Cervical cancer is commonly caused by infection with human papilloma virus(HPV) and some risk factors are involved in the etiology of it.1 All over the world 437000 people are diagnosed with cervical disorders and half of them die due to cervical cancer.2 Annually 12000 new cases of cervical cancer are detected and 5000 women die because of it. In Spain about 2000 women are determined in the 3rd and 4th stage of the disease per year.3 Over the period 2000-2008 cervical cancer rate is 8 %among all cancers in Mongolia. Approximately 16 % of women’s cancer is cervical cancer. 4 In developing nations prevalence rate of cervical cancer is higher because of malnutrition, quality and framework for early detection are not satisfying and some reproductive risk factors also influence on it. 5 Worldwide diagnosing early and rapid management of precancerous condition and cervical abnormalities turn into main issue. Therefore based on these detection of premalignant lesion of cervix by colposcopy the main objective of the study. The overall goal of the study is to detect the premalignant lesion of cervix by colposcopy and determine of some risk factors and study the results.A total of 71 women, who are treated in Women’s inflammatory disease unit, Infertility and Women’s endocrine disorder unit are recruited for the cross sectional study. The women, who conducted the study were selected by accidently and colposcopy was done. They also have completed special questionnaires. The data were analyzed using the SPSS 19.0, Windows Office. The average age of the women was 38±9.4. Colposcopy was done 90.1% (n=64) of women, 9.9% (n=7) of women had not colposcopy. Among the women who had colposcopy, biopsies were taken 56.3% (n=36). During colposcopy we analyzed condition of cervix then we took biopsy from suspected areas and sent it histology laboratory. We compared predictive diagnosis, histology results after colposcopy and 33.3% (n=12) were identified as normal, CIN I was 52.7%, (n=19), CIN II was 5.5% (n=2), CINIII was 2.7% (n=1), cervical cancer is confirmed in 5.5% (n=2). We studied risk factors that can influence the cervical disorders among the women recruited in the study and age of first sexual intercourse (r=0.356, p=0.033), number of abortion (r=0.412, p=0.029) were statistically significant. However age of the women, parity, usage of contraceptive pills, smoking, number of sexual partners were statistically not significant.(p>0.05) When women’s age of first sexual intercourse is younger, cervical cancer disorder occurs30% greater comparing to women having first sexual intercourse later, (p<0.05, R=0.3), when number of abortion increases cervical cancer disorder increases 40%(p<0.05, R=0.41).F-1 to recruit osteoprogenitor /mesenchymal stem cells in the bone regeneration process.

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder of reproductive-age women, affecting an estimated 5-8% of all women in this age group. Clinically, hyperandrogenism, chronic amenorrhea, central obesity and polycystic ovary can all occur in women with PCOS and may cause of infertility. Dehydroepiandrosterone sulfate is an androgenic hormone produced inadrenal cortex and recently, there is no any data determined DHEA-S in patients with PCOS.Our study was designed to evaluate obesity, central obesity, hirsute grade and infertility and to determine serum DHEA-S hormone in women with PCOS and healthy non-PCOS women.We have used a cross-sectional study design and the study included reproductive-age 36 women, of whom 18 were diagnosed with PCOS and 18 were non-PCOS. Anthropometric components were measured and ELISA test to determine serum DHEA-S hormone was analyzed for all of these women. When we analyzed ELISA test to determine serum DHEA-S hormone, DHEA-S level was2.9±2.0 µg/ ml in non-PCOS reproductive-age women and 8.0±2.1 µg/ml in women with PCOS, respectively (р=0.01). Among the women diagnosed with PCOS had higher incidence of central obesity and grade II hirsute and infertility than healthy women (p=0.001). By the result, higher level of serum DHEA-S in women diagnosed with PCOS may cause of sign of hyperandrogenism such as central obesity, infertility and hirsute.

