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1.
Dement. neuropsychol ; 15(3): 366-372, Sept. 2021. tab
Article in English | LILACS | ID: biblio-1339788

ABSTRACT

ABSTRACT The ability to perform instrumental activities of daily living (IADLs) is an important marker within the aging process, as it reflects the level of independence to perform in the real world. However, there is a scarcity of studies that investigate the different performance profiles among older adults. Objective: To investigate the heterogeneity present in the community of elderly people, grouping them based on characteristics and patterns observed through an objective performance-based assessment. Methods: Participants were selected according to the following inclusion criteria: fluency in Portuguese, 360 years, regular participation in a social program offered by the government of Rio de Janeiro, and absence of a caregiver. The evaluation of IADLs was determined by the total and brief version of the University of California, San Diego Performance-Based Skills Assessment (UPSA) and the Lawton and Brody IADL scale. The Brief Cognitive Screening Battery and the Mini-Mental State Examination were used to characterize the sample, in addition to the Geriatric Depression Scale. A total of 61 elderly people with an average age of 72.5 years, predominantly females (85.2%), and average education of 11.2 were evaluated and grouped according to their performance at UPSA through clustering analysis. Results: The analysis revealed three grouping patterns, subdividing the sample into subgroups that differed significantly in terms of age, education, global cognition, and all instrumental activities assessed by UPSA — planning, finance, communication, transportation, and household chores. Conclusions: This study was able to identify the heterogeneity present between the elderly people in the different factors that compose the IADLs through a performance-based assessment.


RESUMO A capacidade para realização das atividades instrumentais da vida diária (AIVDs) é um importante marcador no envelhecimento, uma vez que reflete o grau de independência para atuação no mundo real. No entanto, há uma escassez de estudos que se proponham a investigar os diferentes perfis de desempenho entre idosos. Objetivo: Investigar a heterogeneidade presente em idosos da comunidade, agrupando-os a partir de características e padrões observados através de uma avaliação objetiva baseada em desempenho. Métodos: Participantes foram selecionados conforme critérios de inclusão: ter fluência no Português; ter 60 ou mais anos; participar de forma regular no programa de casas de convivência do Rio de Janeiro e não possuir cuidador. A avaliação das AIVDs foi determinada pela versão total e breve do The University of California, San Diego Performance-Based Skills Assessment (UPSA) e pela escala AIVD de Lawton e Brody. A Bateria Breve de Rastreio Cognitivo e o Miniexame do Estado Mental foram utilizados para caracterização da amostra, além da Escala de Depressão Geriátrica. Um total de 61 idosos com idade média de 72,5 anos, predominantemente do sexo feminino (85,2%) e escolaridade média de 11,2 foram avaliados e agrupados de acordo com o seu desempenho no UPSA por meio de uma análise de cluster. Resultados: A análise revelou três padrões de agrupamento, subdividindo a amostra em subgrupos que se diferenciaram significativamente em termos de idade, escolaridade, cognição global e todas as atividades instrumentais avaliadas pelo UPSA — planejamento, finanças, comunicação, transporte e habilidades domésticas. Conclusões: O presente estudo foi capaz de identificar a heterogeneidade presente na população idosa entre os diferentes fatores que compõe as AIVDs por meio de uma avaliação baseada em desempenho.


Subject(s)
Humans , Population Characteristics , Aged , Physical Functional Performance , Cluster Analysis
2.
Rev. cuba. med ; 60(1): e1382, tab
Article in Spanish | LILACS, CUMED | ID: biblio-1156560

ABSTRACT

Introducción: A partir de la aparición de la epidemia COVID-19 se conforma un equipo multidisciplinario en Santiago de Cuba con participación de varias instituciones y activado por el Consejo de defensa provincial. El análisis integrado epidemiológico, la gestión gubernamental y la respuesta social resultarían determinantes en el control de la enfermedad. Objetivos: Identificar posibles grupos de casos con COVID-19 en la provincia Santiago de Cuba y caracterizar su transmisión según variables epidemiológicas. Métodos: Se desarrolló un estudio ecológico, comparándose los clústeres de transmisión de COVID-19. Se resumieron variables de interés y se realizó análisis de redes sociales desde el punto de vista de las relaciones entre casos y contactos, así como análisis espacial. Resultados: Se identificaron cinco grupos espaciales de transmisión en los municipios, uno en Palma Soriano, uno en Contramaestre y tres en Santiago de Cuba. Los antecedentes patológicos personales (hipertensión y procesos respiratorios), el sexo femenino, los casos sintomáticos y el promedio de 22 a 27 contactos por cada confirmado fueron las variables más relevantes. Se identificó fuente de infección introducida en 51 por ciento (25/49). Además, se identificaron redes sociales complejas en la transmisión de la enfermedad. Conclusiones: La transmisión de COVID-19 en la provincia Santiago de Cuba mostró grupos de casos y contactos con redes sociales epidemiológicas características para cada municipio, así como el modo de transmisión de acuerdo a la fuente de infección, relaciones de familiaridad o cercanía social y la relación de distancia espacial entre contactos, aspectos que influyeron en las bajas tasas de incidencia de la enfermedad, con predominio en su forma sintomática, edades jóvenes y en mujeres(AU)


Introduction: From the onset of COVID-19 epidemic, a multidisciplinary team is formed in Santiago de Cuba with the participation of several institutions and activated by the Provincial Defense Council. Integrated epidemiological analysis, government management and social response would be decisive in controlling the disease. Objectives: To identify possible groups of COVID-19 cases in the Santiago de Cuba province and to describe the transmission according to epidemiological variables. Methods: An ecological study was carried out, comparing COVID-19 transmission clusters. Variables of interest were summarized and analysis of social contact networks was carried out from the point of view of the relationships between cases and contacts, as well as spatial analysis. Results: Five spatial transmission groups were identified in the municipalities, one in Palma Soriano, one in Contramaestre and three in Santiago de Cuba. The personal pathological antecedents (hypertension and respiratory processes), female sex, symptomatic cases and the average of 22 to 27 contacts for each confirmed were the most relevant variables. A source of introduced infection was identified in 51 percent (25/49). In addition, complex social networks were identified in the transmission of the disease. Conclusions: The transmission of COVID-19 in Santiago de Cuba province showed groups of cases and contacts with characteristic epidemiological social networks for each municipality, as well as the mode of transmission according to the source of infection, relationships of familiarity or social closeness and the relationship of spatial distance between contacts, which influenced on the low incidence rates of the disease, with predominance of symptomatic form, young ages and in women(AU)


