Metabolic pathway analysis has been recognized as a central approach to the structural analysis of metabolic networks. The concept of elementary (flux) modes provides a rigorous formalism to describe and assess pathways and has proven to be valuable for many applications. However, computing elementary modes is a hard computational task. In recent years we assisted in a multiplication of algorithms dedicated to it. We require a summarizing point of view and a continued improvement of the current methods.We show that computing the set of elementary modes is equivalent to computing the set of extreme rays of a convex cone. This standard mathematical representation provides a unified framework that encompasses the most prominent algorithmic methods that compute elementary modes and allows a clear comparison between them. Taking lessons from this benchmark, we here introduce a new method, the binary approach, which computes the elementary modes as binary patterns of participating reactions from which the respective stoichiometric coefficients can be computed in a post-processing step. We implemented the binary approach in FluxAnalyzer 5.1, a software that is free for academics. The binary approach decreases the memory demand up to 96% without loss of speed giving the most efficient method available for computing elementary modes to date.The equivalence between elementary modes and extreme ray computations offers opportunities for employing tools from polyhedral computation for metabolic pathway analysis. The new binary approach introduced herein was derived from this general theoretical framework and facilitates the computation of elementary modes in considerably larger networks. The background section presents the importance of computing elementary modes for metabolic system analysis, its computational difficulties and the existence of various known algorithms. A theoretical section brings these algorithms into a unified framework. In a following section we introduce a new approach, called the binary approach. Although relying on concepts introduced in the theoretical section, this section gives enough practical details to be stand-alone for the implementer. Results obtained from example networks and a conclusion section close the article.m metabolites and q reactions. Reactions may involve further metabolites that are not considered as proper members of the system of study. The latter metabolites, considered to be buffered, are called external metabolites in opposition to the m metabolites within the boundary of the system, called internal metabolites. The stoichiometry matrix N is an m × q matrix whose element nij is the signed stoichiometric coefficient of metabolite i in reaction j with the following sign convention: negative for educts, positive for products. Some reactions, called irreversible reactions, are thermodynamically feasible in only one direction under the normal conditions of the system. Therefore, reaction indices are split into two sets: Irrev (the set of irreversible reaction indices) and Rev (the set of reversible reaction indices). A flux vector (flux distribution), denoted v, is a q-vector of the reaction space q, in which each element vi describes the net rate of the ith reaction. Sometimes we are interested only in the relative proportions of fluxes in a flux vector. In this sense, two flux vectors v and v' can be seen to be equivalent, denoted by v ≃ v', if and only if there is some α > 0 such that v = α · v'.We consider a metabolic network with Nv = 0. Thermodynamics impose the rate of each irreversible reaction to be nonnegative. Consequently the set of feasible flux vectors is restricted toMetabolism involves fast reactions and high turnover of substances compared to events of gene regulation. Therefore, it is often assumed that metabolite concentrations and reaction rates are equilibrated, thus constant, in the timescale of study. The metabolic system is then considered to be in quasi steady state. This assumption implies P = {v ∈ q : Nv = 0 and vi ≥ 0, i ∈ Irrev}     (1)P is a set of q-vectors that obey a finite set of homogeneous linear equalities and inequalities, namely the |Irrev| inequalities defined by vi ≥ 0, i ∈ Irrev and the m equalities defined by Nv = 0. P is therefore – by definition – a convex polyhedral cone [ral cone .P of feasible states by providing a (finite) set of vectors that allow the generation of any vectors of P and are of fundamental importance for the overall capabilities of the metabolic system. One of this set is the so-called set of elementary (flux) modes (EMs). For a given flux vector v, we note R(v) = {i : vi ≠ 0} the set of indices of the reactions participating in v. Hence, R(v) can be seen as the underlying pathway of v. By definition, a flux vector e is an elementary mode (EM) if and only if it fulfills the following three conditions [Metabolic pathway analysis -5 servesnditions ,7:e is an EM if and only if it works at quasi steady state, is thermodynamically feasible and there is no other non-null flux vector  that both satisfies these constraints and involves a proper subset of its participating reactions. Note that with this convention, reversible modes are here considered as two vectors of opposite directions.In other words, The concept of elementary modes (and, with some restrictions, the very similar concept of extreme pathways -10) has Identification of pathways: The set of EMs comprises all admissible routes through the network and thus of "pathways" in the classical sense, i.e. of routes that convert some educts into some products [(1) products .Network flexibility: The number of EMs is at least a rough measure of the network's flexibility  to perform a certain function [(2) function -13.Identification of all pathways with optimal yield: Consider the linear optimization problem, where all flux vectors with optimal product yield are to be identified, i.e. where the moles of products generated per mole of educts is maximal. Then, one or several of the EMs reach this optimum and any optimal flux vector is a convex combination of these optimal EMs [3)  Identifiimal EMs .Importance of reactions: The importance or relevance of a reaction can be assessed by its participation frequency or/and flux values in the EMs.(4) Inference of viability of mutants: If a reaction is involved in all growth-related EMs its deletion can be predicted to be lethal, since all EMs would disappear [(4a) isappear .(4b) A more quantitative measure of the importance of a reaction has been given by "control-effective fluxes" (CEFs, ). The CEReaction correlations: EMs can be used to analyze structural couplings between reactions, which might give hints for underlying regulatory circuits [(5) circuits ,16,17. Acircuits ).Detection of thermodynamically infeasible cycles: EMs representing internal cycles  are infeasible by laws of thermodynamics and thus reflect structural inconsistencies [(6) stencies ,19.regulatory rules [(7) The framework of pathway analysis also allows us to combine and to study stoichiometric constraints together with ry rules .Minimal cut sets: EMs allow for a computation of minimal cut sets that represent minimal cuts (deletion sets) in the network repressing certain metabolic functions [(8) unctions .α-spectrum has been introduced to quantify the involvement of extreme pathways in a particular flux distribution (e.g. from an experiment) [α-spectrum specifies a range of possible weights for each extreme pathway. The same could be defined for EMs.(9) The eriment) . Since tDue to the combinatorial explosion in the number of EMs in large networks , computiHere we show that both the Schuster algorithm as well as that by Wagner can be embedded in a more general algorithmic framework stemming originally from computational geometry. These studies do not only give a summarizing point of view, they also lead to a crucial modification of the existing algorithms, decreasing the required memory for computing and storing EMs drastically.In the particular case of a metabolic system with only irreversible reactions, the set of admissible reactions reads:P = {v ∈ q : Nv = 0 and v ≥ 0}     (3)P is in this case a particular, namely a pointed polyhedral cone  to have this 'pointed' effect in 0: P contains no real line (otherwise there coexist x and -x not null in P, a contradiction with the constraint v ≥ 0). The figure even suggests that a pointed polyhedral cone can be either defined in an implicit way, by the set of constraints as we did until now, or in an explicit or generative way, by its 'edges', the so-called extreme rays (or generating vectors) that unambiguously define its boundaries. In the following, we show that elementary modes always correspond to extreme rays of a particular pointed cone as defined in (3) and that their computation therefore matches to the so-called extreme ray enumeration problem, i.e. the problem of enumerating all extreme rays of a pointed polyhedral cone defined by its constraints. An overview on general and current issues on extreme ray enumeration can be found in [Compared with 1)  P is in found in . For theThe pointed polyhedral cone is the central mathematical object throughout this work; therefore we shall introduce more precise definitions and results surrounding it.P is a pointed polyhedral cone of d if and only if P is defined by a full rank h × d matrix A (rank(A) = d) such that,P = P(A) = {x ∈ d : Ax ≥ 0}     (4)h rows of the matrix A represent h linear inequalities, whereas the full rank mention imposes the "pointed" effect in 0. Note that a pointed polyhedral cone is, in general, not restricted to be located completely in the positive orthant as in (3). For example, the cone considered in extreme-pathway analysis may have negative parts (namely for exchange reactions), however, by using a particular configuration it is ensured that the spanned cone is pointed [The  pointed .r is said to be a ray of P(A) if r ≠ 0 and for all α > 0, α · r ∈ P(A). We identify two rays r and r' if there is some α > 0 such that r = α · r' and we denote r ≃ r', analogous as introduced above for flux vectors. For any vector x in P(A), the zero set or active set Z(x) is the set of inequality indices satisfied by x with equality. Noting Ai• the ith row of A, Z(x) = {i : Ai•x = 0}. Zero sets can be used to characterize extreme rays. For simplicity, we adopt in this document the following characteristic . The following statements are equivalent:a) r is an extreme ray of P(A)(r' is a ray of P(A) with Z(r) ⊆ Z(r') then r' ≃ r(b) if A is full rank, 0 is the unique vector that solves all constraints with equality. The extreme rays are those rays of P(A) that solve a maximum but not all constraints with equalities. This is expressed in (b) by requiring that no other ray in P(A) solves the same constraints plus additional ones with equalities. Note that in (b) Z(r) = Z(r') consequently holds.Since P(A) can be expressed as a non-negative linear combination of extreme rays, and the converse is true: all non-negative combinations of extreme rays lie in P(A). Moreover, the set of extreme rays is the unique minimal set of generating vectors of a pointed cone P(A) .An important property of the extreme rays is that they form a finite set of generating vectors of the pointed cone . Consequently, e ∈ P is an extreme ray of P if and only if: for all e' ∈ P : R(e') ⊆ R(e) ⇒ e' = 0 or e' ≃ e, i.e. if and only if e is elementary. Thus, all three conditions in (2) are fulfilled.A does not contain the identity matrix and P (as given in (1)) is not ensured to be a pointed polyhedral cone anymore [+ and v- with v = v+ - v- and v+, v- ≥ 0 [In the general case, some reactions of the metabolic system can be reversible. Consequently,  anymore . Because anymore . One way, v- ≥ 0 . It has , v- ≥ 0 . Here weS and the reconfigured network  by S'. The reactions of S are indexed from 1 to q. Remember that Irrev denotes the set of irreversible reaction indices and Rev the reversible ones. An irreversible reaction indexed i gives rise to a reaction of S' indexed i. A reversible reaction indexed i gives rise to two opposite reactions of S' indexed