RESUMO
DNA mixture has been a problem to be conquered for a long time in the forensic study. The DNA mixtures can be mainly divided into two categories: one comes from the sex assaults, for which we have to detect the sperms among the large amount of vaginal epithelial cells; the other one is the combination of different common samples, such as blood mixtures, salvia-blood mixtures and so on. In recent years, deeper and deeper study on DNA mixtures has led a way to objectiveness and pluralism. Novel techniques, like fluorescence- or magnetic-activated cell sorting strategies,micromanipulation and acoustic different analysis can be utilized to separate sperms in the mixtures; as for the second sort, the application of massively parallel sequencing(MPS), microfluidic droplet, whole-genome amplification, emulsion PCR(ePCR) et al. rise up the chances to detect the minor contributor in the mixtures. Furthermore, the development of both traditional and novel biomarkers which includes STR, Y-STR, SNP, DIP, Microhaplotype, DIP-STR, SNP-STR,, mtDNA-SNP and so on, provide us more analyzing choices in mixture study. The last part of the assay focuses on the latest progresses of evaluating the number of contributors, the explanation theory and calculation software.
RESUMO
Objective To establish a calculation software to determine paternity index(PI) in parentage testing and likelihood ratio (LR) in individual recognition.Methods Based on relevant industry standards and literature, using Visual Basic 6.0 to write the program.Results We successfully developed the calculation software for paternity index (PI) in parentage testing and likelihood ratio (LR) in individual recognition.Conclusion The calculation software can help staff to improve the calculation efifciency, and serve the forensic evidence.
RESUMO
With the growing number of nutrient calculation software packages on the market, there are need to compare each programs. Since each program use different nutrient datanases, the result of calculation may be different in value. In this study, we use three(A, B, C) most popular program package to compare the result of nutrient calculation. For the analysis, 24hour recall data from 97 preschool children, 66 university students and 95 aged persona were used. For the calculation if subjects gave the complete recipe, recipes from the subjects were used. Otherwise, recipe from the program database were used. Common 15 nutrients of which all program can give results, are analyzed and compared for mean nutrient intake and nutrient intake for food groups. Ten nutrients among 15 nutrients which have RDA were analyzed for % of RDA and the distribution of RDA. Mean nutrient intake of Fe, vitamin A, Na were statistically different among results of the calculation using three programs(p<0.001). The distribution of Fe, vitamin A and vitamin B2, niacin were statistically different among three results of the calculation using three program(p<0.001, p<0.05). Nutrient intakes of food groups were statistically different in cereal and products, bean and products, vegetables, fruits, fishes and shellfishes, milk and products, beverages, and seasonings(p<0.0001). It os hard to say that the difference among three program are coming from the difference from nutrient database or recipe database in this study. With these result, we conclude that it is necessary to evaluate nutrient database and recipe database as the foremost consideration in selecting nutrient calculation software. Those differences should be considered when interpreting results, comparing results with other studies, and when developing treatment plans in the clinical settings.