Subject(s)
Humans , Cluster Analysis , Epidemiologic Methods , Coronavirus Infections/epidemiology , Social Networking , Cuba
3.
Rev. argent. salud publica ; 13: 1-10, 5/02/2021.
Article in Spanish | LILACS, BINACIS, ARGMSAL | ID: biblio-1150807

ABSTRACT

INTRODUCCIÓN: las lesiones y muertes de tránsito constituyen un problema importante de salud pública. El presente trabajo se propuso analizar, desde una perspectiva multidimensional, los datos oficiales sobre fallecidos por siniestros viales en la provincia de Buenos Aires. En primer lugar, se buscó construir una tipología de siniestros viales, y, en segundo lugar, se analizó la distribución de los conglomerados en distintas zonas de la provincia. MÉTODOS: se realizó un estudio no experimental, transversal y correlacional. Se aplicaron métodos de clasificación jerárquica a datos registrados por la Unidad del Observatorio y Estadísticas en Seguridad Vial; (n original = 1369, n luego de la depuración de datos = 1154). Los conglomerados resultantes se analizaron luego por región sanitaria. RESULTADOS: los resultados sugirieron ocho grupos relativamente homogéneos de víctimas con perfiles diferenciables de siniestralidad. Los conglomerados más importantes fueron dos: uno correspondiente a personas de sexo masculino, jóvenes y conductores de moto que fallecen en siniestros urbanos, y otro caracterizado por conductores de automóviles y adultos, también de sexo masculino, que fallecen en siniestros interurbanos. Los grupos se distribuyeron de manera diferente según la región sanitaria, aunque se advirtieron dos grandes perfiles: uno correspondiente al Gran Buenos Aires y otro al interior de la provincia. DISCUSIÓN: los resultados pueden ofrecer una base de segmentación útil para orientar intervenciones focalizadas en grupos de usuarios viales.


Subject(s)
Argentina , Accidents, Traffic , Cluster Analysis , Multivariate Analysis
4.
Article in English | WPRIM | ID: wpr-880321

ABSTRACT

BACKGROUND@#Household air pollution from biomass fuels burning in traditional cookstoves currently appeared as one of the most serious threats to public health with a recent burden estimate of 2.6 million premature deaths every year worldwide, ranking highest among environmental risk factors and one of the major risk factors of any type globally. Improved cookstove interventions have been widely practiced as potential solutions. However, studies on the effect of improved cookstove interventions are limited and heterogeneous which suggested the need for further research.@*METHODS@#A cluster randomized controlled trial study was conducted to assess the effect of biomass-fuelled improved cookstove intervention on the concentration of household air pollution compared with the continuation of an open burning traditional cookstove. A total of 36 clusters were randomly allocated to both arms at a 1:1 ratio, and improved cookstove intervention was delivered to all households allocated into the treatment arm. All households in the included clusters were biomass fuel users and relatively homogenous in terms of basic socio-demographic and cooking-related characteristics. Household air pollution was determined by measuring the concentration of indoor fine particulate, and the effect of the intervention was estimated using the Generalized Estimating Equation.@*RESULTS@#A total of 2031 household was enrolled in the study across 36 randomly selected clusters in both arms, among which data were obtained from a total of 1977 households for at least one follow-up visit which establishes the intention-to-treat population dataset for analysis. The improved cookstove intervention significantly reduces the concentration of household air pollution by about 343 μg/m@*CONCLUSIONS@#The biomass-fuelled improved cookstove intervention significantly reduces the concentration of household air pollution compared to the traditional method. This suggests that the implementation of these cookstove technologies may be necessary to achieve household air pollution exposure reductions.@*TRIAL REGISTRATION@#The trial project was retrospectively registered on August 2, 2018, at the clinical trials.gov registry database ( https://clinicaltrials.gov/ ) with the NCT03612362 registration identifier number.


Subject(s)
Air Pollutants/analysis , Air Pollution, Indoor/prevention & control , Biomass , Cluster Analysis , Cooking/methods , Ethiopia
5.
Article in English | WPRIM | ID: wpr-878372

ABSTRACT

Objective@#To study the polymorphism in P66 and its human B-cell epitopes of @*Methods@#Polymerase chain reaction (PCR) and sequencing were used to obtain the P66 sequences of 59 Chinese @*Results@#Results showed that genetic and amino acid diversity presented in the 66 kD protein of all 59 Chinese strains, especially in @*Conclusion@#In P66 of 59 Chinese strains, polymorphisms were widely distributed. More importantly, the P66 amino acid sequences of


Subject(s)
Bacterial Proteins/genetics , Borrelia burgdorferi/genetics , China , Cluster Analysis , Epitopes, B-Lymphocyte/genetics , Genetic Markers , Genotype , Humans , Mutation , Polymerase Chain Reaction , Polymorphism, Genetic , Porins/genetics
6.
Braz. arch. biol. technol ; 64: e21200118, 2021. tab, graf
Article in English | LILACS | ID: biblio-1339316

ABSTRACT

Abstract This paper focuses on developing a reduced distance matrix to improve the computational performance during the protein interactions clustering. This proposed matrix considers as centroids two alpha carbon atoms from a protein structure and stores the distances between these centroids and the other atoms from this same structure. Each row in this matrix represents a database record and each column is a distance value. Through this build matrix, clusters were performed using K-Means Clustering. The precision and performance of this presented technique were compared with aCSM, RID and another distance matrix methodology that considers the distances between all atoms from each protein structure. The results were satisfactory. The reduced distance matrix obtained a high precision and the best computational performance.


