Fatemeh Bagheri, Hakimeh Alizadeh Majd, Zahra Mehrbakhsh, Majid Ziaratban,
Volume 2, Issue 2 (10-2014)
Abstract
Background & Objective: Prediction of health status in newborns and also identification of its affecting factors is of the utmost importance. There are different ways of prediction. In this study, effective models and patterns have been studied using decision tree algorithm.
Method: This study was conducted on 1,668 childbirths in three hospitals of Shohada, Omidi and Mehr in city of Behshahr. Variables such as baby's gender, birth weight, birth order, maternal age, maternal history of illness, gestational diseases, type of delivery, reason of caesarean section, maternal age, family relationship of father and mother, mother's blood type, mother's occupation and blood pressure and place of residence were chosen as predictive factors of decision tree categorization method. The health status of the baby was used as a dependent dual-mode variable. All variables were used in clustering and correlation rules. Prediction was done and then compared using 4 decision-tree algorithms.
Results: In the clustering method, the optimal number of clusters was determined as 8, using the Dunn index measurement. Among all the implemented algorithms of CART, QUEST, CHAID and C5.0, C5.0 algorithm with detection rate of 94.44% was identified as the best algorithm. By implementing the Apriori algorithm, strong correlation rules were extracted with regard to the threshold for Support and Confidence. Among the characteristics, maternal age, birth weight and reason of caesarean section with the highest impacts were found as the most important factors in the prediction.
Conclusion: Due to the simple interpretation of the decision tree and understandability of the extracted rules derived from it, this model can be used for (most individuals) professionals and pregnant women at different levels.
Alireza Mohebbi, Sanaz Baghban Rahimi, Alijan Tabarraei, Mohsen Saeedi, Mirsaeed Ebrahimzadeh, Leila Alizadeh, Amir Ghaemi,
Volume 4, Issue 2 (10-2016)
Abstract
Background and Objectives: Human papilloma virus (HPV) is known as the etiologic agent of cervical cancer and second common cancer among women. HPV viruses with the elevated risk of infection have more potentiality to cause cancer. The carcinogenesis in these viruses is accomplished by oncoproteins such as E7. Employing DNA vaccines which code specific antigens such as E7 is a novel therapeutic approach against such cancers.
Methods: In the present study, plasmid coding HPV16 E7 was administered intracutaneously to C57BL/6 tumoric mice models for investigation of its immunostimulating potential. PcDNA3.1+ vector was used as control vector. After immunization, spleen of animals were removed. Then, release of lactate dehydrogenase (LDH) was evaluated to address the cytotoxic activity (CTL) induced by cellular immunity in spleenocytes. Interferon-γ (IFN-γ) and interleukin-4 (IL-4) cytokines were also analyzed as profiles of Th1 and Th2, respectively. Anti-inflammatory cytokine interleukin-10 (IL-10) levels were also investigated in tumor microenvironments.
Results: Our results showed that CTL activity was higher among samples receiving HPV16 E7 coding vector in comparison to the group receiving pcDNA3.1+ control vector (P < 0.05). Levels of IFN-γ and IL-4 were also higher in the group receiving HPV16 E7 plasmid in comparison to the control group (P < 0.05). Similarly, IL-10 levels were significantly lower in tumor carrying mice groups receiving HPV16 DNA vaccine compare to PBS and pcDNA3.1 receiving control groups.
Conclusion: HPV16 E7 expressing DNA vaccine could increase the release of LDH due to immune system CTL activity. Elevation in IFN-γ and IL-4 levels as well as IL-10 reduction indicates an increase in both Th1 and Th2 profiles resulted by using potent DNA vaccine coding HPV16 E7 in tumor animal model.
Sanaz Baghbanrahimi, Hoorieh Soleimanjahi, Alireza Mohebbi, Mir Saeid Ebrahimzadeh, Leyla Alizade, Amir Ghaemi,
Volume 5, Issue 1 (5-2017)
Abstract
Background & Objective: Human papillomavirus (HPV) oncoproteins, including E6 and E7 are constitutively expressed in cervical cancer cells. These proteins are ideal targets to be used for developing therapeutic vaccines against existing HPV-associated carcinomas. The aim of this study was to measure the proliferation response rate of splenic lymphocytes derived from E7-HPV16 encoding plasmid injection on the tumor mouse model of papillomavirus.
Method: C57BL/6 mice were inoculated subcutaneous with 5× 10⁵ TC-1 cells in three times with two weeks intervals and then immunized with HPV-16 E7 DNA vaccine. The proliferation response of splenic cells was measured by MTT assay. IL12 cytokine was measured by ELISA assay and the mass of tumor was calculated with caliper for six weeks.
Results: Following the application of DNA vaccines containing E7 therapeutic gene, the proliferative response of splenic cells was provoked significanltly higher than the stimulation in control group (P<0.05). Moreover, the secretion of IL12 was significantly increased in vaccinated mice tumor tissue (P<0.05). The growth of tumor in vaccinated group was markedly decreased in comparison to PBS and pcDNA3 groups (P<0.05).
Conclusion: Our findings revealed that the application of DNA vaccine containing E7 gene in a tumor mouse model may induce anti-tumor cellular immune responses.
Seyed Farid Nourbakhsh, Reza Fadayevatan, Mahtab Alizadeh-Khoei, Farshad Sharifi,
Volume 5, Issue 2 (10-2017)
Abstract
Background & Objective: 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).
Methods: 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.
Results: 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<0.001). The ADL scores among elderlies were lowered by increasing the severity of cognitive impairment. Moreover, the average scores of IADL among elderlies with different cognitive status were significantly different (p<0.001). The IADL scores in cases with moderate dementia were markedly declined in comparison to healthy subjects and elderlies with MCI and mild dementia.
Conclusion: 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.
