Abstract. Due to the increase in the prevalence and incidence of allergic diseases, improving the sensitivity and specificity of screening indexes is critical. Total immunoglobulin E (IgE) is a traditional index for judging allergic diseases, while its specificity is relatively poor. Serum-specific IgE (sIgE) is an objective index with high specificity in the diagnosis of allergic diseases. In the present research, the total IgE and sIgE of 3,721 patients with allergic diseases were analyzed to further illuminate the association between them. The data were derived from 3,721 patients. The serum-sIgE to 14 types of common allergens and total IgE were detected. A total of 2,419 cases (65.0%) of 3,721 patients exhibited increasing total IgE and 1,215 patients (32.7%) exhibited positive sIgE. The consistency rate of the two indexes was 60.4%, and the κ-value was 0.28. In 135 patients with normal total IgE, 82.2% exhibited one sIgE positive and 17.8% exhibited two or more sIgE positive. While the number of positive sIgE increased and the detecting level enhanced, the number of positive total IgE markedly increased. Patients (84.1%) with increasing total IgE were associated with positive sIgE, but the increase of total IgE could not be completely explained by the total accumulation of sIgE. Total IgE may play an important role on screening allergic disease while sIgE could be used as crucial evidence for allergy diagnosis. Although the consistency of the two methods was poor, neither total IgE nor sIgE could replace each other. Combining the two indexes with clinical manifestations together will improve the method.

Background: Peroxisome proliferator-activated receptor gamma (PPARγ) plays a critical role in protecting against distinct brain damages, including ischemia. Our previous data have shown that the protein level of PPARγ is increased in the cortex after middle cerebral artery occlusion (MCAO); PPARγ up-regulation contributes to PPARγ activation and is effective in reducing ischemic damage to brain. However, the regulatory mechanism of PPARγ after focal cerebral ischemia in rats is still unclear. In this study, we evaluated the effect of microRNA on PPARγ in rats subjected to MCAO. Methods: Focal cerebral ischemia was established by surgical middle cerebral artery occlusion; the protein level of PPARγ was detected by Western blotting; the level of microRNA-383 (miR-383) was quantified by real-time PCR; the neurological outcomes were defined by infarct volume and neurological deficits. Luciferase assay was used to identify the luciferase activities of PPARγ and miR-383. Results: We showed here that miR-383 level was down-regulated in the ischemic hemisphere of rats 24h after MCAO. Overexpression of miR-383 by miR-383 agomir increased infarct volume and aggravated neurological damage. Administration of miR-383 antagomir had the opposite effects. Furthermore, we found that PPARγ protein was down-regulated by miR-383 overexpression, and up-regulated by miR-383 inhibition both in rat model of MCAO and in primary culture cells. Finally, we found that miR-383 suppressed the luciferase activity of the vector carrying the 3'UTR of PPARγ, whereas mutation of the binding sites relived the repressive effect of miR-383. Conclusion: Our study demonstrated that miR-383 may play a key role in focal cerebral ischemia by regulating PPARγ expression at the post-transcriptional level, and miR-383 may be a potential therapeutic target for stroke.

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Peroxisome proliferator-activated receptor gamma (PPARgamma) has been shown to protect against stroke and improve neurological outcome after cerebral ischemia. This study investigated whether activation of cerebral PPARgamma improves recovery from focal cerebral ischemia by reducing expression of cyclin D1, which is associated with programmed neuron death. Focal cerebral ischemia was induced by 90 min of middle cerebral artery occlusion (MCAO), followed by reperfusion. Intracerebroventricular (i.c.v.) infusion of the PPARgamma agonist ciglitazone, beginning 5 days before and continuing through 1 day after MCAO, reduced infarct size and cyclin D1 expression in the peri-infarct cortical region. Furthermore, primary cortical neurons treated with ciglitazone showed suppressed expression of cyclin D1 in response to hypoxia-reoxygenation. This protective effect was reversed after cotreatment with the selective PPAR-gamma antagonist GW 9662 (2-chloro-5-nitrobenzanilide), clearly demonstrating the involvement of a PPARgamma-dependent mechanism. Our data provide evidence that activation of neuronal PPARgamma makes a substantial contribution to neuroprotection by preventing cyclin D1 up-regulation in vitro and in vivo.

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Support Vector Machines (SVMs) have become one of the most popular methods in MachineLearning during the last few years, but its performance mainly depends on the selection of optimal parameters which is very complex. In this study, the SCEM-UA algorithm developed by Vrugt is employed for parameters selection of Support Vector Regression (SVR). The SCEM-UA algorithm, which operates by merging the strengths of the Metropolis algorithm, controlled random search, competitive evolution, and complex shuffling, can avoid the tendency of falling into local minima. The proposed method was tested on a complicated nonlinearly runoff forecasting. The results illustrated that SCEM-UA algorithm can successfully identify the optimal parameters of SVR than grid search method, and can achieve an accurate prediction.

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