Clinical variables associated with leprosy reactions and persistence of physical impairment

Introduction Leprosy is a chronic disease that affects skin and peripheral nerves. Disease complications include reactional episodes and physical impairment. One World Health Organization (WHO) goal of leprosy programs is to decrease the number of grade 2 impairment diagnoses by 2015. This study aims to evaluate clinical factors associated with the occurrence of leprosy reactions and physical impairment in leprosy patients. Methods We conducted a retrospective study of data from medical records of patients followed in two important centers for the treatment of leprosy in Aracaju, Sergipe, Brazil, from 2005 to 2011. We used the chi-square test to analyze associations between the following categorical variables: gender, age, operational classification, clinical forms, leprosy reactions, corticosteroid treatment, and physical impairment at the diagnosis and after cure. Clinical variables associated with multibacillary leprosy and/or reactional episodes and the presence of any grade of physical impairment after cure were evaluated using the logistic regression model. Results We found that men were more affected by multibacillary forms, reactional episodes, and grade 2 physical impairment at diagnosis. Leprosy reactions were detected in a total of 40% of patients and all were treated with corticosteroids. However, physical impairment was observed in 29.8% of the patients analyzed at the end of the treatment and our multivariate analysis associated a low dose and short period of corticosteroid treatment with persistence of physical impairments. Conclusions Physical impairment should receive an increased attention before and after treatment, and adequate treatment should be emphasized.

Skin lesions simulating blue toe syndrome caused by prolonged contact with a millipede

Venomous animals are those that, by means of a hunting and defense mechanism, are able to inject their prey with a toxic substance produced in their bodies, directly from specialized glands (e.g., tooth, sting, spur) through which the poison passes. Millipedes are poisonous animals; they can be harmful to humans, and their effects usually manifest as erythematous, purpuric, and cyanotic lesions; local pain; and paresthesia. Here, we report a case of skin contact with a millipede for 6h resulting in skin lesions similar to blue toe syndrome.

Using the International Classification of Functioning, Disability and Health as a tool for analysis of the effect of physical therapy on spasticity in HAM/TSP patients

INTRODUCTION: This study aimed to evaluate spasticity in human T-lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) patients before and after physical therapy using the International Classification of Functioning, Disability and Health (ICF). METHODS: Nine subjects underwent physical therapy. Spasticity was evaluated using the Modified Ashworth Scale. The obtained scores were converted into ICF body functions scores. RESULTS: The majority of subjects had a high degree of spasticity in the quadriceps muscles. According to the ICF codes, the spasticity decreased after 20 sessions of physical therapy. CONCLUSIONS: The ICF was effective in evaluating spasticity in HAM/TSP patients.

Evaluation of the reference value for the Montenegro skin test

Abstract:INTRODUCTION:The Montenegro skin test (MST) has good clinical applicability and low cost for the diagnosis of American tegumentary leishmaniasis (ATL). However, no studies have validated the reference value (5mm) typically used to discriminate positive and negative results. We investigated MST results and evaluated its performance using different cut-off points.METHODS:The results of laboratory tests for 4,256 patients with suspected ATL were analyzed, and 1,182 individuals were found to fulfill the established criteria. Two groups were formed. The positive cutaneous leishmaniasis (PCL) group included patients with skin lesions and positive direct search for parasites (DS) results. The negative cutaneous leishmaniasis (NCL) group included patients with skin lesions with evolution up to 2 months, negative DS results, and negative indirect immunofluorescence assay results who were residents of urban areas that were reported to be probable sites of infection at domiciles and peridomiciles.RESULTS:The PCL and NCL groups included 769 and 413 individuals, respectively. The mean ± standard deviation MST in the PCL group was 12.62 ± 5.91mm [95% confidence interval (CI): 12.20-13.04], and that in the NCL group was 1.43 ± 2.17mm (95% CI: 1.23-1.63). Receiver-operating characteristic curve analysis indicated 97.4% sensitivity and 93.9% specificity for a cut-off of 5mm and 95.8% sensitivity and 97.1% specificity for a cut-off of 6mm.CONCLUSIONS:Either 5mm or 6mm could be used as the cut-off value for diagnosing ATL, as both values had high sensitivity and specificity.

