Only a small percentage of patients with Alzheimer's disease benefit from current drug therapy and for only a relatively short time. This is not surprising as the goal of these drugs is to enhance existing cerebral function in Alzheimer patients and not to block the progression of cognitive decline. In contrast, immunotherapy is directed at clearing the neurotoxic amyloid beta peptide from the brain that directly or indirectly leads to cognitive decline in patients with Alzheimer's disease. The single trial of active immunization with the amyloid beta peptide provided suggestive evidence of a reduction in cerebral amyloid plaques and of stabilization in cognitive function of half the patients who developed good antibody responses to the amyloid beta peptide. However, 6% of actively immunized Alzheimer patients developed sterile meningoencephalitis that forced the cessation of the clinical trial. Passive immunotherapy in animal models of Alzheimer's disease has provided similar benefits comparable to those seen with active immunotherapy and has the potential of being effective in the half of Alzheimer's disease patients who do not make a significant anti-amyloid beta peptide antibody response and without inducing T-cell-mediated encephalitis. Published studies of 5 patients with sporadic Alzheimer disease treated with intravenous immunoglobulin containing anti-amyloid beta peptide antibodies showed that amyloid beta peptide was mobilized from the brain and cognitive decline was interrupted. Further studies of passive immunotherapy are urgently required to confirm these observations. The headline "Minimal benefit is seen in drugs for Alzheimer's disease" summarized an article in the New York Times concerning drug therapy of Alzheimer's disease . The ineIn contrast to today's drug therapy for Alzheimer's disease, immunotherapy is directed at the neurotoxic amyloid beta peptide that directly or indirectly leads to cognitive decline in patients with Alzheimer's disease. Most investigators believe that the accumulation of amyloid beta peptide in the brain of elderly adults is not only a hallmark of Alzheimer's disease but is the primary cause of cognitive decline . There iInduction or infusion of anti-amyloid beta peptide antibodies prevents the accumulation of cerebral amyloid beta peptide from the brain of mouse models of familial Alzheimer's disease and may work in humans with sporadic Alzheimer's disease ,7. Even th century in China to protect from virulent smallpox infection [Immunity was first recognized by the fact that people who recovered from an infection were often protected from re-infection. Thus, Thucydides wrote of the Athens epidemic of plaque that occurred in 430 BC "the same man was never attacked twice – at least fatally" . Twelve nfection  and brounfection . Despiteth century the link between the fine complexion  of milkmaids and their exposure to cowpox (vaccinia) was recognized [The next advance in immunotherapy followed the realization that exposure to a related, less virulent, infectious organism such as cowpox, protected individuals from the virulent pathogen, smallpox. In England during the second half of the 18cognized . But it cognized . In the cognized . Most vath century, von Behring and Kitasato discovered that immunity to diphtheria and tetanus was conveyed by serum antibodies against the exotoxins of these bacteria [th century. The first successful application of immunotherapy to humans occurred in 1891 when a child suffering from diphtheria was cured by an infusion of horse serum containing anti-diphtheria antibodies. The horse serum containing anti-toxin antibodies could be lifesaving although many patients, receiving large doses of xenogeneic proteins, developed serum sickness resulting from the patients' immune response to the foreign serum. During the first part of the 20th century passive immunotherapy of other infectious diseases including pneumococal pneumonia entered clinical practice but was replaced when antibiotics became available during the second third of the 20th century.At the end of the 19Today, passive immunotherapy is attracting renewed interest as a new means to treat neurodegenerative, infectious, autoimmune, and neoplastic diseases ,20,21. PImmunotherapy of Alzheimer's disease followed the development of a mouse model of familial Alzheimer's disease. In 1995, an APP-transgenic mouse expressing a mutant, human APP gene isolated from a Swedish family with inherited Alzheimer's disease was developed . These mThese observations offered great promise for the treatment of patients with familial Alzheimer's disease and, perhaps, elderly patients with sporadic Alzheimer's disease. A clinical trial of active immunization of elderly patients with sporadic Alzheimer's disease was organized and initiated in 2001. However, there were reasons to question whether the benefits seen in a middle-aged mice model of familial Alzheimer's disease could be directly extrapolated to elderly patients with sporadic Alzheimer's disease.First of all, aging is associated with a decreasing immune response . Thus, aThe clinical trial of active immunization of patients with Alzheimer's disease with amyloid beta peptide, started in 2001, was stopped a year later after 4 patients in the actively immunized group developed sterile meningoencephalitis . ApproxiNo comprehensive report of the clinical study of active immunization has yet been published but oral presentations and published results from a subset of actively immunized Alzheimer's disease patients have provided some information . It appeIn summary, active immunization with amyloid beta peptide in elderly patients with Alzheimer's disease appears to be less effective and more toxic than in the middle-aged APP-transgenic mouse model of familial Alzheimer's disease. These differences may reflect the greater age of the patients with sporadic Alzheimer's disease and the decreased antibody responses to vaccines and the paradoxical increase in autoimmune responses in the elderly..Administration of anti-amyloid beta peptide antibodies would bypass immune senescence and would not be expected to lead to T cell-mediated encephalitis. Furthermore, anti-amyloid beta peptide antibodies not only dissolved aggregates of amyloid beta peptide in vitro but also inhibited aggregated amyloid beta peptide-mediated cytotoxicity in vitro . In vivoThe potential benefit of anti-amyloid beta peptide antibodies in humans with sporadic Alzheimer's disease was also inferred from studies of cognitive function in a subset of actively immunized patients with Alzheimer's disease . In thesPassive immunotherapy of Alzheimer's disease would require repeated administration of anti-amyloid beta peptide antibodies. For this reason, human anti-amyloid beta peptide antibodies should be used to prevent an immune response to the currently available murine monoclonal immunoglobulins. Several methods are known to obtain human anti-amyloid beta peptide antibodies: (i) purification of specific antibodies from human IVIg; (ii) humanization of murine anti-amyloid beta peptide antibodies by replacing framework portions of the murine anti-amyloid beta peptide antibodies with human framework sequences using recombinant DNA technology ; (iii) gHuman IVIg, purified from human plasma, was initially developed as replacement therapy for immunodeficient patients but IVIg has also been shown to be effective therapy in patients with a variety of autoimmune diseases . RecentlThere is no evidence that anti-amyloid beta peptide antibodies induce sterile encephalitis, observed following passive immunization of several strains of APP-transgenic mice or in the small number of elderly patients with Alzheimer's disease. However, it may be premature to conclude that passive immunotherapy with anti-amyloid beta peptide antibodies does not induce cerebral pathology. It should be remembered that most of the APP-transgenic mice strains tested do not develop amyloid vascular deposits (congophilic angiopathy) that occurs in elderly patients with Alzheimer's disease. It was reported that infusion of murine anti-amyloid beta peptide monoclonal antibodies specific for the N-terminal epitope of the amyloid beta peptide into a strain of APP-transgenic mice, which develop congophilic angiopathy, cerebral hemorrhage was observed . This unPre-clinical data and inferences drawn from immunotherapy in patients with sporadic Alzheimer's disease suggest that passive immunotherapy with anti-amyloid beta peptide antibodies is preferable to active immunotherapy for the treatment of elderly patients with sporadic Alzheimer's disease. However, which anti-amyloid beta peptide antibodies would have greatest therapeutic efficacy and least risk of untoward effects for patients with Alzheimer's disease remains to be determined. However, there is general agreement that anti-amyloid beta peptide antibodies to be administered repeatedly to patients should not stimulate an antibody response to the infused immunoglobulin. There is evidence that humans not only can make immune response to therapeutic antibodies but that such immune responses compromise the action of the therapeutic antibodies . To dateIf the therapeutic benefit of polyclonal human anti-amyloid beta peptide antibodies is confirmed, it remains to be determined which antibody or antibodies are responsible for the therapeutic effect. Whether a single monoclonal antibody will be effective in humans as it has been in APP-transgenic mice is not certain. In some infectious diseases, a single monoclonal antibody has not been less protective than a mixture of several monoclonal antibodies . Thus, wMonoclonal anti-amyloid beta peptide antibodies are known to differ in their fine specificity: isotype, affinity, as well as epitope, aggregate, and Fc specificity . WhetherMonoclonal anti-amyloid beta peptide have different specificities. There are three major epitopes on the amyloid beta peptide: (i) antibodies to the N-terminal epitope (amino acids 1–6) of the amyloid peptide bind to aggregated amyloid beta peptide in vitro as well as cerebral and vascular deposits in vivo and APP (ii) antibodies specific for the central region (amino acids 15–25) of the amyloid peptide bind to APP but not to aggregated amyloid beta peptide in vitro, amyloid plaques or vascular amyloid deposits (iii) antibodies specific for the C-terminal region have been less well studied but reported to lack a therapeutic effect in APP-transgenic mice. This may be the reason why the N-terminal-specific anti-amyloid beta peptide antibodies but not central region-specific antibodies cause cerebral hemorrhage presumably from vessels with amyloid beta deposits .Anti-amyloid beta peptide antibodies that differ in epitope and Fc specificities, dissolve cerebral amyloid plaques and block cognitive decline in APP-transgenic mice . Anti-amSurprisingly, treatment of APP-transgenic mice with anti-amyloid beta peptide antibodies specific for the central region of the amyloid peptide that do not stain cerebral amyloid plaques ex vivo and were not detectable within the brain also cleared cerebral amyloid peptide and plaques . A novelBoth N-terminal-specific and central region-specific anti-amyloid beta peptide antibodies but not C-terminal-specific anti-amyloid beta peptide antibodies also bind to APP the ubiquitous transmembrane cellular protein. C-terminal-specific anti-amyloid beta peptide antibodies can distinguish between amyloid beta 1–40 and 1–42 peptide. As amyloid beta 1–42 peptide is more neurotoxic peptide and forms the nidus of cerebral amyloid plaques antibodies to this amyloid beta peptide might be the most effective antibody for passive immunotherapy as they target the most pathogenic form of the amyloid beta peptide without binding to APP or the less pathogenic amyloid beta 1–40 peptide. However, the C-terminal specific anti-amyloid beta peptide antibodies have been reported not to clear cerebral amyloid beta peptide . RecentlFinally, there is considerable interest in the greater neurotoxicity of soluble amyloid beta peptide oligomers than either the amyloid beta monomers or fibrils . If thisPassive immunotherapy of sporadic Alzheimer's disease offers the potential of reversing the pathologic accumulation of cerebral amyloid beta peptide. To date the only preparation of human anti-amyloid beta peptide antibodies that have been reported to reverse cognitive defects in patients with sporadic Alzheimer's disease are polyclonal anti-amyloid beta peptide antibodies contained in human IVIg. Selection of human anti-amyloid beta peptide antibodies for clinical trial can be tested for therapeutic effect in vivo by their treatment of immunodeficient APP-transgenic mice.The authors declare that they have no competing interests.


