The Generalized Hidden Markov Model (GHMM) has proven a useful framework for the task of computational gene prediction in eukaryotic genomes, due to its flexibility and probabilistic underpinnings. As the focus of the gene finding community shifts toward the use of homology information to improve prediction accuracy, extensions to the basic GHMM model are being explored as possible ways to integrate this homology information into the prediction process. Particularly prominent among these extensions are those techniques which call for the simultaneous prediction of genes in two or more genomes at once, thereby increasing significantly the computational cost of prediction and highlighting the importance of speed and memory efficiency in the implementation of the underlying GHMM algorithms. Unfortunately, the task of implementing an efficient GHMM-based gene finder is already a nontrivial one, and it can be expected that this task will only grow more onerous as our models increase in complexity.As a first step toward addressing the implementation challenges of these next-generation systems, we describe in detail two software architectures for GHMM-based gene finders, one comprising the common array-based approach, and the other a highly optimized algorithm which requires significantly less memory while achieving virtually identical speed. We then show how both of these architectures can be accelerated by a factor of two by optimizing their content sensors. We finish with a brief illustration of the impact these optimizations have had on the feasibility of our new homology-based gene finder, TWAIN.In describing a number of optimizations for GHMM-based gene finders and making available two complete open-source software systems embodying these methods, it is our hope that others will be more enabled to explore promising extensions to the GHMM framework, thereby improving the state-of-the-art in gene prediction techniques. A number of tructure -6, and nNotwithstanding our eagerness to utilize this expected flood of genomic data, methods have yet to be demonstrated which can perform such large-scale parallel analyses without requiring inordinate computational resources. In the case of Generalized Pair HMMs (GPHMMs), for example, the only systems in existence of which we are familiar make a number of relatively restrictive assumptions in order to reduce the computational complexity of the problem to a more tolerable level ,8,15. Yesemi-Markov model) generalizes this scenario by allowing individual states to emit strings of symbols rather than one symbol at a time [A Hidden Markov Model (HMM) is a state-based generative model which transitions stochastically from state to state, emitting a single symbol from each state. A GHMM  and their corresponding exon-intron structures [Eukaryotic gene prediction entails the parsing of a DNA sequence into a set of putative CDSs (ructures . Thus, tATGΣ*(GTΣ*AG)*Σ*Γ)*Σ*,     (1)Σ* have been underlined for clarity, and where Γ = {TAG,TGA,TAA} represents a stop codon. . An additional constraint not explicitly represented in Formula 1 is that the number of non-intron nucleotides between the start and stop codons of a single gene must be a multiple of three, and furthermore, if these nucleotides are aggregated into a discrete number of nonoverlapping triples, or codons, then none of these codons must be a stop codon, other than the stop codon which terminates the gene. Note that the Σ* terms in Formula 1 permit the occurrence of pseudo-signals – e.g., an ATG triple which does not comprise a true start codon. Gene prediction with a GHMM thus entails parsing with an ambiguous stochastic regular grammar; the challenge is to find the most probable parse of an input sequence, given the GHMM parameters and the input sequence.where the decoding) problem can be solved with the well-known Viterbi algorithm, a dynamic programming algorithm with run time linear in the sequence length (for a fixed number of states) [In the case of simple Hidden Markov Models, this optimal parsing (or  states) . A modif states) , resultiparse of the sequence consisting of a series of states qi and state durations di, 0≤i≤n, with each state qi emitting subsequence Si of length di, so that the concatenation of all S0S1...Sn produces the complete output sequence S (but note that states q0 and qn are silent, producing no output). Pe(Si|qi,di) denotes the probability that state qi emits subsequence Si, given duration di; Pt(qi|qi-1) is the probability that the GHMM transitions from state qi-1 to state qi; and Pd(di|qi) is the probability that state qi has duration di. The argmax is over all parses of the DNA sequence into well-formed exon-intron structures; hence, the problem is one of finding the parse which maximizes the product in Equation 2.where φ is a Prefix Sum Arrays (PSA) approach, since the values in the aforementioned arrays represent cumulative scores for prefixes of the sequence.The approach commonly used in GHMM gene finders for evaluating Equation 2 is to allocate several arrays, one per variable-length feature state, and to evaluate the arrays left-to-right along the length of the input sequence according to a dynamic programming algorithm, which we will detail below. We refer to this approach as the Without loss of generality, let us consider the GHMM structure depicted in Figure sng = single exon, Einit = initial exon, Eint = internal exon, Efin = final exon). This model generates genes only on the forward strand of the DNA; to obtain a double-stranded model one can simply mirror the structure and link the forward and reverse models through a single merged intergenic state.The diamonds denote the states for fixed length features (ATG = start codon, TAG = stop codon, GT = donor, AG = acceptor) and the circles denote states for variable length features  or some other fixed-length model (e.g., a WAM, WWAM, MDD tree, etc.) [content sensor, such as a Markov chain (MC) or an Interpolated Markov Model (IMM) [Associated with each diamond state is a e, etc.) , and witel (IMM) .For the purposes of illustration, we will consider only the simplest of each model type, since the more complex model types commonly in use can in general be handled generically within the GHMM framework. The simplest fixed-length model is the WMM:xh..xh+n denotes the subsequence currently within a sliding (n + 1)-element window, called the context window, and P(x|θ[i]) denotes the probability of nucleotide x occurring at position i within the window, for model θ. In practice, all of the probabilities described in all of these models are represented in log space , so that products of probabilities can be replaced with sums of their logs.where nth-order Markov chain M for state qi would evaluate the probability P(Si|qi,di) of a putative feature Si according to:The simplest variable-length model used in practice is the Markov chain. An xj is the jth nucleotide in the sequence of the putative feature, di is the length of that feature, and PM(xj|xj-n..xj-1) is the probability of nucleotide xj conditional on the identities of its n predecessor nucleotides, according to content model M. As with the fixed-length model described above, this computation is typically done in log space.where In scoring the signals and content regions of a putative gene parse, it will be important for us to carefully differentiate between the nucleotides which are scored by a signal sensor and those which are scored by a content sensor in a putative parse. As shown in Figure The first step of the PSA algorithm is to compute a prefix sum array for each content sensor. For noncoding states (introns and intergenic) this can be formalized as shown in Figure phase 0, phase 1, and phase 2. We employ three Markov chains, M0, M1, and M2, corresponding to these three phases. Together, these three chains constitute a three-periodic Markov chain, M{0,1,2}. Exon states then require three arrays, each of which can be initialized using the procedure shown in Figure In the case of exon states, it is important to capture the different statistical properties present in the three codon positions, referred to as i, 0, αi, 1, and αi, 2 for an exon state qi as follows:In this way, we can initialize the three arrays αfor ω ← 0 to 2 doi,ω, S, M{0, 1, 2},ω) ;   init_phased.The individual chains RS = log P(xh..xh+n-1|θ), where h is the position of the beginning of the window and n is the window length. If signal thresholding is desired, RS can be compared to a pre-specified threshold and those locations scoring below the threshold can be eliminated from consideration as putative signals.Once the prefix sum arrays have been initialized for all variable-duration states, we make another left-to-right pass over the input sequence to look for all possible matches to the fixed-length states, via the signal sensors. In general, a signal sensor θ models the statistical biases of nucleotides at fixed positions surrounding a signal of a given type, such as a start codon. Whenever an appropriate consensus is encountered (such as ATG for the start codon sensor), the signal sensor's fixed-length window is superimposed around the putative signal  and evaluated to produce a logarithmic signal score signal queue for consideration later as possible predecessors of subsequent signals in a putative gene model. As each new signal is encountered, the optimal predecessors for the signal are selected from among the current contents of the signal queues, using a scoring function described below. In the example (forward strand) GHMM depicted in Figure The remaining candidates for signals of each type are then inserted into a type-specific ATG→TAGATG→GTGT→AGAG→GTAG→TAGTAG→ATGPt(qi|qi-1), which is included in the scoring of a possible predecessor; this probability can be accessed quickly by indexing into a two-dimensional array. The logarithmic transition score will be denoted RT(qi-1,qi) = log Pt(qi|qi-1).Associated with each of these patterns is a transition probability, Pd(di|qi) for distance (=duration) di and signal type (=state) qi. This probability can usually be obtained relatively quickly, depending on the representation of the duration distributions. If the distributions have been fitted to a curve with a simple algebraic formula, then evaluation of the formula is typically a constant-time operation. If a histogram is instead maintained, then a binary search is typically required to find the histogram interval containing the given distance. We denote the logarithmic duration score RD(qi,qj) = log Pd(di|qi:j) where di is the length of the content region delimited by signals qi and qj, and qi:j is the variable-length state corresponding to that content region.The distance from a prospective predecessor to the current signal is also included in the evaluation in the form of Pe(Si|qi,di). For a fixed-length state, this is simply the score produced by the signal sensor. For a variable-length state qi, Pe can be evaluated very quickly by indexing into the prefix sum array αi,γ for state qi and phase γ at the appropriate indices for the two signals and simply performing subtraction:Following Equation 2, the final component of the scoring function is the emission probability RC(spred,scur,ω) ← αi,γ [wpos(scur) - 1] - αi,γ [wpos(spred) + wlen(spred) - 1],     (5)wpos(s) is the 0-based position (within the full input sequence) of the first nucleotide in the context window for signal s, wlen(s) is the length of the context window for signal s, and spred and scur are the predecessor and current signals, respectively. In the case of coding features, γ is the phase of the array and ω = (γ + pos(scur))mod3 is the phase of scur, for pos(scur) the position of the leftmost consensus base of scur. For reverse-strand features, since the prefix sum arrays tabulate their sums from the right instead of the left, the subtraction must be reversed:where RC(spred,scur,ω) ← αi,γ[wpos(spred) + wlen(spred)] - αi,γ[wpos(scur)],     (6)L - pos(scur) - 1)mod3, for L the sequence length. For noncoding features, the phases can be ignored when computing RC, since there is only one array per noncoding state.and ω =  denotes the logarithmic inductive score for signal si in phase γi. For forward-strand coding features, the phases γi and γj are related by:for current signal i = (γj - Δ)mod3,     (8)γfor Δ the putative exon length, or, equivalently,j = (γi + Δ)mod3.     (9)γi = γj. For intergenic features, the phase will always be 0 for a forward strand signal and 2 for a reverse strand signal .These relations can be converted to the reverse strand by swapping + and -. For introns, γsj. This scoring function is evaluated for all appropriate predecessor signals, which are readily available in one or more queues, as mentioned above. A pointer called a trellis link is then created, pointing from the current signal to its optimal predecessor. In the case of those signals that can terminate an exon or an intron, three optimal predecessors must be retained, one for each phase. The inductive score RI(sj,γj) of the new signal sj is then initialized from the selected predecessor si as follows:The result of Equation 7 is the optimal predecessor for signal RI(sj, γj) ← RI(si, γj) + RT(si, sj) + RD(si, sj) + RC(si, sj, γj) + RS(sj),     (10)RS(sj) is the logarithmic score produced by the signal sensor for signal sj.where in-phase (i.e., in phase 0) stop codons are generally not permitted in coding exons; for this reason, any potential stop codon  will eclipse any preceding start codon or acceptor site (or, on the reverse strand, stop codon or donor site) in the corresponding phase. The algorithm shown in Figure A final step to be performed at each position along the input sequence is to drop from each queue any signal that has been rendered unreachable from all subsequent positions due to intervening stop codons. Except for the final stop codon of a gene, For the reverse strand, line 3 of eclipse should be changed to:mod3;ω ← (p-pos(s)-len(s) - 1) mod3 we mean the positive remainder after division of x by 3; in some programming languages (such as C/C++), a negative remainder may be returned, in which case 3 should be added to the result.where len(s) is the length of the consensus sequence for signal s (e.g., 3 for ATG). Note that by xA special case of eclipsing which is not handled by eclipse is that which occurs when a stop codon straddles an intron; this can be handled fairly simply by checking for such when considering each donor signal as a prospective predecessor for an acceptor signal (or vice-versa on the reverse strand). As each predecessor is evaluated, the bases immediately before the donor and immediately following the acceptor are examined, and if a stop codon is formed, the predecessor is no longer considered eligible for selection in the corresponding phase.As shown in Figure In the case of noncoding queues (e.g., those holding forward strand donors or stop codons, etc.), the assumption that noncoding features follow a geometric  distribution allows us to limit these queues to a single element (per phase), because once a noncoding predecessor has been selected in a given phase, no other noncoding predecessor which has already been compared to the selected predecessor can ever become more attractive by virtue of its transition probability , its duration probability (since the geometric distribution ensures that their respective duration probabilities decrease at the same rate), nor its sequence probability .L) for an input sequence of length L and a GHMM with a fixed number of states. It will be seen that the traceback procedure described below also requires time O(L), and so this is the time complexity of the PSA decoding algorithm for normal eukaryotic genomes .Because the coding and noncoding queues are effectively limited to a constant load (as argued above), the expected processing time at each nucleotide is O(1) in practice and therefore the entire algorithm up to this point requires time O must be instantiated at either terminus of the sequence . Those at the left terminus will have been entered into the appropriate queues at the very start of the algorithm as prospective targets for the first trellis links (and having inductive scores RI = 0), and those at the right terminus are the last signals to be evaluated and linked into the trellis. The highest scoring of these right terminal anchor signals is selected (in its highest-scoring phase) as the starting point for the traceback procedure. Traceback consists merely of following the trellis links backward while adjusting for phase changes across exons, as shown in Figure Once the end of the sequence is reached, the optimal parse φ can be reconstructed by tracing back through the trellis links. In order for this to be done, a set of virtual, Modifications to Figure O(L|Q|) for sequence length L and variable-duration state set Q. If, for example, array elements are 8-byte double-precision floating point numbers, then the GHMM depicted in Figure It should be clear from the foregoing that the space requirements of the PSA decoding algorithm are The memory requirements can be reduced in several ways. First, Markov chains can be shared by similar states. For example, the intron and intergenic states can share a single Markov chain trained on pooled noncoding DNA, and all the exon states can use the same three-periodic Markov chain trained on pooled coding DNA. To our knowledge, the extent to which this optimization affects the accuracy of the resulting gene finder has not been systematically investigated, though it is commonly used in practice. Second, the models for exons can be modified so as to utilize likelihood ratios instead of probabilities. If the models for exons are re-parameterized to compute:and the noncoding models are modified to compute:L|Q|). An additional consideration is that the log-likelihood strategy makes unavailable (or at least inseparable) the raw coding and noncoding scores, which might be desired later for some unforeseen application.then the latter can be seen to be unnecessary, since it will always evaluate to 1. Such a modification is valid and will have no effect on the mathematical structure of the optimization problem given in Equation 2 as long as the denominator is evaluated using a Markov chain or other multiplicative model, since the effect of the denominator on inductive scores will then be constant across all possible predecessors for any given signal. Using such ratios allows us to skip the evaluation of all noncoding states, so that the number of prefix sum arrays required for a double-stranded version of the GHMM in Figure A third method of reducing the memory requirements is to eliminate the prefix sum arrays altogether, resulting in what we call the Dynamic Score Propagation (DSP) algorithm.L+|Q|), where the constant factor associated with the L term is small, reflecting only the number of signals per nucleotide emitted by the signal sensors, as well as the memory required to store the sequence itself.Informally, the DSP algorithm is similar to the PSA algorithm except that rather than storing all nucleotide scores for all content sensors in a set of prefix sum arrays, we instead store only the specific elements of those arrays that are needed for assessing prospective predecessors during the trellis formation. Associated with each signal is a "propagator" variable which represents the log probability of the highest-scoring partial parse up to and including this signal. As processing proceeds left-to-right along the sequence, these propagators are updated so as to extend these partial parses up to the current position. In this way, the inductive score of each signal is incrementally propagated up to each potential successor signal that is encountered during processing; when a signal is eclipsed in all phases by stop codons (i.e., removed from its respective queue), propagation of that signal's inductive score halts, since further updates would be useless beyond that point. Because no prefix sum arrays are allocated, and because the signal queues are effectively limited in size (as argued previously), the expected memory requirements of DSP will be seen to be O, the signal will have one propagator per queue, but it will be clear from the context to which propagator we refer. Each queue will also have a propagator associated with it, though for the sake of reducing ambiguity we will refer to these as accumulators and represent them with the symbol α. The purpose of the accumulators is to reduce the number of updates to individual signal propagators; otherwise, every signal propagator in every queue would need to be updated at every position in the input sequence. The accumulator for a given queue will accumulate additions to be made to the propagators of the signals currently in the queue. The update of signal propagators from their queue's accumulator is delayed as long as possible, as described below. Accumulator scores are initialized to zero, as are the propagator scores for the left terminus anchor signals; the general case of propagator initialization will be described shortly.Each signal Updating of a propagator π from an accumulator α is simple in the case of a noncoding queue:0≤ω≤2 π[ω] ← π[ω] + α[0].     (13)∀s associated with the propagator π, in order to synchronize the periodic association between phase and array index:For coding queues, the update must take into account the location of the signal 0≤ω≤2 π[ω] ← π[ω] + α[(ω - pos(s) - len(s))mod3],     (14)∀or, on the reverse strand:0≤ω≤2 π[ω] ← π[ω] + α[(ω + pos(s) + len(s))mod3].     (15)∀M, a coding accumulator can be updated according to the rule:Given a content sensor 0≤ω≤2 α[ω] ← α[ω] + log PM[(ω+f)mod3](xf),     (16)∀or, on the reverse strand:0≤ω≤2 α[ω] ← α[ω] + log PW[(ω-f)mod3](xf),     (17)∀f is the position of the current nucleotide xf, PM[ω](xf) is the probability assigned to xf by the content sensor M in phase ω, and W is the reverse-complementary model to M which computes the probability of its parameter on the opposite strand and taking contexts from the right rather than from the left. This update occurs once at each position along the input sequence. Use of f provides an absolute frame of reference when updating the accumulator. This is necessary because the accumulator for a queue has no intrinsic notion of phase: unlike an individual signal, a queue is not rooted at any particular location relative to the sequence.where th element of the accumulator must be updated:For noncoding queues, only the 0log PM(xf).     (18)α[0] ← α[0] + si denote the predecessor under consideration and sj the new signal. Denote by Δ the length of the putative exon. Then on the forward strand, we can compare predecessors with respect to phase ω via the scoring function RCI + RD + RT, where RD and RT are the duration and transition scores described earlier and RCI includes the content score and the inductive score from the previous signal:All that remains is to specify the rule for selecting an optimal predecessor and using it to initialize a new signal's propagator. We first consider new signals which terminate a putative exon. Let 0≤ω≤2 RCI(si,ω) ← πi[(ω - Δ)mod3].     (19)∀On the reverse strand we have:0≤ω≤2 RCI(si,ω) ← πi [(ω + Δ)mod3].     (20)∀For introns it is still necessary to separate the three phase-specific scores to avoid greedy behavior, though the phase does not change across an intron, so no Δ term is necessary:0≤ω≤2 RCI(si,ω) ← πi[ω].     (21)∀When the preceding feature is intergenic we need only refer to phase zero of the preceding stop codon:RCI(si,ω) ← πi[0],     (22)or, on the reverse strand, phase 2 of the preceding start codon (since the leftmost base of the reverse-strand start codon will reside in phase 2).RCI + RD + RT is selected with respect to a given phase ω, the appropriate element of the new signal's propagator can be initialized directly:Once an optimal predecessor with score j[ω] ← RCI(si,ω) + RD(si,sj) + RT(si,sj) + RS(sj),     (23)πRS(sj) = P(context(sj)|θj) is the score assigned to the context window of the new signal sj by the appropriate signal sensor θj. An exception to Equation 23 occurs when ω is not a valid phase for signal sj (e.g., phase 1 for a start codon), in which case we instead set πj[ω] to -∞.where One final complication arises from the fact that the algorithm, as we have presented it, does not permit adjacent signals in a prospective parse to have overlapping signal sensor windows; to allow such would be to permit double-counting of nucleotide probabilities, thereby biasing the probabilistic scoring function. It is a simple matter to reformulate the algorithm so that signal sensors score only the two or three consensus nucleotides of the signals under consideration; this would allow adjacent signals in a prospective parse to be as close as possible without actually overlapping (i.e., a single exon consisting of the sequence ATGTAG would be permitted, even if the start codon and stop codon context windows overlapped). However, doing so might be expected to decrease gene finder accuracy, for two reasons: (1) statistical biases occurring at fixed positions relative to signals of a given type can in general be better exploited by a signal sensor specifically trained on such positions than by a content sensor trained on data pooled from many positions at variable distances from the signal, and (2) in the case of Markov chains and Interpolated Markov Models, probability estimates for nucleotides immediately following a signal can be inadvertently conditioned on the few trailing nucleotides of the preceding feature (assuming the chain has a sufficiently high order), even though the models are typically not trained accordingly. For these reasons, we prefer to use signal sensors which impose a moderate margin around their respective signals, both to detect any biologically relevant biases which might exist within those margins, and to ensure that content sensors condition their probabilities only on nucleotides within the same feature.Given the foregoing, it is necessary to utilize a separate "holding queue" for signals which have recently been detected by their signal sensors but which have context windows still overlapping the current position in the DSP algorithm. The reason for this is that propagator updates via Equations 13–15 must not be applied to signals having context windows overlapping any nucleotides already accounted for in the accumulator scores, since to do so would be to double-count probabilities. It is therefore necessary to observe the following discipline.Gi there must be a separate holding queue, Hi. When a signal is instantiated by a signal sensor it is added to the appropriate Hi rather than to Gi. As the algorithm advances along the sequence, at each new position we must examine the contents of each holding queue Hi to identify any signal having a context window which has now passed completely to the left of the current position. If one or more such signals are identified, then we first update the propagators of all the signals in the main queue Gi using Equations 13–15, then zero-out the values of the accumulator αi for that queue, and then allow the recently passed signals to graduate from Hi to Gi. Observe that at this point all the signals in Gi have in their propagators scores which have effectively been propagated up to the same point in the sequence, and that point is immediately left of the current position; this invariant is necessary for the proper operation of the algorithm. All content sensors are then evaluated at the current position and their resulting single-nucleotide scores are used to update the accumulators for their respective queues. Finally, whenever it becomes necessary to evaluate the signals in some queue Gi as possible predecessors of a new signal, we must first update the propagators of all the elements of Gi as described above, so that the comparison will be based on fully propagated scores.Associated with each signal queue We now give a proof that DSP is mathematically equivalent to PSA, since it may not be entirely obvious from the foregoing description. We will consider only the forward strand cases; the proof for the reverse strand cases can be derived by a series of trivial substitutions in the proof below.j[ω] for signal sj is initialized to the PSA inductive score RI(sj,ω). For the basis step, recall that the left terminus anchor signals were initialized to have zero scores in both PSA and DSP, regardless of whether a given signal began a coding or noncoding feature. In the case of coding features, substituting Equation 19 into Equation 23 yields:To begin, we show by induction that the signal propagator πj[ω] ← πi[(ω - Δ)mod3] + RD(si,sj) + RT(si,sj) + RS(sj).     (24)πj[ω] = RI(sj,ω) only if:According to Equation 10, this initialization will result in πi[(ω - Δ)mod3] = RI(si,γi) + RC(si,sj,ω),     (25)πi = (ω - Δ)mod3 according to Equation 8. At the time that signal sj is instantiated by its signal sensor, πi has been propagated up to e = wpos(sj) - 1, the nucleotide just before the leftmost position of the context window for sj. By the inductive hypothesis, πi[γi] was initialized to RI(si,γi). This initialization occurred at the time when the current DSP position was at the beginning of the predecessor's context window. Note, however, that πi effectively began receiving updates at position b = wpos(si) + wlen(si), the position immediately following the end of the signal's context window, at which point si graduated from its holding queue. Thus, πi[γi] will have accumulated content scores for positions b through e, inclusive. In order to establish Equation 25, we need to show that these accumulations sum to precisely RC(si,sj,ω).where γM:Substituting Equation 16 into Equation 14 we get the following formula describing propagator updates as if they came directly from content sensor 0≤ω≤2 π[ω] ← π[ω] + log PM[(ω+Δ)mod3](xf),     (26)∀f-(pos(si) + len(si)) is the distance between the rightmost end of signal si and the current position f in the DSP algorithm. Let us introduce the notation:where Δ = i,j,ω) = ∑k = i..jlog PM[(ω+k)mod3](xk).     (27)F - len(si)); this can be verified by expanding this expression via Equation 27 and observing that the result equals a summation of the log term in Equation 26 over f = b to e. Looking at init_phased, it should be obvious that the effect of lines 5 and 8 will be that:Using this notation, πi,γ [h] = ∑k = 0..hlog PM [(k+γ)mod3](xk) = F(0,h,γ).     (28)αi[γi] has accumulated RC(si,sj,ω) is therefore equivalent to:According to Equation 5, showing that πF(b,e,ψ) = F(0,wpos(sj) - 1,γ) - F(0,wpos(si) + wlen(si) - 1,γ),     (29)i - pos(si) - len(si) and γ = ω - pos(sj). Equivalently:where ψ = γF(b,e,ψ) = F(0,e,γ) - F(0,b - 1,γ).     (30)mod3), observe that pos(sj) - (pos(si) + len(si)) = Δ, the length of the putative exon (possibly shortened by three bases, in the case where si is a start codon), and further that γi - ω ≡ -Δ(mod3) according to Equation 8, so that ψ - γ ≡ Δ-Δ ≡ 0(mod3). Thus, Equation 30 is equivalent to:To see that ψ ≡ γ(F(b,e,γ) = F(0,e,γ) - F(0,b - 1,γ),     (31)sj is initialized to the PSA inductive score RI(sj,ω), and thus establishes the inductive step of the proof in the case of coding features.which can be established as a tautology by simple algebra after expansion with Equation 27. This shows that the signal propagator for signal To see that the above arguments also hold for noncoding features, note that Equation 21 simplifies Equation 25 to:i[ω] = RI(si,ω) + RC(si,sj),     (32)πthat Equations 13 and 18 combine to simplify Equation 26 to:0≤ω≤2 π[ω] ← π[ω] + log PM(xf),     (33)∀and that lines 4 and 6 of init_nonphased cause:i[h] = ∑k = 0..hlog PM(xk) = FNC(0,h),     (34)αFNC(i,j) = ∑k = i..jlog PM(xk). We can thus reformulate Equation 29 as:for FNC(b,e) = FNC(0,wpos(scur) - 1) - FNC(0,wpos(spred) + wlen(spred) - 1),     (35)or, equivalently:FNC(b,e) = FNC(0,e) - FNC(0,b - 1),     (36)which is again a tautology. In the interests of brevity, we leave it up to the reader to verify that the above arguments still apply when the noncoding features are intergenic, thereby invoking Equation 22 rather than Equation 21 in formulating Equation 31.RCI + RD + RT) criterion of DSP as long as RCI(si,ω) = RC(si,sj,ω) + RI(si,γi) at the time the optimal predecessor is selected, which we have in fact already shown by establishing Equation 25.To see that the selection of optimal predecessors is also performed identically in the two algorithms, note that the PSA criterion given in Equation 7 is equivalent to the argmax with the sequence xj-n..xj. Although hash tables provide a relatively efficient solution for this task, they are wasteful in the sense that as we evaluate the chain on successive nucleotides in a sequence, we repeatedly manipulate preceding nucleotides in forming successive substrings to be indexed into the hash table.Markov chains are typically implemented in GHMM-based gene finders using hash tables, due to the simplicity of such an implementation. Thus, for a given Markov chain n+1 or less, and where the state having label xj-n..xj emits the probability PM(xj|xj-n..xj-1), for nth-order Markov chain M. In this way, the transition probabilities of the Markov chain become the state emissions of the FSM. During a single left-to-right scan of a sequence, each base requires only a single two-dimensional array indexing operation to access the desired probability, and a single integer value store operation to remember the identity of the new state. When compared to the typical regime of arithmetic and bit-shift operations over an (n+1)-element string that would be required for a typical hash function, the difference can be significant.A much faster (and much more elegant) solution is to employ a Finite State Machine (FSM) in which states exist for all possible sequences of length Implementing this optimization is fairly straightforward, both for conventional Markov chains and for Interpolated Markov Models, whether homogeneous or three-periodic. Central to the method is a means of mapping between state labels and integer state identifiers for use in indexing into the transition table. The base-4 number system can be utilized for this purpose, assuming a nucleotide mapping such as ∇ = {A↔0, C↔1, G↔2, T↔3}. To account for lower-order states, define:L. Converting a string S = x0..xL-1 to base-4 can be accomplished as follows:which gives the total number of strings of length less than S can be mapped to a state index using:Now a string state(S) = B(|S|) + λ(S),     (39)S| denotes the length of S.where |nth-order Markov chain in hash table format, the FSM state emissions can be initialized by indexing state labels into the hash table to obtain the Markov chain transition probabilities. The transition table can be initialized fairly simply by noting that the successor of state x0..xL-1 upon seeing symbol s is x1..xL-1s if L = n + 1, or x0..xL-1s for L <n + 1. A model for the reverse strand can be handled by applying this scheme in reverse, so that the state with label xj-n..xj emits the probability PM(xj-n|xj-n+1..xj), and the lower-order states are reserved for the end of the sequence rather than the beginning.Given this integer↔label mapping and an Table not use the C++ Standard Template Library (STL) implementations of string and hash, due to efficiency concerns regarding the re-copying of string arguments to the hash function. Our custom string hashing implementation was found to be much faster than the STL implementation (data not shown). Accordingly, one can expect an FSM implementation to show even greater gains as compared to an STL-based hashing implementation.Table We utilized our DSP-based gene finder TIGRscan  in the cAspergillus fumigatus and A. nidulans) while consuming under 50 Mb of RAM, whereas an earlier prototype of this system applied to the same input data routinely exhausted all available memory on a computer with 1 Gb of RAM. We are hopeful that through the use of optimizations such as those described here we will be able to apply TWAIN to other pairs of genomes with longer genes, and possibly extend the program to handle more than two species simultaneously.As a result of these and other optimizations  we were able to apply TWAIN's gene prediction component to a pair of fungal genomes (In describing a number of optimizations for GHMM-based gene finders and making available two complete open-source software systems embodying these methods, it is our hope that others will be more enabled to explore promising extensions to the GHMM framework, thereby improving the state-of-the-art in gene prediction techniques.Project name: TIGRscan, GlimmerHMM* Project home page: * Operating system(s): Linux/UNIX* Programming language: C/C++* Other requirements: compiled using gcc 3.3.3* License: Artistic License, see * Any restrictions to use by non-academics: terms of Artistic License* The DSP algorithm was devised by WHM, who also performed the computational experiments and wrote the manuscript. The PSA gene finder GlimmerHMM was implemented by MP. MP, ALD, and SLS provided detailed insights into the PSA architecture and provided valuable comments on the manuscript.


