Background: Measuring the concentration of hepatitis B surface antigen (HbsAg) in HBV patients can be determined with immunoassay techniques. This study aimed to measure the HbsAg titers in chronic HBV patients and to assess its correlation with patients' ages, gender, and with the levels of liver enzymes and total serum bilirubin. Materials and Method: Fifty-eight chronic hepatitis B infected patients were enrolled in this study. Age and gender of the patients were recorded. HbsAg concentration was tested with automated Immunoanalyzer. The patients were also tested for ALT, AST, ALP, and TSB by automated chemistry analyzer. Results: All the chronic HBV patients have positive HBsAg titers above the negative cutoff (0.05U/L) with mea

Pregnancy and childbirth are physiological states characterized by sudden hormonal and immunologically described changes. The current study aimed to investigate the influence of maternal variables (age, previous abortion, placental position, and fetal position) on some physiological biomarkers, such as oxytocin (OT), prolactin (PRL), cortisol, and insulin growth factor 2 (IGF -2) and some immune biomarkers such as programmed cell death protein 1 (PD-1), programmed cell death ligand 1 (PD-L1) and interleukin 6 (IL-6) in Iraqi women undergoing caesarean section (CS). Blood samples were collected from 48 pregnant women in the age range (16-43 years) and serum was obtained to determine the levels of the above biomarkers. The effect of

Background/Objectives: Nonsurgical periodontal treatment (NSPT) is the gold-standard technique for treating periodontitis. However, an individual’s susceptibility or the inadequate removal of subgingival biofilms could lead to unfavorable responses to NSPT. This study aimed to assess the potential of salivary and microbiological biomarkers in predicting the site-specific and whole-mouth outcomes of NSPT. Methods: A total of 68 periodontitis patients exhibiting 1111 periodontal pockets 4 to 6 mm in depth completed the active phase of periodontal treatment. Clinical periodontal parameters, saliva, and subgingival biofilm samples were collected from each patient at baseline and three months after NSPT. A quantitative PCR assay was us

Toxoplasmosis is an infection caused by Toxoplasma gondii that leads to abortion or hydrocephalus during pregnancy.One hundered and twenty two aborted women were selected for this study. Serum samples were collected form Al-Kadhmia and Kamal Al-Samari Hospitals,and laboratories around Baghdad, and tested for specific IgG and IgM anti-toxoplasma antibodies to confirm toxoplasmosis in those women by using ELISA test.The result recorded that 51(41.8%) women had antibodies against Toxoplasma gondii, 25(59.5%) women were positive for IgG, and 17(40.5%) women were positive forIgM, while 9(17.6%)women were positive for both.

    Periodontal diseases such as gingivitis and periodontitis are considered common diseases. This study is aimed to predicate these diseases using non-harmful specimens such as saliva throughout the detection of some parameters. In the beginning, a random 51 patients' saliva was collected from outpatients who suffered from different degrees of periodontal diseases. Concurrently, another 40 people who appeared to be healthy were collected, and both patients and healthy people were subjected to a questionnaire form and diagnosed by a specialist dentist. The results of this study revealed that there is no significant difference between males and females in infection with periodontal diseases. As well, smoking is not acting as the m

Review Article Immunomodulatory Role of Cytokines in Periodontal Disease Batool Hassan Al-Ghurabi*, Maha Adel Mahmood, Zainab A. Aldhaher, Sahar Hashim Al-Hindawi Adv. life sci., vol. 11,...

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD