914 resultados para Reactive Probabilistic Automata
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Dorsal and ventral pathways for syntacto-semantic speech processing in the left hemisphere are represented in the dual-stream model of auditory processing. Here we report new findings for the right dorsal and ventral temporo-frontal pathway during processing of affectively intonated speech (i.e. affective prosody) in humans, together with several left hemispheric structural connections, partly resembling those for syntacto-semantic speech processing. We investigated white matter fiber connectivity between regions responding to affective prosody in several subregions of the bilateral superior temporal cortex (secondary and higher-level auditory cortex) and of the inferior frontal cortex (anterior and posterior inferior frontal gyrus). The fiber connectivity was investigated by using probabilistic diffusion tensor based tractography. The results underscore several so far underestimated auditory pathway connections, especially for the processing of affective prosody, such as a right ventral auditory pathway. The results also suggest the existence of a dual-stream processing in the right hemisphere, and a general predominance of the dorsal pathways in both hemispheres underlying the neural processing of affective prosody in an extended temporo-frontal network.
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PURPOSE: As compared with natural tumor peptide sequences, carefully selected analog peptides may be more immunogenic and thus better suited for vaccination. However, T cells in vivo activated by such altered analog peptides may not necessarily be tumor specific because sequence and structure of peptide analogs differ from corresponding natural peptides. EXPERIMENTAL DESIGN: Three melanoma patients were immunized with a Melan-A peptide analog that binds more strongly to HLA-A*0201 and is more immunogenic than the natural sequence. This peptide was injected together with a saponin-based adjuvant, followed by surgical removal of lymph node(s) draining the site of vaccination. RESULTS: Ex vivo analysis of vaccine site draining lymph nodes revealed antigen-specific CD8+ T cells, which had differentiated to memory cells. In vitro, these cells showed accelerated proliferation upon peptide stimulation. Nearly all (16 of 17) of Melan-A-specific CD8+ T-cell clones generated from these lymph nodes efficiently killed melanoma cells. CONCLUSIONS: Patient immunization with the analog peptide leads to in vivo activation of T cells that were specific for the natural tumor antigen, demonstrating the usefulness of the analog peptide for melanoma immunotherapy.
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This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.
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When dealing with the design of service networks, such as healthand EMS services, banking or distributed ticket selling services, thelocation of service centers has a strong influence on the congestion ateach of them, and consequently, on the quality of service. In this paper,several models are presented to consider service congestion. The firstmodel addresses the issue of the location of the least number of single--servercenters such that all the population is served within a standard distance,and nobody stands in line for a time longer than a given time--limit, or withmore than a predetermined number of other clients. We then formulateseveral maximal coverage models, with one or more servers per service center.A new heuristic is developed to solve the models and tested in a 30--nodesnetwork.
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Superantigens are defined by their ability to stimulate a large fraction of T cells via interaction with the T cell receptor (TCR) V beta domain. Endogenous superantigens, classically termed minor lymphocyte-stimulating (Mls) antigens, were recently identified as products of open reading frames (ORF) in integrated proviral copies of mouse mammary tumor virus (MMTV). We have described an infectious MMTV homologue of the classical endogenous superantigen Mls-1a (Mtv-7). The ORF molecules of both the endogenous Mtv-7 and the infectious MMTV(SW) interact with T cells expressing the TCR V beta 6, 7, 8.1, and 9 domains. Furthermore, the COOH termini of their ORF molecules, thought to confer TCR specificity, are very similar. Since successful transport of MMTV from the site of infection in the gut to the mammary gland depends on a functional immune system, we were interested in determining the early events after and requirements for MMTV infection. We show that MMTV(SW) infection induces a massive response of V beta 6+ CDC4+ T cells, which interact with the viral ORF. Concomitantly, we observed a B cell response and differentiation that depends on both the presence and stimulation of the superantigen-reactive T cells. Furthermore, we show that B cells are the main target of the initial MMTV infection as judged by the presence of the reverse-transcribed viral genome and ORF transcripts. Thus, we suggest that MMTV infection of B cells leads to ORF-mediated B-T cell interaction, which maintains and possibly amplifies viral infection.
