, seed or grass and may result in EA contamination of cereal products and feedstuffs causing ergotism in humans and animals. Rye is the most susceptible species [START_REF] Lorenz | Ergot on cereal grains[END_REF] but C. purpurea attacks more than 400 monocotyledonous hosts [START_REF] Bové | The Story of Ergot: for physicians, pharmacists, nurses, biochemists, biologists and others interested in the life sciences[END_REF]. Ergot cannot be controlled with fungicides [START_REF] Tenberger | Biology and life strategy of the ergot fungi[END_REF].

Epidemics of ergotism were common in Europe in the Middle Ages where it was known as "Holy Fire" or "St. Anthony's fire" [START_REF] Barger | Ergot and ergotism[END_REF]. A case of ergotism involving hundreds of people of the town of Pont St. Esprit, France occurred in 1951 [START_REF] Gabbai | Ergot poisoning at Pont St. Esprit[END_REF][START_REF] Fuller | The day of St. Anthony's fire[END_REF]). More recently an outbreak of gangrenous ergotism was observed in Ethiopia in 2001 [START_REF] Urga | Laboratory studies on the outbreak of gangrenous ergotism associated with consumption of contaminated barley in Arsi, Ethiopia[END_REF]. Symptoms of EA intoxication include abdominal pains, vomiting, burning sensations of the skin, insomnia, hallucinations, and in severe cases convulsions, cardiovascular collapse and gangrene of extremities [START_REF] Barger | Ergot and ergotism[END_REF][START_REF] Gabbai | Ergot poisoning at Pont St. Esprit[END_REF]. Today effective cleaning techniques at the mills make it possible to remove a large proportion of ergots from grain [START_REF] Shuey | Distribution of ergot in mill streams[END_REF][START_REF] Dexter | Physical properties and processing quality of durum wheat fractions recovered from a specific gravity table[END_REF][START_REF] Posner | Wheat flour milling[END_REF]. Nonetheless EAs have been detected in surveys of Swiss, German, Danish, and Canadian cereals and cereal based products in concentrations up to 4000 µg kg -1 [START_REF] Baumann | Mutterkornalkaloide in schweizerischen Getreideprodukten[END_REF][START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF][START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF][START_REF] Scott | Analysis of ergot alkaloids in flour[END_REF][START_REF] Scott | Analysis of grain foods for ergot alkaloids by gradient liquid chromatography[END_REF][START_REF] Lombaert | Mycotoxins in infant cereal foods from the Canadian retail market[END_REF][START_REF] Rasmussen | Ergot in grain, an overview[END_REF].

In the EU no regulatory limits apply to grain for human consumption (Danish Food Directorate 1996;[START_REF] Egmond | Worldwide regulations for mycotoxins in food and feed in 2003[END_REF]. A maximum content of 500 mg ergot bodies kg -1 in grain (0.05 % (w/w)) applies to cereals taken-over by intervention agencies (EU Commission 2000) and a threshold limit of 1000 mg ergot bodies kg -1 (0.10 % (w/w)) applies to feed products containing unground cereals (EU Parliament 2002). No limits apply to ground cereals. The presence of ergot alkaloids in feed, their effects on animal health and the possibility of carry-over to food of animal origin has recently been reviewed by the European Food Safety Authority [START_REF] Efsa | Opinion of the scientific panel on contaminants in food chain on request from the Commission related to ergot as undesirable substance in animal feed[END_REF]. They attend the inaccuracy of expressing the rate of contamination by a percentage of sclerotia, as the alkaloid content and composition may vary with fungal strain, host plant, growth conditions and even within fields and cereal ears [START_REF] Németh | Parasitic production of ergot alkaloids[END_REF]Young 1981a). Furthermore they recommend that more data is supplied on the variability of ergot alkaloids patterns in European feed materials.

There are few published articles on the content of ergot alkaloids in European cereal products.

With the recent attention on the subject some survey have been conducted e.g. by Lauber (Lauber [START_REF] Rasmussen | Ergot in grain, an overview[END_REF] on 55 samples of cereal products including 15 rye flour samples. Rye flour is particularly interesting in Denmark, because rye is the most susceptible cereal [START_REF] Lorenz | Ergot on cereal grains[END_REF] and Danes consume on average 72 g of rye per day, which is more than in any other European country [START_REF] Miraglia | Assessment of dietary intake of Ochratoxin A by the population of EU Member States[END_REF]. Other surveys on cereals and cereal based products are from 1980 [START_REF] Scott | Analysis of ergot alkaloids in flour[END_REF]), 1983[START_REF] Scott | Analysis of grain foods for ergot alkaloids by gradient liquid chromatography[END_REF][START_REF] Baumann | Mutterkornalkaloide in schweizerischen Getreideprodukten[END_REF][START_REF] Baumann | Mutterkornalkaloide in schweizerischen Getreideprodukten[END_REF][START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF][START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF][START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF][START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF] and2003 [START_REF] Lombaert | Mycotoxins in infant cereal foods from the Canadian retail market[END_REF], the latest being concerned only with cereal based infant foods.

[Insert figure 1] More than 100 EAs are known [START_REF] Flieger | Ergot alkaloids -sources, structures and analytical methods[END_REF]. The most commonly found EAs in rye flour are ergotamine and ergocristine, with ergocryptine, ergocornine, ergosine, and ergonovine present in smaller amounts [START_REF] Scott | Analysis of ergot alkaloids in flour[END_REF][START_REF] Scott | Analysis of grain foods for ergot alkaloids by gradient liquid chromatography[END_REF][START_REF] Baumann | Mutterkornalkaloide in schweizerischen Getreideprodukten[END_REF][START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF]). These EAs are very similar differing only in substituents on C8 (Figure 1). An important feature of EAs containing a C9=C10 double bond is the rapid isomerisation at C8, especially in aqueous acidic or alkaline solutions [START_REF] Hofmann | Die Mutterkornalkaloide[END_REF]Komarova & Tolkachev 2001b). The C8-(R) isomers are designated the suffix -ine (e.g. ergotamine) while the C8-(S) isomers have the suffixinine (e.g. ergotaminine). C8 isomers differ in physicochemical and biological properties. pK avalues differ within 0.7 unit [START_REF] Stoll | Über die Stereochemie der Lysergsäuren un der Dihydro-lysergsäuren[END_REF][START_REF] Maulding | Physical chemistry of ergot alkaloids and derivatives .1. Ionization constants of several medicinally active bases[END_REF], the epimers are readily separated by high-pressure liquid chromatography (HPLC) [START_REF] Scott | Analysis of ergot alkaloids in flour[END_REF][START_REF] Szepesi | Separation of ergotoxine alkaloids by high-performance liquid-chromatography on silica[END_REF][START_REF] Baumann | Mutterkornalkaloide in schweizerischen Getreideprodukten[END_REF][START_REF] Ware | Liquid chromatographic determination of ergot alkaloids in wheat[END_REF][START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF], and C8-(R) isomers are physiologically active, while the C8-(S) isomers are inactive [START_REF] Berde | Introduction to the pharmacology of ergot alkaloids and related compounds as a basis of their therapeutic application[END_REF][START_REF] Pierri | Conformational analysis of the ergot alkaloids ergotamine and ergotaminine[END_REF]. However, this does not mean that the C8-(S) isomers may be disregarded. C8isomerisation may occur during the extraction and clean-up procedure which imply acidic or alkaline solutions [START_REF] Stoll | Über die Isomerie von Lysergsäure und Isolysergsäure[END_REF]). It is thus not possible to say how much of the EA was in the C8-(R) and the C8-(S) form prior to sample treatment.

Another important characteristic of EAs is the alkalinity of N6 with pK a values of the protonised EAs ranging from 5-7.4 [START_REF] Hofmann | Die Mutterkornalkaloide[END_REF][START_REF] Stoll | Über die Stereochemie der Lysergsäuren un der Dihydro-lysergsäuren[END_REF]. Thus EAs are positively charged in acidic solutions and neutral at higher pH values. EAs are also light sensitive and degrade upon UVradiation [START_REF] Rutschmann | Chemical background[END_REF]Komarova & Tolkachev 2001b). Many EAs, including the most common, are naturally fluorescent (Komarova & Tolkachev 2001b;[START_REF] Flieger | Ergot alkaloids -sources, structures and analytical methods[END_REF].

