Private and Public Dental Care in the City of Sao Paulo in the First Decade of the XXI Century

Two concomitant movements occur in the first decade of the XXI century within the private and public dental services in Brazil: the entrance of oral health on the agenda of political priorities of the federal government and the vigorous growth of additional dental care. We analyzed the occurrence of these phenomena in the city of Sao Paulo, by seeking information in official documents and electronic databases in the Municipality of Sao Paulo, the Ministry of Health and National Health Agency (ANS), and also in scientific literature. During the studied period - January 2000 to December 2009 - and with basis on indicators such as coverage of First Consultation Program and Dental coverage Population Potential, percentages were found that characterize low public assistance and a situation far short of the constitutional principle of universal access to dental care. The growing number of beneficiaries of additional services through exclusively dental coverage insurance plans and other types of private insurance plans in the same period was significant, accounting for a major expansion of population coverage in this mode of care. It was found that, compared to the overall national framework, the city of Sao Paulo offers poor access to public dental care, with reduced supply of services to adults and aged people. Furthermore, considering the limitations of market additional services to provide dental care to all Brazilians, it reinforces the need for continuity and expansion of Brasil Sorridente, which is the programmatic expression of the National Oral Health Politics.

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE)

Abstract Background An important challenge for transcript counting methods such as Serial Analysis of Gene Expression (SAGE), "Digital Northern" or Massively Parallel Signature Sequencing (MPSS), is to carry out statistical analyses that account for the within-class variability, i.e., variability due to the intrinsic biological differences among sampled individuals of the same class, and not only variability due to technical sampling error. Results We introduce a Bayesian model that accounts for the within-class variability by means of mixture distribution. We show that the previously available approaches of aggregation in pools ("pseudo-libraries") and the Beta-Binomial model, are particular cases of the mixture model. We illustrate our method with a brain tumor vs. normal comparison using SAGE data from public databases. We show examples of tags regarded as differentially expressed with high significance if the within-class variability is ignored, but clearly not so significant if one accounts for it. Conclusion Using available information about biological replicates, one can transform a list of candidate transcripts showing differential expression to a more reliable one. Our method is freely available, under GPL/GNU copyleft, through a user friendly web-based on-line tool or as R language scripts at supplemental web-site.