Background: It had been found that passive smoking may have the same harmful effect as tobacco cigarettes smoking. Aims: This study was conducted to determine the effect of passive smoking on salivary glutathione peroxidase and selenium in relation to dental caries severity. Settings and Design: The sample consisted of 120 children aged 5 years old, classified into four groups according to the number of cigarettes smoked by their fathers daily: Passive smoking children of 5-10 cigarettes, those of 10–15 cigarettes daily, those of 15–20 cigarettes daily and non-passive smoking children of no smokers indoor (the control group). The sample was further classified according to dental caries severity into three groups: mild (DMFS values <4

Background: Any child with Down's syndrome does not develop in the same manner as normal child. Therefore, the child should not be viewed as being like everyone else. Developmental enamel defects in primary teeth have been found at least twice as frequently in disabled children as in control children. Down's syndrome consumed protein more than the recommended daily allowance compared to other disabled groups. Therefore, the aim of this study was to investigate developmental defects of enamel and their relations to nutrient intake among Down's syndrome children in comparison to normal children. Materials and Methods: A sample consisted of fifty institutionalized Down's syndrome children (study group) and 50 normal children (control group)

A case–control study (80 patients with chronic hepatitis B virus [HBV] infection and 96 controls) was performed to evaluate the association of an IL12A gene variant (rs582537 A/C/G) with HBV infection. Allele G showed a signifcantly lower frequency in patients compared to controls (31.2 vs. 46.9%; probability [p]=0.009; corrected p [pc]=0.027) and was associated with a lower risk of HBV infection (odds ratio [OR]=0.49; 95% confdence interval [CI]=0.29–0.83). A similar lower risk was associated with genotypes CG (17.5 vs. 29.2; OR=0.25; 95% CI=0.08–0.81; p=0.02) and GG (10.0 vs. 16.7; OR=0.25; 95% CI=0.07–0.91; p=0.036), but the pc value was not signifcant (0.12 and 0.126, respec‑ tively). Serum IL35 levels showed signifcant difere

Biofilms formation by pathogens microbial Control considered important in medical research because it is the hazarded virulence factor leading to becoming difficult to treat because of its high resistance to antimicrobials. Glycopeptide antibiotic a (Vancomycin) and the commercial bacteriocin (Nisin A) were used to comparative with purification bacteriocin (MRSAcin) against MRSA biofilm. One hundred food samples were collected from Baghdad markets from July 2016 to September 2016, including (cheese, yogurt, raw milk, fried meat, grilled meat, and beef burger). All samples were cultures; S. aureus was confirmation by macroscopic culture and microscopic examination, in addition to biochemical tests. Methicillin resistance S. asureus (

In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior

BACKGROUND: Preeclampsia (PE) is a possible etiology of obstetrical and neonatal complications which are increased in resource-limited settings and developing countries. AIM: We aimed to find out the prevalence of PE in Iraqi ladies and specific outcomes, including gestational weight gain (GWG), cesarean section (CS), preterm delivery (PD), and low birth weight (LBW). METHODS: All singleton pregnant women visiting our tertiary center for delivery were involved over 3 years. PE women were compared with non-PE ladies. Complete history and examination were done during pregnancy and after delivery by the attending obstetrician and neonatologist with full documentation in medical records. RESULTS: PE prevalence was 4.79

The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue