Optimization of the Manufacturing Process and Mechanical Evaluation of a Functionally Graded Biodegradable Composite Screw for Orthopedic Applications.

Background: Metal screws are commonly used for fracture fixations. However, the high modulus of elasticity relative to bones and releasing metallic ions by the metal screw needed a second surgery to remove the implant after the healing period. Furthermore, the removal of metal screws following the healing of the bone is a serious problem that can lead to refracture due to the presence of holes in the screw. Bioresorbable screws can overcome most of the problems associated with metallic screws which motivated research on manufacturing nonmetallic screws. Methods: In this study, three-layer poly L-lactic acid/bioactive glass composite screws were manufactured according to functionally graded material theory, by the forging process. All of the physical and chemical parameters in the manufacturing stages from making composite layers to the forging process were optimized to obtain suitable mechanical properties and durability off the screw in load-bearing positions. Results: The tri-layer composite screw with unidirectional, ±20° angled, and random fibers orientation from core to shell shows a flexural load of 661.5 ± 20.3 (N) with a decrease about 31% after 4-week degradation. Furthermore, its pull-out force was 1.8 ± 0.1 (N) which is considerably more than the degradable polymeric screws. Moreover, the integrity of the composite screws was maintained during the degradation process. Conclusions: By optimizing the manufacturing process and composition of the composite and crystallinity, mechanical properties (flexural, torsion, and pull-out) were improved and making it a perfect candidate for load-bearing applications in orthopedic implants. Improving the fiber/matrix interface through the use of a coupling agent was also considered to preserve the initial mechanical properties. The manufactured screw is sufficiently robust enough to replace metals for orthopedic load-bearing applications.

Fabrication and characterization of bilayer scaffolds made of decellularized dermis/nanofibrous collagen for healing of full-thickness wounds.

Skin tissue engineering has progressed from simple wound dressings to biocompatible materials with desired physico-chemical properties that can deliver regenerative biomolecules. This study describes using a novel biomimetic hybrid scaffold of decellularized dermis/collagen fibers that can continuously deliver stromal cell-derived factor-1 alpha (SDF-1α) for skin regeneration. In diabetic rat models, the idea that sustained SDF-1α infusion could increase the recruitment of CXCR4-positive cells at the injury site and improve wound regeneration was investigated. The morphology of the scaffold, its biocompatibility, and the kinetics of SDF-1 release were all assessed. SDF-1α was successfully incorporated into collagen nanofibers, resulting in a 200-h continuous release profile. The microscopic observations exhibited that cells are attached and proliferated on proposed scaffolds. As evaluated by in vivo study and histological examination, fabricated scaffold with SDF-1α release capacity exhibited a remarkably more robust ability to accelerate wound regeneration than the control group. Besides, the SDF-1α-loaded scaffold demonstrated functional effects on the proliferation and recruitment of CD31 and CXCR4-positive cells in the wound bed. Additionally, no adverse effects such as hyperplasia or scarring were found during the treatment period. It may be concluded that the fabricated hybrid scaffold based on natural polymer opens up a new option for topical administration of bioactive molecules. We believe the SDF-1α-loaded hybrid scaffold has promise for skin tissue engineering.

Leveraging artificial intelligence in ischemic stroke imaging.

Artificial intelligence (AI) is having a disruptive and transformative effect on clinical medicine. Prompt clinical diagnosis and imaging are critical for minimizing the morbidity and mortality associated with ischemic strokes. Clinicians must understand the current strengths and limitations of AI to provide optimal patient care. Ischemic stroke is one of the medical fields that have been extensively evaluated by artificial intelligence. Presented herein is a review of artificial intelligence applied to clinical management of stroke, geared toward clinicians. In this review, we explain the basic concept of AI and machine learning. This review is without coding and mathematical details and targets the clinicians involved in stroke management without any computer or mathematics' background. Here the AI application in ischemic stroke is summarized and classified into stroke imaging (automated diagnosis of brain infarction, automated ASPECT score calculation, infarction segmentation), prognosis prediction, and patients' selection for treatment.

Artificial Intelligence in the Management of Glioma: Era of Personalized Medicine.

Purpose: Artificial intelligence (AI) has accelerated novel discoveries across multiple disciplines including medicine. Clinical medicine suffers from a lack of AI-based applications, potentially due to lack of awareness of AI methodology. Future collaboration between computer scientists and clinicians is critical to maximize the benefits of transformative technology in this field for patients. To illustrate, we describe AI-based advances in the diagnosis and management of gliomas, the most common primary central nervous system (CNS) malignancy. Methods: Presented is a succinct description of foundational concepts of AI approaches and their relevance to clinical medicine, geared toward clinicians without computer science backgrounds. We also review novel AI approaches in the diagnosis and management of glioma. Results: Novel AI approaches in gliomas have been developed to predict the grading and genomics from imaging, automate the diagnosis from histopathology, and provide insight into prognosis. Conclusion: Novel AI approaches offer acceptable performance in gliomas. Further investigation is necessary to improve the methodology and determine the full clinical utility of these novel approaches.