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Motivation: The topology of the network induced by the neurons connectivity's in the Caenorhabditis elegans differs from most common random networks. The neurons positions of the C.elegans have been previously explained as being optimal to induce the required network wiring. We here propose a complementary explanation that the network wiring is the direct result of a local stochastic synapse formation process., Results: We show that a model based on the physical distance between neurons can explain the C.elegans neural network structure, specifically, we demonstrate that a simple model based on a geometrical synapse formation probability and the inhibition of short coherent cycles can explain the properties of the C.elegans' neural network. We suggest this model as an initial framework to discuss neural network generation and as a first step toward the development of models for more advanced creatures. In order to measure the circle frequency in the network, a novel graph-theory circle length measurement algorithm is proposed.

B lymphocytes producing high-affinity Abs are critical for protection from extracellular pathogens, such as bacteria and parasites. The process by which high-affinity B cells are selected during the immune response has never been elucidated. Although it has been shown that high-affinity cells directly outcompete low-affinity cells in the germinal center (GC), whether there are also intrinsic differences between these cells has not been addressed. It could be that higher affinity cells proliferate more rapidly or are more likely to enter cell cycle, thereby outgrowing lower affinity cells. Alternatively, higher affinity cells could be relatively more resistant to cell death in the GC. By comparing high- and low-affinity B cells for the same Ag, we show here that low-affinity cells have an intrinsically higher death rate than do cells of higher affinity, even in the absence of competition. This suggests that selection in the GC reaction is due at least in part to the control of survival of higher affinity B cells and not by a proliferative advantage conferred upon these cells compared with lower affinity B cells. Control over survival rather than proliferation of low- and high-affinity B cells in the GC allows greater diversity not only in the primary response but also in the memory response.

Ligand binding to B-cell receptors (BcRs) on the B-cell surface induces crosslinking and phosphorylation of BCRs by the Src family kinases, followed by initiation of signaling. Although the nature of the earliest events following receptor engagement is currently under intensive investigation, the precise connection between crosslinking and the signaling cascade triggering has thus far remained unclear. Using a novel multiscale, agent-based simulation of B-cell surface dynamics, we present a coherent quantitative analysis of the initial stages of B-cell activation following ligand presentation. The simulation reproduces experimental results of H3 uptake, immunoglobulin secretion, immunoelectron photomicrography and FRET. While merging multiple experimental techniques, the simulation captures all essential events in the first twenty seconds following ligand presentation, and is used to make predictions on subsequent molecular events. We show that B-cell activation is mediated through a positive feedback loop between Lyn and ITAM phosphorylation, but that specificity is achieved through a combination of BcR spatial segregation and BcR selective partitioning within lipid rafts following clustering.

Background: Viruses employ various means to evade immune detection. One common evasion strategy is the removal of CD8 cytotoxic T-lymphocyte (CTL) epitopes., Method: Here, we use bioinformatic tools to compute the HIV CTL epitope repertoire presented by over 8000 HIV sequences in multiple Human Leukocyte Antigen alleles. We define the 'Size of Immune Repertoire' (SIR) score, which represents the ratio between the number of the predicted epitopes within a protein and their expected number within a scrambled version of the same protein., Results: We show that HIV proteins present less epitopes than expected and that the number of epitopes gradually decreases from SIV to recent HIV sequences. The decrease of the SIR score of HIV is accompanied by a high frequency of replacement mutations within epitopes. The SIR score of the different HIV proteins is not uniform. The regulatory proteins, Tat and Rev, expressed early during cellular infection have a low SIR score, whereas virion-associated genes that are expressed later, such as Env, Pol and Gag, have a higher SIR score. Actually, the SIR score of Gag keeps increasing over time., Conclusion: We hypothesize that our results reflect an HIV immune evasion strategy. This involves the targeting of the CTL immune response to viral structural and enzyme proteins, allowing the virus a time interval to propagate before its host cells are destroyed by CTLs. An efficient anti-HIV CTL response against HIV should thus also target the regulatory genes that HIV seeks to hide from the immune system.