The management of unresectable or metastatic gastrointestinal stromal tumors (GISTs) has previously been difficult as they are resistant to conventional chemotherapy and radiation. The development of imatinib mesylate has made a major impact on the management of advanced GISTs. It is apparent that there are sanctuary sites such as the central nervous system where imatinib does not achieve adequate concentrations. We describe the case of a man with metastatic GIST who experienced multiple cerebral relapses of disease while systemic disease progression appeared to be controlled by imatinib.A 47-year-old man presented in July 1999 with a jejunal GIST with multiple hepatic metastases. The jejunal primary was resected and after unsuccessful cytoreductive chemotherapy, the liver metastases were also resected in December 1999. The patient subsequently relapsed in August 2001 with symptomatic hepatic, subcutaneous gluteal, left choroidal and right ocular metastases all confirmed on CT and PET scanning. Biopsy confirmed recurrent GIST. MRI and lumbar puncture excluded central nervous system involvement. The patient was commenced on imatinib 400 mg bd in September 2001 through a clinical trial.The symptoms improved with objective PET and CT scan response until December 2002 when the patient developed a right-sided foot drop. MRI scan showed a left parasagittal tumor which was resected and confirmed histologically to be metastatic GIST. Imatinib was ceased pre-operatively due to the trial protocol but recommenced in February 2003 on a compassionate use program. The left parasagittal metastasis recurred and required subsequent re-excision in September 2003 and January 2004. Control of the systemic GIST was temporarily lost on reduction of the dose of imatinib (due to limited drug supply) but on increasing the dose back to 800 mg per day, systemic disease was stabilized for a period of time before generalised progression occurred.This case illustrates that the brain can be a sanctuary site to treatment of GISTs with imatinib. Maintaining dosing of imatinib in the face of isolated sites of disease progression is also important, as other metastatic sites may still be sensitive. This oral drug is also active in all phases of chronic myeloid leukemia (CML) as it also targets the bcr-abl tyrosine kinase. It is apparent that there are sanctuary sites such as the central nervous system where imatinib does not achieve adequate concentrations. We describe the case of a man with metastatic GIST who experienced multiple cerebral relapses of disease while systemic disease progression appeared to be controlled by imatinib.Gastrointestinal stromal tumors (GISTs) are rare mesenchymal gastrointestinal tumors which can have an aggressive course. Management of these tumors apart from surgical resection has been difficult in the past because they are resistant to conventional chemotherapy  and radiA 47-year-old man presented in July 1999 with melena. A small bowel series and CT abdomen showed a jejunal mass and a 5 × 5 cm complex hepatic mass. A biopsy of the liver lesion revealed a spindle cell tumor. Laparotomy was performed, and the 7.5 cm jejunal mass was resected. A total of 4 liver lesions were noted, but not resected. The histopathology confirmed a gastrointestinal stromal tumor with clear resection margins. He subsequently had 4 cycles of attempted cytoreductive chemotherapy using doxorubicin and dacarbazine. A repeat CT scan showed progression of the liver metastases. An extended right hemihepatectomy was performed in December 1999 with successful excision of all 4 liver metastases.The patient remained well until review in August 2001 when he complained of lethargy, right upper quadrant abdominal pain, diplopia and blurred vision in the left eye. Examination revealed weakness of the right lateral rectus ocular muscle, an amelanotic left choroidal lesion, hepatomegaly and a subcutaneous nodule in the gluteal region. An enhancing lesion in the infero-lateral region of the right globe was confirmed on CT which was thought to be the cause of the ocular muscle weakness. The CT scan also demonstrated a recurrence of multiple hepatic metastases. There were no intracerebral lesions. The gluteal lesion was biopsied and confirmed recurrence of GIST (CD117 positive). A positron emission tomogram (PET) scan also confirmed disease recurrence in the same distribution. Lumbar puncture and MRI scan of the brain excluded the presence of leptomeningeal or cerebral metastases. The patient was commenced on imatinib mesylate (STI-571, Gleevec, Novartis) 400 mg bd in September 2001 as part of a clinical trial. He felt much improved by November 2001 when a repeat CT abdomen showed stable disease but PET scan now showed no FDG uptake. By January 2002 his diplopia had completely resolved but the left-sided choroidal lesion remained unchanged on fundoscopy. The buttock lesion had also resolved.th January 2003 with complete resection of the lesion. Histopathology demonstrated metastatic GIST (CD117 positive) , the patient's dose of imatinib mesylate was reduced to 400 mg per day in March 2003. Six weeks later, his diplopia had returned and a progress CT abdomen demonstrated a minor progression of the liver lesions. His liver function tests remained normal. A subsequent PET scan again showed no abnormal uptake despite disease progression on the CT scan. His dose of imatinib mesylate was increased initially to 600 mg per day with resolution of the diplopia.By May 2003 his foot drop had worsened and his dose of imatinib mesylate was increased back to 800 mg per day. Despite the increase in dose, his foot drop worsened. A repeat CT brain demonstrated a recurrence of the cerebral metastasis with surrounding vasogenic oedema in the previous site of resection. A repeat abdominal CT showed no significant change in the size of the liver metastasis and mild shrinking of the nodule in the buttock.th September 2003. A small residual area of tumor was seen on the postoperative scan. Abdominal imaging two months later showed that two of the liver lesions had increased in size with the other areas stable. He was not a candidate for further hepatic resection as there was insufficient liver reserve due to the past surgery. Radiofrequency ablation was declined as the patient did not have symptoms referable to the area.Due to limited treatment options available for the cerebral metastasis, a re-resection of the cranial metastasis was offered. A repeat MRI of the brain in late July 2003 confirmed the presence of the left parasagittal lesion with surrounding edema but no mass effect. Repeat craniotomy and incomplete debulking of the parasagittal metastasis was performed on the 9The patient remained well until December 2003 when he experienced symptoms of headaches, worsening diplopia, right foot drop and left arm weakness. MRI scan confirmed recurrence of the cerebral metastasis with extension across the falx cerebri. He declined cranial radiotherapy treatment at the time and instead underwent a third resection of the lesion in January 2004 where incomplete debulking was achieved with early improvement of his limb weakness. In April 2004 the patient enrolled into a randomised placebo controlled clinical trial of a novel multi-kinase inhibitor SU-11248 (Pfizer) for the treatment of imatinib refractory GIST. However his condition slowly deteriorated and he died in July 2004.This case illustrates a man who has had evidence of presumed ocular involvement by the GIST that initially responded to imatinib who had a cranial relapse while the systemic disease initially remained controlled. This would imply that the central nervous system could be a sanctuary site where the imatinib mesylate does not achieve adequate levels. Preclinical mice models of CML have shown development of central nervous involvement on imatinib despite systemic disease control with cerebral spinal fluid levels being 155 times lower than plasma . This iskit and clinical outcomes of GISTs on imatinib [502 and Tyr503 This may be marker for malignant course of the disease as 71% have a highly malignant course and 59% arise exclusively in the small intestine [There appears to be a relationship between the presence of different activating kinase mutations of imatinib . The exontestine . The difntestine . The absThe central nervous system can be a sanctuary site to treatment of GIST with imatinib mesylate. Prolonged control of the recurrences in this location was achieved by repeated resections. This patient also highlights the importance of maintaining dosing of imatinib mesylate in the face of isolated sites of disease progression, as other metastatic sites may still be sensitive. Cessation and lowering of the dose of the drug led to temporary loss of systemic control in this case.David Goldstein and Paul Waring have both consulted and spoken on behalf of Novartis Pharma on imatinib and GIST.BH, DY, DG and GC participated in the clinical care of the case. PW and VB performed the mutation analysis and prepared the histopathology images. BH and DY drafted the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Prostate cancer continues to occur in over 230,000 men each year. Although the majority of these will be diagnosed in the early stages, there remains a proportion who will either be diagnosed in late stage disease or develop progressive disease. In patients with advanced disease, research has recently focused on using chemotherapy for symptom management and palliation. Given that the focus is not on cure, the effect of chemotherapy on quality of life is of utmost importance. The present article will 1) summarize the current chemotherapeutic studies that have included a quality of life component, with a particular focus on pain and fatigue, 2) discuss the issue of distress in advanced prostate cancer patients treated with chemotherapy, and 3) suggest future research directions.From the studies that have investigated quality of life, it appears that several chemotherapeutic agents reduce pain and fatigue, although the development of fatigue is often the dose-limiting factor of some agents. The assessment of overall quality of life has occurred in several studies, however, an examination into the impact of chemotherapy on functional status and interpersonal relationships has not been studied. Finally, in contrast to the numerous studies in early stage prostate cancer patients, the presence and effect of distress in chemotherapy-treated prostate patients has not been examined. As such, increased attention is needed to quality of life during phase I-III chemotherapy trials. Prostate cancer will be diagnosed in an estimated 230,110 men during 2004 [For men with late stage disease, chemotherapy is increasingly being examined as a treatment option, although the goal is usually palliative in nature and may not extend length of survival ,3. ChemoThe inclusion of QOL endpoints in chemotherapy trials with cancer patients started in earnest during the last decade, with the majority of studies assessing the impact of chemotherapeutic agents on symptoms such as pain and fatigue. Since then, the inclusion of QOL endpoints has become a more common outcome in chemotherapy studies, although many continue to neglect the psychological component, focusing instead on the occurrence of symptoms and their impact on physical QOL.A comprehensive search of English-language articles in PubMed was conducted to identify studies that had assessed quality of life and/or emotional distress as part of chemotherapeutic trials in advanced cancer patients Table . The keyIn one of the first studies to examine the impact of chemotherapy on pain, Tannock, Osoba, Stockler et al.  randomizPain was also assessed in several studies utilizing docetaxel either alone or in combination with estramustine in androgen-independent prostate cancer -9. In onIn a recent study, docetaxel was administered intravenously on a daily basis for 6 consecutive weeks followed by a 2-week break between each of up to 4 cycles . The autReductions in pain have also been observed in studies using suramin and epirubicin. In a study by Small et al. , compariThe use of the more commonly known platinum compounds (e.g., cisplatin, carboplatin) have also demonstrated beneficial efforts on pain reduction. In advanced prostate cancer patients treated with a carboplatin/epirubicin/etoposide regimen, pain relief was observed in 44% of the patients .The overall point of these studies is that for prostate cancer patients with advanced disease, there are a variety of chemotherapeutic agents that have beneficial palliative effects, specifically pain reduction. Despite this, there is no definitive palliative pain regimen in this population and no defined algorithm for pain management using chemotherapy.Several studies have investigated the relationship between chemotherapeutic agents and fatigue in prostate cancer patients. Among the agents studied are the taxanes, specifically docetaxel and paclitaxel. In phase I studies of docetaxel and estramustine, the presence of fatigue has been used to identify the dose-limiting factor ,22. CurrFatigue was also an endpoint in a well-designed study that assessed the effect of 25 mg/m2 epirubicin administered intravenously on a weekly basis compared to 100 mg/m2 administered every 4-weeks . After fIn contrast to the numerous QOL studies of early-stage prostate cancer patients, beyond pain and fatigue, the assessment of QOL in advanced stage prostate cancer patients is relatively lacking. By and large there are no studies assessing the common areas of physical well-being  or psychological well-being (e.g., distress related to treatment or sequelae), and social or family well-being in chemotherapy treated patients. The notable exception is a study of the QOL of 44 hormone refractory prostate cancer patients and their partners by Kornblith et al. . In a phIn contrast to the various studies that have investigated the presence of emotional distress, depression, and anxiety in early stage prostate cancer patients, there is remarkably little concerning these issues in those with advanced cancer. Indeed, a Pubmed search using the terms "distress AND advanced prostate cancer" resulted in only 12 studies. Of these, only 3 studies specifically focused on advanced prostate cancer -27, withChemotherapy is being examined with greater frequency in the treatment of advanced prostate cancer. Since the goal of treatment for these individuals is more likely to be palliation than cure, understanding the impact on QOL is that much more important. For example, understanding the impact on QOL can assist clinicians and patients in decision-making by providing data on whether symptom benefit obtained outweighs the toxicities from treatment.Thus far, several studies have identified improvements in pain and fatigue as a result of chemotherapeutic protocols, although in some studies, the presence of fatigue is a dose-limiting factor. Disappointing is the lack of focus on the more global aspects of quality of life, the impact on physical, psychological, social, and family well-being. How the treatment of the individual affects their relationships with others  has yet to be studied in this population. Also yet to be studied is the impact on emotional well-being. The presence of distress in cancer patients is well-documented (e.g., ), and it