Subject(s)
Protein Interaction Maps , Carbon , Cluster Analysis , Computing Methodologies
7.
Rev. panam. salud pública ; 45: e49, 2021. tab, graf
Article in Spanish | LILACS | ID: biblio-1252005

ABSTRACT

RESUMEN Objetivo. Determinar y caracterizar áreas de riesgo potencial de la ocurrencia de leishmaniasis cutánea (LC) en América Latina (AL). Método. Estudio observacional ecológico con unidades de observación definidas por municipios con transmisión de LC entre 2014-2018. Se utilizaron variables medioambientales y socioeconómicas disponibles para al menos 85% de los municipios, combinados en una sola base de datos, a través del software R. Se combinó la metodología de análisis de componentes principales con un análisis de conglomerados jerárquicos para la formación de conglomerados de municipios en función de su similitud. Se estimó el V-test para definir la asociación positiva o negativa de las variables con los conglomerados y separación por divisiones naturales para determinar cuáles contribuyeron más a cada conglomerado. Se incorporaron los casos para atribuir el riesgo de LC para cada conglomerado. Resultados. Se incluyeron en el estudio 4 951 municipios con transmisión de LC (36,5% del total en AL) y se definieron siete conglomerados por su asociación con 18 variables medioambientales y socioeconómicas. El riesgo histórico de LC se asocia de manera positiva y en forma decreciente con los conglomerados Amazónico, Andino y Sabana; y de manera negativa con los conglomerados Boscoso/perenne, Boscoso/cultivo y Boscoso/poblado. El conglomerado Agrícola no reveló ninguna asociación con los casos de LC. Conclusiones. El estudio permitió identificar y caracterizar el riesgo de LC por conglomerados de municipios y conocer el patrón propio epidemiológico de distribución de la transmisión, lo que proporciona a los gestores una mejor información para las intervenciones intersectoriales para el control de la LC.


ABSTRACT Objective. Determine and characterize areas at potential risk for the occurrence of cutaneous leishmaniasis (CL) in Latin America. Method. Ecological observational study with observation units defined by municipalities with CL transmission during 2014-2018. Environmental and socioeconomic variables available for at least 85% of municipalities were combined in a single database, using R software. Principal component analysis was combined with hierarchical cluster analysis for the formation of clusters of municipalities according to their similarity. The V-test was used to define positive or negative association of variables with clusters and separation by natural divisions to determine which contributed more to each cluster. Cases were included to attribute CL risk for each cluster. Results. The study included 4 951 municipalities with CL transmission (36.5% of municipalities in Latin America); seven clusters were defined by their association with 18 environmental and socioeconomic variables. Historical risk of CL is associated positively and in descending order with the Amazonian, Andean, and Savanna clusters; and negatively with the Forest/perennial, Forest/cultivated, and Forest/populated clusters. The Agricultural cluster showed no association with CL cases. Conclusions. The study made it possible to identify and characterize CL risk by clusters of municipalities and to understand the characteristic epidemiological distribution patterns of transmission, providing program managers with better information for intersectoral interventions to control CL.


RESUMO Objetivo. Determinar e caracterizar as áreas de risco de ocorrência de leishmaniose cutânea na América Latina. Método. Estudo observacional ecológico com unidades de observação definidas por municípios com transmissão de leishmaniose cutânea entre 2014 e 2018. Foram usadas as variáveis ambientais e socioeconômicas disponíveis em 85% ou mais dos municípios, reunidas em uma única base de dados com o uso do software R. A metodologia de análise de componentes principais foi combinada a uma análise de conglomerados com agrupamento hierárquico para formar conglomerados de municípios por semelhança. O teste V foi usado para estabelecer a associação (positiva ou negativa) das variáveis com os conglomerados e uma separação por divisões naturais foi usada para determinar as variáveis que mais contribuíram em cada conglomerado. Os casos foram incluídos para avaliar o risco de leishmaniose cutânea em cada conglomerado. Resultados. A amostra do estudo compreendeu 4.951 municípios com transmissão de leishmaniose cutânea (36,5% do total na América Latina). Foram definidos sete conglomerados por apresentarem associação com 18 variáveis ambientais e socioeconômicas. Foi observada associação positiva e decrescente do risco histórico de leishmaniose cutânea com os conglomerados Amazônico, Andino e Savana e negativa com os conglomerados Mata/perene, Mata/cultivo e Mata/povoado. O conglomerado Agrícola não demonstrou associação com casos de leishmaniose cutânea. Conclusões. Este estudo permitiu identificar e caracterizar o risco de leishmaniose cutânea por conglomerados de municípios e conhecer o padrão epidemiológico de distribuição da transmissão da doença, oferecendo às autoridades dados melhores para subsidiar as intervenções intersetoriais para o controle da leishmaniose cutânea.


Subject(s)
Humans , Leishmaniasis, Cutaneous/epidemiology , Socioeconomic Factors , Cluster Analysis , Risk Assessment , Latin America/epidemiology
8.
Bol. latinoam. Caribe plantas med. aromát ; 20(1): 61-70, 2021. tab, ilus
Article in English | LILACS | ID: biblio-1284444

ABSTRACT

Identification of the chemical compositionof essential oils is very important for ensuring the quality of finished herbal products. The objective of the study was to analyze the chemical components present in the essential oils of five Beilschmiediaspecies (i.e. B. kunstleri, B. maingayi, B. penangiana, B. madang, and B. glabra) by multivariate data analysis using principal component analysis (PCA) and hierarchical clustering analysis (HCA) methods. The essential oils were obtained by hydrodistillation and fully characterized by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS). A total of 108 chemical components were successfully identified from the essential oils of five Beilschmiediaspecies. The essential oils were characterized by high proportions of ß-caryophyllene (B.kunstleri), δ-cadinene (B. penangianaand B. madang), and ß-eudesmol (B. maingayiand B. glabra). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) revealed that chemical similarity was highest for all samples, except for B. madang. The multivariate data analysis may be used for the identification and characterization of essential oils from different Beilschmiediaspecies that are to be used as raw materials of traditional herbal products.


