951 resultados para vector auto-regressive model


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Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

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RÉSUMÉ : Le traitement répété à la phencyclidine (PCP), un bloqueur du récepteur NMDA (NMDAR), reproduit chez les rongeurs une partie de la symptomatologie typique de la schizophrénie. Le blocage prolongé du NMDAR par la PCP mime une hypofunction du NMDAR, une des principales altérations supposées exister dans les cerveaux des patients schizophréniques. Le but de notre étude était d'examiner les conséquences neurochimiques, métaboliques et fonctionnelles du traitement répété à la phencyclidine in vivo, au niveau du cortex préfrontal (cpf), une région cérébrale qui joue un rôle dans les déficits cognitifs observés chez les patients schizophréniques. Pour répondre à cette question, les rats ou les souris ont reçu chaque jour une injection soit de PCP (5 mg/kg), soit de solution saline, pendant 7 ou 14 jours. Les animaux ont ensuite été sacrifiés au moins 24 heures après le dernier traitement. Des tranches aiguës du cpf ont été préparées rapidement, puis stimulées avec une concentration élevée de KCI, de manière à induire une libération de glutamate à partir des terminaisons synaptiques excitatrices. Les résultats montrent que les tranches du cpf des animaux traités à la PCP ont libéré une quantité de glutamate significativement inférieure par rapport à celles des animaux contrôle. Ce déficit de libération a persisté 72 heures après la fin du traitement, tandis qu'il n'était pas observé dans le cortex visuel primaire, une autre région corticale. En outre, le traitement avec des antipsychotiques, l'halopéridol ou l'olanzapine, a supprimé le déficit induit par la PCP. Le même déficit de libération a été remarqué sur des synaptosomes obtenus à partir du cpf des animaux traités à la phenryclidine. Cette observation indique que la PCP induit une modification plastique adaptative du mécanisme qui contrôle la libération du glutamate dans les terminaisons synaptiques. Nous avons découvert que cette modification implique la sous-régulation d'un NMDAR présynaptique, qui serait doué d'un rôle d'autorécepteur stimulateur de la libération du glutamate. Grâce à des tests comportementaux conduits en parallèle et réalisés pour évaluer la fonctionnalité du cpf, nous avons observé chez les souris traitées à la PCP une flexibilité comportementale réduite lors d'un test de discrimination de stimuli visuels/tactiles. Le déficit cognitif était encore présent 4 jours après la dernière administration de PCP. La technique de l'autoradiographie quantitative du [14C]2-deoxyglucose a permis d'associer ce déficit à une réduction de l'activité métabolique cérébrale pendant le déroulement du test, particulièrement au niveau du cpf. Dans l'ensemble, nos résultats suggèrent que le blocage prolongé du NMDAR lors de l'administration répétée de PCP produit un déficit de libération du glutamate au niveau des terminaisons synaptiques excitatrices du cpf. Un tel déficit pourrait être provoqué par la sousrégulation d'un NMDAR présynaptique, qui aurait une fonction de stimulateur de libération; la transmission excitatrice du cpf s'en trouverait dans ce cas réduite. Ce résultat est en ligne avec l'activité métabolique et fonctionnelle réduite du cpf et l'observation de déficits cognitifs induits lors de l'administration de la PCP. ABSTRACT : Sub-chronic treatment with phencyclidine (PCP), an NMDA receptor (NMDAR) channel blocker, reproduces in rodents part of the symptomatology associated to schizophrenia in humans. Prolonged pharmacological blockade of NMDAR with PCP mimics NMDAR hypofunction, one of the main alterations thought to take place in the brains of schizophrenics. Our study was aimed at investigating the neurochemical, metabolic and behavioral consequences of repeated PCP administration in vivo, focusing on the functioning of the prefrontal cortex (pfc), a brain region highly relevant for the cognitive deficits observed in schizophrenic patients. Rats or mice received a daily administration of either PCP (5 mg/kg) or saline for 7 or 14 days. At least 24 hours after the last treatment the animals were sacrificed. Acute slices of the pfc were quickly prepared and challenged with high KCl to induce synaptic glutamate release. Pfc slices from PCP-treated animals released significantly less glutamate than slices from salinetreated animals. The deficit persisted 72 hours after the end of the treatment, while it was not observed in another cortical region: the primary visual cortex. Interestingly, treatment with antipsychotic drugs, either haloperidol or olanzapine, reverted the glutamate release defect induced by PCP treatment. The same release defect was observed in synaptosomes prepared from the pfc of PCP-treated animals, indicating that PCP induces a plastic adaptive change in the mechanism controlling glutamate release in the glutamatergic terminals. We discovered that such change most likely involves the down-regulation of a newly identified, pre-synaptic NMDAR with stimulatory auto-receptor function on glutamate release. In parallel sets of behavioral experiments challenging pfc function, mice sub-chronically treated with PCP displayed reduced behavioral flexibility (reversal learning) in a visual/tactile-cued discrimination task. The cognitive deficit was still evident 4 days after the last PCP administration and was associated to reduced brain metabolic activity during the performance of the behavioral task, notably in the pfc, as determined by [14C]2-deoxyglucose quantitative autoradiography. Clverall, our findings suggest that prolonged NMDAR blockade by repeated PCP administration results in a defect of glutamate release from excitatory afferents in the pfc, possibly ascribed to down-regulation of apre-synaptic stimulatory NMDAR. Deficient excitatory neurotransmission in the pfc is consistent with the reduced metabolic and functional activation of this area and the observed PCP-induced cognitive deficits.

