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Gac. méd. Méx ; 157(3): 240-245, may.-jun. 2021. tab, graf
Article in Spanish | LILACS | ID: biblio-1346102


Resumen Introducción: La escasez de aplicaciones centradas en la persona y con vistas al desarrollo de la conciencia del riesgo que representa la pandemia de COVID-19 estimula la exploración y creación de herramientas de carácter preventivo accesibles a la población. Objetivo: Elaboración de un modelo predictivo que permita evaluar el riesgo de letalidad ante infección por el virus SARS-CoV-2. Métodos: Exploración de datos públicos de 16 000 pacientes positivos a COVID-19, para generar un modelo discriminante eficiente, valorado con una función score y que se expresa mediante un cuestionario autocalificado de interés preventivo. Resultados: Se obtuvo una función lineal útil con capacidad discriminante de 0.845; la validación interna con bootstrap y la externa, con 25 % de los pacientes de prueba, mostraron diferencias marginales. Conclusión: El modelo predictivo, basado en 15 preguntas accesibles puede convertirse en una herramienta de prevención estructurada.

Abstract Introduction: The scarcity of person-centered applications aimed at developing awareness on the risk posed by the COVID-19 pandemic, stimulates the exploration and creation of preventive tools that are accessible to the population. Objective: To develop a predictive model that allows evaluating the risk of mortality in the event of SARS-CoV-2 virus infection. Methods: Exploration of public data from 16,000 COVID-19-positive patients to generate an efficient discriminant model, evaluated with a score function and expressed by a self-rated preventive interest questionnaire. Results: A useful linear function was obtained with a discriminant capacity of 0.845; internal validation with bootstrap and external validation, with 25 % of tested patients showing marginal differences. Conclusion: The predictive model with statistical support, based on 15 accessible questions, can become a structured prevention tool.

Humans , Male , Female , Infant , Child, Preschool , Child , Adolescent , Adult , Middle Aged , Aged , Young Adult , Models, Statistical , COVID-19/prevention & control , Discriminant Analysis , Linear Models , Risk , COVID-19/mortality
Article in Chinese | WPRIM | ID: wpr-888208


Vision is an important way for human beings to interact with the outside world and obtain information. In order to research human visual behavior under different conditions, this paper uses a Gaussian mixture-hidden Markov model (GMM-HMM) to model the scanpath, and proposes a new model optimization method, time-shifting segmentation (TSS). The TSS method can highlight the characteristics of the time dimension in the scanpath, improve the pattern recognition results, and enhance the stability of the model. In this paper, a linear discriminant analysis (LDA) method is used for multi-dimensional feature pattern recognition to evaluates the rationality and the accuracy of the proposed model. Four sets of comparative trials were carried out for the model evaluation. The first group applied the GMM-HMM to model the scanpath, and the average accuracy of the classification could reach 0.507, which is greater than the opportunity probability of three classification (0.333). The second set of trial applied TSS method, and the mean accuracy of classification was raised to 0.610. The third group combined GMM-HMM with TSS method, and the mean accuracy of classification reached 0.602, which was more stable than the second model. Finally, comparing the model analysis results with the saccade amplitude (SA) characteristics analysis results, the modeling analysis method is much better than the basic information analysis method. Via analyzing the characteristics of three types of tasks, the results show that the free viewing task have higher specificity value and a higher sensitivity to the cued object search task. In summary, the application of GMM-HMM model has a good performance in scanpath pattern recognition, and the introduction of TSS method can enhance the difference of scanpath characteristics. Especially for the recognition of the scanpath of search-type tasks, the model has better advantages. And it also provides a new solution for a single state eye movement sequence.

Algorithms , Discriminant Analysis , Eye Movements , Humans , Markov Chains , Normal Distribution , Probability
Article in Chinese | WPRIM | ID: wpr-888202


Error self-detection based on error-related potentials (ErrP) is promising to improve the practicability of brain-computer interface systems. But the single trial recognition of ErrP is still a challenge that hinters the development of this technology. To assess the performance of different algorithms on decoding ErrP, this paper test four kinds of linear discriminant analysis algorithms, two kinds of support vector machines, logistic regression, and discriminative canonical pattern matching (DCPM) on two open accessed datasets. All algorithms were evaluated by their classification accuracies and their generalization ability on different sizes of training sets. The study results show that DCPM has the best performance. This study shows a comprehensive comparison of different algorithms on ErrP classification, which could give guidance for the selection of ErrP algorithm.

Algorithms , Brain , Brain-Computer Interfaces , Discriminant Analysis , Electroencephalography , Support Vector Machine
Article in Chinese | WPRIM | ID: wpr-880106


OBJECTIVE@#To observe the changes of serum metabolites in patients with multiple myeloma (MM) by metabonomics, and explore the potential biomarkers for diagnosis, prognosis, and progression of MM.@*METHODS@#Serum samples were collected from 26 patients with MM and 50 healthy controls. The data detected by liquid chromatography-mass spectrometry (LC-MS) was input into SIMCA-14.0 software for multivariate statistical analysis. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to analyze the changes of metabolites.@*RESULTS@#The metabolic change of uric acid and trans-vaccenic acid in serum samples of MM patients was 9.39 times and 2.77 times of these in healthy people, respectively, which were significantly higher than those of healthy people, and the difference was statistically significant(P<0.01).@*CONCLUSION@#Uric acid and trans-vaccenic acid are expected to be important metabolic indicators for the diagnosis, prognosis, and efficacy evaluation of MM, thus providing some clues for the pathogenesis of MM.