Analysis for EAs is most commonly conducted by Reverse Phase High-Performance Liquid Chromatography (RP-HPLC) combined with UV or fluorescence detection (Komarova & Tolkachev 2001a;[START_REF] Flieger | Ergot alkaloids -sources, structures and analytical methods[END_REF] or by LC-MS [START_REF] Mohamed | Quantitative determination of five ergot alkaloids in rye flour by liquid chromatograpy-electrospray ionisation tandem mass spectrometry[END_REF]. In most known and validated methods for qualitative and quantitative determination of EAs in cereal products extraction is done either with non-polar organic solvents under alkaline conditions [START_REF] Scott | Analysis of ergot alkaloids in flour[END_REF] [START_REF] Ware | Liquid chromatographic determination of ergot alkaloids in wheat[END_REF][START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF][START_REF] Rottinghaus | An HPLC method for the detection of ergot in ground and pelleted feeds[END_REF][START_REF] Fajardo | Retention of ergot alkaloids in wheat during processing[END_REF][START_REF] Lauber | Analysis of rye grains and rye meals for ergot alkaloids[END_REF] or with polar solvents under acidic conditions [START_REF] Ware | Liquid chromatographic preparative method for isolating ergot alkaloids, using a particle-loaded membrane extracting disk[END_REF], thus exploiting the acid/base properties of N6. Clean-up is done either by liquid/liquid partitioning at alternating acidic and alkaline conditions [START_REF] Scott | Analysis of ergot alkaloids in flour[END_REF][START_REF] Baumann | Mutterkornalkaloide in schweizerischen Getreideprodukten[END_REF][START_REF] Ware | Liquid chromatographic determination of ergot alkaloids in wheat[END_REF][START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF][START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF][START_REF] Lauber | Analysis of rye grains and rye meals for ergot alkaloids[END_REF] or by solid phase extraction (SPE) [START_REF] Rottinghaus | An HPLC method for the detection of ergot in ground and pelleted feeds[END_REF][START_REF] Fajardo | Retention of ergot alkaloids in wheat during processing[END_REF][START_REF] Ware | Liquid chromatographic preparative method for isolating ergot alkaloids, using a particle-loaded membrane extracting disk[END_REF]. The use of health and environmentally damaging organic solvents is undesirable and liquid/liquid partitioning is time consuming, so SPE is preferred.

Separation of the cleaned extract is done by RP-HPLC with mobile phases of acetonitrile (ACN) mixed with either aqueous base [START_REF] Scott | Analysis of ergot alkaloids in flour[END_REF][START_REF] Baumann | Mutterkornalkaloide in schweizerischen Getreideprodukten[END_REF][START_REF] Ware | Liquid chromatographic determination of ergot alkaloids in wheat[END_REF][START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF][START_REF] Rottinghaus | An HPLC method for the detection of ergot in ground and pelleted feeds[END_REF][START_REF] Lauber | Analysis of rye grains and rye meals for ergot alkaloids[END_REF] or acid [START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF][START_REF] Fajardo | Retention of ergot alkaloids in wheat during processing[END_REF][START_REF] Ware | Liquid chromatographic preparative method for isolating ergot alkaloids, using a particle-loaded membrane extracting disk[END_REF] solutions. Acidic mobile phases are often preferred because silica based HPLC columns are degraded at high pH, but none of the methods employing acidic mobile phases report on the detection of both C8-isomers of EAs.

In this paper we report a method developed for detecting and quantifying both C8-isomers of the most common EAs in rye flour without employing hazardous organic solvents and time-consuming liquid/liquid partitioning. The method was subsequently used to determine the EA content and specific ergot alkaloid distribution of rye flour containing known amounts of ergot sclerotia and unknown rye flour samples from Danish mills.

Experimental

Chemicals and reagents

The same brands of materials were used throughout the experimental period. Chemicals were of analytical reagent grade. Solvents were of analytical reagent grade or of HPLC grade when in contact with the HPLC system. De-ionized water was cleaned on a Milli-Q water purification system (Millipore Corp., Bedford, MA). The standards employed were ergonovine, α-ergocryptine, and ergocristine (Sigma-Aldrich), ergotamine hemitartrate (Tocris), and ergocornine (ICN Biomedicals Inc.). Each standard was dissolved in methanol to a concentration of 500 µg ml -1 of the pure standard. Ergocornine was insoluble in pure methanol and was dissolved in methanol:dichloromethane (1:1 v/v). These standard solutions were stored at -20 o C and used for calibration and for spiking of flour samples. Prior to analysis dilution was performed with mobile phase A (acetonitrile:aq. 0.01 M ammonium carbamate (1:4 v/v)). To avoid light-induced degradation of the EAs all procedures were performed under subdued light. Furthermore glassware was either amber or wrapped in aluminium foil.

Extraction and clean-up

The extraction and clean-up method was modified after [START_REF] Ware | Liquid chromatographic preparative method for isolating ergot alkaloids, using a particle-loaded membrane extracting disk[END_REF]. 25.0 g of rye flour was weighed in a 250 ml Erlenmeyer flask. 100 ml of extraction solution (methanol:0.013 M aq. phosphoric acid (70:30 v/v) was added and the EAs extracted for 30 min. at room temperature on a horizontal shaker (Heto, Birkerød, Denmark). Extracts were transferred to 100 ml glass centrifuge tubes and centrifuged for 10 min. at room temperature (3500 rpm, i.e. 2630 RCF). The supernatant was filtered through a filter paper (Macherey-Nagel, 15 cm Ø, filter paper circles) into Erlenmeyer flasks. 2.0 ml of the extract was mixed with 2.0 ml 0.013 M aq. phosphoric acid and filtered through a Sartorius Minisart RC15 (0.20 µm) filter. The SPE columns (SPEC PLUS 3ML SCX, Ansys Diagnostics Inc., USA) were mounted in a vacuum manifold (Vac Elut 20, Varian) and conditioned with 1.0 ml methanol followed by 1.0 ml 0.013 M aq. phosphoric acid. 3.0 ml of the diluted extract was then applied to the SPE columns followed by 1.0 ml rinsing solution (methanol:0.007 M aq. phosphoric acid (70:130 v/v) to rinse off unwanted matrix compounds. The SPE discs were not allowed to dry out until after the rinsing; when they were dried under vacuum for 1 min. Up to this point all eluates were discarded. Elution of EAs was done into a test tube with 2.5 ml elution solution (methanol:0.01 M ammonium acetate adjusted to pH 10.2 with 1 M sodium hydroxide (60:40 v/v)). A flow of approximately 2 ml/min was maintained throughout the SPE clean-up. Eluted samples were evaporated to dryness in a thermostated waterbath (max. 40 °C) under a gentle stream of N 2 . Prior to HPLC analysis samples were reconstituted in 1.0 ml mobile phase A (acetonitrile:aq. 0.01 M ammonium carbamate (1:4 v/v)).

HPLC protocol

The chromatographic analysis was performed on a Hewlett Packard Series 1100 HPLC systems equipped with the corresponding HP 1100 series fluorescence detector. The column was an X-Terra MS C 18 (250 mm x 3.0 mm; 5 µm) (Waters) protected by a 3.0 x 20 mm guard column of the same material. 20.0 µl of sample was injected and separated by gradient elution employing the following gradient (time, mobile phase B):0.0 min, 0 %; 7.0 min, 0 %; 7.1min, 1 %; 10.0 min, 16 %; 14.0 min, 16 %;16.0 min, 32 %; 24.0 min, 32 %; 33.0 min,75 %; 38.0 min, 75 %; 40.0 min, 0 %; 50.0 min, 0 %. The flow was 0.7 ml min -1 for the first 7 minutes and 1.0 ml min -1 from 7-50 minutes.

Mobile phase A consisted of acetonitrile: aq. 0.01 M ammonium carbamate adjusted to pH 9.6 with 0.5 M sodium hydroxide (1:4 v/v) and mobile phase B of acetonitrile. Column temperature was maintained at 25 o C and fluorescence detection was performed with excitation at 240 nm and emission at 410 nm.

Data processing

Peaks from ergocornine, ergocristine, α-ergocryptine, ergonovine and ergotamine and their C8isomers were identified based on comparison with retention times of pure standards (Figure 2).

The rapid C8-isomerisation was unavoidable in samples and standards. Therefore quantification was done on the assumption of mass conservation and equal response factors for both C8isomers by relating the summed peak area of two C8-isomers to the known initial concentration of Statistical comparisons were performed as one-or two-way analysis of variance utilising the ANOVA or GLM procedure of the SAS system (SAS Institute 2001). Linear regressions were also performed with the GLM procedure. A significance level of 0.05 applies to all statistical calculations.

Validation

The storage stability of standards (-20 °C and 5 °C), evaporated samples (5 °C) and standards and reconstituted samples during a HPLC sequence was tested by comparing HPLC response of standards and samples repeatedly over time.

Recoveries were determined with two series of recovery experiments, each with unspiked flour samples and 4 spiking levels. Four repetitions were performed for each level in each series, resulting in 8 repetitions at each level and 40 samples in total. A batch of organic rye flour with a very low EA content was used and spiked with standard solution diluted with methanol. 100 µl of solutions containing 100, 25, 13, 6.3 or 0 µg ml -1 were added to each portion of flour to give concentrations of 400, 100, 50, 25 or 0 µg kg -1 , respectively. The standard solutions were added to the flour and mixed by shaking 5-10 min. before extraction solution was added. For calibration curves two serial dilutions of standard solutions were performed with mobile phase A on separate days.

Background levels of EAs could be detected in the flour used for spiking experiments. The concentrations were however below the LOQs for many standards, so determination of EA background concentrations was done by the method of standard addition performed on the results of the recovery experiment. The recovered amounts of ergot alkaloids from spiked samples were corrected for the background concentrations in the rye flour before calculation of recoveries.

