Calcifying Odontogenic Cyst Associated With Dentigerous Cyst in a 15-Year-Old Girl.

Calcifying odontogenic cyst (COC) is a rare odontogenic cyst with ameloblastic epithelial lining containing clusters of ghost cells. COCs have been described in association with several odontogenic tumors, more commonly odontomas and rarely with dentigerous cyst (DC). In this article, we describe a case of COC associated with DC in a 15-year-old girl, who presented with a swelling on the right middle third of the face, producing facial asymmetry. Panoramic radiography showed a well-circumscribed, corticated, and unilocular radiolucency at the level of the right maxillary sinus, involving 2 unerupted premolars. The lesion was enucleated and histologically revealed a COC associated with DC, which presented mucous metaplasia. Immunohistochemical reactions were performed to better illustrate this rare synchronous occurrence of COC and DC, showing positivity for CK5, CK14, CK19, and p63 in both lesions. CK18 was negative in COC, and Bcl-2 was negative in DC. Periodic acid Schiff highlighted the mucous cells in the DC lining.

[Relation of genetic variants of CYP2A6 with tobacco dependence and smoking habit in Chilean subjects. A pilot study]. / Variantes genéticas de CYP2A6 y su relación con la dependencia tabáquica y el hábito de fumar en una muestra individuos chilenos. Un estudio piloto.

BACKGROUND: Genetic and metabolic factors associated with nicotine metabolism may be related to smoking behavior. AIM: To assess the prevalence of allelic and genotype variants of CYP2A6 in a sample of Chilean subjects and to evaluate their relationship with smoking and tobacco dependence. MATERIAL AND METHODS: The genotype frequencies for *2, *3 and *4 of CYP2A6*1 (wild type) gene were determined by polymerase chain reaction (PCR) in 54 volunteers. Addiction to tobacco was evaluated using the Fagerstrom Test. The association between the presence of allelic variants of CYP2A6 and smoking and tobacco dependence was evaluated with chi square test. RESULTS: The prevalence of *1, *2 (wt/*2), *3 (wt/*3 or *31*3) and *4 (del/del) were 92.6%, 3.7%, 0% y 3.7%, respectively. No significant association was observed between being a carrier of a variant genotype of CYP2A6 and smoking or tobacco dependence. CONCLUSIONS: In this sample of Chilean individuals we did not find a relation between any CYP2A6 genotype with smoking or tobacco dependence.

Variantes genéticas de CYP2A6 y su relación con la dependencia tabáquica y el hábito de fumar en una muestra individuos chilenos: Un estudio piloto / Relation of genetic variants of CYP2A6 with tobacco dependence and smoking habit in Chilean subjects: A pilot study

Background: Genetic and metabolic factors associated with nicotine metabolism may be related to smoking behavior. Aim: To assess the prevalence of allelic and genotype variants of CYP2A6 in a sample of Chilean subjects and to evaluate their relationship with smoking and tobacco dependence. Material and Methods: The genotype frequencies for *2, *3 and *4 of CYP2A6*1 (wild type) gene were determined by polymerase chain reaction (PCR) in 54 volunteers. Addiction to tobacco was evaluated using the Fagerstrom Test. The association between the presence of allelic variants of CYP2A6 and smoking and tobacco dependence was evaluated with chi square test. Results: The prevalence of *1, *2 (wt/*2), *3 (wt/*3 or *31*3) and *4 (del/del) were 92.6%, 3.7%, 0% y 3.7%, respectively. No significant association was observed between being a carrier of a variant genotype of CYP2A6 and smoking or tobacco dependence. Conclusions: In this sample of Chilean individuals we did not find a relation between any CYP2A6 genotype with smoking or tobacco dependence.

Modelación de episodios críticos de contaminación por material particulado (PM10) en Santiago de Chile. Comparación de la eficiencia predictiva de los modelos paramétricos y no paramétricos / Modeling critical episodes of air pollution by PM10 in Santiago, Chile. Comparison of the predictive efficiency of parametric and non-parametric statistical models