La identificación de la composición química de los aceites esenciales es muy importante para garantizar la calidad de los productos herbales terminados. El objetivo del estudio fue analizar los componentes químicos presentes en los aceites esenciales de cinco especies de Beilschmiedia (B. kunstleri, B. maingayi, B. penangiana, B. madangy B. glabra) mediante análisis de datos multivariados utilizando los métodos de análisis de componente principal (PCA) y análisis de agrupamiento jerárquico (HCA). Los aceites esenciales se obtuvieron por hidrodestilación y se caracterizaron completamente por cromatografía de gases (GC) y cromatografía de gases-espectrometría de masas (GC-MS). Se identificaron con éxito un total de 108 componentes químicos a partir de los aceites esenciales de las cinco especies de Beilschmiedia. Los aceites esenciales se caracterizaron por altas proporciones de ß-cariofileno (B. kunstleri), δ-cadineno (B. penangianay B. madang) y ß-eudesmol (B. maingayiy B. glabra). El análisis de componentes principales (PCA) y el análisis de conglomerados jerárquicos (HCA) revelaron que la similitud química fue más alta para todas las muestras, excepto para B. madang. El análisis de datos multivariados puede usarse para la identificación y caracterización de aceites esenciales de diferentes especies de Beilschmiedia que se utilizan como materias primas de productos herbales tradicionales.


Subject(s)
Oils, Volatile/chemistry , Lauraceae/chemistry , Sesquiterpenes/analysis , Cluster Analysis , Distillation , Multivariate Analysis , Chromatography, Gas/methods , Principal Component Analysis , Monoterpenes/analysis
9.
São Paulo; s.n; 2021. 176 p.
Thesis in Portuguese | LILACS | ID: biblio-1178443

ABSTRACT

Introdução: A avaliação do consumo alimentar permite gerar conhecimento sobre a alimentação de indivíduos e populações, além de identificar os determinantes e tendências no consumo. Com ela é possível planejar ações, orientar serviços e implementar políticas públicas de saúde adequadas as necessidades da população. Com o apoio da tecnologia é possível automatizar algumas etapas do processo de análise de dados, com redução do tempo e recursos necessários, especialmente em grandes grupos. Entretanto, em países como o Brasil, ainda são escassas as aplicações de algoritmos de machine learning na avaliação da dieta. Objetivo: Aplicar algoritmos de machine learning na avaliação do consumo alimentar de servidores públicos em um grande estudo brasileiro. Métodos: Este estudo analisou transversalmente os dados da linha de base do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil). A partir destes dados, para explorar e classificar padrões alimentares, foi utilizado o algoritmo de cluster - K-Means. Na sequência, quatro algoritmos preditivos - Support Vector Machines (SVM), Decision Trees (DT), Naïve Bayes (NB), K-Nearest Neighbours (Knn) - foram aplicados incluindo variáveis demográficas, socioeconômicas e clínicas para predizer padrões alimentares. Adicionalmente, Sistemas de Recomendações foram construídos com algoritmos de Filtragem Colaborativa Baseada em Usuário e Itens (UBCF / IBCF) para o aconselhamento personalizado de dieta. As análises foram realizadas com a utilização do ambiente R. Resultados: Dois padrões alimentares foram derivados na amostra. O primeiro padrão, rotulado como "Padrão Ocidental", no qual os participantes apresentaram ingestões médias superiores para cereais refinados, feijões, carnes vermelhas e processadas, leite e produtos lácteos com alto teor de gorduras e bebidas adoçadas, quando comparados aqueles incluídos no outro padrão. O segundo padrão, rotulado como "Padrão Prudente", os participantes apresentaram consumo superior de frutas, vegetais, cereais integrais, aves, peixes, leite e produtos lácteos com redução de gorduras. Para a construção dos Sistemas de Recomendações foi fixado o limite de cinco itens, por participante, para evitar recomendações extensas e inespecíficas sobre a dieta (precisão entre 90% [IBCF] e 91% [UBCF]). Conclusão: Através da aplicação de algoritmos de machine learning foi possível realizar a análise de dados sobre o consumo, predizer padrões e personalizar recomendações sobre a dieta. Com o apoio das técnicas utilizadas, é possível subsidiar profissionais na gestão e no planejamento de ações de educação alimentar e nutricional personalizadas.


Introduction: The evaluation of food consumption allows generating knowledge about the diet of individuals and populations, in addition to identifying the determinants and trends in consumption. With it is possible to plan actions, guide services and implement public health policies appropriate to the needs of the population. With the support of technology, it is possible to automate some stages of the data analysis process, reducing the time and resources needed, especially in large groups. However, in countries like Brazil, the applications of machine learning algorithms in diet assessment are still scarce. Objective: Apply machine learning algorithms in the evaluation of food consumption by public servants in a large Brazilian study. Methods: This study cross-sectionally analyzed the baseline data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). From these data, to explore and classify dietary patterns, the cluster algorithm K-Means was used. Next, four predictive algorithms - Support Vector Machines (SVM), Decision Trees (DT), Naïve Bayes (NB), K-Nearest Neighbors (Knn) - were applied including demographic, socioeconomic and clinical variables to predict dietary patterns. Additionally, Recommendation Systems were built with User- and Items-Based Collaborative Filtering algorithms (UBCF / IBCF) for personalized diet advice. The analyzes were performed using the environment R. Results: Two dietary patterns were derived in the sample. The first pattern, labeled as "Western Pattern", in which the participants had higher average intakes for refined cereals, beans, red and processed meats, milk and dairy products with a high fat content and sweetened drinks, when compared to those included in the other pattern. The second pattern, labeled "Prudent Pattern", participants showed a higher consumption of fruits, vegetables, whole grains, poultry, fish, milk and dairy products with reduced fats. For the construction of the Recommender Systems, a limit of five items was set, per participant, to avoid extensive and unspecific recommendations on the diet (accuracy between 90% [IBCF] and 91% [UBCF]). Conclusion: Through the application of machine learning algorithms, it was possible to perform data analysis on consumption, predict patterns and personalize diet recommendations. With the support of the techniques used, it is possible to subsidize professionals in the management and planning of personalized food and nutrition education actions.


Subject(s)
Diet , Nutritional Epidemiology , Feeding Behavior , Machine Learning , Data Analysis , Cluster Analysis
11.
Article in Chinese | WPRIM | ID: wpr-879245

ABSTRACT

For speech detection in Parkinson's patients, we proposed a method based on time-frequency domain gradient statistics to analyze speech disorders of Parkinson's patients. In this method, speech signal was first converted to time-frequency domain (time-frequency representation). In the process, the speech signal was divided into frames. Through calculation, each frame was Fourier transformed to obtain the energy spectrum, which was mapped to the image space for visualization. Secondly, deviations values of each energy data on time axis and frequency axis was counted. According to deviations values, the gradient statistical features were used to show the abrupt changes of energy value in different time-domains and frequency-domains. Finally, KNN classifier was applied to classify the extracted gradient statistical features. In this paper, experiments on different speech datasets of Parkinson's patients showed that the gradient statistical features extracted in this paper had stronger clustering in classification. Compared with the classification results based on traditional features and deep learning features, the gradient statistical features extracted in this paper were better in classification accuracy, specificity and sensitivity. The experimental results show that the gradient statistical features proposed in this paper are feasible in speech classification diagnosis of Parkinson's patients.