by the pairs (i,+1) and (i,-1) for the forward and the backward respectively. The reconfiguration of a flux vector v ∈ q of S is a flux vector v' ∈ Irrev ∪ Rev × {-1;+1} of S' such thatWe first introduce some notations. We denote the original reaction network by N' be the stoichiometry matrix of S'. N' can be written as N' = [N - NRev] where NRev consists of all columns of N corresponding to reversible reactions. Note that if v is a flux vector of S and v' is its reconfiguration then Nv = N'v'.Let v' ∈ Irrev ∪ Rev × {-1;+1} is such that for any reversible reaction index i ∈ Rev at least one of the two coefficients v'i,+1) (or v'i,-1)  the set of reconfigured EMs of Sthe set of two-cycles made of a forward and a backward reaction of S' derived from the same reversible reaction of Sb) Proof: see Methods.Thus, the set of EMs of the original network is equivalent (up to the two-cycles) to the set of EMs in the reconfigured network and therefore can be seen as a reduced set of extreme rays of the pointed convex polyhedron as defined by:P = {v' ∈ q + |Rev| : N'v' = 0 and v' ≥ 0}     (5)Hence, EMs computation can be derived from any extreme ray enumeration algorithm applied to the reconfigured network and followed by vector back-configuration and the elimination of meaningless vectors, namely the two-cycles.extreme currents. Thus, extreme currents are identical to the EMs in the reconfigured network and, hence, also (up to the 2-cycles) equivalent to the EMs from the original networkNote that exactly the same procedure – splitting reversible reactions into two irreversible ones – was carried out also in the original work of Clarke  on stabiIn the following we present a simple yet efficient algorithm for extreme ray enumeration, the so-called Double Description Method . We showgenerating matrix R of a pointed polyhedral cone P(A) is a matrix such that P(A) = {x ∈ d : x = Rλ for some λ ≥ 0}. The pair (A,R) is called a Double Description pair, or DD pair. As mentioned above, the extreme rays form the unique set of minimal generating vectors of P(A) and thus, considered as set of d-vectors, the extreme rays of P(A) form the columns of a generating matrix R that is minimal in terms of number of columns. The pair (A,R) is then called a minimal DD pair.A Ak, Rk) from a minimal DD pair (Ak - 1, Rk - 1), where Ak is a submatrix of A made of k rows of A. At each step the columns of Rk are the extreme rays of P(Ak), the convex polyhedron defined by the linear inequalities Ak. The incremental step introduces a constraint of A that is not yet satisfied by all computed extreme rays. Some extreme rays are kept, some are discarded and new ones are generated. The generation of new extreme rays relies on the notion of adjacent extreme rays. Here again, for the sake of simplicity, we adopt a characteristic . Then the following statements are equivalent:r and r' are adjacent extreme rays(a) r" is a ray of P(A) with Z(r) ∩ Z(r') ⊆ Z(r") then either r" ≃ r or r" ≃ r'(b) if P is pointed, A has full rank and contains a nonsingular submatrix of order d denoted by Ad. Hence, (Ad, Ad-1) is a minimal DD pair which works as initialization and leads directly to step k = d. Note that there is some freedom in choosing a submatrix Ad or some alternative starting minimal DD pair.The initialization of the double description method must be done with a minimal DD pair. One possibility is the following. Since Ak - 1, Rk - 1) is a minimal DD pair and consider a kth constraint defined by a not yet extracted row of A, denoted Ai•. Let J be the set of column indices of Rk - 1 and rj, j ∈ J, its column vectors, i.e. the extreme rays of P(Ak - 1), the polyhedral cone of the previous iteration. Ai• splits J in three parts , with equality (zero ray) or does not satisfy it (negative ray):Assume J- = {j ∈ J : Ai•rj < 0}Rk is ensured in considering all positive rays, all zero rays and new rays obtained as combination of a positive and a negative ray that are adjacent to each other [Adj the index set of the newly generated rays in which every new ray is expressed by a pair of indices corresponding to the two adjacent rays combined. Hence, Rk is defined as the set of column vectors rj, j ∈ J' withMinimality of ch other . For conk = h i.e. having treated all rows of the matrix A. The columns of the final matrix Rm are the extreme rays of P(A).The incremental step is repeated until A, and a post-processing step that gets rid of futile two-cycles and computes the back-configuration. The dimension of the space is given by the number of reactions in the reconfigured network: q' = q + |Rev|. This results in the general algorithmic scheme as given in Table The Double Description Method together with Theorem 1 offers a framework for computing EMs. The only steps to include are a reconfiguration step that splits reversible reactions and builds the matrix FluxAnalyzer version 5.0 [R.As mentioned in the introduction section, the two most efficient algorithms for computing EMs available are the recently introduced null-space approach  and the sion 5.0 ). Both aI represents q independent rows extracted from A = [NT -NT I]T and can thus be used for Aq. The matrix Aq-1 = I-1 = I gives the q extreme rays that obey to these q independent constraints and works as initialization of R.The matrix m linear inequalities defined by Nr ≥ 0 and -Nr ≥ 0, i.e. m equalities: Nr = 0. The processing of an equality constraint is done in a single pass by only keeping rays of J0 instead of J+ ∪ J0. This is achieved by replacing the line R' ← {rj : j ∈ J+ ∪ J0} with R' ← {rj : j ∈ J0} in the part "Processing of constraints in a given order" in Table Arj (required for the Gaussian combination step) are explicitly stored throughout the algorithm (in the left-hand side of the tableau [The remaining constraints are 2 tableau ) and adaR by a well-defined kernel (or null-space) matrix K of N with a particular structure (the transposed KT is in (reduced) row-echelon form):The idea there is to initialize null(N,'r'). One can assume N to be of rank m, the opposite case being discussed below ("On redundancies and network compression"). This implies  to be of size m × (q - m) and the identity of size q - m. This structure is obtained by allowing a reordering of the rows of K, i.e. of the reaction indices. Without losing generality, one can assume that the reactions corresponding to the block I are indexed from 1 to q - m. Consider the (q + m) × q matrix . For all x in P(Aq + m), there is some vector λ ≥ 0  such that x = Kλ. Reciprocally, for all λ ≥ 0, the vector x = Kλ lies in P(Aq + m). Thus (Aq + m, K) is a DD pair. Since K is a kernel matrix, its columns are independent vectors therefore (Aq + m, K) is a minimal DD pair. K as defined in (8) works as initial value for R. Hence, the initialization in this setup delivers directly k = q + m solved constraints.which can be computed, for example, by the MATLAB command m linear inequalities defined by ri ≥ 0, i = q - m + 1...q. The Gaussian elimination step simplifies tooThe remaining constraints are  and , because  is positive and  negative due to the definitions of J+ and J-.The right hand-side is practically a positive combination of the two vectors Here we give explicitly the adjacency test in the case of reconfigured networks for each setup. Variants handling reversible reactions directly were introduced for CBA and NSA. They lead in general to more complex algorithmic steps for a little (at most 2-fold) memory gain.k + 1 to check whether two extreme rays r and r' of the cone P(Ak) are adjacent. The adjacency test is based on Definition 2(b). Note that for a given extreme ray r of the cone P(Ak), the considered zero set Z(r) is defined over the k constraints Ak.The test is used when processing the constraint CBA: As mentioned above, in a CBA setup, equality constraints are solved within a single iteration. After the l-th iteration step, k = q + 2l constraints are processed, therefore . The last 2l constraints are satisfied with equality for all computed rays. We denote by Zu(v) the Zero set of a vector v over the u first constraints. Here, with u = q it matches to the set of non-participating reactions in v. The adjacency test is then equivalent to the search of a third extreme ray r" such that Zq(r) ∩ Zq(r') ⊆ Zq(r"). If such an r" exists, then r and r' are not adjacent.NSA: After the l-th iteration step in an NSA setup, k = q + m + l constraints including p = q - m + l sign constraints are processed. Thus . The last 2m constraints are satisfied with equality for all computed rays. Therefore, the adjacency test is then equivalent to the search of a third extreme ray r" such thatZp(r) ∩ Zp(r') ⊆ Zp(r")     (10).p(q - m ≤ p ≤ q) elements of the rays, in contrast to all q elements for CBA. This is one reason behind the relative velocity of NSA compared to CBA.Thus, for NSA we only have to check the first N and thus the input size of the problem: the detection of conservation relations, of strictly detailed balanced reactions and of enzyme subsets.It is common practice to reduce the problem of extreme ray enumeration by restricting the input set to the set of irredundant constraints . AlthougN . This iK, the kernel matrix of N, and can be eliminated from the system. A non-trivial example is shown in Figure K. Some of those can be found by a simple analysis of N. For example, all the uni-directional reactions pointing into an internal sink (or emanating from a source) are certainly not participating in any steady-state flux . If α < 0, the constraints r1 ≥ 0 and r2 ≥ 0 imply r1 = r2 = 0, hence, a special case of strictly detailed balanced reactions. In this case we say that the reactions contradict each other. Both reactions are not used and can be eliminated from the system as reactions R1 and R4 in Figure An enzyme subsets is defined as a group of reactions with relative constant flux ratio at steady state. Many of them can be identified as row vectors of uniquely produced (respectively consumed) if only one single reaction, say i, can produce (respectively consume) M for several consuming (respectively producing) it  M with reaction i and remove metabolite M, decreasing the dimension of the problem further  ray because only positive combinations of rays are performed. The same holds for the NSA with respect to the p already processed inequality (irreversibility) constraints. This is of great importance since the adjacency test requires the information on zero/non-zero places in the rays only.Using the reconfigured network with only irreversible reactions we have shown that the most important algorithms for EM computation belong to the same general framework. However, the original algorithms from Schuster and Wagner operate directly on the original network without splitting reversible reactions. At a first look, this seems to be more efficient since the dimension (number of reactions) is lower, decreasing seemingly also the memory requirement and the costs for adjacency tests. However, using the reconfigured network N has full rank m, i.e. there is no conservation relation. In this section, all variables correspond again to the network with split reversible reactions.We illustrate this idea for NSA because this approach turned out to be more efficient than CBA. We assume that R we use a kernel matrix K of N having form (8):As described above, for an initialization of q - m rows (reactions)) during the next iterations. The first row to be processed now is p = q - m + 1. Using the general algorithmic scheme provided above all rays with non-negative entries at row p are retained and all negative entries can be combined with positive ones that are adjacent to them to obtain a zero at position p.Note that we use here the transposed representation of the tableau compared to Wagner's original article . Since bp-th row leads to a collection of t rays, we have:Assuming that the procession of the R1, contains the p processed rows which only contain non-negative values. Again, positive combinations of rays performed during the next iterations lead in the upper part to sums of non-negative numbers. Hence, it is easy to keep track of the zeroes in the upper part R1 by the use of bit masks. After the procession of the p-th inequality constraint the p-th row (i.e. the first row of R2) can be transformed to its binary representation and moved from R2 to R1. Using a binary representation for R1 has many advantages:The upper part, p + 1 to be processed we have to perform the adjacency test for pairs of vectors , . This test only requires the first p elements of these rays (see (10)), hence, exactly the columns of R1. Test (10) can then be written as a simple (and fast) bit operation. Two distinct vectors ,  are adjacent if and only if for all vectors rk distinct from  and , it holds:(i) For the next row  taken from R1; rp 1...denotes the first p elements of r). Of course, the identical terms in the parentheses are computed only once.. The other  components of the two rays (contained in R2) are combined as usual by eq. (9).