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Estudi realitzat a partir d’una estada al Institut de Génétique Moléculaire de Montpellier, França, entre 2010 i 2012. En aquest projecte s’ha avaluat les avantatges dels vectors adenovirals canins tipus 2 (CAV2) com a vectors de transferència gènica al sistema nerviós central (SNC) en un model primat no-humà i en un model caní del síndrome de Sly (mucopolisacaridosis tipus 7, MPS VII), malaltia monogènica que cursa amb neurodegeneració. En una primera part del projecte s’ha avaluat la biodistribució, l’eficàcia i la durada de l’expressió del transgen en un model primat no humà, (Microcebus murinus). Com ha vector s’ha utilitzat un CAV2 de primera generació que expressa la proteïna verda fluorescent (CAVGFP). Els resultats aportats en aquesta memòria demostren que en primats no humans, com en d’altres espècies testades anteriorment per l’equip de l’EJ Kremer, la injecció intracerebral de CAV2 resulta en una extensa transducció del SNC, siguent les neurones i els precursors neuronals les cèl•lules preferencialment transduïdes. Els vectors canins, servint-se de vesícules intracel•lulars són transportats, majoritàriament, des de les sinapsis cap al soma neuronal, aquest transport intracel•lular permet una extensa transducció del SNC a partir d’una única injecció intracerebral dels vectors virals. En una segona part d’aquest projecte s’ha avaluat l’ús terapèutic dels CAV2. S’ha injectat un vector helper-dependent que expressa el gen la b-glucuronidasa i el gen de la proteïna verda fluorescent (HD-RIGIE), en el SNC del model caní del síndrome de Sly (MPS VII). La biodistribució i la eficàcia terapèutica han estat avaluades. Els nivells d’activitat enzimàtica en animals malalts injectats amb el vector terapèutic va arribar a valors similars als dels animals no afectes. A més a més s’ha observat una reducció en la quantitat dels GAGs acumulats en les cèl•lules dels animals malalts tractats amb el vector terapèutic, demostrant la potencialitat terapèutica dels CAV2 per a malalties que afecten al SNC. Els resultats aportats en aquest treball ens permeten dir que els CAV2 són unes bones eines terapèutiques per al tractament de malalties que afecten al SNC.

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Purpose: Gene therapy of severe retinal dystrophies directly affecting photoreceptor is still a challenge in terms of clinical application. One of the main hurdles is to generate high transgene expression specifically in rods or cones. In the present study, we are investigating the possibility to drive hPDE6b expression in the Rd10 mouse retina using a specific sequence of the human PDE6b promoter. Methods: Two 5' flanking fragments of the human PDE6b gene: (-93 to +53 (146 bp) and -297 to +53 (350 bp, see Di Polo and Farber, 1995) were cloned in different plasmids in order to check their expression in vitro and in vivo. These elements drove the activity of either luciferase (pGL3 plasmids) or EGFP (AAV2/8 backbone). Then, an AAV2/8 vector carrying the PDE6b cDNA was tested with subretinal injections at P9 in the Rd10 eyes. Eye fundus, OCT, ERG recordings and histological investigations were performed to assess the efficacy of the gene transfer. Results: The short PDE6b promoter containing 146bp (-93 to +53) showed the highest activity in the Y-79 cells, as described previously (Di Polo and Farber, 1995). Subretinal administrations of AAV2/8-PDE6bpromoter-EGFP allowed a rapid expression specifically in rods and not in cones. The expression is faster than a vector containing the CMV promoter. The AAV2/8-PDE6bpromoter-PDE6b and the control vector were injected at P9 in the Rd10 mouse retina and investigated 5 weeks post-injection. Out of 14 eyes, 6 presented an increased rod sensitivity of about 300 fold, and increased a- and b-wave responses in ERG recordings. Flicker stimulations revealed that cones are also functional. OCT images and histological analyses revealed an increased ONL size in the injected area. The retina treated with the therapeutic vector presented 4-6 rows of photoreceptors with outersegments containing PDE6b. In the control eyes, only 2-4 rows of photoreceptors with almost no OS were observed . Conclusions: The 146 bp promoter sequence (-93 to + 53) is the shortest regulatory element described to date which allows to obtain efficient rod-specific expression in the context of somatic gene transfer. This first result is of great interest for AAV vector design in general allowing more space for the accommodation of transgenes of interest and good expression in rods. Moreover we showed the proof of principle of the efficacy of AAV2/8-PDE6bp-PDE6b vector in the Rd10 mouse model of severe photoreceptor degeneration without using neither AAV mutated capsids, nor self-complementary vectors.

