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Frequency of Chlamydia trachomatis in genital specimens: kerman city, PCR method
Khalili M, Atapour M, Aali S, Azizollahi Ga, Azizollahi S,
Volume 66, Issue 2 (1 2008)
Abstract

Background: Chlamydia trachomatis (CT) is an obligate intracellular bacterium that causes genital disease and the most common sexually transmitted infection in the world. The most frequent risk factors associated with chlamydial infection are related to sexual behavior, multiple partners, and inconsistent condom use. Presenting primarily as urtheritis in men and cervicitis in women, CT a major cause of chronic pelvic inflammatory disease and subsequent infertility in women, eye and lung infection in newborns and other manifestations. Identification of CT-infected patients may prevent its spread and thereby reduce the high morbidity associated with CT infections. Polymerase chain reaction (PCR) is a sensitive and specific method for the detection of small quantity of bacterial DNA in clinical samples. The aim of this study was to determine the frequency of C. trachomatis by PCR in genital samples from patients in the city of Kerman.

Methods: A total of 130 genital samples including 64 endocervical and 66 urethral swab samples were collected by physicians. Nucleic acid was extracted from each sample using a commercial DNA extraction kit. PCR primers specific for a conserved region of the C. trachomatis omp2 gene, encoding an outer membrane protein, were used for amplification. 

Results: A total of 9.2% (6.25% of cervicitis and 12.1% of urethritis) of the samples were found positive for CT using this PCR method.

Conclusions:  The present study shows a high prevalence of CT infection, especially in men with urethritis. Such patients should be referred to genitourinary clinics for treatment and partner notification. Given its worldwide prevalence, further CT studies on more populations are needed to assess potential public health implications of these infections.


Effects of probiotic lactobacillus acidophilus and lactobacillus casei on the behavior of colorectal tumor cells
Soltan Dallal Mm, Mojarrad M, Salehipour Z, Atapour Mashhad H, Raoofian R, Rajabi Z,
Volume 70, Issue 4 (5 2012)
Abstract

Background: Probiotic microorganisms are living normal flora of human body that have nutritional value and health benefits when administered in adequate amounts. The health benefits include prevention of bacterial diarrhea, skin eczema and recently understood, prevention and control of various cancers, as well. Different mechanisms such as stimulating the immune system, modifying the composition of gastrointestinal and genitourinary tract normal flora and prevention of the carcinogenic activity of fecal enzymes have been identified for their probiotic activity. Due to the high density of the normal flora in the gut and also preferentially sporadic nature of colorectal cancers, these cancers are among the main candidates of treatment trials with probiotics. In this study, direct effects of probiotic lactobacilli on colon cancer tumor cells were studied.

Methods: Supernatant fluid and bacterial extracts were prepared and CaCo-2 cells were treated by these materials. Subsequently, the effects of the aforesaid elements were evaluated on cell proliferation, cell necrosis and cell apoptosis by MTT assay, LDH assay and caspase-3 activity.

Results: The supernatants of lactobacilli decreased cell proliferation and increased cell apoptosis but they did not have any effect on cell necrosis. In contrast, when cancerous cells were treated by lactobacilli extract, it lead to cell necrosis in addition to reduction in cell proliferation and increase in cell apoptosis.

Conclusion: The use of lactobacillus probiotics may reduce proliferation of tumor cells in the early stages of colorectal cancers.


Predicting the cause of kidney stones in patients using random forest, support vector machine and neural network
Mojgan Mortazavi, Abdolamir Atapour, Maryam Mohammadi, Mohammad Sattari,
Volume 79, Issue 9 (December 2021)
Abstract
Background: Today, with the advancement of technology in various fields, the importance of recording data in the field of health is increasing so much that for many diseases around the world, including kidney disease, registration systems have been set up. This is happening in our country and in the future, the number of these systems will increase. The medical data set contains valuable information that will be time-consuming and costly to obtain using laboratory methods, so there is a need for low-cost methods for extracting information. This study focuses on developing a predictive model for classifying the cause of kidney stones in Isfahan using three data mining techniques.
Methods: This cross-sectional research has been done from February 2021 to May 2021. The used medical data set includes information of 353 kidney stone patients in Isfahan. In this study, six target attributes of sodium, phosphate, oxalate, citrate, cysteine and uric acid were identified. The techniques for each of the 6 attributes are used separately. The techniques used in this study were three data mining techniques including random forest (RF), artificial neural network (ANN) and support vector machine (SVM).
Results: The best performance in terms of accuracy is related to support vector machine techniques in uric acid class, support vector machine in oxalate class and neural network in cysteine class. The worst performance is related to the random forest technique in the citrate class. The safest rules with a 66% confidence level are for the citrate and sodium classes, and the least reliable rule with a 50% confidence level is for the oxalate class.
Conclusion: Kidney stones can occur due to various reasons such as low citrate and high calcium oxalate. For example, for citrate, factors such as blood pH (potential of hydrogen), blood sugar and blood pressure are effective. To prevent any of the causes of kidney stones, factors should be controlled.

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