Detection of human papillomavirus DNA in intraosseus ameloblastoma

Human Papillomavirus (HPV) infection has been shown as a risk factor in oral carcinogenesis. The association between HPV and benign and malignant neoplasm of oral mucosa, especially surface epithelium-derived tumors, is well established. The role of HPV in pathogenesis of odontogenic cysts and tumors has been published in few articles. The aim of this study was detection of HPV in Iranian patients with intrabony ameloblastoma and investigation of specific risk factors associated with ameloblastoma. One hundred intrabony ameloblastoma and 50 age-sex matched samples as controls were evaluated by polymerase chain reaction for the detection and typing of HPV. Fisher exact and chi square tests were used to assess the data. HPV DNA was detected in 32% of patients and 10% of controls. HPV-6 was the most prevalent genotype (31.6%) in infected cases. It was followed by HPV-11 (12.5%), HPV-16 (12.5%) and HPV-31 (3.1%). We found a significant association between presence of HPV and location of tumor (p = 0.02), traumatic history (p = 0.03) and ododontic therapy (p = 0.01). These findings indicated that HPV-6 probably is one of the most important etiologic agents in causing intraosseous ameloblastoma in Iranian population. © 2006 Academic Journals Inc., USA

INVESTIGATING THE MORTALITY CAUSES OF 1-59 MONTHS BABIES OF VILLAGE FROM 2012 TO 2015, ZAHEDAN, IRAN

Since the mortality of 1-59 babies is the most serious challenges facing human society and an important indicator of the health and development of countries, providing solutions to reduce this rate as much as possible is of paramount importance. The main objective of the present study is to examine mortality causes of 1-59 months babies in villages under the protection of Zahedan University of Medical Sciences from 2012 to 2015. The present cross-sectional study was conducted through census. The study included the death of all babies registered in Zahedan villages from 2012 to 2015. Required data was collected using raw information form and Child Health Bureau of the Ministry of Health standard questionnaire; SPSS, version 18, was used to process and analyze collected data. The present study examined the death of an overall number of 1252 Zahedan village babies aged between 1 to 59 months; 752 infants aged less than month and this age group turned out to have highest mortality rate; i.e. 60; the lowest mortality rate, 16.7, happened in the age group of 1 to 4 years. The most common causes of death included perinatal disease (29.8), unintentional injuries (17.5), respiratory system diseases (13.2), infectious and parasitic diseases (6.5), congenital and chromosome diseases (6), and cardiovascular disease (2.5). Since the highest mortality rate, 29.8, is related to perinatal diseases of infants, couples pre-pregnancy care and counselling can play crucial role in decreasing the rate of baby, and specially infants, mortality

Nearest neighbor exchange in Co- and Mn-doped ZnO

We calculate the magnetic interactions between two nearest neighbor substitutional magnetic ions (Co or Mn) in ZnO by means of density functional theory and compare it with the available experimental data. Using the local spin density approximation we find a coexistence of ferro- and antiferromagnetic couplings for ZnO:Co, in contrast to experiment. For ZnO:Mn both couplings are antiferromagnetic but deviate quantitatively from measurement. That points to the necessity to account better for the strong electron correlation at the transition ion site which we have done by applying the LSDA+U method. We show that we have to distinguish two different nearest neighbor exchange integrals for the two systems in question which are all antiferromagnetic with values between -1.0 and -2.0 meV in reasonable agreement with experiment

A probabilistic approach for pediatric epilepsy diagnosis using brain functional connectivity networks

Background The lives of half a million children in the United States are severely affected due to the alterations in their functional and mental abilities which epilepsy causes. This study aims to introduce a novel decision support system for the diagnosis of pediatric epilepsy based on scalp EEG data in a clinical environment. Methods A new time varying approach for constructing functional connectivity networks (FCNs) of 18 subjects (7 subjects from pediatric control (PC) group and 11 subjects from pediatric epilepsy (PE) group) is implemented by moving a window with overlap to split the EEG signals into a total of 445 multi-channel EEG segments (91 for PC and 354 for PE) and finding the hypothetical functional connectivity strengths among EEG channels. FCNs are then mapped into the form of undirected graphs and subjected to extraction of graph theory based features. An unsupervised labeling technique based on Gaussian mixtures model (GMM) is then used to delineate the pediatric epilepsy group from the control group. Results The study results show the existence of a statistically significant difference (p \u3c 0.0001) between the mean FCNs of PC and PE groups. The system was able to diagnose pediatric epilepsy subjects with the accuracy of 88.8% with 81.8% sensitivity and 100% specificity purely based on exploration of associations among brain cortical regions and without a priori knowledge of diagnosis. Conclusions The current study created the potential of diagnosing epilepsy without need for long EEG recording session and time-consuming visual inspection as conventionally employed