Recently, mass spectrometry data have been mined using a genetic algorithm to produce discriminatory models that distinguish healthy individuals from those with cancer. This algorithm is the basis for claims of 100% sensitivity and specificity in two related publicly available datasets. To date, no detailed attempts have been made to explore the properties of this genetic algorithm within proteomic applications. Here the algorithm's performance on these datasets is evaluated relative to other methods.In reproducing the method, some modifications of the algorithm as it is described are necessary to get good performance. After modification, a cross-validation approach to model selection is used. The overall classification accuracy is comparable though not superior to other approaches considered. Also, some aspects of the process rely upon random sampling and thus for a fixed dataset the algorithm can produce many different models. This raises questions about how to choose among competing models. How this choice is made is important for interpreting sensitivity and specificity results as merely choosing the model with lowest test set error rate leads to overestimates of model performance.The algorithm needs to be modified to reduce variability and care must be taken in how to choose among competing models. Results derived from this algorithm must be accompanied by a full description of model selection procedures to give confidence that the reported accuracy is not overstated. When Petricoin et al.  publisheThe specifics of the genetic algorithm used here are based on webpages at the NCI-FDA website housing the data  and 1,9,91,9. Asm/z values. In the GA framework such a collection of markers is called a chromosome. Each chromosome is evaluated by a fitness function in the following way. Suppose a given chromosome is composed of N "genes" . Each sample's intensity values at the N genes are linearly scaled to lie between 0 and 1; the smallest of the N intensities is assigned 0, the largest assigned 1, and intermediate values interpolated in a linear way. The first sample is assigned its own cluster with centroid  given by its N values. The next sample is compared to the first and if the Euclidean distance between the two samples exceeds .1· then the second sample is assigned a new cluster with centroid given by its values. If the distance is less than this limit the second sample is assigned to the first cluster and the centroid values recalculated as the mean of both cases. Subsequent cases are handled similarly – if a sample's representation as an N dimensional point lies within the .1· limit of a cluster the case is assigned to the closest cluster and centroid values are recalculated. If the smallest distance to any cluster centroid exceeds the limit then the case is assigned a new cluster. When all the cases are clustered a cluster's type is designated by majority vote – those clusters composed mostly of cancer cases are deemed cancer clusters and those composed mostly of nondiseased are likewise defined. The fitness function then computes the chromosome's fitness as its classification accuracy, i.e. the proportion of cases assigned to a cluster of the appropriate type.• As described, the genetic algorithm (GA) seeks to find a collection of markers that separate cases and controls. Here the markers correspond to a biological sample's measurements at a given set of • The selection process starts with 1500 randomly chosen chromosomes, i.e. sets of markers. The documentation indicates that chromosomes with length between 5 and 20 markers are used. In this implementation, different chromosomes may have different lengths – the 1500 are chosen to have a length between 5 and 20 with a uniform probability of 1/16 governing the choice. It is not clear how the original GA treated chromosomes of different length.α and β such thatEach of the 1500 chromosomes is evaluated by the fitness function as described above. Chromosome pairs are then produced with the likelihood of being selected for a pair related to the fitness function. The available documentation does not make clear how this probability is explicitly related to the fitness. Here the choice was made by ranking the fitness scores and setting parameters Prob [ selecting kth ranked chromosome ] = α + βkα and β were chosen such thatwhere This approach is described in section 2.1 of  – rankinm/z locations = (2500, 4200, 909, 15002) and the first chromosome breaks between its second and third elements while the second chromosome breaks after its third. Then the resulting new chromosomes are (3001, 5500, 15002) and (2500, 4200, 909, 7800, 11011, 13059). In this way the 750 pairs of chosen chromosomes produce a next generation of 1500 chromosomes. At this point each gene in each new chromosome may be randomly changed to any other gene in the entire spectrum range with probability .0002 (this corresponds to genetic mutation). In our implementation it is possible to match sub-chromosomes that would merge to be longer than 20 units. In this event the chromosome is truncated to 20. Further, here it is allowed to have chromosomes composed of as few as 2 markers as there seemed no compelling reason to impose a lower limit of 5 m/z values as described in the documentation. It is unclear if the original GA allowed chromosomes of different lengths to reproduce or instead restricted cross-overs to pairs with the same length.• A new generation of chromosomes is produced by first creating 750 parent pairs from the set of 1500 chromosomes. A parent pair is created by choosing two of the 1500 chromosomes using the above probabilities. A given chromosome can be chosen to be in more than one pair. For a given pair each chromosome is broken to produce two sub-chromosomes. The location of the break is random with uniform probabilities. The two sets of sub-chromosomes are then crossed-over to produce two new chromosomes. As an example suppose chromosome 1 has genes = (3001, 5500, 7800, 11011, 13059) and chromosome 2 is composed of • After mutation this new generation of 1500 chromosomes is then evaluated by the fitness test and then another round of selection, cross-over, and mutation processes produce the next generation. Typically, the average fitness of generations increases over time. According to the documentation, the process stops 1) after 250 generations, or 2) when a perfectly discriminating chromosome is found. In the first instance, that model that has produced the highest fitness score is chosen.; otherwise assign the case as of a third, unknown/new type. In this current work, classification errors for a test set correspond to the first criteria of nearest centroid, without the .1· requirement. Empirically, this led to greater classification accuracy.• Given a chosen model derived from a training set, an unlabeled spectrum (e.g. test set spectrum) is classified by determining that cluster with the centroid that lies closest to the unlabeled case and assigning the label of the cluster. The documentation describes a second, related approach that is to make this assignment only if the nearest centroid is with .1·Some concerns about this algorithm have been raised by others ; a few i• Each chromosome is evaluated by a fitness function that measures how well the chromosome classifies the training set. However it is clear that the order in which the cases are considered may make a difference in what cluster a case is assigned as well as the clusters' centroid values. Consequently, different results may arise in attempts to replicate findings.• The GA algorithm starts with a random selection of 1500 chromosomes and then letting these evolve through a random mating process. As the initial selection and evolutionary process is random it is again the case that different ultimate models may be chosen, depending on the seed of a random number generator. apart from one another. It is not uncommon to find chromosomes that partition perfectly, but rely upon a large number of clusters (e.g. > 30). This suggests overfitting of data. As described, this algorithm does not penalize or otherwise take into account the number of clusters or length of chromosomes.• In this application, each chromosome partitions the samples of the training set into clusters defined as groups of cases with centroids that are at least .1·Largely because of insufficient information, this implementation of the algorithm likely differs from that supporting the published results. However, some elements should be the same. In particular, the evaluation of the fitness function should yield the same results except for the issue of how the order of the cases can change the clusters' attributes. Therefore, we should be able to match or come close to verifying the published results for a given model. However, our results are likely to be different as far as generating best models. This is in part due to the inherent randomness the process employs as well as possible differences in how the fitness function scores generate members of the next generation.Two publicly available datasets were used to evaluate the algorithm; information regarding them is available from an NCI-FDA website . Both daFor both datasets GA-produced models are presented on the NCI-FDA website that were developed from a training set and perfectly discriminate a test set. There is no designation as to which individuals were used for training and which for testing.m/z values {435.46, 465.57, 2760.67, 3497.55, 6631.70, 14051.98, 19643.41} was able to perfectly discriminate a test set drawn from the low resolution dataset, DSl. The 253 samples were randomly split into a training set of 81 cancer and 46 control individuals with the remainder forming a test set. Here we illustrate how the test set looks for these seven markers. Figure The NCI-FDA website shows the chromosome consisting of This exercise verifies that the model does quite well though it establishes that results do change with ordering