Ergot alkaloids in rye flour

To test the method and evaluate the variability in EA content and composition, rye flour samples with known amounts of ergot sclerotia from four locations (I-IV) were produced and analysed. (w/w)) was produced for each location by grinding 1000 mg of sclerotia with 199 g ergot free grain from a fifth location on a centrifugal mill with a 0.50 mm filter. Flour samples containing 500 and 2500 mg ergot sclerotia kg -1 (0.05 and 0.25 % (w/w)) were produced by mixing the ergot containing flour with ergot free flour produced from hand sorted grain milled on the same mill. The samples were analysed for their content of the EAs identifiable by the method.

To evaluate the EA content of Danish rye flour in general 34 rye flour samples collected at mills all over Denmark between 2000 and 2005 were analysed for their content of the EAs detected by the developed method. The sampling procedure followed the official EU method for control of ochratoxin A (EU Commission 2002) e.g. sampling of 100 subsamples of approximately 100 g from lots of 50 to 300 tons followed by thorough homogenisation. Flour samples were stored at -20 o C. The determined recovery rates were used for recovery correction of the concentrations found in rye flour both naturally contaminated and samples with known amounts of sclerotia.

Results and discussion

Method development

Stepwise development of the method was performed by varying one or two factors at a time. For the extraction, different proportions of methanol to 0.013 M aqueous phosphoric acid (40:60, 50:50, 60:40 and 70:30 v/v) were tested and a 70:30 mixture was found to be the most efficient. The elution solution of 0.05 M phosphate buffer in methanol (40:60) [START_REF] Ware | Liquid chromatographic preparative method for isolating ergot alkaloids, using a particle-loaded membrane extracting disk[END_REF] was tested against 0.01 M aqueous ammonium acetate in methanol (40:60) and no significant difference was found in recoveries. 0.01 M ammonium acetate was chosen because it is volatile, so samples eluted with this buffer could be evaporated to dryness thereby prolonging the storage time.

Reconstitution was done in the mobile phase of the HPLC system minimising the risk of precipitation and immiscibility in the chromatographic system. The optimal pH of the elution solution was 10.2. Optimal conditioning and elution volumes were determined within the ranges 0.5-2.0 ml and 1.0-2.5 ml, respectively. The original rinsing solution consisting of extraction solution was discovered to remove not only matrix compounds but also 16 % of added ErTm standard (n=3). As the sample extracts were diluted with 0.013 M aq. phosphoric acid prior to the SPE clean-up the extraction solution used for rinsing actually contained more methanol than the sample solution. A 2x2 factorial experiment with phosphoric acid concentration (0.013 and 0.007 M) and methanol:phosphoric acid-ratio (70:30 and 70:130 v/v) as independent variables showed that the mixing ratio had a significant effect (P=0.003) on the ErTm concentration in the eluent.

With the rinsing solution of methanol:0.007 M phosphoric acid (70:130 v/v) the loss of ergotamine with rinsing solution was reduced to 2 % (n=3). To minimise the damaging effect of alkaline mobile phases on silica based HPLC columns a hybrid column containing both inorganic (silica) and organic (organosiloxane) components was employed for the chromatographic separation. The chosen X-Terra column was stable over time.

After more than 500 runs over a period of a year there were only minor differences in performance between the old column and a newly acquired one. The chromatographic conditions were carefully adjusted for optimal resolution. The interference of matrix peaks X with EAs was found to be highly dependent on the pH of the mobile phase. pH values of 8.8, 9.3 and 9.8 in pure mobile phase buffer gave retention times (Rt) for peak X of 17.9, 20.0, and 20.8 respectively, while Rt for e.g. ergocristine differed only 0.2 min. With a pH value of 9.6 in the ammonium carbamate buffer used for mobile phase A, X eluted between ergocristine and ergotaminine, where the risk of interference with standards was minimal (Figure 2). Equilibration of the X-terra column is slow after rinsing with unbuffered solutions of water and ACN. The problem was solved by introducing an equilibration sequence of 3-4 runs with a test sample prior to resuming analysis after the cleaning procedure.

Validation

Standard solutions stored at -20 °C for two months showed no significant reduction in response for the standard compound groups in calibration samples. Standard solution could be stored at 5 °C for 8 days without significant reduction in the response for the standard groups in calibration samples. Evaporated samples could be stored at 5 °C for 1 day without significant degradation (P>0.05, n=3).

[Insert Figure 3] Repeated analysis of a cleaned-up extract of spiked flour and a calibration sample documented the C8-isomerisation occurring during execution of a HPLC sequence (Figure 3). Isomerisation was particularly fast for ergocornine and very slow for ergonovine. No significant effect of time on compound group concentrations in the extracts was found during 66 hours at room temperature. It is thus apparent that recoveries and repeatability could only be determined for EA groups, and not for the individual C8-isomers.

The calibration curves for the method were examined in the range 6.7-530 µg kg -1 (2.5·10 -3 -0.200 µg ml -1 ) with duplicate preparations of each of the six serial standard dilutions. Linear regressions were performed and residual plots examined. The calibration curves were linear in the range 0-400 µg kg -1 . If the highest level of 530 µg kg -1 was included in the linear regression the residual plots gave evidence of a negative curvature. The intercepts of the 0-400 µg kg -1 calibration curves were Correlation coefficients were in the range 0.9990 to 0.9999. Limits of detection (LOD) and limits of quantification (LOQ) were determined for all standards and their C8-isomers as, respectively 3 and 10 times the average signal noise in 10 runs of an EA free rye flour sample made from hand-sorted rye kernels. Noise was determined as the standard deviation of a linear regression on the signal in noise intervals of approximately 1 min around the retention times of standards. The LODs were in the range 0.2 -1.1 µg kg -1 for ergocryptine and ergonovine, respectively. This is low and comparable to previous methods [START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF][START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF][START_REF] Ware | Liquid chromatographic preparative method for isolating ergot alkaloids, using a particle-loaded membrane extracting disk[END_REF].

[Insert Table I]

The recoveries determined for spiked rye flour samples were on average 61 % with a standard deviation of 10 %. The lowest recoveries are obtained for ErNo, but the difference between EA groups is small (Table I). The recoveries are low compared to recoveries of previous method of 77 % [START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF], 93 % [START_REF] Rottinghaus | An HPLC method for the detection of ergot in ground and pelleted feeds[END_REF]) and 88 % [START_REF] Ware | Liquid chromatographic preparative method for isolating ergot alkaloids, using a particle-loaded membrane extracting disk[END_REF]. In these studies the procedure for the recovery determination is not described in details, and the disparity may be due to differences in the applied spiking procedures. In the present study standards were mixed with dry flour 5-10 min prior to extraction. Experiments performed with flour extract spiked after centrifugation and filtration gave recoveries of 85-94 % (n=6). The application of standard solutions to dry flour was considered a more realistic scenario for the evaluation of extraction efficiency from a naturally EA contaminated flour sample. However, the low recoveries indicate that extraction of EAs from whole flour is the critical step.

Ergot alkaloids in rye flour.

The EA content and composition of the grain samples with added sclerotia (Table II) vary between locations. The sclerotia from one location (III) contained none of the five EAs identifiable by this method. Sclerotia from two locations contained only ErCo and ErCp while the sclerotia from another location contained all five standard EAs.

[Insert Table II]

The high variability in EA composition is consistent with the findings of a previous investigation of Canadian rye sclerotia (Young 1981a). Based on the results within the linear range of the calibration curves the average contents of ergot alkaloids in the sclerotia from the four locations were calculated to 270, 130, non detectable and 50 µg g -1 , respectively. These values exhibit a large variation between locations (coefficient of variation > 100 %) and are low compared to the [START_REF] Osborne | Analysis of ergots from winter wheat in northern Scotland[END_REF], Young (Young 1981b;Young 1981a), Young et al. [START_REF] Young | Reduction in alkaloid content of ergot sclerotia by chemical and physical treatment[END_REF][START_REF] Porter | Ergot peptide alkaloid spectra of Claviceps-infected tall fescue, wheat, and barley[END_REF] for rye and wheat, where average concentrations in tested sclerotia were between 1100 and 3600 µg g -1 .

However, the existence of virtually EA free ergot strains has also been reported [START_REF] Ruokola | Possibilities of ergot production in Finland[END_REF].

Large variations in EA content is also observed in Canadian ergot sclerotia (Young 1981b;Young 1981a). It cannot be excluded that some degradation of EAs has occurred during the storage of collected samples, but the deterioration of EAs measured by percent and activity by bioassay is reported to proceed very slowly in sclerotia stored dry at room temperature [START_REF] Barger | Ergot and ergotism[END_REF]. The EA content of 20-25 year old sclerotia has also been determined to 1460 µg g -1 (0.146 %) [START_REF] Frach | Separation of ergot alkaloids and their epimers and determination in sclerotia by capillary electrophoresis[END_REF].

