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Introduction: Due to the high importance of egg shell quality in terms of hardness, extensive transportation with high volume of this product between different countries, the importance of shell quality in terms of protecting the internal content from extra-shell contamination and also one of the ways to improve traits, relying on The genetic structure of a trait is the application of genetic selection. Therefore, the aim this study is to use transcriptome data obtained from uterine tissue of two groups of laying hens with hard and weak eggshell, in each of the three stages of the calcification period (initiation, growth and termination). Gene expression profile was determined and differential expression of genes is analyzed so that different index genes can be expressed and their ontology can be studied to help the results. As a result, the genetic structure of the trait and the list of index genes have been regularly completed, and with the information obtained from the present study, the correct and practical genetic selection can be made in laying hen breeds.Materials and Methods: The aim of this study was to investigate the gene expression profile between two groups of chickens with hard and weak eggshells in three stages of calcification period (initiation, growth and termination), to identify significant index genes with different expression and analysis. Ontology and the paths involved are related to them. Therefore, in this study, transcripts (total mRNA sequences) of 18 samples of uterine tissue including three replicates in each stage of each group were prepared. The process of converting the initial format of readings was done using SRAtoolkit software, measuring the quality of readings with fastQC software, editing readings with Trimmomatic software and re-measuring the quality of readings after editing with fastQC software; Also, the alignment and mapping of the readings were done using Hisat2 software and format conversion and sorting of results was performed using Samtools software. Finally, the differential expression analysis of genes was performed using Cufflinks software package (Cufflink, Cuffmerge and Cuffdiff software) and Then, considering p-value +4 and log2(fold_change) < -4, 51 genes at the initiation stage, two genes at the growth stage and four genes at the termination stage had different and significant expression. The largest difference in gene expression between the two groups at the initiation stage, ENSGALG0000000044418 gene with log2 (fold_change) equal to 8/63 and at the growth stage, ENSGALG0000000049618 gene with log2 (fold_change) equal to 6/82 and at the termination stage, ENSGALG0000000049618 gene with log2 (fold_change) equal to 5/14 was observed. Ontological analysis of index genes showed that they are mainly involved in protein binding activities (ENSGAL000000444418, NMRAL1, SLITRK4, CHL1, ENSGAL00000009041, PHACTR3 and CORIN genes), DNA transcription regulation (LHX1, TFAP2A, RUNX3, ETV1, NR4A3 and RUNX1 genes), immune response (ENSGAL0000000043996, TMEM117, AvBD9, GCNT3, ENSGAL00000046947 and ENSGAL00000051617 genes), fat metabolism (PNPLA3, NR4A3, CD36, FFAR4 and DGKB genes) and calcium ion binding (ANXA10, CAPN8, CDH18 and DGKB genes), respectively.Conclusion: In the differential expression analysis of genes, considering log2 (fold_change) more than +4 and less than -4, in the initial stage, 51 genes, in the growth stage, two genes and in the termination stage, four genes were identified. The highest differences in gene expression between the two groups were observed in the initial stage, ENSGALG00000044418 and PDZK1IP1 genes, in the growth stage, ENSGALG00000049618, ENSGALG00000048945 and TMEM63C genes and in the termination stage, ENSGALG000000004400 and ENSG26 genes; The results of ontological analysis of index genes showed that they are mainly involved in protein binding, DNA transcription regulation, immune response, lipid metabolism and calcium ion binding, respectively.

Background and Aim: The new Coronavirus Disease 2019 (COVID-19) outbreak initiated from China in late December 2019, has posed a great global health threat. Since patients with high blood pressure, diabetes, and cardiovascular diseases are at high risk of COVID-19, this study aims to investigate the prevalence, severity, clinical manifestations, and mortality rate in COVID-19 patients with underlying diseases compared to those without underlying diseases. Methods & Materials: This study was performed on 1408 patients with COVID-19 admitted to Golestan, Hajar, Khanevadeh and Besat hospitals in Tehran, Iran. Required data including disease prevalence, severity, clinical manifestations and mortality rate in patients with and without underlying diseases were collected and then analyzed using statistical tests in SPSS software, considering a significance level of P

Abstract- The optimal power flow (OPF) is one of the key tools in the planning and operation of power systems. However, due to extensive using of the renewable energy sources especially, wind generation in the electric energy generation, application of this tool encounter with a major challenge. Uncertainty in the available wind generation level rooted in forecast error necessitates the change in the modeling and solution method of OPF problem. In this research work, Locational Marginal Price (MCP) as an important parameter in the market-based power systems is modeled in the context of optimal power flow problem and its probability density function is computed using a new point estimation method. The proposed point estimation method approximate the desired probability characteristics using their a few moments. Apart from that the proposed method guarantees the feasibility of the obtained estimated points, as the significant advantage, it notably outperforms the conventional point estimation methods in the required time and approximation accuracy aspects. Application of the obtained results is discussed from practical point of view as well. Effectiveness of the proposed method is examined on the 9-bus and 24-bus IEEE test systems together with realistic 118-bus power system and its advantages in accuracy and quickness with respect to the other methods are shown.

Introduction & Aims: From World Health Organization’s point of view, health is well-being in terms of physical, social and mental not merely the absence of disease. Public health is the very important factor in the industries if neglecting, its effects on both individuals and organization would be irreparable. This study aimed to assess the general health condition and its effective factors in an industry staff. Methods: This was across sectional study and all employees in this industry were recurred or collected by census (n= 110). The demographic questionnaire and the General Health Questionnaire (GHQ) was used for data collection. Data analysis was performed by using SPSS software (Ver.20) and the independent t-tests, ANOVA and Spearman correlation coefficient test.Results: Based on the results, the average score for general health in sub-groups of physical disorders was 6.06±2.78, anxiety was 4.01±2.64, social disorder was 11.97±3.98 and depression was 3.30 ±3.74. In these sub-groups 67.3%, 82.7%, 7.3% and 85.5% of the subjects were in healthy group. There was no statistically significant difference between the variables of age and work history, and score of public health sub-groups whereas there was a statistically significant difference between the total score of general health and education.Conclusion: Factors such as education can be named as effective factor on the general health condition of employees in this industry. In the present study, a very small percentage of individuals in social disorder sub-groups, were normal. Therefore, by conducting survey and focus in this area and executive decisions positively, we can contribute to increase general health condition.*Corresponding Author: Emkani Mojtaba, Master of Science, department of occupational health engineering, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.Email: mojtabaemkani@gmail.com