and test/training set splits. Also, it confirms that results of 100% accuracy should be understood to depend upon the particular split and ordering. This may be of great importance when the goal is to develop tests with sensitivity and specificity exceeding 99% .Next, the GA developed for this paper was then applied to these data with the expectation it should produce something like the 7 marker chromosome given above. After 7 generations, a chromosome was found that perfectly split the training set, but 7 clusters were required and 10 markers were used.The graph of test set classification, Figure In each case a perfectly discriminating (i.e. training set error of 0%) chromosome was found within a few generations. Table The results in Table Table Fitness = Accuracy= % Correctly classified cases.This could now be modified toFitness = % Correctly classified casesp1·# of clusters- p2·# of markers- p1 and p2 are non-negative penalization weights.where p1 among {0, .002, .005, .008} and p2 in {0, .001, .002}. Specifically, random training samples (chosen without replacement) were selected from the entire set of samples so the original training sample size of 127 was maintained with 81 cancer and 46 control spectra. Then, for a given pair of p1 and p2 values the GA was trained on this pseudo-random training set and a model chosen. The remaining cases that were omitted from the training set (81 cancer and 45 control) were then treated as a test set. We repeat this procedure for 50 randomly chosen training sets and examine the distribution of the test set classification accuracy for the different parameter combinations. The same 50 training and test sets were used for each set of p1 and p2 combinations. In addition to illustrating the test set accuracy, the number of clusters, the number of markers associated with the different GA models, and the proportion of times (out of 50) a perfectly discriminating chromosome was found (for the training set) are also indicated.A resampling method was used to determine the performance of different parameter combinations of p1 and p2 combinations performed best in terms of predicting the omitted cases (in the event of ties the model associated with the most restrictive p1 and p2 was chosen with p1 the first tie-breaker). The chosen parameters were then used with the entire training set to develop a model that was evaluated on the associated test set. As before, this procedure was performed on the same 50 training and test sets. In the tables that follow, the results for this model are labeled as "Best GA". These results are perhaps most representative of overall performance for the algorithm developed here.This procedure gives a sense for the performance of the algorithm for different parameter combinations. Another question concerns performance if model selection were incorporated into the procedure. This was assessed in the following way. For each of the 50 training sets, an additional 5-fold cross-validation determined which of the 12 m/z values showing Bonferroni-corrected differential expression . Computer code and information regarding the parameters and details of these methods are available on a webpage [As a means of comparison two other classification schemes were applied to the same bootstrap samples. Boosting is a general method of combining a weighted set of classifiers that each "vote" on the class of a sample in question with majority vote dictating the set's aggregate classification. It has been successfully used in classification of mass spectrometry data ,13. Here webpage  with supth and 75th percentiles for test set accuracy among 50 samples as described above. The two penalty parameters have the desired effect in reducing the number of clusters/markers but there is relatively small variation over the different parameter combinations. The GA models apparently perform a bit better than PAM and a little worse than the boosting method though all models have high accuracy. Some reviewers of these data [m/z range should be used. The criticism centers around the strong signals that are present in very low m/z values  that are speculated to be products of experimental procedures rather than reflective of biological differences. Other investigators [m/z range restricted to be greater than 1500 Daltons.Table ese data , have qum/z restricted dataset and shows evidence of greater spread among the different GA models – those with p1 = 0 or .008 do not appear to do as well as p1 = .002 or .005. With no penalty on the number of clusters one sees very high dimensional models (median number of clusters > 90), perfect training set performance every time, and relatively poor test set performance indicating some type of penalization is necessary. Increasing the value of p2 has the desired effect of yielding more parsimonious models without an obvious decline in performance. As before, the GA models seem to perform better than PAM but less well relative to the boosting model.Table m/z values in the 700 – 12,000 Dalton range while other samples have about 330,000 data points. This discrepancy is particularly worrisome as the cancer samples appear more likely to have fewer datapoints. The information presented at the NCI-FDA website and in [Next, results from the high resolution dataset are presented. The data require preprocessing. Some samples contain raw data from approximately 370,000 e and in . After am/z >1500 range in that poorly performing high dimensional models are associated with p1 = 0 and the GA appears to again perform at an intermediate level.The results in Table m/z > 1500 and DS2) those models produced with p1 = 0 are associated with a large number of clusters (median ≥ 90), indicating that many clusters have only 1 or 2 individuals. As demonstrated above, a resampling approach shows that models with large numbers of clusters will generally not perform as well as more parsimonious chromosomes and the use of penalization parameters greatly improves performance.As implemented here, the genetic algorithm without penalties produces a large number of chromosomes that can perfectly discriminate a training set of the type considered here. For the last two analyses  that have no such reliance on random processes and will produce the same answer given a fixed dataset and parameters. Some methods such as decision trees and PAM employ cross-validation as part of their fitting process and therefore do have a random component, but the results are not nearly so variable, at least for the data considered here. Next we explore some consequences when the GA is repeatedly applied to a fixed training and test set with the goal of finding "best" or superior models. Such repeated examination of test set performance violates the principal of evaluating the test set only after the model has been selected .Given a model developed on a training set, the performance of such a model on an independent test set is an unbiased estimate of its performance when exposed to a subsequent group of unlabeled cases that are generated by the same process. However, the situation becomes more complicated when a collection of models is considered. It is generally not true that the best performing model (judged by which model attains highest test set accuracy) will reproduce similar results on a yet another group of cases. Essentially, while every model has a true error rate, its performance on a particular test set is a function of both the true error and random variation. The best performing model is likely the beneficiary of positive random variation that is unlikely to be repeated in application to yet another set of data. In this sense the best performing model has an underestimated error rate when the selection of the best model is performed via repeated examination of a test set. We present a final set of bootstrap based analyses to illustrate the degree of bias.Xb while the original cohort is X. This bootstrap sample is then split into training (81 cancer, 46 control) and test sets (81 cancer, 45 control). On the training part of the bootstrap sample the GA is run with p1 = .005 and p2 = .001. These parameters were chosen as they seemed to perform relatively well in Tables . The performance of that model was then evaluated by the error rate in the test set portion of the bootstrap sample, denoted . Because the GA process produces different estimates when run on the same data due to randomness as described above, the model-fitting process is then repeated 19 more times on the same bootstrap sample to obtain 20 different models  and 20 different measures of performance . The order of the training set and random sampling decisions made by the GA were allowed to vary though the composition of the test and training set were fixed for a given bootstrap sample. The best model, denoted , was chosen as that among the 20 with lowest classification error, . In the event of a tie, the number of clusters served as a tie-breaker . This procedure is meant to mimic the idea of applying 20 models to the test set and settling upon the best one. To get an idea of the bias in estimation error we then examine how the chosen, best model performs for the original cohort of 253 cases – this error rate is denoted as  and the bias estimated by . This procedure was performed 50 times and one obtains an estimate of the distribution of the bias fromFor DS1, 50 runs of the following type of experiment were performed. First, a bootstrap sample of size 253 with 162 cancer and 91 controls is drawn . This is denoted as m/z range, 2) DS1 restricting the range to m/z > 1500, and 3) DS2 with 700 <m/z < 12000 (using different corresponding sample sizes). The use of the bootstrap to assess bias in this way conforms to the notion of treating the full sample distribution like a population distribution and the bootstrap sample distribution like the full sample distribution – see chapter 10 of [in 1) DS1 using the whole er 10 of .The results in Table m/z <20000 Daltons), the