Traditionally, immunology has considered a meaningful antibody response to be marked by large amounts of high-affinity antibodies reactive with the specific inciting antigen; the detection of small amounts of low-affinity antibodies binding to seemingly unrelated antigens has been considered to be beneath the threshold of immunological meaning. A systems-biology approach to immunology, however, suggests that large-scale patterns in the antibody repertoire might also reflect the functional state of the immune system. To investigate such global patterns of antibodies, we have used an antigen-microarray device combined with informatic analysis. Here we asked whether antibody-repertoire patterns might reflect the state of an implanted tumor. We studied the serum antibodies of inbred C57BL/6 mice before and after implantation of syngeneic 3LL tumor cells of either metastatic or non-metastatic clones. We analyzed patterns of IgG and IgM autoantibodies binding to over 300 self-antigens arrayed on slides using support vector machines and genetic algorithm techniques. We now report that antibody patterns, but not single antibodies, were informative: 1) mice, even before tumor implantation, manifest both individual and common patterns of low-titer natural autoantibodies; 2) the patterns of these autoantibodies respond to the growth of the tumor cells, and can distinguish between metastatic and non-metastatic tumor clones; and 3) curative tumor resection induces dynamic changes in these low-titer autoantibody patterns. The informative patterns included autoantibodies binding to self-molecules not known to be tumor-associated antigens (including insulin, DNA, myosin, fibrinogen) as well as to known tumor-associated antigens (including p53, cytokeratin, carbonic anhydrases, tyrosinase). Thus, low-titer autoantibodies that are not the direct products of tumor-specific immunization can still generate an immune biomarker of the body-tumor interaction. System-wide profiling of autoantibody repertoires can be informative.

Motivation: Viruses employ various means to evade immune detection. One common evasion strategy is the removal of CD8+cytotoxic T-lymphocyte epitopes. We here use a combination of multiple bioinformatic tools and large amount of genomic data to compute the epitope repertoire presented by over 1300 viruses in many HLA alleles. We define the 'Size of Immune Repertoire score', which represents the ratio between the epitope density within a protein and the expected density. This score is used to study viral immune evasion., Results: We show that viral proteins in general have a higher epitope density than human proteins. This difference is due to a good fit of the human MHC molecules to the typical amino-acid usage of viruses. Among different viruses, viruses infecting humans present less epitopes than non-human viruses. This selection is not at the amino-acid usage level, but through the removal of specific epitopes. Within a single virus, not all proteins express the same epitopes density. Proteins expressed early in the viral life cycle have a lower epitope density than late proteins. Such a difference is not observed in non-human viruses. The removal of early epitopes and the targeting of the cellular immune response to late viral proteins, allow the virus a time interval to propagate before its host cells are destroyed by T cells.

The cellular immune system recognizes self-epitopes in the context of MHC-I molecules. The immunological general view presumes that these self-epitopes are just a background, both positively and negatively selecting T cells. We here estimate the number of epitopes in each human protein for many frequent HLA alleles, and a score representing over or under presentation of epitopes on these proteins. We further show that there is a clear selection for the presentation of specific self-protein types. Proteins presenting many epitopes include, for example, autoimmune regulator (AIRE) upregulated tissue-specific antigens, immune system receptors and proteins with a high expression level. On the other hand, proteins that may be considered less "useful" for the immune system, such as low expression level proteins, are under-presented. We combine our epitope estimate with single nucleotide polymorphism (SNP) measures to show that this selection can be directly observed through the fraction of non-synonymous SNP (replacement fraction), which is significantly higher inside epitopes than outside.

Background: Listeriosis is a severe food-borne disease caused by Listeria monocytogenes. It mostly affects immune-compromised individuals, pregnant women, and the elderly, and it is associated with huge economic losses, especially to the food industry. In the last decade, a sharp increase in listeriosis incidence was observed in several European countries. No suitable explanation was found for this increase, which occurred only in old patients and not in pregnant women., Methods: We developed a mathematical model to explore this upsurge by studying the balance between the immunized population fraction and the force of infection, and its influence on the incidence of listeriosis., Results: The model shows that the current upsurge could be the result of a decrease in exposure to the pathogen in food a few decades ago and hence decreased level of population immunity. The model also suggests that, counterintuitively, the incidence of listeriosis can be higher under reduced exposure to L. monocytogenes than under high exposure. These results rely on the accepted assumption that immunity to L. monocytogenes is long-lived (at least 20 years) or that there is a long-lived boosting effect by previous exposure to L. monocytogenes. The results are robust to wide changes in all other model parameters., Conclusions: Historical alterations in exposure to L. monocytogenes might explain current changes in incidence of listeriosis. The model may also be implied for other noncontagious infectious diseases (eg, food borne diseases or vector-borne diseases for which humans are considered dead-end hosts) for which susceptibility increases with age.

