Prescription patterns for diabetes mellitus and therapeutic implications: a population-based analysis

Objective: To analyze drug prescriptions for insulin and oral antidiabetic drugs in type 1 and type 2 diabetes mellitus patients seen in the Brazilian Public Healthcare System (Unified Health System - SUS) in Ribeirao Preto, SP, Brazil. Subjects and methods: All the patients with diabetes seen in the SUS in the western district of Ribeirao Preto, SP, Brazil between March/2006 and February/2007 were included in the study. Results: A total of 3,982 patients were identified. Mean age of the patients was 60.6 years, and 61.0% were females. Sixty percent of the patients were treated with monotherapy. Doses of oral antidiabetic drugs were lower in monotherapy than in polytherapy. Ten patients received doses of glibenclamide or metformin above the recommended maximum doses, and in elderly patients there was no reduction in drug doses. Conclusion: Monotherapy with oral antidiabetic drugs was the predominant procedure, and the doses were not individualized according to age. Arq Bras Endocrinol Metab. 2012;56(2):120-7

Toll-like receptor 3: implications for proinflammatory microenvironment in human breast cancer

Under many circumstances, the host constituents that are found in the tumor microenvironment support a malignancy network and provide the cancer cells with advantages in proliferation, invasiveness and metastasis establishment at remote organs. It is known that Toll like receptors (TLRs) are expressed not only on immune cells but also on cancer cells and it has suggested a deleterious role for TLR3 in inflammatory disease. Hypothesizing that altered IFN gamma signaling may be a key mechanism of immune dysfunction common to cancer as well CXCR4 is overexpressed among breast cancer patients, the mRNA expression of TLR3, CXCR4 and IFN gamma in breast cancer tumor tissues was investigated. No statistically significant differences in the expression of CXCR4 mRNA, IFN gamma and TLR3 between healthy and tumor tissues was observed, however, it was verified a positive correlation between mRNA relative expression of TLR3 and CXCR4 (p < 0.001), and mRNA relative expression of TLR3 was significantly increased in breast cancer tumor tissue when compared to healthy mammary gland tissue among patients expressing high IFN gamma (p = 0.001). Since the tumor microenvironment plays important roles in cancer initiation, growth, progression, invasion and metastasis, it is possible to propose that an overexpression of IFN gamma mRNA due to the pro-inflammatory microenvironment can lead to an up-regulation of CXCR4 mRNA and consequently to an increased TLR3 mRNA expression even among nodal negative patients. In the future, a comprehensive study of TLR3, CXCR4 and IFN gamma axis in primary breast tumors and corresponding healthy tissues will be crucial to further understanding of the cancer network.

Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

Is production the core competence for the internationalization of emerging country firms?

The rise of new multinationals in countries like Brazil provides an opportunity to revisit and carefully construct theories of how firms internationalize, a topic on which extant theory is weak. Brazilian firms are "infant multinationals", unlike developed country firms that are "mature multinationals". They are also internationalizing in a very different global context, and can do so on the basis of different competitive advantages than multinationals that came before. Therefore, this study aims at creating subsidies for theory building about early-stage internationalization. Emerging country firms have Production competences as main competitive asset to internationalize, what reflects their competitive positioning in home markets and their entry strategy in international markets. In the case of early-entrants - Western multinationals in the 1950s and Japanese in the 1980s - the Production competence played a key role for successful internationalization. Thus, the focus of the study is the role that the Production competence plays in the internationalization of late-entrants, the emerging country multinationals. The research design considers not only the position of the headquarters but also the initiatives of the subsidiaries and the dynamic interplay between both. The paper allows a better understanding of internationalization processes and the role of Production, when firms start building their own international networks. It brings relevant insights about the paths that are being followed by emerging country multinationals, the difficulties they find, the solutions they develop. These are important inputs not only for new theory building but also for managerial practice. (C) 2012 Elsevier B.V. All rights reserved.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.