algorithms' performances will not change regardless of the answer to this question. Therefore, in the limited context of algorithmic performance considered here this critical issue is of secondary importance and not addressed. This observation indicates that these algorithmic analyses may still be valuable even if one believes the datasets to be flawed.There is considerable controversy regarding these ovarian cancer datasets – particularly with respect to whether the multitude of models with high or perfect sensitivity and specificity are more the result of rich complexity reflecting true biological variation ,20 or flm/z < 20000 Daltons) are easiest to correctly classify  was used to exclude the lower mass values that some [m/z values that can distinguish spectra. In this case one could speculate that repeated model fittings may identify primarily the same chromosome and therefore lead to very little bias.The truncated, low resolution dataset . While this can be a problem for classification algorithms in general, the random characteristics of this procedure may make it especially hard to resist. Here we saw some sense of the bias resulting from, such an approach. As the discussion regarding bias demonstrates, the reported sensitivities and specificities cannot be adequately assessed without very detailed description of the models' discovery. In this sense, those who employ such a scheme must supply complete information regarding the entire process used to choose the given models and users of algorithms that have this property of producing multiple models from a fixed dataset must be aware of this potential bias.Overall, once modifications have been incorporated to address the overfitting concerns, the algorithm's performance seems comparable to other methods. It should be noted that the final models produced by this GA are of a simple to interpret form that may be based on a small number of markers and clusters. This simplicity is not necessarily present for other algorithms . This algorithm seems a reasonable option for creating discrimination models though it does have disadvantages that might guide analysts to choose a different approach.The low resolution dataset, DS1, was obtained from a ProteinChip Biomarker System-II (PBS-II) surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) instrument produced by Ciphergen Biosystems, Inc. of Fremont, CA, USA using a WCX2 ProteinChip array, also produced by Ciphergen. Further details regarding sample handling and preparation are not readily available from the NCI-FDA website. While data from earlier low resolution datasets were available from the NCI-FDA website, these data (labeled 8-7-02) were chosen because the baseline does not appear to have been subtracted. As discussed by others  it does I, Applied Biosystems, Inc. Framingham, MA, USA) modified to read the WCX2 ProteinChip. Additional information regarding handling and preparation of samples is available in [The high resolution dataset, DS2, was obtained from a hybrid quadrupole time-of-flight mass spectrometer  and was the approach described in . This trFor the DS2 data, once the raw values were aggregated into 7106 bins the spectra were normalized to have the same average intensity. Here it seemed necessary to try to address the fact that the intensities for samples processed later were generally less than those processed earlier – see the QC document on the NCI-FDA website and . Again, Computing for all the classification algorithms (GA, boosting, and PAM) was done using the R programming language. Results for the PAM algorithm were obtained using the pamr package available from the R website . On the


Evolutionary autonomous agents are robots or robot simulations whose controller is a dynamical neural network and whose evolution occurs autonomously under the guidance of a fitness function without the detailed or explicit direction of an external programmer. They are embodied agents with a simple neural network controller and as such they provide the optimal forum by which sensorimotor interactions in a specified environment can be studied without the computational assumptions inherent in standard neuroscience.Evolutionary autonomous agents were evolved that were able to perform identical movements under two different contexts, one which represented an automatic movement and one which had a symbolic context. In an attempt to model the automatic-voluntary dissociation frequently seen in ideomotor apraxia, lesions were introduced into the neural network controllers resulting in a behavioral dissociation with loss of the ability to perform the movement which had a symbolic context and preservation of the simpler, automatic movement.Analysis of the changes in the hierarchical organization of the networks in the apractic EAAs demonstrated consistent changes in the network dynamics across all agents with loss of longer duration time scales in the network dynamics.The concepts of determinate motor programs and perceptual representations that are implicit in the present day understanding of ideomotor apraxia are assumptions inherent in the computational understanding of brain function. The strength of the present study using EAAs to model one aspect of ideomotor apraxia is the absence of these assumptions and a grounding of all sensorimotor interactions in an embodied, autonomous agent. The consistency of the hierarchical changes in the network dynamics across all apractic agents demonstrates that this technique is tenable and will be a valuable adjunct to a computational formalism in the understanding of the physical basis of neurological disorders. The conceptual framework by which a neurological syndrome such as apraxia is presently explained is based on a computational understanding of brain function. Briefly, this framework assumes the existence of well-defined, determinate perceptual representations and motor programs that interact in a fashion similar to the way that symbols are manipulated in a computer. Recent theoretical and applied work in natural and artificial systems, however, has conspired to shift the emphasis in neuroscience from the computational paradigm to a dynamical understanding of brain function -5. This The apraxias constitute a spectrum of movement disorders in which there is impairment in the performance of a skilled, learned movement that cannot be attributed to an elementary motor or sensory deficit. Based of the pioneering work of Liepmann , the aprThe standard conceptualization of apraxia is based on a two-system model of action: a conceptual system, located in the dominant parietal lobe, and a production system localized to the frontal lobe . DysfuncRegardless of whether the standard two-system scheme of action or the more detailed model based on multiple, specialized parietofrontal circuits is used, the standard conceptualization of the origin of apraxia still conforms to the computational paradigm in which a specific motor program is activated based on the conceptual framework in place in the dominant parietal lobe. Similarly, the usual explanation for the automatic-voluntary dissociation frequently seen in ideomotor apraxia relies on this computational framework. This framework postulates that a verbal command establishes a conceptual bias in the parietal lobe that activates the appropriate motor program in the frontal lobe. In ideomotor apraxia there would be a disconnection between the instruction and the effector mechanisms frontally. To explain the preservation of the corresponding automatic movement, alternative pathways not dependent on the parietal lobe would need to remain functional.Evolutionary autonomous agents (EAAs) are robots or robot simulations whose controller is a dynamical neural network and whose evolution is guided by a genetic algorithm. They are embodied agents-either software programs living in a virtual environment or true robots that function in a specified environment. These agents function autonomously in their environments with the agents performing such functions as navigation around obstacles, gathering food, seeking prey or mating partners.  Their deTo model the voluntary-automatic dissociation seen in ideomotor apraxia, a lesioned EAA needs to demonstrate a behavioral dissociation between a movement that the agent does automatically and an identical movement that has a symbolic context. An analysis of the change in network dynamics that occurs in the apractic EAA will provide information on the physical basis of the dissociation without the assumptions inherent in a computational formalism. The extrapolation of results in the EAA to human brain function is based on a principle concerning the organization of complex systems that has been emphasized by Herbert Simon. He suggested that the organization of self-organizing complex systems is dependent only on the behavioral characteristics of the system and not the nature of the constituent elements of the system. "My central theme is that complexity takes the form of hierarchy and that hierarchic systems have some common properties independent of their specific content" . RegardlThe presence of multiple time scales in the dynamics of a neural network is indicative of a temporal hierarchical structure. Simon discussed the presence of higher and lower frequency dynamics in complex systems and associated more executive function with the lower frequency components. He stated that "it is generally believed that the relevant planning horizon of executives is longer, the higher their location in the organizational hierarchy" and that "the average interval between interactions are greater at higher than lower levels ." In theA simulation platform, WEBOTS (Cyberbotics, Switzerland), was used to simulate the movement of a Khepera robot (K-TEAM Corporation, Switzerland) in a dark 1 m square arena without walls or obstacles. The Khepera is a two-wheeled mobile robot with eight ambient light sensors and a rotation encoder for each