Motivation: An 8-10mer can become a cytotoxic T lymphocyte epitope only if it is cleaved by the proteasome, transported by TAP and presented by MHC-I molecules. Thus most of the epitopes presented to cytotoxic T cells in the context of MHC-I molecules are products of intracellular proteasomal cleavage. These products are not random, as peptide production is a function of the precise sequence of the proteins processed by the proteasome., Results: We have developed a score for the probability that a given peptide results from proteasomal cleavage. High scoring peptides are those that are cleaved in their extremities and not in their center, while low scoring peptides are either cleaved in their centers or not cleaved in their extremities. The current work differs from most previous works, in that it determines the production probability of an entire peptide, rather than trying to predict specific cleavage sites. We further present different score functions for the constitutive and the immunoproteasome. Our results were validated to have low error levels against multiple epitope databases. We provide here a novel computational tool and a website to use it-http://peptibase.cs.biu.ac.il/PepCleave_II/ to assess the probability that a given peptide indeed results from proteasomal cleavage.

Viruses employ various modes to evade immune detection. Two possible evasion modes are a reduction of the number of epitopes presented and the mimicry of host epitopes. The immune evasion efforts are not uniform among viral proteins. The number of epitopes in a given viral protein and the similarity of the epitopes to host peptides can be used as a measure of the viral attempts to hide this protein. Using bioinformatics tools, we here present a genomic analysis of the attempts of four human herpesviruses (herpes simplex virus type 1-human herpesvirus 1, Epstein-Barr virus-human herpesvirus 4, human cytomegalovirus-human herpesvirus 5, and Kaposi's sarcoma-associated herpesvirus-human herpesvirus 8) and one murine herpesvirus (murine herpesvirus 68) to escape from immune detection. We determined the full repertoire of CD8 T-lymphocyte epitopes presented by each viral protein and show that herpesvirus proteins present many fewer epitopes than expected. Furthermore, the epitopes that are presented are more similar to host epitopes than are random viral epitopes, minimizing the immune response. We defined a score for the size of the immune repertoire (the SIR score) based on the number of epitopes in a protein. The numbers of epitopes in proteins expressed in the latent and early phases of infection were significantly smaller than those in proteins expressed in the lytic phase in all tested viruses. The latent and immediate-early epitopes were also more similar to host epitopes than were lytic epitopes. A clear trend emerged from the analysis. In general, herpesviruses demonstrated an effort to evade immune detection. However, within a given herpesvirus, proteins expressed in phases critical to the fate of infection (e.g., early lytic and latent) evaded immune detection more than all others. The application of the SIR score to specific proteins allows us to quantify the importance of immune evasion and to detect optimal targets for immunotherapy and vaccine development.

The rapid accumulation of knowledge and the recent emergence of new dynamic and practically unmoderated information repositories have rendered the classical concept of the hierarchal knowledge structure irrelevant and impossible to impose manually. This led to modern methods of data location, such as browsing or searching, which conceal the underlying information structure. We here propose methods designed to automatically construct a hierarchy from a network of related terms. We apply these methods to Wikipedia and compare the hierarchy obtained from the article network to the complementary acyclic category layer of the Wikipedia and show an excellent fit. We verify our methods in two networks with no a priori hierarchy (the E. Coli genetic regulatory network and the C. Elegans neural network) and a network of function libraries of modern computer operating systems that are intrinsically hierarchical and reproduce a known functional order.

