Susceptible-infected-recovered and susceptible-exposed-infected models

Two stochastic epidemic lattice models, the susceptible-infected-recovered and the susceptible-exposed-infected models, are studied on a Cayley tree of coordination number k. The spreading of the disease in the former is found to occur when the infection probability b is larger than b(c) = k/2(k - 1). In the latter, which is equivalent to a dynamic site percolation model, the spreading occurs when the infection probability p is greater than p(c) = 1/(k - 1). We set up and solve the time evolution equations for both models and determine the final and time-dependent properties, including the epidemic curve. We show that the two models are closely related by revealing that their relevant properties are exactly mapped into each other when p = b/[k - (k - 1) b]. These include the cluster size distribution and the density of individuals of each type, quantities that have been determined in closed forms.

Beta-binomial/Poisson regression models for repeated bivariate counts

We analyze data obtained from a study designed to evaluate training effects on the performance of certain motor activities of Parkinson`s disease patients. Maximum likelihood methods were used to fit beta-binomial/Poisson regression models tailored to evaluate the effects of training on the numbers of attempted and successful specified manual movements in 1 min periods, controlling for disease stage and use of the preferred hand. We extend models previously considered by other authors in univariate settings to account for the repeated measures nature of the data. The results suggest that the expected number of attempts and successes increase with training, except for patients with advanced stages of the disease using the non-preferred hand. Copyright (c) 2008 John Wiley & Sons, Ltd.

Unsupervised learning to cluster the disease stages in parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder (after Alzheimer's disease) and directly affects upto 5 million people worldwide. The stages (Hoehn and Yaar) of disease has been predicted by many methods which will be helpful for the doctors to give the dosage according to it. So these methods were brought up based on the data set which includes about seventy patients at nine clinics in Sweden. The purpose of the work is to analyze unsupervised technique with supervised neural network techniques in order to make sure the collected data sets are reliable to make decisions. The data which is available was preprocessed before calculating the features of it. One of the complex and efficient feature called wavelets has been calculated to present the data set to the network. The dimension of the final feature set has been reduced using principle component analysis. For unsupervised learning k-means gives the closer result around 76% while comparing with supervised techniques. Back propagation and J4 has been used as supervised model to classify the stages of Parkinson's disease where back propagation gives the variance percentage of 76-82%. The results of both these models have been analyzed. This proves that the data which are collected are reliable to predict the disease stages in Parkinson's disease.

Digital spiral analysis for objective assessment of fine motor timing variability in Parkinson's disease

OBJECTIVES: To develop a method for objective assessment of fine motor timing variability in Parkinson’s disease (PD) patients, using digital spiral data gathered by a touch screen device. BACKGROUND: A retrospective analysis was conducted on data from 105 subjects including65 patients with advanced PD (group A), 15 intermediate patients experiencing motor fluctuations (group I), 15 early stage patients (group S), and 10 healthy elderly subjects (HE) were examined. The subjects were asked to perform repeated upper limb motor tasks by tracing a pre-drawn Archimedes spiral as shown on the screen of the device. The spiral tracing test was performed using an ergonomic pen stylus, using dominant hand. The test was repeated three times per test occasion and the subjects were instructed to complete it within 10 seconds. Digital spiral data including stylus position (x-ycoordinates) and timestamps (milliseconds) were collected and used in subsequent analysis. The total number of observations with the test battery were as follows: Swedish group (n=10079), Italian I group (n=822), Italian S group (n = 811), and HE (n=299). METHODS: The raw spiral data were processed with three data processing methods. To quantify motor timing variability during spiral drawing tasks Approximate Entropy (APEN) method was applied on digitized spiral data. APEN is designed to capture the amount of irregularity or complexity in time series. APEN requires determination of two parameters, namely, the window size and similarity measure. In our work and after experimentation, window size was set to 4 and similarity measure to 0.2 (20% of the standard deviation of the time series). The final score obtained by APEN was normalized by total drawing completion time and used in subsequent analysis. The score generated by this method is hence on denoted APEN. In addition, two more methods were applied on digital spiral data and their scores were used in subsequent analysis. The first method was based on Digital Wavelet Transform and Principal Component Analysis and generated a score representing spiral drawing impairment. The score generated by this method is hence on denoted WAV. The second method was based on standard deviation of frequency filtered drawing velocity. The score generated by this method is hence on denoted SDDV. Linear mixed-effects (LME) models were used to evaluate mean differences of the spiral scores of the three methods across the four subject groups. Test-retest reliability of the three scores was assessed after taking mean of the three possible correlations (Spearman’s rank coefficients) between the three test trials. Internal consistency of the methods was assessed by calculating correlations between their scores. RESULTS: When comparing mean spiral scores between the four subject groups, the APEN scores were different between HE subjects and three patient groups (P=0.626 for S group with 9.9% mean value difference, P=0.089 for I group with 30.2%, and P=0.0019 for A group with 44.1%). However, there were no significant differences in mean scores of the other two methods, except for the WAV between the HE and A groups (P<0.001). WAV and SDDV were highly and significantly correlated to each other with a coefficient of 0.69. However, APEN was not correlated to neither WAV nor SDDV with coefficients of 0.11 and 0.12, respectively. Test-retest reliability coefficients of the three scores were as follows: APEN (0.9), WAV(0.83) and SD-DV (0.55). CONCLUSIONS: The results show that the digital spiral analysis-based objective APEN measure is able to significantly differentiate the healthy subjects from patients at advanced level. In contrast to the other two methods (WAV and SDDV) that are designed to quantify dyskinesias (over-medications), this method can be useful for characterizing Off symptoms in PD. The APEN was not correlated to none of the other two methods indicating that it measures a different construct of upper limb motor function in PD patients than WAV and SDDV. The APEN also had a better test-retest reliability indicating that it is more stable and consistent over time than WAV and SDDV.