Biomarkers , Chromatography, Liquid , Discriminant Analysis , Humans , Mass Spectrometry , Metabolomics , Multiple Myeloma
Int. j. morphol ; 38(6): 1651-1656, Dec. 2020. tab, graf
Article in English | LILACS | ID: biblio-1134493


SUMMARY: Although molecular techniques evolved considerably in last years, anthropological methods of assessing skeletal remains, continues to be an important tool in the identification process in medico legal investigations. The objective of this study was to develop a discriminant function equation for estimating sex and stature using several measurements of lumbar vertebrae in a Thai population. We studied 150 lumbar columns (75 male and 75 female) age range of 22 to 89 years from the Forensic Osteology Research Center, Chiang Mai University, Thailand. The quantitative variables with sex were analyzed by the discriminant function analysis and that with stature were calculated using linear regression. The pixel density of the major axis of the trabecular surface of superior endplate of the first lumbar vertebra had the most accuracy in sex determination. The regression equation with quantitative variables in stature estimation described 32.3 % of the total variance with standard error of estimate of 7.736 cm. Lumbar vertebrae can be used as part of the stature and sex quantitatively and qualitatively estimating in Thais incomplete skeletal remains.

RESUMEN: Los métodos antropológicos de evaluación del esqueleto siguen siendo una herramienta importante en el proceso de identificación en las investigaciones médico-legales. El objetivo de este estudio fue desarrollar una ecuación de función discriminante para estimar el sexo y la estatura utilizando varias medidas de las vértebras lumbares en una población tailandesa. Se estudiaron 150 columnas lumbares (75 hombres y 75 mujeres) con un rango etario de 22 a 89 años del Centro de Investigación de Osteología Forense, Universidad de Chiang Mai, Tailandia. Las variables cuantitativas de sexo se analizaron mediante el análisis de función discriminante y la estatura fue calculada mediante regresión lineal. En cuanto a la determinación de sexo, la densidad de píxeles del eje mayor de superficie trabecular de la placa terminal superior de la primera vértebra lumbar fue de mayor precisión. La ecuación de regresión con variables cuantitativas en la estimación de la estatura describió el 32,3 % de la varianza total con el error estándar de estimación de 7,736 cm. Las vértebras lumbares se pueden utilizar como parte de la estatura y el sexo, estimando cuantitativa y cualitativamente los restos esqueléticos incompletos en sujetos tailandeses.

Humans , Male , Female , Adult , Middle Aged , Aged , Aged, 80 and over , Young Adult , Body Height , Sex Determination by Skeleton/methods , Lumbar Vertebrae/diagnostic imaging , Thailand , Discriminant Analysis , Linear Models , Forensic Anthropology , Lumbar Vertebrae/anatomy & histology
Acta bioquím. clín. latinoam ; 54(3): 257-266, set. 2020. graf, tab
Article in Spanish | LILACS | ID: biblio-1130600


EL HOMA-IR (homeostasis model assessment-insulin-resistance) es un estimador de insulinorresistencia (IR) pero depende de la determinación de insulina. Los índices triglicéridos-glucosa (T-G)-circunferencia de la cintura (CC) (T-G-CC) o triglicéridos-glucosa-índice de masa corporal (TG- IMC) podrían ser sustitutos. Los objetivos de este trabajo consistieron en investigar en personas con riesgo de desarrollar diabetes tipo 2 (DT2): a) los índices T-G, T-G-CC y T-G-IMC como estimadores de HOMA-IR>2,1; b) determinar su poder discriminante. Se realizó un estudio prospectivo en el que se estudiaron 223 individuos ≥45 años con riesgo de desarrollar diabetes tipo 2 (DT2). La relación T-G se calculó como ln [triglicéridos (mg/dL) x glucemia (mg/dL)/2]. La relación T-G-CC y T-G-IMC fue el producto de T-G por CC o IMC. Se utilizó análisis de regresión logística y se calcularon las áreas bajo las curvas ROC (receiver operating characteristic curves) (ABC) para comparar las asociaciones de T-G, T-G-CC y T-G-IMC con HOMA-IR>2,1. Mediante análisis discriminante se evaluó la clasificación de los sujetos entre HOMA-IR>2,1 y HOMA-IR≤2,1. ABC, sensibilidad, especificidad, poder predictivo positivo y negativo para T-G-CC y T-G-IMC fueron mayores que para T-G, con los siguientes valores de corte: T-G=8,75, T-G-CC=821 y T-G-IMC=255. Los odds ratios (OR) para HOMA-IR>2,1, ajustados para confusores, fueron: T-G>8,75, OR: 4,85 (IC 95% 2,73-8,62); T-G-CC>821, OR: 10,41 (IC 95% 5,55-19,53); T-GIMC> 255, OR: 10,41 (IC 95% 5,55-19,53). Con el análisis discriminante T-G>8,75 clasificó correctamente 69,2% individuos con HOMA-IR≤2,1 y 68,3% con HOMA-IR>2,1; T-G-CC y T-G-IMC clasificaron 74,4% y 78,2% respectivamente (p<0,001 en todos los casos). Se concluyó que T-GCC> 821 y T-G-IMC>255 fueron mejores estimadores de HOMA-IR>2,1 que T-G>8,75. Estas son determinaciones simples y accesibles y podrían ser útiles en la práctica clínica y en estudios epidemiológicos.

HOMA-IR ((homeostasis model assessment-insulin-resistance) is a surrogate estimator of insulin resistance (IR) but it depends on insulin determination. Triglyceride-glucose-waist circumference (T-G-WC) or triglyceride-glucose-body mass index (BMI) (T-G-BMI) could be substitutes. The objectives of this work were: to investigate in people at risk of developing type 2 diabetes (T2D): a) T-G, T-G-CC and T-G-BMI as estimators of HOMA-IR>2.1 and b) to determine their discriminating power. A prospective study was conducted studying 223 individuals ≥45 years of age at risk of developing type 2 diabetes (T2D). The T-G ratio was calculated as ln [triglycerides (mg/dL) x glycemia (mg/dL)/2]. The T-G-CC and T-G-BMI ratio was the product of T-G by CC or BMI. Logistic regression analysis was used and the areas under the receiver operating characteristic curves (ROC) curves were calculated to compare the associations of T-G, T-G-CC and T-G-BMI with HOMA-IR>2.1. Using a discriminant analysis, the classification of the subjects between HOMA-IR>2.1 or HOMA-IR≤2.1 was evaluated. AUC, sensitivity, specificity, positive and negative predictive powers for T-G-CC and T-G-BMI were higher than for T-G, with the following cut-off values: TG=8.75, T-G-CC=821 and T-G-BMI=255. Odds ratios (OR) for HOMA-IR>2.1, adjusted for confounders, were: T-G>8.75, OR 4.85 (95% CI 2.73-8.62); T-G-CC>821, OR 10.41 (95% CI 5.55-19.53); T-G-BMI>255, OR 10.41 (95% CI 5.55-19.53). With the discriminant analysis T-G>8.75, 69.2% correctly classified with HOMA-IR≤2.1 and 68.3% with HOMA-IR>2.1; T-G-CC and T-G-BMI correctly classified 74.4% and 78.2% respectively (p <0.001 in all cases). It is concluded that T-G-CC>821 and T-G-BMI>255 were better estimators of HOMA-IR>2.1 than T-G>8.75. T-G-WC and T-G-BMI are simple and reliable determinations and could be useful in clinical practice and epidemiological studies.

O HOMA-IR (homeostasis model assessment-insulin-resistance) e um estimador de resistencia a insulina (RI), mas depende da determinacao da insulina. Triglicerideos-glicose (T-G), circunferencia da cintura (CC) (T-G-CC) ou triglicerideos-glicose-indice de massa corporal (T-G-IMC) poderiam ser substitutos. Os objetivos desse trabalho foram investigar em pessoas com risco de desenvolver diabetes tipo 2 (DT2): a) os indices T-G, T-G-CC e T-G-IMC como estimadores de HOMA-IR> 2,1; b) determinar seu poder discriminante. Um estudo prospectivo foi realizado em 223 pessoas ≥45 anos com risco de desenvolver diabetes tipo 2 (DT2). A razao T-G foi calculada como ln [triglicerideos (mg/dL) x glicemia (mg/dL)/2]. A razao T-G-CC e T-G-IMC foi o produto de T-G por CC ou IMC. A analise de regressao logistica foi utilizada e as areas sob as curvas ROC (receiver operating features) ABC foram calculadas para comparar as associacoes de T-G, T-G-CC e T-G-IMC com HOMA-IR>2.1. Por meio de analise discriminante, avaliou-se a classificacao dos sujeitos entre HOMA-IR>2,1 e HOMA-IR≤2,1. ABC, sensibilidade, especificidade, poder preditivo positivo e negativo para TG-CC e TG-IMC foram maiores que para TG, com os seguintes valores de corte: TG=8,75, TG-CC=821 e TG-IMC=255. Odds Ratios (OR) para HOMA-IR>2,1, ajustados para fatores de confusao, foram: TG>8,75, OR 4,85 (IC95% 2,73-8,62); T-G-CC>821, OR 10,41 (IC 95% 5,55-19,53); T-G-IMC>255, OR 10,41 (IC 95% 5,55-19,53). Com a analise discriminante T-G>8,75, 69,2% foram classificados corretamente com HOMA-IR≤2,1 e 68,3% com HOMA-IR>2,1; T-G-CC e T-G-IMC classificaram 74,4% e 78,2%, respectivamente (p<0,001 em todos os casos). Conclui-se que T-G-CC>821 e TG- IMC>255 foram melhores estimadores de HOMA-IR>2,1 que T-G>8,75. Elas sao determinacoes simples e acessiveis e poderiam ser uteis na pratica clinica e em estudos epidemiologicos.

Humans , Triglycerides , Power, Psychological , Epidemiologic Studies , Logistic Models , Odds Ratio , Confounding Factors, Epidemiologic , ROC Curve , Sensitivity and Specificity , Classification , Area Under Curve , Courtship , Diabetes Mellitus, Type 2 , Diabetes Mellitus, Type 2/complications , Glucose , Goals , Insulin , Persons , Organization and Administration , Association , Blood Glucose , Insulin Resistance , Body Mass Index , Discriminant Analysis , Risk , Regression Analysis , Waist Circumference
Int. j. morphol ; 38(2): 367-373, abr. 2020. tab, graf
Article in English | LILACS | ID: biblio-1056449


Sexual dimorphism in Homo-sapiens is a phenomenon of a direct product of evolution by natural selection where evolutionary forces acted separately on the sexes which brought about the differences in appearance between male and female such as in shape and size. Advances in morphometrics have skyrocketed the rate of research on sex differences in human and other species. However, the current challenges facing 3D in the acquisition of facial data such as lack of homology, insufficient landmarks to characterize the facial shape and complex computational process for facial point digitization require further study in the domain of sex dimorphism. This study investigates sexual dimorphism in the human face with the application of Automatic Homologous Multi-points Warping (AHMW) for 3D facial landmark by building a template mesh as a reference object which is thereby applied to each of the target mesh on Stirling/ESRC dataset containing 101 subjects (male = 47, female = 54). The semi-landmarks are subjected to sliding along tangents to the curves and surfaces until the bending energy between a template and a target form is minimal. Principal Component Analysis (PCA) is used for feature selection and the features are classified using Linear Discriminant Analysis (LDA) with an accuracy of 99.01 % which demonstrates that the method is robust.

El dimorfismo sexual en el Homo-sapiens es un fenómeno directo de la evolución por selección natural, donde las fuerzas evolutivas actuaron por separado en los sexos, lo que provocó las diferencias en la apariencia entre hombres y mujeres, tal como la forma y tamaño. Los avances en el área de la morfometría, han generado un aumento significativo de las investigaciones en las diferencias de sexo en humanos y otras especies. Sin embargo, los desafíos actuales que enfrenta el 3D en el análisis de datos faciales, como la falta de homología, puntos de referencia insuficientes para caracterizar la forma facial y la complejidad del proceso computacional para la digitalización de puntos faciales, requiere un estudio adicional en el área del dimorfismo sexual. Este estudio investiga el dimorfismo sexual en el rostro humano con la aplicación de la deformación automática de múltiples puntos homólogos para el hito facial 3D, mediante la elaboración de una malla de plantilla como objeto de referencia, y se aplica en cada una de las mallas objetivas en el conjunto de datos Stirling / ESRC que contiene 101 sujetos (hombre = 47, mujer = 54). Los semi-puntos de referencia se deslizan a lo largo de las tangentes a las curvas y superficies hasta que la energía de flexión entre una plantilla y una forma objetivo es mínima. El análisis de componentes principales (PCA) se utiliza para la selección de características y las características se clasifican mediante el análisis discriminante lineal (ADL) con una precisión del 99,01 %, lo que demuestra la validez del método.