Video capture virtual reality (VR) uses a video camera and software to track movement in a single plane without the need to place markers on specific bodily locations. The user's image is thereby embedded within a simulated environment such that it is possible to interact with animated graphics in a completely natural manner. Although this technology first became available more than 25 years ago, it is only within the past five years that it has been applied in rehabilitation. The objective of this article is to describe the way this technology works, to review its assets relative to other VR platforms, and to provide an overview of some of the major studies that have evaluated the use of video capture technologies for rehabilitation. Two major goals of rehabilitation are the enhancement of functional ability and the realization of greater participation in community life. These goals are achieved by intensive intervention aimed at improving sensory, motor, cognitive and higher level-cognitive functions on the one hand, and practice in everyday activities and occupations to increase participation on the other hand ,2. InterVirtual reality typically refers to the use of interactive simulations created with computer hardware and software to present users with opportunities to engage in environments that appear to be and feel similar to real world objects and events -8. UsersThe objective of this article is to briefly describe the use of VR in rehabilitation, and then emphasize the unique attributes of the video capture VR to rehabilitation, including an overview of some of the major studies that have evaluated the use of this technology for rehabilitation.Virtual reality has a number of well-known assets, which make it highly suitable as a rehabilitation intervention tool . These aDuring the mid to late 1990s, virtual reality technologies first began to be developed and studied as potential tools for rehabilitation assessment and treatment intervention . The lisGiven the variety of VR platforms and the diverse clinical populations that may benefit from VR-based intervention, it is helpful to view the VR experience as a multidimensional model that appears to be influenced by many parameters. A conceptual model was developed within the context of terminology established by the International Classification of Functioning, Disability and Health (ICF)  and the The "Interaction Space" denotes the interaction that occurs when the client performs within the virtual environment, experiencing functional or game-like tasks of varying levels of difficulty, i.e., the activity component according to the ICF terminology. This interaction is influenced by user characteristics, which include personal factors , body functions (e.g. cognitive, sensory, motor abilities) and structures (e.g., the parts of the body activated during the task). It is also influenced by the characteristics of VR platform and its underlying technology (e.g. point of view, encumbrance) that presents the virtual environment and the nature and demands of the task to be performed within the virtual environment.It is during the interaction process that sensations and perceptions related to the virtual experience take place; here the user's sense of presence is established, and the process of assigning meaning to the virtual experience as well as the actual performance of virtual tasks or activities occurs. The sense of presence enables the client to focus on the virtual task, separating himself temporarily from the real world environment. This is an important requirement when motor and, especially, cognitive abilities and skills are trained or restored. The concept of meaning is also thought to be an essential factor that enhances task performance and skills in rehabilitation in general ,3, and tTwo outer circles, the "Transfer Phase" and the "Real World" denote the goal of transferring skills and abilities acquired within the "Interaction Space" and eliminating environmental barriers in order to increase participation in the real world . The "Transfer Phase" may be very rapid and accomplished entirely by the client or may take time and need considerable guidance and mediation from the clinician. The entire process is facilitated by the clinician whose expertise helps to actualize the potential of VR as a rehabilitation tool.Virtual environments are experienced with the aid of special hardware and software for input (transfer of information from the user to the system) and output (transfer of information from the system to the user). The selection of appropriate hardware is important since its characteristics may greatly influence what is taking place in the Interaction Space, i.e., the way users respond (e.g. sense of presence, performance) to a virtual environment . The outIn addition to specialized hardware, application software is also necessary. In recent years, off-the-shelf, ready-for-clinical-use VR software has become available for purchase. However, more frequently, special software development tools are required in order to design and code an interactive simulated environment that will achieve a desired rehabilitation goal. In many cases, innovative intervention ideas may entail customized programming to construct a virtual environment from scratch, using traditional programming languages.Video capture VR consists of a family of camera-based, motion capture platforms that differ substantially from the HMD and desktop platforms in wider use. When using a video-capture VR platform, users stand or sit in a demarcated area viewing a large video screen that displays one of a series of simulated environments. Users see themselves on the screen, in the virtual environment, and their own natural movements entirely direct the progression of the task, i.e., the user's movement is the input. The result is a complete engagement of the user in the simulated task. A single video camera converts the video signal of the user's movements wherein the participant's image is processed on the same plane as screen animation, text, graphics, and sound, which respond in real-time. This process is referred to as "video gesture", i.e., the initiation of changes in a virtual reality environment through video contact. The user's live, on-screen video image responds at exactly the same time to movements, lending an intensified degree of realism to the virtual reality experience. Video capture provides both visual and auditory feedback with the visual cues being most predominant.Myron Krueger  was the  in 1996, together with a suite of interactive, game-type environments. This platform makes use of a chroma key-based setup so that the existing background is subtracted and replaced by a simulated background. GX VR has enjoyed considerable success around the world in numerous entertainment and educational facilities including science museums and entertainment parks. During the past five years it has also begun to be adapted for use in rehabilitation and has generated great interest in clinical settings (see below). GX VR currently offers a wide variety of gaming applications including, Birds & Balls, wherein a user is required to touch balls of different colors; if the touch is "gentle", the balls turn into doves whereas an abrupt touch causes them to burst. In another application, a soccer game, the user sees himself as the goalkeeper whose task it is to prevent balls from entering the goal area  platform In the late 1990s two other commercial companies developed video-capture gaming platforms, Reality Fusion's GameCam and Intel's Me2Cam Virtual Game System . Both of. This is an off-the-shelf, low-cost gaming application, which provides the opportunity to interact with virtual objects that can be displayed on a standard TV monitor [Somewhat later, Sony developed its very popular EyeToy application designed to be used with the PlayStation II platform  monitor . As withThe EyeToy application includes many motivating and competitive environments which may be played by one user or more than one user sequentially in a tournament fashion. With GX VR, two users can compete together simultaneously (e.g., boxing, spinning plates) as well as combine their efforts to create different visual effects without a competitive component (e.g., painting a rainbow, mirror image distortions and popping bubbles). which enables therapists to adapt levels of difficulty and record performance outcomes [The potential of these platforms for rehabilitation was readily apparent despite the fact that they were originally developed for entertainment and gaming purposes. Indeed, VividGroups's GX platform was first applied without adaptations within a clinical setting by Cunningham and Krishack  who usedoutcomes .Video-capture VR differs from other platforms in a number of ways that have great relevance for its use as a tool for rehabilitation evaluation and intervention. Some of these characteristics appear to be advantageous whereas others may limit the utility of video-capture VR.Video-capture VR provides users with a mirror image view of themselves actively participating within the environment. This contrasts with other VR platforms such as the HMD which provides users with a "first person" point of view, or many desktop platforms in which the user is represented by an avatar. The use of the user's own image has been suggested to add to the realism of the environment and to the sense of presence . It alsoThe user in video-capture VR does not have to wear or support extraneous devices such as an HMD, glove or markers in order to achieve a substantial intensity of immersion within the virtual environment. This eliminates a source of encumbrance that would likely hinder the motor response of patients with neurological or orthopedic deficits. Although the newer HMDs and stereoscopic glasses are considerably less cumbersome than previous models, little information is available regarding their use by individuals undergoing cognitive or motor rehabilitation.This characteristic relates to how the user controls objects within the virtual environment. As indicated above, rather than relying on a pointing device or tracker, interaction within video-capture based environments is accomplished in a completely intuitive manner via natural motion of the head, trunk and limbs. Not only is the control of movement more natural, but, in the case of the chroma key GX VR, a "red glove" option (or any object with a distinct color) may be used to restrict system response to one or more body parts as deemed suitable for the attainment of specified therapeutic goals. For example, when it is appropriate to have the intervention directed in a more precise manner, a client may be required to repel projected balls via a specific body part (e.g., by the hand when wearing a red glove or by the head when wearing a red hat). Or, when intervention is more global, the client will not use the red glove option and thus be able to respond with any part of the body. The ability to direct a client's motor response to be either specific or global makes it possible to train diverse motor abilities such as the range of motion of different limbs and whole body balance training.A limitation of currently available video capture platforms is the reliance on visual and auditory feedback and the absence of a haptic interface that would provide participants with real-time indications of contact with the virtual stimuli. Such feedback could serve as an important addition when used in therapy since the balls, for example, could be rendered to appear to have progressively greater mass, making the task more or less difficult. It would also add an additional element of realism to the gaming experience, and ensure that feedback to participants was more realistic. This could be accomplished to some degree via a quasi-haptic effect that might use vibration to simulate a true haptic interface . For example, small buzzers may be affixed to the tips of the digits. Touching a virtual ball in the Vivid GX Birds & Balls application would generate a low amplitude, high frequency "buzz". In contrast, repelling a larger ball in the Soccer application would generate a high amplitude, low frequency "buzz".Video-capture VR may be implemented while users stand, sit, or even walk on a treadmill. For example, the same environment may thus be suitable for training standing balance of a patient who had a stroke, sitting balance of an individual with an incomplete quadriplegic spinal cord injury, and balance during treadmill locomotion of an individual with a paraplegic spinal cord injury.Moreover, one or more users may participate within the same environment. In some applications, the ability to have two "rival" users interact simultaneously within the same game or task adds an element of competitiveness that may be motivating. Of greater importance is the ability of the therapist to support a client or use handling techniques in order to facilitate active movement while the client interacts with the virtual stimuli. The therapist can be