Clinical related factors to neuroendocrine tumors in Ecuadorian patients: a logistic biplot approach / Factores clínicos asociados a tumores neuroendocrinos en pacientes ecuatorianos: un análisis biplot logístico

Abstract Neuroendocrine tumors (NETs) are relative rare, affecting neuroendocrine cells throughout the body. Most tumors are diagnosed at advanced stages. NETs prevalence has increased in the last years but there is little data available in developing countries. The aim of this study was to describe symptoms associated with NETs in patients of the Society for the Fight Against Cancer (SOLCA) in Ecuador from 2005 to 2020; using logistic biplots, in a hospital database, generating binary responses (presence/absence) relevant to this study. The results showed that the mean age was 59 and the study showed no difference in prevalence between genders. NETs were mainly found in lungs (19%), followed by stomach (18%) and skin (9%). Most patients had pathological diagnosis G2 and G3 (30% and 70%, respectively). Symptoms as cough, dyspnea, weight loss, diarrhea, constipation, abdominal pain, dyspepsia, hypertensive crisis, distended abdomen and intestinal obstruction had p values <0.05. Additionally, the statistical analysis showed that cough and intestinal obstruction were also common, bearing in mind that patients had most frequent NETs in the lungs and skin. In summary, our results indicate that symptoms of NETs patients were positively associated with lung and skin. Further investigation is needed focusing on the type of NETs and their symptoms in order to establish an early marker for diagnosis.

Resumen Los tumores neuroendocrinos (TNE) son relativamente raros y afectan a las células neuroendocrinas de todo el cuerpo. La mayoría de los tumores se diagnostican en etapas avanzadas. La prevalencia de los TNE ha aumentado en los últimos años, pero hay pocos datos en los países en desarrollo. El objetivo de este estudio fue determinar los síntomas asociados a los TNE en pacientes de la Sociedad de Lucha contra el Cáncer (SOLCA) en Ecuador entre 2005 y 2020, utilizando biplots logísticos en una base de datos hospitalaria, generando respuestas binarias (presencia / ausencia) relevantes para este estudio. Los resultados mostraron que la edad promedio era de 59 años y el estudio no encontró diferencias en la prevalencia entre géneros. Los TNE se encontraron con mayor frecuencia en los pulmones (19%), seguidos del estómago (18%) y piel (9%). La mayoría de los pacientes tenían diagnóstico patológico G2 y G3 (30% y 70% respectivamente). Los síntomas como tos, disnea, pérdida de peso, diarrea, estreñimiento, dolor abdominal, dispepsia, crisis hipertensiva, abdomen distendido y obstrucción intestinal tuvieron valores de p <0,05. Además, el análisis estadístico mostró que la tos y la obstrucción intestinal también eran comunes, teniendo en cuenta que los pacientes tenían TNE más frecuentes en los pulmones y la piel. En resumen, nuestros resultados indican que los síntomas de los pacientes con TNE se asociaron positivamente con los pulmones y la piel. Se necesitan más investigaciones que se centren en el tipo de TNE y sus síntomas a fin de establecer un marcador más temprano para el diagnóstico.

Relative performance of wheat genotypes under individual and combined water deficit and salinity stress