Expression of annexin A1 in Leishmania-infected skin and its correlation with histopathological features

ABSTRACTINTRODUCTION:The aim of this study was quantify annexin A1 expression in macrophages and cluster of differentiation 4 (CD4) + and cluster of differentiation 8 (CD8)+ T cells from the skin of patients with cutaneous leishmaniasis (n=55) and correlate with histopathological aspects.METHODS:Infecting species were identified by polymerase chain reaction-restriction fragment length polymorphism, and expression of annexin A1 was analyzed by immunofluorescence.RESULTS:All patients (n = 55) were infected with Leishmania braziliensis . Annexin A1 was expressed more abundantly in CD163 + macrophages in infected skin (p < 0.0001) than in uninfected skin. In addition, macrophages in necrotic exudative reaction lesions expressed annexin A1 at higher levels than those observed in granulomatous (p < 0.01) and cellular lesions p < 0.05). This difference might be due to the need to clear both parasites and necrotic tissue from necrotic lesions. CD4 + cells in cellular lesions expressed annexin A1 more abundantly than did those in necrotic (p < 0.05) and granulomatous lesions (p < 0.01). Expression in CD8 + T cells followed the same trend. These differences might be due to the pervasiveness of lymphohistiocytic and plasmacytic infiltrate in cellular lesions.CONCLUSIONS:Annexin A1 is differentially expressed in CD163 + macrophages and T cells depending on the histopathological features of Leishmania -infected skin, which might affect cell activation.

Evaluation of the World Health Organization 2009 classification of dengue severity in autopsied individuals, during the epidemics of 2011 and 2012 in Brazil

Abstract: INTRODUCTION: The dengue classification proposed by the World Health Organization (WHO) in 2009 is considered more sensitive than the classification proposed by the WHO in 1997. However, no study has assessed the ability of the WHO 2009 classification to identify dengue deaths among autopsied individuals suspected of having dengue. In the present study, we evaluated the ability of the WHO 2009 classification to identify dengue deaths among autopsied individuals suspected of having dengue in Northeast Brazil, where the disease is endemic. METHODS: This retrospective study included 121 autopsied individuals suspected of having dengue in Northeast Brazil during the epidemics of 2011 and 2012. All the autopsied individuals included in this study were confirmed to have dengue based on the findings of laboratory examinations. RESULTS: The median age of the autopsied individuals was 34 years (range, 1 month to 93 years), and 54.5% of the individuals were males. According to the WHO 1997 classification, 9.1% (11/121) of the cases were classified as dengue hemorrhagic fever (DHF) and 3.3% (4/121) as dengue shock syndrome. The remaining 87.6% (106/121) of the cases were classified as dengue with complications. According to the 2009 classification, 100% (121/121) of the cases were classified as severe dengue. The absence of plasma leakage (58.5%) and platelet counts <100,000/mm3 (47.2%) were the most frequent reasons for the inability to classify cases as DHF. CONCLUSIONS: The WHO 2009 classification is more sensitive than the WHO 1997 classification for identifying dengue deaths among autopsied individuals suspected of having dengue.

Analysis of classification algorithms for crop detection using LANDSAT 8 images

Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.

