This study demonstrated an increase in hypertension prevalence from 1988 to 2004. Meanwhile the state of awareness remained stable but there was a significant increase in the state of treatment and control, which were in accordance with public policies and changes in antihypertensive treatment.
The effects of block copolymer molecular weight (MW) and composition on the critical micelle concentration (CMC) were studied using ionic liquids (ILs) as model solvents. Pyrene fluorescence was used to measure CMCs as a function of block MW for three polystyrene–poly(ethylene oxide) (PS–PEO) samples and three PS–poly(methyl methacrylate) (PS–PMMA) samples in 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)amide. The CMC decreased by a modest factor of 1.5 in the PS–PEO series, in which the solvophobic PS block MW remained unchanged (20 000) while the PEO block MW was decreased from 13 000 to 5000. This result correlated reasonably well with calculations from self-consistent-field (SCF) theory. A greater decrease (factor of 5) was seen in the PS–PMMA series, where the solvophobic PS block MW was varied from 3000 to 11 000 while maintaining a constant overall MW (ca. 15 000). However, this decrease was much weaker than that predicted by SCF calculations. A compilation of literature CMC data for amphiphilic block copolymers in water generally reveals a strong dependence on solvophobic block degree of polymerization N for low N, but a much weaker dependence for longer solvophobic blocks. From master plots of the compiled data, a scaling parameter shift from CMC ∼ exp(−cN) to CMC ∼ exp(−cN 1/3) was found above a critical solvophobic block N. The parameter c correlates with the χ parameter between the solvophobic block and the solvent. The weaker N dependence was found to fit the IL data very well. While such a change in MW dependence has previously been attributed to the collapse of unimer solvophobic blocks, we also discuss the potential role of kinetic limitations.
Fibroblasts are increased in AC, and they are associated with mast cell density, epithelial p53 and COX-2 expression, and actinic elastosis. Therefore, fibroblasts may contribute to lip photodamage and could be considered useful markers of early lip carcinogenesis.
Background:Hyposalivation is an objective decrease in salivary flow and it can produce xerostomia; which is a subjective sensation of dry mouth, common condition in senior population. objectives: To identify the association between xerostomia and hyposalivation and its risk factors in people aged 60 years and older, and to investigate the association with medications, habits and other oral complications. Methods: 211 participants were included. Xerostomia data was collected using a validated Spanish-Xerostomia Inventory (XI-sp). Unstimulated whole-salivary flow rates were measured to detect hyposalivation. Results were analyzed using Chi-square, Fisher tests and multivariate logistic regression analysis. p <.05. results: No significant association was detected between Xerostomia and Hyposalivation (p=.0666). Xerostomia 84.3%(p=.036) and hyposalivation 81.4%(p=.004) occur more frequently in women. A significant association was found between hyposalivation with the female gender (OR = 2.46, 95% confidence interval (CI): 1.19-5.11, p=0.015); denture stomatitis (OR=3.71, 95% CI:1.03-13.3, p=0.045) and atrophic glossitis (OR=3.72, 95% CI:1.78-8.1, p=0.001). Only female gender (OR=2.54; 95% CI:1.19-5.43, p=0.016) was significantly associated with xerostomia. conclusions: No statistically significant association was found between hyposalivation and xerostomia. A significant association was found between oral candidiasis, denture stomatitis and the atrophic tongue with hyposalivation. Being woman was a risk factor for xerostomia and hyposalivation.
ARTÍCULO ORIGINAL / ORIGINAL ARTICLE ¿Predicen los requisitos de ingreso a odontología el rendimiento académico durante primer año? Do admission requirements to dentistry predicts the academic performance over the first year?Resumen: Introducción: Al tener claridad respecto de cuáles son los predictores de desempeño académico, se puede mejorar la selección de los estudiantes que ingresan a la universidad asegurando que estén en posesión de las competencias necesarias que garanticen un buen rendimiento. Objetivos: Determinar la capacidad predictiva de los requisitos de ingreso y del proceso PSU, para el rendimiento académico de los alumnos de primer año de la carrera de odontología. Material y Método: Estudio observacional descriptivo de corte transversal con alumnos que cursaron primer año entre el 2004-2008 (inclusive). Se revisó las planillas de ingreso de la Unidad de Admisión y Registro Académico Estudiantil (UDARAE) obteniendo información referida al género, año de ingreso, promedio de notas de enseñanza media (NEM), puntaje de selección (PSU-SEL) y puntajes de las pruebas de lenguaje (PSU-L), matemáticas (PSU-M) y ciencias (PSU-C). Para el rendimiento académico se consultó las planillas de notas de la Oficina de Registro y Control de la Facultad. Resultados: El mayor porcentaje de aporte a la explicación del rendimiento académico correspondió al promedio NEM, con 10%, luego la PSU-C, con 5,6%. Las PSU-L y PSU-M arrojaron un 0% de aporte y el PSU-SEL un 23,4%. Conclusiones: La variable que más fuertemente se asocia con el rendimiento académico es el promedio NEM, seguido por la PSU-C. Tanto la PSU-L como la PSU-M presentaron una capacidad predictiva nula. El proceso PSU presentó una capacidad predictiva limitada. Introducción.Debido al carácter multidimensional del rendimiento académico, predecirlo no resulta una tarea fácil. Para Eysenck y Eysenck 1 y para Tyler 2 las capacidades predictivas, tanto de los factores intelectuales como los de de aptitud, son las de mayor importancia, ya que, para ellos, son los que mejor predicen el rendimiento futuro del alumno. En contraposición a este planteamiento, están quienes afirman que los factores intelectuales y aptitudinales son predictores pobres del rendimiento académico a largo plazo, ya que, investigaciones hechas en los últimos años, que consideraron sólo factores intelectuales, han revelado que éstos explican no más allá de un 25% en la varianza del desempeño de los estudiantes, dejando un alto porcentaje no explicado y atribuible por lo tanto a otras causas 3 . Lo anterior es avalado por Nováez 4 , quien indica que el rendimiento académico no sólo estaría ligado al concepto de aptitud sino también a factores volitivos, afectivos y emocionales, que son características internas del sujeto, que jugarían un importante rol en el desempeño académico. 15Lowman 5 afirma que para predecir el rendimiento académico es útil incluir tanto predictores de inteligencia como de motivación y personalidad.Para Artunduaga 6 las capacidades y habilidades del alumno para organi...
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