Ascertaining the genetic variability and its relationships among valuable genetic resources is important for crop improvement programme. Here, we assessed the response of eleven wheat (Triticum aestivum L.) genotypes using cluster and principal component analysis (PCA) based on morphophysiological data and yield under nine different environments. Wheat genotype WH 1080 maintained higher photosynthetic efficiency under individual stress of 50% water deficit (drought) and 100 mM NaCl (salt), whereas under interactive stresses KRL 370 and KRL 283 were found to be the best genotypes. The highest value of Na+/K+ ratio in shoots was recorded for WH 1080 (1.167) and lowest in KRL 283 (0.612) under combined stresses. Proline accumulation was maximum in KRL 330 (3.17 mg g-1 FW) and minimum in KRL 283 (2.8 mg g-1 FW). Significantly higher reduction (73.4%) was observed in HD 2009 for grain weight/plant at 100 mM NaCl + 50% WD stress treatment whereas minimum reduction of 39.18% was recorded in KRL 370 in comparison to the control treatment. The PCA showed that the first three components comprising about 91% of the total variation for which the variables were analyzed. AMMI model revealed KRL 210 to be stable genotype as being close to center on biplot. E5 environment (100 mM NaCl) was most stable followed by E9 (50% WD + 100 mM NaCl). HD 2888, C-306, HD 2851 and HD 2009 were having positive interaction with E1 (Control) whereas WH 1080 had positive interaction with water deficit environments i.e. E2 and E3 (25 and 50% WD) while KRL 433 had highest positive interaction with combined water deficit and salt stress environments E6, E7, E8 and E9, followed by KRL 370. Similarly, KRL 283, KRL 330, KRL 210 and Kharchia 65 had high positive interaction with saline environments E4 and E5. Findings of the experiment would be beneficial to wheat breeders, specifically the location-specific promising genotypes could possibly be used to develop/breed MAGIC populations to tag genes/alleles conferring drought and salinity tolerance.

Análisis multivariado HJ-Biplot de la ocurrencia de Helicobacter pylori como riesgo para cáncer gástrico, en la ciudadela el Cristo de Consuelo, Milagro Ecuador / HJ-Biplot multivariate analysis of the occurrence of Helicobacter pylori as a risk for gastric cancer, in the citadel of El Cristo de Consuelo, Milagro Ecuador

El Helicobacter pylori, es el causante del mayor número de úlceras y cáncer gástrico a nivel mundial. Población de 15 a 20 años, de escasos recursos y con mayor precariedad en el funcionamiento de los servicios públicos como es el agua potable son altamente vulnerables. Por lo que se planteó como objetivo, realizar un análisis multivariado HJ-Biplot de la ocurrencia de H. pylori como riesgo para cáncer gástrico, en la ciudadela el Cristo de Consuelo, Milagro Ecuador. Estudio epidemiológico transversal, descriptiva y de tipo observacional, contó con una población finita de 230 personas. Técnicas de recolección de datos: la encuesta, la observación directa y la detección de H. pylori en las muestras de heces. El análisis de las muestras biológicas se realizó mediante el método de Elisa en muestras de suero y heces. A los datos obtenidos se les aplicó el método de análisis multivariado bidireccional llamado HJ-Biplot, reflejándose en las variables las relaciones de las composiciones químicas, físicas y biológicas. Los resultados conforman dos grupos de puntos de muestra que coinciden satisfactoriamente con las estaciones de la región. Con este estudio se demuestra que los métodos estadísticos multivariantes son valiosos para interpretar conjuntos de datos complejos, concretamente, para la red de prevalencia de cáncer gástrico causado por el bacilo H. pylori, ha ido en aumento en los últimos años tanto en el Ecuador como en el resto del mundo. Es necesario que se establezcan los mecanismos de control de los agentes causantes de la propagación de este bacilo lo que incidirá en la disminución en la tasa de crecimiento del cáncer gástrico(AU)

Helicobacter pylori is the cause of the highest number of ulcers and gastric cancer worldwide. Population aged 15 to 20 years, with limited resources and with greater precariousness in the operation of public services such as drinking water, are highly vulnerable. Therefore, the objective was to carry out a multivariate HJ-Biplot analysis of the occurrence of H. pylori as a risk for gastric cancer, in the citadel of Cristo de Consuelo, Milagro Ecuador. Cross-sectional, descriptive and observational epidemiological study, had a finite population of 230 people. Data collection techniques: survey, direct observation and detection of H. pylori in stool samples. Analysis of biological samples was performed using the Elisa method in samples of serum and feces. The obtained data were applied the method of bi-directional multivariate analysis called HJ-Biplot, reflecting in the variables the relationships of the chemical, physical and biological compositions. The results form two groups of sample points that successfully coincide with the stations in the region. This study shows that multivariate statistical methods are valuable for interpreting complex data sets, specifically for the prevalence network of gastric cancer caused by the H. pylori bacillus, which has been increasing in recent years both in Ecuador and in the rest of the world. it is necessary to establish the control mechanisms of the agents that cause the spread of this bacillus, which will affect the decrease in the growth rate of gastric cáncer(AU)

