To determine the relationship between Helicobacter pylori infection and skin disorders, sixty six patients who suffering from skin diseases include chronic urticarial (CU) and atopic dermatitis (AD) who attended at Dermatological Clinic/ Al-Numan Teaching Hospital from the beginning of October 2015 to the end of January 2016 with age (6-62) have been investigated and compared to twenty two samples of apparently healthy individuals were studied as control group. All the studied groups were subjected to measurement of antiHelicobacter pylori IgG antibodies by enzyme linked immuno sorbent assay (ELISA) and detection of 16S rRNA and CagA genes by using singleplex and multiplex PCR methods. The results of current study revealed that there was a highly significant elevation (P<0.01) in concentration of H. pylori IgG antibodies in sera of the CU and AD patients compared with control group, also the results revealed that there was a significant elevation (P<0.05) in concentration of H. pylori IgG antibodies in sera of the CU patients compared with control group, and significant elevation (P<0.05) in concentration of H. pylori IgG antibodies in sera of AD patients compared with control group. The results of present study indicated that 26(66.67%) patients out of 39 CU patients were positive for both of 16S rRNA and CagA genes, while 13(33.33%) patients out of 39 CU patients were negative for those genes. Also, the results revealed that 19(70.37%) patients out of 27 AD patients were positive for both of 16S rRNA and CagA genes, whereas only 8(29.62%) were negative for both those genes comparing with control group which showed 1(4.54%) individuals out of 22 apparently healthy individuals were positive for both 16S rRNA and CagA genes, the statistical analysis was highly significant (P<0.01).
Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the
... Show MoreCommunity detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a
... Show MoreMigraine affects more than one billion individuals each year across the world, and is one of the most common neurologic disorders, with a high prevalence and morbidity, especially among young adults and females. Migraine is associated with a wide range of comorbidities, which range from stress and sleep disturbances to suicide. The complex and largely unclear mechanisms of migraine development have resulted in the proposal of various social and biological risk factors, such as hormonal imbalances, genetic and epigenetic influences, as well as cardiovascular, neurological, and autoimmune diseases. Experimental findings suggest an involvement of neuroinflammatory mechanisms in the pathophysiology of migraine. Specifically, preclinical
... Show MoreBackground: Both bladder cancer and schistosomiasis are endemic in Egypt. The former has a unique epidemiological pattern, which has been linked to bladder infestation by Schistosoma. The last decades have witnessed a great reduction in the infection rate of schistosomiasis and a decline in the incidence and changes in the patterns of bladder cancer. Whether these changes are linked to each other or a co-incidence is a subject of investigations.
Method: Literature on epidemiological data of bladder cancer and Schistosoma in Egypt was searched for in Medline, Scopus, PubMed, and Google Scholar. Furthermore, a hand search for literature and reports released by the Egyptian government and involved agencies was perfo
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