Experimental models of autoimmune inflammatory ocular diseases

A inflamação ocular é uma das principais causas de perda visual e cegueira. As uveítes constituem um grupo complexo e heterogêneo de doenças caracterizadas por inflamação dos tecidos intraoculares. O olho pode ser o único órgão envolvido ou a uveíte pode ser parte de uma doença sistêmica. A etiologia é desconhecida em um número significativo de casos, que são considerados idiopáticos. Modelos animais têm sido desenvolvidos para estudar a fisiopatogênese da uveíte autoimune devido às dificuldades na obtenção de tecidos de olhos humanos inflamados para experimentos. Na maioria desses modelos, que simulam as uveítes autoimunes em humanos, a uveíte é induzida com proteínas específicas de fotorreceptores (antígeno-S, proteína ligadora de retinoide do interfotoreceptor, rodopsina, recoverina e fosducina). Antígenos não retinianos, como proteínas associadas à melanina e proteína básica de mielina, são também bons indutores de uveíte em animais. Entender os mecanismos básicos e a patogênese dessas doenças oculares é essencial para o desenvolvimento de novas formas de tratamento das uveítes autoimunes e de novos agentes terapêuticos. Nesta revisão serão abordados os principais modelos experimentais utilizados para o estudo de doenças inflamatórias oculares autoimunes.

Effects of two chronic stress models on ligature-induced periodontitis in Wistar rats

Objectives: The present study aims at comparing the effects of physical and variable chronic stress on ligature-induced periodontitis in rats.Design: Forty-eight adult Wistar rats were randomly assigned to four groups (n = 12): physical stress, variable stress, positive control and negative control. The models of physical stress were immobilization and immobilization associated with exposure to cold. The models of variable stress were exposure to intermittent light, 24 h isolation, oral cavity examination, crowded environment, smell of blood and noise. After 10 days of physical or variable stress animals underwent experimental induction of periodontal disease in one oral side. Positive control also underwent experimental induction of periodontal disease on the 10th day. Negative control did not receive any type of intervention. At the end of the experimental period (60 days), all animals were euthanized. After routine laboratory processing, images of the histological sections were digitised and submitted to histometric measurement using two parameters: histologic attachment loss and bone loss.Results: Histological attachment loss and bone loss were greater (p < 0.05) in the physical stress group than in the other groups (variable stress, positive and negative control groups). on the non-periodontitis side, these same histological parameters did not significantly differ amongst groups.Conclusions: Physical stress negatively modulated the response pattern to experimentally induced periodontitis in rats. (C) 2011 Elsevier Ltd. All rights reserved.