Of the 34 rye flour samples from Danish mills 32 contained ergot alkaloids in concentrations above LOQ (Table III). The distribution between individual EAs was highly variable with some samples containing all five types and their epimers, while other contained only a few types, thus consistent with the variations between ergot sclerotia from different locations. The most common EAs were ErCp and ErTm. Other surveys report ErTm and ErCs to be the most common EAs in rye flour [START_REF] Scott | Analysis of ergot alkaloids in flour[END_REF]Young 1981a;[START_REF] Scott | Analysis of grain foods for ergot alkaloids by gradient liquid chromatography[END_REF][START_REF] Baumann | Mutterkornalkaloide in schweizerischen Getreideprodukten[END_REF][START_REF] Scott | Ergot Alkaloids in grain foods sold in canada[END_REF]). The overall mean content of EA was 46 µg kg -1 with a maximum content of 234 µg kg -1 , which is comparable to the findings of the latest Danish survey [START_REF] Rasmussen | Ergot in grain, an overview[END_REF]).

[Insert Table III]

With the measured EA content of 270 µg g -1 in sclerotia and a sclerotia content of 500 mg kg -1 in grain, corresponding to the maximum recommendation, the EA concentration in flour would be 135 µg kg -1 . The maximum concentration of 234 µg kg -1 observed in one sample from a Danish mill can therefore only be obtained with sclerotia of higher EA content or by sclerotia contents in grain exceeding 500 mg kg -1 . With an EA content in sclerotia of 0.25 % (2500 µg g -1 ) as determined by Young (Young 1981a) the EA concentration would be 1250 µg kg -1 . Taking into account, that ergot sclerotia have different milling properties to grain [START_REF] Shuey | Distribution of ergot in mill streams[END_REF][START_REF] Dexter | Physical properties and processing quality of durum wheat fractions recovered from a specific gravity table[END_REF][START_REF] Fajardo | Retention of ergot alkaloids in wheat during processing[END_REF], the EA concentrations in commercial flour are expected to be lower than the EA concentrations in grain before milling. About 25 % of the ergot alkaloids present in wheat before milling was retained in straight-grade flours of a pilot mill [START_REF] Fajardo | Retention of ergot alkaloids in wheat during processing[END_REF]. It is thus reasonable to assume that ergot alkaloid concentrations in Danish ergot sclerotia can be higher than the 270 µg g -1 found in the examined sclerotia. With large variations in EA content of sclerotia (Young 1981a;Young 1981b;[START_REF] Osborne | Analysis of ergots from winter wheat in northern Scotland[END_REF] a threshold limit based on percent of ergot bodies in grain is of limited relevance. Both conventionally and organically grown rye flour samples were examined. In organic rye flour samples examined by Rasmussen [START_REF] Rasmussen | Ergot in grain, an overview[END_REF] the average EA content was 205 µg kg -1 (n=2) compared to 3 µg kg -1 (n=13) for conventional rye flour. No such difference between organic and conventional rye flour was found by [START_REF] Klug | Method for the determination of ergot alkaloids in food[END_REF]) and an inverse relationship was seen by Lauber [START_REF] Lauber | Analysis of rye grains and rye meals for ergot alkaloids[END_REF]. The differences in total EA content between the 17 organic and 17 conventional rye flour samples of this investigation are not significant. Differences in EA content in rye flour are more likely to relate to the particle size of cereal products. Ergot sclerotia have different milling properties from wheat and ends up mainly in the coarsest milling fractions like bran and germ [START_REF] Shuey | Distribution of ergot in mill streams[END_REF][START_REF] Dexter | Physical properties and processing quality of durum wheat fractions recovered from a specific gravity table[END_REF][START_REF] Fajardo | Retention of ergot alkaloids in wheat during processing[END_REF]. A similar partitioning is expected for rye.

Finally, the C8-(S) isomers account for on average 54 % of the determined EAs in the 34 analysed flour samples, ranging from 0 % ergonovinine in the ErNo group to 73 % ergocryptinine in the ErCp group. It is thus apparent, that determination of the C8-(S) isomers is of vital importance for the overall assessment of EA levels in rye flour, since the distribution between isomers prior to sample processing is unknown.

Conclusion

The HPLC method reported here performed well for the detection of both C8-isomers of the most common ergot alkaloids: ergocornine, α-ergocryptine, ergocristine, ergonovine and ergotamine.

The clean-up by cation exchange SPE combined with HPLC separation under alkaline conditions retains and separates both C8-isomers without the use of hazardous organic solvents. C8isomerisation took place during the HPLC analysis which emphasizes the importance of determining both isomers, as the C8(R) to C8(S) ratio prior to extraction is unknown. The C8-(S) isomers accounted for 54 % of the total EA content of the 34 tested samples and there was no significant difference in EA content between organic and conventional rye flour. 32 samples were positive and the most common ergot alkaloids were ergotamine and α-ergocryptine including their C8-isomers. Large variations were observed in the EA content of sclerotia from different locations emphasizing the inaccuracy of the maximum recommended content of 500 mg kg -1 (0.05 % (w/w)) ergot bodies in grain for human consumption. The method provides chemical determination of both C8-isomers of the most common EAs and gives a more accurate measure of EA content in grain, than the common weight percentages or methods measuring only the C(8)-R isomers. (2), ergotamine (3), ergocornine (4), α-ergocryptine (5), ergocristine (6), ergotaminine (7), ergocorninine (8), α-ergocryptinine (9) and ergocristinine (10). X designates the matrix peak named X.

  convenience five compound groups were defined, each group comprising the two C8-isomers of a standard: ErNo = ergonovine + ergonovinine; ErTm = ergotamine + ergotaminine; ErCo = ergocornine + ergocorninine; ErCp = α-ergocryptine + α-ergocryptinine; ErCs = ergocristine + ergocristinine.

  Sclerotia and grain were collected at different farms immediately after harvest in 2003 (I, II, and ergot free grain) and approximately 1 month after harvest in 2004 (III and IV). Sclerotia and grain were stored at -20 °C until analysis. Rye flour containing 5000 mg ergot sclerotia kg -1 (0.50 %

  from 0. Therefore the calibration curves were forced through origin.

Figure 1 :

 1 Figure 1: Chemical structure and CAS no. of common ergot alkaloids.

Figure 2 :

 2 Figure 2: Chromatogrammes of I: standard solution (0.025 µg ml -1 ) and II: rye flour sample naturally contaminated with ergot alkaloids. The numbered EAs are: Ergonovine (1), ergonovinine(2), ergotamine (3), ergocornine (4), α-ergocryptine (5), ergocristine (6), ergotaminine (7), ergocorninine (8), α-ergocryptinine (9) and ergocristinine (10). X designates the matrix peak named X.

Figure 3 :

 3 Figure 3: C8-isomerisation of ergocornine to ergocorninine (I) and ergonovine to ergonovinine (II) in reconstituted sample during storage in the HPLC autosampler. The amount of each isomer is expressed as the percent of the total amount.

  Figure 3

  et al. 2005). The latest Danish survey was conducted in 1987-88

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Table I :

 I Recoveries of EAs ± standard deviations at four spiking levels (n=8). The values are corrected for background levels calculated by the method of standard addition. Repeatabilities (n=32) are standard deviations for recoveries at all concentration levels, measured in two series on two separate days.

				Location
	EA		I	II	III	IV
	ErCo		430	450	nd	17
	ErCp		390	260	2.9	30
	ErCs		nd	nd	nd	100
	ErNo		nd	nd	nd	39
	ErTm Total	EA a	4.6 830	nd 25.0 710	nd Amount added (µg kg -1 ) 56 50.0 100.0 2.9 240	400.0	(%) Mean rec.	(%) Repeatability
		ErCo		60 ± 11	62 ± 11	61 ± 15	61 ± 7.3	61	12
		ErCp		61 ± 15	61 ± 12	60 ± 15	60 ± 7.6	61	13
	ErCs ErNo ErTm a ErCo: Ergocornine+ergoconinine; ErCp: α-ergocryptine+α-ergocryptinine; ErCs: ergocristine+ergocristinine; ErNo: 62 ± 8.8 67 ± 10 65 ± 13 65 ± 6.8 65 9.9 55 ± 7.7 62 ± 7.7 57 ± 12 58 ± 6.3 58 8.8 61 ± 8.0 63 ±7.2 63 ± 10 63 ± 7.7 62 8.4 ergonovine+ergonovinine; ErTm: ergotamine+ergotaminine. F o r
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Table II :

 II Ergot alkaloid content of rye flour with ergot sclerotia from different locations added, to sclerotia contents of 5000 mg kg -1 . For compound abbreviations see TableI. A discrepancy between the sum of subtotals and the stated total is due to rounding of errors.

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Table III :

 III Number of positive samples (n positive ), average concentrations (mean, mean positive ), and maximum concentrations (max.) of 34 conventional and organic rye flour samples collected between 2000 to 2005. All concentrations are in µg kg -1 and corrected for recovery percentages. The average percentages of the alkaloids found as C8-(S) isomers (% C8-(S)) are shown in the bottom line. For compound abbreviations see tableI.