About 10-15% of infertility among reproductive aged couples. According to the Centers for Disease Control, 1/3 of the women among 30 over aged, ½ of the women among 40 over aged women have infertility. Infertility rate is in Europe 10%,in USA 15%, in Russia 17 % (Speroff L. Endocrinology and Infertility. 2005). Female infertility is 45.6%, caused by damage to fallopian tubes is 61%, hormonal causes infertility is 30-40%. In Mongolia the report of study in 1997, infertility rate was 13.06%, report of IVF laboratory of Bayangol hospital infertility rate was 8-10% in 2010, the female infertility was 40-60%. We have first time to study female infertility risk factor among our gynecological department. Aim of study is to identify the some risk factor of female infertility We separated the women into 2 groups by fertile (normal 48 women and infertility 48 women). Hormonal findings was obtained from all women and had survey of questionnaire to risk factor. Statistical analysis did SPSS 20, data were given as mean±SD, the frequencies of the alleles and genotypes in patients and controls were compared with X2 analysis. Odds ratio (OR) and 95% confidence intervals were calculated.The mean age was 33.4±6.1 and mean years of infertility was 7.0±4.5. The primary infertility was 27.1% (n=13), secondary infertility was 72.9% (n=35). The 1.2% (n=15) were given birth, the 33.3% (n=16) had miscarriage and 58.3% (n=28) had abortion of total women. The mean BMI was 24.7±4.6 and 23% were overweight and 13% women were obesity among infertility women. The mean length of uterus was 5.1±1.1 sm, width was 4.0±0.8 sm, mean length of ovaries was 3.1±0.6 sm, mean width was 2.3±0.6 sm among infertility women. Also estradiol mean level was 41.6±22.1 pg/ml, FSH was 15.6±6.1mIU/ml, LH 5.5±1.7mIU/ml, and prolactin 14.4±10.6 ng/ml, progesteron mean level was 0.6±0.1 ng/ml among infertility women. These hormonal level was same in normal women. The risk factor of infertility were sexually transmitted disease (p=0.007, OR=7.667, CI 1.612-36.455), and curettage of uterus (p=0.024, OR=1.357, CI 1.156-1.1819). Secondary female infertility rate was (72.9%) and the women with STD 7.6 hold and women with previous had curettage of uterus will get 1.3 hold the risk of infertility.

Introduction: The complete blood count (CBC) is a frequently performed laboratory test today. This study evaluated the effects of temperature and sample storage time on parameters of CBC which could produce misleading results of clinical significance. Methods: In a cross-sectional study, CBC was checked in 20 randomly selected out-patients and baseline measurements were analyzed using the XN-2000 (Sysmex, Kobe, Japan) fully automated hematology analyzer. CBC was done all samples of storage at room temperature. Values were checked at time intervals of 0, 6, and 24 hr. Results: Among CBC parameters, white blood cell, red blood cell, hemoglobin, mean cell hemoglobin (MCH), neutrophils and lymphocytes were stable at time up to 6 h. Hematocrit increased between 0 and 24 hours, averaging 41.5% and 45.2%, respectively. MCV, RDW-SD, and RDW-CV increased between 0 and 24 hours. The mean value was statistically significant. There were 85.6fL/ 93.4fL (p<0.001), 40.7fL /48.2fL (p<0.001), 13.1% and 14.2% (p<0.05), respectively.
However, the MCHC was affected by time differences. (p <0.001 at 0 and 24 hours, p <0.001 at 3 and 24 hours). Platelet PDW, MPV, and P-LCR values increased between 0 and 24 h, respectively. Conclusion Whole blood samples were stored at room temperature for 24 hours for CBC tests, there were statistically significant differences in the size of red blood cells and platelets.

Introduction: The traditional microscopic method is to visually count the elements in the urine, but it is difficult to distinguish between the cells because they are not stained. Sternheimer Malbin staining, on the other hand, contains a variety of dyes that help to distinguish elements in urine sediment, improve the differentiation between cell nuclei and cytoplasm, provide more information about cell shape and image, and make it easier to differentiate kidney disease. Objective: To study the results of the reading of a fully automatic urine sediment analyzer of compared with the Sternheimer Malbin stained bright field microscope method. Research materials and methods: In this study included 150 people who served the MJTH of the MNUMS received permission to participate in the research. The urine sample collected in accordance with the standard operating instructions was counted by a fully automated analyzer and stained with Sternheimer Malbin dye and counted red cells (RBC), white blood cells (WBC), epithelial cells (EC), and renal epithelium (RTEC) under a microscope using a Fuchs-Rosenthal chamber. Results: 23.3% (n=35) of the respondents were male, 76.6% (n=115) were female, and the average age was 44.3±11.6. There 16.6% (25)/9.3% (14) of the RBCs were counted in excess of the reference volume when analyzed under an microscope stained with an automated urine sediment analyzer and Sternheimer-Malbin dye. For each WBC method, 45.4% (68)/41 (61)% and EC 24.7% (37)/23.3% (35) were counted above the reference volume. 90% (135)/32% (48) of the total samples were counted in excess of the RTEC reference volume. Comparing the performance of the automatic urine sediment analyzer with the light microscope method, the sensitivity and specificity were RBC-99.8%/99.1%, WBC-99.3%/99.6%, EC-99.7%/99.2, and RTEC-99.1%/99.2%. False-positive and false-negative results were rated for each RBC-99.9%/99.1%, WBC-99.3%/99.6%, EC 99.8%/99.2%, and RTEC-99.7%/99.9%, respectively. The positive likelihood ratio was RBC, WBC, RTEC 1.0, or the test was useless, while the negative likelihood ratio was RBC was very different, WBC was slightly different, EC was very different, and RTEC was very different. Positive and negative predictive value indicators RBC-99.3%/99.4%, WBC-99.4%/99.4%, EC-99.4%/99.5, RTEC-99.2%/99.1%, optimality for RBC, WBC, EC 99.4%, RTEC -99.1%. Conclusion
1. The results of an automated urine sediment analyzer and a bright field microscope stained by Sternheimer Malbin were similar for red blood cells, white blood cells, and epithelial cells, but different for renal tubular epithelial cells.
2. The resuls UF-5000 analyzer and bright field microscope analysis using Sternheimer Malbin dye were comparable.

