BackgroundMany studies have reported that hypertension is common in chronic daily headache (CDH) and its subtype chronic migraine (CM), but the reason is still poorly understood. Our clinical literature review suggested that analgesic overuse may be associated with elevated blood pressure (BP), so we performed the present study to investigate the frequency of elevated BP and its link with analgesic overuse in CDH and its subtypes.MethodsA cross-sectional study was conducted in neurology outpatients with a diagnosis of CDH according to International Headache Society criteria. CDH patients were classified into CM and non-CM groups, and subclassified with or without analgesic overuse.ResultsElevated BP was present in 27.96% of CDH patients. Compared with non-CM patients, patients with CM had a longer duration of headache and more severe pain intensity, and a family history of headache and analgesic overuse were also more common, but the elevated BP frequency was not different between the two groups. Almost one-third of the patients had analgesic overuse; 96.8% of which comprised acetaminophen-containing agents. Those with analgesic overuse had a higher frequency of headache than those without analgesic overuse in both the CM and non-CM groups.ConclusionsAlthough the CM patients had a longer duration of headache, more severe intensity, the frequency of elevated BP wasn’t higher than non-CM group. Analgesic overuses maybe the reason of higher frequency of elevated BP in CDH and its subtypes. This may have predictive value for clinicians to improve CDH management.

BackgroundAllergy involves a series of complex reactions and factors that contribute to the development of the disease and triggering of the symptoms, including rhinitis, asthma, atopic eczema, skin sensitivity, even acute and fatal anaphylactic shock. Prediction and evaluation of the potential allergenicity is of importance for safety evaluation of foods and other environment factors. Although several computational approaches for assessing the potential allergenicity of proteins have been developed, their performance and relative merits and shortcomings have not been compared systematically.ResultsTo evaluate and improve the existing methods for allergen prediction, we collected an up-to-date definitive dataset consisting of 989 known allergens and massive putative non-allergens. The three most widely used allergen computational prediction approaches including sequence-, motif- and SVM-based (Support Vector Machine) methods were systematically compared using the defined parameters and we found that SVM-based method outperformed the other two methods with higher accuracy and specificity. The sequence-based method with the criteria defined by FAO/WHO (FAO: Food and Agriculture Organization of the United Nations; WHO: World Health Organization) has higher sensitivity of over 98%, but having a low specificity. The advantage of motif-based method is the ability to visualize the key motif within the allergen. Notably, the performances of the sequence-based method defined by FAO/WHO and motif eliciting strategy could be improved by the optimization of parameters. To facilitate the allergen prediction, we integrated these three methods in a web-based application proAP, which provides the global search of the known allergens and a powerful tool for allergen predication. Flexible parameter setting and batch prediction were also implemented. The proAP can be accessed at http://gmobl.sjtu.edu.cn/proAP/main.html.ConclusionsThis study comprehensively evaluated sequence-, motif- and SVM-based computational prediction approaches for allergens and optimized their parameters to obtain better performance. These findings may provide helpful guidance for the researchers in allergen-prediction. Furthermore, we integrated these methods into a web application proAP, greatly facilitating users to do customizable allergen search and prediction.

