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The cerebral cortex is divided into many functionally distinct areas. The emergence of these areas during neural development is dependent on the expression patterns of several genes. Along the anterior-posterior axis, gradients of Fgf8, Emx2, Pax6, Coup-tfi, and Sp8 play a particularly strong role in specifying areal identity. However, our understanding of the regulatory interactions between these genes that lead to their confinement to particular spatial patterns is currently qualitative and incomplete. We therefore used a computational model of the interactions between these five genes to determine which interactions, and combinations of interactions, occur in networks that reproduce the anterior-posterior expression patterns observed experimentally. The model treats expression levels as Boolean, reflecting the qualitative nature of the expression data currently available. We simulated gene expression patterns created by all possible networks containing the five genes of interest. We found that only of these networks were able to reproduce the experimentally observed expression patterns. These networks all lacked certain interactions and combinations of interactions including auto-regulation and inductive loops. Many higher order combinations of interactions also never appeared in networks that satisfied our criteria for good performance. While there was remarkable diversity in the structure of the networks that perform well, an analysis of the probability of each interaction gave an indication of which interactions are most likely to be present in the gene network regulating cortical area development. We found that in general, repressive interactions are much more likely than inductive ones, but that mutually repressive loops are not critical for correct network functioning. Overall, our model illuminates the design principles of the gene network regulating cortical area development, and makes novel predictions that can be tested experimentally.  相似文献   
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The healthcare of people with HIV is transitioning from specialty care to the primary healthcare (PHC) system. However, many of the performance indicators used to measure the quality of HIV care pre-date this transition. The goal of this work was to examine how existing HIV care performance indicators measure the comprehensive and longitudinal care offered in a PHC setting. A scoping review consisting of peer-reviewed and grey literature searches was performed. Two reviewers evaluated study eligibility and indicators in documents meeting inclusion criteria were extracted into a database. Indicators were matched to a PHC performance measurement framework to determine their applicability for evaluating quality of care in the PHC setting. The literature search identified 221 publications, of which 47 met inclusion criteria. 1184 indicators were extracted and removal of duplicates left 558 unique indicators. A majority of the 558 indicators fell under the ‘secondary prevention’ (12%) and ‘care of chronic conditions’ (33%) domains when indicators were matched to the PHC performance framework. Despite the imbalance, nearly all performance domains in the PHC framework were populated by at least one indicator with significant concentrations in domains such as patient-provider relationship, patient satisfaction, population and community characteristics, and access to care. Existing performance frameworks for the care of people with HIV provide a comprehensive set of indicators that align well with a PHC performance framework. Nonetheless, some important elements of care, such as patient-reported outcomes, are poorly covered by existing indicators. Advancing our understanding of how the experience of care for people with HIV is impacted by changes in health services delivery, specifically more care within the PHC system, will require performance indicators to capture this aspect of HIV care.  相似文献   
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