wheel. The Khepera also has eight infrared proximity sensors but these were not activated in the present study. The neural network controller was composed of a layer of 5 fully connected radial basis function units or neurons. In addition, each unit projected to the two linear units or motor neurons and received inputs from the eight light sensors and the two wheel encoders.A combined genetic and adaptation algorithm was used similar to that described by Urzelai and Floreano . BrieflyThe arena was maintained dark, except at random times when a light of constant intensity would appear at random locations. The robot had to attempt to reach the light. There were two tasks for the robot during each trial. In the first task, the robot simply had to go to the light when it appeared. The light remained on and was extinguished when the robot moved to within 2 body diameters, or 7 cm of the light. After a 1–3 s of random delay (in darkness) another light would appear in the arena at another random location requiring the robot to approach that light. This would continue for a total of 4–6 constant lights. The second task began after this series of constant lights. With the second task the robot had to go to the location of a brief light flash (1 s or 16 sensorimotor cycles in duration) that did not persist while the robot approached the location. Since the robot could not use light intensity to continuously guide its movement to the location, successful completion of this task required the robot to have some notion of objective orientation and distance. Each trial lasted a total of 75 seconds.F was defined as:The fitness function F = T (s)·nT (s) = 1 for s ≤ 1 andwhere T (s) = s for s > 1,n the number of lights reached, df the average distance of the robot from the flash point once the flash occurred, tf the time between flash onset and end of simulation, and ts the duration of simulation. Mutation rate was in the 0.2 – 0.5% range.Evolution was continued until the fitness plateaued. Three populations were evolved requiring up to 1300 generations before there was a clear plateau. Individuals in each population were screened for their ability to accomplish the tasks. Each screening trial was the same as the trials in which the robots were evolved, that is, a 75 second epoch during which the robot had to approach several sustained light locations followed by a single unsustained light flash. Invariably, individuals appeared first that were able to go to the sustained light but failed to respond to the light flash. Eventually, individuals with high fitness were found that were able to successfully complete both tasks. From this latter group, lesions were introduced into the neural networks and the subsequent individual was screened with the same 75 s trial. Individuals were subsequently identified in whom the lesion resulted in the loss of the ability to move toward the brief light flash with preservation of the ability to move toward the sustained light.The lesions that were introduced into the networks were inactivations of single synapses. Typically, an individual that could successfully accomplish both tasks was screened for apraxia by lesioning each synapse in the network and observing the subsequent behavior of that individual. Although individual neurons could have been inactivated, this approach was avoided because the network only had 5 neurons and the resulting lesioned individual often demonstrated gross motor deficits.Once individuals were identified which could successfully accomplish both tasks and in whom a specific lesion resulted in a dissociation between movement towards the sustained light and movement towards the light flash, their network dynamics were characterized in two ways. First, a fast Fourier transform (FFT) was performed on the activation pattern of all 5 neurons in the network. The time window chosen in the calculation of the FFT was the entire test epoch. The Hurst exponent was then calculated by the average wavelet coefficient method  for all Five agents were identified which were able to successfully accomplish both tasks and in whom a lesion resulted in the dissociation between the two tasks. Analysis was performed on all 5 of the neurons in each individual. Five trials were used in each individual to allow statistical analysis of the Hurst exponent data.Figures -7) for 24 of the 25 neurons, with the remaining neuron showing the same trend but not reaching statistical significance. The grand average of the 125 Hurst exponents  was1.0957 ± 0.2325 for the normal condition, and 0.8292 ± 0.1833 for the apractic condition.We computed the Hurst exponents of the 25 neurons from the 5 individuals drawn from 3 populations. Five trials were executed for each individual. When comparing the Hurst exponents for each neuron before and after the lesion, highly significant differences were obtained  in the hierarchical organization of the neural network Since the calculation of the Hurst exponent is based on the full test epoch and since most of the robot movement during this period was the movement to the constant light rather than the light flash, this result also demonstrates that the strategy for both movements was influenced by the lesion despite maintained ability to move to the constant light.Despite significant advances in the understanding of the anatomy and physiology of normal movement and the pathophysiology of movement disorders, their conceptual framework still relies on the computational paradigm used by cognitive science and neuroscience for decades. This approach assumes the existence of determinate structures in the CNS that are manipulated in the same fashion that a computer manipulates symbols or language combines words. In the last 10 years, there has been a shift in focus with appreciation of the limitations of the computational approach and the realization of the importance of embodiment in conceptualization of motor behavior. When the social and the environmental influences on behavior are analyzed without prejudice, it becomes clear that indeterminacy is a hallmark of our functioning  and the We have demonstrated that in an evolved agent with two modes of environmental interaction that can be viewed as automatic and symbolic, lesions that produce the equivalent of the automatic-voluntary dissociation seen in ideomotor apraxia cause a change in the hierarchical organization of its dynamical neural network controller with a loss of the longer duration time scales corresponding to the loss of symbolic function. Two techniques were utilized to demonstrate these changes in the network dynamics, a Fourier analysis of the activity of all 5 neurons in the network and the calculation of the their Hurst exponents. With Fourier analysis, EAAs that were able to successfully perform both tasks demonstrated a 1/f power spectral distribution. This type of scale free distribution has been encountered in a number of physical and biological systems including heart rate variability, electrical currents and reaction times in human cognition ,20. The Does the EAA paradigm described capture the essential features necessary to causally explain the automatic-voluntary dissociation seen in ideomotor apraxia? Ideally, to most reliably model this phenomenon, an EAA would need to have language capabilities. Barring that, it is argued that the ability to move to a target site without the continued visual presence of that target captures the minimal requirements necessary to extrapolate to the case of a verbal command. Although controversy exists concerning the conceptual or operational definition of internal representations in evolved agents ,23, ClarIt was clear while individual EAAs were being observed as they performed the trial in the normal and apractic conditions that the apractic robots often demonstrated minor deficits even in the case in which they were approaching the sustained light target. Usually, this took the form of a mild slowness in movement although other deficits were seen such as altered trajectories toward the sustained light source. It has been assumed that patients with ideomotor apraxia function normally in the environments to which they are accustomed and in which automatic behavior is expected. This has also been suggested as a reason why apraxia is not detected as frequently as its true incidence predicts . This clThe notion that a lesion that causes apraxia has a global effect on the patient that is not restricted to those functions that can be considered symbolic was elaborated in detail by Merleau-Ponty . He perfIn an embodied agent with two modes of environmental interaction which can be viewed as automatic and symbolic, lesions that produce the experimental equivalent of voluntary-automatic dissociation of ideomotor apraxia cause a change in the hierarchical organization of its dynamical neural network controller with a loss of the longer duration time scales corresponding to the loss of symbolic function. The identification of the dynamical changes in an apractic nervous system may provide a causally mechanistic explanation for the syndrome that may complement the higher-order descriptive explanation of the standard computational approach. The methodology of EAAs is just beginning to be recognized and it is hoped that further studies can be performed with this methodology to further understand the physical origin of normal and pathological brain function.This study was funded by a research grant from the Toronto East General Research Foundation.We thank Weyland Cheng and Owen Wong for assistance in the research.DSB conceived the study, participated in its design and the data analysis and drafted the manuscript. FJ carried out all computer simulations, participated in the study design and the data analysis and contributed to the manuscript draft. HCK conceived the study, participated in its design and the data analysis and contributed to the manuscript draft. All authors read and approved the final manuscript.


