In the field of implantology, peri-implantitis is still a common complication of implant failure. Similar to periodontal disease, this kind of pathological condition is characterized by inflammation of the tissues surrounding dental implants or fillings. The sources of infection have been shown to be chronic periodontitis and poor maintenance of the communion. A thorough examination of the intricate components of peri-implantitis was sought in this review in order to identify common characteristics of the disease with regard to bacteria, biofilm formation, host immunological responses, diagnostic tools, and therapeutic treatments. The aim of this study was to provide a detailed overview of the different bacterial species associated with peri-implantitis, a clinical condition similar to periodontitis, characterized by a higher prevalence of staphylococci and enteric bacteria. The study underscores the importance of employing sophisticated diagnostic methods like cone beam computed tomography. It covers a range of therapeutic approaches including surgical and non-surgical techniques as well as strategies stressing host-modification and photodynamic treatment. The study was conducted using pertinent publications from scientific databases, including Scopus, Google Scholar, PubMed, and Web of Science. We searched these databases using the following terms: periodontitis, microbial, dental implants, peri-implantitis, and biofilm formation.
Sixty samples of commercially available contact lens solutions were collected from students at the Pharmacy College/Baghdad University. The types of lenses used varied from medical to cosmetic. They were cultured to diagnose any microbial contamination within the solutions. Both used and unused solutions were subject for culturing. Thirty six (60%) used samples showed bacterial growth, fungal growth was absent. Pseudomonas aeruginosa accounts for the highest number of isolates (25%) followed by E. coli (21%), Staphylococcus epidermidis (6.6%), Pseudomonas fluorescence (5%) and Proteus mirabilis (1.6%) respectively. Only one (1) unused (sealed) sample showed growth of P. fluorescence.
... Show MorePhenol condensed with β-keto esters via Pechmann condensation to form derivatives of Coumarin in various reaction conditions by two ways. Present paper is comparative study of synthesis Coumarin with the yield of product , reaction time and reaction conditions.
The occurrences of invasive candidiasis has increased over the previous few decades. Although Candida albicans considers as one of the most common species of organisms, that cause acquired fungal infections. Candida albicans is an opportunistic fungal pathogen and inherent in as a lifelong, the yeast is present in healthy individuals as a commensal, and can reside harmlessly in human body. However, in immuno-compromised individuals, the fungus can invade tissues, producing superficial infections and, in severe cases, life-threatening systemic infections. This review wills emphasis on virulence factor of C. albicans including (adhesion, invasion, candida proteinase, and phenotypic switching and biofilm formation. I
... Show MoreThe finite element approach is used to solve a variety of difficulties, including well bore stability, fluid flow production and injection wells, mechanical issues and others. Geomechanics is a term that includes a number of important aspects in the petroleum industry, such as studying the changes that can be occur in oil reservoirs and geological structures, and providing a picture of oil well stability during drilling. The current review study concerned about the advancements in the application of the finite element method (FEM) in the geomechanical field over a course of century.
Firstly, the study presented the early advancements of this method by development the structural framework of stress, make numerical computer solution
... Show MoreWellbore instability is a significant problem faced during drilling operations and causes loss of circulation, caving, stuck pipe, and well kick or blowout. These problems take extra time to treat and increase the Nonproductive Time (NPT). This paper aims to review the factors that influence the stability of wellbores and know the methods that have been reached to reduce them. Based on a current survey, the factors that affect the stability of the wellbore are far-field stress, rock mechanical properties, natural fractures, pore pressure, wellbore trajectory, drilling fluid chemicals, mobile formations, naturally over-pressured shale collapse, mud weight, temperature, and time. Also, the most suitable ways to reduce well
... Show MoreThis study aimed to investigate the feasibility of treatment actual potato chips processing wastewater in a continuously operated dual chambers microbial fuel cell (MFC) inoculated with anaerobic sludge. The results demonstrated significant removal of COD and suspended solids of more than 99% associated with relatively high generation of current and power densities of 612.5 mW/m3 and 1750 mA/m3, respectively at 100 Ω external resistance.
The relationships between the related parties constitute a normal feature of trading and business processes. Entities may perform parts of their activities through subsidiary entities, joint ventures and associate entities. In these cases, the entity has the ability to influence the financial and operating policies of the investee through control, joint control or significant influence, So could affect established knowledge of transactions and balances outstanding, including commitments, and relationships with related to the evaluation of its operations by users of financial statements, including the risks and opportunities facing the entity assess the parties. So research has gained importance of the importance of the availability
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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