			Food Additives and Contaminants			Page 18 of 21
	Figure 1
	Conventional n positive (n=17) Mean Mean positive	ErCo 10 Ergot alkaloid 9.1 Ergonovine 15 Ergocornine	ErCp 14 CAS no. 19 60-79-7 23 564-36-3	ErCs 11 12 CH(CH 3 )CH 2 OH ErNo 3 R 1.7 19 9.4	ErTm 9 R 1 18 35 isopropyl	Total 15 60 68 isopropyl R 2
	Organic (n=17) All	Maximum n positive Mean Mean positive Maximum % C8-(S) r o α-ergocryptine 27 13 6.6 8.7 27 56 F Ergocristine	73 15 16 18 62 73 511-09-1 511-08-0	58 10 2.5 4.3 15 68	17 0 0 0 0 0	83 6 6.2 17 38 30 isopropyl isopropyl	230 15 32 36 100 54 isobutyl benzyl
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http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.ukFood Additives and Contaminants


MD, PhD Christophe ; Piketty
email: christophe.piketty@egp.aphp.fr

Laurence Weiss

Lambert Assoumou

Marianne Burgard

Aurelie Melard

Jean-Michel Ragnaud

Michele Bentata

Pierre-Marie Marie Girard

Christine Rouzioux

Dominique Costagliola

Assoumou

Marie

Aurélie Mélard

Salto

A High HIV DNA Level in PBMCs at Antiretroviral Treatment Interruption Predicts a Shorter Time to Treatment Resumption Independently of CD4 Nadir

Keywords: HIV, treatment interruption, HIV-DNA, CD4 nadir, cART HIV, treatment interruption, HIV-DNA, CD4 nadir, ART

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

and to identify baseline factors predictive of the time to reach fixed criteria for 5 treatment resumption. 6 Prospective, open-label, multicentre trial. Patients were eligible if they had a 7 CD4 cell count >350/mm 3 and plasma HIV RNA <50000 copies/ml when they 8 first started antiretroviral therapy (ART); and if they had a CD4 count >450/mm 3 9 and stable plasma HIV RNA <5000 copies/mL for at least six months prior to 10 enrolment. The criteria for ART resumption were a CD4 cell count <300/mm 3 11 and/or a CDC stage B or C event. 12 116 patients had received ART for a median of 5.3 years. The median CD4 cell 13 count and plasma HIV RNA values at inclusion were 809/mm 3 and 2.6 log 14 copies/mL, respectively. Median HIV DNA load at inclusion was 2.3 log 15 copies/10 6 PBMCs. Thirty-six months after TI, 63.9% of the patients had not yet [START_REF] Boschi | CD4+ cell-count-17 guided treatment interruptions in chronic HIV-infected patients with good 18 response to highly active antiretroviral therapy[END_REF] reached the criteria for ART resumption, and 55.9% of patients had not 17 resumed ART. In Cox multivariable analysis, a high HIV DNA level at TI, a low 18 CD4 nadir, and pre-existing AIDS status were the only significant risk factors for [START_REF] Chomont | HIV reservoir size and persistence are 22 driven by T cell survival and homeostatic proliferation[END_REF] reaching the criteria for ART resumption (hazards ratio: 2.15(1.02-4.53), 20 4.59(1.22-17.24) and 5.74(1.60-20.56), respectively). 21 Patients who started ART with a CD4 cell count above 350/mm 3 were able to 22 interrupt treatment for long periods without a high absolute risk of either AIDS or 23 severe non-AIDS morbidity/mortality. A high PBMC HIV DNA level at treatment 24 interruption was a strong predictor for more rapid treatment resumption. 25 plasma HIV RNA levels and improves patient survival [START_REF] Hogg | Improved survival among HIV-infected individuals following initiation 13 of antiretroviral therapy[END_REF]; Hogg 3 et al., 2001;[START_REF] Lee | Survival after AIDS diagnosis 22 in adolescents and adults during the treatment era, United States[END_REF][START_REF] Li | Long lasting 25 recovery in CD4 T-cell function and viral-load reduction after highly active 26 antiretroviral therapy in advanced HIV-1 disease[END_REF][START_REF] Mocroft | AIDS across Europe, 1994-98: the 45 EuroSIDA study[END_REF]Murphy et al., 4 2001;Palella et al., 1998;Palella et al., 2003]. However, efficacy can be 5 undermined by suboptimal adherence to treatment and by adverse effects. 6

Treatment interruption appears to be feasible and safe in patients with high CD4 7 cell counts, a high CD4 nadir, and long-term undetectable plasma HIV RNA, as 8 suggested by several small uncontrolled studies [START_REF] Boschi | CD4+ cell-count-17 guided treatment interruptions in chronic HIV-infected patients with good 18 response to highly active antiretroviral therapy[END_REF] [START_REF] Tarwater | Prolonged treatment interruption after 11 immunologic response to highly active antiretroviral therapy[END_REF] and by two controlled trials [START_REF] Ananworanich | CD4-7 guided scheduled treatment interruptions compared with continuous therapy for 8 patients infected with HIV-1: results of the Staccato randomised trial[END_REF]13 Maggiolo et al., 2008]. However, recent large randomized trials indicate that, 14 compared with patients who continue ART, unselected patients undergoing 15 treatment interruption experience significantly worse clinical outcomes, [START_REF] Boschi | CD4+ cell-count-17 guided treatment interruptions in chronic HIV-infected patients with good 18 response to highly active antiretroviral therapy[END_REF] including HIV disease progression and cardiovascular events [Danel et al., 17 2006;[START_REF] El-Sadr | CD4+ count-guided interruption of 32 antiretroviral treatment[END_REF]. 18

In view of the results of these latter studies, treatment interruptions are no 19 longer recommended. However, many patients are concerned with the toxicity 20 and potential long-term adverse effects of ART, and spontaneously stop taking 21 their treatment. Factors predictive of treatment resumption would therefore be 22 useful for clinicians managing such patients, but have not been studied 23 extensively. 24

Study population 13

The following patients were eligible: HIV-infected men and non pregnant women 14 at least 18 years of age; who had a CD4 cell count above 350/mm 3 and plasma 15 HIV RNA below 50 000 copies/ml (4.7 log 10 copies/ml) at ART initiation; who 16 had been on a stable ART regimen (at least two drugs) for 6 months prior to 17 inclusion; who had had no more than one treatment failure; and who, at 18 baseline, had a CD4 cell count above 450/mm 3

Study design

3

ART was interrupted at enrolment in the study and the patients were monitored 4 for up to 36 months. Patients taking a non nucleoside reverse transcriptase 5 inhibitor were advised to discontinue it 7 days before their other antiretroviral 6 drugs. 7

The patients were evaluated at the screening visit (week -4), then at day 0 (TI), 8 week 2, months 1, 2, 4 and 6, and every 3 months thereafter until month 36. 9

Absolute numbers of CD4 T lymphocytes were determined by flow cytometry in 10 whole blood. The plasma HIV RNA level was determined with the techniques 11 routinely used in each participating center, all of which had a detection limit of 12 400 genome copies/mL. Each patient's samples were all tested with the same 13 technique. The plasma HIV RNA level and the CD4 cell count were determined 14 at each study visit. 15

The HIV DNA level in peripheral blood mononuclear cells (PBMCs) was 16 measured in blood samples taken at day 0 and at months 6, 12 and 18. PBMC 17 HIV-1 DNA was quantified by real-time PCR with amplification of the LTR gene, 18 using the 8E5 cell line as an external standard [START_REF] Avettand-Fenoel | Failure of bone marrow transplantation 12 to eradicate HIV reservoir despite efficient HAART[END_REF]19 Goujard et al., 2006;[START_REF] Rouzioux | Early levels of HIV-1 DNA in peripheral blood 40 mononuclear cells are predictive of disease progression independently of HIV-1 41 RNA levels and CD4+ T cell counts[END_REF]. Briefly, PBMCs were separated by 20 Ficoll-Hypaque gradient centrifugation and aliquots were frozen until use. Total 21 DNA extracted from each aliquot of PBMCs was first quantified with the 22 Hoechst dye method (Pharmacia), 1 µg of DNA being considered equivalent to 23 ~150 000 cells. This HIV-DNA PCR method quantifies total HIV-DNA (both 24 integrated and non integrated). Final results were expressed as the number or 25 log 10 number of HIV-1 DNA copies per 10 6 PBMCs (quantification limit: 5 1 copies/PCR, i.e. 30 copies/10 6 PBMCs). 2

Frozen plasma samples were collected at months 1, 6, 12, 18 and 24. HIV 3 genotypic resistance mutations were studied before treatment resumption, as 4 described elsewhere [START_REF] Mouroux | Low-rate emergence of thymidine analogue 49 mutations and multi-drug resistance mutations in the HIV-1 reverse 50 transcriptase gene in therapy-naive patients receiving stavudine plus 51 lamivudine combination therapy[END_REF]. 5

Safety was assessed at each visit by means of an interview, a physical 6 examination, and collection of adverse events. Adverse events were coded with 7 the Medical Dictionary for Regulatory Activities (MedDRA) and their severity 8 was graded from 1 to 4 with the ANRS Adverse Event Grading Scale. 9

