Publications by authors named "Mohamed Elhakeem"
Article Synopsis
- * A deep learning model using convolutional neural networks (CNNs) was developed to predict the hemolytic activity of AMPs based on their sequences, represented through one-hot encoding.
- * The model was trained on multiple datasets and demonstrated strong performance, improving the prediction of hemolysis compared to previous methods, thus aiding in the design of safer AMPs for treating bacterial infections.
Study Design: Narrative review.
Objectives: The objectives of this study were to answer the following questions: (1) What is the quality of informed consent in spine surgery, including both neurosurgery and orthopaedic spine surgery? (2) What limitations impede the ability of surgeons to engage in effective shared decision-making (SDM) and obtain adequate informed consent? (3) What strategies and solutions may improve the quality of informed consent and SDM? (4) What factors decrease the incidence of litigation in spine surgery?
Methods: N/A.
Results: SDM is a collaborative process where patients are involved in their treatment choices through open communication about risks, alternatives, and postoperative expectations.
Hemolysis is a crucial factor in various biomedical and pharmaceutical contexts, driving our interest in developing advanced computational techniques for precise prediction. Our proposed approach takes advantage of the unique capabilities of convolutional neural networks (CNNs) and transformers to detect complex patterns inherent in the data. The integration of CNN and transformers' attention mechanisms allows for the extraction of relevant information, leading to accurate predictions of hemolytic potential.
View Article and Find Full Text PDFWaste incineration and coincineration plants in most European countries have frequently updated their flue gas cleaning systems, surpassing in most cases E.U. air emission standards.
View Article and Find Full Text PDFBackground: Identifying the molecular mechanisms of intrinsic aging is critical in developing modalities for reversal of cutaneous aging.
Objective: The objective was to evaluate the expression of epidermal Fas, epidermal thickness, collagen, and elastic fibers degeneration in unexposed skin of aged individuals compared with young ones.
Materials And Methods: Skin biopsies were taken from normal skin of the back of 22 old subjects (age range: 48-75 years) and 15 young subjects (age range: 18-28 years).