Humans , Male , Female , Sex Characteristics , Connective Tissue/anatomy & histology , Face/anatomy & histology , Discriminant Analysis , Multivariate Analysis , Connective Tissue/diagnostic imaging , Imaging, Three-Dimensional , Face/diagnostic imaging , Anatomic Landmarks
Int. j. morphol ; 38(1): 78-82, Feb. 2020. tab, graf
Article in Spanish | LILACS | ID: biblio-1056401


Dentro del espectro de conformación del cráneo, se reconocen generalmente tres amplias categorías que se corresponden con el concepto de biotipo cefálico, determinado por el Índice Cefálico. El Estos tres biotipos cefálicos son: el braquiocefálico, mesaticefálico y dolicocefálico, pero están basados en medidas lineales. A fin de revisar esta clasificación en base a su geometría, se estudiaron 53 cráneos de perros adultos, correspondientes a los tres grupos craneométricos descritos: 16 braquicéfalos, 20 mesaticéfalos y 17 dolicocéfalos. Para ello se obtuvieron fotografías en el plano ventral, en las que posteriormente se ubicaron 17 hitos anatómicos que se analizaron mediante técnicas de morfometría geométrica. De estos hitos, 5 correspondían a la zona neurocraneal y el resto al esplacnocráneo. Los tres grupos craneométricos mostraron diferencias estadísticamente significativas entre ellos tanto por el tamaño como por la forma. Las variables que contribuyeron más a explicar la diferenciación fueron las ubicadas en el margen más lateral de los arcos cigomáticos y en la base de este mismo arco. Las variables esplacnocraneales presentaban una alometría mucho más marcada que las neurocráneos. Puesto que el arco cigomático debe ser considerado como parte del esplacnocráneo, sugerimos que es tan importante el índice cefálico (que tiene en cuenta la máxima anchura de la cabeza) como el facial (que tiene en cuenta la máxima anchura de la cara). La conformación neurocraneal sería mucho más conservativa y por ende el índice craneal, de mucho menor poder discriminatorio entre grupos. El cambio entre tipos se debería a los músculos masetero y temporal, que tienen su inserción en el arco.

Within the wide conformation of skull spectrum, there are generally three recognized broad categories that correspond to the concept of cephalic biotype, determined by the cephalic index. The three cephalic biotypes are: brachiocephalic, mesaticephalic and dolichocephalic, which are based on linear measures. In order to revise this classification based on its geometry, we studied 53 skulls of adult dogs, corresponding to the three craneometric groups previously described: 16 brachycephalic, 20 mesaticephalic and 17 dolichocephalic. Images on ventral plane were obtained and 17 anatomical landmarks were subsequently located and analyzed by means of geometric morphometric techniques. Five of those landmarks corresponded to the neurocraneal area and the rest of the splanchnocranium. The three craneometric groups showed statistically significant differences between them for both size and shape. The variables that contributed to the differentiation between them were located along the edge of the zygomatic arches and on the basis of this arch. Splanchnocranial variables also presented a much more marked allometry than the neurocraneal variables. Since the zygomatic arch should be considered as part of the splanchnocranium, we suggest that the cephalic index (which takes into account the maximum width of the head) is as important as the facial index (which takes into account the maximum width of the face). The neurocraneal index would be much more conservative, and therefore less discriminatory between the groups.

Animals , Dogs , Skull/anatomy & histology , Cephalometry/methods , Dogs/anatomy & histology , Zygoma/anatomy & histology , Discriminant Analysis , Principal Component Analysis
Braz. arch. biol. technol ; 63(spe): e20190489, 2020. tab, graf
Article in English | LILACS | ID: biblio-1142502


Abstract The soil tillage practiced over a long period of time impacts soil quality. The first step in soil quality assessment is to select which indicators should be used. The objective of this study was to identify the soil attributes that discriminate soil tillage systems and can be used as indicators for soil quality assessments. Sixteen soil physical and chemical attributes were evaluated: macroporosity (MaP), microporosity (MiP), total porosity (TP), bulk density (BD), field-saturated hydraulic conductivity (Kfs), soil resistance to penetration (SRP), pH (H2O), pH (CaCl2), aluminium (Al), calcium (Ca), magnesium (Mg), potassium (K), available phosphorus (P), total organic carbon (TOC), cation exchange capacity (CEC) and base saturation (BS), of a very clayey Red Latosol, cultivated for a long period in no-till (NT), conventional tillage (CT) and minimum tillage (MT). The soil attributes (indicators) were selected using canonical discriminant analysis. MiP, Kfs, pH (CaCl2), Ca, Mg, CEC e BS were the most efficient indicators to discriminate soil tillage systems. In the indicator interpretation step was sustained MiP as the indicator that represents the function of physical stability and support, Kfs as the indicator that represents the function of water relations, BS as the indicator that represents the function of nutrient cycling and pH (CaCl2) as the indicator that represents the function of filtering and buffering. These indicators can be used for future soil quality assessment and monitoring of tillage systems in similar regions and conditions.

