Enhanced Neural Progenitor/Stem Cells Self-Renewal via the Interaction of Stress-Inducible Protein 1 with the Prion Protein

Prion protein (PrPC), when associated with the secreted form of the stress-inducible protein 1 (STI1), plays an important role in neural survival, neuritogenesis, and memory formation. However, the role of the PrP(C)-STI1 complex in the physiology of neural progenitor/stem cells is unknown. In this article, we observed that neurospheres cultured from fetal forebrain of wild-type (Prnp(+/+)) and PrP(C)-null (Prnp(0/0)) mice were maintained for several passages without the loss of self-renewal or multipotentiality, as assessed by their continued capacity to generate neurons, astrocytes, and oligodendrocytes. The homogeneous expression and colocalization of STI1 and PrP(C) suggest that they may associate and function as a complex in neurosphere-derived stem cells. The formation of neurospheres from Prnp(0/0) mice was reduced significantly when compared with their wild-type counterparts. In addition, blockade of secreted STI1, and its cell surface ligand, PrP(C), with specific antibodies, impaired Prnp(+/+) neurosphere formation without further impairing the formation of Prnp(0/0) neurospheres. Alternatively, neurosphere formation was enhanced by recombinant STI1 application in cells expressing PrP(C) but not in cells from Prnp(0/0) mice. The STI1-PrP(C) interaction was able to stimulate cell proliferation in the neurosphere-forming assay, while no effect on cell survival or the expression of neural markers was observed. These data suggest that the STI1-PrP(C) complex may play a critical role in neural progenitor/stem cells self-renewal via the modulation of cell proliferation, leading to the control of the stemness capacity of these cells during nervous system development. STEM CELLS 2011;29:1126-1136

MyD88 Signaling Is Required for Efficient Innate and Adaptive Immune Responses to Paracoccidioides brasiliensis Infection

The mechanisms that govern the initial interaction between Paracoccidioides brasiliensis, a primary dimorphic fungal pathogen, and cells of the innate immunity need to be clarified. Our previous studies showed that Toll-like receptor 2 (TLR2) and TLR4 regulate the initial interaction of fungal cells with macrophages and the pattern of adaptive immunity that further develops. The aim of the present investigation was to assess the role of MyD88, an adaptor molecule used by TLRs to activate genes of the inflammatory response in pulmonary paracoccidioidomycosis. Studies were performed with normal and MyD88(-/-) C57BL/6 mice intratracheally infected with P. brasiliensis yeast cells. MyD88(-/-) macrophages displayed impaired interaction with fungal yeast cells and produced low levels of IL-12, MCP-1, and nitric oxide, thus allowing increased fungal growth. Compared with wild-type (WT) mice, MyD88(-/-) mice developed a more severe infection of the lungs and had marked dissemination of fungal cells to the liver and spleen. MyD88(-/-) mice presented low levels of Th1, Th2, and Th17 cytokines, suppressed lymphoproliferation, and impaired influx of inflammatory cells to the lungs, and this group of cells comprised lower numbers of neutrophils, activated macrophages, and T cells. Nonorganized, coalescent granulomas, which contained high numbers of fungal cells, characterized the severe lesions of MyD88(-/-) mice; the lesions replaced extensive areas of several organs. Therefore, MyD88(-/-) mice were unable to control fungal growth and showed a significantly decreased survival time. In conclusion, our findings demonstrate that MyD88 signaling is important in the activation of fungicidal mechanisms and the induction of protective innate and adaptive immune responses against P. brasiliensis.

