Dot-Elisa for evaluation of hydatid cyst wall, protoscoleces and hydatid cyst fluid antigens in the serodiagnosis of cystic echinococcosis

The aim of the present study is to evaluate cyst wall and protoscolex as an alternate source of antigen in serodiagnosis of cystic echinococcosis (CE). A total of 90 blood samples, 30 each of confirmed CE cases, disease controls and healthy controls were collected. Dot-ELISA using cyst wall, protoscolex and cyst fluid were used to demonstrate anti-hydatid antibodies. The sensitivity of Dot-ELISA using cyst wall, protoscolex and cyst fluid was 96.66%, 86.66% and 93.33% respectively and the specificity of the assay was 70% for Dot-ELISA using cyst fluid, protoscolex and cyst wall antigens. Results of the present study show that cyst wall and protoscolex can also be an useful source of antigen in detection of hydatid antibodies in the serodiagnosis of CE.

Non-linear time series models

The last three decades have seen quite dramatic changes the way we modeled time dependent data. Linear processes have been in the center stage in modeling time series. As far as the second order properties are concerned, the theory and the methodology are very adequate.However, there are more and more evidences that linear models are not sufficiently flexible and rich enough for modeling purposes and that failure to account for non-linearities can be very misleading and have undesired consequences.

A score test for non-nested hypotheses with applications to discrete data models

This paper suggests that a convenient score test against non-nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. It is shown that this procedure is essentially a test for the correct specification of the conditional distribution of the variable of interest.

Summer Vacations not Only a Memory for Life, but Also a Rare Infection

Introduction: Rhinoscleroma is a rare, chronic, granulomatous disease that most frequently affects the upper respiratory tract, especially the nasal cavity and sometimes extends through the lower respiratory tract. Is associated with Klebsiella rhinoscleromatis, which is endemic in certain geographic regions namely Central America. The pathogenesis and risk factors remain unclear. Clinical case: We report a five years Old Portuguese boy, previously healthy, brought to the Emergency Department with epistaxis, without other accompanying signs or symptoms. The Otorhinolaryngologist (ORL) performed rhinoscopy and identified an intranasal bleeding mass. The MRI revealed an intranasal mass with extension to the ethmoid bone sinus, and performed biopsy. The histopathology was vital, making the diagnosis of Rhinoscleroma. The child had traveled abroad for the first time on vacations a year before to Dominican Republic. The bacteriologic exam identified a Klebsiella spp. sensible to the association of amoxicillin and clavulanic acid. Blood test performed excluded association of immunodeficiency. Since it’s a rare disease genetic study are under course. Monthly evaluation by ORL and pediatrician was performed which documented progressive reduction until total disappearing of the macro and microscopic lesion, and negative bacteriologic exam. Six months of antibiotic therapy were completed without any known secondary effects. The child remained asymptomatic up to the last visit, 3 months following treatment and has shown no evidence of recurrence. Conclusion: Globalization and free transit of people to areas far from origin countries here some rare diseases are endemic brings a new challenge to modern medicine. Sometimes vacations bring more than memories.

Comparing the performance of geostatistical models with additional information from covariates for sewage plume characterization

In this work, kriging with covariates is used to model and map the spatial distribution of salinity measurements gathered by an autonomous underwater vehicle in a sea outfall monitoring campaign aiming to distinguish the effluent plume from the receiving waters and characterize its spatial variability in the vicinity of the discharge. Four different geostatistical linear models for salinity were assumed, where the distance to diffuser, the west-east positioning, and the south-north positioning were used as covariates. Sample variograms were fitted by the Mat`ern models using weighted least squares and maximum likelihood estimation methods as a way to detect eventual discrepancies. Typically, the maximum likelihood method estimated very low ranges which have limited the kriging process. So, at least for these data sets, weighted least squares showed to be the most appropriate estimation method for variogram fitting. The kriged maps show clearly the spatial variation of salinity, and it is possible to identify the effluent plume in the area studied. The results obtained show some guidelines for sewage monitoring if a geostatistical analysis of the data is in mind. It is important to treat properly the existence of anomalous values and to adopt a sampling strategy that includes transects parallel and perpendicular to the effluent dispersion.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.

Analysis of Synaptic Proteins in the Cerebrospinal Fluid as a New Tool in the Study of Inborn Errors of Neurotransmission

Abstract In a few rare diseases, specialised studies in cerebrospinal fluid (CSF) are required to identify the underlying metabolic disorder. We aimed to explore the possibility of detecting key synaptic proteins in the CSF, in particular dopaminergic and gabaergic, as new procedures that could be useful for both pathophysiological and diagnostic purposes in investigation of inherited disorders of neurotransmission. Dopamine receptor type 2 (D2R), dopamine transporter (DAT) and vesicular monoamine transporter type 2 (VMAT2) were analysed in CSF samplesfrom 30 healthy controls (11 days to 17 years) by western blot analysis. Because VMAT2 was the only protein with intracellular localisation, and in order to compare results, GABA vesicular transporter, which is another intracellular protein, was also studied. Spearman’s correlation and Student’s t tests were applied to compare optical density signals between different proteins. All these synaptic proteins could be easily detected and quantified in the CSF. DAT, D2R and GABA VT expression decrease with age, particularly in the first months of life, reflecting the expected intense synaptic activity and neuronal circuitry formation. A statistically significant relationship was found between D2R and DAT expression, reinforcing the previous evidence of DAT regulation by D2R. To our knowledge, there are no previous studies on human CSF reporting a reliable analysis of these proteins. These kinds of studies could help elucidate new causes of disturbed dopaminergic and gabaergic transmission as well as understanding different responses to L-dopa in inherited disorders affecting dopamine metabolism. Moreover, this approach to synaptic activity in vivo can be extended to different groups of proteins and diseases.