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This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results
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BACKGROUND: Reactive electroencephalography (EEG) background during therapeutic hypothermia (TH) is related to favorable prognosis after cardiac arrest (CA), but its predictive value is not 100 %. The aim of this study was to investigate outcome predictors after a first reactive EEG recorded during TH after CA. METHODS: We studied a cohort of consecutive comatose adults admitted between February 2008 and November 2012, after successful resuscitation from CA, selecting patients with reactive EEG during TH. Outcome was assessed at three months, and categorized as survivors and non-survivors (no patient was in vegetative state). Demographics, clinical variables, EEG features, serum neuron-specific enolase (NSE) and procalcitonin, were compared using uni- and multivariable analyses. RESULTS: A total of 290 patients were treated with TH after cardiac arrest; 146 had an EEG during TH, which proved reactive in 90 of them; 77 (86 %) survived and 13 (14 %) died (without recovery from coma). The group of non-survivors had a higher occurrence of discontinuous EEG (p = 0.006; multivariate analysis p = 0.026), and a higher serum NSE peak (p = 0.021; multivariate analysis p = 0.014); conversely, demographics, and other clinical variables including serum procalcitonin did not differ. CONCLUSIONS: A discontinuous EEG and high serum NSE are associated with mortality after CA in patients with poor outcome despite a reactive hypothermic EEG. This suggests more severe cerebral damage, but not to higher extent of systemic disease.
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We prospectively compared the diagnostic value of C-reactive protein (CRP) and white blood cell counts for detection of neonatal septicaemia. Sensitivity and specifity in receiver operating characteristics, and positive and negative predictive value of CRP and white blood cell count were compared in 195 critically ill preterm and term newborns clinically suspected of infection. Blood cultures were positive in 33 cases. During the first 3 days after birth CRP elevation (sensitivity 75%, specifity 86%), leukopenia (67%/90%), neutropenia (78%/80%) and immature to total neutrophil count (I/T) ratio (78%/73%) were good diagnostic parameters, as opposed to band forms with absolute count (84%/66%) or percentage (79%/71%), thrombocytopenia (65%/57%) and toxic granulations (44%/94%). Beyond 3 days of age elevated CRP (88%/87%) was the best parameter. Increased total (84%/66%) or percentage band count (79%/71%) were also useful. Leukocytosis (74%/56%), increased neutrophils (67%/65%), I/T ratio (79%/47%), thrombocytopenia (65%/57%) and toxic granulations had a low specifity. The positive predictive value of CRP was 32% before and 37% after 3 days of age, that of leukopenia was 37% in the first 3 days. CONCLUSION: During the first 3 days of life CRP, leukopenia and neutropenia were comparably good tests while after 3 days of life CRP was the best single test in early detection of neonatal septicaemia. Serial CRP estimations confirm the diagnosis, monitor the course of infection and the efficacy of antibiotic treatment.
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Primary tumor growth induces host tissue responses that are believed to support and promote tumor progression. Identification of the molecular characteristics of the tumor microenvironment and elucidation of its crosstalk with tumor cells may therefore be crucial for improving our understanding of the processes implicated in cancer progression, identifying potential therapeutic targets, and uncovering stromal gene expression signatures that may predict clinical outcome. A key issue to resolve, therefore, is whether the stromal response to tumor growth is largely a generic phenomenon, irrespective of the tumor type or whether the response reflects tumor-specific properties. To address similarity or distinction of stromal gene expression changes during cancer progression, oligonucleotide-based Affymetrix microarray technology was used to compare the transcriptomes of laser-microdissected stromal cells derived from invasive human breast and prostate carcinoma. Invasive breast and prostate cancer-associated stroma was observed to display distinct transcriptomes, with a limited number of shared genes. Interestingly, both breast and prostate tumor-specific dysregulated stromal genes were observed to cluster breast and prostate cancer patients, respectively, into two distinct groups with statistically different clinical outcomes. By contrast, a gene signature that was common to the reactive stroma of both tumor types did not have survival predictive value. Univariate Cox analysis identified genes whose expression level was most strongly associated with patient survival. Taken together, these observations suggest that the tumor microenvironment displays distinct features according to the tumor type that provides survival-predictive value.
