Nature Reviews Disease Primers is a peer-reviewed medical journal published by Nature Portfolio. It was established in 2015. The editor-in-chief is Clemens Thoma. The journal publishes broad review articles about disease areas, offering a global overview of the field and outlining "key open research questions". Current impact factor is 76.9.
This study evaluates novel bioabsorbable scaffolds composed of poly-L-lactic acid and amorphous calcium phosphate nanoparticles in porcine coronary arteries, finding that these scaffolds exhibit better lumen patency, reduced stent recoil, and greater radial strength compared to traditional PLLA scaffolds over six months.
This research developed biocomposites based on a ternary system of softwood Kraft lignin, poly-L-lactic acid (PLLA), and polyethylene glycol (PEG), demonstrating that PEG enhances flexibility while lignin increases stiffness, and introduced a novel approach using a transesterification catalyst to improve PLLA and PEG compatibility, resulting in a well-balanced, high-performance material.
This study explores creating a living bone allograft using the perfusion/decellularization/recellularization (PDR) technique on vascularized porcine bone grafts, successfully preserving the extracellular matrix and vascular network while promoting cell growth and differentiation, offering potential for future in vivo reimplantation for large bone defect repairs.
This study demonstrates that using poly(epsilon-caprolactone) (PCL) nanoneedle arrays, particularly with a height of 50 nm, as substrates can maintain the multipotency of bone marrow mesenchymal stem cells (BMMSCs) in vitro by promoting clustered growth and strong cell-cell interactions, offering insights into designing effective tissue engineering scaffolds.
By encouraging diverse perspectives and interdisciplinary approaches, FAIR seeks to address complex scientific challenges and drive breakthroughs that benefit society as a whole.
Nice poster! Convolutional Neural Networks (CNNs) are deep learning algorithms that mimic the human brain's visual processing to automatically learn and classify features from images, making them highly effective in applications like facial recognition, medical image analysis, and self-driving cars.
How do Recurrent Neural Networks (RNNs), particularly with the advancements of Long Short-Term Memory (LSTM) units and Gated Recurrent Units (GRUs), address the challenge of vanishing gradients to enhance tasks such as language translation, speech recognition, and stock price prediction by maintaining context and order in sequences of data?
Given the challenges associated with the hydrophobic nature of PVDF membranes, how do the incorporation of cellulose acetate (CA) and the modulation of PVDF enhance the antifouling properties and overall performance of β phase PVDF de blend membranes in wound healing applications?
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