The types of mathematical models used in immunology and their scope have changed drastically in the past 10 years. Classical models were based on ordinary differential equations (ODEs), difference equations, and cellular automata. These models focused on the 'simple' dynamics obtained between a small number of reagent types (e.g. one type of receptor and one type of antigen or two T-cell populations). With the advent of high-throughput methods, genomic data, and unlimited computing power, immunological modeling shifted toward the informatics side. Many current applications of mathematical models in immunology are now focused around the concepts of high-throughput measurements and system immunology (immunomics), as well as the bioinformatics analysis of molecular immunology. The types of models have shifted from mainly ODEs of simple systems to the extensive use of Monte Carlo simulations. The transition to a more molecular and more computer-based attitude is similar to the one occurring over all the fields of complex systems analysis. An interesting additional aspect in theoretical immunology is the transition from an extreme focus on the adaptive immune system (that was considered more interesting from a theoretical point of view) to a more balanced focus taking into account the innate immune system also. We here review the origin and evolution of mathematical modeling in immunology and the contribution of such models to many important immunological concepts.

A model of intentional actions is presented through the operation of two connected neural networks. A deterministic causal recurrent network relates a random initial state to an ordered final state. A perceptron-like, feed-forward network provides a memory mechanism that links the final states to the original initial states. A non-supervised learning mechanism that selects which final states are defined as goals to be retrieved together with initial states leading to them. Causal sequences of states are transformed into procedures directed towards the achievements of goals. We propose a mechanism through which goals and their achievement in goal-directed actions can be emerging properties of self-organizing networks, not initially endowed with intentionality. This allows for a monist, non-mentalist description which does not need to resort to intentional mental states as causes of intentional actions. Cognitive, neurophysiological and philosophical implications are discussed.

Attempts to develop peptide vaccines, based on a limited number of peptides face two problems: HLA polymorphism and the high mutation rate of viral epitopes. We have developed a new genomic method that ensures maximal coverage and thus maximal applicability of the peptide vaccine. The same method also promises a large number of epitopes per HLA to prevent escape via mutations. Our design can be applied swiftly in order to face rapidly emerging viral diseases. We use a genomic scan of all candidate peptides and join them optimally. For a given virus, we use algorithms computing: peptide cleavage probability, transfer through TAP and MHC binding for a large number of HLA alleles. The resulting peptide libraries are pruned for peptides that are not conserved or are too similar to self peptides. We then use a genetic algorithm to produce an optimal protein composed of peptides from this list properly ordered for cleavage. The selected peptides represent an optimal combination to cover all HLA alleles and all viral proteins. We have applied this method to HCV and found that some HCV proteins (mainly envelope proteins) represent much less peptide than expected. A more detailed analysis of the peptide variability shows a balance between the attempts of the immune system to detect less mutating peptides, and the attempts of viruses to mutate peptides and avoid detection by the immune system. In order to show the applicability of our method, we have further used it on HIV-I, Influenza H3N2 and the Avian Flu Viruses.

Spatially extended catalyst-induced growth processes are studied. This type of processes exists in all domains of biology, ranging from ecology (nutrients and growth), through immunology (antigens and lymphocytes) to molecular biology (signaling molecules initiating signaling cascades). The extinction-proliferation transition is considered for a system containing discrete catalysts (A) that induces the proliferation of a discrete reactant (B). The realization of this model on an infinite capacity d-dimensional discrete lattice for immortal catalysts has been previously considered (the AB model). It was shown that the adaptation of the reactants to the diffusive noise induced by stochastic fluctuations of catalyst density yields proliferation even if the average environmental conditions lead to extinction. This model is extended here to include more realistic situations, like finite lifespan of the catalysts and finite carrying capacity of the reactants. By using a combination of Monte Carlo simulation, percolation-theory-based estimations and an analytic perturbative analysis, the asymptotic behavior of these systems is studied. In both cases studied, it turns out that the overall survival of the reactant population at the long run is based on the size and shape of a typical single colony, related to the localized proliferation around spatio-temporal catalyst density fluctuations. If the density of these colonies (based on the lifetime of the spatial fluctuation and the carrying capacity of the medium) is large enough, i.e. above the percolation threshold, the reactant population survives even in (on average) hostile environment. This model provides a new insight on the population dynamics in chemical, biological and ecological systems.

Motivation: B cells responding to antigenic stimulation can fine-tune their binding properties through a process of affinity maturation composed of somatic hypermutation, affinity-selection and clonal expansion. The mutation rate of the B cell receptor DNA sequence, and the effect of these mutations on affinity and specificity, are of critical importance for understanding immune and autoimmune processes. Unbiased estimates of these properties are currently lacking due to the short time-scales involved and the small numbers of sequences available., Results: We have developed a bioinformatic method based on a maximum likelihood analysis of phylogenetic lineage trees to estimate the parameters of a B cell clonal expansion model, which includes somatic hypermutation with the possibility of lethal mutations. Lineage trees are created from clonally related B cell receptor DNA sequences. Important links between tree shapes and underlying model parameters are identified using mutual information. Parameters are estimated using a likelihood function based on the joint distribution of several tree shapes, without requiring a priori knowledge of the number of generations in the clone (which is not available for rapidly dividing populations in vivo). A systematic validation on synthetic trees produced by a mutating birth-death process simulation shows that our estimates are precise and robust to several underlying assumptions. These methods are applied to experimental data from autoimmune mice to demonstrate the existence of hypermutating B cells in an unexpected location in the spleen.

Unlabelled: We study two kinds of networks: genetic regulatory networks and the World Wide Web. We systematically test microscopic mechanisms to find the set of such mechanisms that optimally explain each networks' specific properties. In the first case we formulate a model including mainly random unbiased gene duplications and mutations. In the second case, the basic moves are website generation and rapid surf-induced link creation (/destruction). The different types of mechanisms reproduce the appropriate observed network properties. We use those to show that different kinds of networks have strongly system-dependent macroscopic experimental features. The diverging properties result from dissimilar node and link basic dynamics. The main non-uniform properties include the clustering coefficient, small-scale motifs frequency, time correlations, centrality and the connectivity of outgoing links. Some other features are generic such as the large-scale connectivity distribution of incoming links (scale-free) and the network diameter (small-worlds). The common properties are just the general hallmark of autocatalysis (self-enhancing processes), while the specific properties hinge on the specific elementary mechanisms., Supplementary Information: Supplementary data are available at Bioinformatics Online.

During thymic education, strongly self-reactive T cells are selected against, while weakly self-reactive cells are positively selected. However, the probability of an antigen being self derived and the number of self-peptides have never been properly defined. We merge algorithms for: cleavage prediction, TAP binding probability estimates and MHC binding properties to estimate the number and distribution of all MHC binding peptides. We show that the number of self-peptides with a high affinity to a given human MHC-I molecule is between 200 and almost 200,000 and is much less than the estimated total number of peptide sequences. This result suggests that MHC molecules are selected through evolution in order to reduce the number of self-peptides presented. The number of viral peptides presented is also low and varies between zero and a few hundred per virus for a given HLA allele. These low numbers explain the need for multiple alleles within an individual. We show that six codominantly expressed MHC-I alleles are sufficient to present at least one or two peptides per virus for the vast majority of viruses. Viruses can escape detection either by using peptides that cannot be presented on MHC molecules or by using peptides whose presented segments overlap significantly with self. Most viral families (such as influenza, HIV, Hepatitis and HPV) present as many peptides as predicted from their genome length, and overlap minimally with the human self-peptide repertoire. However, a few latent viruses, such as herpes and adenovirus share considerable peptide sequence homology with their human hosts.

The cell membrane lies at the interface between an extracellular set of signals and the appropriate intracellular response. Specifically, lymphocyte activity is determined by the spatial and structural response to antigens, as mediated by cell surface receptors. In order to correlate experimentally observed cellular activities, such as secretion, anergy, death, survival and division to external stimuli, it is necessary to monitor cell surface dynamics. B-lymphocyte activation results from the stimulation by large immune complexes comprising antigens, B-cell receptors (BcRs) and co-receptors. Compartmentalisation of the interacting molecular components is required in order to assure the rapid initiation of specialised and sustained signalling cascades. In this study, a Monte Carlo simulation of the cell membrane dynamics was developed to clarify the receptor dynamics, aggregation mechanisms and their combined effect on cellular functions. This simulation is based on experimentally measured parameters and represents a feasible, advanced and reliable framework to investigate the cell surface. The current study focussed on B-cell surface dynamics. A model demonstrating the basic properties of BcR dynamics and how BcR kinetics is affected by lipid rafts is developed. The authors studied BcR interactions with multivalent ligands and the influence of lipid rafts on this interaction. Finally, the dynamics of the initial steps of BcR-mediated cell activation is estimated and the effect of the association of signalling molecules with lipid rafts is demonstrated. These results are used to suggest some novel hypotheses on BcR-mediated B-cell activation.