(ii) Combination step of two adjacent rays (eq. (9)) reduces for the part in R1 are not only fast, they are numerically exact in contrast to operations on real numbers.(iii) Bit operations as applied in R1 binary takes only 1.6 % of the memory needed for real numbers. Taking into account that in the worst case  the number of reactions in the reconfigured network is twice of that from the original one we still have a reduction in memory requirements of more than 96%. Note that R2 is empty at the end of the algorithm, hence, all EMs are then stored binary.(iv) The binary representation requires much less memory. Taking a typical 64-bit floating-point variable, storing in parallel to the full  tableau of EMs which is not necessary here.Bitmap representations of EMs have already been used in earlier implementations for accelerating the adjacency (elementarity) tests. However, binary tableaus had then been stored and updated S' as binary vectors. Binary patterns of EMs are completely sufficient for many applications of EMs (see discussion). However, a well-known lemma ([After the whole processing, EMs (extreme rays) are obtained for the reconfigured network n lemma . The following statements are equivalent:r is an extreme ray of P(A)(a) rank(AZ(r)) = d - 1(b) Zq(e) and its complement the reaction set R(e) of an EM e in the reconfigured network S'. Lemma 2 says that the equation  and thereforeEach obtained binary vector provides the zero set NR(e)eR(e) = 0     (14)R(e) is 1. NR(e) denotes the m × |R(e)| sub-matrix of N containing all those reactions (columns) of N which are involved in e. Solving the homogeneous linear system (14) gives a vector that can be normalized and properly oriented for example by dividing it by the value on its first participating reaction (see the example below). The reconstruction process reflects the fact that an EM is – up to a scalar – determined by its participating reactions.admit a one-dimensional solution space, i.e. the dimension of the null space of NS' back into their representation in the original network S by using the rules given before Theorem 1. Note that it is also possible to transform first the binary EMs from S' into the binary EMs of S and then to reconstruct the real numbers (by using eq. (14) for the stoichiometric matrix of the non-reconfigured network S; see pseudo-code). In both cases, if the original network had been compressed during pre-processing, the EMs can finally be expanded to their corresponding modes in the uncompressed network.In a second post-processing step, we transform the  EMs of Using the results of the previous sections we are now able to give a pseudo-code of the binary (null-space) approach Figure . The codNote that the pseudo-code in Figure m equality constraints are always solved for each ray during the procession of sign constraints. Since any ray satisfies by Lemma 2 at least a total of q - 1 constraints, this implies that at least q-1-m sign restrictions are solved by equality. Hence each ray contains at least q-1-m zero-places. This fact can be used as a shortcut when checking the adjacency of two rays (see pseudo-code). At the end of the algorithm, it follows that the maximal pathway length |R(e)|max, that is the maximal number of involved reactions in an EM, reads (cf. [In the null-space approach, the ads (cf. ):R(e)|max = q - (q - m - 1) = m + 1     (15)|R for the reconfigured network can be done with a null space matrix K' of N' having the special structure (8). Several of such kernel matrices may exist. We are interested in such a one that contains as many zeros as possible because the number of zeros in the starting tableau R has great impact on the number of ray combinations to be performed. For this purpose, it can be exploited that very sparse vectors of the null space of N' (not contained in the null space of N) are known, namely the two-cycles emerging by splitting up reversible reactions. We detail in Method section a technique that incorporates as many two-cycles as possible into K to construct K'.As for the non-reconfigured network, the initialization of N of this network reads accordingly:This section is devoted to illustrate our binary approach for computing elementary modes. Figure NC of the compressed system reads:Using our rules for removing redundancies, this network can be compressed as depicted in Figure From this compressed network, we can compute a null space matrix having structure (8), here even without permuting rows (reactions):KC would be the starting tableau in the original null-space approach. Applying our binary approach we have now to split the (only) reversible reaction R4c in the compressed network  (Methods section). KC – as given in (18) – contains only irreversible reactions in the identity sub-matrix. Therefore, without further rearrangements, we can already use it to construct KC' as described in the Methods section. We introduce an additional row in the identity sub-matrix of KC (corresponding to R4cb) and an additional column representing the two-cycle from the split reversible reaction R4c:Now we need to determine a null space matrix KC' is now a proper initialization for the R tableau according to (11). The first four rows (in the identity sub-matrix) can be seen as already completed, we therefore denote the starting tableau as R4. According to (12) we can divide R4 into a binary (a non-zero entry is demarked by "×") and unprocessed real number part:R5 has 6 columns and reads:We proceed now with the 5-th row (R4c). All columns with non-negative entries in R4c are retained (columns 1 and 4). Columns 2 and 3 have a negative entry at position R4c and are therefore combined with 1 and 4 to obtain a zero at position R4c. In the binary sub-tableau, the combination step is a simple OR operation. Thereby, using the obtained binary patterns, the adjacency test (13) must be performed for each pair of combined columns. Here, all 4 possible pairs are adjacent. Accordingly, after completing row 5, tableau q'-m-1 = 6-2-1) and that their respective combinations would give columns with only 2 zeros. These combinations are therefore not included in the tableau. We obtain:Now we have already reached the last iteration step where R5c – the last row in real number format – is processed. Columns 1–5 are retained and column 6 is combined with columns 1,3 and 5. However, the column pairs (1,6) and (3,6) are not pairs of adjacent rays. This can be detected in two alternative ways. The usual way is that both column pairs violate condition (13) because of column 4. The second and quicker way is to observe that the minimal number of zeros in this network is 3 (R6 is the binary representation of the EMs (extreme rays) from the split compressed network. Now, the post-processing begins. First, we remove the spurious 2-cycle (second column in R6) raised by splitting R4c. Then, rows R4c and R4cb are combined by an OR operation and row R4cb is dropped. Note, if a completely reversible elementary mode exists in the non-split network, it would lead to two EMs – one for each direction – in the split network. In such a case, either both are kept or only one, then marked as reversible EM. We have now obtained the 5 EMs of the compressed network as binary vectors:Tableau e1 using eq. (14):Here, it is easy to reconstruct the real numbers of the EMs from their binary patterns. For illustrating the general case, we reconstruct the first mode , hence of the solution space of eq. (25) is 1 . A scalable solution vector is (2,1,1)T, normalizing to the first component yields the unique solution (1,0.5,0.5)T. Thus, the first EM in the compressed network is e1 = (1,0,0,0.5,0.5)T. Reminding that we lumped the original reactions R1 and R2 into R1c and R6 and R7 into R5c, we can finally reconstruct the original elementary mode from the uncompressed network, that is R1 + R2 + 0.5 × R5 + 0.5 × R6 + 0.5 × R7.The dimension of the null space of FluxAnalyzer [Escherichia coli investigated originally in [coverN .We implemented the binary null-space approach (binary NSA) in MATLAB (Mathworks Inc.) and incorporated it into the Analyzer ,34. The nally in ,23. For Table coverN and in FluxAnalyzer, respectively. Besides, different row orders in the starting tableau can generally result in different computation times. However, it seems that the original and the binary NSA are comparable with respect to computation time. The adjacency tests in the binary null-space approach need to consider more elements (due to the split of reversible reactions) but are simpler to perform because preliminary modes from a previous iteration cannot lose their elementary property. Note also that implementing the full algorithm in C  might further accelerate the computation considerably.Comparing the required computation times, the binary NSA seems to be slightly faster than the original NSA. This observation should not be considered as a general result, since we cannot exclude that there are different potentials in optimizing the source code of K' as initialization of R (as explained in the Methods section) contributes considerably to a reduced computational effort. We can estimate this by the total sum  over the number of candidates Pi occurring in the tableau before iteration i. In S1, for example, . Computing instead an arbitrary null-space matrix K' for N' (e.g. via MATLAB null command) results in a more dense initialization for R and the naive initialization would lead to . The larger numbers of candidates increase the costs for adjacency tests and accordingly the running time drastically. This underlines that the success of the null-space approach  depends strongly on the initially chosen null space matrix.Using a special null space matrix Generally, computing the stoichiometric coefficients of the EMs from their binary patterns is in larger networks in low proportion to the overall computation time (S3: ca. 0.8%).Whereas the computational demands seem to be comparable for both null-space approaches, the memory requirements for the binary NSA are much lower, in particular during the last iterations. For this reason, the 2.45 millions of EMs from network S3 could be computed on a typical PC, whereas the original NSA ends in the 26-th iteration step  due to memory overflow.matroid theory [oriented vector matroid, the elementary modes correspond to the positive circuits (or positive cycles), which are minimal dependent sets. In fact, an elementary mode is a minimal linearly dependent set of the column vectors of the stoichiometric matrix (in the reconfigured network with only non-negative coefficients). This has been mentioned only rarely so far [Elementary modes are smallest functional sub-networks, which can be interpreted geometrically as extreme rays from a pointed convex cone (corresponding to the network with split reversible reactions). The computation of extreme rays has been intensively studied by the polyhedral computation community and we think that the metabolic community can benefit from it. We shall also mention another abstraction of elementary modes within the framework of d theory . In an oy so far . MatroidAdjacent extreme rays can also be detected by an algebraic characterization that completes Definition 2 :c) r and r' are extreme