Subject(s)
Cluster Analysis , Humans , Parkinson Disease/diagnosis , Speech
12.
Electron. j. biotechnol ; 48: 101-108, nov. 2020. tab, ilus
Article in English | LILACS | ID: biblio-1254920

ABSTRACT

BACKGROUND: Collagen is the most abundant protein in animals and can be obtained from residues of the food industry. Its hydrolysate has many desirable properties that make it suitable as an additive in foods and cosmetics, or as a component of scaffold materials to be used in biomedicine. RESULTS: We report here the characterization of type I collagen from five different sources, namely bovine, porcine, chicken, trout and salmon, as well as their hydrolysates by means of bioinformatics tools. As expected, the results showed that bovine and porcine collagen, as well as trout and salmon collagen, can be used interchangeably due to their high identity. This result is consistent with the evolution of proteins with highly identical sequences between related species. Also, 156 sequences were found as potential bioactive peptides, 126 from propeptide region and 30 from the central domain, according to the comparison with reported active sequences. CONCLUSIONS: Collagen analysis from a bioinformatic approach allowed us to classify collagen from 5 different animal sources, to establish its interchangeability as potential additive in diverse fields and also to determine the content of bioactive peptides from its in silico hydrolysis.


Subject(s)
Animals , Cattle , Peptides , Collagen/chemistry , Computational Biology , Protein Hydrolysates , Salmon , Swine , Cluster Analysis , Collagen Type I , Additives in Cosmetics , Food Additives , Hydrolysis
13.
Aval. psicol ; 19(3): 289-297, jul.-set. 2020. tab
Article in English | LILACS, INDEXPSI | ID: biblio-1131874

ABSTRACT

A new dimensional-based framework was proposed, the Hierarchical Taxonomy of Psychopathology (HiTOP). This study aimed to develop a specific version of the Dimensional Clinical Personality Inventory 2 (IDCP-2), focused on the assessment of the schizoid personality disorder (SZPD) according to the HiTOP. In stage 1, we developed a new factor to cover all SZPD traits, as presented in the HiTOP. Six factors (one new and five from the IDCP-2) composed the IDCP-SZPD. In stage 2, 434 adults from the community, aged from 18 to 67 years (M=31.6, SD=9.7), completed factors from three self-report measures: the IDCP-SZPD, PID-5, and FFaVA. The IDCP-SZPD factors and total score presented high reliability. Correlations and a bootstrap two-sample t-test comparison corroborated the expectations. Although we found evidence supporting the use of the IDCP-SZPD for the measurement of SZPD traits, further research is needed to verify the replicability of the present findings in samples composed of SZPD patients. (AU)


Um novo framework dimensional foi proposto, o Hierarchical Taxonomy of Psychopathology (HiTOP). O objetivo deste estudo foi desenvolver uma versão específica do Inventário Dimensional Clínico da Personalidade 2 (IDCP-2), com foco na avaliação do transtorno da personalidade esquizoide (TPE) de acordo com o HiTOP. No estágio 1, foi desenvolvido um novo fator, buscando cobrir todos os traços do TPE apresentados no HiTOP. Compuseram o IDCP-SZPD seis fatores (um novo e cinco do IDCP-2). No estágio 2, 434 adultos da população geral, com idade entre 18 e 67 anos (M = 31.6; DP = 9,7), completaram fatores de três medidas de autorrelato: IDCP-SZPD, PID-5 e FFaVA. Os fatores do IDCP-SZPD e o escore total apresentaram alta precisão. Correlações e comparações via bootstrap two-sample t teste corroboraram as expectativas. Embora evidências favoráveis tenham sido observadas para o uso do IDCP-SZPD, na avaliação de traços do TPE, estudos futuros devem verificar a replicabilidade dos achados em amostras de pacientes com TPE. (AU)


Un nuevo framework dimensional fue propuesto, el Hierarchical Taxonomy of Psychopathology (HiTOP). El objetivo fue el de desarrollar una versión específica del Inventario Dimensional Clínico de Personalidad 2 (IDCP-2), centrado en la evaluación del trastorno esquizoide de la personalidad (TPE) según el HiTOP. En la etapa 1 se desarrolló un nuevo factor para cubrir todos los rasgos del TPE presentados en el HiTOP. Seis factores (uno nuevo y cinco del IDCP-2) compusieron el IDCP-SZPD. En la etapa 2, 434 adultos de la comunidad, con edades comprendidas entre 18 y 67 años (M =31,6, DS=9,7), completaron los factores de tres medidas de auto-informe: IDCP-SZPD, PID-5 y FFaVA. Los factores del IDCP-SZPD y el puntaje total mostraron una alta confiabilidad. Las correlaciones y la comparación del bootstrap two-sample t test corroboraron las expectativas. Aunque se observaron evidencias favorables para el uso de la IDCP-SZPD para la medición de rasgos de TPE, los estudios posteriores deberían verificar la replicabilidad de los presentes hallazgos en muestras compuestas por pacientes con TPE. (AU)


Subject(s)
Humans , Female , Adolescent , Middle Aged , Aged , Schizoid Personality Disorder/diagnosis , Psychometrics , Cluster Analysis
14.
Psico USF ; 25(3): 507-518, jul.-set. 2020. graf
Article in English | LILACS, INDEXPSI | ID: biblio-1135731

ABSTRACT

In this study we investigated the relationship between the anti-prejudice norm and the expression of attitudes towards minority groups. Participated 100 people who evaluated a list with 16 target groups of prejudice, answering two questions: indicate the groups that feel less prejudice; and which ones do you prefer. The results showed that there are different levels of prejudice depending on the target-group, with the women, blacks and people with disabilities being the most protected by the norm. A hierarchical analysis of clusters evidenced an organization of the groups, classified as naturalised, blamed, sexual and political minorities. The anti-prejudice norm and the attitudes presented a strong and positive relation (r = 0.65, p < 0.001). A multilevel logistic regression analysis showed that this relation was moderated by the type of group. These results contribute to the studies on the expression of prejudice, besides demonstrating the role of norms in the understanding of the phenomenon. (AU)


