Association of social determinants with the severity of congenital heart disease.

BACKGROUND: Congenital heart diseases are the most prevalent congenital malformations and cause greater morbi-mortality in newborns and infants. The aim of this study was to analyze the social determinants in families with children with the severity of congenital heart disease. METHODS: Analytical cross-sectional study in 140 families of children with congenital heart disease to whom a structured survey was applied addressing topics related to family structure, health, economic conditions, exposure factors, and other social conditions relevant to the study, during 1 year. RESULTS: In all, 53.7% of the studied population belonged to low socioeconomic levels. No association was found between the severity of the heart disease and the presence of pathological antecedents in the parents. The families resided in urban areas. Also, 28.3% of the mothers had four or fewer prenatal controls during pregnancy. Only 22% of heart diseases were diagnosed during pregnancy. It was found that exposure to cigarette and wood smoke during pregnancy, in addition to low socioeconomic status, was associated with greater severity of heart disease (RACHS-1 and STS-Score), when evaluated by pathophysiological groups (cyanotic/non-cyanotic/single ventricle). CONCLUSIONS: Exposure to cigarette smoke, wood smoke during pregnancy, and low socioeconomic status turned out to be social determinants associated with the severity of heart disease analyzed by pathophysiological groups. IMPACT: The social component has not been well characterized as a cause of congenital heart disease, especially in countries like ours, where the existence of gaps and social inequities have a high impact. The findings of this study could have an impact on public health to the extent that policies are implemented to reduce exposure to cigarettes, especially during pregnancy. Knowledge of these changes and their measurement in this type of pathology could open the door to the creation of policies aimed at their prevention, focusing on the local risk factors found, which can impact the disease.

Stokes Dynamic Polarimeter for Non-Organic and Organic Samples Characterization.

The light polarization properties provide relevant information about linear-optical media quality and condition. The Stokes-Mueller formalism is commonly used to represent the polarization properties of the incident light over sample tests. Currently, different Stokes Polarimeters are mainly defined by resolution, acquisition rate, and light to carry out accurate and fast measurements. This work presents the implementation of an automatic Stokes dynamic polarimeter to characterize non-biological and biological material samples. The proposed system is configured to work in the He-Ne laser beam's reflection or transmission mode to calculate the Mueller matrix. The instrumentation stage includes two asynchronous photoelastic modulators, two nano-stepper motors, and an acquisition data card at 2% of accuracy. The Mueller matrix is numerically calculated by software using the 36 measures method without requiring image processing. Experiments show the efficiency of the proposed optical array to calculate the Mueller matrix in reflection and transmission mode for different samples. The mean squared error is calculated for each element of the obtained matrix using referenced values of the air and a mirror. A comparison with similar works in the literature validates the proposed optical array.

Geometric Analysis of Signals for Inference of Multiple Faults in Induction Motors.

Multiple fault identification in induction motors is essential in industrial processes due to the high costs that unexpected failures can cause. In real cases, the motor could present multiple faults, influencing systems that classify isolated failures. This paper presents a novel methodology for detecting multiple motor faults based on quaternion signal analysis (QSA). This method couples the measured signals from the motor current and the triaxial accelerometer mounted on the induction motor chassis to the quaternion coefficients. The QSA calculates the quaternion rotation and applies statistics such as mean, variance, kurtosis, skewness, standard deviation, root mean square, and shape factor to obtain their features. After that, four classification algorithms are applied to predict motor states. The results of the QSA method are validated for ten classes: four single classes (healthy condition, unbalanced pulley, bearing fault, and half-broken bar) and six combined classes. The proposed method achieves high accuracy and performance compared to similar works in the state of the art.

Contrast and Homogeneity Feature Analysis for Classifying Tremor Levels in Parkinson's Disease Patients.

