• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5917-5921
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• 2015

Background: Prostate cancer is the most commonly diagnosed form of cancer and the sixth leading cause of cancer-related deaths among men in the entire world. Reported standardized incidence rates are 12.6, 61.7, 11.9 and 27.9 in Iran, developed countries, developing countries and the entire world, respectively. The present study investigated the relative risk of PC in Iran at the province level and also explored the impact of some factors by the use of Bayesian models. Materials and Methods: Our study population was all men with PC in Iran from 2005 to 2008. Considered risk factors were smoking, fruit and vegetable intake, physical activity, obesity and human development index. We used empirical and full Bayesian models to study the relative risk in Iran at province level to estimate the risk of PC more accurately. Results: In Iran from 2005 to 2008 the total number of known PC cases was 10,361 with most cases found in Fars and Tehran and the least in Ilam. In all models just human development index was found to be significantly related to PC risk Conclusions: In the unadjusted model, Fars, Semnam, Isfahan and Tehran provinces have the highest and Sistan-and-Baluchestan has the least risk of PC. In general, central provinces have high risk. After adjusting for covariates, Fars and Zanjan provinces have the highest relative risk and Kerman, Northern Khorasan, Kohgiluyeh Boyer Ahmad, Ghazvin and Kermanshah have the lowest relative risk. According to the results, the incidence of PC in provinces with higher human development index is higher.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.131-146
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• 2022

Logit models are commonly used to predicting and classifying categorical response variables. Most Bayesian approaches to logit models are implemented based on the Metropolis-Hastings algorithm. However, the algorithm has disadvantages of slow convergence and difficulty in ensuring adequacy for the proposal distribution. Therefore, we use auxiliary mixture sampler proposed by Frühwirth-Schnatter and Frühwirth (2007) to estimate logit models. This method introduces two sequences of auxiliary latent variables to make logit models satisfy normality and linearity. As a result, the method leads that logit model can be easily implemented by Gibbs sampling. We applied the proposed method to diabetes data from the Community Health Survey (2020) of the Korea Disease Control and Prevention Agency and compared performance with Metropolis-Hastings algorithm. In addition, we showed that the logit model using auxiliary mixture sampling has a great classification performance comparable to that of the machine learning models.

• Safety and Health at Work
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• v.15 no.2
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• pp.220-227
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• 2024

Background: Though the artificial neural network (ANN) technique has been used to predict noise-induced hearing loss (NIHL), the established prediction models have primarily relied on cross-sectional datasets, and hence, they may not comprehensively capture the chronic nature of NIHL as a disease linked to long-term noise exposure among workers. Methods: A comprehensive dataset was utilized, encompassing eight-year longitudinal personal hearing threshold levels (HTLs) as well as information on seven personal variables and two environmental variables to establish NIHL predicting models through the ANN technique. Three subdatasets were extracted from the afirementioned comprehensive dataset to assess the advantages of the present study in NIHL predictions. Results: The dataset was gathered from 170 workers employed in a steel-making industry, with a median cumulative noise exposure and HTL of 88.40 dBA-year and 19.58 dB, respectively. Utilizing the longitudinal dataset demonstrated superior prediction capabilities compared to cross-sectional datasets. Incorporating the more comprehensive dataset led to improved NIHL predictions, particularly when considering variables such as noise pattern and use of personal protective equipment. Despite fluctuations observed in the measured HTLs, the ANN predicting models consistently revealed a discernible trend. Conclusions: A consistent correlation was observed between the measured HTLs and the results obtained from the predicting models. However, it is essential to exercise caution when utilizing the model-predicted NIHLs for individual workers due to inherent personal fluctuations in HTLs. Nonetheless, these ANN models can serve as a valuable reference for the industry in effectively managing its hearing conservation program.

• Biomolecules & Therapeutics
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• v.23 no.1
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• pp.1-11
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• 2015

Lysophosphatidic acid (LPA) is a signaling lipid that binds to six known lysophosphatidic acid receptors (LPARs), named $LPA_1-LPA_6$. These receptors initiate signaling cascades relevant to development, maintenance, and healing processes throughout the body. The diversity and specificity of LPA signaling, especially in relation to cancer and autoimmune disorders, makes LPA receptor modulation an attractive target for drug development. Several LPAR-specific analogues and small molecules have been synthesized and are efficacious in attenuating pathology in disease models. To date, at least three compounds have passed phase I and phase II clinical trials for idiopathic pulmonary fibrosis and systemic sclerosis. This review focuses on the promising therapeutic directions emerging in LPA signaling toward ameliorating several diseases, including cancer, fibrosis, arthritis, hydrocephalus, and traumatic injury.