Neste estudo investigamos a relação entre a norma antipreconceito e a expressão de atitudes frente a grupos minoritários. Participaram 100 pessoas que avaliaram uma lista com 16 grupos-alvo de preconceito, respondendo a duas perguntas: indique os grupos que sente menos preconceito; e quais os que mais prefere. Os resultados indicaram que há níveis diferentes de preconceito consoante o tipo de grupo-alvo, sendo os grupos de mulheres, negros e pessoas com deficiência os mais protegidos pela norma. Uma análise hierárquica de clusters evidenciou uma organização dos grupos, classificados como naturalizados, culpabilizados, minorias sexuais e políticas. A norma antipreconceito e as atitudes apresentaram uma relação forte e positiva (r = 0,65; p < 0,001). Uma análise de regressão logística multinível mostrou que essa relação foi moderada pelo tipo de grupo. Tais resultados contribuem aos estudos sobre a expressão do preconceito, além de demonstrarem o papel das normas na compreensão do fenômeno. (AU)


En este estudio investigamos la relación entre la norma anti-prejuicio y la expresión de actitudes frente a grupos minoritarios. Participaron 100 personas que evaluaron una lista con 16 grupos que sufren prejuicio, respondiendo a dos preguntas: indique los grupos que siente menos prejuicio; y los que más prefiere. Los resultados demuestran que hay niveles diferentes de expresión del prejuicio según el tipo de grupo, siendo los grupos de mujeres, negros y personas con discapacidad los más protegidos por la norma. Un análisis jerárquico de clusters evidenció una organización de los grupos, clasificados como naturalizados, culpabilizados, minorías sexuales y políticas. La norma anti-prejuicio y las actitudes presentaron una relación fuerte y positiva (r = 0,65, p < 0,001). Un análisis de regresión logístico multinivel mostró que esta relación fue moderada por el tipo de grupo. Tales resultados contribuyen a los estudios sobre la expresión del prejuicio, además de demostrar el papel de las normas en la comprensión del fenómeno. (AU)


Subject(s)
Humans , Female , Adolescent , Adult , Middle Aged , Prejudice/psychology , Minority Groups/psychology , Cluster Analysis , Regression Analysis
15.
Rev. salud pública ; 22(2): e212, mar.-abr. 2020. tab, graf
Article in Spanish | LILACS | ID: biblio-1139441

ABSTRACT

RESUMEN El 11 de marzo de 2020 la OMS declara el estado de pandemia por COVID-19. Para el 31 de julio de 2020, se han reportado 17 106 007 casos y 668 910 muertes a nivel global. La región de las Américas ha reportado 9 152 173 casos (53%) y 351 121 muertes (52,2%), por lo que resulta de interés el análisis de los datos en países de esta región. Argentina, Chile y Colombia, debido a sus características culturales, políticas y económicas, presentan similitudes que favorecen su estudio y comparación. Objetivo Realizar un análisis exploratorio de variables relacionadas con los sistemas de salud y datos epidemiológicos de COVID-19 en Argentina, Chile y Colombia. Metodología Estudio descriptivo de variables reportadas por los organismos oficiales de cada Estado. Resultados Se presentaron diferencias importantes en los casos activos, el número de pruebas realizadas y la mortalidad entre los tres países. La Ciudad Autónoma de Buenos Aires presenta la mayor tasa de casos activos a julio de 2020. De estos tres países, Colombia presenta las mayores cifras de fallecimientos confirmados por COVID-19 con cierre a 31 de julio de 2020. Se sugiere la unificación de un sistema de información para América Latina que permita hacer un monitoreo integral de variables de interés, que favorezca la calidad de los datos y que unifique el lenguaje técnico.(AU)


ABSTRACT On March 11, 2020 the WHO declared the state of pandemic by COVID-19. As of July 29, 2020, 17 106 007 cases and 668 910 deaths have been reported globally. The region of the Americas has reported 9 152 173 cases (53%) and 351 121 deaths (52,2%), so the aggregate analysis of the data in countries in this region is of interest. Argentina, Chile and Colombia, due to their demographic and economic characteristics, are countries that can be studied. Objetive Analyze variables related to health systems and epidemiological data of SARS-CoV-2 virus disease in Argentina, Chile and Colombia. Methods A descriptive study of variables reported by the official organisms of each state was used. Results There is an important difference in active cases and mortality among the three countries; the Autonomous City of Buenos Aires has the highest number of active cases as of July 2020. Colombia has the highest numbers of deaths confirmed by COVID-19 in the months of February to July 2020. We suggest the unification of an information system for Latin America that allows a comprehensive monitoring of variables, improves the qua-lity of data and unifies the technical language.(AU)


Subject(s)
Humans , Coronavirus Infections/epidemiology , Betacoronavirus , Cluster Analysis , Morbidity , Latin America/epidemiology
16.
Rev. chil. nutr ; 47(2): 255-263, abr. 2020. tab, graf
Article in English | LILACS | ID: biblio-1115496

ABSTRACT

The objective of this study was to identify dietary patterns in an outpatient cohort of coronary heart disease (CHD) patients, to compare these patterns with dietary recommendations of the international cardiology guidelines, and verify associations with cardiovascular risk factors. Dietary intake was assessed through a food frequency questionnaire. Dietary patterns were identified by cluster analysis. The total energy intake, fiber, cholesterol, macro and micronutrients were calculated. Two dietary patterns were identified in 123 patients. Pattern I was characterized by a greater consumption of whole carbohydrates, beans, meats, vegetables, and fruits. Pattern II was rich in refined carbohydrates, fried foods, and sweets. Participants in pattern I had lower values of diastolic blood pressure (DBP) with 77.1 ± 9.9 mmHg (p= 0.002) and glycated hemoglobin (HbA1c) of 7.83 ± 1.76 % (p= 0.029) compared to pattern II with 84.1 ± 14.3 mmHg and 9.02 ± 2.29 %, respectively. Therefore, pattern I had a healthier nutritional composition, however, nutritional adequacy was still lacking. Despite this, participants in pattern I had significantly lower values of DBP and HbA1c, in addition to being associated with a better control of DBP.