concealed behind the client in order not to be seen in the VE, or can join the client within the virtual environment.Another limitation of the currently available video capture VR platforms is that they may be operated with only one camera. This means that all tasks must be performed within a single plane. In the case of the typical coronal plane setup where the camera is positioned to face the user, any functional movement that takes place in the sagittal or transverse planes is disregarded. Virtual scenarios must therefore be carefully designed such that a meaningful task can be performed despite the restriction to uniplanar movement. Moreover, care must be taken when analyzing the kinematic trajectories since any out-of-plane motion will not be recorded. It is encouraging to note that three dimensional, functional environments will likely soon become available .Although video-capture platforms have only begun to be used for rehabilitation applications within the last five years, there are already results from a number of research groups who have studied its utility with different patient populations. In this section we highlight the major studies that provide evidence that this technology appears to be suitable for use in rehabilitation. The evidence concerning participant sense of presence, enjoyment, usability and performance are summarized as reported by studies of single platforms and by studies that compared different VR platformsNone of the studies carried out to date have reported any significant occurrence of cybersickness-type side effects when using video-capture VR. Rand et al.  explicitSeveral studies examined the influence of video capture platform of the user's sense of presence and level of enjoyment. Rand et al.  in theirThe results of these studies showed that a high sense of presence and level of enjoyment can be achieved in a video capture VR platform. They also demonstrate that user characteristics such as age influence the sense of presence.In another study, Rand et al.  comparedRand at al.  reportedThe GX VR platform has consistently generated high levels of presence and enjoyment across a wide range of clinical populations and ages including adults with paraplegic spinal cord injury , stroke The measures of performance used by video-capture VR studies to date include response times to presented virtual stimuli, percent success with which a given game is performed , a subjective report on how much effort the user has felt while in the environment. The chroma key video capture platforms such as GX and IREX also provide a relatively gross measure of limb kinematics. Whether these data have sufficient precision and resolution to warrant their inclusion in a research study remains to be investigated .Sveistrup, McComas and colleagues have used the IREX platform for balance retraining. Following six weeks of training at an intensity of three sessions per week, improvement was found for all 14 participants in both the VR and control groups . HoweverKizony et al.  performeIn a second study Kizony et al.  examinedRand et al.  used a vWeiss at al. , in a stPerformance within two games (Kung-Foo and Wishy-Washy) was measured while three different groups, young adult participants, healthy senior participants and individuals who were several years post-stroke, used several of the EyeToy games . PerformThe performance results described above highlight the interplay between the user and VR platform characteristics, and emphasize the importance of taking these characteristics into consideration while using VR in rehabilitation. Moreover, they demonstrate the sensitivity of the VR performance measures in their capacity to differentiate between levels of participant ability.Due to the motivating nature of the game-like environments, it is important to determine how much effort healthy subjects and those with disabilities expend while engaged in these tasks. In a study of healthy young adults, the participants using the GX platform perceived the highest level of exertion while playing Soccer, less for Birds & Balls and still less for a third game, Snowboard where only weight transfer was needed . When diUsing the IREX platform, Sveistrup et al.  performeCunningham & Krishack  presenteAnalysis of conventional and video capture VR treatment for SCI by specialists in rehabilitation highlighted several key differences between the two methods of intervention . First, One of the newest developments in video-capture VR is the simulation of more functional environments. Rand et al.  have creSony's EyeToy Wishy Washy application involves the cleaning of successive dirty windows via wiping movements of the hand and arms. Most recently, VividGroup has developed a laundry application . These moves towards more functional applications are encouraging.Evidence from the literature has demonstrated the feasibility, usability and flexibility of video-capture VR, and there is little doubt that this technology provides a useful tool for rehabilitation intervention. The results of presence questionnaires, reports of user satisfaction, and the sensitivity to differences in user ability as functions of age, gender and disability are all strong indicators of the suitability of this tool. A short video-clip, taken from a local news report of applications of video-capture VR for stroke, illustrates the extremely positive response of one user to the use of this technology (see Video 1).To date, as indicated by the studies reviewed above, video capture VR shows great promise for a variety of therapeutic goals including intervention for cognitive and motor rehabilitation, functional activities and leisure opportunities. The general assets of virtual reality summarized above combined with several assets that are unique to video-capture VR, are compelling arguments for the inclusion of this technology in the repertoire of tools available in clinical settings.Market demand, user interest and improvements in technology have led to the availability of a number of different video-capture platforms. There is no doubt that these platforms are valuable as intervention tools during the rehabilitation of patients with neurological and musculoskeletal disorders. Motivated patients would be encouraged to practice movements in a repetitive manner thereby improving their condition, an achievement that is not easy to attain via conventional therapy . CurrentStudies comparing these two platforms have shown that presence, enjoyment, usability and performance were equivalent under many conditions and for diverse users. Thus, despite the EyeToy's limitations, its low cost, user-friendly interface and simple setup requirements makes it highly attractive to therapists. It may be readily acquired for use in any clinical setting, and even be purchased for use at home to provide regular, intensive therapy after discharge from hospital.Nevertheless, it is clear that the EyeToy is not suited for use with the most severely impaired users. The currently available games seem to have a broad appeal for users of different ages but an open architecture that permits adaptations of existing applications and development of new environments appears to be a basic requirement to make this platform truly functional as a clinical tool. A system for generating an outcomes report comparable to the IREX platform would also be of great benefit for clinicians. Additional low-cost video-capture platforms are currently under development . Moreover, video-capture platforms that will provide three dimensional, functional environments will likely soon become available .In contrast to the EyeToy's closed architecture, VividGroup's IREX platform provides a user-friendly interface that a therapist may use to specify a much greater range of levels of difficulty. Their SDK (Software Development Kit) provides programmers with the ability to further adapt existing applications such as the standard set of games  and to dVideo 1: This video clip shows a patient who had a stroke using the VividGroup VR system for cognitive and motor rehabilitation.Click here for file


The history of one of the world's first electronic archives for scientific journals JSTOR is successful for reasons its founders did not intend. Bill Bowen's inspired vision was of a solution to libraries' ever-voracious demands for space to house paper volumes. The idea was that libraries could save space by removing volumes available in electronic format. Few libraries have discarded the volumes digitised in JSTOR, but many libraries without the paper volumes have been able to offer their users access to the important journal runs JSTOR has digitised. Paper holdings have not decreased dramatically, but electronic holdings have increased. So a space-saving service became an access service.As an access service, JSTOR is a creation of its time. Understandable though the decision to use page images may have been eight years ago, future user-friendly access requires searching capabilities across full-text, which page images cannot supply. Likewise, the decision to digitise the back-runs of around 100—now 218—paper journals was a bold decision at the time, but the future for access to journal literature lies in electronic versions of thousands rather than hundreds of titles, both current and retrospective. When we reach that point, JSTOR will still have a valued place in the content on offer, but it is difficult to see JSTOR providing thousands rather than a few hundred titles. Its technical solutions and financial models look dated as both subscription-based and open-access publishers improve their services to authors and to readers. As the number of journal articles accessible over the networks increases, JSTOR will be seen as a small-scale pioneer from which we learned valuable lessons.Roger Schonfeld ends his very detailed description of JSTOR with a chapter on ‘Lessons Learned’, many of which are relevant to current access initiatives. The need for grant funding to launch any such initiative has to be accompanied by a sound business plan to ensure long-term economic viability. JSTOR has achieved that transition, and its success provides a model for others. Much of the credit must go to JSTOR's enterprising president, Kevin Guthrie, who found the quickest way through the maze of conflicting advice—much of which could have resulted in JSTOR's reaching a deadend—and convinced the library and publishing communities to buy into a product that was only a promise. Meeting user needs for easy access to high-quality content was the key to the fulfilment of that promise. JSTOR's public image is of quality in depth—long runs of core journals—and that image has to become the hallmark of the new open-access initiatives as they develop.It is understandable that some mistakes were made on the way. The difficulty that JSTOR financial planning had in coming to terms with consortial purchases delayed its growth as an access service. Although selling to consortia of academic libraries may not have improved JSTOR's financial position in the short-term, consortia are a route to spreading access and therefore securing longer-term financial stability . Some opportunities were also delayed—not lost—through too slow an adaptation of the JSTOR purchasing model for selling outside the United States, the United Kingdom being the exception. The UK deal was with JISC, the Joint Information Systems Committee of the UK Higher Education Funding Councils, acting more as a negotiating agent than a consortium, and this model could have been applied in other countries. More countries would have valued access to JSTOR earlier, but the approach to non-US deals had to be imaginative. For all vendors, there has to be an understanding of the political, social, economic, and educational structure of the country into which the product is being sold, an understanding that takes time to acquire but that pays dividends. Open-access publishers do not have to sell their product to users of their journals, but local knowledge is essential in ‘selling’ their services to authors. The globalisation of publishing has combined with the globalisation of the networks and with the globalisation of research to provide opportunities for high-quality research conducted outside North America and Western Europe to be published in peer-reviewed open-access journals more readily than in the traditional subscription-based journals.Roger Schonfeld's book draws out many of the significant points about JSTOR's place in the history of electronic publication through a minute examination of the process leading to JSTOR as it is today. There is so much detail in the book that the reader may feel that its comprehensiveness cannot be questioned, but one small omission of which I have personal knowledge makes me question the value of so much detail. The omission concerns the interest by my institution, University College London, in joining JSTOR before the JISC deal was considered. Not a detail of world-shattering significance, but it does illustrate the fact that outside the United States, as well as within, the early interest in JSTOR came from individual institutions rather than from consortia. I sympathise with Roger Schonfeld in attempting to write such a comprehensive history, but what is the point of appearing to be comprehensive when comprehensiveness is an impossible goal? Would a briefer history have been just as valuable?Leaving aside quibbles and caveats about the book and about JSTOR, this remains a fascinating and instructive history of an important and ground-breaking initiative. Bill Bowen's vision may not have developed in quite the way he expected, but the ‘bottom-line’ is that the vision did become a successful reality. The problem of ever-expanding libraries has not gone away in the ten years since JSTOR was conceived, but the ultimate solution—the availability of electronic content—has become closer, and JSTOR's success has encouraged others to develop services that are more in accord with 2003 than 1993. One lesson Roger Schonfeld does not draw out is the pace of change in electronic publishing, and if so much has been achieved since 1993, what promise is held out by the next ten years'!