Soil Quality , Soil Characteristics/statistics & numerical data , Indicators (Statistics) , Discriminant Analysis , Soil Characteristics/classification , Elements
Article in Chinese | WPRIM | ID: wpr-828424


Resin-containing drugs in Dracaena from four different appearances were analyzed by headspace sampling-gas chromatography-mass spectrometry(HS-GC-MS) metabolomics technique and hierarchical clustering analysis(HCA) chemometrics method. This study was to analyze differential volatile components in resin-containing drugs in Dracaena from different appearance and metabolic pathways. The results of partial least squares discriminant analysis(PLS-DA) and HCA analysis indicated that there was little difference in volatile components between fiber-rich sample and hollow cork cambium sample, however, the volatile components in the two samples compared with whole body resin-containing sample and resin-secreting aggregated sample had a large metabolic difference. Twenty differential metabolites were screened by VIP and P values of PLS-DA. The content of these differential metabolites was significantly higher in whole body resin-containing sample and resin-secreting aggregated sample than in fiber-rich sample and hollow cork cambium sample. Sixteen significant metabolic pathways were obtained through enrichment analysis(P<0.05), mainly involved in terpenoids biosynthesis and phenylpropanoid metabolism. This result provided a reference for further study of resin formation mechanism of resin-containing drugs in Dracaena from different appearances. At the same time, it also provided a reference for establishing a multi-index quality evaluation system.

Cluster Analysis , Discriminant Analysis , Dracaena , Gas Chromatography-Mass Spectrometry , Resins, Plant
Article in Chinese | WPRIM | ID: wpr-827971


The purpose of this article is to study the degradation of chemical compositions after the silkworm excrement being expelled from the silkworm, and to determine its main metabolic compositions and their changing relationships. This research is based on UPLC-Q-TOF-MS technology. Based on the systematic analysis of the main chemical compositions contained in silkworm excrement, the principal compositions analysis(PCA) and partial least squares discriminant analysis(OPLS-DA) on commercial silkworm excrement and fresh silkworm excrement were analyzed for differences. The S-plot chart of OPLS-DA was used to select and identify the chemical compositions that contributed significantly to the difference. At the same time, the relative peak areas of the different compositions were extracted by Masslynx to obtain the relative content of different compositions in fresh silkworm excrement. The results showed that there was a significant difference in the chemical compositions between fresh silkworm excrement and commercial silkworm excrement. The difference compositions were mainly flavonoid glycosides and Diels-Alder type composition, and two types of compounds are degradated during the storage of silkworm sand. In this study, the chemical compositions of fresh silkworm excrement were systematically identified and analyzed for the first time by mass spectrometry, and it was found that some chemical compositions of silkworm excrement were degradated with time during storage.

Animals , Bombyx , Chromatography, High Pressure Liquid , Discriminant Analysis , Drugs, Chinese Herbal , Mass Spectrometry
Rev. argent. microbiol ; 51(4): 359-362, dic. 2019. graf
Article in English | LILACS | ID: biblio-1057401


Abstract Listeria monocytogenes is a foodborne pathogen. The recent alert for L. monocytogenes in vegetables from Argentina warns about the importance of reinforcing its isolation, characterization and subtyping in food, clinical and environmental samples. The aim of the present study was to compare the discriminatory power of enterobacterial repetitive interpower; genic consensus polymerase chain reaction (ERIC-PCR), automated ribotyping and pulsed-field gel electrophoresis (PFGE) to subtype strains of L. monocytogenes isolated from Argentine meat and environmental samples. Simpson's Diversity Index (DI) was calculated on the basis of based on the dendrograms obtained in the by cluster analysis, showing the following discriminatory power: ApaI-PFGE (0.980), AscI-PFGE (0.966), ribotyping (0.912), ERIC-PCR (0.886). The ID values between ApaI- and AscI-PFGE and between ribotyping and ERIC-PCR were not significantly different. Of the three techniques evaluated, PFGE showed the highest discriminatory power. However, the subtyping techniques should be accompanied by effective food monitoring strategies and reliable clinical and epidemiological studies.

Resumen Listeria monocytogenes es un patógeno alimentario. La reciente alerta por la presencia de L. monocytogenes en vegetales en Argentina advierte sobre la importancia de reforzar el aislamiento, la caracterización y la subtipificación de esta bacteria en muestras clínicas de alimentos y ambientales. El objetivo del presente estudio fue comparar el poder discriminatorio de enterobacterial repetitive intergenic consensus polymerase chain reaction (ERIC-PCR), la ribotipificación automatizada y la pulsed-field gel electrophoresis (PFGE) para subtipificar cepas de L. monocytogenes aisladas de carne y de muestras ambientales en Argentina. El índice de diversidad (ID) de Simpson, calculado a partir de los dendrogramas obtenidos en el análisis de agrupamiento, mostró los siguientes resultados: Apal-PFGE (0,980), AscI-PFGE (0,966), riboti-pado (0,912), ERIC-PCR (0,886). Los valores obtenidos no fueron significativamente diferentes al comparar entre Apal- y AscI-PFGE, ni entre ribotipadoy ERIC-PCR. De las técnicas evaluadas, la PFGE presentó el mayor poder discriminatorio. Sin embargo, las técnicas de subtipificación deberían acompañarse de estrategias de control de los alimentos efectivas y de estudios clínicos y epidemiológicos confiables.

Bacterial Typing Techniques/methods , Listeria monocytogenes/classification , Discriminant Analysis , Ribotyping/methods , Listeria monocytogenes/isolation & purification
Rev. cuba. obstet. ginecol ; 45(4): e496, oct.-dic. 2019. tab, graf
Article in Spanish | LILACS, CUMED | ID: biblio-1126710


RESUMEN Introducción: La preeclampsia es uno de los síndromes en mujeres embarazadas que afecta al menos 3 - 8 por ciento de todos los embarazos. Objetivo: Desarrollar un modelo predictivo de preeclampsia a partir del estado redox en embarazadas, que clasifique a las mujeres pertenecientes a los grupos de gestantes preeclámpticas y gestantes sanas. Métodos: Se realizó un estudio analítico transversal. Los parámetros bioquímicos y clínicos se evaluaron utilizando el análisis de componentes principales para identificar las variables más influyentes en la aparición de preeclampsia. Los seleccionados como las variables más importantes fueron evaluados por el análisis discriminante lineal de Fisher. Resultados: El análisis de componentes principales determinó la varianza del set de datos, mostrando la relación con los procesos de peroxidación lipídica, metabolismo de proteínas, daño a tejidos y microangiopático, considerados factores en la fisiopatología de la preeclampsia. Las variables más influyentes fueron usadas para modelar una función discriminante capaz de clasificar gestantes sanas y preeclámpticas. El valor de Lambda de Wilks y el alto autovalor asociado a la función discriminante muestran el poder discriminante del modelo. La ecuación obtenida fue validada con el método Leave one out y reveló un excelente poder clasificatorio del mismo. Conclusiones: El modelo predictivo puede ser considerado como apropiado para clasificar los casos de preeclampsia, y muestran a los biomarcadores como buenos candidatos para la clasificación y como potenciales indicadores predictivos de preeclampsia(AU)