rays and the rank of the matrix AZ(r) ∩ Z(r') is d-2(r and r') and to the fixed size matrix A, in practice to the stoichiometry matrix. In comparison, the combinatorial test implies a loop over all other rays (r"). Therefore, the algebraic test could be suited for distributed computing.In practical cases the characterization of adjacency is mostly computed in its combinatorial form than its algebraic one . HoweverB for the number of EMs is (reversible modes are counted only once):Some theoretical issues of the combinatorial complexity of EMs were discussed in . An uppeAssuming that no conservation relations occur in the stoichiometric matrix, we obtain:q and m should be taken from the non-split, compressed network to obtain the lowest upper bound. In larger, realistic networks, even if compressed, the values for B explode quickly. Fortunately, the actual number of modes in real networks proved to be much smaller than the boundary (cf. B ≈ 2.54 · 1011 for S1 in Table Note that R(e)|max which is, by eq. (15), m + 1. However, many EMs, if not all, have a lower length immediately reducing the possible number of modes [E. coli modes on glucose (network S1) is shown in Figure m + 1 = 89 + 1 = 90. Modes that are not involved in biomass synthesis, in particular, are much smaller. In terms of linear algebra this means that there exist vector sets W containing fewer than m + 1 column vectors of N that are linearly dependent. In polyhedral computation this phenomenon is known as degeneracy. Generally, degenerate systems may cause annoying difficulties and must be handled often differently to non-degenerate systems, albeit they reduce here the number of modes. The algorithms related to EM computation may be, in general, especially suited for computing extreme rays in such strongly degenerate systems, whereas other programs may be better suited for only weakly degenerate problems. For example, the software lrs [A third reason is related to short pathway length. The upper bound reflects the case where all EMs have maximal pathway length |of modes . The patware lrs  implemenware lrs  that is q' = 51 + 17 = 68). Of course, only a fraction of this amount can be stored during the algorithm due to other  temporary variables. Besides, reactions that are not yet processed are still stored as real numbers. The amount M of memory required for storing E modes after the procession of p reactions (stored binary) is Albeit the general framework was formulated long time ago, the explicit introduction of the null-space approach was an important mile-stone in accelerating the computation of EMs. The binary null-space approach as introduced herein increases the efficiency of this approach also with respect to the memory requirements and enables now to compute EMs in networks significant larger as those investigated before. A simple computation gives the number of about 85 millions of EMs in a network of 100 (compressed) reactions that can be stored in 1 GB RAM (cf. compressed and reconfigured S3: M = E · (p + 64 · (q - p)).     (28)It depends on the evolution of the number of EMs during the algorithm where the maximal memory demand occurs. Generally, much larger networks can now be treated.The four main results of this work are: (i) showing the equivalence between extreme rays and elementary modes, (ii) showing that algorithms for computing elementary modes can be seen as variants of the double description method for computing extreme rays in pointed polyhedral cones, (iii) introduction of a general framework and of new methods for redundancy removal and network compression, (iv) introduction of the new binary approach for computing extreme rays and elementary modes.α-spectrum need the explicit  coefficients, i.e. the reaction rates, in the EMs. Whenever needed, the explicit representation of an EM can be determined (possibly temporarily) from its binary pattern.The binary approach computes elementary modes as binary patterns of participating reactions that are sufficient to compute the respective stoichiometric coefficients in a post-processing step. For many applications – following the computation – it is even sufficient to operate on the binary patterns of EMs. Among all applications of EMs presented in the introduction section, only the identification of all pathways with optimal yield, the "control-effective fluxes", and the The binary approach decreases the memory demand up to 96% without loss of speed and without loss of information giving the most efficient method available for computing elementary modes to date. The limiting step in computing elementary modes has thus been shifted back to the computation time. Parallelization – as investigated within the traditional, not-binary, schema in  – might S'. Let e' be a flux vector defined by either case a) or b). Clearly N'e' = 0 and e' ≥ 0. In case b) e' is not elementary only if the single forward or backward reaction balances all internal metabolites, i.e. if the reaction includes not any internal species. We can safely exclude this pathologic case by considering that N does not contain a null column. Therefore, e' is elementary. In case a), assume e' is not elementary, i.e. there exists a non-null flux vector x' of S' not equivalent to e' such that x' ≥ 0, N'x' = 0 and R(x') ⊆ R(e'). By definition of the reconfiguration, for each i ∈ Rev, at least one among e'i,+1) (or e'i,-1)  ⊆ R(e), a contradiction.We prove first that each case a) and b) defines EMs of e' neither defined by a) nor b), such that e' ≥ 0, N'e' = 0 and e' elementary. For each i ∈ Rev at least one among e'i,+1) (and e'i,-1) . Thus the back-configuration e of e' can be defined. By definition, e is not an EM of S. There exists x not equivalent to e such that Nx = 0, xi ≥ 0i for i ∈ Irrev and R(x) ⊆ R(e). The reconfiguration x' of x is such that x' is not equivalent to e', x' ≥ 0, N'x' = 0 and R(x') ⊆ R(e'), a contradiction.Hence each case a) and b) defines EMs of S'. We prove now that there is no other case. Assume there exists R in reconfigured networks as a null space matrix K' of N' having the special structure (8), i.e. . Several kernel matrices having this form can exist. Here we are interested in such a one that contains as many zeros as possible because the number of zeros in the starting tableau R has a great impact on the number of ray combinations to be performed. For this purpose, we can exploit the fact that we already know |Rev| many very sparse vectors of the null space of N', namely the two-cycles emerging by splitting up reversible reactions. Our goal is therefore to incorporate many  of these vectors into K to obtain K'. For this purpose, we first compute the kernel matrix K of N. Then, by simple linear combinations of columns  and possibly by permutation of rows in K, we try to obtain , where only irreversible reactions (rows) are contained in the identity matrix I. If this is possible then we can easily include the backward directions of reversible reactions (as rows) and the two-cycles (as columns) into K yielding K':As in the case of non-reconfigured networks, we must initialize q - m columns in K' correspond to the original columns in K, but contain additionally zeros for the inserted backward reaction of originally reversible reactions. These columns are obviously linearly independent and are contained in the null space of N'. Sub-matrix  is a |Rev| × |Rev| identity matrix whose rows correspond to the backward directions of split reactions. Finally, C is a |Rev| × m sub-matrix which complements  in such a way that they represent together the two-cycles of the split reactions.  I and  yield together the new I', whereas  and C represent together  of K'. Thus, K' contains q - m + |Rev| linearly independent (basis) vectors of the null space of N' and is in form (8).The first K' as in (M1) can be found. Using instead an arbitrary K' can lead to a much larger computation effort because much more candidates are computed at an early state .To our experience, in most realistic networks, a matrix  ascending with respect to the number of their non-zero entries.A further simple strategy avoiding that many rays are computed early is to sort the rows in I of K, we can nevertheless find a matrix K' with the same basic structure as in (M1). However, for some originally reversible reactions, the forward (in I) and backward (in ) direction will then be contained in I'. For each of those, the two-cycle cannot be represented by C and  (because the row of the forward direction is contained in I' and not in K') and another corresponding column in C has to be constructed. Assume a reversible reaction is contained as j-th row in I. Assume further that the inserted backward direction of this reaction corresponds to the k-th row of . For the k-th column ck of C we can then chose the j-th column  of  multiplied by -1, i.e. . Together with the k-th column in , this gives a null space vector of N', which is linearly independent of the others and can therefore serve as basis vector in K'. The vector ck is now probably not that sparse. However, it enables us to retain the 2-cycles at least for those split reactions whose forward direction is not contained in I.In case it is not possible to arrange only irreversible reactions into the sub-matrix initializeR that provides a proper initialization of R as described above (starting with the stoichiometric matrix N and the indices of the reversible reactions) can be obtained from the corresponding author.A MATLAB function Numeric variables in MATLAB can be scalars, vectors or two-dimensional arrays (i.e. matrices). To be more precise, a scalar in MATLAB is actually a 1 × 1 array and a vector is a 1 × n or n × 1 array. Size and type of a variable are automatically declared (or changed) by assignments to it. The following examples illustrate how to assign or access values of variables:• scalar: a = 1;b.• b(3) = 5; the value 5 is assigned to the third element of (vector) c. It is also possible to use an array of integers to access the elements of a vector, e.g. a = [2,3,4]; b = [1,3]; c = a(b). Vector c reads then [2,4].• c(1:3) = [5,8,9]; here, "1:3" expresses "from 1 to 3", thus, 5, 8 and 9 are assigned to the first three elements of vector mat.• mat(2,5) = 3; value 3 is assigned to the element in the second row and fifth column of matrix mat1 is copied into the third row of matrix mat2. Here, the colon operator ":" expresses "all elements of the respective dimension" (here: columns). Of course, it must be ensured that mat1 and mat2 have the same number of columns.• mat1(3,:) = mat2(5,:); the values of the fifth row of matrix mat are assigned to a which is now a 3-element vector.• a = mat(7,1:3); the first three elements of the seventh row of matrix a and shifts all elements behind one position back, i.e. vector a reads now [17,39].• a= [17,34,39]; a(2)= []; deletes the second element of The pseudo-code given in Figure length(a); if a is a vector  then length returns the number of elements in a.• c = find(a); if a is a vector  then find returns all positions in a which are not zero. Example: find([23,0,5,9,0]) returns (1, 3, 4).• c = or(a,b) returns the result of the logical OR operation applied element-wise to a and b. a and b can be scalars, vectors or matrices and must have the same size. Example: if a = [1,0,29], b = [1,0,0] then or(a,b) returns [1,0,1]. In the pseudo-code, we use this routine exclusively for OR-operations of bit masks (arrays with only "ones" and "zeros").• c = zeros(m,n) returns a matrix of size m × n filled with zeros.• c = null(a) returns a null-space matrix of matrix a.• c = intersect(a,b) returns the intersection of elements in vectors a and b.• c = all(b) returns "1" if all entries in vector b are not zero and "0" otherwise.• c = EM(s): Elementary Mode(s) also known as Elementary Flux Mode(s).Both authors contributed equally to this work, the starting idea of the binary approach coming from a discussion between them. JG mainly established the relationships between extreme ray and elementary modes computation. SK mainly devised and implemented the binary null-space algorithm. Both authors prepared the manuscript jointly.