Early detection of different levels of tremors helps to obtain a more accurate diagnosis of Parkinson's disease and to increase the therapy options for a better quality of life for patients. This work proposes a non-invasive strategy to measure the severity of tremors with the aim of diagnosing one of the first three levels of Parkinson's disease by the Unified Parkinson's Disease Rating Scale (UPDRS). A tremor being an involuntary motion that mainly appears in the hands; the dataset is acquired using a leap motion controller that measures 3D coordinates of each finger and the palmar region. Texture features are computed using sum and difference of histograms (SDH) to characterize the dataset, varying the window size; however, only the most fundamental elements are used in the classification stage. A machine learning classifier provides the final classification results of the tremor level. The effectiveness of our approach is obtained by a set of performance metrics, which are also used to show a comparison between different proposed designs.

Fast and accurate electromagnetic solutions of finite periodic optical structures.

Electromagnetic applications of periodic materials have become popular in many modern optical and RF applications. The accurate computation of the electromagnetic response of large structures requires solving problems with high number of unknowns. Fast methods are useful to deal with such big problems, but, in general they do not take advantage of the periodicity properties. Based on the behaviour of impedance matrices involved in the solution of the surface integral equations with the Method of Moments, an accelerated solution based on the FFT is implemented. The presented approach slots the original impedance matrix and it applies the FFT to calculate the exact solution of the matrix vector product in an iterative process. The proposed solution achieves a linear memory cost proportional to 𝒪(N) and a computing time of 𝒪(N log N), where N is the problem number of unknowns. Also, in this paper, the advantages of this technique are shown in the developed applications.

Quaternion-Based Signal Analysis for Motor Imagery Classification from Electroencephalographic Signals.

Quaternions can be used as an alternative to model the fundamental patterns of electroencephalographic (EEG) signals in the time domain. Thus, this article presents a new quaternion-based technique known as quaternion-based signal analysis (QSA) to represent EEG signals obtained using a brain-computer interface (BCI) device to detect and interpret cognitive activity. This quaternion-based signal analysis technique can extract features to represent brain activity related to motor imagery accurately in various mental states. Experimental tests in which users where shown visual graphical cues related to left and right movements were used to collect BCI-recorded signals. These signals were then classified using decision trees (DT), support vector machine (SVM) and k-nearest neighbor (KNN) techniques. The quantitative analysis of the classifiers demonstrates that this technique can be used as an alternative in the EEG-signal modeling phase to identify mental states.

An architecture for measuring joint angles using a long period fiber grating-based sensor.

The implementation of signal filters in a real-time form requires a tradeoff between computation resources and the system performance. Therefore, taking advantage of low lag response and the reduced consumption of resources, in this article, the Recursive Least Square (RLS) algorithm is used to filter a signal acquired from a fiber-optics-based sensor. In particular, a Long-Period Fiber Grating (LPFG) sensor is used to measure the bending movement of a finger. After that, the Gaussian Mixture Model (GMM) technique allows us to classify the corresponding finger position along the motion range. For these measures to help in the development of an autonomous robotic hand, the proposed technique can be straightforwardly implemented on real time platforms such as Field Programmable Gate Array (FPGA) or Digital Signal Processors (DSP). Different angle measurements of the finger's motion are carried out by the prototype and a detailed analysis of the system performance is presented.

Diagnostic Strategies for Breast Cancer Detection: From Image Generation to Classification Strategies Using Artificial Intelligence Algorithms.

Breast cancer is one the main death causes for women worldwide, as 16% of the diagnosed malignant lesions worldwide are its consequence. In this sense, it is of paramount importance to diagnose these lesions in the earliest stage possible, in order to have the highest chances of survival. While there are several works that present selected topics in this area, none of them present a complete panorama, that is, from the image generation to its interpretation. This work presents a comprehensive state-of-the-art review of the image generation and processing techniques to detect Breast Cancer, where potential candidates for the image generation and processing are presented and discussed. Novel methodologies should consider the adroit integration of artificial intelligence-concepts and the categorical data to generate modern alternatives that can have the accuracy, precision and reliability expected to mitigate the misclassifications.

Ranking the ecological effects of coastal armoring on mobile macroinvertebrates across intertidal zones on sandy beaches.