ABSTRACT Introduction: Preeclampsia is one of the syndromes in pregnant women that affects at least 3 - 8 percent of all pregnancies. Objective: To develop a predictive model of preeclampsia from the redox state in pregnant women, which allows to classify them in groups of preeclamptic pregnant women and healthy pregnant women. Methods: A cross-sectional analytical study was performed. Biochemical and clinical parameters were evaluated using principal component analysis to identify the most influential variables in the occurrence of preeclampsia. Those selected as the most important variables were evaluated by Fisher's linear discriminant analysis. Results: The main component analysis determined the variance of the data set, showing the relationship with lipid peroxidation processes, protein metabolism, tissue damage and microangiopathy, considered factors in the pathophysiology of preeclampsia. The most influential variables were used to model a discriminant function capable of classifying healthy and preeclamptic pregnant women. Wilks Lambda value and the high eigenvalue associated with the discriminant function show the discriminant power of the model. The equation obtained was validated with the Leave one out method and revealed excellent classifying power. Conclusions: The predictive model can be considered as appropriate to classify pre-eclampsia cases, and to show biomarkers as good candidates for classification and as potential predictive indicators of pre-eclampsia(AU)

Humans , Female , Pregnancy , Pre-Eclampsia/diagnosis , Discriminant Analysis , Lipid Peroxidation , Cross-Sectional Studies
Int. j. morphol ; 37(4): 1375-1381, Dec. 2019. tab, graf
Article in English | LILACS | ID: biblio-1040140


Determining sex may be more difficult in cases such as natural disasters, accidents or situations in which bodies are subjected to high temperatures, when individuals must be identified from their remains. The mandible is a very strong bone, presents high sexual dimorphism and may be useful in forensic identification. The object of the present study was to determine sex by metrical analysis of macerated mandibles of Brazilian adults. We analysed 113 fully dentate macerated mandibles of Brazilian adults, 47 belonging to women and 66 to men. We took 8 measurements using a digital calliper: bicondilar breadth (BC), bigonial breadth (BG), bimental foramina breadth (BM), distance between mental foramen and mandibular base (MF-MB), mandibular ramus height (MRH), maximum mandibular ramus breadth (MaRB), minimum mandibular ramus breadth (MiRB) and mandibular body length (MBL). The t test was used for statistical analysis of independent samples, and a ROC curve was constructed. Direct and stepwise discriminant analysis was carried out. SPSS v.22 software was used, with a significance threshold of 5 %. We observed that all the measurements presented statistically significant differences between the sexes, with greater mean values for men than for women. BG was the measurement which presented the greatest area under curve (AUC), and the highest correct prediction, followed by MRH and BC. The BM distance presented the smallest AUC and lowest correct prediction. The mean correct prediction was 85 % for direct discriminant analysis and 83.2 % for stepwise discriminant analysis, using the BG and MRH measurements. The measurements analysed in this study can be used to determine the sex of Brazilian individuals.

En casos de desastres naturales, catástrofes o situaciones en las cuales los cuerpos son sometidos a altas temperaturas la identificación sexual queda más difícil, siendo necesaria la identificación de los individuos a partir de restos mortales. La mandíbula es un hueso muy resistente, que presenta gran dimorfismo sexual, pudiendo ser útil en la identificación forense. El objetivo de este estudio fue determinar la predicción sexual mediante el análisis métrico de mandíbulas maceradas de individuos brasileños adultos. Fueron analizadas 113 mandíbulas maceradas completamente dentadas de Brasileños adultos, siendo 47 mujeres y 66 hombres. Con un cáliper digital fueron evaluadas 8 medidas: amplitud bi-condilar (BC), amplitud bi-gonial (BG), amplitud entre forámenes mentonianos (BM), distancia entre el foramen mentoniano y la base de la mandíbula (MF-MB), altura de la rama mandibular (MRH), anchura máxima de la rama mandibular (MaRB), anchura mínima de la rama mandibular (MiRB) y longitud del cuerpo de la mandíbula (MBL). Para análisis estadístico se utilizó la prueba t para muestras independientes. Además se construyó una curva ROC. Se realizó análisis discriminante directo y por pasos. Se utilizó el software SPSS V.22, considerando umbral de significación de 5 %. Se observó que todas las medidas presentaron diferencias estadísticas entre sexos, siendo los valores medios encontrados para hombres mayores que los encontrados para mujeres. La BG fue la medida que presentó mayor área bajo la curva (AUC) y mayor predicción, seguido de la MRH y de la BC. La distancia BM fue la medida que presentó la menor AUC y menor predicción. La correcta predicción para el análisis discriminante directo alcanzó el 85 % y por pasos alcanzó el 83.2 % utilizándose las medidas BG y MRH. Las medidas analizadas en este estudio pueden ser utilizadas en el diagnóstico sexual de individuos Brasileños.