MnSOD promoter contains an activator protein-2 (AP-2) binding site that modifies transcription of MnSOD. Mutations have been identified in the proximal region of the promoter in human tumor cell lines. One of these mutations (-102C>T) has been shown to change the binding pattern of AP-2 leading to a reduction in transcriptional activity. The aim of our study was to develop a method to identify and determine the frequency of this (-102C>T) polymorphism in human tissues.Manganese superoxide dismutase (MnSOD) plays a critical role in the detoxification of mitochondrial reactive oxygen species constituting a major cellular defense mechanism against agents that induce oxidative stress. The A new TaqMan allelic discrimination genotype method was successfully applied to genomic DNA samples derived from blood, buccal swabs, snap frozen tissue and paraffin blocks. The polymorphism was shown to be in Hardy-Weinberg Equilibrium in an evaluation of 130 Caucasians from Warsaw, Poland: 44 (33.8%) were heterozygous and 6 (4.6%) were homozygous for -102T.MnSOD -102C>T polymorphism in human subjects by a novel Taqman allelic discrimination assay. This method should enable molecular epidemiological studies to evaluate possible associations of this polymorphism with malignancies and other diseases related to reactive oxygen species.This report represents the first description of the  Three distinct types of SODs have been identified in human cells: 1) a homodimeric cytosolic CuZnSOD [Antioxidant enzymes such as superoxide dismutase (SOD) protect cells from oxidative stress. Generation of reactive oxygen species (ROS) has been implicated in the etiology of a diversity of human diseases, including cancer, aging22, athero CuZnSOD , 2) an e CuZnSOD , and 3)  CuZnSOD .Numerous reports indicate a relative deficiency of superoxide dismutase catalytic activity, including mitochondrial MnSOD, in many types of solid tumors ,10. InteFurther evaluation of MnSOD suggests that it is critically important in maintenance of mitochondrial function. Mice with deficiency of this enzyme exhibit progressive cardiomyopathy, neurodegeneration and perinatal death. These sMnSOD mitochondrial targeting sequence has been associated with risks to various diseases including breast cancer[Genetic polymorphism in the st cancer,18, lungst cancer, cardiomst cancer and Parkst cancer.A reduction of MnSOD activity has been shown to exist in many types of human cancer cells when compared to normal cells . A recenMnSOD gene is localized to chromosome 6 (6q25). The MnSOD promoter region is characterized by a lack of TATA or CAAT boxes but the presence of a GC rich region containing multiple SP-1 and AP-2 binding sites [MnSOD promoter sequence (MnSOD -102C>T) has been shown to change the binding pattern of AP-2 leading to a reduction in transcriptional activity. However the presence of this polymorphism has not been reported in human tissue.The human ng sites . Furthersome 6 6q. The MnSMnSOD promoter.In this study we developed a TaqMan allelic discrimination assay to reliably genotype DNA from many tissues  for the -102C>T polymorphism in the We confirmed the presence of the -102C>T single nucleotide polymorphism in human subjects and submitted the sequence variant to Genbank. The genReactive oxygen species in the form of superoxide radicals, hydrogen peroxide, and hydroxy-radicals are formed during incomplete reduction of molecular oxygen during normal respirations. The production of reactive oxygen species remains relatively stable during normal physiologic respirations. A significant increase in the production of reactive oxygen species such as superoxide radicals can be greatly increased as a result of metabolic disorders or more commonly from exposure to toxins such as cigarette smoke, well-cooked meat, urban residency, and excessive alcohol consumption.MnSOD gene in E. coli significantly increased mutation frequency and cell death when bacteria were grown under aerobic conditions [MnSOD gene has led to detrimental effects. Polymorphisms of the human MnSOD gene have been found in the promoter region, the sequence coding for mature protein, and the mitochondrial targeting sequence. Initial evaluation of the five prime flanking regions from human tumor cell lines indicated that there were no major additions or deletions in the five prime flanking regions of the human MnSOD gene [MnSOD gene [Under normal physiologic conditions, superoxide radicals are detoxified by superoxide dismutase. Among the three SODs, MnSOD has been demonstrated to be the only form that has been essential for survival of aerobic life . Inactivnditions . This haSOD gene . HoweverSOD gene . This chSOD gene , no evalEvaluation of the -102C>T polymorphism is complicated by difficulty in PCR because of the excessive GC rich region in which this polymorphism exists. This location, upstream from the transcription start site was extremely difficult to identify through multiple PCR-restriction fragment length polymorphism (RFLP) assays, which failed to adequately digest at this polymorphism site, and led to multiple false negative results. We found only the highest quality DNA (i.e. blood) was able to be evaluated using a PCR RFLP assay with only 50% genotyping success. This failure to accurately reproduce the PCR-RFLP assay , led us The TaqMan allelic discrimination assay provided results that were confirmed by automated DNA sequencing and blind repeat genotyping. Although we did not test it use on DNA from multiple tissues from the same individual, it was successful for DNA samples derived from buccal swabs and paraffin blocks. It has significant advantages over RFLP analysis, allele-specific amplification, allele-specific hybridization, and oligo-nucleotide ligation assay techniques. The reasons for this advantage come from the reduction in labor intensive work up, the lack of need for special handling of radioactive probes, and the ability to modify this technique to evaluate multiple polymorphisms in this gene. In addition as more significant polymorphisms within the MnSOD gene are discovered, this technique will facilitate detection within the MnSOD gene.The limitations of this technique ultimately come from the quality of DNA that is available and the significant initial expense that is required for a TaqMan assay instrumentation.MnSOD -102C>T polymorphism in human subjects by a novel Taqman allelic discrimination assay. This method should enable molecular epidemiological studies to evaluate possible associations of this polymorphism with malignancies and other diseases related to reactive oxygen species.This report represents the first description of the Most DNA samples (130) were isolated from buffy coats of Caucasian controls derived from a population-based case-control study of stomach cancer carried out in Warsaw, Poland as previously described . To testDNA extraction from paraffin sections was performed after tissue sections (10 sections, 10 μm thick) were cut from paraffin blocks. Samples were removed from paraffin through a sequential extraction with histaclear, 100% ethanol and acetone, and dried under vacuum. The pellet was incubated overnight with proteinase K (200 μg/ml in 50 mM Tris-HCL pH 8.5, 1 mM EDTA and 0.5% Tween-20) at 55°C. After heating at 100°C for 10 min, digestion was sequentially extracted with phenol, phenol/chloroform and chloroform. DNA was precipitated with the addition of 3X volume 95% ethanol.MnSOD promoter region. A MGB quencher probe was utilized on the 3' end by a linker arm. TaqMan Universal PCR Master Mix (Applied Biosystems) was used to prepare the PCR. The 2X mix was optimized for TaqMan reactions and contained AmpliTaq-Gold DNA polymerase, AmpErase, UNG, dNTPs with UTP and a Passive Reference. Primers, probes and genomic DNA were added to final concentrations of 300 nM, 100 nM, and 0.5–2.5 ng/μl respectively. Controls (no DNA template) were run to ensure there was no amplification of contaminating DNA. Reference control DNA was also utilized to verify the polymorphisms identified. The amplification reactions were carried out in an ABI Prism 7700 Sequence Detection System (Applied Biosystems) with two initial hold steps (50°C for 2 min, followed by 95°C for 10 min) and 50 cycles of a two step PCR (95°C for 15 sec, 60°C for 1 min). The fluorescence intensity of each sample was measured at each temperature change to monitor amplification of the 278 base pair MnSOD promoter region. The -102 nucleotide was determined by the fluorescence ratio of the two SNP-specific fluorogenic probes. The fluorescence signal increases when the probe with the exact sequence match binds to the single stranded template DNA and is digested by the 5'-3' exonuclease activity of AmpliTaq-Gold DNA polymerase (Applied Biosystems). Digestion of the probe releases the fluorescent reporter dye (either FAM or VIC) from the quencher dye. As shown in figure MnSOD promoter region.SNP-specific polymerase chain reaction (PCR) primers and fluorogenic probes Table  were desTwenty samples with genotypes C/T (4 samples), T/T (3 samples), and C/C (13 samples), some of which were derived from paraffin-embedded tissues, were all confirmed by automated DNA sequencing. These sequence-confirmed samples served as reference standards for the remaining samples. In addition, 10% of the samples were genotyped blind a second time with identical results obtained.RM: Participated in design of study and manuscript preparationKH: Participated in genotyping samplesMD: Participated in design of methods of assayQL: Participated in statistical analysisBM: Participated in design of methods of assayJL: Participated in sample collectionNR: Contributed to the study design and the analysis and interpretation of the dataDH: Participated in design of study and manuscript preparation


