Background: Bone defect healing is a multidimensional procedure with an overlapping timeline that involves the regeneration of bone tissue. Due to bone's ability to regenerate, the vast majority of bone abnormalities can be restored intuitively under the right physiological conditions. The goal of this study is to examine the immunohistochemistry of bone sialoprotein in order to determine the effect of local application of bone sialoprotein on the healing of a rat tibia generated bone defect. Materials and Methods: In this experiment, 48 albino male rats weighing 300-400 grams and aged 6-8 months will be employed under controlled temperature, drinking, and food consumption settings. The animals will be subjected to a surgical procedure on the medial side of the tibiae bone, with the bone defect repaired with absorbable hemostatic material in the control group (12 rats). The experimental group (12 rats) will be treated with local administration of 30 μl bone sialoprotein fixed by absorbable hemostatic sponge. After surgery, the rats will be slaughtered at 7, 14, and 28 days (four rats for each period). Results: Immunohistochemical analysis of bone sialoprotein by stromal cells reveal a substantial difference between the bone sialoprotein group and the control group. Conclusion: The study concludes that local application of bone sialoprotein could be a successful therapeutic treatment for bone injuries; these findings are encouraging for future clinical use.
Objectives: To evaluate the families’ attitudes toward environment pollution, and determine the relationship
between families’ attitudes towards environment pollution and their demographic characteristics of age,
education, type of family, and socioeconomic status.
Methodology: A descriptive design is carried throughout the present study to evaluate families’ attitudes toward
environment pollution for the period of October 5th2013 to May 7th2014. A non-probability "purposive" sample of
(110) families’ is selected. The sample is comprised of two groups; (75) urban families’ and (35) rural ones. An
evaluation tool is designed and constructed for the purpose of the study. It is consisted of (4) main parts;
dem
Warm mix asphalt (WMA) is relatively a new technology which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt HMA. In the present work, six asphalt concrete mixtures were produced in the mix plant (1 ton each) in six different batches. Half of these mixes were WMA and the other half were HMA. Three types of fillers (limestone dust, Portland cement and hydrated lime) were used for each type of mix. Samples were then taken from these patches and transferred to lab for performance testing which includes: Marshall characteristics, moisture susceptibility (indirect tension test), resilient modulus, permanent deformation (axial repe
... Show MoreWarm mix asphalt (WMA) is relatively a new technology which enables the production and compaction of asphalt concrete mixtures at temperatures 15-40 °C lower than that of traditional hot mix asphalt HMA. In the present work, six asphalt concrete mixtures were produced in the mix plant (1 ton each) in six different batches. Half of these mixes were WMA and the other half were HMA. Three types of fillers (limestone dust, Portland cement and hydrated lime) were used for each type of mix. Samples were then taken from these patches and transferred to lab for performance testing which includes: Marshall characteristics, moisture susceptibility (indirect tension test), resilient modulus, permanent deformation (axial repeated load test)
... Show MoreBackground: Practicing self-medication is common and a worrisome issue because of irrational drug use. This study aimed to evaluate self-medication knowledge and views among the final year pharmacy students in Iraq. Methods: A cross-sectional descriptive study was conducted from December 2018 to January 2019. A pre-validated and self-administered questionnaire was recruited to survey pharmacy students at the University of Baghdad and Al-Rafedain University College. The Statistical Package for the Social Sciences version 20 (SPSS v. 20) software used to save and analyze the data. Results expressed as numbers and percentages. Results: A total of 344 students (response rate: 94.24%) with a mean age of 22.10 years includ
... Show MoreA new, simple and sensitive method was used forevaluation of propranolol withphosphotungstic acidto prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on reaction between propranolol and phosphotungstic acid in an aqueous medium to obtain a yellow precipitate. Optimum parameters was studied to increase the sensitivity for developed method. A linear range for calibration graph was 0.007-13 mmol/L for cell A and 5-15 mmol/L for cell B, and LOD 207.4792 ng/160 µL and 1.2449 µg/160 µL respectively to cell A and cell B with correlation coefficient (r) 0.9988 for cell A, 0.9996 for cell B, RSD% was lower than 1%, (n=8) for the
... Show MoreThis research aims to develop new spectrophotometric analytical method to determine drug compound Salbutamol by reaction it with ferric chloride in presence potassium ferricyanide in acid median to formation of Prussian blue complex to determine it by uv-vis spectrophotmetric at wavelengths rang(700-750)nm . Study the optimal experimental condition for determination drug and found the follows: 1- Volume of(10M) H2SO4 to determine of drug is 1.5 ml . 2- Volume and concentration of K3Fe(CN)6 is 1.5 ml ,0.2% . 3- Volume and concentration of FeCl3 is 2.5ml , 0.2%. 4- Temperature has been found 80 . 5- Reaction time is 15 minute . 6- Order of addition is (drug + K3Fe(CN)6+ FeCl3 + acid) . Concentration rang (0.025-5 ppm) , limit detecti
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.