Receptor editing is performed by replacement of Vkappa genes that contribute to autoreactivity. In addition, the Ckappa locus can be deleted by Vkappa rearrangement to intronic or 3' of Ckappa RS sequences (also referred to as kappa deletion elements). B cells that delete the Ckappa can then express lambda light chains. However, the lambda locus, either of man or mouse, does not allow V gene replacement. Nor does it appear to be deleted. Therefore, editing of autoreactive lambda B cells may require alternative pathways. We have found that in anti-DNA heavy chain transgenic mice (tgs) VH3H9/56R, B cells that express anti-DNA receptors comprised of lambda1 in association with an anti-DNA heavy chain often coexpress a kappa chain that prevents DNA binding. We speculate that such isotypically included cells may have low anti-DNA receptor densities, a feature that may lead to self-tolerance. Here we describe a mechanism of preventing DNA binding by expression of a rarely used member of the Vlambda family, Vlambdax. The lambdax B cells of the tgs also express CD25 and may represent B cells that have exhausted light chain editing possibilities.

Background: Persistent, intrusive re-experiencing in posttraumatic stress disorder (PTSD) is commonly construed as a failure of cingulate inhibition (i.e., extinction) over a hyperresponsive amygdala, based primarily on animal research of fear conditioning and the finding of cingulate hypoperfusion in PTSD., Methods: We examined functional connectivity in patients with PTSD and healthy trauma survivors during repeated symptom provocation using H(2)O(15) positron emission tomography., Results: Memory retrieval networks (right prefrontal cortex, hippocampus, and visual cortex) were common to both groups. Networks supporting autonomic and emotional control and preparatory motor action (amygdala, anterior cingulate, subcallosal gyrus, and premotor cortex) differed between the two groups and became progressively disparate with successive presentations of the traumatic script. Patterns of effective connectivity demonstrated the predominance of direct influences of the amygdala on visual cortex, subcallosal gyrus, and anterior cingulate in PTSD but not in control subjects. There was little evidence for failure of inhibition of cingulate or subcallosal cortex over the amygdala., Conclusions: These patterns might represent excessive influences of the amygdala over regions involved in autonomic, and higher-order visual memory processing in PTSD. The present data suggest that inferences of direct correspondence between animal studies and pathophysiology of PTSD should be made with caution.

B lymphocyte activation results from the stimulation by large immune complexes involving antigens, antibodies, rafts and complement factors. Cell activation requires co-localization of the interacting molecular components. One of the main elements leading to this localization is the presence on the cell surface of lipid rafts. We show here that an appropriate amount of lipid rafts help to significantly (2- 3 orders of magnitude) raise the sensitivity of B lymphocyte to surrounding high valence antigens. The analysis was done using a newly developed graphically visualized, Monte Carlo (MC) simulation of the cell surface dynamics. Currently this platform represents a feasible, advanced and reliable framework to investigate the cell surface in general. We describe the model and determine, utilizing our model, the effect of lipid rafts surface fraction on the properties of B cell response to immune complexes. We validate our results using an approximate set of ODEs.

Patients with mild traumatic brain injury (MTBI) challenge physicians' skills and test their patience. Their manifold symptomatology is often not supported by objective neurological findings. We sought to compare regional cerebral blood flow (rCBF) between symptomatic subjects with longstanding MTBI and healthy controls, and to examine the correspondence between neuropsychological deficit and rCBF compromise. Twenty-eight clinically symptomatic male subjects with MTBI and twenty matched controls underwent neuropsychological testing and Tc-99m-HMPAO brain SPECT imaging. Neuropsychological test data were used to categorize subjects into sub-groups according to the presumed location of lesions based on their neurobehavioral deficits. Image subtraction comparisons were made between controls, all MTBI subjects and sub-groups. MTBI patients demonstrated regions of hypoperfusion in frontal, pre-frontal and temporal cortices, and sub-cortical structures. Hypoperfusion in 'frontal', 'left posterior' and to a lesser extent 'sub-cortical' sub-groups was concordant with neuropsychological localization. This was not the case for the 'right posterior' group, where no concordance was found. The rCBF is reduced in symptomatic patients with longstanding MTBI and unremarkable structural brain imaging. Although group analysis is appropriate for the generation of statistically significant differences, the clinical application of brain SPECT imaging in MTBI calls for a capability to associate clinical examination, neuropsychological assessment and cerebral perfusion at the individual subject level. Such competence is still to be attained.