El objetivo de este estudio fue identificar los modelos dietéticos de una cohorte de pacientes ambulatorios con enfermedad de las arterias coronarias (EAC) y compararlos con las recomendaciones dietéticas de las directrices internacionales de cardiología y verificar su asociación con el control de los factores de riesgo cardiovascular. La ingesta dietética se evaluó mediante un cuestionario de frecuencia de consumo. El modelo dietético fue identificado por análisis de conglomerados. Se calculó la ingesta energética total, fibras, colesterol, macro y micronutrientes. Se identificaron dos modelos dietéticos en 123 pacientes. El modelo I se caracterizó por un mayor consumo de carbohidratos enteros, frijoles, carnes, verduras y frutas. El modelo II era rico en carbohidratos refinados, alimentos fritos y dulces. Los participantes en el modelo I tuvieron valores más bajos de presión arterial diastólica (PAD) con 77.1 ± 9.9 mmHg (p= 0.002) y hemoglobina glucosilada (HbA1c) de 7.83 ± 1.76 % (p= 0.029) en comparación con el modelo II con 84.1 ± 14.3 mmHg y 9.02 ± 2.29%, respectivamente. Por lo tanto, el modelo I tenía una composición nutricional más saludable, sin embargo, todavía carece de adecuación nutricional. A pesar de esto, los participantes del modelo I tuvieron valores más bajos de PAD y HbA1c.


Subject(s)
Humans , Male , Female , Middle Aged , Coronary Disease , Diet , Brazil , Energy Intake , Cluster Analysis , Cross-Sectional Studies , Surveys and Questionnaires , Feeding Behavior , Heart Disease Risk Factors
17.
J. health med. sci. (Print) ; 6(1): 29-36, ene.-mar. 2020. ilus
Article in Spanish | LILACS | ID: biblio-1096530

ABSTRACT

En la actualidad, los análisis de distribución espacial mediante el uso de técnicas de clusters para enfermedades crónicas como el cáncer de mama, son relevantes para la identificación de patrones espaciales de la mortalidad por cáncer según áreas geográficas. Identificar clústeres espaciales de la mortalidad por cáncer de mama en mujeres a nivel de las provincias del Ecuador, entre 2004 al 2018. Estudio observacional, de tipo descriptivo, ecológico multigrupal que compara a nivel espacio ­ temporal las tasas de mortalidad por cáncer de mama en mujeres según las provincias del Ecuador, utilizando el índice de Móran para el análisis de autocorrelación y el algoritmo de k-medias para el análisis de agrupamiento en períodos quinquenales mediante el programa informático ArcGIS versión 10.5. Resultados. En el Ecuador, el 86,5% de las muertes por cáncer de mama en mujeres se registraron en el área urbana, dichas muertes tienen un patrón no aleatorio según el índice de Morán, distinto al área rural que tiene un patrón aleatorio; se identificó diferencia en el agrupamiento de la mortalidad por cáncer de mama en las provincias urbanas y rurales, donde se obtuvo para el área urbana, clústeres con altas, media-altas, media-baja y bajas tasas de mortalidad, mientras que en lo rural se obtuvieron solo clústeres con altas, medias y bajas tasas de mortalidad. La distribución espacial y el análisis de agrupamiento identificó clústeres de la mortalidad por cáncer de mama en el Ecuador, evidenciando entre lo urbano y rural diferencias en los clústeres obtenidos, siendo esta información de utilidad para la implementación de estrategias de control del cáncer en el país.


Currently spatial distribution analyzes through the use of cluster techniques for chronic diseases such as breast cancer are revealing for the identification of spatial patterns of cancer mortality according to geographic areas. Objective. Identify spatial clusters of breast cancer mortality in women at the level of the provinces of Ecuador, between 2004 to 2018. We used an observational, descriptive, ecological multigroup study that compares at a Spatio-temporal level the rates of breast cancer mortality in women according to the provinces of Ecuador, using the Moran index for the autocorrelation analysis and the k-, means algorithm for cluster analysis in five-year periods using the ArcGIS version 10.5 software. Results. In Ecuador, 86.5% of breast cancer deaths in women were recorded in the urban area, these deaths have a non-random pattern according to the Morán Index different from the rural area that has a random pattern; difference was identified in the grouping of breast cancer mortality in urban and rural provinces, where it was obtained for urban areas, clusters with high, medium. high, medium-low and low mortality rates. While in rural areas only clusters with high, medium and low mortality rates were obtained. Conclusions. The spatial distribution and cluster analysis identified clusters of breast cancer mortality in Ecuador; evidencing between urban and rural differences in the clusters obtained, this information is useful for the development of cancer control strategies in the country.


Subject(s)
Humans , Female , Breast Neoplasms/mortality , Cluster Analysis , Rural Areas , Demography , Urban Area , Ecuador/epidemiology , Spatial Analysis
18.
J. health med. sci. (Print) ; 6(1): 45-50, ene.-mar. 2020. tab, ilus
Article in Spanish | LILACS | ID: biblio-1096716

ABSTRACT

Los métodos de clasificación permiten explorar y analizar grandes conjuntos de datos visualmente, lo cual es de gran utilidad para tomar decisiones rápidas. El objetivo fue comparar dos métodos de análisis de clúster para big data en variables demográficas de las provincias del Ecuador. Se hizo uso de un estudio observacional de tipo comparativo mediante la representación simultanea del HJ-Biplot y el método Two Step (clúster bietápico), a través del software MultBiplot y SPSS. Los datos corresponden a variables demográficas de interés sociosanitarias tasa de mortalidad general, tasa de mortalidad infantil, tasa de natalidad, densidad poblacional, porcentaje urbano y esperanza de vida, medidas en las provincias del Ecuador. Se utilizaron datos provenientes del Instituto de Estadísticas y Censos INEC. Se analizó la asociación entre variables y se identificaron clústeres de las provincias del Ecuador según estas variables demográficas. Según la representación simultánea del HJ-Biplot se identificaron 3 clústeres, el clúster 1 son provincias con mayor densidad poblacional y tasas de mortalidad general, pero valores bajos de tasas de natalidad, el clúster 2 agrupa provincias con mayor esperanza de vida y tasas de mortalidad infantil pero bajos valores de tasa de natalidad y el clúster 3 están las provincias con valores altos de tasas de natalidad y valores bajos de densidad poblacional, esperanza de vida, tasas de mortalidad general y mortalidad infantil, distintos resultados se obtuvieron con el método Two Step. Se pudo concluir que estos métodos son de utilidad para explorar las similitudes entre las provincias según variables demográficas.