Signaling pathways associated with the expression of inflammatory mediators activated during the course of two models of experimental periodontitis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sequential IL-23 and IL-17 and increased Mmp8 and Mmp14 expression characterize the progression of an experimental model of periodontal disease in type 1 diabetes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Molecular models of NS3 protease variants of the Hepatitis C virus

Background: Hepatitis C virus (HCV) currently infects approximately three percent of the world population. In view of the lack of vaccines against HCV, there is an urgent need for an efficient treatment of the disease by an effective antiviral drug. Rational drug design has not been the primary way for discovering major therapeutics. Nevertheless, there are reports of success in the development of inhibitor using a structure-based approach. One of the possible targets for drug development against HCV is the NS3 protease variants. Based on the three-dimensional structure of these variants we expect to identify new NS3 protease inhibitors. In order to speed up the modeling process all NS3 protease variant models were generated in a Beowulf cluster. The potential of the structural bioinformatics for development of new antiviral drugs is discussed.Results: the atomic coordinates of crystallographic structure 1CU1 and 1DY9 were used as starting model for modeling of the NS3 protease variant structures. The NS3 protease variant structures are composed of six subdomains, which occur in sequence along the polypeptide chain. The protease domain exhibits the dual beta-barrel fold that is common among members of the chymotrypsin serine protease family. The helicase domain contains two structurally related beta-alpha-beta subdomains and a third subdomain of seven helices and three short beta strands. The latter domain is usually referred to as the helicase alpha-helical subdomain. The rmsd value of bond lengths and bond angles, the average G-factor and Verify 3D values are presented for NS3 protease variant structures.Conclusions: This project increases the certainty that homology modeling is an useful tool in structural biology and that it can be very valuable in annotating genome sequence information and contributing to structural and functional genomics from virus. The structural models will be used to guide future efforts in the structure-based drug design of a new generation of NS3 protease variants inhibitors. All models in the database are publicly accessible via our interactive website, providing us with large amount of structural models for use in protein-ligand docking analysis.

p53, p16 and Fhit Proteins Expressions in Chronic Esophagitis and Chagas Disease

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Weather-based prediction of anthracnose severity using artificial neural network models

Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides. Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21.9% for the Australian and 22.1% for the South American model. of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development.

Genetic Parameters For the Somatic Cells Count In the Milk of Buffaloes Using Ordinary Test Day Models

The buffaloes dairy milk production (BDMP) has increased in the last 20 years, mainly for the manufacturing of mozzarella cheese, which is recognized by its high nutritional quality. However, this quality can be affected by several factors i. e. high somatic cells count (SCC) provokes changes in the milk's constituents. As in bovine dairy milk, the SCC is used as diagnostic tool for milk quality; because it enables the diagnosis of sub-clinic mastitis and also allows the selection of individuals genetically resistant to that disease. Based on it, we collected information about SCC and BDMP along the lactation in Murrah breed buffaloes, during the period between 1997 and 2005. Curves were designed to estimate genetic parameters. These parameters were estimated by ordinary test-day models. There were observed variations in the estimated heritability for both characteristics the lowest score for somatic cells count (SSCC) was seen at first month (0.01) and the highest at sixth months (0.29 the genetic correlation between these traits varied from -1 at the 1 and 9(th) months to 0.31 and 0.30 in the2 and 4(th) month of lactation. Phenotypic correlations were all negative (-0.07 in the second month and up to -0.35 in the eighth month of lactation). These results showed that environmental factors are more important than genetics in explain SCC, for this reason, selection for genetic resistance to mastitis in buffalos based in SCC should not be done. In the other hand, negative phenotypic correlations demonstrated that as the SCC increased, the milk production decreased.

Experimental Basis and New Insights for Cell Therapy in Chronic Obstructive Pulmonary Disease

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A disease evolution model with uncertain parameters

In this study we consider the SIS epidemiological model (susceptible-infected-susceptible) in which the transmission and recuperation rates are considered fuzzy sets. The concepts of possibility measures and fuzzy expectancy value are used to obtain the basic reproduction value for infected groups with different viral charge.

Effect of induced diabetes mellitus on alveolar bone loss after 30 days of ligature-induced periodontal disease

Several studies have shown that diabetics are more susceptible to the development of severe periodontal disease. Currently, the use of animal models can be considered a feasible alternative in radiographic assessments of these two pathologies. The purpose of this radiographic study was to evaluate the effect of induced diabetes mellitus on alveolar bone loss after 30 days of ligature-induced periodontal disease. Sixty-four Wistar rats were randomly distributed into four experimental groups. Diabetes was induced in Groups II and IV, while periodontal disease was induced in Groups III and IV; Group I was used as control. In order to perform the radiographic assessment of the specimens, the rats were killed on the 3rd and 30th days of the study. Radiographic measurements were assessed with ANOVA and Tukey's test to determine statistically significant differences (p < 0.05). It was observed that Groups III and IV featured greater bone loss when compared to Groups I and II. Only the diabetic group with periodontal disease (Group IV) featured statistically significant greater bone loss when compared to the other groups. These results suggested that the alveolar bone loss resulting from the periodontal disease installation is greater when associated to the diabetes mellitus.