Background: Brain imaging research in posttraumatic stress disorder has been largely performed on patients with chronic disease, often heavily medicated, with current or past alcohol and substance abuse. Additionally, virtually only activation brain imaging paradigms have been done in posttraumatic stress disorder, whereas in other mental disorders both resting and activation studies have been performed., Methods: Twenty-eight (11 posttraumatic stress disorder) trauma survivors underwent resting state hexamethylpropyleneamineoxime single photon emission computed tomography and magnetic resonance imaging 6 months after trauma. Eleven nontraumatized subjects served as healthy controls., Results: Regional cerebral blood flow in the cerebellum was higher in posttraumatic stress disorder than in both control groups. Regional cerebral blood flow in right precentral, superior temporal, and fusiform gyri in posttraumatic stress disorder was higher than in healthy controls. Cerebellar and extrastriate regional cerebral blood flow were positively correlated with continuous measures of depression and posttraumatic stress disorder. Cortisol level in posttraumatic stress disorder was negatively correlated with medial temporal lobe perfusion. Anterior cingulate perfusion and cortisol level were positively correlated in posttraumatic stress disorder and negatively correlated in trauma survivors without posttraumatic stress disorder., Conclusions: Recent posttraumatic stress disorder is accompanied by elevated regional cerebral blood flow, particularly in the cerebellum. This warrants attention because the cerebellum is often used as a reference region in regional cerebral blood flow studies. The inverse correlation between plasma cortisol and medial temporal lobe perfusion may herald hippocampal damage.

To understand the mechanisms underlying the varying patterns of mutations that occur during immune and autoimmune responses, estimates of the somatic hypermutation rate are critical. However, despite its significance, precise estimates of the mutation rate do not currently exist. Microdissection studies of mutating B cell clones provide an opportunity to measure this rate more accurately than previously possible. Each microdissection provides a number of clonally related sequences that, through the analysis of shared mutations, can be genealogically related to each other. The shape of these clonal trees is influenced by many processes, including the hypermutation rate. We have developed two different methods to estimate the mutation rate based on these data. These methods are applied to two sets of experimental data, one from an autoimmune response and one from the antihapten response to (4-hydroxy-3-nitrophenyl)acetyl (NP). Comparable mutation rates are estimated for both responses, 0.7-0.9 x 10(-3) and 0.9-1.1 x 10(-3) bp(-1) division(-1) for the autoimmune and NP responses, respectively. In addition to comparing the results of the two procedures, we investigate the effect on our estimate of assumptions, such as the fraction of lethal mutations.

Economic and cultural globalization is one of the most important processes humankind has been undergoing lately. This process is assumed to be leading the world into a wealthy society with a better life. However, the current trend of globalization is not unprecedented in human history, and has had some severe consequences in the past. By applying a quantitative analysis through a microscopic representation we show that globalization, besides being unfair (with respect to wealth distribution), is also unstable and potentially dangerous as one event may lead to a collapse of the system. It is proposed that the optimal solution in controlling the unwanted aspects and enhancing the advantageous ones lies in limiting competition to large subregions, rather than making it worldwide.

Functional brain imaging has assumed a leading role in neuropsychiatric research. However, findings reported for mental disorders often vary. Whether this reflects diversity in pathophysiology or heterogeneity of imaging techniques and data-analytic procedures is still unknown. This study compares region of interest (ROI) and statistical parametric mapping (SPM) analyses of a Tc99m-HMPAO single photon emission computed tomography (SPECT) imaging study of 23 depressed and 21 control subjects. Reduced regional cerebral blood flow (rCBF) was demonstrated by both methods in the right parietal and occipital lobes, but additional regions were identified only on ROI analysis (left temporal) and only on SPM analysis (left parietal). To investigate the contribution of SPM spatial normalization to these discrepancies, further ROI analyses were performed, applying the original ROI templates to normalized images, and applying regions identified by SPM to the original images. This study demonstrated considerable overlap in findings of SPM and ROI analyses. Differences between these methods may be mostly related to subjective placement of ROIs in ROI analysis, and standardized warping inherent in normalization in SPM. Given the advantages and drawbacks of each procedure, the choice of methodology should be determined in accordance with the study design, and complementary use of both methods may be considered., (Copyright 2002 Elsevier Science Ireland Ltd.)