Factors associated with seropositivity for APGL-Iamong household contacts of leprosy patients

Abstract: INTRODUCTION: Leprosy is mainly transmitted among family members who share genetic and ambient factors. The clinical form of leprosy in the index case and kinship could be risk factors for leprosy transmission. High antibody levels in household contacts (HC) in the absence of neural or skin lesions may characterize latent infection. This study aimed to evaluate the association between seropositivity for anti-phenolic glycolipid-I immunoglobulin M antibodies (APGL-I) in HC and the clinical classification of the index case and to analyze the association between APGL-I positivity with other factors such as age, kinship, and gender. METHODS: We performed a survey among 320 HC of 120 leprosy patients who were evaluated and followed-up in a leprosy outpatient clinic of a university hospital. All HC underwent complete skin examination, peripheral nerve palpation, skin sensory tests, and serologic tests for the detection and quantification of APGL-I. RESULTS: The overall seropositivity rate was 20%, and was greatly affected by kinship. APGL-I seropositivity was higher in siblings (41%), followed by parents (28%), spouses (26%), other (19%), and offspring (14%). Independent risk factors for seropositivity were being siblings (OR 3.3) and being a HC of an index case with indeterminate leprosy (OR 5.3). APGL-I seropositivity was associated with index cases with a bacillary index of 4 (88%; p<.001). Seropositivity among HC was not significantly associated with their gender and age. There was no statistical difference in the seropositivity rates of HC of index patients with paucibacillary and multibacillary leprosy. CONCLUSIONS: Strict evaluation and follow-up of HC with positive results for APGL-I is recommended. Special attention should be paid during the screening of siblings of the index cases, HC of patients with a high bacillary index, and HC of patients with indeterminate leprosy.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Skin-derived cell-sheets as powerful tools to engineer skin analogues

Cell/cell-extracellular matrix (ECM) dynamic interactions appear to have a major role in regulating communication through soluble signaling, directing cell binding and activating substrates that participate in the highly organized wound healing process. Moreover, these interactions are also crucial for in vitro mimicking cutaneous physiology. Herein we explore cell sheet (CS) engineering to create cellular constructs formed by keratinocytes (hKC), fibroblasts (hDFB) and dermal microvascular endothelial cells (hDMEC), to target skin wound healing but also the in vitro recreation of relevant models. Taking advantage of temperature-responsive culture surfaces, which allow harvesting cultured cells as intact sheets along with the deposited native ECM, varied combinations of homotypic and heterotypic three-dimensional (3-D) CS-based constructs were developed. Constructs combining one CS of keratinocytes as an epidermis-like layer plus a vascularized dermis composed by hDFB and hDMECs were assembled as skin analogues for advancing in vitro testing. Simultaneously both hKC and hDMEC were shown to significantly contribute to the re-epithelialization of full-thickness mice skin wounds by promoting an early epithelial coverage, while hDMEC significantly lead to increased vessels density, incorporating the neovasculature. Thus, although determined by the cellular nature of the constructs, these outcomes demonstrated that CS engineering appear as an unique technology that open the possibility to create numerous combinations of 3D constructs to target defective wound healing as well as the construction of in vitro models to further mimic cutaneous functions crucial for drug screening and cosmetic testing assays.

Safety classification using GIS in decision-making process to define priority road interventions

Given the current economic situation of the Portuguese municipalities, it is necessary to identify the priority investments in order to achieve a more efficient financial management. The classification of the road network of the municipality according to the occurrence of traffic accidents is fundamental to set priorities for road interventions. This paper presents a model for road network classification based on traffic accidents integrated in a geographic information system. Its practical application was developed through a case study in the municipality of Barcelos. An equation was defined to obtain a road safety index through the combination of the following indicators: severity, property damage only and accident costs. In addition to the road network classification, the application of the model allows to analyze the spatial coverage of accidents in order to determine the centrality and dispersion of the locations with the highest incidence of road accidents. This analysis can be further refined according to the nature of the accidents namely in collision, runoff and pedestrian crashes.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Supercritical fluid and pharmaceutical applications. Part I: Process classification

The supercritical fluid technology has been target of many pharmaceuticals investigations in particles production for almost 35 years. This is due to the great advantages it offers over others technologies currently used for the same purpose. A brief history is presented, as well the classification of supercritical technology based on the role that the supercritical fluid (carbon dioxide) performs in the process.