• Journal of Integrative Natural Science
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• v.8 no.1
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• pp.75-79
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• 2015

Thromboxane A2 receptors (TXA2-R) are the G protein coupled receptors localized on cell membranes and intracellular structures and play pathophysiological role in various thrombosis/hemostasis, modulation of the immune response, acute myocardial infarction, inflammatory lung disease, hypertension and nephrotic disease. TXA2 receptor antagonists have been evaluated as potential therapeutic agents for asthma, thrombosis and hypertension. The role of TXA2 in wide spectrum of diseases makes this as an important drug target. Hence in the present study, homology modeling of TXA2 receptor was performed using the crystal structure of squid rhodopsin and night blindness causing G90D rhodopsin. 20 models were generated using single and multiple templates based approaches and the best model was selected based on the validation result. We found that multiple template based approach have given better accuracy. The generated structures can be used in future for further binding site and docking analysis.

• IMMUNE NETWORK
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• v.8 no.4
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• pp.107-123
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• 2008

It has now been well documented in a variety of models that T regulatory T cells (Treg cells) play a pivotal role in the maintenance of self-tolerance, T cell homeostasis, tumor, allergy, autoimmunity, allograft transplantation and control of microbial infection. Recently, Treg cell are isolated and can be expanded in vitro and in vivo, and their role is the subject of intensive investigation, particularly on the possible Treg cell therapy for various immune-mediated diseases. A growing body of evidence has demonstrated that Treg cells can prevent or even cure a wide range of diseases, including tumor, allergic and autoimmune diseases, transplant rejection, graft-versus-host disease. Currently, a large body of data in the literature has been emerging and provided evidence that clear understanding of Treg cell work will present definite opportunities for successful Treg cell immunotherapy for the treatment of a broad spectrum of diseases. In this Review, I briefly discuss the biology of Treg cells, and summarize efforts to exploit Treg cell therapy for autoimmune diseases. This article also explores recent observations on pharmaceutical agents that abrogate or enhance the function of Treg cells for manipulation of Treg cells for therapeutic purpose.

• 대한예방의학회:학술대회논문집
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• 2005.10a
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• pp.402-402
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• 2005

• Genomics & Informatics
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• v.5 no.4
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• pp.168-173
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• 2007

In previous nuclear genomic association studies, Random Forests (RF), one of several up-to-date machine learning methods, has been used successfully to generate evidence of association of genetic polymorphisms with diseases or other phenotypes. Compared with traditional statistical analytic methods, such as chi-square tests or logistic regression models, the RF method has advantages in handling large numbers of predictor variables and examining gene-gene interactions without a specific model. Here, we applied the RF method to find the association between mitochondrial single nucleotide polymorphisms (mtSNPs) and diabetes risk. The results from a chi-square test validated the usage of RF for association studies using mtDNA. Indexes of important variables such as the Gini index and mean decrease in accuracy index performed well compared with chi-square tests in favor of finding mtSNPs associated with a real disease example, type 2 diabetes.

• Journal of Microbiology and Biotechnology
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• v.11 no.6
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• pp.1071-1076
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• 2001

Chemopreventive activities of polysaccharides from soybeans fermented with either Phellinus igniarius or Agrocybe cylindracea were investigated by measuring the induction of quinone reductase (QR), glutathione S-transferase (GST) activities, and glutathione (GSH) levels in the cell culture along with inhibition of polyamine biosynthesis. The polysaccharides from soybeans fermented with P. igniarius strongly (p<0.005) induced QR activity at all concentrations tested. The extract not only induced GST activity in a dose-dependent manner in the concentration range of 0.1-1.0 mg, but significantly induced GSH revels in cultured Hepa 1c1c7 cells with a maximal 1.4-fold increase at 0.1 mg. The polysaccharides from soybeans fermented with A. cylindracea were effective in inhibiting polyamine metabolism. These results suggest that polysaccharides from soybeans fermented with P. igniarius or A. cylindracea have cancer chemopreventive activities in in vitro models and, therefore, could be considered as potential agents for cancer chemoprevention.

• Journal of applied mathematics & informatics
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• v.38 no.5_6
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• pp.375-406
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• 2020

The anti-predator factor due to fear of predator in eco- epidemiological models has a great importance and cannot be evaded. The present paper consists of a modified Lesli-Gower predator-prey model with contagious disease in the predator population only and also consider the fear effect in the prey population. Boundedness and positivity have been studied to ensure the eco-epidemiological model is well-behaved. The existence and stability conditions of all possible equilibria of the model have been studied thoroughly. Considering the fear constant as bifurcating parameter, the conditions for the existence of limit cycle under which the system admits a Hopf bifurcation are investigated. The detailed study for direction of Hopf bifurcation have been derived with the use of both the normal form and the central manifold theory. We observe that the increasing fear constant, not only reduce the prey density, but also stabilize the system from unstable to stable focus by excluding the existence of periodic solutions.