Accuracy of 54K to HD gebotype imputation in Brown Swiss cattle

Imputation of genotypes can be used to reduce the implementation costs of genomic selection. In this study, we evaluated the accuracy of genotype imputation from Illumina 54k to Illumina High Density (HD) in Brown Swiss cattle. Genotype data comprised 6,106 54k and 880 HD genotyped bulls and cows of Brown Swiss and Original Braunvieh cattle. Genotype data was checked for parentage conflicts and SNP were excluded if MAF was below 0.5% and SNP call rate was lower than 90%. The final data set included 39,004 SNP for the 54k and 627,306 SNP for the HD chip. HD genotypes of animals born between 2004 and 2008 (n=365) were masked to mimic animals genotyped with the 54k chip. Methods used for imputation were FImpute and Findhap V2. Both programs use pedigree information for imputation. The accuracy of imputation was assessed by the correlation (r) between true and imputed genotypes, the percentage of correctly and incorrectly imputed genotypes. Both programs gave high imputation accuracy with FImpute outperforming Findhap. Accuracy of imputation increased with increasing relationship between the HD genotyped reference population and 54k genotyped imputation candidates. Average r for FImpute and Findhap were 0.992 and 0.988 when both parents of the 54k genotyped candidate were HD genotyped, respectively. Correlations were lower when no direct relatives were HD genotyped (0.971 and 0.918 for FImpute and Findhap, respectively). Accuracy of imputation highly depended on MAF of the imputed SNP. For FImpute, average r ranged between 0.89 (MAF <0.025) and 0.99 (MAF between 0.4 and 0.5)

Accuracy of genotype imputation with different low density panels in Braford and Hereford cattle.

The main objective of this research was to test alternative low density SNP panels to impute Illumina 50K SNP panel genotypes in Braford and Hereford cattle. Genotypes from 3,768 Hereford, Braford and Nellore animals were used for testing imputation from low density SNP panels (3K, 6K, 8K, 15K and 20K) to the Illumina 50K SNP panel, under four different scenarios: including or not Nellore genotypes in the reference population in combination with the use or not of pedigree information. There were no significant differences in imputation accuracy among these four scenarios within each panel. However, significant differences between panels were found. The best accuracy was given by a customized 15K SNP panel, with an overall genotype concordance rate of 0.977, with 93.3% of the animals imputed with a concordance rate above 0.95. The concordance rates for the other SNP panels were 0.872, 0.952, 0.957 and 0.958 for 3K, 6K, 8K and 20K SNP panel, respectively. Therefore, in the Braford/Hereford population considered in this study, all the alternative panels denser than 3K could be used for imputing to the 50K SNP panel with an overall high imputation accuracy. However, the best results were obtained with the customized 15K SNP instead of the alternative commercial panels. The use of Nellore sire genotypes and pedigree information did not increase accuracy of imputation in this population

Genomic predictions for economically important traits in Brazilian Braford and Hereford beef cattle using true and imputed genotypes.

Genomic selection (GS) has played an important role in cattle breeding programs. However, genotyping prices are still a challenge for implementation of GS in beef cattle and there is still a lack of information about the use of low-density Single Nucleotide Polymorphisms (SNP) chip panels for genomic predictions in breeds such as Brazilian Braford and Hereford. Therefore, this study investigated the effect of using imputed genotypes in the accuracy of genomic predictions for twenty economically important traits in Brazilian Braford and Hereford beef cattle. Various scenarios composed by different percentages of animals with imputed genotypes and different sizes of the training population were compared.Article 2