KE Sharquie, KI Al-Hamdi, AA Noaimi, AA Al-Mohammadi, J Clin Exp Invest www. clinexpinvest. org Vol, 2011 - Cited by 1

Background. After tooth extraction, alveolar bone resorption is inevitable. This clinical phenomenon challenges dental surgeons aiming to restore esthetic and function. Alveolar ridge preservation can be applied to minimize dimensional changes with a new socket grafting material, an autogenous dentin graft, produced by mechanically and chemically processing natural teeth. This study assessed the safety and efficacy of using autogenous dentin biomaterial in alveolar ridge preservation. Materials and Methods. Patients with nonrestorable maxillary anterior teeth bounded by natural sound teeth were included in this study. After a detailed clinical and tomographic examination, eligibl

Purpose: The purpose of this study was to compare the outcomes of 2 different anesthetic techniques (local infiltration vs infraorbital nerve block) for eliminating pain during apical surgeries that are associated with extensive periapical pathology in the anterior maxilla. Materials and Methods: Patients were randomly divided into 2 groups: patients in group I were anesthetized labially by local infiltration injections, whereas those in group II received a single infraorbital nerve block. Palatal injections were given for the 2 groups. Once the pain was initiated during surgery, the procedure was discontinued until profound anesthesia was secured. The studied variables were age, gender, onset of anesthesia, operative time, and intraoperati

Background. After tooth extraction, alveolar bone resorption is inevitable. This clinical phenomenon challenges dental surgeons aiming to restore esthetic and function. Alveolar ridge preservation can be applied to minimize dimensional changes with a new socket grafting material, an autogenous dentin graft, produced by mechanically and chemically processing natural teeth. This study assessed the safety and efficacy of using autogenous dentin biomaterial in alveolar ridge preservation. Materials and Methods. Patients with nonrestorable maxillary anterior teeth bounded by natural sound teeth were included in this study. After a detailed clinical and tomographic examination, eligible participants were randomly allocated into two groups

Mixed ligand complexes of bivalent metal ions, viz; Co(II), Ni(II), Cu(II) and Zn(II) of the composition [M(A)2((PBu3)2]in(1:2:2)(M:A:(PBu3). molar ratio, (where A- Anthranilate ion ,(PBu3)= tributylphosphine. M= Co(II),Ni(II),Cu(II) and Zn(II). The prepared complexes were characterized using flame atomic absorption, by FT-IR, UV/visible spectra methods as well as magnetic susceptibility and conductivity measurements. The metal complexes were tested in vitro against three types of pathogenic bacteria microorganisms: (Staphylococcus, Klebsiella SPP .and Bacillas)to assess their antimicrobial properties. Results. The study shows that all complexes have octahedral geometry; in addition, it has high activity against tested bacteria. Based on th

Penetrating cardiac injuries caused by nail guns are exceedingly rare but often life-threatening, with reports showing an increasing trend. We described the case of an adolescent male who sustained accidental cardiac penetration by an iron nail while performing carpentry work. Rapid referral to a specialized cardiac center enabled timely surgical intervention, illustrating the pivotal role of early recognition, expedited transfer, and expert management in optimizing outcomes. This case also highlights the grave risks associated with the employment of minors in hazardous occupational settings, where exposure to unsafe environments may lead to catastrophic consequences.

Background : The hepatopulmonary syndrome (HPS) is defined as the triad of liver disease, arterial deoxygenation, and pulmonary vascular dilatation. The reported prevalence of HPS in cirrhotic patients varies between 5% -17.5%.Objective : To estimate the prevalence of hepatopulmonary syndrome among patients with chronic liver disease and portal hypertension and to study the correlation between HPS and the severity of liver disease.Patients and methods : Thirty patients were studied for the presence of HPS using transthoracic contrast echocardiography for detection of pulmonary vasodilatation. Arterial oxygen saturation (SaO2) was determined in erect and supine position using a pulse oximeter , (SaO2 ≤ 92 % in supine position and/or a d

Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D