We present an analysis of physical chemical constraints on the accuracy of DNA micro-arrays under equilibrium and nonequilibrium conditions. At the beginning of the article we describe an algorithm for choosing a probe set with high specificity for targeted genes under equilibrium conditions. The algorithm as well as existing methods is used to select probes from the full Saccharomyces cerevisiae genome, and these probe sets, along with a randomly selected set, are used to simulate array experiments and identify sources of error. Inasmuch as specificity and sensitivity are maximum at thermodynamic equilibrium, we are particularly interested in the factors that affect the approach to equilibrium. These are analyzed later in the article, where we develop and apply a rapidly executable method to simulate the kinetics of hybridization on a solid phase support. Although the difference between solution phase and solid phase hybridization is of little consequence for specificity and sensitivity when equilibrium is achieved, the kinetics of hybridization has a pronounced effect on both. We first use the model to estimate the effects of diffusion, crosshybridization, relaxation time, and target concentration on the hybridization kinetics, and then investigate the effects of the most important kinetic parameters on specificity. We find even when using probe sets that have high specificity at equilibrium that substantial crosshybridization is present under nonequilibrium conditions. Although those complexes that differ from perfect complementarity by more than a single base do not contribute to sources of error at equilibrium, they slow the approach to equilibrium dramatically and confound interpretation of the data when they dissociate on a time scale comparable to the time of the experiment. For the best probe set, our simulation shows that steady-state behavior is obtained in a relaxation time of approximately 12-15 h for experimental target concentrations approximately (10(-13) - 10(-14))M, but the time is greater for lower target concentrations in the range (10(-15)-10(-16))M. The result points to an asymmetry in the accuracy with which up- and downregulated genes are identified.

A probabilistic model of allelic exclusion fails to explain the status of receptor genes and the receptor phenotype of most B cells. A large proportion of B cells have incompletely rearranged H and/or L chain genes (e.g. kappa0/kappa+) and most B cells express only one receptor. These properties seem to require deterministic features of B cell development such as special mechanisms that stop rearrangement. However, receptor editing has revealed that rearrangement-stop is not stable and that multi-receptor lymphocytes make up a significant fraction of certain B and T cell populations. Consequently we have revived the purely probabilistic approach in a model that now includes receptor editing and allows for some multi-receptor B cells. We find that this model can explain the observed properties of B cells when the frequency of self-reactive B cells is high. Indeed, as we illustrate for anti-DNA, this is the case. Hence the probabilistic model has life and assiduous use of the model suggests unexpected but not unrealistic features of lymphocyte development.

A sharp TH1/TH2 dichotomy has often been used to define the effects of cytokines on autoimmune diseases. However contradictory results in recent research indicate that the situation may be more complex. Here, we build a simple mathematical model aimed at settling the contradictions. The model is applied using Ordinary Differential Equations (ODE). We show here that a TH1/TH2 paradigm is only an external view of a complex multivariate system., (Copyright 2001 Academic Press.)

Many systems in chemistry, biology, finance, and social sciences present emerging features that are not easy to guess from the elementary interactions of their microscopic individual components. In the past, the macroscopic behavior of such systems was modeled by assuming that the collective dynamics of microscopic components can be effectively described collectively by equations acting on spatially continuous density distributions. It turns out that, to the contrary, taking into account the actual individual/discrete character of the microscopic components of these systems is crucial for explaining their macroscopic behavior. In fact, we find that in conditions in which the continuum approach would predict the extinction of all of the population (respectively the vanishing of the invested capital or the concentration of a chemical substance, etc.), the microscopic granularity insures the emergence of macroscopic localized subpopulations with collective adaptive properties that allow their survival and development. In particular it is found that in two dimensions "life" (the localized proliferating phase) always prevails.