Evaluation of drought tolerance indices for barley landraces under irrigated and dry conditions / Avaliação de índices de tolerância seca para terraços de cevada em condições irrigadas e secas

Barley cultivation for drought areas requires a reliable assessment of drought tolerance variability among the breeding germplasms. Hence, 121 barley landraces, advanced breeding lines, and varieties were evaluated under both moisture non-stress and stress field conditions using a lattice square (11×11) design with two replications for each set of the trials. Twelve drought tolerance indices (SSI, TOL, MP, GMP, STI, YI, YSI, HM, SDI, DI, RDI, and SSPI) were used based on grain yield under normal (Yp) and drought (Ys) conditions. Analysis of variance showed a significant genetic variation among genotypes for all indices except for TOL and SSPI indices. Yp had a very strong association with Ys (r = 0.92**) that indicates high yield potential under non-stress can predict better yield under stress conditions. Yp and Ys were positively and significantly correlated with MP, GMP, STI, YI, HM, and DI indices, whereas they were negatively correlated with SSI and SDI. In principal component analysis (PCA), the first PC explained 64% of total variation with Yp, Ys, MP, GMP, STI, YI, HM, and DI. The second PC explained 35.6% of the total variation and had a positive correlation with SSI, TOL, SDI, and SSPI. It can be concluded that MP, GMP, STI, YI, HM and DI indices with the most positive and significant correlation with the yield at both non-stress and stress environments would be better indices to screen barley genotypes, although none of the indices could undoubtedly identify high yield genotypes under both conditions.

O cultivo de cevada para áreas secas exige uma avaliação confiável da variabilidade da tolerância à seca entre os germoplasmas reprodutores. Assim, 121 linhagens crioulas de cevada (linhas de reprodução avançada e variedades) foram avaliadas em campo sob condições sem estresse e com estresse de umidade do solo, utilizando-se para isso um arranjo experimental de malha quadrada (11×11), com duas repetições para cada conjunto de ensaios. Foram utilizados 12 índices de tolerância à seca (SSI, TOL, MP, GMP, STI, YI, YSI, HM, SDI, DI, RDI e SSPI), com base no rendimento de grãos sob condições normais sem estresse (Yp) e com estresse de seca (Ys). A análise de variância mostrou uma variação genética significativa entre os genótipos para todos os índices, com exceção dos índices TOL e SSPI. Yp teve uma associação muito forte com Ys (r = 0,92**), o que indica que o potencial de alto rendimento sob condições sem estresse pode prever melhor rendimento sob condições de estresse. Yp e Ys foram positivamente e significativamente correlacionados com os índices MP, GMP, STI, YI, HM e DI, enquanto, foram correlacionados negativamente com os índices SSI e SDI. Na análise de componentes principais (PCA), o primeiro PC explicou 64% da variação total com Yp, Ys, MP, GMP, STI, YI, HM e DI. O segundo PC explicou 35,6% da variação total e apresentou correlação positiva com SSI, TOL, SDI e SSPI. Pode-se concluir que, os índices MP, GMP, STI, YI, HM e DI com a correlação mais positiva e significativa com a produção nos ambientes sem estresse e com estresse seriam melhores índices para a seleção de genótipos de cevada, embora nenhum dos índices pudesse concretamente identificar genótipos de alto rendimento sob ambas as condições.

Análisis clúster para big data: una aplicación con variables demográficas en provincias del Ecuador / Cluster analysis for big data: an application with demographic variables in provinces of Ecuador

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.