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Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.

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The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

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Recognition systems play a key role in a range of biological processes, including mate choice, immune defence and altruistic behaviour. Social insects provide an excellent model for studying recognition systems because workers need to discriminate between nestmates and non-nestmates, enabling them to direct altruistic behaviour towards closer kin and to repel potential invaders. However, the level of aggression directed towards conspecific intruders can vary enormously, even among workers within the same colony. This is usually attributed to differences in the aggression thresholds of individuals or to workers having different roles within the colony. Recent evidence from the weaver ant Oecophylla smaragdina suggests that this does not tell the whole story. Here I propose a new model for nestmate recognition based on a vector template derived from both the individual's innate odour and the shared colony odour. This model accounts for the recent findings concerning weaver ants, and also provides an alternative explanation for why the level of aggression expressed by a colony decreases as the diversity within the colony increases, even when odour is well-mixed. The model makes additional predictions that are easily tested, and represents a significant advance in our conceptualisation of recognition systems.

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Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by an expansion of CAG repeats in the huntingtin (Htt) gene. Despite intensive efforts devoted to investigating the mechanisms of its pathogenesis, effective treatments for this devastating disease remain unavailable. The lack of suitable models recapitulating the entire spectrum of the degenerative process has severely hindered the identification and validation of therapeutic strategies. The discovery that the degeneration in HD is caused by a mutation in a single gene has offered new opportunities to develop experimental models of HD, ranging from in vitro models to transgenic primates. However, recent advances in viral-vector technology provide promising alternatives based on the direct transfer of genes to selected sub-regions of the brain. Rodent studies have shown that overexpression of mutant human Htt in the striatum using adeno-associated virus or lentivirus vectors induces progressive neurodegeneration, which resembles that seen in HD. This article highlights progress made in modeling HD using viral vector gene transfer. We describe data obtained with of this highly flexible approach for the targeted overexpression of a disease-causing gene. The ability to deliver mutant Htt to specific tissues has opened pathological processes to experimental analysis and allowed targeted therapeutic development in rodent and primate pre-clinical models.

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OBJECTIVE: Fibrotic changes are initiated early in acute respiratory distress syndrome. This may involve overproliferation of alveolar type II cells. In an animal model of acute respiratory distress syndrome, we have shown that the administration of an adenoviral vector overexpressing the 70-kd heat shock protein (AdHSP) limited pathophysiological changes. We hypothesized that this improvement may be modulated, in part, by an early AdHSP-induced attenuation of alveolar type II cell proliferation. DESIGN: Laboratory investigation. SETTING: Hadassah-Hebrew University and University of Pennsylvania animal laboratories. SUBJECTS: Sprague-Dawley Rats (250 g). INTERVENTIONS: Lung injury was induced in male Sprague-Dawley rats via cecal ligation and double puncture. At the time of cecal ligation and double puncture, we injected phosphate-buffered saline, AdHSP, or AdGFP (an adenoviral vector expressing the marker green fluorescent protein) into the trachea. Rats then received subcutaneous bromodeoxyuridine. In separate experiments, A549 cells were incubated with medium, AdHSP, or AdGFP. Some cells were also stimulated with tumor necrosis factor-alpha. After 48 hrs, cytosolic and nuclear proteins from rat lungs or cell cultures were isolated. These were subjected to immunoblotting, immunoprecipitation, electrophoretic mobility shift assay, fluorescent immunohistochemistry, and Northern blot analysis. MEASUREMENTS AND MAIN RESULTS: Alveolar type I cells were lost within 48 hrs of inducing acute respiratory distress syndrome. This was accompanied by alveolar type II cell proliferation. Treatment with AdHSP preserved alveolar type I cells and limited alveolar type II cell proliferation. Heat shock protein 70 prevented overexuberant cell division, in part, by inhibiting hyperphosphorylation of the regulatory retinoblastoma protein. This prevented retinoblastoma protein ubiquitination and degradation and, thus, stabilized the interaction of retinoblastoma protein with E2F1, a key cell division transcription factor. CONCLUSIONS: : Heat shock protein 70-induced attenuation of cell proliferation may be a useful strategy for limiting lung injury when treating acute respiratory distress syndrome if consistent in later time points.