BackgroundAllergy involves a series of complex reactions and factors that contribute to the development of the disease and triggering of the symptoms, including rhinitis, asthma, atopic eczema, skin sensitivity, even acute and fatal anaphylactic shock. Prediction and evaluation of the potential allergenicity is of importance for safety evaluation of foods and other environment factors. Although several computational approaches for assessing the potential allergenicity of proteins have been developed, their performance and relative merits and shortcomings have not been compared systematically.ResultsTo evaluate and improve the existing methods for allergen prediction, we collected an up-to-date definitive dataset consisting of 989 known allergens and massive putative non-allergens. The three most widely used allergen computational prediction approaches including sequence-, motif- and SVM-based (Support Vector Machine) methods were systematically compared using the defined parameters and we found that SVM-based method outperformed the other two methods with higher accuracy and specificity. The sequence-based method with the criteria defined by FAO/WHO (FAO: Food and Agriculture Organization of the United Nations; WHO: World Health Organization) has higher sensitivity of over 98%, but having a low specificity. The advantage of motif-based method is the ability to visualize the key motif within the allergen. Notably, the performances of the sequence-based method defined by FAO/WHO and motif eliciting strategy could be improved by the optimization of parameters. To facilitate the allergen prediction, we integrated these three methods in a web-based application proAP, which provides the global search of the known allergens and a powerful tool for allergen predication. Flexible parameter setting and batch prediction were also implemented. The proAP can be accessed at http://gmobl.sjtu.edu.cn/proAP/main.html.ConclusionsThis study comprehensively evaluated sequence-, motif- and SVM-based computational prediction approaches for allergens and optimized their parameters to obtain better performance. These findings may provide helpful guidance for the researchers in allergen-prediction. Furthermore, we integrated these methods into a web application proAP, greatly facilitating users to do customizable allergen search and prediction.

BackgroundBurkholderia cenocepacia employs both N-Acyl homoserine lactone (AHL) and cis-2-dodecenoic acid (BDSF) quorum sensing (QS) systems in regulation of bacterial virulence. It was shown recently that disruption of BDSF synthase RpfFBc caused a reduction of AHL signal production in B. cenocepacia. However, how BDSF system influences AHL system is still not clear.ResultsWe show here that BDSF system controls AHL system through a novel signaling mechanism. Null mutation of either the BDSF synthase, RpfFBc, or the BDSF receptor, RpfR, caused a substantial down-regulation of AHL signal production in B. cenocepacia strain H111. Genetic and biochemical analyses showed that BDSF system controls AHL signal production through the transcriptional regulation of the AHL synthase gene cepI by modulating the intracellular level of second messenger cyclic di-GMP (c-di-GMP). Furthermore, we show that BDSF and AHL systems have a cumulative role in the regulation of various biological functions, including swarming motility, biofilm formation and virulence factor production, and exogenous addition of either BDSF or AHL signal molecules could only partially rescue the changed phenotypes of the double deletion mutant defective in BDSF and AHL signal production.ConclusionsThese results, together with our previous findings, thus depict a molecular mechanism with which BDSF regulates AHL signal production and bacterial virulence through modulating the phosphodiesterase activity of its receptor RpfR to influence the intracellular level of c-di-GMP.

BackgroundCancer stem cells (CSCs) are thought to be capable of surviving conventional chemotherapeutic treatments because the cells have more resistant to anticancer drugs than common cancer cells. Most in vitro studies in experimental cancer cells have been done in a two-dimensional (2D) monocultures, while accumulating evidence suggests that cancer cells behave differently when they are grown within a three-dimensional (3D) culture system.ResultsThe CD44+CD117+cells isolated from human epithelial ovarian cancer SKOV-3 cell line using magnetic-activated cell sorting were found to grow faster than the SKOV-3 cells in the 3D culture and in the nude mice. Anticancer drugs 5FU, docetaxel, cisplatin, and carboplatin were seen to inhibit growth of the CD44+CD117+ cells by 50% in the 2D culture with IC50 concentration, whereas, in the 3D culture, the four drugs inhibited the cell growth by only 34.4%, 40.8%, 34.8% and 21.9% at 3D one, respectively. Effect of paclitaxel on the CD44+CD117+cell viability indicated that fewer cells underwent apoptosis in 3D culture than that in 2D one. In addition, anticancer drugs markedly increased the expression of ABCG2 and ABCB1 of CD44+CD117+cells in 3D culture.ConclusionOur assay demonstrated that human epithelial ovarian cancer CD44+CD117+cells possessed the properties of CSCs that exhibited more chemoresistance in the 3D culture than that of in 2D one. The 3D culture provides a realistic model for study of the CSC response to anticancer drugs.