[Non-parametric estimation of the pattern of the age at natural menopause in Garmsar]

Based on WHO, menopause is defined as the permanent cessation of menstruation resulting from the loss of ovarian follicular activity which is recognized to have occurred after 12 consecutive months of amenorrhea, for which there is no other obvious pathological or physiological cause. It is the beginning of a phase of women's' life with somatic and metabolic changes which leads to decrease in quality of life, osteoporosis and heart diseases. Because of increasing the number of women experiencing post-menopausal life, studying the pattern of age in onset of menopause seems necessary. Non-parametric method to estimation the pattern of the age at natural menopause was introduced. For applied purpuses, data from a survey in Garmsar that it is performed on 581 women aged 30 years or older. The pattern of age at menopause was estimated for them using prevalence of menopause in each age group. The mean and median of age at natural menopause were 51.9 +/- 3.6 and 52.2, respectively. Increasing of menopause was slow from age 30 to 43, but a speed-up in monopause was observed until 55 years old, and then it was decreased slowly. compared to the other regions of Iran, the mean of age at natural menopause in Garmsar seems greater

[Analyzing the methodologies to estimate age at natural menopause and its effective factors]

Menopause, cessation of menstruation, is a public event for all women that occur between the ages of 45-55 [or even sooner]. A variety of researches done in Iran and the rest of the world show age at menopause can depend on numerous factors such as race and genetics, socioeconomics, history of fertility, physical activity, nutrition, sexual behaviors, diseases and etc. However, there are inconsistencies between results from different researches which can be related to methodology and methods of analysis. Present research has been done to analyze methodologies which estimate age at natural menopause and its associated factors by considering their power and weakness points. The cohort and cross-sectional methodologies to estimate age at natural menopause are introduced as well as appropriate statistical techniques to determine effective factors. Iranian and the some foreign papers, which their main object or one of the principle objects was estimating age at menopause, are introduced and analyzed. The results show that prediction and estimation of age at menopause are more complicated than it seems. Nearly all Iranian and some foreign surveys are poor in methodology and methods of analysis which decreases the efficacy and correctness of their findings

Cloning, optimization of expression condition, purification and immunological characterization of hydrophilic section of HCV core Ag, expressed in E-coli by T7-ara BAD promoter

The capsid or core Ag of Hepatitis C virus is a multifunctional protein which has the principal pathogenesis and diagnostic role in HCV related infections and most of these properties are attributed to the hydrophilic section [amino acids 2-122] of this protein. For different research and diagnostic applications, high amounts of this protein in pure and original form are required. So, the aim of this study was to clone the gene, optimize the expression condition, purify it in the original form, and immunologically characterize hydrophilic section of HCV Core Ag, expressed by T7-araBAD promoter system in E.coli. The PCR amplified region corresponding to 2-122 section of this Ag from genotype lb was cloned in pIVEX 2.3, a T7 promoter derived vector. The proper construct after digestional analysis and sequencing confirmations was transformed into BL2 1 -Al E. coli, and protein expression under control of araBAD promoter by addition of 0.2% Arabinose was induced. After optimization of expression condition, purification of protein by NI-NTA agarose gel chromatography in native condition by immidazole yielded about 3.5mg/L of HCV core Ag. Immunological studies by western blotting through application of core specific mAbs and results of ELISA tests indicated that the protein is with desired immunological properties. AraBAD promoter can be perfectly utilized to produce the hydrophilic section of HCV core in high yields, and purification through NI-NTA in native condition may provide the antigen for different research and diagnostic applications

Evaluation of a native preparation of HCV core protein [2-122] for potential applications in immunization, diagnosis and mAb production

Infection with hepatitis C virus [HCV] is a worldwide problem. Among HCV proteins, core antigen [Ag], besides its importance for diagnostic application is a prime candidate for component of a vaccine. Herein, we report results of studies on production of the hydrophilic domain of core Ag [2-122] in native conformation by an arabinose induction system in E.coli and the primary characterization of this recombinant protein for applications in diagnosis, immunization and mAb production. Recombinant core [r-Core] was able to detect anti-core antibodies in HCV positive serum samples in a dilution rate of 1/3200. It was also capable to elicit a potent anti-HCV humoral immune response in BALB/c mice. Finally, we established two stable clones of hybridoma which shown to produce specific and sensitive mAbs against the core protein. HCV core was able to elicit a broad range of antibody specificities depending on the immunogen conformation. Therefore, it may be possible to get new mAbs with higher affinities towards native conformation of core Ag

[Sample size determination for matched studies]

One faced to matched data when the main object for a study is investigation of the effect of a given factor on an outcome, such that the samples are matched on the some factors which are known as confounders. The response can be according to quantitative or qualitative scales. Matched case-control, before-after and crossover studies are used frequently in medicine. The significant tests are required to sufficient samples. In this paper, formulas for determination of sample size in matched studies are introduced by considering the scale of response and extended for matched case-control studies with multiple controls and illustrated using practical examples. Using statistical techniques, formulas for determination of sample size are introduced according to the scale of response. The practical examples interpreted in order to clarify the formulas and their applications. One can increase the power and the accuracy of the statistical tests for matched studies, using the introduced formulas

Analyzing receiver operating characteristic curves to compare medical diagnostic tests

One exposes with diagnosis problems when she or he does an experiment or modeling to predict and allocate objects or persons to certain groups. For example in medicine in order to discriminate diabetes or cancers [level 2 of prevention] different criterions or indices can used. The simplest status is allocating objects to two possible categories, therefore one can measure a test variable in ordinal or continuous scale and regarding an appropriate cut-off in range of test variable and sensitivity, specificity and value of loss function, he or she can determine objects for each category. A suitable and single value index to evaluate test variable is A, area under receiver operating characteristic [ROC] curve. Since probably there are several test variables that measured on a unique sample, so there are natural correlations between A's. When one wants to compare and select the best test [s] among them, ignoring of these correlations can lead to confused results. We have detailed a method to compute A's and their variance-covariance matrix and introduced an adequate statistical test to compare them also using a set of simulated data have showed effectiveness of correlations on statistical results. For applied purposes we have prepared a software package using Delphi5. Based on simulated data for two indices we found: A[1] = 0.660, SE[A[1]] = 0.054, A[2] -0.49, SE [A[2]] - 0.06. By ignoring correlations between A[1], A[2] we computed Z =2.1, it leads to reject equality of As in a alpha = 0.05 level, otherwise by regarding correlation, Z =1.92 and equality will accept. Ignoring correlation between As can lead to incorrect results