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The effect of prednisolone on sperm viability, sperm penetration rate and intra-uterine insemination rates in men with marked sperm agglutination and antisperm antibodies
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Summary:
Background: the immune system differentiates between the endogenous and exogenous bodies that inter the body. The break-down of blood-testis barrier results in the production of antisperm antibodies. This may occur in the case of an infection to the prostate, seminal vesicle and epididymes. Antisperm antibodies (ASA) cause sperm agglutination and affect sperm motility, viability and sperm migration in the female reproductive tract. ASA also impair fertilization process. The objective of the present work was to study the effect of prednisolone on sperm motility index (SMI), viability and sperm penetration assay (SPA) in immunologically infertile men.
Materials and methods: The semen and serum samples of 140 infertile men were examined by microagglutination test and slide agglutination test to detect ASA and sperm agglutination. Semen fliud analysis was performed to report sperm motility index (SMI), sperm viability and hypo-osmotic swelling test (HOST). Sperm penetration assay was done to record sperm penetration rate (SPR), sperm decondensation rate (SDR) and sperm penetration index (SPI). Men with positive ASA were treated with prednisolone and considered as treated group Prednisolone was given orally in a dose of 5 mg three times daily for three months. The semen analysis, SMI HOST and SPA were performed before and after treatment with prednisolone. The number of semen samples in the treated group was 144 and in the control fertile group was 80. HOST-SPA positive semen was exposed to antisperm antibodies separation (ASAS) and invitro sperm activation prior to intra-uterine insemination.
Results: The SMI was significantly higher in the post-treated group compared to pretreated group (240 vs. 52.5, P<0.0l). The SPI in the control group was significantly higher than the post and pre-treated groups. The HOST and viability test results were significantly increased in the post-treated group compared to pre-treated group (73.42 vs. 48.56 and 71.36 vs, 50. 74 respectively, P<0.01). The sperm penetration rate, sperm decondensation rate and sperm penetration index were significantly increased in the post-treated vs. pre-treated groups (26.49 vs. 10.84, 10.91 vs. 3.47, P<0.05, 14.45 vs. 4.30, P<0.01 respectively). HOST-SPA positive semen was used for intra-uterine insemination (IUI). The semen was exposed to ASAS and in vitro activation prior to IUI and resulted in 42.86% pregnancy rate per cycle. The pregnancy was confirmed by the observation of gestation sac and viable fetal hear beet 5 weeks following IUI.
Conclusion: It was concluded from the results of the present study that treatment of immunological infertile men with prednisolone improves SMI, sperm viability and SPA results. The application of HOST-SPA positive semen for IUI resulted in successful pregnancy. The authors indicate that these viable spermatozoa with high fertilizable potential could be used for IVF and/or ICSI in immunologically infertile men.

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Publication Date
Wed Oct 01 2008
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Intrauterine Insemination and Luteal Support Therapy Outcomes in Unexplained Infertility, Mild and Marked Luteal Defective Infertile Women
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Back ground: Inadequate secretory transformation of the endometrium resulting from deficient ovarian progesterone secretion is a cause of infertility and recurrent abortion
in luteal phase defects (LPD) women. LPD are diagnosed in 20% of infertile patients and 60% of patients with recurrent abortion and 50% of anovulatory women.
Aim : The objective of the present study was to compare pregnancy outcome following sperm penetration assay (SPA), intrauterine insemination (IUI) and luteal support
therapy (LST) in infertile patients with unexplained infertility (UI) mild and marked LPD.
Materials and Methods: Men with normal semen analyses and positive sperm penetration assay scores were included in this St

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

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Publication Date
Tue Aug 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of Stimulating Maize Seeds with Potassium Nitrate and Licorice Extract on the Seed Viability and Vigor
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Germination and field emergence are delayed and their duration is prolonged due to the declining soil temperature during the spring season, which is reflected in the subsequent stages of crop growth, therefore, this study aimed to improve germination. Under a wide range of environmental conditions, a laboratory factorial experiment was carried out to study the effect of seed stimulation with potassium nitrate (distilled water only (0), 2, 4, and 6 mg L-1) and with an aqueous extract of licorice roots (distilled water only (0), 3, 6, and 9 g L-1) on the seed viability and vigor. The laboratory experiment was carried out according to the Completely Randomized Design (CRD) with four repetitions. The results showed the superiority of the intera

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Photodynamic Inactivation (Effect of Laser with and Without Photosensitizer) on Viability of Streptococcus Pyogenes
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     This study focused on the bactericidal potency of toluidine blue” TBO”photosensitizer and red laser radiation of 635nmwith different doses against multi-drug resistant streptococcus pyogenes (S. pyogenes) isolated from infected burns wounds to see if it is susceptible to photodynamic inactivation .

Atotal of 45 isolates were collected from 38” patients” with infected burnwounds samples were collected from September to December 2019.Burns wounds swabs were employed using standard procedures of swab collection. Among these, eleven isolates were multidrug resistant”S.pyogenes”. More resistant isolates that has been proved to all antibiotics used. This multidrug resistant isolate used in

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Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Wed Sep 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Correlation of Penetration Rate with Drilling Parameters For an Iraqi Field Using Mud Logging Data
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This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.

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Publication Date
Thu Nov 21 2019
Journal Name
Al-kindy College Medical Journal
Investigate The Different Effect Of Nicotine On H460 And H441 Lung Cells Viability
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Background: Nicotine is the foremost chemical constituent responsible for addiction in tobacco products, in the non-ionized condition can be easily absorbed via epithelial tissue of the lung, the mouth, the nose  and across the skin

Objective:The study examines the harmful effect of   the nicotine which is an important component of cigarette in vitro.

Type of the study: Cross-sectional study.

Methods: Examines the harmful effect of   the nicotine which is an important component of cigarette in vitro by using two types of lung cancer cell lines (H460 TP53+/+, H441 TP53-/-).

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