Coastal armoring is widely applied to coastal ecosystems, such as sandy beaches, in response to shoreline erosion and threats to infrastructure. Use of armoring is expected to increase due to coastal population growth and effects of climate change. An increased understanding of armoring effects on those ecosystems and the services they provide is needed for impact assessments and the design of these structures. We investigated the following hypotheses: 1) impacts of coastal armoring on beach macroinvertebrates increase from lower to upper intertidal zones and 2) location of an armoring structure on beach profiles affects the number of intertidal zones, using comparative surveys of armored and unarmored beach sections in Chile and California. The effects of armoring were greater for upper intertidal (talitrid amphipods) and mid-intertidal species (cirolanid isopods) than for lower shore fauna (hippid crabs). Our surveys of sections of armoring structures located higher and lower on the beach profile (with and without interactions with waves and tides), showed loss of upper zone talitrid amphipods and mid-zone isopods and a reduction of lower zone hippid crabs in sections where the structures were lower on the beach profile and interacted with waves, compared to non-interacting sections. Our results support the hypothesis that impacts of armoring on intertidal macroinvertebrates increase from the lower to the upper intertidal zones of sandy beaches and also suggest that the relative position of an armoring structure on the beach profile, determines the number of intertidal zones it affects. Our findings also imply that by altering the position of existing armoring structures on the shore profile and increasing the amount of interaction with waves and tides, sea level rise and regional factors, such as coseismic coastal subsidence, can be expected to exacerbate the impacts of these widely used coastal defense structures on sandy beach ecosystems.

Artificial Intelligence to Analyze the Cortical Thickness Through Age.

In this study, Artificial Intelligence was used to analyze a dataset containing the cortical thickness from 1,100 healthy individuals. This dataset had the cortical thickness from 31 regions in the left hemisphere of the brain as well as from 31 regions in the right hemisphere. Then, 62 artificial neural networks were trained and validated to estimate the number of neurons in the hidden layer. These neural networks were used to create a model for the cortical thickness through age for each region in the brain. Using the artificial neural networks and kernels with seven points, numerical differentiation was used to compute the derivative of the cortical thickness with respect to age. The derivative was computed to estimate the cortical thickness speed. Finally, color bands were created for each region in the brain to identify a positive derivative, that is, a part of life with an increase in cortical thickness. Likewise, the color bands were used to identify a negative derivative, that is, a lifetime period with a cortical thickness reduction. Regions of the brain with similar derivatives were organized and displayed in clusters. Computer simulations showed that some regions exhibit abrupt changes in cortical thickness at specific periods of life. The simulations also illustrated that some regions in the left hemisphere do not follow the pattern of the same region in the right hemisphere. Finally, it was concluded that each region in the brain must be dynamically modeled. One advantage of using artificial neural networks is that they can learn and model non-linear and complex relationships. Also, artificial neural networks are immune to noise in the samples and can handle unseen data. That is, the models based on artificial neural networks can predict the behavior of samples that were not used for training. Furthermore, several studies have shown that artificial neural networks are capable of deriving information from imprecise data. Because of these advantages, the results obtained in this study by the artificial neural networks provide valuable information to analyze and model the cortical thickness.

Resilience of an aquatic macrophyte to an anthropogenically induced environmental stressor in a Ramsar wetland of southern Chile.