Lipodystrophy was scored clinically, and anthropometric measurements were 10 made (waist and hip circumference, waist/hip ratio, thigh circumference and 11 body mass index) on day 0 and at months 6, 24 and 36. 12 Total cholesterol, HDL cholesterol, LDL cholesterol and triglyceride serum 13 levels were measured after an overnight fast on day 0 and every 6 months 14 thereafter. 15

The criteria for ART resumption were a fall in the CD4 cell count to below 16 300/mm 3 The results are reported as proportions (and 95% confidence intervals when 3 appropriate) for categorical variables, and as medians and interquartile ranges 4 for continuous variables. Changes in the CD4 cell count during treatment 5 interruption were analyzed by using mixed linear models, testing for changes in 6 the slopes during the interruption, with cut points chosen after visual inspection 7 of the median CD4 cell count at each time point. In these analyses, patients 8 resuming ART were censored at the time of treatment resumption. The primary 9 endpoint was the time to the first of two consecutive CD4 cell counts below 10 300/mm 3 , 15 days apart, or a CDC stage B or C AIDS-defining event. All events 11 were reviewed by the Data and Safety Monitoring Board. Patients who reached 12 the primary endpoint were analyzed as such even if they did not resume 13 treatment, while patients who resumed treatment without reaching the primary 14 endpoint were censored at time of treatment resumption in the intent-to-treat 15 analysis. In the analysis of observational data, all patients resuming therapy 16 were considered to have reached the primary endpoint. The percentage of 17 patients reaching the primary endpoint was determined using Kaplan-Meier 18 estimates. Factors associated with the occurrence of the primary endpoint were 19 analyzed with univariate and multivariable Cox proportional hazards models. 20

The following variables were tested: baseline age, gender, transmission group, 21 AIDS status, the CD4 cell nadir, the pre-ART CD4 cell count, the baseline CD4 22 cell count, pre-ART plasma HIV-1 RNA, baseline PMBC HIV DNA, the duration 23 of ART at treatment interruption, and the use of dual-or triple-drug therapy. [START_REF] Li | Long lasting 25 recovery in CD4 T-cell function and viral-load reduction after highly active 26 antiretroviral therapy in advanced HIV-1 disease[END_REF] Akaike's criteria were used to determine whether continuous variables were 25 1. Follow-up during treatment interruption lasted 6 a total of 270.2 person-years. Three patients had had AIDS-defining events 7 prior to enrolment (pulmonary tuberculosis, esophageal candidiasis, cutaneous 8 Kaposi's sarcoma). The interrupted treatments comprised a protease inhibitor-9 based regimen in 16% of cases, a non-nucleoside analogue regimen in 35% of 10 cases, a triple nucleoside analogue regimen in 34% of cases (Trizivir in 17% of 11 cases), a dual nucleoside analogue regimen in 14% of cases, and a non 12 nucleoside analogue plus a protease inhibitor in 1% of cases. The median (IQR) 13

CD4 cell count at inclusion was 806/mm 3 (676 -940) and the median CD4 14 nadir was 381/mm 3 (341 -490). Only 11% of the patients had a CD4 nadir 15 below 300/mm 3 . The median pre-ART plasma HIV RNA level was 4.2 log 10 16 copies/mL (3.8 -4.5). Ninety-one percent of the patients had a plasma HIV 17 RNA level below 400 copies at inclusion. The median baseline HIV DNA value 18 was 2.3 log copies per million PBMCs (1.9 -2.8). Figure 1b. After a rapid increase from 2.6 to 4.0 log 10 copies per ml during the 12 first month, the median plasma HIV RNA level stabilized. Median plasma HIV 13 RNA values at months 12, 24 and 36 were respectively 4.1 log 10 copies/mL (3.6 14 -4.4), 4.1 log 10 copies/mL (3.7 -4.5) and 4.3 log 10 copies/mL (3.7 -4.6). 15

Respectively 5%, 6% and 2% of patients still had plasma HIV RNA values 16 below 400 copies/mL at months 12, 24 and 36 of treatment interruption. Median 17 PBMC HIV DNA load in these patients at baseline and month 6 were 18 respectively 1.0 (1.0 -1.4) and 2.2 (1.8 -2.4) log 10 per million PBMCs. [START_REF] Chomont | HIV reservoir size and persistence are 22 driven by T cell survival and homeostatic proliferation[END_REF] Changes in HIV DNA load during the first 18 months of the study are shown in 20 Figure 1c. The HIV DNA level increased from 2.3 (1.9 -2. Another nine patients (12.4%) resumed therapy because of CDC stage B or C 3 events, and 20 patients (20.0%) resumed therapy for other reasons (mainly at 4 the patient's request). 5

The nine CDC stage B/C events consisted of severe thrombocytopenia (2 6 cases), oral hairy leukoplakia (3 patients), oral candidiasis (2 patients) and 7 cutaneous Kaposi's sarcoma (2 patients). One of the two patients who 8 developed cutaneous Kaposi's sarcoma during treatment interruption had 9 already had a first episode prior to enrolment in the study. The CD4 cell counts 10 of these two patients at the onset of Kaposi's sarcoma during treatment 11 interruption were 648/mm 3 and 364/mm 3 . No AIDS-defining events occurred 12 during the first 12 months of treatment interruption. 13 In the intent-to-treat analysis the proportions of patients who did not meet the 14 criteria for ART resumption at months 12, 24 and 36 were respectively 97.3% 15 (95% CI: 92.5 -99.1), 86.5% (78. [START_REF] Strain | Heterogeneous clearance rates of 8 long-lived lymphocytes infected with HIV: intrinsic stability predicts lifelong 9 persistence[END_REF] Of the 47 patients who resumed therapy during the 36 months of follow-up, 31 11 patients (66%) were prescribed a regimen different from that received prior to 12 enrolment. The median CD4 cell count was 345/mm 3 (256 -446) at resumption, 13 and 475/mm 3 (388 -587) six months later. The median plasma HIV RNA level 14 was 26470 copies/mL (4790 -81430) at resumption, and 39 patients (81%) had 15 plasma HIV RNA levels below 400 copies/mL six months later. Genotypic 16 mutations conferring resistance to NRTIs and NNRTIs were identified in all 8 17 patients (19%) who had plasma HIV RNA levels above 400 copies/mL six 18 months after resumption. The baseline profile was not available in three of 19 these patients. Only one of the remaining five patients acquired resistance to a 20 new drug (3TC). At treatment interruption, 6 of these 8 patients had plasma HIV 21 RNA values below 400 copies/mL. The ART regimens were subsequently 22 optimized, and plasma HIV RNA became undetectable (<400 copies/mL) after a 23 further 6 months in 7 of the 8 patients. [START_REF] Li | Long lasting 25 recovery in CD4 T-cell function and viral-load reduction after highly active 26 antiretroviral therapy in advanced HIV-1 disease[END_REF] No B or C events were diagnosed after treatment resumption. 25 This study indicates that treatment interruption in selected patients with a high 2 CD4 cell nadir is associated with a low rate of HIV disease progression after 36 3 months. Only 36% of the patients met the criteria for treatment resumption 4 during the 36 months of follow-up, namely a CD4 cell count below 300/mm 3 or a 5 CDC stage B or C event. Only two CDC grade C clinical events (two cases of 6 cutaneous Kaposi's sarcoma) occurred during the 36 months of follow-up. It 7 should be noted that patients with AIDS were eligible for this study. One of the 8 two patients who developed Kaposi's sarcoma during follow-up, when their CD4 9 cell counts were above 350/mm3, had already had an episode of Kaposi's 10 sarcoma prior to inclusion. Both these events occurred after one year off 11 treatment, and the incidence was 0.7/100 P-Y. This is within the range of 12 incidence rates observed elsewhere in antiretroviral-naive patients with CD4 cell 13 counts >350/mm 3 with AIDS or HIV-related disorders, and included patients with different degrees 7 of immune impairment and low CD4 cell nadirs. One study in which there was a 8 high rate of events (mainly bacterial infections) during treatment interruption 9 involved patients in Africa, where the background rate of opportunistic infections 10 may be higher [START_REF] Danel | CD4-guided structured antiretroviral treatment 26 interruption strategy in HIV-infected adults in west Africa (Trivacan ANRS 1269 27 trial): a randomised trial[END_REF]. 11

Among the patients enrolled in the SMART trial, opportunistic infections and 12 deaths were significantly more frequent in the "drug conservation" arm, in which 13 ART initiation or resumption was deferred until the CD4 cell count fell to 14 250/mm 3 ), than in the continuous ART arm. Even in the subgroup of patients 15 whose last CD4 cell count was above 350/mm 3 , the incidence of AIDS-related 16 events in the "drug conservation" arm was 1.28 per 100 person-years [Lundgren 17 et al., 2008], a rate similar to that found in the present study (0.7/100 P-Y;IQR 18 0.2 -2.0). However, clinical events were infrequent in our study, in which the 19 patients had started first-line antiretroviral therapy with CD4 cell counts above 20 350/mm 3 . This further suggests that lengthy treatment interruption is less risky 21 in AIDS-free patients with a high CD4 cell nadir. 22

