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Salivary lactate dehydrogenase and salivary total protein as potential biomarkers for screening periodontal disease
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Abstract Background: Timely diagnosis of periodontal disease is crucial for restoring healthy periodontal tissue and improving patients’ prognosis. There is a growing interest in using salivary biomarkers as a noninvasive screening tool for periodontal disease. This study aimed to investigate the diagnostic efficacy of two salivary biomarkers, lactate dehydrogenase (LDH) and total protein, for periodontal disease by assessing their sensitivity in relation to clinical periodontal parameters. Furthermore, the study aimed to explore the impact of systemic disease, age, and sex on the accuracy of these biomarkers in the diagnosis of periodontal health. Materials and methods: A total of 145 participants were categorized into three groups based on their basic periodontal examination index, with 20 in the periodontally healthy group, 50 in the gingivitis group, and 75 in the periodontitis group. Salivary LDH was measured using the rate of nicotinamide adenine dinucleotide (NADH) oxidation, to measure the kinetics of LDH activity, while total protein was measured using the Lowry method. Descriptive and analytical statistical analyses were performed to examine the associations between the variables and biomarkers. Results: The results of the study demonstrated that salivary LDH was 72% sensitive, while salivary total protein was 78% sensitive in correlation to clinical periodontal parameters. The accuracy of the test was not influenced by sex, but age had a significant effect on both biomarkers, particularly LDH. Systemic disease was another factor that significantly affected the accuracy of the test. Conclusions: Although salivary LDH and total protein show promise as biomarkers for screening periodontal disease, their interpretation may be impacted by age and systemic disease.

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Publication Date
Tue Jun 15 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation and Characterization of Self-Microemulsifying Drug Delivery System of Tacrolimus
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Abstract

The present investigation aimed to formulate a liquid self-microemulsifying drug delivery system (SMEDDS) of tacrolimus to enhance its oral bioavailability by improving its dispersibility and dissolution rate. Four liquid SMEDDS were prepared using maisine CC as oil phase, labrasol ALF as surfactant and transcutol HP as co-surfactant based on the solubility studies of tacrolimus in these components. The phase behavior of the components and the area of microemulsion were evaluated using pseudoternary phase diagrams. The formulations were also assessed for thermodynamic stability, robustness to dilution, self-emulsification time, drug content, globule size and polydispersity index. The prepared SMEDDS formulations exhibi

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Publication Date
Wed Jan 19 2022
Journal Name
Asian Journal Of Water, Environment And Pollution
Air Pollution: A Study of Its Concept, Causes, Sources and Effects
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Air pollution is very important topic for those interested in studying the environment because of its importance and the damage caused by it to human, animal and plant life. This research addresses the concept of air pollution, its causes, and its danger, and sheds light on the influence of climate elements on environmental pollution and the effect of temperature, rain, humidity, wind direction and speed, and atmospheric pressure on the increase or decrease of air pollution. This research discusses the sources of air pollution, including natural ones, including dust, smoke resulting from fires, erupting volcanoes, and others, including those resulting from human uses such as the use of fuel and others. The research addressed the dam

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Publication Date
Fri Mar 12 2021
Journal Name
Sensors
A Robust Handwritten Numeral Recognition Using Hybrid Orthogonal Polynomials and Moments
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Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

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Publication Date
Fri Dec 01 2023
Journal Name
Russian Journal Of Bioorganic Chemistry
A Brief Review on Schiff Base, Synthesis, and Their Antimicrobial Activities
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Publication Date
Tue Mar 01 2022
Journal Name
Malaysian Journal Of Medicine & Health Sciences
Detection of Iron and Ferritin in Diabetes Mellitus Type 2 Patients
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Publication Date
Wed May 26 2021
Journal Name
Communications In Mathematical Biology And Neuroscience
Modelling and stability analysis of the competitional ecological model with harvesting
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The interplay of predation, competition between species and harvesting is one of the most critical aspects of the environment. This paper involves exploring the dynamics of four species' interactions. The system includes two competitive prey and two predators; the first prey is preyed on by the first predator, with the former representing an additional food source for the latter. While the second prey is not exposed to predation but rather is exposed to the harvest. The existence of possible equilibria is found. Conditions of local and global stability for the equilibria are derived. To corroborate our findings, we constructed time series to illustrate the existence and the stability of equilibria numerically by varying the different values

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Publication Date
Sat Jan 01 2022
Journal Name
Lecture Notes In Electrical Engineering
Dynamics Modeling and Motion Simulation of a Segway Robotic Transportation System
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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Concepts of statistical learning and classification in machine learning: An overview
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Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

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Publication Date
Mon Dec 25 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Spectrophotometric Determination of Cefixime Following Simple Diazotization and Coupling with ?-Naphthol
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Cefixime (CFX) was treated with sodium nitrite and hydrochloric acid for diazotization reaction followed by coupling with ?-Naphthol in alkaline medium to form, a yellow colored azo dye compound which exhibits maximum absorption (?max) at 412 nm where the concentration of (CFX) was determined spectrophotometrically. The optimum reaction conditions and other analytical parameters were evaluated. Beer’s law was obeyed in the concentration range of (1-20) ?g.mL-1 with a molar absorptivity of 34870.5 L.mol-1.cm-1. The limit of detection was found to be 0.1090 ?g.mL-1 and the Sandell's sensitivity value was 0.0130 ?g.cm-2. The proposed method could be successfully applied to

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Cognitive bias and its relation to emotional thinking among university students
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The study aims to identify the cognitive bias and the level of emotional thinking among university students, besides, identifying the significant differences between male and female students regarding those two variables, and determine if there is a correlation between cognitive bias and emotional thinking. To this end, two scales were adopted to collect needed data: cognitive bias scale designed by (Al-any, 2015), composed of (14) items, and emotional thinking scale designed by (Abdu Allah, 2017), consisted of (27) items. These two scales were administered to (140) students composed the study sample. They were chosen from four different colleges at Al-mustansiriyah University for the academic year (2017-1018). The findings revealed that

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