Reports of the use of psyllium, largely in hypercholesterolemic men, have suggested that it lowers serum cholesterol as a result of the binding of bile acids in the intestinal lumen. Widespread advertisements have claimed an association between the use of soluble fibre from psyllium seed husk and a reduced risk of coronary heart disease. Given the purported mechanism of cholesterol-lowering by psyllium, we hypothesized that there would be a greater effect when psyllium is taken with breakfast than when taken at bedtime. Secondarily, we expected to confirm a cholesterol-lowering effect of psyllium in subjects with "average" cholesterol levels.Sixteen men and 47 women ranging in age from 18 to 77 years [mean 53 +/- 13] with LDL cholesterol levels that were normal or slightly elevated but acceptable for subjects at low risk of coronary artery disease were recruited from general gastroenterology and low risk lipid clinics. Following a one month dietary stabilization period, they received an average daily dose of 12.7 g of psyllium hydrophilic mucilloid, in randomized order, for 8 weeks in the morning and 8 weeks in the evening. Change from baseline was determined for serum total cholesterol, LDL, HDL and triglycerides.Total cholesterol for the "AM first" group at baseline, 8 and 16 weeks was 5.76, 5.77 and 5.80 mmol/L and for the "PM first" group the corresponding values were 5.47, 5.61 and 5.57 mmol/L. No effect on any lipid parameter was demonstrated for the group as a whole or in any sub-group analysis.The timing of psyllium administration had no effect on cholesterol-lowering and, in fact, no cholesterol-lowering was observed. Conclusions regarding the effectiveness of psyllium for the prevention of heart disease in the population at large may be premature. A cholesterol lowering effect has been reported for a variety of soluble dietary fibres -5. In FeThe accumulation and concentration of bile in the gallbladder is a continuous process. In rats which lack a gallbladder, the biliary excretion rate of bile salts is maximal at night  and bilePatients identified in gastroenterology practices as requiring long-term treatment with psyllium, typically for chronic constipation or the irritable bowel syndrome, were invited to participate in the study. In addition, individuals who had received dietary counselling in a lipid clinic regarding cholesterol-lowering and who subsequently had cholesterol levels deemed not to require further intervention because they met targets set out in clinical practice guidelines were invited by clinic staff to participate. Subjects were deemed ineligible if they were under age 18 years, were under active treatment for hyperlipidemia, had total cholesterol greater than 7.00 mmol/L, required alterations in dosage of medications which might have an effect on lipid levels, had had a gastrectomy, had any disease which is associated with hyperlipidemia, were receiving a bile acid binding resin, or if they did not eat breakfast regularly.The study was approved by the Conjoint Health Research Ethics Board of the University of Calgary, Faculty of Medicine. Subjects were given a description of the study indicating our interest in comparing the relative efficacy of hs versus am dosing with psyllium without indicating the specific hypothesis, and were asked to sign a consent form.Gastroenterology patients were given a high fibre diet sheet as part of their therapeutic regimen and were asked to take this on a continuing basis, beginning one month prior to the initiation of the study. The diet sheet emphasized dietary sources containing predominantly insoluble fibre. Lipid clinic patients had all received in-depth counselling regarding dietary measures for hypercholesterolemia, including a high fibre regimen, and had implemented their dietary changes at least one month before beginning the study. An unsweetened psyllium preparation, "Novo-Mucilax" [NovoPharm], providing three grams of hydrophilic mucilloid per 6.2 gram powder, and a scoop known to provide at least ten grams of psyllium were provided. Containers were numbered and weighed at the conclusion of each test interval. Subjects were randomized to initially take a scoop full of psyllium either with breakfast or at bedtime. Using a crossover design, psyllium was taken in the morning or evening for eight weeks and at the alternate time for the subsequent eight weeks.Determinations of serum total cholesterol, LDL, HDL and triglycerides were made before beginning psyllium, at eight weeks and at sixteen weeks after commencing its use. A trained dietician obtained a dietary history and patients were weighed at the beginning and at the conclusion of the study. All lipid determinations were undertaken following a 14 hour fast and analyses were done in a central laboratory.After initial data inspection based on boxplots and summary measures, cholesterol values at 8 and 16 weeks were examined using analysis of variance, taking into account treatment, period, and between and within subject effects in accordance with the cross-over design. The pattern of change from baseline to 16 weeks was evaluated using paired t-tests.Of 86 subjects beginning the study, 33 of those referred from the gastroenterology clinics and 30 of those referred from the lipid clinic completed it. Of those withdrawing, eight did so because they could not tolerate the psyllium or it was felt to interfere with prescribed medication, 2 had elevated lipids, 4 did not complete all the required blood work, 5 were unable to comply with the protocol because of work or lifestyle changes and 4 developed intercurrent diseases which precluded completing the protocol.The age range of subjects was 18 to 77 years, mean 53 +/- 13 years, including 16 men and 47 women. The mean dose of psyllium taken was 12.7 +/ - 2.3 g for morning dosing and 12.7 +/- 2.2 g when taken in the evenings.Values for total, LDL, HDL cholesterol and triglycerides at baseline, eight and sixteen weeks for various subgroupings are tabulated in tables The mean caloric intake or the intakes of fat or fibre did not change significantly during the study table . There wWe failed to prove our hypothesis that administration of psyllium in the morning would have a greater cholesterol-lowering effect than it would in the evening. Not only was there no observable difference in lipid levels between the crossover periods but the daily ingestion of a greater daily dose than the 10.2 g of psyllium for which the FDA allows health claims to be made  had no eWe used a crossover design since this was the most appropriate one for the primary question being addressed; accordingly, our study did not include a control group. However, the nature of the study should not have provided any motivation for study subjects to adopt any new lifestyle or dietary changes beyond those implemented well before the introduction of psyllium. Observational data has been shown to provide valid information, which is consistent with that observed in randomized, controlled trials ,18. The Failure of lipid-lowering by psyllium has also been demonstrated in twenty hypercholesterolemic children , in twenPublished studies include few normocholesterolemic subjects. Cholesterol reduction was observed in 7 normal men  and in 5A meta-analysis of 17 studies of patients with hypercholesterolemia has suggested a small but significant cholesterol-lowering effect of psyllium . All of Several factors may contribute to the difference between our observations and those of others. A meta-analysis has demonstrated that the initial level of cholesterol was highly predictive of the subsequent reduction of cholesterol by oat bran . A greatThe small increase in the weight of subjects is believed to be have resulted from reduced physical activity. In a meta-analysis of the effect of weight reduction on lipids, predominantly through dietary change, a reduction in total cholesterol of 0.05 mmol/L and of 0.02 mmol/L in LDL cholesterol per kilogram of weight lost was identified . DietaryA small cholesterol-lowering effect of psyllium appears to occur in hypercholesterolemic individuals, at least in men and possibly postmenopausal women. The notion of a benefit accruing to the general population requires additional study. The promotion of foods containing psyllium as reducing the risk of heart disease for the population at large  may be pThe timing of psyllium administration had no effect on cholesterol-lowering and, in fact, no cholesterol-lowering was observed. Conclusions regarding the effectiveness of psyllium for the prevention of heart disease in the population at large may be premature.The authors declare that they have no competing interests.GVR carried out the study design, data review and writing. EAS carried out the study design and data review. RB carried out the study design, data review and statistical analysis. ALE carried out the study design and data review.


One of the cornerstones of immune system function is movement. When word spreads that a virus has entered the body, chemical signals tell lymphocytes to proliferate and travel to the site of infection. Efforts to combat HIV have focused on understanding how the virus disrupts this immune response in the hopes of developing drugs to block its replication as well as vaccines to control the virus itself. Toward this end, scientists are investigating how each of the virus's nine genes—which all appear to have multiple functions—contribute to HIV infection.When HIV infects a cell, viral enzymes copy its RNA genes into DNA, which can then invade the infected cell's chromosomes. The viral DNA might lay dormant or it might use the cell to reproduce more viruses, which go on to infect other cells. The course of infection is determined by interactions between circulating T cells and antigen-presenting cells (cells that present evidence of infection), like macrophages, which may unwittingly aid the virus by transferring it to the T cells. Macrophages, for example, produce proteins that tell T cells to come check out an infection.A viral protein called Nef sparked intensive research after observations that patients with a rare strain of HIV lacking Nef took a very long time to develop AIDS symptoms. Nef has been linked to molecules involved in macrophage- and other antigen-signaling pathways and may use the molecules to appropriate these pathways for its own ends—enhancing virulence by facilitating viral replication. How Nef does this is not entirely clear. Now Jacek Skowronski and his colleagues at Cold Spring Harbor Laboratory in New York have identified the key molecules that Nef enlists to coopt the signaling machinery of immune cells.To understand how this might happen, biochemically speaking, Skowronski's lab first needed to determine which molecules Nef associates with. An adaptor protein, Nef does not directly catalyze reactions, but binds to enzymes that do. The researchers identified two proteins, DOCK2 and ELMO1, that form a complex with Nef. DOCK2 regulates enzymes, called Rac1 and Rac2, that are required for normal lymphocyte migration and antigen-specific responses. ELMO1 has also been shown to help DOCK2 activate Rac. Because DOCK2 activates Rac as part of two different signaling pathways—one activated by the T cell receptor, which mediates T cell activation, and one by a chemokine receptor, which controls T cell migration—the researchers investigated whether Nef could affect these important pathways by modulating Rac activity. They found that Nef in fact activates Rac by binding to the DOCK2–ELMO1 complex. And they went on to show that HIV uses these components of the chemokine receptor pathway to disrupt T cell migration. To generate an effective immune response, it is crucial that T cells travel to sites within lymphatic tissues where they interact with other lymphocytes. By inhibiting T cell migration, the researchers propose, Nef prevents these critical interactions, thereby providing a mechanism for stifling the immune response.These results, the authors argue, provide the biochemical evidence that Nef targets a protein “switch” that can interfere with important aspects of T cell function. In this way, Nef subverts the immune response pathways controlled by receptors on the surface of T cells to effectively disarm the immune system and turn T cells into viral replication factories. Understanding how Nef interacts with these proteins to spread infection could lay the foundation for valuable new therapies aimed at inhibiting and arresting HIV infection by blocking Nef-mediated effects.


