Making dentition model from negative dental impression in implant treatment / Fabricación de un modelo de dentición a partir de una impresión dental negativa para el tratamiento con implantes

In dental implant treatment or corrective surgery, a dental plaster model is produced to recognize the shape of the teeth. Understanding this dentition model is an important issue in prosthetic dentistry and craniomaxillofacial surgery. However, dental models are time consuming and costly to produce via traditional casting methods. We provide a method which makes dentition model from both a positive and a negative dental impression. Also we produce a system for making a digital dentition model using computed tomography (CT) data during the impression process. Additionally, the system allows the digital dentition model to be realized via a three-dimensional printer. The result simplifies production of the dentition model, since a physical model can be produced directly from an impression of the patient. Our system can simplify the dentition process and treatment intervention involved in making a dentition model. The digital model enables clinicians to manage the patient's cumulative data and to predict changes during the course of treatment.

En el tratamiento de implantes dentales, o cirugía correctiva, se produce un modelo de yeso dental para reconocer la forma de los dientes. La comprensión de este modelo de dentición es un tema importante en la odontología protésica y la cirugía craniomaxilofacial. Sin embargo, los modelos dentales con sumen tiempo y son costosos de producir a través de los métodos tradicionales de fundición. Proporcionamos un método que hace que el modelo de dentición sea tanto positivo como negativo. También proponemos un sistema para hacer un modelo de dentición digital utilizando datos de tomografía computarizada (TC) durante el proceso de impresión. Además, el sistema permite que el modelo de dentición digital se imprima a través de una impresora tridimensional. El resultado simplifica la producción del modelo de dentición, ya que un modelo físico puede ser producido directamente a partir de una impresión del paciente. Nuestro sistema puede simplificar el proceso de dentición y la intervención de tratamiento involucrados en la elaboración de un modelo de dentición. El modelo digital permite a los médicos manejar los datos acumulados del paciente y predecir los cambios durante el curso del tratamiento.

Single nucleotide polymorphisms in DKK3 gene are associated with prostate cancer risk and progression.

We had investigated whether sequence variants within DKK3 gene are associated with the development of prostate cancer in a Korean study cohort. We evaluated the association between 53 single nucleotide polymorphisms (SNPs) in the DKK3 gene and prostate cancer risk as well as clinical characteristics (PSA, clinical stage, pathological stage and Gleason score) in Korean men (272 prostate cancer subjects and 173 benign prostate hyperplasia subjects) using unconditional logistic regression analysis. Of the 53 SNPs and 25 common haplotypes, 5 SNPs and 4 haplotypes were associated with prostate cancer risk (P=0.02-0.04); 3 SNPs and 2 haplotypes were significantly associated with susceptibility to prostate cancer, however 2 SNPs and 2 haplotypes exhibited a significant protective effect on prostate cancer. Logistic analyses of the DKK3 gene polymorphisms with several prostate cancer related factors showed that several SNPs were significant; three SNPs and two haplotypes to PSA level, three SNPs and two haplotypes to clinical stage, nine SNPs and two haplotype to pathological stage, one SNP and one haplotypes to Gleason score. To the author's knowledge, this is the first report documenting that DKK3 polymorphisms are not only associated with prostate cancer but also related to prostate cancer-related factors.

Single nucleotide polymorphisms in DKK3 gene are associated with prostate cancer risk and progression

ABSTRACT We had investigated whether sequence variants within DKK3 gene are associated with the development of prostate cancer in a Korean study cohort. We evaluated the association between 53 single nucleotide polymorphisms (SNPs) in the DKK3 gene and prostate cancer risk as well as clinical characteristics (PSA, clinical stage, pathological stage and Gleason score) in Korean men (272 prostate cancer subjects and 173 benign prostate hyperplasia subjects) using unconditional logistic regression analysis. Of the 53 SNPs and 25 common haplotypes, 5 SNPs and 4 haplotypes were associated with prostate cancer risk (P=0.02–0.04); 3 SNPs and 2 haplotypes were significantly associated with susceptibility to prostate cancer, however 2 SNPs and 2 haplotypes exhibited a significant protective effect on prostate cancer. Logistic analyses of the DKK3 gene polymorphisms with several prostate cancer related factors showed that several SNPs were significant; three SNPs and two haplotypes to PSA level, three SNPs and two haplotypes to clinical stage, nine SNPs and two haplotype to pathological stage, one SNP and one haplotypes to Gleason score. To the author's knowledge, this is the first report documenting that DKK3 polymorphisms are not only associated with prostate cancer but also related to prostate cancer-related factors.