Objetivo Evaluar la eficiencia predictiva de modelos estadísticos paramétricos y no paramétricos para predecir episodios críticos de contaminación por material particulado PM10 del día siguiente, que superen en Santiago de Chile la norma de calidad diaria. Una predicción adecuada de tales episodios permite a la autoridad decretar medidas restrictivas que aminoren la gravedad del episodio, y consecuentemente proteger la salud de la comunidad. Método Se trabajó con las concentraciones de material particulado PM10 registradas en una estación asociada a la red de monitorización de la calidad del aire MACAM-2, considerando 152 observaciones diarias de 14 variables, y con información meteorológica registrada durante los años 2001 a 2004. Se ajustaron modelos estadísticos paramétricos Gamma usando el paquete estadístico STATA v11, y no paramétricos usando una demo del software estadístico MARS v 2.0 distribuida por Salford-Systems. Resultados Ambos métodos de modelación presentan una alta correlación entre los valores observados y los predichos. Los modelos Gamma presentan mejores aciertos que MARS para las concentraciones de PM10 con valores <240μg/m3 para el año 2001, y los modelos MARS presentan mejores aciertos para aquellas que exceden los 240μg/m3 de PM10 para todos los años. Conclusiones Los modelos MARS son más eficientes para predecir episodios graves de alta contaminación por PM10 y posibilitan a la autoridad sanitaria adoptar restricciones preventivas que aminoren su efecto sobre la salud de la población. Esto se explicaría porque MARS corrige las variaciones de la serie a lo largo del tiempo, ajustando mejor la curva asociada a la concentración de PM10 (AU)

Objective To evaluate the predictive efficiency of two statistical models (one parametric and the other non-parametric) to predict critical episodes of air pollution exceeding daily air quality standards in Santiago, Chile by using the next day PM10 maximum 24h value. Accurate prediction of such episodes would allow restrictive measures to be applied by health authorities to reduce their seriousness and protect the community’s health. Methods We used the PM10 concentrations registered by a station of the Air Quality Monitoring Network (152 daily observations of 14 variables) and meteorological information gathered from 2001 to 2004. To construct predictive models, we fitted a parametric Gamma model using STATA v11 software and a non-parametric MARS model by using a demo version of Salford-Systems. Results Both models showed a high correlation between observed and predicted values. However, the Gamma model predicted PM10 values below 240μg/m3 more accurately than did MARS. The latter was more efficient in predicting PM10 values above 240μg/m3 throughout the study period. Conclusion MARS models are more efficient in predicting extreme PM10 values and allow health authorities to adopt preventive methods to reduce the effects of these levels on the population’s health. The reason for this greater accuracy may be that MARS models correct variations in the series over time, thus better fitting the curve associated with PM10 concentrations (AU)

[Modeling critical episodes of air pollution by PM10 in Santiago, Chile. Comparison of the predictive efficiency of parametric and non-parametric statistical models]. / Modelación de episodios críticos de contaminación por material particulado (PM10) en Santiago de Chile. Comparación de la eficiencia predictiva de los modelos paramétricos y no paramétricos.

OBJECTIVE: To evaluate the predictive efficiency of two statistical models (one parametric and the other non-parametric) to predict critical episodes of air pollution exceeding daily air quality standards in Santiago, Chile by using the next day PM10 maximum 24h value. Accurate prediction of such episodes would allow restrictive measures to be applied by health authorities to reduce their seriousness and protect the community's health. METHODS: We used the PM10 concentrations registered by a station of the Air Quality Monitoring Network (152 daily observations of 14 variables) and meteorological information gathered from 2001 to 2004. To construct predictive models, we fitted a parametric Gamma model using STATA v11 software and a non-parametric MARS model by using a demo version of Salford-Systems. RESULTS: Both models showed a high correlation between observed and predicted values. However, the Gamma model predicted PM10 values below 240 µg/m³ more accurately than did MARS. The latter was more efficient in predicting PM10 values above 240 µg/m³ throughout the study period. CONCLUSION: MARS models are more efficient in predicting extreme PM10 values and allow health authorities to adopt preventive methods to reduce the effects of these levels on the population's health. The reason for this greater accuracy may be that MARS models correct variations in the series over time, thus better fitting the curve associated with PM10 concentrations.

Polymorphism of glutathione S-transferase (GST) variants and its effect on distribution of urinary arsenic species in people exposed to low inorganic arsenic in tap water: an exploratory study.

Glutathione S-tranferases (GST) are multigenic enzymes that have been associated with arsenic metabolism. The objective of this study was to evaluate the relationship between polymorphic variants of GST and urinary concentration of arsenic species in people exposed to low levels of arsenic. A cross-sectional study among 66 nonoccupationally exposed subjects, living in the city of Antofagasta, Chile. Polymorphic variants were analyzed by polymerase chain reaction (PCR) and arsenic species was determined by atomic absorption spectrometry. The effect of GST variants on arsenic concentration was evaluated using univariate and covariate-adjusted regressions. For both GSTT1 and GSTM1 there were no significant differences in detected arsenic relative species between carriers of the active and null polymorphic variants. There was nondefinitive evidence that polymorphic variants of GST play a role in arsenic metabolism in sample of the Chilean subjects studied.