Autotaxin (ATX, NPP-2), originally purified as a potent tumor cell motility factor, is now known to be the long-sought plasma lysophospholipase D (LPLD). The integrity of the enzymatic active site, including three crucial histidine moieties, is required for motility stimulation, as well as LPLD and 5'nucleotide phosphodiesterase (PDE) activities. Except for relatively non-specific chelation agents, there are no known inhibitors of the ATX LPLD activity.We show that millimolar concentrations of L-histidine inhibit ATX-stimulated but not LPA-stimulated motility in two tumor cell lines, as well as inhibiting enzymatic activities. Inhibition is reversed by 20-fold lower concentrations of zinc salt. L-histidine has no significant effect on the Km of LPLD, but reduces the Vmax by greater than 50%, acting as a non-competitive inhibitor. Several histidine analogs also inhibit the LPLD activity of ATX; however, none has greater potency than L-histidine and all decrease cell viability or adhesion.L-histidine inhibition of LPLD is not a simple stoichiometric chelation of metal ions but is more likely a complex interaction with a variety of moieties, including the metal cation, at or near the active site. The inhibitory effect of L-histidine requires all three major functional groups of histidine: the alpha amino group, the alpha carboxyl group, and the metal-binding imidazole side chain. Because of LPA's involvement in pathological processes, regulation of its formation by ATX may give insight into possible novel therapeutic approaches. Lysophosphosphatidic acid (LPA) is both an intracellular and an extracellular signaling molecule that affects biological processes such as cell proliferation, rescue from apoptosis, cell migration, neurite retraction, wound healing, platelet aggregation and vascular remodeling . As a cyATX was originally purified as a potent tumor cell motogen , an effeATX is a member of the nucleotide pyrophosphatase and phosphodiesterase (NPP) family of enzymes. The NPPs are part of the superfamily of alkaline phosphatases, metalloenzymes in which the active site is characterized by histidine residues coordinated around central divalent cations and by a serine, threonine, or cysteine residue, which is utilized to form an intermediate during the reaction ,15. SiteHistidine has been implicated as a requirement for many metalloenzymatic reactions, presumably by virtue of its imidazole moiety. Reversible reagents such as diethylpyrocarbonate, which react with imidazole, inhibit these enzymes . Such fiATX, isolated as a motility-stimulating protein, is a member of the NPP family of metalloenzymes. Both its motogenic and its enzymatic activities appear to require the same active site since both are abolished when T210  or any oFig. ATX was pre-incubated with 200 nM LPC with or without addition of various concentrations of L-histidine, then heated to abolish its enzymatic activity  and adde++ and Zn++ were markedly effective in restoring enzymatic activity to LPLD in EDTA-treated plasma. In fact, addition of Co++ to EDTA-treated heparinized plasma resulted in a recovery from 37% of the untreated value in the presence of EDTA alone to 154% in the presence of Co++ and EDTA. Since histidine plays an important structural role in the catalytic process, we determined first that addition of free histidine has an inhibitory effect upon ATX-catalyzed hydrolysis of both nucleotide and lyso-phospholipid substrates. After establishing the concentration requirements for histidine inhibition, we next examined the capacity of different metal cations to reverse this inhibition. Finally, we determined how histidine and metal cations affect the kinetics of the LPLD reaction.The PDE activity of the NPPs has been shown to be dependent upon the presence of metal ions . TokumurAs seen in Fig. ++ nor Ca++ significantly reversed the inhibitory effect of histidine although Ca++ alone enhanced both reactions by at least 30%. However, Zn++ and Co++ each significantly overcame inhibition caused by free histidine. In the case of Zn++, the presence of the cation alone increased both reactions by up to 50% above control, and virtually abolished the inhibition caused by histidine, with recoveries of 90 – 100% of the activity measured in the presence of Zn++ alone. In the case of Co++, the cation alone increased the PDE activity by 50% and the LPLD activity by 300%; however, histidine still inhibited PDE by ~70% and LPLD by 50% compared to adding Co++ alone. Zn++, therefore, appears to be the most effective cation in reversing the inhibition by histidine. It should also be noted that none of the cations at the levels tested had any inhibitory effects upon the enzymatic reactions of ATX. Histidine therefore inhibits a process that is required for the hydrolysis of both nucleotides and phospholipids. This may be a rate-limiting cation-dependent step in their common reaction mechanism [We tested the effects of a number of divalent cations in both the presence and absence of histidine upon the PDE and LPLD activities of ATX Fig. . Neither++ reversed the inhibitory effect of histidine upon ATX enzymatic reactions, we tested its effect upon the histidine-induced inhibition of ATX- and LPA-stimulated motility. As shown in Fig. ++, or both together had no effect upon LPA-induced motility. In contrast, ATX-induced motility was affected in a more complex manner. Histidine (20 mM) alone inhibited ATX-induced motility by ~65%, while 0.25 mM Zn++ alone increased this same motility by ~30%. When these same concentrations of histidine and zinc were added together to an ATX-stimulated motility assay, the histidine inhibition was largely reversed with greater motility than seen with ATX alone, though not quite up to levels seen with ATX + Zn++. However, statistical analysis of these results revealed no statistically significant difference between ATX + Zn++ + histidine vs. ATX + Zn++. In contrast, there was a statistical significance between ATX + Zn++ + histidine vs. ATX + histidine (p < 0.001).Since Zn++, alone or in addition to histidine. Zn++ alone had no significant effect on the Vmax or Km of the reaction. In the presence of histidine, Zn++ reversed the inhibition, restoring Vmax to untreated levels. It might be noted that the pattern of inhibition seen when histidine is added is typical of a non-competitive inhibitor.Fig. ++), the possibility arose that the imidazole ring of histidine acts as a weak chelation agent, competing with the enzymatic active site for binding to the metal ion. EDTA has been shown to inhibit the nucleotide phosphodiesterase and pyrophosphatase activities of PC-1/NPP1 [++ and with Zn++.Because the histidine-induced inhibition of ATX activities could be reversed by addition of appropriate metal ions  for both LPLD and PDE activities, while an equimolar concentration of Ca++ resulted in ~75% recovery of control activity.In a series of preliminary experiments (data not shown), we found that, under the conditions of our enzymatic assays, addition of 10 – 20 mM Na++ [++ resulted in a 70 – 80% recovery compared to control values, while adding up to 5 mM Ca++ had no significant effect upon phenanthroline-induced inhibition of activity. As can be seen in Fig. Addition of 0.5 mM 1,10-phenanthroline also profoundly inhibited the LPLD activity of ATX  in about 15 – 20 min, and 1,10-phenanthroline inhibited cellular adhesion at concentrations utilized for inhibition of LPLD and PDE activity. Therefore, we were unable to obtain motility data in the presence of these agents.Testing the effect of these chelating agents on motility was problematic because chelation agents have multiple, complex effects upon living cells. For example, NaA number of histidine-derived agents, as well as histamine and imidazole Fig. , were teAs seen in Fig. Among the five histidine analogs found to inhibit ATX LPLD activity, the relative inhibitory activity is: D-histidine = L-histidine > histidine methyl ester >> N-methyl histidine > histidinamide. The effects of all of these agents are reversed by zinc. In contrast, glycine, L-alanine, imidazole, histidinol, and N, N-dimethyl histidine had no significant effect on activity; and histamine appeared to be slightly stimulatory. Most of these histidine analogs, including D-histidine, histidine methyl ester, histidinamide, N, N-dimethyl histidine, and histamine, were toxic to cells. N-methyl histidine resulted in reduced adhesion to our gelatin-coated membranes, precluding an effective motility assay. Only imidazole could easily be tested for its effect on ATX-stimulated motility. At 10–20 mM concentrations, imidazole had no significant effect on ATX-stimulated motility (data not shown).++ to the motility assays. Pre-incubation of ATX and LPC in the presence of L-histidine, followed by heat-killing the ATX, also resulted in much decreased activity, suggesting that L-histidine inhibits ATX-stimulated motility by ablating its LPLD activity. This hypothesis was in fact confirmed both by direct enzymatic studies in which L-histidine inhibited both PDE and LPLD activities and by the failure of ATX, in the presence of L-histidine, to produce an inhibitor of LPA-stimulated motility. Again, addition of Zn++ abrogated this inhibition of enzyme activity. These data provide further evidence that the LPLD activity of ATX, which results in the production of the mediator LPA, is essential for ATX stimulation of cellular motility.We have shown that L-histidine, at concentrations that are innocuous to cells, can inhibit the motility-stimulating action of ATX upon two tumor cell lines derived from human melanoma (A2058) and human ovarian carcinoma (SKOV-3). This inhibition is largely abrogated by addition of 0.25 mM Zn++, Mg++, Zn++ and Co++ to reverse the histidine-induced inhibition of ATX enzymatic activities. Neither Ca++ nor Mg++ reversed the inhibitory effect of histidine, whereas Co++ alone stimulated a 50% increase in PDE and a 300% increase in LPLD activities of ATX. Histidine partially reversed both of these Co++-stimulated increases: PDE activity was reduced to below uninhibited levels of product while LPLD activity, though reduced by 50% compared to treatment with Co++ alone, remained at levels above untreated controls. The mechanism by which cobalt activates ATX remains unexplained; however, Co++ has long been reported to replace one or more zinc cations in a variety of zinc-bound metalloenzymes [The role of metal cations in the activation of ATX was further investigated by first comparing the capacity of Caoenzymes -23, someoenzymes ,25.