In mid-2004, anthropogenically induced changes in water quality of the Río Cruces wetland, a Ramsar site located in southern Chile (ca. 40°S), enhanced the resuspension of iron-enriched sediments, which were subsequently deposited over the most abundant aquatic macrophyte of the wetland (Egeria densa Planch. 1849). This event triggered the formation of brownish, necrotic patches and increased iron contents in the leaves and stems of E. densa, which contributed to a significant demise of the plant within the wetland. In this study, we estimate the recovery time as a proxy for resilience of this macrophyte at organismal and population levels. Macro- and micro-optical characteristics, as well as iron contents in tissues of E. densa, were documented in four time windows (2004, 2008, 2012, and 2014). In addition, the size of the macrophyte population and its spatial occurrence were monitored from 2008 to 2016 across 36 study sites within the wetland. Our results suggest necrotic patches and high iron contents in E. densa persisted at least until 2008. After 2013, a significant increase in the spatial occurrence of E. densa was observed within the wetland, reaching full recovery of the population during 2015. The health of plant tissues and iron contents in leaves and stems showed recovery period close to 4 years, while the recovery of the spatial occurrence of E. densa took approximately 9 years. While the monitoring of plant health was not performed on a strict annual basis, the recovery rates estimated here are slower than those described for other macrophytes. This finding might reflect the long-lasting effects of the disturbance from 2004 and the interaction with biotic processes, such as foraging by waterbirds recolonizing the Río Cruces wetland. These results show that full recovery of E. densa was achieved through a cascade of effects starting with abiotic factors (water quality) and passing through physiological and individual levels, to finally reach the population level. A key aspect of this response is the invasive nature of the macrophyte, which likely contributed to its recovery as a consequence of improved water quality. Less successful macrophyte species in other systems may not reach the specific population recovery, and become subdominant species instead, or even be eradicated from the wetland either as the result of herbivory or due to competition with other macrophytes.

Recovery of black-necked swans, macrophytes and water quality in a Ramsar wetland of southern Chile: Assessing resilience following sudden anthropogenic disturbances.

In 2004 migration and mortality for unknown reasons of the herbivorous Black necked swan (Cygnus melancorhyphus (Molina, 1782)) occurred within the Río Cruces wetland (southern Chile), a Ramsar Site and nature sanctuary. Before 2004, this wetland hosted the largest breeding population of this water bird in the Neotropic Realm. The concurrent decrease in the spatial occurrence of the aquatic plant Egeria densa Planch. 1849 - the main food source of swans - was proposed as a cause for swan migration and mortality. Additionally, post-mortem analyses carried out on swans during 2004 showed diminished body weight, high iron loads and histopathological abnormalities in their livers, suggesting iron storage disease. Various hypotheses were postulated to describe those changes; the most plausible related to variations in water quality after a pulp mill located upstream the wetland started to operate in February 2004. Those changes cascaded throughout the stands of E. densa whose remnants had high iron contents in their tissues. Here we present results of a long-term monitoring program of the wetland components, which show that swan population abundance, body weights and histological liver conditions recovered to pre-disturbance levels in 2012. The recovery of E. densa and iron content in plants throughout the wetland, also returned to pre-disturbance levels in the same 8-year time period. These results show the temporal scale over which resilience and natural restoring processes occur in wetland ecosystems of temperate regions such as southern Chile.

Analysis of the Cluster Prominence Feature for Detecting Calcifications in Mammograms.

In mammograms, a calcification is represented as small but brilliant white region of the digital image. Earlier detection of malignant calcifications in patients provides high expectation of surviving to this disease. Nevertheless, white regions are difficult to see by visual inspection because a mammogram is a gray-scale image of the breast. To help radiologists in detecting abnormal calcification, computer-inspection methods of mammograms have been proposed; however, it remains an open important issue. In this context, we propose a strategy for detecting calcifications in mammograms based on the analysis of the cluster prominence (cp) feature histogram. The highest frequencies of the cp histogram describe the calcifications on the mammography. Therefore, we obtain a function that models the behaviour of the cp histogram using the Vandermonde interpolation twice. The first interpolation yields a global representation, and the second models the highest frequencies of the histogram. A weak classifier is used for obtaining a final classification of the mammography, that is, with or without calcifications. Experimental results are compared with real DICOM images and their corresponding diagnosis provided by expert radiologists, showing that the cp feature is highly discriminative.

Calibrating coseismic coastal land-level changes during the 2014 Iquique (Mw=8.2) earthquake (northern Chile) with leveling, GPS and intertidal biota.