Sleep deprivation of rats: The hyperphagic response is real

Study Objectives: Chronic sleep deprivation of rats causes hyperphagia without body weight gain. Sleep deprivation hyperphagia is prompted by changes in pathways governing food intake; hyperphagia may be adaptive to sleep deprivation hypermetabolism. A recent paper suggested that sleep deprivation might inhibit ability of rats to increase food intake and that hyperphagia may be an artifact of uncorrected chow spillage. To resolve this, a palatable liquid diet (Ensure) was used where spillage is insignificant. Design: Sleep deprivation of male Sprague Dawley rats was enforced for 10 days by the flowerpot/platform paradigm. Daily food intake and body weight were measured. On day 10, rats were transcardially perfused for analysis of hypothalamic mRNA expression of the orexigen, neuropeptide Y (NPY). Setting: Morgan State University, sleep deprivation and transcardial perfusion; University of Maryland, NPY in situ hybridization and analysis. Measurements and Results: Using a liquid diet for accurate daily measurements, there was no change in food intake in the first 5 days of sleep deprivation. Importantly, from days 6-10 it increased significantly, peaking at 29% above baseline. Control rats steadily gained weight but sleep-deprived rats did not. Hypothalamic NPY mRNA levels were positively correlated to stimulation of food intake and negatively correlated with changes in body weight. Conclusion: Sleep deprivation hyperphagia may not be apparent over the short term (i.e., <= 5 days), but when extended beyond 6 days, it is readily observed. The timing of changes in body weight and food intake suggests that the negative energy balance induced by sleep deprivation prompts the neural changes that evoke hyperphagia.

Early Increase in Autoantibodies Against Human Oxidized Low-Density Lipoprotein in Hypertensive Patients After Blood Pressure Control

BACKGROUND Oxidized lipoproteins and antioxidized low-density lipoprotein (anti-oxLDL) antibodies (Abs) have been detected in plasma in response to blood pressure (BP) elevation, suggesting the participation of the adaptive immune system. Therefore, treatment of hypertension may act on the immune response by decreasing oxidation stimuli. However, this issue has not been addressed. Thus, we have here analyzed anti-oxLDL Abs in untreated (naive) hypertensive patients shortly after initiation of anti hypertensive therapeutic regimens. METHODS Titers of anti-oxLDL Abs were measured in subjects with recently diagnosed hypertension on stage 1 (n = 94), in primary prevention of coronary disease, with no other risk factors, and naive of anti hypertensive medication at entry. Subjects were randomly assigned to receive perindopril, hydrochlorothiazide (HCTZ), or indapamide (INDA) for 12 weeks, with additional perindopril if necessary to achieve BP control. Abs against copper-oxidized LDL were measured by enzyme-linked immunosorbent assay. RESULTS Twelve-week antihypertensive treatment reduced both office-based and 24-h ambulatory BP measurements (P < 0.0005). The decrease in BP was accompanied by reduction in thiobarbituric acid-reactive substances (TBARS) (P < 0.05), increase in anti-oxLDL Ab titers (P < 0.005), and improvement in flow-mediated dilation (FMD) (P < 0.0005), independently of treatment. Although BP was reduced, we observed favorable changes in anti-oxLDL titers and FMD. CONCLUSIONS We observed that anti-oxLDL Ab titers increase after antihypertensive therapy in primary prevention when achieving BP targets. Our results are in agreement with the concept that propensity to oxidation is increased by essential hypertension and anti-oxLDL Abs may be protective and potential biomarkers for the follow-up of hypertension treatment.

A Robust, Fully Adaptive Hybrid Level-Set/Front-Tracking Method for Two-Phase Flows with an Accurate Surface Tension Computation

We present a variable time step, fully adaptive in space, hybrid method for the accurate simulation of incompressible two-phase flows in the presence of surface tension in two dimensions. The method is based on the hybrid level set/front-tracking approach proposed in [H. D. Ceniceros and A. M. Roma, J. Comput. Phys., 205, 391400, 2005]. Geometric, interfacial quantities are computed from front-tracking via the immersed-boundary setting while the signed distance (level set) function, which is evaluated fast and to machine precision, is used as a fluid indicator. The surface tension force is obtained by employing the mixed Eulerian/Lagrangian representation introduced in [S. Shin, S. I. Abdel-Khalik, V. Daru and D. Juric, J. Comput. Phys., 203, 493-516, 2005] whose success for greatly reducing parasitic currents has been demonstrated. The use of our accurate fluid indicator together with effective Lagrangian marker control enhance this parasitic current reduction by several orders of magnitude. To resolve accurately and efficiently sharp gradients and salient flow features we employ dynamic, adaptive mesh refinements. This spatial adaption is used in concert with a dynamic control of the distribution of the Lagrangian nodes along the fluid interface and a variable time step, linearly implicit time integration scheme. We present numerical examples designed to test the capabilities and performance of the proposed approach as well as three applications: the long-time evolution of a fluid interface undergoing Rayleigh-Taylor instability, an example of bubble ascending dynamics, and a drop impacting on a free interface whose dynamics we compare with both existing numerical and experimental data.