Hammerhead ribozymes are RNA-based molecules which bind and cleave other RNAs specifically. As such they have potential as laboratory reagents, diagnostics and therapeutics. Despite having been extensively studied for 15 years or so, their wide application is hampered by their instability in biological media, and by the poor translation of cleavage studies on short substrates to long RNA molecules. This work describes a systematic study aimed at addressing these two issues.in vitro for cleavage of RNA derived from the carbamoyl phosphate synthetase II gene of Plasmodium falciparum. Against a 550-nt transcript the most efficient (t1/2 = 26 seconds) was a miniribozyme with helix II reduced to a single G-C base pair and with twelve nucleotides in each hybridising arm. Miniribozymes of this general design were targeted to three further sites, and they demonstrated exceptional cleavage activity. A series of chemically modified derivatives was prepared and examined for cleavage activity and stability in human serum. One derivative showed a 103-fold increase in serum stability and a doubling in cleavage efficiency compared to the unmodified miniribozyme. A second was almost 104-fold more stable and only 7-fold less active than the unmodified parent.A series of hammerhead ribozyme derivatives, varying in their hybridising arm length and size of helix II, were tested in vitro. Using commonly available phosphoramidites and reagents, two patterns of nucleotide substitution in this derivative were identified which conferred both good cleavage activity against long RNA targets and good stability in human serum.Hammerhead ribozyme derivatives in which helix II is reduced to a single G-C base pair cleave long RNA substrates very efficiently  Haseloff and Gerlach [in vivo, since RNA is degraded very rapidly by ribonucleases present in cells and extracellular fluids. Significant segments of ribonucleotides in the hammerhead ribozyme can be replaced with more nuclease-resistant analogues like DNA, phosphorothioate linkages, or 2' O-methyl analogues; however, within the conserved core of the hammerhead, the majority of ribonucleotides are sensitive to modification. Yang et al [5, G8, A9 and A15.1 or G15.2 numbered according to [3, U4 & U7) resulted in significant increase in stability in human serum with a 6-fold loss in cleavage activity [5, G8, A9, A15.1 and G15.2) were required for activity [et al [4, G5, A6, G8, G12 and A15.1, in the conserved domain in which substitution with 2' O-allyl ribonucleotides inhibited activity. Eckstein's group [4 and U7, and 2'-fluoro-2'-deoxycytidine at C3. Hammerheads in which helix II was shortened to only two base pairs, and all the pyrimidines were 2'-fluoro or 2'-methoxyethoxy derivatives except for U4 and U7 which were 2'-amino-2'-deoxy, were only 2–3 fold less active than the unmodified parent hammerhead [4-fold increase in nuclease stability. A study of the effects of various modified nucleotides on stability and activity of the 2'-O-methyl-pyrimidine modified hammerhead found a number of modifications, including 2'-amino-2'-deoxyuridine, 2'-O-methyl-uridine, and 2'-C-allyl-uridine at positions U4 and U7, supported good rates of cleavage [3-fold increase in stability in human serum, while the addition of an inverted thymidine at the 3' end of the oligonucleotide (a 3'-3' linkage) further improved the stability by two orders of magnitude.Hammerhead ribozymes were discovered as self-cleaving motifs in a number of small, circular, pathogenic RNAs in plants -3. Uhlen Gerlach  divided  Gerlach -8. Sinceng et al  demonstrrding to ) displayactivity . In the y [et al  identifi's group ,14 showecleavage . These m10.1–C11.1 base pair joined by a flexible linker in place of helix-loop II [Plasmodium falciparum [Our laboratory is interested in the relationship between hammerhead design and reactivity. We have described a number of ribozyme derivatives that appear to have promise as RNA cleavage agents. Minizymes (Mz) possess a non-base-pairing tetranucleotide linker in place of helix II . In gene-loop II . Asymmet-loop II ,21. The lciparum ) in the Plasmodium falciparum. The chosen target site, centred at position 3733 in the nucleotide sequence (Genbank reference L32150), has the local sequence 5' UAA CUU AUC AAG GUC* AAG AAC AUG AUG UUC 3', where the site of cleavage is denoted by the asterisk. A number of ribozyme designs were tested for their ability to cleave this RNA sequence either as a short (30-mer) oligonucleotide or in a transcribed RNA segment (550 nt). These designs included standard hammerhead ribozymes (Rz) which are defined as those with a helix II consisting of four base pairs closed at the end with a four-nucleotide loop, minizymes (Mz) [2 under pseudo first-order conditions with an excess of ribozyme. Ribozyme concentrations ranged from 50 nM to 10 μM. Cleavage data fitted well to single exponential curves to yield observed rate constants which were plotted against the ribozyme concentration in each experiment to determine the apparent dissociation constant ("Kd") and the maximum cleavage rate constant (kmax) for each ribozyme-substrate pair   which lames (Mz)  which hamax, and marginal increase in "Kd", was by far the most efficient of all the designs tested. In contrast Mrz-8/8, Rz-12/12 and Rz-6/12 displayed "Kd"'s between 2 and 3 mM, which, in the case of Rz-12/12, is an increase of about 400-fold. Interestingly the kmax values displayed by Rz-12/12 and Rz-6/12 were within experimental error, and were the same as displayed by Rz-12/12 for cleavage of the short substrate.The abilities of all the ribozymes to cleave the same target in the context of transcribed RNA (550 nt) was also examined. Mrz-12/12, by virtue of only a modest decrease in kTetrahymena IVS ribozyme [-1 (t1/2 = 10 seconds), to about 70%, at pH 7.6, 37°C and 10 mM MgCl2. Another miniribozyme with 14-mer arms (HC Mrz), targeting a segment of Hepatitis C polyprotein mRNA, was tested against a synthetic 29-mer substrate. Under our standard conditions about 70% of the substrate was cleaved, and the cleavage rate (>5 min-1) was too fast to be measured reliably. In contrast, the standard ribozyme HC Rz cleaved 78% of the same substrate with a rate constant of only 0.2 ± 0.02 min-1. Finally, PDGF MRz, with hybridising arms each of 10 ribonucleotides, was tested against both 25-mer synthetic and 707-nt transcribed substrates. Under standard conditions, the 25-mer was ~ 80% cleaved with a rate constant > 5 min-1. Reducing the magnesium ion concentration to 1 mM yielded a rate constant of 2.8 min-1 and 63% cleavage for the 25-mer substrate, and 1.6 min-1 and 45% cleavage for the 707-nt transcript.We examined whether the effectiveness of the miniribozyme design was limited to this target site. Miniribozymes, with long (>10 nucleotides) hybridising arms were designed to cleave RNAs of interest to other projects in the laboratory. Tet Mrz was a 53-mer oligonucleotide with conserved bases of RNA and hybridising arms and stem loop II composed of DNA. This Mrz, with hybridising arms of 18 and 19 nucleotides, was targeted to cleave the GUC triplet at position 60 of the ribozyme . It clea32P 5'-end labelled ribozyme at 37°C  ribonucleotides.The single degradation site in Mrz-J suggested that a more robust modification at this position would have a significant effect on its lifetime in serum. Mrz-12/12 K was synthesised with a 2'-amino modification at the U4, was about 15-fold less efficient at cleaving S-30,  shows excellent cleavage kinetics against both short and long substrates. It appears that the more flexible miniribozyme is better suited to binding to the target in the context of a long RNA. These data can be interpreted according to a simple model in which ribozymes possessing a stable helix II form a more rigid three-dimensional structure [obs and "Kd". This observation is not specific to target or cleavage triplet, since four unrelated targets, including three long transcripts, one with an AUC cleavage triplet, were cleaved with rate constants much higher than typically reported for cleavage even of short substrates. It is worth noting the magnitude of the observed cleavage rate constants; under our standard conditions these miniribozymes cleave their targets with half-lives in the range of < 5 to 25 seconds.It is commonly observed, for conventional hammerhead ribozymes, that cleavage efficiencies for long transcripts are about 2 orders of magnitude lower than for short substrates . This hatructure ,34 which4, U7-amino derivatised ribozyme with a standard helix II was only marginally diminished in activity [4, U7-amino derivatised ribozyme [et al [ie C3, C15.2-fluoro and U4, U7-amino) but in a ribozyme with a standard helix II resulted in a more than 10-fold loss in turnover number (kcat). The series of singly and doubly substituted miniribozymes (C-E) showed clearly that a 2'-aminouridine at position 4 was solely responsible for the loss in activity. This is consistent with the result of Beigelman et al [7. A phosphorothioate linkage between U4 and G5 (Mrz-12/12 I) was the only modification tested here that did not