The April 1st 2014 Iquique earthquake (MW 8.1) occurred along the northern Chile margin where the Nazca plate is subducted below the South American continent. The last great megathrust earthquake here, in 1877 of Mw ~8.8 opened a seismic gap, which was only partly closed by the 2014 earthquake. Prior to the earthquake in 2013, and shortly after it we compared data from leveled benchmarks, deployed campaign GPS instruments, continuous GPS stations and estimated sea levels using the upper vertical level of rocky shore benthic organisms including algae, barnacles, and mussels. Land-level changes estimated from mean elevations of benchmarks indicate subsidence along a ~100-km stretch of coast, ranging from 3 to 9 cm at Corazones (18°30'S) to between 30 and 50 cm at Pisagua (19°30'S). About 15 cm of uplift was measured along the southern part of the rupture at Chanabaya (20°50'S). Land-level changes obtained from benchmarks and campaign GPS were similar at most sites (mean difference 3.7±3.2 cm). Higher differences however, were found between benchmarks and continuous GPS (mean difference 8.5±3.6 cm), possibly because sites were not collocated and separated by several kilometers. Subsidence estimated from the upper limits of intertidal fauna at Pisagua ranged between 40 to 60 cm, in general agreement with benchmarks and GPS. At Chanavaya, the magnitude and sense of displacement of the upper marine limit was variable across species, possibly due to species-dependent differences in ecology. Among the studied species, measurements on lithothamnioid calcareous algae most closely matched those made with benchmarks and GPS. When properly calibrated, rocky shore benthic species may be used to accurately measure land-level changes along coasts affected by subduction earthquakes. Our calibration of those methods will improve their accuracy when applied to coasts lacking pre-earthquake data and in estimating deformation during pre-instrumental earthquakes.

Automatic selection of localized region-based active contour models using image content analysis applied to brain tumor segmentation.

Brain tumor segmentation is a routine process in a clinical setting and provides useful information for diagnosis and treatment planning. Manual segmentation, performed by physicians or radiologists, is a time-consuming task due to the large quantity of medical data generated presently. Hence, automatic segmentation methods are needed, and several approaches have been introduced in recent years including the Localized Region-based Active Contour Model (LRACM). There are many popular LRACM, but each of them presents strong and weak points. In this paper, the automatic selection of LRACM based on image content and its application on brain tumor segmentation is presented. Thereby, a framework to select one of three LRACM, i.e., Local Gaussian Distribution Fitting (LGDF), localized Chan-Vese (C-V) and Localized Active Contour Model with Background Intensity Compensation (LACM-BIC), is proposed. Twelve visual features are extracted to properly select the method that may process a given input image. The system is based on a supervised approach. Applied specifically to Magnetic Resonance Imaging (MRI) images, the experiments showed that the proposed system is able to correctly select the suitable LRACM to handle a specific image. Consequently, the selection framework achieves better accuracy performance than the three LRACM separately.

Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method.

We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications.

[Clinical practice guideline. Drug prescription in elderly]. / Guía de práctica clínica. Prescripción farmacológica en el adulto mayor.

The process of prescribing a medication is complex and includes: deciding whether it is indicated, choosing the best option, determining the dose and the appropriate management scheme to the physiological condition of the patient, and monitoring effectiveness and toxicity. We have to inform patients about the expected side effects and indications for requesting a consultation. Specific clinical questions were designed based on the acronym PICOST. The search was made in the specific websites of clinical practice guidelines, was limited to the population of older adults, in English or Spanish. We used 10 related clinical practice guidelines, eight systematic reviews and five meta-analyses. Finally, we made a search of original articles or clinical reviews for specific topics. The development and validation of clinical practice guidelines for "rational drug prescriptions in the elderly" is intended to promote an improvement in the quality of prescription through the prevention and detection of inappropriate prescribing in the elderly and, as a result of this, a decrease in the adverse events by drugs, deterioration of health of patients and expenditure of resources.

