Jorjani Biomedicine Journal
Volume:5 Issue: 2, 2018

Gastroenteritis is one of the most common Salmonella infections in human which is caused by Salmonella serotypes especially S.enteritidis and S.typhimurium. The spread of multi-drug resistant (MDR) Salmonella strains is a serious global issue. Obtaining integrons is considered as one of the most important factors in multi-drug resistance among gram-negative microorganisms, particularly in intestinal bacteria. The aim of this study was to investigate the molecular level of class 1, 2 and 3 integrons which are the most important integrons in Salmonella enteritidis isolated from patients using Multiplex PCR.
In this study, 567 stool and blood samples were collected from patients with acute gastroenteritis and Salmonella enteritidis were detected using culture method, standard biochemical test, and PCR. After DNA extraction, the presence of class 1, 2, and 3 of integrons was analyzed by multiplex PCR.
From 567 samples, 48 strains were identified as Salmonella enteritidis. Of all 48 strains, 45 strains (95%) had the intI gene, 7 strains (14.5%) had the intII gene, and 2 strains (4%) had the intIII gene.
In this study, high incidence of class 1, 2 and 3 integrons was detected. Screening integrons as a sign of obtaining and expansion of antibiotic resistance could be considered as an important mechanism to deal with antibiotic resistance in microorganisms.

The fair distribution of medical specialists among the population of a country is one of the requirements for the public health. We aimed to investigating the distribution of medical specialists using Gini coefficient in all governmental hospitals in two medical universities of Golestan (15 hospitals) and Mazandaran (23 hospitals) provinces.
The present practical study was conducted using descriptive and analytical methods. The research data including the number of physicians, population and number of active beds in each city and province were obtained from the deputy of treatment of medical universities in each province. The Lorenz curve and the Gini coefficient were used to analyze the distribution of specialists using Excel software. T-test was used to compare the Gini coefficients between the two provinces. Multiple regression tests were performed using SPSS software version 16 to investigate the relationship between variables.
The results showed that Gini coefficients on the basis of population in Mazandaran province were within optimum limit (less than 0.2). However, Gini coefficients on the basis of population in Golestan province were undesirable (more than 0.2) and there was also an inequality in the Gini coefficients based on the number of population between the two provinces of Golestan and Mazandaran (P=0.000, t=17.89).
According to the findings, the distribution of specialist physicians is desirable in Mazandaran province based on population. However, there was inequality in the distribution of specialist physicians in Golestan province. The accurate and fair estimation of the required human resources and the distribution on the basis of population and required indicators could lead to a reduction in the cost of treatment for families and better efficiency of health resources.

Migration, in any forms and by any motivations or outcomes, as a demographic phenomenon, has various cultural and socio-economic effects on local, regional, national and international levels. On the other hand, fertility plays an important role in health and population studies and researchers have examined its changes and trends in various aspects. The aim of this research was modeling the mean number of children ever born (CEB) for women who have left their cities or villages and migrated to Tehran city using regression tree model.
Data was obtained from 2% of raw data from the census of 2011 and analyzed by regression tree model. Tree models are nonparametric statistical techniques which do not need complicated and unreachable assumptions of traditional parametric ones and have a considerable accuracy of modeling. These models are associated with simple interpretation of results. Therefore, they have been used by researches in many fields such as social sciences.
Age, educational level, job status, cause of migration, internet use for urban migrant women and age for rural migrant women were assumed as influential covariates in predicting the mean number of CEB.
Regression tree findings revealed that urban migrants who were in higher age groups, lower educational levels, unemployed and have not used internet have had more mean number of CEBs.

Poisonings are of the major public health challenges. Non-medicinal poisonings are of the most common types and causes of referring to medical centers worldwide. The present study was aimed to determine the non-medicinal poisonings pattern in adults of Gorgan city.
The present cross-sectional study was conducted on all non-medicinal poisoned patients referred to the 5Azar hospital from 2008 – 2015. Data were collected on checklists using census data collection method and were analyzed by Stata 11.0 software using Pearson’s Chi- square test.
Of all 800 admitted poisoning cases, 227 individuals were non-medicinal and mostly male (72.7%). The ages of 34.4 % of cases were between 20 and 29 years. Moreover, 68.7% of all cases were living in urban areas, 57.7% were married and 27.8% were educated up to high school. Poisonings mostly occurred during summer (30%) and intentional (suicidal) poisonings were known as the major form (47.1%). Opium and aluminum phosphide were the most important poisoning agents (54.2%). Finally, 29 patients (12.8%) had passed away where aluminum phosphide poisoning was the main reason (55.2%).
Intentional poisonings by opium and aluminum phosphide were identified as the main causes of non-medicinal poisonings. It is necessary to emphasize on educational programs, prevention methods and general awareness.