Background: Chronic kidney disease (CKD) is a global health problem. In Mongolia, urine is analyzed by methods of urine chemistry and urine sediment to diagnose kidney disease. The currently automated urine sediment analyzers have been widely used in clinical laboratories and are replacing traditional manual microscopic examination. Nonetheless, visual microscopic examination is still required in many cases. When chemical and sediment analyzers are used together, urine sediment could be confirmed under a microscope, if the results are inconsistent. Sternheimer-Malbin stain has contained a variety of dyes that help to distinguish particles (white blood cells, red blood cells, epithelial cells, casts, crystals, fatty drops, bacteria, yeast, trichomonas) in urine sediment, improve the differentiation between cell nuclei and cytoplasm, and provide more information about cell shape and image.
Therefore, the low-cost method that can be used on a daily basis.Although there are more than 4,500 laboratories in Mongolia that need to perform urinalysis, which is an important part of clinical laboratories, less than 10 percent of hospitals have fully automated sediment analyzers. For this reason, one of the most important issues in the clinical laboratories, the search for low-cost and useful methods for the analysis of urine sediments in order to provide access to services to the public. Our aim was the comparison of methods of the microscopic examination with Shternheimer-Malbin stain and fully automated UF-5000 analyzer for urine sediment. Methods: There was a comparative study, people who served the Clinical Central Laboratory of Mongolia-Japan Hospital received permission to participate in this research. One hundred five fresh, first morning, clean catch mid-stream urine samples were collected in accordance with standard operating instructions for urinalysis, between November 2020 and May 2021. Sternheimer-Malbin (SM) staining and direct microscopy observation methods with Fuchs-Rosenthal counting chamber were used to red blood cells (RBC), white blood cells (WBC) and epithelial cells (EC) in urine samples. The agreements between the automated urine analyzer and microscopic methods were calculated using Cohen’s kappa (k) with 95% confidence intervals (CI). Results: A total of 105 samples were collected and analysed in this study. The average age was 46.97±15.0and gender by 18% (n=19)were male and 82% (n=86) were female.
Compared to traditional manual methods and automated analyzer, the agreement within the same grade was 99/105 (94.3%) for erythrocytes, 96/105 (91.4%) for leukocytes, 92/105 (87.6%) for epithelial cells. And compared to Sternheimer-Malbin staining microscopy observation and automated analyzer, the agreement within the same grade was 98/105 (93.3%) for erythrocytes, 99/105 (94.3%) for leukocytes, 96/105 (91.4%) for epithelial cells. Agreement between traditional manual method and automated analyzer was higher than 85% and between Sternheimer-Malbin staining microscopy observation and automated analyzer was higher than 90%. The concordance between traditional manual method and automated analyzer was substantial (k=0.74, p<0.001; k=0.79, p<0.001) for RBC and EC, almost perfect (k=0.92, p<0.001) for WBC. Whereas the concordance between SternheimerMalbin staining microscopy observation and automated analyzer was substantial (k=0.70, p<0.001) for RBC, almost perfect (k=0.94, p<0.001; k=0.89, p<0.001) for WBC and EC. Comparison of Sysmex UF-5000 with microscopic particle counting methods resulted specificity was 98.9/100% for RBC, sensitivity was 97.7/95.3% and negative predictive value was 98.4/96.8% for WBC, sensitivity was 87.5/68.8% and negative predictive value was 97.8/94.7% for EC. Conclusion The Cohen’s k analysis result of comparisons between the SternheimerMalbin staining microscopic method and automated urine sediment analyzer showed significant almost perfect agreement (k=0.70-0.94, p<0.001).
The sensitivity and negative predictive value were high for both of WBC and EC were determined by Sternheimer-Malbin (SM) staining microscopy observation method. Results indicate the ability of a test to correctly identify those with the true positive and individual with a negative test result is truly negative better than comparison of Sysmex UF-5000 with traditional manual microscopic method assessment.