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Fluvial deposits are a challenge for modelling flow in sub-surface reservoirs. Connectivity and continuity of permeable bodies have a major impact on fluid flow in porous media. Contemporary object-based and multipoint statistics methods face a problem of robust representation of connected structures. An alternative approach to model petrophysical properties is based on machine learning algorithm ? Support Vector Regression (SVR). Semi-supervised SVR is able to establish spatial connectivity taking into account the prior knowledge on natural similarities. SVR as a learning algorithm is robust to noise and captures dependencies from all available data. Semi-supervised SVR applied to a synthetic fluvial reservoir demonstrated robust results, which are well matched to the flow performance

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Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.

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Neuronal autophagy is increased in numerous excitotoxic conditions including neonatal cerebral hypoxia-ischemia (HI). However, the role of this HI-induced autophagy remains unclear. To clarify this role we established an in vitro model of excitotoxicity combining kainate treatment (Ka, 30 µM) with hypoxia (Hx, 6% oxygen) in primary neuron cultures. KaHx rapidly induced excitotoxic death that was completely prevented by MK801 or EGTA. KaHx also stimulated neuronal autophagic flux as shown by a rise in autophagosome number (increased levels of LC3-II and punctate LC3 labeling) accompanied by increases in lysosomal abundance and activity (increased SQSTM1/p62 degradation, and increased LC3-II levels in the presence of lysosomal inhibitors) and fusion (shown using an RFP-GFP-LC3 reporter). To determine the role of the enhanced autophagy we applied either pharmacological autophagy inhibitors (3-methyladenine or pepstatinA/E64) or lentiviral vectors delivering shRNAs targeting Becn1 or Atg7. Both strategies reduced KaHx-induced neuronal death. A prodeath role of autophagy was also confirmed by the enhanced toxicity of KaHx in cultures overexpressing BECN1 or ATG7. Finally, in vivo inhibition of autophagy by intrastriatal injection of a lentiviral vector expressing a Becn1-targeting shRNA increased the volume of intact striatum in a rat model of severe neonatal cerebral HI. These results clearly show a death-mediating role of autophagy in hypoxic-excitotoxic conditions and suggest that inhibition of autophagy should be considered as a neuroprotective strategy in HI brain injuries.

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Cervical cancer results from infection with high-risk type human papillomaviruses (HPV). Therapeutic vaccines aiming at controlling existing genital HPV infections and associated lesions are usually tested in mice with HPV-expressing tumor cells subcutaneously implanted into their flank. However, effective vaccine-induced regression of these ectopic tumors strongly contrasts with the poor clinical results of these vaccines produced in patients with HPV-associated genital neoplasia. To assess HPV therapeutic vaccines in a more relevant setting, we have, here, established an orthotopic mouse model where tumors in the genital mucosa (GM) develop after an intravaginal instillation of HPV16 E6/E7-expressing tumor cells transduced with a luciferase-encoding lentiviral vector for in vivo imaging of tumor growth. Tumor take was 80-90% after nonoxynol-9 induced damage of the epithelium. Tumors remained localized in the genital tract, and histological analysis showed that most tumors grew within the squamous epithelium of the vaginal wall. Those tumors induced (i) E7-specific CD8 T cells restricted to the GM and draining lymph nodes, in agreement with their mucosal location and (ii) high Foxp3+ CD4+ infiltrates, similarly to those found in natural non-regressing HPV lesions. This novel genital HPV-tumor model by requiring GM homing of vaccine-induced immune responses able to overcome local immuno-suppression may be more representative of the situation occurring in patients upon therapeutic vaccination.

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The paper presents a novel method for monitoring network optimisation, based on a recent machine learning technique known as support vector machine. It is problem-oriented in the sense that it directly answers the question of whether the advised spatial location is important for the classification model. The method can be used to increase the accuracy of classification models by taking a small number of additional measurements. Traditionally, network optimisation is performed by means of the analysis of the kriging variances. The comparison of the method with the traditional approach is presented on a real case study with climate data.

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This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.