suppress cleavage activity. This is in accord with interference studies [4 as insensitive to phosphorothioate modification. The results for dU and 2'O-methyl substitutions contrast with Beigelman et al [4 were relatively minor.The unmodified Mrz-12/12 was very unstable in 10% human serum. Degradation occurred by endonucleolytic cleavage at the 3' side of pyrimidine nucleotides. Since the hybridising arms and helix-loop II are composed of DNA, the four remaining ribo-pyrimidine nucleotides in the conserved domain were the critical residues for stabilisation. Modification of all four ribopyrimidines with 2'-aminouridine and 2'-fluorocytidine, (Mrz-12/12 B), resulted in a more than 10-fold decrease in maximum cleavage rate constant. This contrasts with some previous results where a Uactivity , and a Uribozyme , in whice [et al  was confe [et al , a modifan et al , but, in studies ,36 identan et al  where, i4 phosphorothioate, where an initial, quite rapid degradation was followed by a slower step which is not complete at 6 hours. Chemically synthesised phosphorothioate linkages are a mixture of two enantiomers and it is likely that the multiphase kinetics observed were due in part to the different susceptibility of the two isomers (Rp and Sp) to the nucleases present in the serum [4, is very stable in serum, and is only 7-fold less active than the unmodified parent. The products of nuclease cleavage of Mrz-12/12 K indicate that degradation occurred by cleavage at the unprotected ribopurine sites. This derivative was not protected at the 3' terminus, but unlike earlier work [In serum, Mrz-12/12 J was degraded by cleavage at the Uhe serum ,38. Mrz1ier work ,16,38, tin vivo were not successful. The results obtained here, and in other recent studies on the effect of non-conserved sequences on the kinetics of cleavage [in vivo catalytic efficiency of the hammerheads under study was compromised by their simplistic design, which was based on in vitro studies performed with very short substrates. We were too quick to ascribe poor cleavage of transcripts to "accessibility" issues, and too slow to undertake comprehensive studies to understand the phenomenon. The miniribozyme design, and the effective nuclease protection afforded by the simple chemical modifications described here, provide an opportunity to revisit cellular and in vivo experiments with hammerheads that are around two orders of magnitude more efficient.In recent times RNAi has surplanted catalytic RNA as the method of choice for suppression of gene expression in many eukaryotic cells . Resultscleavage ,40,41, ain vivo studies on suppression of gene expression.Long RNA substrates are much more effectively cleaved by miniribozymes than similarly targeted standard hammerheads. The presence of a stable helix II in the standard hammerhead appears to inhibit binding of the ribozyme to the substrate, and prevent the conformational mobility required for activity. Miniribozymes are affected by serum nucleases in a similar way to standard hammerheads, with cleavage occurring at the 3' side of unprotected ribopyrimidines. This work shows that it is readily possible to modify RNA/DNA hammerhead ribozymes, using commercially available reagents, to yield greatly improved nuclease resistance and retention of significant cleavage activity. These modified miniribozymes represent excellent candidates for cellular and 32P phosphate using T4 polynucleotide kinase (New England Biolabs, Beverly, MA, USA) and [γ-32P]-ATP (Du Pont, Wilmington, DE), followed by electrophoresis in a 15% polyacrylamide gel containing 7 M urea and visualisation using a Molecular Dynamics PhosphorImaging system . The concentrations of the purified oligonucleotides were determined by UV spectroscopy using the following molar extinction coefficients for the various nucleotides at 260 nm: A, 15.4 × 103; G, 11.7 × 103; C, 7.3 × 103; T/U, 8.8 × 103 l mol-1 cm-1. All oligonucleotides were stored in distilled, deionised and autoclaved water at -20°C.Oligoribonucleotides were synthesised using DNA phosphoramidites and ancillary reagents supplied by Perkin Elmer (Applied Biosystems Division, Foster City, CA), RNA and modified phosphoramidites from Glen Research (Sterling, VA) and using an Applied Biosystems Model 394 DNA synthesiser. Phosphorothioates were introduced by oxidation with Beaucage reagent (Glen Research, Sterling, VA). Deprotection and purification of oligonucleotides were as described previously . The pur32P UTP at about 1 nM. The transcription was for 90 minutes at 37°C, followed by the addition of 0.5 μL of DNAaseI and incubation for a further 20 minutes. The mixture was extracted three times with a 1:1 phenol/chloroform mix and once with chloroform, before precipitation of the transcript by the addition of 1/3 volume of 7.5 M ammonium acetate and incubation on ice for at least 2 hours. After recovery of the transcript by centrifugation and washing, the degree of incorporation of 32P-labelled uridine was measured by Cerenkov counting of the transcript and the unincorporated UTP. The Tetrahymena intervening sequence transcript was generated from the ScaI digested pT7L-21 vector [The 550-nt CPSII substrate was transcribed by T7 RNA polymerase from the vector pCPS3b.1  after li1 vector  , catcatgttctt CUGAUGA gttttc GAAAC cttgataagt; Mrz-12/12-B, catcatgttctt CfUamGAUamGA gttttc GAAACf cttgataagt; Mrz-12/12-C, catcatgttctt CUamGAUamGA gttttc GAAAC cttgataagt; Mrz-12/12-D, catcatgttctt CUamGAUGA gttttc GAAAC cttgataagt; Mrz-12/12-E, catcatgttctt CUGAUamGA gttttc GAAAC cttgataagt; Mrz-12/12-F, catcatgttctt CtGAUGA gttttc GAAAC cttgataagt; Mrz-12/12-G, catcatgttctt CuGAUGA gttttc GAAAC cttgataagt; Mrz-12/12-H, catcatgttctt CUmeGAUGA gttttc GAAAC cttgataagt; Mrz-12/12-I, catcatgttctt CUpsGAUGA gttttc GAAAC cttgataagt; Mrz-12/12-J, catcatgttctt CmeUpsGAUmeGA gttttc GAAACme cttgataagtpstpst; Mrz-12/12-K, catcatgttctt CmeUamGAUmeGA gttttc GAAACme cttgataagt; Rz-12/12-L, catcatgttctt CUamGAUGA GUCC UUUU GGAC GAAAC cttgataagt; Tet Mrz, gcaatctattggtttaaa CUGAUGA gttttc GAAAC tagctaccaggtgcatg 3'; HC Mrz, 5' gtcgccacgacgac CUGAUGA gttttc GAAAC gttcccgctggt 3'; HC Rz, 5' gtcgccacgacgac CUGAUGA GGCC GAAA GGCC GAAAC gttcccgctggt 3'; HC S29, 5' ACCAGCGGGAACGUCGUCGUCGUGGCGAc 3'; PDGF Mrz, 5' CAGCUUCCUC CUGAUGA ggtaac GAAAU GCUUCUCt 3' ; PDGF S25, 5' GAAGAGAAGCAUCGAGGAAGCUGUc 3'.Deoxyribonucleotides are denoted by lower case letters, ribonucleotides by uppercase letters, modified nucleotides are shown in bold, 2 under conditions of ribozyme excess; the substrate concentrations varied between 4 and 20 nM, and the ribozyme concentrations were between 20 nM and 10 μM. The short, synthetic substrates were labelled at their 5' ends using polynucleotide kinase  and γ-32P ATP. The long, transcribed substrates were uniformly labelled by including α-32P UTP in the transcription reaction. The ribozymes and 32P-labelled substrates were mixed together in 20 μL of 50 mM Tris buffer and heated to 85°C for two minutes, then incubated at 37°C for 2 minutes. The tube containing the mix was centrifuged, and 2 μL was removed and put into 4 μL quenching solution which contained 90% formamide, 20 mM EDTA and 0.01 % xylene cyanol and bromophenol blue. The reaction was initiated by the addition of 2 μL of 100 mM MgCl2, and 2 μL samples were removed at various times and quenched as described above. The reaction products were separated using 15% denaturing polyacrylamide gels (containing 7 M urea), and then imaged using a Molecular Dynamics PhosphorImager. At each time-point, the amount of the substrate cleaved was calculated and plotted versus time. The data were fitted by a least-squares method using the program MacCurveFit [t = P∞-(exp(-kobst)PΔ) where Pt is the amount of product at time t, P∞ is amount of product generated in the exponential phase of the reaction, kobs is the first-order rate constant for the reaction, and PΔ is the difference in the amount of product at t = 0 and P∞. Some reactions resulted in biphasic kinetics in which the first-order phase described above was followed by a slower step which was accommodated adequately in the curve-fitting process by the addition of a linear term, Pt = {P∞-(exp(-kobst)PΔ)} + d*t. Apparent dissociation constants "Kd" and the maximal first-order rate constants kmax were determined from the plot of kobs versus ribozyme concentration according to the simple binding isotherm: kmax = (kobs * [Rz])/("Kd" + [Rz]) by least-squares fitting using the program MacCurveFit.Cleavage kinetics were studied at 37°C, pH 7.6 and 10 mM MgClCurveFit , to an e32P phosphate were dissolved in RPMI medium (Gibco) at 2 μM and the reactions were initiated by adding human serum (pooled human serum, Red Cross Blood Bank, Sydney, NSW), to a final concentration of 10%. A 2 μL sample was removed immediately and the remainder incubated at 37°C with samples removed at the times indicated in Figures Ribozymes labelled at their 5' end with The authors jointly conceived and designed this study. PH synthesised the ribozymes and performed the kinetic and stability analyses. All authors read and approved the final manuscript.