Directed Differentiation of Neural Progenitors into Neurons Is Accompanied by Altered Expression of P2X Purinergic Receptors

Neural differentiation has been extensively studied in vitro in a model termed neurospheres, which consists of aggregates of neural progenitor cells. Previous studies suggest that they have a great potential for the treatment of neurological disorders. One of the major challenges for scientists is to control cell fate and develop ideal culture conditions for neurosphere expansion in vitro, without altering their features. Similar to human neural progenitors, rat neurospheres cultured in the absence of epidermal and fibroblast growth factors for a short period increased the levels of beta-3 tubulin and decreased the expression of glial fibrillary acidic protein and nestin, compared to neurospheres cultured in the presence of these factors. In this work, we show that rat neurospheres cultured in suspension under mitogen-free condition presented significant higher expression of P2X2 and P2X6 receptor subunits, when compared to cells cultured in the presence of growth factors, suggesting a direct relationship between P2X2/6 receptor expression and induction of neuronal differentiation in mitogen-free cultured rat neurospheres.

A fuzzy logic controller for intestinal levodopa infusion in Parkinson’s disease

The aim of this work is to evaluate the fuzzy system for different types of patients for levodopa infusion in Parkinson Disease based on simulation experiments using the pharmacokinetic-pharmacodynamic model. Fuzzy system is to control patient’s condition by adjusting the value of flow rate, and it must be effective on three types of patients, there are three different types of patients, including sensitive, typical and tolerant patient; the sensitive patients are very sensitive to drug dosage, but the tolerant patients are resistant to drug dose, so it is important for controller to deal with dose increment and decrement to adapt different types of patients, such as sensitive and tolerant patients. Using the fuzzy system, three different types of patients can get useful control for simulating medication treatment, and controller will get good effect for patients, when the initial flow rate of infusion is in the small range of the approximate optimal value for the current patient’ type.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

Metabolismo da homocisteína e defeitos do tubo neural : um estudo bioquímico e molecular no sul do Brasil

Os defeitos de fechamento de tubo neural constituem uma das malformações mais freqüentes na espécie humana, apresentando alta morbi-mortalidade. Sua etiologia é considerada multifatorial, estando envolvidos fatores genéticos e ambientais. Estes fatores estão relacionados principalmente com o metabolismo da homocisteína. Realizamos um estudo de caso-controle com o objetivo de estudar os fatores bioquímicos e genéticos relacionados ao DTN na nossa população. Em pares de afetados com DTN e suas mães e pares de pacientes normais e suas mães foram avaliados dosagem de folato, vitamina B12, homocisteína e polimorfismos da enzima metileno tetraidrofolato redutase (MTHFR), C677T e A1298C. A dosagem de folato nos casos foi 11,37 ng/mL(±6,72) e nos controles 5,64 ng/mL(±4,16) (p<0,001). O folato sérico das mães foi 7,27 ng/mL (±4,48) e 3,90 ng/mL (±1,77) nas mães controles (p<0,001). A média de dosagem de vitamina B12 foi de 641,88 pg/mL ((±262,21) nos casos e 743,27 pg/mL (±433,52) nos controles (p= 0,205). A média de dosagem de vitamina B12 nas mães dos casos foi 354,75 pg/mL (±142,06) e 465,25 pg/mL (±194,91) nas mães controles (p=0,004). O nível de homocisteína plasmático médio foi 6,89 μmol/L(±4,48) para os casos e 5,41 μmol/L (±2,55) para os controles (p=0,099). Nas mães dos casos a dosagem média de homocisteína foi 7,23 μmol/L (±2,64) e 7,00 μmol/L (±2,24) nas mães controles (p=0,666). Não houve diferença entre a freqüência dos genótipos C677T e A1298C da MTHFR nos casos e controles e suas mães. Para o polimorfismo C677T as freqüências dos alelo C e T foram respectivamente 0,6585 e 0,3414 nos pacientes com DTN; 0,6590 e 0,3410 nos controles; 0,6460 e 0,3540 nas mães dos casos e 0,6136 e 0,3860 nas mães controles. Para o polimorfismo A1298C as freqüências dos alelos A e C foram respectivamente 0,7436 e 0,2564 nos pacientes com DTN; 0,7610 e 0,2390 nos controles; 0,8055 e 0,1945 nas mães dos casos e 0,8065 e 0,1935 nas mães controles. Identificamos que indivíduos homozigotos 677TT apresentam um maior nível de homocisteína e este é inversamente relacionado com os níveis de vitamina B12. Estes achados sugerem que uma alteração metabólica relacionada ao metabolismo da homocisteína e principalmente devido à diminuição da vitamina B12 seja um fator de risco para DTN na nossa população.

