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Filename: controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
File: /var/www/html/index.php
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File: /var/www/html/application/controllers/Detail.php
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Function: _error_handler
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Many applications using drug-carrying biomedical materials require on-demand, localized delivery of multiple therapeutic agents in precisely controlled and patient-specific time sequences, especially after assembly of the delivery vehicles; however, creating such materials has proven extremely challenging. Here, we report a novel strategy to create polypeptide multilayer films integrated with capsules as vehicles for co-delivery of multiple drugs using layer-by-layer self-assembly technology. Our approach allows the multilayered polypeptide nanofilms and preimpregnated capsules to assemble into innovative biomedical materials with high and controllable loading of multiple drugs at any time postpreparation and to achieve pH-responsive and sustained release. The resulting capsule-integrated polypeptide multilayer films effectively co-deliver various drugs with very different properties, including proteins (e.g., growth factors) and nanoparticles, achieving bovine serum albumin loading of 80 μg cm and release of 2 weeks, and histone loading of 100 μg cm and release of 6 weeks; which also enable Staphylococcus aureus killing efficacy of 83% while maintaining osteoblast viability of >85% with silver nanoparticle delivery; and >5-fold cell adhesion and proliferation capability with live cell percentage of >90% via human recombinant bone morphogenetic protein 2 delivery. The successful development of such fascinating materials can not only function as advanced nanocoatings to reduce two major complications of orthopedic bone injuries (i.e., infection and delayed bone regeneration) but also provide new insights into the design and development of multifunctional materials for various other biomedical applications.
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http://dx.doi.org/10.1021/acsami.8b17264 | DOI Listing |
Methods
December 2024
Center for Research Innovation and Biomedical Informatics, Faculty of Medical Technology, Mahidol University, Bangkok 10700, Thailand. Electronic address:
Identifying angiotensin-I-converting enzyme (ACE) inhibitory peptides accurately is crucial for understanding the primary factor that regulates the renin-angiotensin system and for providing guidance in developing new potential drugs. Given the inherent experimental complexities, using computational methods for in silico peptide identification could be indispensable for facilitating the high-throughput characterization of ACE inhibitory peptides. In this paper, we propose a novel deep stacking-based ensemble learning framework, termed Deepstack-ACE, to precisely identify ACE inhibitory peptides.
View Article and Find Full Text PDFBiomed Mater
December 2024
Shaheed Beheshti University of Medical Sciences, No 53 west ghobadian street, Tehran, 1516745811, Iran (the Islamic Republic of).
The combining of therapeutic agents with electrospun nanofibers boosts their regeneration potential; therefore, Researchers have increasingly turned towards the development of electrospun nanofiber scaffolds to encapsulate or surface-adsorb biological payloads, such as cytokines, exosomes, peptides, nucleic acids, and enzymes. Due to their high surface-to-volume ratio, ease of manufacturing, and drug-loading capacity, electrospun nanofibers are hopeful in tissue engineering and scaffold fabrication. Electrospun multilayer scaffolds offer a promising construction for preserving the integrity and bioactivity of therapeutic factors while permitting the controlled and prolonged release of biomolecules into the environment.
View Article and Find Full Text PDFSci Rep
December 2024
Eye School, Chengdu University of Traditional Chinese Medicine, Chengdu, 610000, Sichuan Province, China.
Diabetic macular edema (DME) is a common complication of diabetes that can lead to vision loss, and anti-vascular endothelial growth factor (anti-VEGF) therapy is the standard of care for DME, but the treatment outcomes vary widely among patients. This study collected optical coherence tomography (OCT) images and clinical data from DME patients who received anti-VEGF treatment to develop and validate deep learning (DL) models for predicting the anti-VEGF outcomes in DME patients based on convolutional neural network (CNN) and multilayer perceptron (MLP) combined architecture by using multimodal data. An Xception-MLP architecture was utilized to predict best-corrected visual acuity (BCVA), central subfield thickness (CST), cube volume (CV), and cube average thickness (CAT).
View Article and Find Full Text PDFJ Control Release
January 2025
i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal; INEB - Instituto de Engenharia Biomédica, Universidade do Porto, Rua Alfredo Allen 208, 4200-135 Porto, Portugal; IUCS-CESPU - Instituto Universitário de Ciências da Saúde, Rua Central de Gandra 1317, 4585-116 Gandra, Portugal. Electronic address:
Int J Biol Macromol
January 2025
College of Biosystems Engineering and Food Science, National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou 310058, China; Zhejiang University-Wuxi Xishan Modern Agriculture Joint Research Center, Wuxi 214117, China; Zhejiang University-Wuxi Xishan Modern Agriculture Joint Research Center, Wuxi 214117, China. Electronic address:
Oral intake of probiotics is a promising approach to alleviate colitis. However, environmental sensitivity of the gastrointestinal tract and poor adhesion of probiotics to the intestine hamper the remedial effects. In this study, a simple yet effective novel probiotic multilayer coating consisting of Fe-protocatechuic acid (PCA) crosslinked network and Ca-induced sodium alginate (SA) for arming Lactiplantibacillus plantarum (LP) was developed.
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