Analysis of correlation between cerebrospinal fluid and plasma HIV-1 RNA levels in patients with neurological opportunistic diseases

The question of whether HIV-1 RNA in cerebrospinal fluid (CSF) is derived from viral replication in the central nervous system or simply reflects the transit of infected lymphocytes from the blood compartment has long been a matter of debate. Some studies found no correlation between CSF and plasma viral load, whereas others did. The lack of a correlation between the two compartments suggests that the presence of HIV-1 RNA is not simply due to the passive passage of the virus from blood to CSF but rather due to intrathecal replication. To evaluate the correlation between plasma and CSF HIV-1 RNA levels and to identify situations in which there is no correlation between the two compartments, seventy patients were prospectively studied. The association between CSF and plasma viral load was evaluated in the total population and in subgroups of patients with similar characteristics. A correlation between the CSF and plasma compartments was observed for patients undergoing highly active antiretroviral therapy (HAART), those with a CD4 T lymphocyte count lower than 200 cells/mm³, and those with increased CSF protein content. On the other hand, no correlation was observed for patients without adequate virological control, who had a CD4 count higher than 200 cells/mm³ and who did not use HAART. The correlation between the two compartments observed in some patients suggests that CSF HIV-1 RNA levels may reflect plasma levels in these subjects. In contrast, the lack of a correlation between the two compartments in patients who were not on HAART and who had normal CSF proteins and a poor virological control possibly indicates compartmentalization of the virus in CSF and, consequently, plasma-independent intrathecal viral replication.

Tuple-based morphisms for interoperability establishment of financial information models

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

Correlation between the mechanical cycling behavior and microstructure in laser welded joints using NiTi memory shape alloys

Dissertação para obtenção do Grau de Mestre em Engenharia de Materiais

ANIMAL MODELS FOR THE STUDY OF LEISHMANIASIS IMMUNOLOGY

Leishmaniasis remains a major public health problem worldwide and is classified as Category I by the TDR/WHO, mainly due to the absence of control. Many experimental models like rodents, dogs and monkeys have been developed, each with specific features, in order to characterize the immune response to Leishmania species, but none reproduces the pathology observed in human disease. Conflicting data may arise in part because different parasite strains or species are being examined, different tissue targets (mice footpad, ear, or base of tail) are being infected, and different numbers (“low” 1×102 and “high” 1×106) of metacyclic promastigotes have been inoculated. Recently, new approaches have been proposed to provide more meaningful data regarding the host response and pathogenesis that parallels human disease. The use of sand fly saliva and low numbers of parasites in experimental infections has led to mimic natural transmission and find new molecules and immune mechanisms which should be considered when designing vaccines and control strategies. Moreover, the use of wild rodents as experimental models has been proposed as a good alternative for studying the host-pathogen relationships and for testing candidate vaccines. To date, using natural reservoirs to study Leishmania infection has been challenging because immunologic reagents for use in wild rodents are lacking. This review discusses the principal immunological findings against Leishmania infection in different animal models highlighting the importance of using experimental conditions similar to natural transmission and reservoir species as experimental models to study the immunopathology of the disease.

Landslide susceptibility assessment in Karanganyar regency - Indonesia - Comparison of knowledge-based and Data-driven Models

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

BEHAVIORAL AND MEMORY CHANGES IN Mus musculus COINFECTED BY Toxocara canis AND Toxoplasma gondii

Several researchers have stated that parasites can alter the behavior of their hosts, in order to increase the transmission rate, principally when prey-predator relationships are a reliable way of infection transmission. The aim of this study was to verify the occurrence of changes in anxiety and short-term memory patterns in experimentally infected Mus musculus by Toxocara canis and/or Toxoplasma gondii. Forty male Mus musculus (Balb/c) eight-week-old were divided into four groups of 10 mice each. One group was infected with 300 eggs of Toxocara canis; a second group was submitted to infection with 10 cysts of Toxoplasma gondii; a third group was concomitantly infected with both parasites with the same inoculums and the last group was maintained without infection. The anxiety levels were evaluated using an elevated plus maze and an actometer; the short-term memory was determined by a two-way active avoidance equipment. The determination of anxiety levels were conducted 40 and 70 days after infection and the short-term memory was evaluated 140 days after infection. Mice chronically infected by Toxoplasma gondii showed impaired learning and short-term memory, but no significant differences were found in mice infected by Toxocara canis or concomitantly infected by Toxocara canis and Toxoplasma gondii when compared to non infected mice.

Inteligência artificial aplicada na previsão de mercados financeiros

Neste documento, são investigados vários métodos usados na inteligência artificial, com o objetivo de obter previsões precisas da evolução dos mercados financeiros. O uso de ferramentas lineares como os modelos AR, MA, ARMA e GARCH têm muitas limitações, pois torna-se muito difícil adaptá-los às não linearidades dos fenómenos que ocorrem nos mercados. Pelas razões anteriormente referidas, os algoritmos como as redes neuronais dinâmicas (TDNN, NARX e ESN), mostram uma maior capacidade de adaptação a estas não linearidades, pois não fazem qualquer pressuposto sobre as distribuições de probabilidade que caracterizam estes mercados. O facto destas redes neuronais serem dinâmicas, faz com que estas exibam um desempenho superior em relação às redes neuronais estáticas, ou outros algoritmos que não possuem qualquer tipo de memória. Apesar das vantagens reveladas pelas redes neuronais, estas são um sistema do tipo black box, o que torna muito difícil extrair informação dos pesos da rede. Isto significa que estes algoritmos devem ser usados com precaução, pois podem tornar-se instáveis.

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica