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

Background: Although bleaching is typically considered a safe procedure, various investigations have found minor negative effects and changes in mineral composition. The aim was to Evaluate and compare the efficacy of using Nanohydroxyapatite serum on surface microhardness of enamel surface before and after bleaching with chemically cured Boost bleaching. Material and methods: ten sound human permanent upper and lower premolar teeth were used and their roots were removed 2 mm apically to the cementoenamel junction, the crowns were sectioned mesiodistally into two halves buccal and lingual/palatal, the buccal surface was further subdivided into two halves. The samples were embeded in an acrylic resin, resulting in 30 specimens divide

Beyond the immediate content of speech, the voice can provide rich information about a speaker's demographics, including age and gender. Estimating a speaker's age and gender offers a wide range of applications, spanning from voice forensic analysis to personalized advertising, healthcare monitoring, and human-computer interaction. However, pinpointing precise age remains intricate due to age ambiguity. Specifically, utterances from individuals at adjacent ages are frequently indistinguishable. Addressing this, we propose a novel, end-to-end approach that deploys Mozilla's Common Voice dataset to transform raw audio into high-quality feature representations using Wav2Vec2.0 embeddings. These are then channeled into our self-attentio

The aims of this study are to explore the commercial artifacts in the following three kinds of vegetables oils, Nigella Sativa, Trigonella foenum-graecum Linn,and Zingiber officinale. These oils have been very popular medicinal plants which are commonly used in traditional medicine .These commercial oils have been compared with the extracts of these plants.
The physical properties of extracts and commercial oils of these plants have been stuied. We observed that the refractive index of the plants matches and non-significant, while specific gravity of Nigella Sativa has similar specific gravity in both extracts and commercial oil in contrast with Trigonella foenum Linn,and Zingiber officinale and we found significant difference (P&lt

Background: Acute coronary syndrome (ACS) is a common disease, and a major determinant of morbidity and mortality in all races. The pleiotropic effects of the receptor activator of nuclear factor-kappa B ligand (RANKL) such as modulation of cell survival, mineralization and inflammation, make it an interesting candidate mediator in the progression and destabilization of atherosclerotic lesions.Objectives: This study was performed to investigate the role of RANKL in the pathogenesis of ACS.Methods: The levels of RANKL were measured by ELISA method in sera of 60 ACS patients, 31 patients with unstable angina (UA) and 29 patients with myocardial infarction (MI) in comparison with 20 apparently healthy controls.Results: Current data indicate