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The implant-retained overdenture has been advocated as an effective method of restoring the edentulous patient with an appliance that offers significant benefits over conventional prosthetics. However, the success and survival of such appliances have been shown to vary considerably, depending on which jaw is treated: implants supporting overdentures in the maxilla have a significantly higher failure rate. The restoration also requires considerable maintenance, which is both time consuming and costly. The purpose of this paper is to look at common restorative complications and maintenance problems following the placement of dental implants to support an overdenture. A number of implant systems have been reviewed and the results of the authors' clinical experiences with referred and their own cases are reported.

ObjectiveTo prepare a novel nanoemulsion- Carbopol® 934 gel for Eugenol, in order to prevent the periodontitis.Material and methodsSpontaneous emulsification method was used for the preparation of nanoemulsion in which it contain Eugenol (oil phase), Tween-80 (surfactant), and PEG (co-surfactant). To the development of best nanoemulsion, three-factor three-level central composite design was used in which %oil; %Smix and % water were optimized as independent variables. An optimized–nanoemulsion were converted to nanoemulsion–Carbopol® 934 gel.Results5.5% oil, 35.5% Smix and 59.0% water were optimized as independent and dependent variables. Finally dependent variables optimized as a particle size (nm), PDI and %transmittance were observed 79.92 ± 6.33 nm, 0.229 ± 0.019, and 98.88 ± 1.31% respectively. The values of final results for dependent variables like particle size (nm), PDI and % transmittance were evaluated as 79.92 ± 6.33 nm, 0.229 ± 0.019, and 98.88 ± 1.31%, respectively. TEM and SEM showed a spherical shape of developed nanoemulsion with refractive index (1.63 ± 0.038), zeta potential (−19.16 ± 0.11), pH (7.4 ± 0.06), viscosity (34.28 ± 6 cp), and drug content of 98.8 ± 0.09%. After that a final optimized EUG–NE–Gel was assessed on the basis of their pH measurement, drug content, syringeability, and mucoadhesion on the goat buccal mucosa. Optimized EUG-NE-Gel (Tween-80 and Carbopol® 934 used) showed the results, to improve the periodontal drug delivery of EUG in future.ConclusionEUG-NE-Gel showed a significant role in anti-inflammatory activity, analgesic, and anesthetic, antibacterial, and treatment of periodontal disease.

Rub & Farhan Jalees Ahmad (2019) Brain-targeted glycyrrhizic-acid-loaded surface decorated nanoparticles for treatment of cerebral ischaemia and its toxicity assessment,

Epidermolysis bullosa (EB) is a genetic disease associated with fragility and bullous lesions of the skin and mucous membranes. There are various patterns of inheritance and histopathology. The disease is associated with systemic and oral manifestations, among which may be dental decay necessitating oral rehabilitation. The aim of this article is to present the course of the condition in a child with dystrophic EB and also to report an association between EB, hypodontia, and supernumerary teeth which has not been reported earlier in literature.

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The present study explores the efficacy of Machine Learning and Artificial Neural Networks in age assessment using the root length of the second and third molar teeth. A dataset of 1000 panoramic radiographs with intact second and third molars ranging from 12 to 25 years was archived. The length of the mesial and distal roots was measured using ImageJ software. The dataset was classified in three ways based on the age distribution: 2–Class, 3–Class, and 5–Class. We used Support Vector Machine (SVM), Random Forest (RF), and Logistic Regression models to train, test, and analyze the root length measurements. The mesial root of the third molar on the right side was a good predictor of age. The SVM showed the highest accuracy of 86.4% for 2–class, 66% for 3–class, and 42.8% for 5–Class. The RF showed the highest accuracy of 47.6% for 5–Class. Overall the present study demonstrated that the Deep Learning model (fully connected model) performed better than the Machine Learning models, and the mesial root length of the right third molar was a good predictor of age. Additionally, a combination of different root lengths could be informative while building a Machine Learning model.

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