Y-chromosomal STR haplotypes in a population from the Amazon region, Brazil

Haplotype and allele frequencies of the nine Y-STR (DYS19, DYS389 I, DYS389 II, DYS390, DYS391, DYS392, DYS393, DYS385 I/II) were determined in a population sample of 200 unrelated males from Belém, Brazil. The most common haplotypes are shared by 1.5% of the sample, while 186 haplotypes are unique. The haplotype diversity is 0.9995+/-0.0006. The data obtained were compared to those of other Brazilian populations. AMOVA indicates that 99.91% of all the haplotypical variation is found within geopolitical regions and only 0.09% is found among regions.     

Nucleotide variability of HV-I in Afro-descendents populations of the Brazilian Amazon Region

The analysis of genetic variation in the nucleotide sequences of mitochondrial DNA, provides unique information about the population diversity and human identification. In this study, the mitochondrial DNA sequences of the first hypervariable region (HV-I) were analyzed in 243 unrelated individuals of seven Afro-descendents populations of the Amazon Region. Sequence polymorphisms were detected using PCR and direct sequencing analysis. A total of 133 different haplotypes were found determined by 97 variable nucleotides. Each one of the three more frequent haplotypes was shared by 9 samples and 91 sequences were unique. The genetic diversity was estimated to 0.9898+/-0.0016 and the probability of two random individuals showed identical mitochondrial DNA (mtDNA) haplotypes were 1.2%.     

Discontinuity and Disaster: Gaps and the Negotiation of Culpability in Medication Delivery

This paper shows how discontinuities in the process of drug delivery enable but also underdetermine the isolation of a culprit in adverse medication events. A case example illustrates how we are forced to abandon conceptualizations of blame that assume a dichotomy (either culpable or not), and shift instead to a more nuanced version that estimates the degree to which an actor desired, generated, or could have foreseen the harmful outcome, and the extent to which constraints external to the actor altered the event. The paper concludes that meaningful safety interventions in a system as diverse, socially embedded and complex as health care delivery cannot just build on "good science" (e.g., good methods) to generate "root" causes. Rather, they need to somehow be sensitive to how and which narratives of success and failure are created, as these constrain which countermeasures are likely to be encouraged, funded, and accepted.