Humans , Male , Female , Sex Determination by Skeleton/methods , Mandible/anatomy & histology , Brazil , Discriminant Analysis , ROC Curve
Actual. psicol. (Impr.) ; 33(126): 32-49, ene.-jun. 2019. tab, graf
Article in Spanish | LILACS, INDEXPSI, SaludCR | ID: biblio-1088572


Resumen Objetivo. Analizar el posicionamiento de estudiantes y no estudiantes frente a las cuotas raciales en las universidades públicas brasileñas, así como las justificaciones para ese posicionamiento. Además, investigar los niveles de prejuicio existentes entre los participantes y la relación entre su color de piel y sus posicionamientos frente a esas cuotas. Participantes. 83 estudiantes y 63 no estudiantes. Los resultados demostraron que los no estudiantes se perciben más prejuiciosos y un 74% de los participantes son favorables a las cuotas, siendo los autodeclarados negros los que indicaron mayor concordancia. El análisis léxico demostró que los estudiantes anclan sus posicionamientos en principios meritocráticos, mientras que los no universitarios anclan en principios igualitarios, reflejando la forma en cómo estos grupos construyen simbólicamente el significado de las cuotas raciales a partir de sus pertenencias sociales.

Abstract This work aimed at analyzing the positioning of students and non-students about racial quotas in the Brazilian public universities and the justifications for that positioning. We also investigated the levels of prejudice existing among the participants and the relationship between their skin color and their positions about those quotas. The participants were 83 students and 63 non-students. The results showed that non-students perceive themselves as more prejudiced and 74% of the them were favorable to the quotas, being the self-declared black those that indicated greater agreement. The lexical analysis showed that students anchor their positions in meritocratic principles, while non-students anchor on egalitarian principles, reflecting the way in which these groups symbolically construct the meaning of racial quotas based on their group memberships.

Humans , Male , Female , Adult , Students/psychology , Universities , Brazil , Racism/psychology , Social Discrimination/psychology , Discriminant Analysis
São Paulo; s.n; s.n; 2019. 109 p. ilus, graf, tab.
Thesis in Portuguese | LILACS | ID: biblio-1007572


A qualidade microbiológica de medicamentos é fundamental para garantir sua eficácia e segurança. Os métodos convencionais para identificação microbiana em produtos não estéreis são amplamente utilizados, entretanto são demorados e trabalhosos. O objetivo deste trabalho é desenvolver método microbiológico rápido (MMR) para a identificação de contaminantes em produtos farmacêuticos utilizando a espectrofotometria de infravermelho com transformada de Fourier com reflectância total atenuada (FTIR-ATR). Análise de componentes principais (PCA) e análise de discriminantes (LDA) foram utilizadas para obter um modelo de predição com a capacidade de diferenciar o crescimento de oriundo de contaminação por Bacillus subtilis (ATCC 6633), Candida albicans (ATCC 10231), Enterococcus faecium (ATCC 8459), Escherichia coli (ATCC 8739), Micrococcus luteus (ATCC 10240), Pseudomonas aeruginosa (ATCC 9027), Salmonella Typhimurium (ATCC 14028), Staphylococcus aureus (ATCC 6538) e Staphylococcus epidermidis (ATCC 12228). Os espectros de FTIR-ATR forneceram informações quanto à composição de proteínas, DNA/RNA, lipídeos e carboidratos provenientes do crescimento microbiano. As identificações microbianas fornecidas pelo modelo PCA/LDA baseado no método FTIR-ATR foram compatíveis com aquelas obtidas pelos métodos microbiológicos convencionais. O método de identificação microbiana rápida por FTIR-ATR foi validado quanto à sensibilidade (93,5%), especificidade (83,3%) e limite de detecção (17-23 UFC/mL de amostra). Portanto, o MMR proposto neste trabalho pode ser usado para fornecer uma identificação rápida de contaminantes microbianos em produtos farmacêuticos

Microbiological quality of pharmaceuticals is fundamental in ensuring efficacy and safety of medicines. Conventional methods for microbial identification in non-sterile drugs are widely used, however are time-consuming and laborious. The aim of this paper was to develop a rapid microbiological method (RMM) for identification of contaminants in pharmaceutical products using Fourier transform infrared with attenuated total reflectance spectrometry (FTIR-ATR). Principal components analysis (PCA) and linear discriminant analysis (LDA) were used to obtain a predictive model with capable to distinguish Bacillus subtilis (ATCC 6633), Candida albicans (ATCC 10231), Enterococcus faecium (ATCC 8459), Escherichia coli (ATCC 8739), Micrococcus luteus (ATCC 10240), Pseudomonas aeruginosa (ATCC 9027), Salmonella Typhimurium (ATCC 14028), Staphylococcus aureus (ATCC 6538), and Staphylococcus epidermidis (ATCC 12228) microbial growth. FTIR-ATR spectra provide information of protein, DNA/RNA, lipids, and carbohydrates constitution of microbial growth. Microbial identification provided by PCA/LDA based on FTIR-ATR method were compatible to those obtained using conventional microbiological methods. FTIR-ATR method for rapid identification of microbial contaminants in pharmaceutical products was validated by assessing the sensitivity (93.5%), specificity (83.3%), and limit of detection (17-23 CFU/mL of sample). Therefore, the RMM proposed in this work may be used to provide a rapid identification of microbial contaminants in pharmaceutical products

Pharmaceutical Preparations/analysis , Discriminant Analysis , Pharmaceutical Preparations/metabolism , Spectroscopy, Fourier Transform Infrared/instrumentation
Article in English | WPRIM | ID: wpr-759875


The biological profile of a person is crucial in the forensic anthropology casework; and sexual dimorphism of the index and ring fingers makes them a vital tool for sex prediction. This study was undertaken to predict the sex of an individual from the index and ring finger lengths, and index-ring finger length ratio in the Ukwuani of Nigeria. It was a cross-sectional study involving all the indigenous Ukwuani secondary school students and members of staff within Ukwuani local government area that utilized 200 male and 200 female adolescents and 68 male and 83 female adults based on the systematic random sampling technique. The index and ring finger lengths were measured and the index:ring finger ratio calculated. Data were analyzed using SPSS statistics version 23.0. P<0.05 was considered statistically significant. Statistics used were mean, standard deviation, t test, Pearson's correlation, and discriminant function analysis. Males showed statistically longer absolute finger lengths than females. The left index:ring finger ratio in adolescents was significantly greater in females than males, but the others were not. There were significant paired sample correlations in both age groups. There was no significant correlation between age and finger lengths, and ratios. The overall accuracy of the discriminant functions was higher and better for the finger lengths than for the finger ratios that were moderate. This study showed that the index and ring finger lengths can be used as tools to predict the sex of an individual using the discriminant function analysis in a medico-legal situation.