Spatiotemporal and variability gait data in community-dwelling elderly women from Brazil

ABSTRACT Background Gait is an extremely complex motor task; therefore, gait data should encompass as many gait parameters as possible. Objective To provide reference values for gait measurements obtained from a Brazilian group of community-dwelling elderly females between the ages of 65 and 89 years and to apply the PCA-biplot to yield insight into different walking strategies that might occur during the aging process. Method 305 elderly community-dwelling females living in Brazil were stratified into four age groups: 65-69 years (N=103); 70-74 years (N=95); 75-79 years (N=77); and ≥80 years (N=30). Age, height, and BMI were assessed to describe the characteristics of the groups. Gait spatiotemporal and variability data were obtained using the GAITRite® system. Principal component analysis, followed by MANOVA and the PCA-biplot approach were used to analyze the data. Results 95% CI showed that only three components – rhythm, variability, and support - together explained 74.2% of the total variance in gait that were different among the groups. The older groups (75-79 and ≥80 years) walked with lower than average velocity, cadence, and step length and were above average for the variables stance, step, swing, and double support time and the ≥80 year old group presented the highest gait variability compared to the other groups. Conclusion Aging is associated with decreased gait velocity and cadence and increased stance, step time, and variability, but not associated with changes in base of support. In addition, the PCA-biplot indicates a decline towards decreased rhythm and increased variability with aging.

Spatiotemporal gait parameters and recurrent falls in community-dwelling elderly women: a prospective study

BACKGROUND: Falling is a common but devastating and costly problem of aging. There is no consensus in the literature on whether the spatial and temporal gait parameters could identify elderly people at risk of recurrent falls. OBJECTIVE: To determine whether spatiotemporal gait parameters could predict recurrent falls in elderly women. METHOD: One hundred and forty-eight elderly women (65-85 years) participated in this study. Seven spatiotemporal gait parameters were collected with the GAITRite(r) system. Falls were recorded prospectively during 12 months through biweekly phone contacts. Elderly women who reported two or more falls throughout the follow-up period were considered as recurrent fallers. Principal component analysis (PCA) and discriminant analysis followed by biplot graph interpretation were applied to the gait parameters. RESULTS: After 12 months, 23 elderly women fell twice or more and comprised the recurrent fallers group and 110 with one or no falls comprised the non-recurrent fallers group. PCA resulted in three components that explained 88.3% of data variance. Discriminant analysis showed that none of the components could significantly discriminate the groups. However, visual inspection of the biplot showed a trend towards group separation in relation to gait velocity and stance time. PC1 represented gait rhythm and showed that recurrent fallers tend to walk with lower velocity and cadence and increased stance time in relation to non-recurrent fallers. CONCLUSIONS: The analyzed spatiotemporal gait parameters failed to predict recurrent falls in this sample. The PCA-biplot technique highlighted important trends or red flags that should be considered when evaluating recurrent falls in elderly females. .

Análises Biplot: conceitos, interpretações e aplicações / Biplot analysis: concepts, interpretations and uses

A seleção e recomendação de genótipos superiores são dificultadas devido à ocorrência da interação genótipo e ambiente. Nesse contexto, as análises biplot têm sido cada vez mais utilizadas na análise de dados agronômicos, com interações de natureza complexa. Entretanto, as particularidades existentes no gráfico biplot dificultam sua interpretação, podendo induzir o pesquisador a erros. Assim, este artigo de revisão discute a aplicabilidade e a interpretação gráfica dos modelos AMMI (Additive Main effects and Multiplicative Interaction) e GGE biplot (genotype main effects + genotype environment interaction) destas análises no gráfico biplot. Também, visa a desmistificar a necessidade de comparação entre ambas as metodologias. Discute-se quanto à escolha da metodologia mais adequada, levando em consideração a informação requerida e os objetivos do pesquisador.

The genotype environment interaction (GE) influences on the selection and recommendation of cultivars. Biplot analysis has been increasingly used in data analysis of complex traits in agriculture. However, the peculiarities of biplot graphic could induce the researcher to errors on interpretation. Thus, this review argues the applicability and graphic interpretation of models AMMI (Additive Main Effects and Multiplicative Interaction) and GGE biplot (genotype main effects + genotype environment interaction). Moreover, also aims to explain that it is not adequate to compare both statistical methods. It is discussed the best methodology considering the information required and the research objectives.