An evolving possibilistic fuzzy modeling approach for value-at-risk estimation

Market risk exposure plays a key role for nancial institutions risk management. A possible measure for this exposure is to evaluate losses likely to incurwhen the price of the portfolio's assets declines using Value-at-Risk (VaR) estimates, one of the most prominent measure of nancial downside market risk. This paper suggests an evolving possibilistic fuzzy modeling approach for VaR estimation. The approach is based on an extension of the possibilistic fuzzy c-means clustering and functional fuzzy rule-based modeling, which employs memberships and typicalities to update clusters and creates new clusters based on a statistical control distance-based criteria. ePFM also uses an utility measure to evaluate the quality of the current cluster structure. Computational experiments consider data of the main global equity market indexes of United States, London, Germany, Spain and Brazil from January 2000 to December 2012 for VaR estimation using ePFM, traditional VaR benchmarks such as Historical Simulation, GARCH, EWMA, and Extreme Value Theory and state of the art evolving approaches. The results show that ePFM is a potential candidate for VaR modeling, with better performance than alternative approaches.

The combination of neural estimates in prediction and decision problems

In this dissertation, different ways of combining neural predictive models or neural-based forecasts are discussed. The proposed approaches consider mostly Gaussian radial basis function networks, which can be efficiently identified and estimated through recursive/adaptive methods. Two different ways of combining are explored to get a final estimate – model mixing and model synthesis –, with the aim of obtaining improvements both in terms of efficiency and effectiveness. In the context of model mixing, the usual framework for linearly combining estimates from different models is extended, to deal with the case where the forecast errors from those models are correlated. In the context of model synthesis, and to address the problems raised by heavily nonstationary time series, we propose hybrid dynamic models for more advanced time series forecasting, composed of a dynamic trend regressive model (or, even, a dynamic harmonic regressive model), and a Gaussian radial basis function network. Additionally, using the model mixing procedure, two approaches for decision-making from forecasting models are discussed and compared: either inferring decisions from combined predictive estimates, or combining prescriptive solutions derived from different forecasting models. Finally, the application of some of the models and methods proposed previously is illustrated with two case studies, based on time series from finance and from tourism.

Detecção de interface em tanques de petróleo usando transmissores de nível e controladores Fuzzy

This work presents a proposal to detect interface in atmospheric oil tanks by installing a differential pressure level transmitter to infer the oil-water interface. The main goal of this project is to maximize the quantity of free water that is delivered to the drainage line by controlling the interface. A Fuzzy Controller has been implemented by using the interface transmitter as the Process Variable. Two ladder routine was generated to perform the control. One routine was developed to calculate the error and error variation. The other was generate to develop the fuzzy controller itself. By using rules, the fuzzy controller uses these variables to set the output. The output is the position variation of the drainage valve. Although the ladder routine was implemented into an Allen Bradley PLC, Control Logix family it can be implemented into any brand of PLCs