Adolescent , Adult , Cross-Sectional Studies , Discriminant Analysis , Female , Fingers , Forensic Anthropology , Humans , Local Government , Male , Nigeria , Sexism
Article in Chinese | WPRIM | ID: wpr-774174


Individual differences of P300 potentials lead to that a large amount of training data must be collected to construct pattern recognition models in P300-based brain-computer interface system, which may cause subjects' fatigue and degrade the system performance. TrAdaBoost is a method that transfers the knowledge from source area to target area, which improves learning effect in the target area. Our research purposed a TrAdaBoost-based linear discriminant analysis and a TrAdaBoost-based support vector machine to recognize the P300 potentials across multiple subjects. This method first trains two kinds of classifiers separately by using the data deriving from a small amount of data from same subject and a large amount of data from different subjects. Then it combines all the classifiers with different weights. Compared with traditional training methods that use only a small amount of data from same subject or mixed different subjects' data to directly train, our algorithm improved the accuracies by 19.56% and 22.25% respectively, and improved the information transfer rate of 14.69 bits/min and 15.76 bits/min respectively. The results indicate that the TrAdaBoost-based method has the potential to enhance the generalization ability of brain-computer interface on the individual differences.

Algorithms , Brain-Computer Interfaces , Discriminant Analysis , Electroencephalography , Event-Related Potentials, P300 , Humans , Support Vector Machine
Article in English | WPRIM | ID: wpr-773978


OBJECTIVE@#To investigate the effects of Pinggan Prescription (, PGP) on hypertension by the associated methods of metabonomic and pharmacodynamic.@*METHODS@#A total of 32 male spontaneously hypertensive rats (SHRs) were randomly divided into two groups by using the random number table method: a treatment group (n=18) and a model group (n=14). The Wistar rats (n=14) were used as the normal group. Different prescription were used to intervene three groups: the treatment group in which PGP extract was administered orally at a dose of 18.336 g/kg (PGP/body weight), and the model group in which physiological saline was administered at the equivalent dose. The same treatment was applied to the normal group as the model group. The blood pressure was measured by tail-cuff method, and pharmacodynamic indexes including cyclic adenosine monophosphate (cAMP) and angiotensin II (Ang II) were tested by enzyme-linked immunosorbent assay. The plasma samples from three groups were detected by gas chromatography-mass spectrometry (GC-MS).@*RESULTS@#Compared with the model group, blood pressure of treatment group was obviously reduced after continuous curing with PGP (P<0.01). The pharmacodynamic results illustrated that the content of Ang II increased with the raised blood pressure and the cAMP expressed the converse trend. After curing with PGP, the content of Ang II decreased, the difference between model group and treatment group was significant (P<0.01), and the cAMP expressed the converse trend. Five potential biomarkers were identified, including arachidonic acid, hexadecanoic acid, elaidic acid, octadecanedioic acid and 9,12-octadecadienoic acid. These metabolites had shown significantly changes as followed: arachidonic acid, hexadecanoic acid and elaidic acid were significantly higher and octadecanedioic acid and 9,12-octadecadienoic acid were lowered in the model group than those in the normal group. After the treatment of PGP, the metabolites had the trends of returning to normal along with the reduced blood pressure.@*CONCLUSIONS@#PGP intervention for hypertension played a major role in the metabolism of arachidonic acid and linoleic acid. Metabonomic with pharmacodynamic methods could be potentially powerful tools to investigate the mechanism of Chinese medicine.

Animals , Biomarkers , Blood , Discriminant Analysis , Drugs, Chinese Herbal , Pharmacology , Gas Chromatography-Mass Spectrometry , Hypertension , Blood , Drug Therapy , Least-Squares Analysis , Male , Metabolic Networks and Pathways , Metabolomics , Models, Biological , Principal Component Analysis , Rats, Inbred SHR , Rats, Wistar
The Korean Journal of Pain ; : 120-128, 2019.
Article in English | WPRIM | ID: wpr-761685


BACKGROUND: We aimed to explore the American College of Rheumatology (ACR) 1990 and 2011 fibromyalgia (FM) classification criteria’s items and the components of Fibromyalgia Impact Questionnaire (FIQ) to identify features best discriminating FM features. Finally, we developed a combined FM diagnostic (C-FM) model using the FM’s key features. METHODS: The means and frequency on tender points (TPs), ACR 2011 components and FIQ items were calculated in the FM and non-FM (osteoarthritis [OA] and non-OA) patients. Then, two-step multiple logistic regression analysis was performed to order these variables according to their maximal statistical contribution in predicting group membership. Partial correlations assessed their unique contribution, and two-group discriminant analysis provided a classification table. Using receiver operator characteristic analyses, we determined the sensitivity and specificity of the final model. RESULTS: A total of 172 patients with FM, 75 with OA and 21 with periarthritis or regional pain syndromes were enrolled. Two steps multiple logistic regression analysis identified 8 key features of FM which accounted for 64.8% of variance associated with FM group membership: lateral epicondyle TP with variance percentages (36.9%), neck pain (14.5%), fatigue (4.7%), insomnia (3%), upper back pain (2.2%), shoulder pain (1.5%), gluteal TP (1.2%), and FIQ fatigue (0.9%). The C-FM model demonstrated a 91.4% correct classification rate, 91.9% for sensitivity and 91.7% for specificity. CONCLUSIONS: The C-FM model can accurately detect FM patients among other pain disorders. Re-inclusion of TPs along with saving of FM main symptoms in the C-FM model is a unique feature of this model.

Back Pain , Chronic Pain , Classification , Discriminant Analysis , Fatigue , Fibromyalgia , Humans , Logistic Models , Neck Pain , Osteoarthritis , Periarthritis , Rheumatology , Sensitivity and Specificity , Shoulder Pain , Sleep Initiation and Maintenance Disorders