With advancing age, thymic efficiency shows progressive decline due to thymic involution allowing impaired cell-mediated immunity and the appearance of age-related diseases. The intrinsic cause of thymic involution is still undefined. Chronic inflammation and high glucocorticoids (GCs) may be involved. However, transgenic mice, with increased GC sensitivity and over expression of GC receptors, display delayed age-associated thymic involution. This fact suggests that other substances may affect thymic involution. Among them, both isoforms of metallothioneins (MTs) I+II and III are the major candidates because their increments leads to organ atrophy in constant stress and are induced by IL-6, which increases in ageing. Enhanced MTs in ageing allows constant sequester of zinc ions and no subsequent zinc release leading to low zinc ion bioavailability for thymic efficiency. This sequester is very limited in very old age. Thus, we have investigated the MTmRNA (I+II and III) in the thymus from young, old and very old mice.MTmRNA and IL-6mRNA (RT-PCR) in the thymus from different donors were tested. Concomitantly, TECs proliferation, zinc ion bioavailability , thymulin activity and corticosterone were tested from different donors.Both isoforms of MTmRNA and IL-6mRNA increase in old thymus coupled with low zinc ion bioavailability, reduced TECs proliferation, impaired thymulin activity and enhanced plasma corticosterone in comparison with young. Conversely, although the thymus is involuted in very old mice because of no changes in thymus weight in comparison to old mice, reduced MTmRNA, especially MT-I+II isoforms, and low IL6mRNA occur. Concomitantly, good zinc ion bioavailability, maintained TECs proliferation, satisfactory thymulin activity and reduced corticosterone are observed in very old mice.The concomitant increments by high IL-6 of both MT isoforms in the thymus from old mice may be involved in thymic involution because provoking low zinc ion bioavailability, which is relevant for thymic efficiency. By contrast, the limited increments of MTs by low IL-6 induce good zinc ion bioavailability and satisfactory thymic efficiency in very old mice. Therefore, abnormal increased MTs may provoke complete thymic involution during ageing and the possible appearance of age-related diseases. If their increments are instead limited by low inflammation, healthy ageing and longevity may be reached. The thymus gland is a central lymphoid organ in which bone marrow-derived T cell precursors undergo a complex process of maturation and differentiation leading to migration of positively selected thymocytes to the T cell-dependent peripheral areas . AlthougBalb/c male inbred mice were used at the age of 2–3 months (young = n.10 mice), at the age of 20 months (old = n.10 mice) and at the age of 28–30 months (very old = n.10 mice). Although the maximum thymus sizes as well as peaks in thymocytes maturation and differentiation occur at 2–4 weeks of age in mice , no diff+ saturation method [Total RNA was extracted from frozen thymus using Tri-Reagent according manufacture s protocol (Sigma, USA). 3 μg of RNA sample were reverse transcribed adding Olio d(T) and kept at 70°C for 10 min. dent, Raise inhibitor and MMLV reverse transcriptase were subsequently added and incubated at 37°C for 1 h. Samples were heated at 95°C to inactivate enzymes and stored at 20°C. PCRs were performed using sense and antisense primers as follows: MT-I: 5'-ATGGACCCCAACTGCTCCTGCTCCACC-3', 5'-GGGTGGAACTGTATAGGAAGACGCTGG-3' (259 bp) MT-III:5'-ATGGACCCTGAGACCTGCCCCTGTCCT-3', 5'-GGCCTCTGCCTTGGCCCCCTCTTCACC-3',(183 bp); β-actin: 5'-GGACTCCTATGTGGGTGACGAGG-3', 5'-GGGAGAGCATAGCCCTCGTAGAT-3' (366 bp); IL-6: 5'-ATGAAGTTCCTCTCTGCAAGAGACT-3', 5'-CACTAGGTTTGCCGAGTAGATCTC-3' (615 bp). Conditions for amplification were as follows: for MT-I each cycle consisted of 94°C 0.30 min, 50°C 0.30 min, 72°C 0.30 min with 30 cycles; for MT-III each cycle consisted 94°C 45 sec., 55°C 30 sec., 72°C 1.5 min with 30 cycles; for β-actin each cycle consisted 94°C 1 min, 61°C 1 min, 72°C 1 min with 24 cycles; for IL-6 each cycle consisted 94°C 1 min, 65°C 2 min, 72°C 3 min with 40 cycles. The products of amplification were size-fractionated by 2% agarose gel electrophoresis and visualized by staining with ethidium bromide. Semi-quantitative analysis of the amplified products was performed with an image analyser (Gel-doc 2000 instrument, Bio-Rad, USA). The results were evaluated as a relative unit determined by normalisation of the density of each band to that of the β-actin one. This method reflects MT protein production tested with Agn method .-2 of the maximal dilution of tested plasma able to induce this phenomenon [Plasma active zinc-bound thymulin (AT), as extensively described elsewhere , was meaenomenon . In ordeenomenon . The ratenomenon .Plasma and tissue zinc content were determined in Atomic Absorption Spectrophotometer (AAS) against zinc reference standards (Sigma USA). Plasma zinc was determined after plasma dilution 1:5. Thymus tissue (1 gr) was put in muffle furnace at 550°C overnight. The ash obtained was diluted with 3 ml of 3 N HCl and transferred to a 25 ml volumetric flask and further diluted with 3 ml of 0.36 N HCl. The determination of zinc was then performed at AAS.3H kit  and referred against a standard curve. The percentage of cross-reaction with other steroid was <0.01. The sensitivity was of 0.05 ng/ml of corticosterone.Plasma corticosterone level (ng/ml) was determined by RIA rat-corticosterone-Anti pan-cytokeratin IgG1/FITC MoAb (Sigma, USA) diluted 1/25 and anti-keratin MoAb (Sigma, USA) diluted 1/20 were used. For this latter, guinea pig IgG/FITC (Sigma, USA) diluted 1/60 was used as second antibody. These MoAbs are specific to detect TECs  [TECs were separated with method described by Kurz et al. . Briefly2-atmosphere in order to make to adhere the cells. The supernatant containing unattached TEC was seeded into another plastic flask containing DMEM/F12 medium supplemented with 10% horse serum and put in culture in humidified 5% CO2-atmosphere. The cultures were inspected for morphologically visible fibroblasts (spindle shaped cells). In cases of significant contamination, the cells were washed with PBS and underwent again to trypsinization [3) was resuspended in 1 ml of medium and underwent to TEC percentage analysis. Percentages of separated TECs were counted in 1.000 cells at fluorescence microscope [The suspension was then centrifuged (2 min, 400 g) and the pellet suspended in 1 ml of Dulbecco s modified Eagle medium/Ham s F12 medium (1:1) (DMEM/F12, Gibco, Germany). The cells were subjected to two-steps trypsin (0.1 and 0.25%, respectively) and 0.001% DNase treatment in order to avoid fibroblasts . After tnization . Separatcroscope . Tests w3) was resuspended in 4 ml of DMEM/F12 medium for TEC proliferation analysis, which was approached using [3H] thymidine incorporation using 96 microtiter plates (Nunc, Denmark). 40 × 103 TECs were put in 40 wells (100 μl/well = 103 TECs/well). 10 wells were used as young; 10 wells as old; 10 wells as very old. Concomitantly, 1 μCi [3H]-thymidine/well (Amersham, UK) was added. The plates were incubated in humidified 5%-CO2 atmosphere for 6 hrs. Automatic harvester collected the samples and the amount of incorporated radioactivity was determined in a liquid scintillation beta-counter (Perkin-Elmer, USA).After TECs separation, another aliquota (40 × 10Two-tailed Student s t test, and ANOVA test (one-way) evaluated differences between means. Correlations were determined by linear regression analysis by the least square method. Differences were evaluated by analysis of covariance. Differences were significant when p < 0.05.Table Table The ratio total thymulin (TT)/active thymulin (AT) represents the zinc ion bioavailability. More high is the ratio ≥ 2) less zinc ion bioavailability is present, whereas ratio < 2 or equal to 1 means satisfactory or good zinc ion bioavailability, respectively . The rat less zinSignificant inverse correlation exists between zinc and Corticosterone (r = -0.71, p < 0.01), whereas significant positive correlation exists between thymulin activity and TECs number and proliferation  from young, old and very old mice.Although MT-III isoform may be present exclusively within the brain , some peMT-I+II and III are expressed in the brain with a balance between the two isoforms 25). When one isoform increases, the other decreases due to a possible genetic control of MRE region on the chromosome 8, which brings the two isoforms . Concomi5. When oOn the other hand, MT-ImRNA is lower in lymphocytes from human nonagenarians coupled with satisfactory thymic and peripheral immune efficiency and good zinc ion bioavailability . MoreoveHowever, the thymic involution is not irreversible phenomena because zinc treatment in old mice restores thymic efficiency with a re-growth of thymic cortex . This fiIn conclusion, concomitant increments of zinc-bound MT-I+II and III within the thymus may lead to thymic involution in ageing because they sequester zinc and are unable in the subsequent zinc release, which is indispensable for thymic efficiency. The cause may be related to chronic inflammation by high IL-6 and GCs. Without excluding a direct role of GCs in thymic involution . Less inHowever, if the thymic involution may be a necessary event in order to avoid autoimmune phenomena in ageing is an intriguing point to be investigated. Indeed, high IL-6 provokes an enlargement of the thymus with the appearance of autoimmune phenomena . Thus, i