El proceso de prescribir un medicamento incluye decidir si está indicado, elegir el mejor, determinar una dosis y un esquema de administración adecuados a la condición fisiológica del paciente, el seguimiento de la eficacia y toxicidad. Debe informarse a los pacientes sobre los efectos secundarios esperados y las indicaciones para solicitar la consulta. Para la elaboración de esta guía se formularon preguntas clínicas específicas, con base en el acrónimo PICOST. La búsqueda se realizó en los sitios web específicos de guías de práctica clínica, en inglés o español, y se limitó a la población de adultos mayores. Se usaron 10 guías de práctica clínica relacionadas, ocho revisiones sistemáticas y cinco metaanálisis. Por último, se realizó una búsqueda de artículos originales o revisiones clínicas para aspectos específicos. La elaboración y validación de una guía de práctica clínica para "prescripción farmacológica razonada en el adulto mayor" tiene el propósito de promover una mejora en la calidad de la prescripción médica, mediante la prevención y detección de la prescripción inapropiada en el anciano y como resultado de esto disminuir los eventos adversos originados por fármacos, el deterioro de la salud de los pacientes y el gasto no justificado de los recursos.

Ecological implications of extreme events: footprints of the 2010 earthquake along the Chilean coast.

Deciphering ecological effects of major catastrophic events such as earthquakes, tsunamis, volcanic eruptions, storms and fires, requires rapid interdisciplinary efforts often hampered by a lack of pre-event data. Using results of intertidal surveys conducted shortly before and immediately after Chile's 2010 M(w) 8.8 earthquake along the entire rupture zone (ca. 34-38°S), we provide the first quantification of earthquake and tsunami effects on sandy beach ecosystems. Our study incorporated anthropogenic coastal development as a key design factor. Ecological responses of beach ecosystems were strongly affected by the magnitude of land-level change. Subsidence along the northern rupture segment combined with tsunami-associated disturbance and drowned beaches. In contrast, along the co-seismically uplifted southern rupture, beaches widened and flattened increasing habitat availability. Post-event changes in abundance and distribution of mobile intertidal invertebrates were not uniform, varying with land-level change, tsunami height and coastal development. On beaches where subsidence occurred, intertidal zones and their associated species disappeared. On some beaches, uplift of rocky sub-tidal substrate eliminated low intertidal sand beach habitat for ecologically important species. On others, unexpected interactions of uplift with man-made coastal armouring included restoration of upper and mid-intertidal habitat seaward of armouring followed by rapid colonization of mobile crustaceans typical of these zones formerly excluded by constraints imposed by the armouring structures. Responses of coastal ecosystems to major earthquakes appear to vary strongly with land-level change, the mobility of the biota and shore type. Our results show that interactions of extreme events with human-altered shorelines can produce surprising ecological outcomes, and suggest these complex responses to landscape alteration can leave lasting footprints in coastal ecosystems.

Histoplasmosis aguda diseminada en un niño inmunocompetente / Acute disseminated histoplasmosis in an immunocompetent child

La histoplasmosis es una patología endémica en Colombia. La verdadera incidencia en nuestro país es desconocida. En niños inmunocompetentes generalmente es un proceso autolimitado. Algunos casos pueden resultar un dilema diagnóstico por su amplio espectro de manifestaciones clínicas y diagnósticos diferenciales o por las dificultades de su confirmación sobre todo en zonas endémicas. Describimos el caso de un niño inmunocompetente con histoplasmosis diseminada aguda e importante compromiso respiratorio resaltando los dilemas que podrían presentarse en su diagnóstico y manejo.

Histoplasmosis is an endemic pathology in Colombia but its real incidence in the country is unknown. In non-immunocompromised children, the mycosis is mainly a self-limited process. In endemic zones certain cases may represent a diagnostic dilemma due to the broad spectrum of clinical manifestations that complicate differential diagnosis and hinder the proper diagnosis. We describe the case of an immunocompetent child diagnosed with acute disseminated histoplasmosis who exhibited extensive respiratory involvement highlighting the dilemmas faced when attempting to establish the diagnosis and defining management.