Multicellular organisms contain a complete set of genes in nearly all of their cells, each cell harboring the potential to make nearly any protein in their genome. The same holds true for a single-celled bacterium or yeast. Yet a cell activates only a fraction of its genes at any given time, calling on a number of different mechanisms to activate the right genes at the right time. To metabolize sugar, for example, a cell needs to synthesize proteins involved in sugar metabolism, not protein repair, and vice versa. In a new study, Jason Brickner and Peter Walter report a mechanism for gene activation that depends on shuttling DNA to a particular location within the nucleus.In organisms whose cells have nuclei (eukaryotes), genomes lie within the nucleus  but also interact with the inner nuclear membrane. Transcription factors activate gene expression by binding to a promoter sequence in the gene's DNA. The physical structure of DNA—which is packaged with proteins into chromatin—affects gene expression by controlling access to DNA. Where chromatin exists in the nucleus also influences gene expression. Heterochromatin—stretches of highly condensed chromatin—typically lines the nuclear periphery, and genes bundled into heterochromatin are typically silent. Active transcription generally occurs in the less condensed euchromatic regions. But since euchromatic regions are also silenced when they associate with heterochromatin along the membrane, it is thought that delivering chromatin to the nuclear periphery regulates transcriptional repression. Brickner and Walter, however, found evidence of the opposite effect—recruiting genes to the nuclear periphery can promote their activation—suggesting that nuclear membrane recruitment plays a much broader role than previously suspected in gene regulation.INO1, which encodes inositol 1-phosphate synthase, an enzyme involved in phospholipid (fat) biosynthesis. INO1 is also a target gene of the “unfolded protein response,” which is triggered when unfolded proteins accumulate in the endoplasmic reticulum, a subcellular organelle where secreted proteins are folded. The INO1 gene contains a regulatory element  within its promoter region that responds to inositol availability. Genes under the control of this element are transcriptionally repressed by a repressor, Opi1, and activated by two transcription factors, Ino2 and Ino4. The presence of unfolded proteins sets off a chain of events to relieve Opi1 repression and allow activation of INO1.To explore the consequences of chromatin location, the authors focused on a yeast gene called INO1 promoter. Opi1 associates with the chromatin, restricting the INO1 locus to the nucleoplasm and repressing transcription. Induction of the unfolded protein response bumps Opi1 off the chromatin and, with Opi1 out of the way, INO1 travels to the membrane and transcription proceeds. Crucially, the authors show that artificial recruitment of INO1 to the nuclear membrane can be enough to activate the gene. There are several mechanistic aspects of this model to figure out still, but Brickner and Walter argue that for INO1, gene recruitment to the nuclear membrane promotes its activation. In light of other recent work, this phenomenon may be emerging as a more general mechanism for regulating eukaryotic gene expression.Through a series of genetic and biochemical studies, Bricker and Walter show that Ino2 and Ino4 are always bound to the


The development of enzyme replacement therapy for Gaucher disease was a triumph of translational medicine. What were the key steps in its development? What are the controversies surrounding its use? Gaucher disease is the most common lysosomal storage disorder . A deficGaucher disease is an inherited metabolic disorder in which harmful quantities of a fatty substance called glucocerebroside accumulate in the spleen, liver, lungs, bone marrow, and, in rare cases, the brain. There are three common forms.Type 1 is the most common. Clinical features include easy bruising, anemia, low blood platelets, enlargement of the liver and spleen, bone disease, and, in some instances, lung impairment. There are no signs of brain involvement. Problems may begin early in life, be delayed until adulthood, or not occur at all.In type 2, liver and spleen enlargement are apparent by three months of age, and there is extensive and progressive brain damage. These patients usually die by two years of age.In type 3, liver and spleen enlargement is variable, and signs of brain involvement, such as seizures, become apparent gradually.Until 1990, treatment consisted only of palliative measures such as splenectomy and hip replacement. The development of enzyme replacement therapy for Gaucher disease, that is, exogenous administration of the missing enzyme, is a triumph of translational medicine. At the same time, powerful commercial interests may have been influential in physicians adopting a high-dose rather than a low-dose treatment schedule. Moreover, the high cost of enzyme replacement therapy forces us to consider what society can afford in the way of palliative treatments for very rare diseases.The possibility that the therapeutic replacement of enzymes missing from lysosomes could be achieved was first raised by de Duve forty years ago when he wrote: “Any substance that is taken up intracellularly by an endocytic process is likely to end up within lysosomes. This obviously opens up many possibilities for interaction, including replacement therapy” .Type 1 Gaucher disease, the most common type, seems a particularly suitable target for enzyme replacement therapy because of the lack of central nervous system involvement . By the 1970s, the underlying enzyme deficiency had been identified, and methods had been developed to purify the enzyme from human placenta in a high state of purity. Three groups of investigators then attempted to treat the disease by infusing exogenous enzyme.In the United States, at the National Institutes of Health in Bethesda, Maryland, the unaltered enzyme was infused directly into the venous circulation ; at CityThe needed conceptual breakthrough was provided by the identification of a mannose receptor on macrophages and the suggestion that this might prove useful in replacement therapy for Gaucher disease . This leThe first study of commercially produced mannose-enriched glucocerebrosidase was carried out in Bethesda, Maryland, on only 12 patients, presumably because of a limited supply of the enzyme . Given tThe enzyme was promptly approved and marketed. Since only a single dose had been tested, this was the dose that most physicians administered in clinical practice. But the preparation was extremely costly—about US$4.00 per unit. At the dose used in the pivotal trial, a 70-kg patient would receive enzyme costing US$16,800 every two weeks.But was the large dose given actually the dose required? There were no data, and many physicians were unwilling to give less than the dose that had been used in the pivotal trial. Moreover, since most physicians took care of only one or at most two patients with the disease, they were not in a position to perform a dose-ranging study. And industry had no interest in supporting studies to show that a lower dose yielded equivalent results.But clinical trials carried out in our National Institutes of Health–sponsored General Clinical Research Center quickly established that a quarter of the dose given at more frequent intervals was fully effective . By 2000Recent “consensus recommendations,” which were supported in part by the Genzyme Corporation, the manufacturers of recombinant human glucocerebrosidase (imiglucerase, brand name Cerezyme), suggest that children be given an initial dose of 30 to 60 units every two weeks . But theIt is often assumed that patients with severe disease require larger doses of enzyme than those with mild disease, but a meta-analysis based on liver size or spleen size made it clear that this is not the case  12]. La. La12]. The response of enlarged viscera to enzyme infusion is much more rapid than the response of bones. In one early study, the large dose used in the pivotal trial was given for up to four years to patients with bone disease, and although the response was slow, gradual improvement occurred . Strangec.1226 C → G (N370S) mutation never come to medical attention [The severity of Gaucher disease is very variable. We have estimated that some 60% of patients homozygous for the common ttention . Accordittention ,17. WhatEvaluating dose–response relationships in patients with Gaucher disease has been difficult for several reasons. The number of new patients requiring therapy is relatively small, and the Genzyme Corporation has done little to encourage the performance of dose–response studies, making it difficult to enroll patients. But beyond that, the response of patients to any dose is variable. Some authors have suggested that this may be due to individual differences in dose requirements—that some patients are relatively resistant and require a large dose, while others do well on a small dose . This isThe quality of life for patients with Gaucher disease has been greatly improved by the development of enzyme replacement therapy. Manufacturing and selling the enzyme has also been enormously profitable for industry. This profitability has served as a stimulus for the development of enzyme replacement treatments for diseases less common and generally less responsive to treatment than Gaucher disease. Given the small target population, these treatments are enormously costly on a per-patient basis. Treatments for Fabry disease and Hurler-Scheie disease  are already licensed, and others are on the way ,21,22. T


Dementia is a chronic illness associated with a progressive loss of cognitive and intellectual abilities, such as memory, judgment and abstract thinking.The objective of this study was to assess the health utilities of patients with dementia in Europe and identify the key factors influencing their Health-Related Quality of Life (HRQol).This study used cross-sectional data from the Odense study; a Danish cohort of patients aged 65–84 living in Odense, Denmark. A total of 244 patients with mild to severe dementia were interviewed together with a caregiver about their health status and activities of daily living (ADL). Alzheimer's disease was diagnosed according to the NINCDS-ADRDA criteria for probable dementia. Vascular dementia and other types of dementia were diagnosed according to the DSM-IIIR criteria. Severity of dementia was defined by score intervals on the Mini Mental State Examination score: mild (MMSE 20–30), moderate (MMSE 10–19), and severe (MMSE 0–9). Based on the ADL information, the patients' dependency level was defined as either dependent or independent. Questions from the Odense Study were mapped into each of the five dimensions of the EQ-5D in order to assess patients' HRQol. Danish EQ-5D social tariffs were used to value patients' HRQol.A regression analysis of EQ-5D values was conducted with backward selection on gender, age, severity, ADL level and setting in order to determine the main factor influencing HRQoL.The EQ-5D weight in patients independent upon others in ADL was 0.641 (95% CI: [0.612–0.669]), and in those dependent upon others was 0.343 (95% CI: [0.251–0.436]).Dependency upon others to perform ADL was the main factor affecting HRQoL. Dementia is a chronic illness associated with a progressive loss of cognitive and intellectual abilities, such as memory, judgment and abstract thinking. Cognitive disabilities are those that impact an individual's ability to access, process, or remember information. People with profound cognitive disability will need assistance with nearly every aspect of daily living. The most visible manifestation of dementia is the progressive inability – proportional to the severity of the disease – to perform activities of daily living (ADL) and the subsequent loss of independence . ProgresMeasuring the QoL of patients suffering from dementia can take several forms. Firstly, QoL can be measured using generic health indices like the other disease specific measures. Recently several scales have been developed and validated specifically for dementia patients such as the Quality of Life-Alzheimer's Disease (QOL-AD). Another alternative to assess QoL is to use utility measurements, which are preference-based . PrefereHealth utilities have already been measured in AD in the US and Canada using the Health Utility Index (HUI) . In the Based on data collected alongside an epidemiological study conducted in Odense Denmark, we attempted to assess the health utilities of patients with dementia and identify the key factors influencing their HRQoL.Data were derived from the Odense study, an epidemiological survey in which the objective was to estimate the prevalence and incidence of dementia in Denmark ,11 In thDemented patients were classified by type of dementia and by severity of dementia. Alzheimer's disease (AD) was diagnosed according to the NINCDS-ADRDA criteria for probable dementia . VasculaAll interviews were conducted by a certified nurse in the patient's home., Patient's and caregiver's socio-economic and socio-demographic status as well patients' health status and ADL were recorded. In the event that a relative was not present during the interview, a professional caregiver verified information provided by the patient.Each interview included the following information:- sociodemographic questions (age, gender, setting).