The SMART study highlighted an increased risk of cardiovascular events during 23 treatment interruption [START_REF] El-Sadr | CD4+ count-guided interruption of 32 antiretroviral treatment[END_REF]. A slight increase in cardiovascular 24 events was observed in the "drug conservation" arm of the SMART study, with 25 As also observed elsewhere [START_REF] Hatano | Metabolic and anthropometric consequences of interruption of highly 10 active antiretroviral therapy[END_REF], a significant improvement of 6 lipodystrophy and lipid abnormalities was observed during treatment 7 interruption. However, changes in lipodystrophy were assessed with an 8 unvalidated clinical score, and no significant change in anthropometric values 9 was observed during treatment interruption. 10

As reported previously by others, this study showed a rapid initial CD4 cell 11 decline after ART interruption, followed by a more gradual loss during the first 12 months (accompanied by a rapid increase in plasma HIV RNA), and then by 13 CD4 cell count and plasma HIV RNA load stabilization [START_REF] Boschi | CD4+ cell-count-17 guided treatment interruptions in chronic HIV-infected patients with good 18 response to highly active antiretroviral therapy[END_REF]; 14 As 1 also found in some other studies, the pre-ART plasma HIV RNA level was not 2 predictive of the duration of treatment interruption in this study [Maggiolo et al., 3 2004;[START_REF] Tebas | Effect 14 of prolonged discontinuation of successful antiretroviral therapy on CD4+ T cell 15 decline in human immunodeficiency virus-infected patients: implications for 16 intermittent therapeutic strategies[END_REF]. Interestingly, the PBMC HIV DNA levels above 2.56 4 log 10 copies/10 6 PBMCs were an independent predictor of a shorter time to 5 treatment resumption. PBMC HIV DNA load was also found to be a significant 6 predictor of treatment resumption in a pilot study involving 62 patients who 7 stopped their ongoing antiretroviral treatment [START_REF] Sarmati | 47 Prognostic factors of long-term CD4+count-guided interruption of antiretroviral 48 treatment[END_REF]. The HIV-8

DNA level provides an estimate of the proportion of circulating HIV-infected 9 cells and reflects the size of the viral reservoir. Central and transitional memory 10 21 [START_REF] Hammer | Antiretroviral treatment of adult HIV infection: 6 2008 recommendations of the International AIDS Society-USA panel[END_REF][START_REF] Yeni | Prise en charge médicale des personnes infectées par le VIH. 30 Recommandations du groupe d'experts[END_REF]. In current practice, the number of patients 1 who stop taking ART, for whatever reason, has fallen since the results of the 2 SMART trial were first reported in January 2006, but still represented 5.7% of 3 patients monitored in 2007 [START_REF] Yeni | Prise en charge médicale des personnes infectées par le VIH. 30 Recommandations du groupe d'experts[END_REF]. Thus, it remains important to estimate 4 the risk of AIDS and severe non-AIDS morbidity/mortality during treatment 5 interruption, and to identify factors associated with the duration of interruption. 6

The results of this study indicate that patients with a history of AIDS-defining 7 events should not interrupt their treatment. In addition to a low CD4 nadir, a 8 high PBMC HIV DNA level at time of treatment interruption is a strong predictor 9 of more rapid treatment resumption, contrary to the pre-therapy plasma HIV-1 10 RNA level. 11

  therapy (ART) increases CD4 cell numbers, reduces 2

3 The

 3 this study was to evaluate the safety of treatment interruption in 1 chronically HIV-infected patients who started ART based on earlier guidelines 2 and who had a high CD4 nadir. Factors potentially predictive of the length of 3 treatment interruption, and changes in metabolic parameters were also ANRS 116 SALTO trial was a prospective, open-label, multicenter trial of 4 treatment interruption in patients who had started treatment early in the course 5 of HIV infection, based on contemporary guidelines, and who wished to 6 discontinue ART. The study protocol was approved by the ethics committee of 7 Pitié Salpétrière Hospital, Paris, France, and all the patients gave their written 8 informed consent before entering the study. The study conformed to the 9 International Conference on Harmonization guidelines for Good Clinical 10 Practices, and with the Helsinki Declaration. 11 12

  continuous variables, or after log transformation, or as three-1 class categorical variables based on the terciles. Based on the results of these 2 analyses, the baseline CD4 cell count and the baseline HIV DNA level, 3 expressed in log 10 values, were modelled as three-class variables, and the CD4 4 cell nadir and the pre-ART CD4 cell count expressed in log 2 were modelled as 5 continuous variables in the final model. Variables with p values below 0.05 in 6 univariate analysis were entered in the Cox multivariable model by using a 7 backward procedure. 8 Changes in lipodystrophy and metabolic parameters were tested for 9 significance with Wilcoxon's paired test. The SPSS software package version 10 15.0 for Windows (SPSS Inc., Illinois, Chicago) and the SAS software package 11 version 9.1 (SAS institute, Cary, NC, USA) were used for all analyses. sixteen patients (37% women) were enrolled at 21 sites 4 between January 2003 and March 2004. Baseline characteristics of the study 5 population are shown in Table

21 Four 13 1

 2113 Figure 1a. The CD4 cell curve comprised three distinct slopes: a first steep 5

23 Incidence of the primary endpoint 24 F

 2324 Figure 1c. The HIV DNA level increased from 2.3 (1.9 -2.8) at baseline to 3.1 21

11 Severe non AIDS-defining morbidity 12 Four

 1112 count, and AIDS status at baseline were significantly associated with the 1 time taken to reach the primary endpoint. 2In multivariable analyses, HIV DNA load above the upper tercile of 2.56 3 log 10 /10 6 PBMCs (hazards ratio, HR=2.15), a low CD4 nadir (HR=4.59 per 50% 4 reduction in the CD4 nadir) and pre-existing AIDS status (HR=5.74) were all 5 predictive of a shorter time to the first of two CD4 cell counts below 300/mm3 , 6 15 days apart, or to a CDC stage B or C event. The Kaplan-Meier curves 7 representing the time to the primary endpoint are shown in Figure 2 according 8 to HIV DNA load (above or below 2.56 log 10 per million PBMCs) adjusted for the 9 CD4 nadir. 10 cardiovascular events occurred during follow-up, including two cases of 13 coronary artery disease (CD4 cell counts at diagnosis: 337 and 448), one stroke 14 (CD4=346), and one ruptured cerebral aneurysm (CD4=559); the incidence of 15 cardiovascular events was 1.5/100 person-years (95% CI: 0.6 -3.2). 16 No cases of renal or hepatic failure and no non AIDS-related malignancies 17 occurred during follow-up. 18 19 Changes in lipodystrophy and metabolic parameters 20 Changes in anthropometric measurements, lipodystrophy scores and metabolic 21 parameters between day 0 and the last follow-up visit during treatment 22 interruption are shown in Table3. No significant change in anthropometric 23 values occurred, but the proportion of patients with either lipoatrophy or 24 fell significantly (42% versus 23%, p< 0.001; and 43% versus 1 16%, p< 0.001, respectively). 2The median changes in the total serum cholesterol level, the serum HDL 3 cholesterol level, and the serum LDL cholesterol level from baseline to the last 4 follow-up visit off treatment were respectively -0.35 mmol/l (IQR -0.99, 0.08) (p 5 < 0.001), -0.11 mmol/l (-0.33, 0.05) (p < 0.001) and -0.25 mmol/l (-0.78, 0.26) (p 6 = 0.001). Serum glucose and triglycerides levels did not change significantly

3 . 5 [

 35 included in the treatment interruption arm of the Staccato trial[Ananworanich et 20 al., 2006], only minor HIV-related signs and symptoms were observed, with no 21 AIDS-defining events or AIDS-related deaths. In a recent trial[Maggiolo et al., 22 2008], 329 patients with a CD4 cell nadir above 200/mm 3 and a CD4 cell count 23 above 700/mm 3 at inclusion were randomized to continue their ongoing 24 antiretroviral treatment or to discontinue it until their CD4 cell count fell to 25 During 689 P-Y of follow-up, only one AIDS-defining event occurred 1 in the STI arm and none in the control arm, while eight cases of pneumonia 2 occurred in the STI arm, compared to one in the control arm. However, recent 3 large studies have shown a higher rate of clinical events in patients undergoing 4 CD4-guided treatment interruption than in patients who continue on treatment[START_REF] Danel | CD4-guided structured antiretroviral treatment 26 interruption strategy in HIV-infected adults in west Africa (Trivacan ANRS 1269 27 trial): a randomised trial[END_REF][START_REF] El-Sadr | CD4+ count-guided interruption of 32 antiretroviral treatment[END_REF]]. These studies did not exclude patients 6

  1.3/100 P-Y, compared to 1.5/100 P-Y in this study. As HIV 1 replication induces immune activation, plasma HIV RNA rebound during 2 treatment interruption might lead to inflammation and endothelial dysfunction, 3 thereby increasing the risk of cardiovascular events [Blum et al., 2005; Solages 4 et al., 2006; Tebas et al., 2008]. 5

Fagard

  et al., 2005; Maggiolo et al., 2004; Skiest et al., 2007; Tarwater et al., 15 2003; Tebas et al., 2002; Thiebaut et al., 2005; Wit et al., 2005]. The present 16 study showed an increase in HIV DNA levels after treatment interruption, 17 indicative of gradual replenishment of cellular reservoirs. 18 In Cox proportional hazards multivariable analyses, baseline factors predictive 19 of outcome 36 months after treatment interruption were PBMC HIV DNA load 20 above the upper tercile (2.56 log 10 copies/ml), the CD4 nadir, and AIDS status. 21It is commonly reported that the higher the CD4 cell nadir, the smaller the fall in 22 the CD4 cell count and the longer the duration of treatment interruption[Boschi 23 et al., 2004;[START_REF] Guerrero | Long-43 term follow-up of asymptomatic HIV-infected patients who discontinued 44 antiretroviral therapy[END_REF][START_REF] Giuntini | 46 Prolonged treatment interruption in chronic HIV infection: a new strategy[END_REF] al., 2005; Maggiolo et 24 al., 2004; Mata et al., 2005; Mussini et al., 2005; Poulton et al., 2003; Skiest et 25 2004; Skiest et al., 2007; Tarwater et al., 2003; Thiebaut et al., 2005].

