RESUMO
Plants are the source of our understanding of several fundamental biological principles. It is well known that Gregor Mendel discovered the laws of Genetics in peas and that maize was used for the discovery of transposons by Barbara McClintock. Plant models are still useful for the understanding of general key biological concepts. In this article, we will focus on discussing the recent plant studies that have shed new light on the mysterious mechanisms of meiotic crossover (CO) interference, heterochiasmy, obligatory CO, and CO homeostasis. Obligatory CO is necessary for the equilibrated segregation of homologous chromosomes during meiosis. The tight control of the different male and female CO rates (heterochiasmy) enables both the maximization and minimization of genome shuffling. An integrative model can now predict these observed aspects of CO patterning in plants. The mechanism proposed considers the Synaptonemal Complex as a canalizing structure that allows the diffusion of a class I CO limiting factor linearly on synapsed bivalents. The coarsening of this limiting factor along the SC explains the interfering spacing between COs. The model explains the observed coordinated processes between synapsis, CO interference, CO insurance, and CO homeostasis. It also easily explains heterochiasmy just considering the different male and female SC lengths. This mechanism is expected to be conserved in other species.
RESUMO
During the last decade, Chile's private health sector has experienced a dramatic increase in hospitalization rates, growing at four times the rate of ambulatory visits. Such evolution has raised concern among policy-makers. We studied the effect of ambulatory and hospital co-insurance rates on hospitalizations for ambulatory care sensitive conditions (ACSC) among individuals with private insurance in Chile. We used a large administrative dataset of private insurance claims for the period 2007-8 and a final sample of 2,792,662 individuals to estimate a structural model of two equations. The first equation was for ambulatory visits and the second for future hospitalizations for ACSC. We estimated the system by Two Stage Least Squares (2SLS) corrected by heteroskedasticity via Generalized Method of Moments (GMM) estimation. Results show that increased ambulatory visits reduced the probability of future hospitalizations, and increased ambulatory co-insurance decreased ambulatory visits for the adult population (19-65 years-old). Both findings indicate the need to reduce ambulatory co-insurance as a way to reduce hospitalizations for ACSC. Results also showed that increasing hospital co-insurance does have a statistically significant reduction on hospitalizations for the adult group, while it does not seem to have a significant effect on hospitalizations for the children (1-18 years-old) group. This paper's contribution is twofold: first, it shows how the level of co-insurance can be a determinant in avoiding unnecessary hospitalizations for certain conditions; second, it highlights the relevance for policy-making of using data on ACSC to improve the efficiency of health systems by promoting ambulatory care as well as population health.