- activity of daily living (ADL) questionnaire using 7 items describing patients' ability to perform physical activities  and psychosocial activities (activities in the home and hobbies inside and outside of the home). Each activity was scored using a four-point Likert scale anchored at the ends with 1 = "Unable to perform the activity" and 4 = "Perform the activity without help from others". The physical ADL ranged between 4 (worst state) and 16 (best state), while the psychosocial ADL scored between 3 (worst state) and 12 (best state) [- Questions mapped into each of the five dimensions of the EQ-5D: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression as presented in the Table For the mobility dimension of the EuroQol instrument, we assumed that patients that were able to walk without assistance from others had no problems in performing this activity, whereas patients who were unable to walk unassisted were classified as confined to bed. Patients that needed help from others were classified as having some mobility problems.Two questions from the ADL instrument in the Odense Study were used to classify patients on the EuroQol personal care dimension. Patients that performed both activities without help from others were classified as having no problems on this dimension. Patients in need of help with either personal care or dressing or both were classified as having some problems. Only patients unable to wash and dress without help from others were classified as such on the EuroQol instrument.The patient's ability to carry out hobbies in the home was used as a proxy for their ability to perform usual activities.For the pain/discomfort dimension of the EuroQol instrument, it was assumed that patient assessment of their own health status covered this dimension. Therefore, if they found their health status to be very good they were classified as having no pain or discomfort. A good or fair assessment was categorised as having moderate pain or discomfort, whereas a poor assessment was assumed to correspond to extreme pain or discomfort.In the Odense Study, patients stated how often they experienced emotional problems, whereas the health state being described by the EuroQol instrument refers to the patient's health at the time of filling in the instrument. Thus, the questions in the Odense Study included an aspect of time that the EuroQol does not cover. To overcome this, it was assumed that the occurrence of emotional problems converts to the degree of anxiety or depressions. That is, patients that never experience emotional problems were assumed not to be anxious or depressed, whereas patients that sometimes or often experience problems converted to moderate or extreme anxiety or depression, respectively.The procedure of mapping returned a five-digit code, where the first digit referred to the patient's mobility level; the second to the patient's level on personal care; and so forth. This five-digit code described a health state for which we looked up the HRQoL utility weight in a table of EQ-5D tariffs. The EQ-5D tariffs take values between zero and one, where zero is the worst imaginable health status, and one is the best imaginable health status. We used Danish EQ-5D tariffs from a survey based on the time trade-off technique .Based on their cognitive and functional scores patients were classified by severity and dependency level.The severity of a patient's dementia was defined by score intervals on the MMSE . Those sPatients were classified by their ability to perform physical and psychosocial activities of daily living (ADL) This resulted in a classification of either dependent or independent . A binarOne cluster included patients with low scores on both the physical and psychosocial ADL scales. As low scores on both instruments meant that patients required help from others in performing the activities in question, they were classified as "Dependent". The other cluster included patients with high scores on both ADL scales and they were classified as "Independent". As these were composite criteria, the characteristics of the two groups of dependency were analysed.After analysing the descriptive results of the EQ-5D scores, we performed a regression analysis of EQ-5D scores on sociodemographic and clinical characteristics. Sociodemographic characteristics included gender, age and setting  and clinical characteristics took into account the level of severity (Mild, Moderate, and Severe), the type of dementia (AD, vascular or other) and ADL status (independent or dependent).The regression analysis was performed with backward selection (level 5%) in order to determine the main factors influencing QoL.Because of heteroscedasticity, we estimated the heteroscedasticity consistent covariance matrix, which was used to calculate test statistics for the coefficients.Observations with missing data were automatically excluded from the analyses. That is, observations with insufficient information to establish a EQ-5D weight, e.g. that information was lacking to determine a patient's mobility level on the EQ-5D instrument.Table Tables Table Table Patients dependent upon others to perform activities of daily living clearly had a lower QoL than independent patients. The QoL of independent patients suffering from dementia as assessed by their capacity to perform activities of daily living was 0.641  whereas the QoL of dependent patients for the same assessment was 0.343 (95% CI: [0.251 – 0.436]). Severity of dementia and setting has no statistically significant impact on QoL.For the first time, this study provides health utilities for patients with dementia in Denmark. This study has shown that the factor that most affects the HRQoL of a patient with dementia is their dependency status as defined based by their ability to perform activities of daily living. The type of dementia doesn't seem to have a great an influence on patient's HRQoL, and severity does not appear to discriminate significantly between health utilities. However, due to missing data – particularly among patients with severe dementia – caution must be exercised when interpreting the results.In the utility results previously measured by Neumann et al.  using thAs the EQ-5D values were estimated based on mapped questions, it raises the possibility of quotation bias and goodness of fit. Also, both patients and caregivers answered questions. Yet, with AD – and especially when patients are severely demented – it is impossible to collect non-proxy measurements in the later stages. The same methodology was performed in previous evaluations without knowing the impact of the difference between caregivers' and patients' perceptions.A particular strength of this study was that all data have been collected in conjunction with an epidemiological study wherein patients with dementia had been examined carefully and dementia criteria were explicitly stated.Measuring HRQoL is as important as measuring disease severity, progression, symptom response, cognition and behavioural disturbance when assessing the impact of disease and determining proper intervention in the treatment and management of dementia. However, HRQoL is difficult to assess in a disease such as dementia for which patients suffer from cognitive disabilities. Based on study results and as previously shown by Kurz et al. , dependeADL Activities of Daily LivingEQ-5D EuroQol – Five Dimension ScaleEuroQol EuroQol Scalerd editionDSM-IIIR Diagnostic and Statistical Manual of Mental Disorders 3HRQol Health-Related Quality of LifeMMSE Mini Mental State ExaminationQoL Quality of LifeSAS Statistical Analytical SoftwareCKA is principal author and responsible for quality control. K W-J provided mapping of the questions from the Odense Study into the five dimensions of the EQ-5D. AL and KA provided data analysis and data analyses of the Odense database. P K-S provided access to the Odense database.


Celiac artery stenosis (CAS) may be caused by atherosclerotic degeneration or compression exerted by the arched ligament of the diaphragm. Mitral valve prolapse (MVP) is the most common valvular disorder. There are no reports on an association between CAS and MVP.1560 (41%) out of 3780 consecutive patients undergoing echocardiographic assessment of MVP, had Doppler sonography of the celiac tract to detect CAS.CAS was found in 57 (3.7%) subjects  none of whom complained of symptoms related to visceral ischemia. MVP was observed in 47 (82.4%) subjects with and 118 (7.9%) without CAS (p < 0.001). The agreement between MVP and CAS was 39% (95% CI 32–49%). PSV (Peak Systolic Velocity) was the only predictor of CAS in MPV patients (OR 0.24, 95% CI 0.08–0.69) as selected in a multivariate logistic model.CAS and MVP seem to be significantly associated in patients undergoing consecutive ultrasonographic screening. Celiac artery stenosis (CAS) may be caused by atherosclerotic degeneration, as observed in different vascular districts, or by extrinsic compression (ECCA) usually exerted by an abnormally developed arched ligament of the diaphragm -7. ECCA Mitral Valve Prolapse (MVP) is the most common valvular disorder, with a prevalence of about 6–7% in the general population ,9. It coThe association between MVP and CAS has not been extensively investigated. Accordingly, this study was aimed at verifying this hypothesis based on a possible common origin of the two conditions, i.e. the abnormal development of connective tissue causing both ECCA exerted by the arched ligament of the diaphragm and exuberance of valvular mitral tissue.The study population consisted of 1560 out of 3780 (41%) consecutive patients undergoing echocardiographic assessment of MVP, who also had celiac artery Doppler ultrasound performed between November 1999 to September 2004.MVP was defined as clear-cut billowing of one or both mitral leaflets across the mitral annular plane in 2-dimensional parasternal long axis recording or >2 mm late systolic posterior displacement of mitral leaflets by M-mode. A >4 mm displacement defined a moderate-severe prolapse.Ultrasonography (HP Sonos 1000, Tohsiba Corevision, Esaote Caris, Esaote Caris plus, Kontron Iris) was performed without intestinal preparation to limit meteorism. The digestive phase was taken into account, because it may influence visceral arterial flow. The evaluation of arterial flow in the celiac tract was recorded by continuous Doppler (CW) and, whenever possible, with the aid of the color-Doppler signal. No corrections of flow velocity by evaluation of the cosine of the insonorisation axis and the axis of the vessel were used: in this way, flow velocity can never be overestimated. The Doppler signal was collected in apnea during inspiration. During expiration, an increase in the compression of the celiac tripod by the arched ligament occurs in the cases of CAS caused by ECCA, with concurrent increase in flow velocity with respect to the velocity during inspiration . An exam45678CAS was defined as severe in case of Peak Systolic Velocity (PSV) flow velocity in the upper celiac tract greater than 2.0 metres/second ,16 and EContinuous variables are expressed as means ± 1 standard deviation (SD). Differences between groups were compared using Student's t-test and chi-square test, as appropriate. Association between CAS and MPV was performed using the Kappa statistics, estimated with 95% confidence interval.Univariate odds ratio (OR) along with their corresponding 95% confidence intervals were computed for describing association of clinical variables with MPV in CAS patients, using a logistic regression model. Selection of variables significantly associated with MPV in CAS patients was made using a multivariate logistic model. Selection criterion was the Akaike Information Criterion, applied backward to the multivariate logistic model. The statistical significance was settled at a p value < 0.05. The R (release 1.9) statistical package and the Harrell's Design and Hmisc libraries were used for analysis.The incidence of MVP in patients with (10.6%) and without (9.3%) assessment of CAS did not differ significantly.Among those undergoing both examinations, CAS was found in 57/1560 (3.6%) patients. The clinical characteristics of patients with and without CAS are reported in Table No patient with CAS was complaining of symptoms related to visceral ischemia, i.e. abdominal or gastric pain in concurrence with food ingestion.Thirteen (22.8 %) of the 57 subjects with CAS were suffering from cardiovascular disorder. In particular, a macrovascular atherosclerotic disorder  was ascertained in 7 subjects , whilst no sign of macrovascular atherosclerosis was found in the remaining 50 subjects .In patients with CAS, factors associated with MPV are age, sex, PSV and BMI. At multivariate analysis only PSV resulted as an independent factor associated with MPV (OR 0.24 95% CI 0.08 to 0.69).The incidence of CAS is not clearly established, the majority of the literature consisting of isolated reports -21. SurpThe incidence of CAS and MVP in the present study dealing with an unselected population was 3.7% and 10.6%, respectively. In addition, this is the first report, to our knowledge, to demonstrate a strong association between the two conditions.CAS may be caused by ECCA or atherosclerosis. Unfortunately, the ultrasound technique has not enough resolution to allow an etiological discrimination that may be difficult to get even with angiographic examination . HoweverThe results of this study demonstrate that CAS is a relatively frequent finding among patients undergoing Doppler sonography of the celiac artery and is frequently associated to MVP. On the basis of these findings, further investigations are warranted aimed at determining the exact incidence of ECCA associated with MVP, the family distribution of the association between MVP and ECCA, or the prognostic implication of ECCA in subjects with MVP. Additionally, genetic studies could be advisable in subjects presenting with MVP associated to ECCA.CAS Celiac Artery StenosisMVP Mitral Valve ProlapseECCA Extrinsic Compression of Celiac ArteryCACS Celiac Artery Compression SyndromePSV Peak Systolic VelocityEDV End Diastolic Velocity