The classification methods allow to explore and analyze big data sets visually, which is very useful for making quick decisions. This work aimed to compare of two methods of cluster analysis for big data in demographic variables of the provinces of Ecuador. An observational study of comparative type was carried out through the simultaneous representation of the HJ/Biplot and the Two Step method (two-stage cluster), through the MultBiplot and SPSS software. The data correspond to demographic variables of socio-health interest, general mortality rate, infant mortality rate, birth rate, population density, urban percentage and life expectancy, measured in the provinces of Ecuador. Data from Statistics and Census Institute were used. The association between variables was analyzed and clusters of the provinces of Ecuador were identified according to these demographic variables. According to the simultaneous representation of the HJBiplot, 3 clusters were identified, cluster 1 are provinces with higher population density and general mortality rates, but low birth rates values, cluster 2 are provinces with higher life expectancy and mortality rates infantile but low birth rate values and cluster 3 are the provinces with high birth rates values and low population density, life expectancy, general mortality and infant mortality rates, different results were obtained with the Two Step method. It was concluded that these methods are useful for exploring the similarities between provinces according to demographic variables.


Subject(s)
Humans , Cluster Analysis , Demography , Models, Statistical , Vital Statistics , Ecuador/epidemiology
19.
Rev. salud pública ; 22(1): e275841, ene.-feb. 2020. tab, graf
Article in Spanish | LILACS | ID: biblio-1127221

ABSTRACT

RESUMEN Objetivo Describir la distribución geográfica y el rol de factores sociodemográficos sobre la mortalidad por suicidios, de acuerdo con sexo y grupos de edad en Argentina durante los períodos 1999-2003 y 2008-2012. Método El rol de factores sociodemográficos sobre la mortalidad por suicidios y su distribución geográfica fueron analizados mediante regresiones múltiples espaciales. Se incluyeron tres variables independientes: un índice de fragmentación social, un índice de pobreza y la densidad poblacional como indicador del nivel de ruralidad. Resultados La fragmentación social y el suicidio estuvieron directamente relacionados en hombres de 10-59 años y mujeres de 10-29 años durante 1999-2003. Durante 2008-2012 el riesgo de suicidio fue mayor en áreas de baja densidad poblacional, salvo en mujeres de 10-29 años. Conclusiones Los resultados obtenidos en este estudio apoyan la hipótesis de fragmentación social como fenómeno asociado al riesgo de suicidio en departamentos de la Argentina, pero también dan apoyo a la hipótesis de un mayor riesgo de suicidio en áreas rurales. Las medidas de prevención del suicidio podrían enfocarse en políticas que promuevan la integración social, especialmente en población joven, así como también una mayor integración de las áreas rurales con el resto del territorio.(AU)


ABSTRACT Objective The aim of this study was to describe the geographical distribution and the role of sociodemographic factors on mortality by suicides, according to sex and age groups, in Argentina during the periods 1999-2003 and 2008-2012. Methods The role of sociodemographic factors on mortality by suicides and their geographical distribution were analyzed by means of multiple spatial regressions. Three independent variables were included: an index of social fragmentation, a poverty index and population density, as an indicator of the level of rurality. Results Social fragmentation and suicide were directly related in men 10-59 years old and women 10-29 years old during 1999-2003. During 2008-2012, the risk of suicide was higher in areas of low population density, except for women aged 10-29 years. Conclusions The results obtained in this study support the hypothesis of social fragmentation as a phenomenon associated with the risk of suicide in departments of Argentina, but also support the hypothesis of an increased risk of suicide in rural areas. Suicide prevention measures could focus on policies that promote social integration, especially in the young population, as well as greater cohesion of rural areas.(AU)


Subject(s)
Humans , Socioeconomic Factors , Suicide/trends , Argentina/epidemiology , Cluster Analysis , Spatial Analysis
20.
Electron. j. biotechnol ; 43: 23-31, Jan. 2020. ilus, graf
Article in English | LILACS | ID: biblio-1087514

ABSTRACT

Background: Hong Qu glutinous rice wine (HQGRW) is brewed under non-aseptic fermentation conditions, so it usually has a relatively high total acid content. The aim of this study was to investigate the dynamics of the bacterial communities and total acid during the fermentation of HQGRW and elucidate the correlation between total acid and bacterial communities. Results: The results showed that the period of rapid acid increase during fermentation occurred at the early stage of fermentation. There was a negative response between total acid increase and the rate of increase in alcohol during the early fermentation stage. Bacterial community analysis using high-throughput sequencing technology was found that the dominant bacterial communities changed during the traditional fermentation of HQGRW. Both principal component analysis (PCA) and hierarchical clustering analysis revealed that there was a great difference between the bacterial communities of Hong Qu starter and those identified during the fermentation process. Furthermore, the key bacteria likely to be associated with total acid were identified by Spearman's correlation analysis. Lactobacillus, unclassified Lactobacillaceae, and Pediococcus were found, which can make significant contributions to the total acid development (| r| N 0.6 with FDR adjusted P b 0.05), establishing that these bacteria can associate closely with the total acid of rice wine. Conclusions: This was the first study to investigate the correlation between bacterial communities and total acid during the fermentation of HQGRW. These findings may be helpful in the development of a set of fermentation techniques for controlling total acid.


Subject(s)
Bacteria/isolation & purification , Wine/microbiology , Pediococcus/isolation & purification , Pediococcus/genetics , Pediococcus/metabolism , Time Factors , Acetobacter/isolation & purification , Acetobacter/genetics , Acetobacter/metabolism , Cluster Analysis , Sequence Analysis , Computational Biology , Principal Component Analysis , Fermentation , Microbiota , Hydrogen-Ion Concentration , Lactobacillus/isolation & purification , Lactobacillus/genetics , Lactobacillus/metabolism
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