  CD4+ T cells contribute to the HIV reservoir, the size of which correlates with 11 the nadir CD4 cell count[START_REF] Chomont | HIV reservoir size and persistence are 22 driven by T cell survival and homeostatic proliferation[END_REF]. PBMC HIV-1 DNA load shortly 12 after infection is predictive of disease progression, independently of the plasma 13 HIV-RNA level and the CD4 cell count[START_REF] Goujard | CD4 cell count and HIV 50 DNA level are independent predictors of disease progression after primary HIV 51 type 1 infection in untreated patients[END_REF] Rouzioux et al., 14 2005]. The HIV reservoir is established soon after infection, and the degree to 15 which it is diminished by ART, whether initiated during the acute or chronic 16 phase of infection, is variable [Ngo-Giang-Huong et al., 2001;Strain et al., 17 2003]. While all patients in this study had low or undetectable plasma HIV-RNA 18 at inclusion, their HIV-DNA levels varied over a broad range and were therefore 19 informative. These results suggest that the larger the viral reservoir at the time 20 of treatment interruption, the less time the patient can remain off treatment. In 21 other words, a high level of HIV-DNA was indicative of a risk of progression in 22 case of treatment interruption, whatever the prior duration of ART. 23Following the results of the SMART trial, treatment interruptions are not 24 currently recommended in HIV-infected patient management guidelines 25

  Bobigny (M. Bentata); Hôpital Saint Antoine, Paris (P-M 6 Girard, J-L Meynard ); Hôpital Pitié Salpétrière, Paris (C. Katlama, R. Tubiana, 7 A. Simon); Hôpital Bicêtre (J-F Delfraissy, C. Gougard); Hôpital Henri Mondor, 8 Creteil (Y. Levy); Hôpital Tenon, Paris (G. Pialoux); Hôpital Necker, Paris (J-P 9 Viard); Hôpital Saint Jacques, Besançon (B. Hoen); Hôpital Bichat, Paris (P. 10 Yeni, R. Landman); Hôpital Sainte Marguerite, Marseille (JA. Gastaut, I. Poizot-11 Martin); Hôpital Pellegrin, Bordeaux (JM Ragnaut); Hôpital Saint Jacques, 12 Bordeaux (P. Morlat); Hôpital Brabois, Nancy (T. May); CHU de Caen (C. 13 Bazin); CHU Strasbourg (JM. Lang); Hôpital Purpan, Toulouse (P. Massip); 14 Hôpital de l'Archet, Nice (JP. Cassuto); Hôpital Edouard Herriot, Lyon; Hôpital 15 Bretonneau, Tours (P. Choutet). 16 ANRS 116 SALTO Scientific committee: 17 C. Piketty, L. Weiss, D. Costagliola, C. Rouzioux, M. Burgard, C. Goujard, J-P 18 Viard, Y. Levy, G. Pialoux, J-L Meynard, S. Bachir Cherif, L. Assoumou, morbidity in patients with advanced HIV disease. Ann 1 Intern Med 135(1):17-26. 2 Mussini C, Bedini A, Borghi V, Guaraldi G, Esposito R, Barchi E, Enilia R, Cozzi-Lepri 3 A, Philips AN, Ortolani P, Bratt G, Eriksson LE, Sighinolfi L, Cossarizza A, 4 d'Arminio Monforte A, De Luca A, Di Giambenedetto S, Antinori A. 2005. CD4 5 cell-monitored treatment interruption in patients with a CD4 cell count > 500 x 6 106 cells/l. Aids 19(3):287-294. 7 Ngo-Giang-Huong N, Deveau C, Da Silva I, Pellegrin I, Venet A, Harzic M, Sinet M, 8 Delfraissy JF, Meyer L, Goujard C, Rouzioux C. 2001. Proviral HIV-1 DNA in 9 subjects followed since primary HIV-1 infection who suppress plasma viral load 10 after one year of highly active antiretroviral therapy. Aids 15(6):665-673. 11 Palella FJ, Jr., Delaney KM, Moorman AC, Loveless MO, Fuhrer J, Satten GA, 12 Aschman DJ, Holmberg SD. 1998. Declining morbidity and mortality among 13 patients with advanced human immunodeficiency virus infection. New England 14 Journal of Medicine 338(13):853-860. 15 Palella FJ, Jr., Deloria-Knoll M, Chmiel JS, Moorman AC, Wood KC, Greenberg AE, 16 Holmberg SD. 2003. Survival benefit of initiating antiretroviral therapy in HIV-17 infected persons in different CD4+ cell strata. Ann Intern Med 138(8):620-626. 18 Parish MA, Tarwater P, Lu M, Raines C, Gallant JE. Prolonged treatment interruption 19 after immunologic response to HAART; 2002; Barcelona, Spain. p abstract 20 ThOrB1439. 21 Pellegrin I, Thiebaut R, Blanco P, Viallard JF, Schrive MH, Merel P, Chene G, Fleury H, 22 Moreau JF, Pellegrin JL. 2005. Can highly active antiretroviral therapy be 23 interrupted in patients with sustained moderate HIV RNA and > 400 CD4+ 24 cells/microl? Impact on immunovirological parameters. J Med Virol 77(2Gazzard B, Gilson R, Easterbrook P, Johnson M, Walsh J, Leen C, Fisher

Figure 1 : 33 Figure 2 :

 1332 Figure 1: Changes in the CD4 cell count (a) and plasma HIV-RNA (b) during treatment interruption and in PBMC HIV DNA during the first 18 months of treatment interruption (c) Data points represent median values and whiskers represent interquartile ranges in (a) and (b). The dotted curve in (a) represents predicted changes in the CD4 cell count predicted by mixed linear models. The box plots in (c) represent median and interquartile ranges and whiskers indicate minimum and maximum values.

  ; Fagard et 9 al., 2003; Fernandez Guerrero et al., 2005; Giuntini et al., 2005; Krolewiecki et 10 al., 2006; Maggiolo et al., 2004; Parish et al., 2002; Pellegrin et al., 2005; 11 Pogany et al., 2007; Ruiz et al., 2000; Skiest et al., 2004; Skiest et al., 2007; 12

in two consecutive samples collected 15 days apart, and/or the 17

	1
	2	Statistical Analysis
		F o r
		P
		e
		e r
		R
		e
	18 19	occurrence of a stage B or C AIDS-defining event. Immunologic and virologic v i e responses were assessed 1, 3 and 6 months after ART resumption. w
	20
	21	Statistical analysis
	22	Sample size
	23	To estimate the percentage of patients who did not reach the ART resumption
	24	criteria 12 months after antiretroviral treatment interruption, with a precision of
	25	10%, 100 patients needed to be enrolled.
		10

Factors predictive of reaching the primary endpoint

	16	-91.8), and 63.9% (52.9 -73.6). The
	17	proportions of patient who had not resumed ART at months 12, 24 and 36
	18	(observational data) were respectively 92.2% (85.8 -95.8), 75.3% (66.5 -
	19	82.4), and 55.9% (46.1 -65.3).
	20
	21
	22	The results of univariate and multivariable Cox proportional hazards models are
		shown in

Table 2 .

 2 In univariate analyses, HIV DNA load above 2.56 log 10 per 23 million PBMCs, a low CD4 nadir, the pre-ART CD4 cell count, the baseline CD4 24

Table 2 : Risk factors of reaching the criteria for treatment resumption in univariate analysis and multivariable Cox proportional hazards models

 2 Hazard Ratio per two-fold decrease in the CD4 cell count; # Hazard Ratio per ten-fold increase in plasma HIV-RNA; N=number of patients; n=number of events during follow-up; AIC=Akaike's information criterion: used to select models (the best model has the lowest AIC).

	Univariate analysis	Multivariable analysis

is associated with a low rate of clinical progression: a prospective study by

John Wiley & SonsJournal of Medical Virology

Acknowledgments