Genotype X Environment Interaction and Yield Performance of 43 Improved Cassava (Manihot esculenta Crantz) Genotypes at Three Agro-climatic Zones in Nigeria.

Aim: To determine the possible effects of environment and genotypic differences on root yield and other related traits. Methodology: 43 improved cassava genotypes were evaluated for root yield, root number, root dry matter, cassava mosaic disease and Cassava bacterial disease. The experiments were conducted using a randomized complete-block design with four replications for two years in three representative agro-ecological zones (Mokwa, Ibadan and Onne) in Nigeria. The data collected were subjected to combined analyses of variance using the GLM procedure of Statistical Analysis System (SAS 9.2) to determine the magnitude of the main effects and interactions. GGEbiplot software (GGEbiplot, 2007) was applied for visual examination of the GEI pattern of the data. Results: Genotype, Location and genotype by environment (GXE) interaction were highly significant for all the traits studied (P< 0.001), indicating genetic variability between genotypes by changing environments. The partitioning of GGE through GGE biplot analysis showed that PC1 and PC2 accounted for 61.3% and 28.8% of GGE sum of squares respectively for root yield, explaining a total of 90.1% variation. Conclusion: Genotypes G4 and G15 were the highest yielding and stable genotypes. G2 and G7 were equally stable but with poor roots yield. G43, which had a mean yield similar to the grand mean, may be regarded as a desirable genotype. Mokwa and Ibadan were found to be the most discriminative and the least representative environments for root yields while Onne environment was found to be the most representative and the least discriminative.

Testes multiambientais na seleção de genótipos de arroz utilizando o modelo de regressão nos sítios ou locais / Multi-environment tests in the selection of rice genotypes using sites regression model

A análise da interação genótipo x ambiente utilizda no melhoramento de plantas tem sofrido mudanças na última década, melhorando a sua eficiência quanto à seleção dos genótipos sob diferentes condições ambientais. O objetivo deste trabalho foi analisar a produtividade e estabilidade de 12 genótipos de arroz em oito ambientes, durante os anos 2005 e 2006, na Colômbia. O delineamento utilizado foi o de blocos ao acaso com quatro repetições. Os parâmetros de estabilidade fenotípica e o agrupamento dos ambientes foram estimados pelo estudo da interação genótipo x ambiente, segundo o método SREG (Regressão nos sítios ou locais) e seu gráfico biplot (GGE). As análises estatísticas indicaram diferenças significativas (com 5 por cento de probabilidade de erro) entre genótipos e entre ambientes e significância (com 5 por cento de probabilidade de erro) da interação genótipo x ambiente, sugerindo uma resposta diferente dos genótipos nos vários ambientes. No método SREG, os dois primeiros componentes principais da interação explicaram 75,29 por cento da interação. Os genótipos 400094, 350361 e a variedade Fedearroz 50 foram considerados os de maior produtividade. Segundo o gráfico biplot GGE, os ambientes La Libertad e Escobal foram os mais favoráveis para o cultivo do arroz.

The analysis of genotype x environment interaction in plant breeding have been enlarged with new methodologies in the last decade, improving its efficiency on the selection of genotypes under different environmental conditions. The objective of this research was to analyze the yield and stability of twelve genotypes of rice, in eight environments, during the years 2005 and 2006 in Colombia. Completely randomized block designs with four replications were used. The phenotypic stability parameters and grouping of environments were estimated by the genotype-environment interaction study according to SREG (Sites Regression) method and its biplot graphic (GGE). The statistical analysis indicated significant differences (with 5 percent probability error) among genotypes and among environments. Also, it pointed out the significance (with 5 percent probability error) of the genotype-environment interaction, indicating different responses of genotypes confronted with different environments. In SREG method, the two first principal components of interactions explained 75.29 percent of the interaction. The genotypes 400094, 350361 and the variety Fedearroz were found as the highest yields. According to the biplot GGE graphic the environments La Libertad and Escobal were the ones with small variations during the years of study.