Health databases contain a large amount of clinical data. Investigating the relationships and patterns in these databases can lead to new medical knowledge. Nutrition indicators are designed to evaluate the dietary quality in communities. Metabolic syndrome is a set of risk factors which may increase the risk of heart disease. Inappropriate diet is one of the most important factors in the occurrence of metabolic syndrome. The health industry is constantly producing a large amount of data in medical areas which requires a technique to disclose useful information and important relationships. The aim of this study was to compare the dietary diversity score (DDS) with healthy eating index (HEI) in terms of nutrient intake and assessing the association with metabolic syndrome with the approach of data mining.
A total of 1019 teenagers between the ages of 11 to 18 years were enrolled in this study. Data were collected using a past 24-hour food frequency questionnaire (FFQ). Nutrition data collection and determination of anthropometric characteristics and medical examinations were performed in Isfahan Cardiovascular Institute. Data were analyzed by TANAGRA data mining tool.
Statistical, regression and classification techniques were used for data exploration. The average score of DDS was 3.98 ± 1.10, while the HEI average was 59.23 ± 8.84 and the prevalence of metabolic syndrome was 17.39%. The average of DDS provided a better nutritional value in comparison to HEI. HEI was more robust in controlling received energy and carbohydrates. DDS was not significantly correlated with any of the components of metabolic syndrome, while HEI was weakly correlated with high waist circumference. High quartiles of HEI could predict a lower risk of metabolic syndrome, while high quartiles of DDS can predict higher risk of metabolic syndrome.
The findings of this study revealed that the DDS score may result in better nutrition uptake while adhering to the HEI was more effective in reducing the risk of metabolic syndrome.

Dementia is associated with serious effects on memory, cognition and ability to carry out daily activities. There is evidence that impairment in activity of daily living (ADL) is even reported among elder patients who suffer from mild cognitive disorders. Therefore, we aimed to determine the status of ADL and instrumental activity of daily living (IADL) in healthy and cognitive impaired elderlies (MCI, Mild, and Moderate dementia).
In this cross-sectional study which was conducted in 2016, 300 elderlies (60 years and above) were selected using a classified cluster sampling in four groups (each group of 75 individuals). These groups comprised of healthy old people and elderlies with mild cognitive impairment (MCI) and mild to moderate dementia that were residing in rural areas of Isfahan and Tehran and were classified between stages of 1 to 5 according to the Global Deterioration Scale (GDS). All individuals in four groups were assessed by ADL and IADL evaluation tools. The geriatric depression scale (GDS-15) and DSM-IV scale were performed on healthy elderlies by a physician to confirm the lack of mild dementia or depression. Data were analyzed by SPSS 20 software and using descriptive statistics, analysis of variance and independent samples T-test.
According to the cognitive impairment screening results by GDS, 76 elderlies were healthy, 75 were in MCI group, 72 individuals were diagnosed with mild dementia and 77 were suffering from moderate dementia. The mean scores of ADL tool on the basis of different cognitive stages of elderlies were statistically significant (p Although applying the ADL and IADL tools are not considered as gold standards in rapid assessment of cognitive impairments among elderlies, they could be considered as useful and user friendly tools to detect performance alterations in elderlies with dementia to provide healthcare by geriatric teams.

Major management decisions in organizations not only in the present but also in the future have a profound impact on different aspects of the organization. A slight mistake in making decisions may lead to the loss of resources of the organization, including financial and human resources. In the present study, we evaluated the problem of choosing the most convenient location for the construction of hospitals and health centers as one of the most important issues in the field of health. Regarding the numerous factors in decision making and the myriad of possible solutions to this problem and also disability of human in solving such problems, a genetic optimization algorithm has been used to calculate the best location for the construction of hospitals.
This study was simulated according to the actual conditions which may exist in a city. Given the existence of a city with N × N dimensions and having several hospitals and health centers in the city, the issue was raised for the construction of three hospitals. Important factors which could influence the decision making were health status, referring times and land prices. Furthermore, the most proper locations for the construction of three hospitals were calculated using the genetic algorithm.
Three characteristics including the level of health, referring times and land prices were randomly assigned to all urban areas. The coordinates of available health centers in the city were also identified. Another point was the lack of proximity of hospitals in the city. Setting the threshold of 0.2 units for the minimum distance between hospitals (current and new), this restriction was applied. After performing the algorithm with the governing conditions, three optimal points were found.
Considering the importance of locations for the construction of hospitals and health centers in the city and the existence of various factors for selecting the most appropriate place, application of strategies and algorithms which may be helpful in finding the best solution among the myriad of solutions in inevitable. According to the fact that human beings alone or by simple mathematical methods are not capable of taking all the features together and examine the search space to find the best result, we achieved the best solution in the city by setting the parameters of the genetic algorithm and taking into account all important factors.

Animal bites are a major threat to human health, while the subsequent infections such as Rabies could be lethal. The aim of this study was to determine the epidemiologic status of animal bite and the effect of wasting stray dogs on the incidence of animal bites in Galikesh County since 2009 until 2013.
The present study was a cross-sectional study with descriptive-analytical approach. A total of 1712 animal-bitten cases who were residing in Galikesh during the years of 2009-2013 were enrolled by census method. Data were collected from the recorded documents of animal-bitten individuals and analyzed by SPSS.
Of all cases, 1203 (70.3%) individuals were male and 509 (29.7%) were female. Regarding the age, cases were ranged between 1 to 89 years with a mean and standard deviation of 26.88 ± 18.39 years. The majority of bite cases (92.3%) were related to dogs. Moreover, 71.4% of bites were on legs. There was a significant relationship between sex and the place of residence as well as between the place of the event (biting) and delay to the first vaccination (P The current plan of wasting the stray dogs has no effect on reducing the incidence of bites in Galikesh. Therefore, it is recommended to carry out controlling programs, education and community awareness in this field.