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Résumé Il est actuellement reconnu que l'endothélium vasculaire joue un rôle primordial dans la genèse des maladies cardiovasculaires, notamment l'artériosclérose. Dès lors, il est important de pouvoir investiguer la fonction endothéliale en clinique. Pour ce faire, il est particulièrement simple d'examiner la microcirculation cutanée, car celle-ci est très simplement accessible, de manière non-invasive, par fluxmétrie laser-Doppler. Pratiquement, on mesure l'augmentation du flux sanguin dermique en réponse à des stimuli connus pour agir via l'endothélium vasculaire. Les stimuli endothélium-dépendants les plus courants sont l'interruption temporaire du flux sanguin qui est suivie d'une hyperémie réactive, et l'administration transcutanée d'acétylcholine (Ach) par iontophorèse. La iontophorèse consiste à obtenir le transfert d' une substance ionisée, telle l'Ach, par l'application d'un courant électrique de polarité appropriée. L'objectif du présent travail était de déterminer le rôle des prostaglandines dans ces réponse vasodilatatrices dépendante de l'endothélium, rôle actuellement peu clair. 23 jeunes hommes volontaires non fumeurs et en bonne santé habituelle ont été examinés lors de deux visites séparées par 1 à 3 semaines. Lors de chaque visite, l'hyperémie réactive et la réponse vasodilatatrice à l'Ach ont été déterminées dans la peau de l'avant bras après administration soit d'un placebo, soit d'un inhibiteur de la cyclooxygénase (COX, enzyme qui contrôle la synthèse des prostaglandines). Chez certains sujets, l'inhibiteur était de l'acétylsalicylate de lysine (900 mg par voie intraveineuse). Chez d'autres sujets, il s'agissait d'indométhacine. (75 mg par voie orale). Comme la stimulation nociceptive liée au courant iontophorétique peut influencer la réponse à l'Ach, celle-ci a été déterminée en présence et en l'absence d'anesthésie de surface (crème de lidocaine). La réponse à l'Ach a été obtenue pour 4 doses différentes de cet agent (exprimées sous la forme de la densité de charge iontophorétique appliquée : 0.28, 1.4, 7, et 14 millicoulombs par cm2 de peau exposée). Le flux sanguin dermique était mesuré par imagerie laser-Doppler, une variante de la fluxmétrie laser-Doppler classique permettant l'exploration d'une surface de peau de taille arbitraire. Quelle que soit la condition testée, nous n'avons jamais observé la moindre influence de l'inhibition de la COX sur l'hyperémie réactive, ni sur la réponse à l'Ach. Cette dernière était augmentée significativement par l'anesthésie cutanée, que les sujets aient reçu ou non de l'acétylsalicylate de lysine ou de l'indométhacine . Par exemple, la réponses moyenne (±SD) à la plus haute dose d'Ach (testée sur 6 sujets, et exprimée en unités de perfusion, comme il est d'usage en fluxmétrie laser-Doppler ) était la suivante : en l'absence d'anesthésie : acétylsalicylate de lysine 339 ± 105, placebo 344 ± 68 ; avec l'anesthésie : acétylsalicylate de lysine 453 ± 76 , placebo 452 ± 65 (p * 0.001 pour les effets de l'anesthésie). En conclusion, nos résultats infirment une contribution des prostaglandines à l'hyperémie réactive ou à la vasodilatation induite par l'acétylcholine dans la microcirculation cutanée. Dans ce lit vasculaire, l'anesthésie locale accroît la vasodilatation induite par l'acétylcholine par un mécanisme indépendant des prostaglandines.
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L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.
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Background: Metabolic flux profiling based on the analysis of distribution of stable isotope tracer in metabolites is an important method widely used in cancer research to understand the regulation of cell metabolism and elaborate new therapeutic strategies. Recently, we developed software Isodyn, which extends the methodology of kinetic modeling to the analysis of isotopic isomer distribution for the evaluation of cellular metabolic flux profile under relevant conditions. This tool can be applied to reveal the metabolic effect of proapoptotic drug edelfosine in leukemia Jurkat cell line, uncovering the mechanisms of induction of apoptosis in cancer cells. Results: The study of 13C distribution of Jukat cells exposed to low edelfosine concentration, which induces apoptosis in ¿5% of cells, revealed metabolic changes previous to the development of apoptotic program. Specifically, it was found that low dose of edelfosine stimulates the TCA cycle. These metabolic perturbations were coupled with an increase of nucleic acid synthesis de novo, which indicates acceleration of biosynthetic and reparative processes. The further increase of the TCA cycle fluxes, when higher doses of drug applied, eventually enhance reactive oxygen species (ROS) production and trigger apoptotic program. Conclusion: The application of Isodyn to the analysis of mechanism of edelfosine-induced apoptosis revealed primary drug-induced metabolic changes, which are important for the subsequent initiation of apoptotic program. Initiation of such metabolic changes could be exploited in anticancer therapy.
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Increased production of reactive oxygen species (ROS) in mitochondria underlies major systemic diseases, and this clinical problem stimulates a great scientific interest in the mechanism of ROS generation. However, the mechanism of hypoxia-induced change in ROS production is not fully understood. To mathematically analyze this mechanism in details, taking into consideration all the possible redox states formed in the process of electron transport, even for respiratory complex III, a system of hundreds of differential equations must be constructed. Aimed to facilitate such tasks, we developed a new methodology of modeling, which resides in the automated construction of large sets of differential equations. The detailed modeling of electron transport in mitochondria allowed for the identification of two steady state modes of operation (bistability) of respiratory complex III at the same microenvironmental conditions. Various perturbations could induce the transition of respiratory chain from one steady state to another. While normally complex III is in a low ROS producing mode, temporal anoxia could switch it to a high ROS producing state, which persists after the return to normal oxygen supply. This prediction, which we qualitatively validated experimentally, explains the mechanism of anoxia-induced cell damage. Recognition of bistability of complex III operation may enable novel therapeutic strategies for oxidative stress and our method of modeling could be widely used in systems biology studies.