++ at concentrations as low as 0.25 mM abrogated the inhibitory effects of 10 mM histidine upon both the PDE and LPLD activities of ATX. This 40:1 ratio of ligand to cation appears to be inconsistent with a simple stoichiometric coordination of the cation with the metal-binding imidazole moiety. This would predict that the maximum number of ligand groups to coordinate with a Zn++ would be six. Our result is, therefore, difficult to explain as simple chelation in solution between cations and histidine. Perhaps, Zn++ acts upon ATX in a manner that blocks the entry of histidine into the active site. For example, Zn++ might coordinate with an electronically available locus in proximity with the active site of ATX or it might induce conformational changes in ATX that lowers the affinity of free histidine for the active site. Another possibility is that Zn++ replaces another metal ion, resulting in a binding conformation with a lower affinity for L-histidine. Interestingly, 0.25 mM Zn++ appeared to have a slightly stimulatory effect upon ATX-induced motility, but not LPA-induced motility. This suggests that Zn++ might act in a way that stabilizes ATX in an active configuration.In contrast, Zn++ or Zn++ plus Mg++ incorporated into their catalytic site, although a number of other metal requirements have been documented [4-EDTA and 1,10-phenanthroline both inactivate ATX, confirming that it is a metalloenzyme. Na4-EDTA complexes with a variety of cations, including transition metals as well as alkali and alkaline earth metals, and is thought to inactivate metalloenzymes by removing the metal cation from its binding site. Under the conditions of our assays, the IC50 of EDTA was ~5 mM. This inhibition was completely reversed by addition of equimolar Zn++ and significantly reversed (about 75% recovery) by addition of equimolar Ca++. In contrast, 1, 10-phenanthroline has more complicated and diverse mechanisms of action. When utilized with metalloenzymes, it can form mixed complexes with the metal ions as well as other cationic sites on the protein, resulting in inactivation of the enzyme but not necessarily removal of the metal cation [++ (approximately 1:10) to reverse its inhibitory effect on ATX. Based on all of our data with metal cations, it appears that Zn++, Co++ and perhaps Ca++ can function as the metal moiety in at least one of the two metal binding sites [Many members of the alkaline phosphatase superfamily of metalloenzymes have Zncumented ,26. The l cation . Like hing sites  of the a++-binding groups in matrix metalloproteinase inhibitors indicated that slight changes to the Zn++-binding groups can result in major changes in efficacy of inhibition [In order to determine what portion of the histidine molecule was responsible for its inhibitory activity, we utilized a number of commercially available histidine analogs. These analogs were predominantly substituted on the alpha carboxyl and alpha amino groups of histidine; but they also included histamine, which lacks the alpha carboxyl group altogether, and imidazole, the weakly chelating ring that makes up the major portion of the histidine side chain. Except for D-histidine, none of the other imidazole-containing compounds were as inhibitory as L-histidine. Among the 5 agents found to have significant inhibitory activity, the relative potency is as follows: D-histidine = L-histidine > histidine methyl ester >> N-methyl histidine > histidinamide. Methylation of the alpha amino group of histidine resulted in a stepwise loss of potency, with a single methylation (N-methyl histidine) resulting in about a 40% reduction in activity and a double methylation (N, N-dimethyl histidine) not significantly different from untreated control reactions. Since these two compounds should retain the positive charge properties of the native alpha amino group, this could be a steric effect. Similarly, change in the carboxyl group (particularly amidylation or reduction) also decreased the inhibitory potency, though that of esterified histidine methyl ester was only slightly reduced. Interestingly, imidazole itself, a moiety postulated to coordinate with the cation at the active site of ATX, was not effective at the tested concentrations. Likewise, amino acids, which lacked imidazole on their side chains , were also ineffective as inhibitors. Clearly, three functional groups of histidine are required for full inhibitory activity: the alpha amino group, the alpha carboxyl group, and the metal-binding imidazole side chain. Recent work with Znhibition , suggest++ metal cations. Our data suggest that the L-histidine-induced inhibition of the ATX enzymatic activities is predominantly non-competitive, i.e. Vmax is decreased significantly, while Km is not significantly affected. Furthermore, the mechanism of action of L-histidine does not appear to be simple stoichiometric chelation of the metal cations within a metalloenzyme but is more likely a complex interaction with a variety of moieties, including the metal cation, at or near the active site. At concentrations required for an inhibitory effect, most available histidine analogs resulted in loss of cell viability. Free L-histidine, therefore, appears to be unique in its ability to inhibit LPLD, and hence regulate a major source of LPA, in living systems. Since LPA has significant pathological effects, the regulation of its formation is of considerable interest. Potential problems with L-histidine as a therapeutic agent include its lack of potency and its conversion in vivo to histamine. While there are known inhibitors of histidine decarboxylase, such as the polyphenols of green tea [ATX, the major source of plasma LPA, has been implicated in a number of physiological and disease-related processes , includireen tea , potent,L-histidine inhibits the LPLD activity of ATX at millimolar concentrations, reducing its capacity to produce its major mediator, LPA.4-EDTA, and 1,10-phenanthroline were from Sigma-Aldrich (St Louis, MO). N-methyl histidine was from Bachem Bioscience (King of Prussia, PA).LPA (18:1) and S1P were purchased from Biomol Research Laboratories, Inc. (Plymouth Meeting, PA). LPC (18:1), SPC, N-ethyl-N-(2-hydroxy-3-sulfopropyl)-m-toluidine (TOOS), 4-aminoantipyrene (4-AAP), horseradish peroxidase, choline oxidase, p-nitrophenyl-TMP, L-histidine, D-histidine, imidazole, histamine, histidinamide, histidine methyl ester, N,N-dimethyl histidine, histidinol, NaA2058  and SKOVHighly purified recombinant human ATX (vATX), cloned from an MDA-MB-435 cell library, was prepared from a Vaccinia viral lysate, as described previously, through the concanavalin A-agarose step .6 cells/ml in DMEM supplemented with 1 mg/ml bovine serum album (DBA). Ten min before the start of the assay, appropriate concentrations of potential inhibitors were added to the different treatment groups. Chemotaxis was assayed as described previously in detail [Cells were detached from their flasks with a brief exposure to 0.05% trypsin and 0.02% versene and then resuspended at 2 × 10n detail , utilizi3 or HCl, as appropriate. The inhibitor was added to the reaction mixture; then, reactions were initiated by adding ATX.Enzyme activities were determined using a modification of the previously described assays . Briefly2, 0.3 mM N-ethyl-N-(2-hydroxy-3-sulfopropyl)-m-toluidine (TOOS), 0.5 mM 4-aminoantipyrene (4-AAP), 5.3 U/ml horseradish peroxidase, and 2 U/ml choline oxidase was added to the 50 μl reaction mixture and incubated for 20 min at 37°C. Absorbance was read at 555 nm and converted to nmoles of choline by comparison to a choline standard curve (A555 × 17 = nmoles).For determination of 5'-nucleotide PDE activity, reactions were stopped by the addition of 450 μl 0.1 N NaOH and the nitrophenol product was detected by reading the absorbance at 410 nm (A410 × 64 = nmoles). In order to determine LPLD activity, released choline was detected as follows: a 450 μl cocktail containing 50 mM Tris-HCl (pH 8), 5 mM CaClATX AutotaxinDBA DMEM with 1% bovine serum albuminDMEM Dulbecco's Modified Essential MediumLPA Lysophosphatidic acidLPC LysophosphatidylcholineLPLD Lysophospholipase DNPP Nucleotide pyrophosphatase and phosphodiesterasePDE PhosphodiesterasepNp-TMP p-Nitrophenyl-TMPS1P Sphingosine-1-phosphateSPC SphingosylphosphorylcholineTC carried out the enzymatic studies, EK performed cellular studies with A2058 cells, MP performed cellular studies with SKOV-3 cells, and RWB carried out background studies and fine-tuned methodology. ES originated the idea of studying the effect of L-histidine on LPLD activities. LAL and MLS analyzed and interpreted data. MLS drafted and coordinated the manuscript between authors. All authors participated in reading and refining the manuscript drafts.