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1.
ACS Nano ; 2024 Jul 22.
Artículo en Inglés | MEDLINE | ID: mdl-39038287

RESUMEN

Indoor UV damage is a serious problem that is often ignored. Common glasses cannot filter UV rays well and have fragility and environmental issues. UV-shielding transparent wood (TW) holds promise, yet striking the right balance between blocking UV rays and allowing sufficient visible-light transmission poses a challenge. The pronounced capillary force, fueled by persistent moisture and extractives in wood, alongside the existence of multiphase interfaces, collectively hinder the uniform penetration of polymers and the effective dispersion of nanomaterials within the wood skeleton. Here, we incorporate high-pressure supercritical CO2 fluid-assisted impregnation (HSCFI) into fabricating UV-shielding TW. The supercritical CO2 pretreatment efficiently eliminates moisture and refines wood structure by extracting polar substances, resulting in a prominent 52.4% increase in average water permeability. Subsequently, this HSCFI method facilitates the infiltration of methyl methacrylate (MMA) monomer and Ce-ZnO nanorods (NRDs) into the refined anhydrous wood, leveraging the excellent solvency of supercritical CO2 for MMA. The impregnation rate of PMMA undergoes a substantial increase from 34.5 to 59.1%. With the robust UV-blocking capability of Ce-ZnO NRDs, thanks to dual-valence Ce doping widening the ZnO energy gap via the Burstein-Moss effect and their unique photoactive microstructure featuring a solid prism with a sharp hexahedral pyramidal tip, along with intrinsic physical scattering/reflection actions, Ce-ZnO NRDs@TW achieves an impressive 99.6% UVA radiation blockage (the highest for TW) and maintains high visible-light transmission (83.2%). Furthermore, Ce-ZnO NRDs@TW presents favorable energy-saving, sound absorption, and antifungal abilities, making it a promising candidate for future green buildings.

2.
Nanoscale ; 16(10): 5014-5041, 2024 Mar 07.
Artículo en Inglés | MEDLINE | ID: mdl-38323627

RESUMEN

Addressing significant medical challenges arising from tissue damage and organ failure, the field of tissue engineering has evolved to provide revolutionary approaches for regenerating functional tissues and organs. This involves employing various techniques, including the development and application of novel nanomaterials. Among them, chiral nanomaterials comprising non-superimposable nanostructures with their mirror images have recently emerged as innovative biomaterial candidates to guide tissue regeneration due to their unique characteristics. Chiral nanomaterials including chiral fibre supramolecular hydrogels, polymer-based chiral materials, self-assembling peptides, chiral-patterned surfaces, and the recently developed intrinsically chiroptical nanoparticles have demonstrated remarkable ability to regulate biological processes through routes such as enantioselective catalysis and enhanced antibacterial activity. Despite several recent reviews on chiral nanomaterials, limited attention has been given to the specific potential of these materials in facilitating tissue regeneration processes. Thus, this timely review aims to fill this gap by exploring the fundamental characteristics of chiral nanomaterials, including their chiroptical activities and analytical techniques. Also, the recent advancements in incorporating these materials in tissue engineering applications are highlighted. The review concludes by critically discussing the outlook of utilizing chiral nanomaterials in guiding future strategies for tissue engineering design.


Asunto(s)
Nanopartículas , Nanoestructuras , Ingeniería de Tejidos , Nanoestructuras/química , Materiales Biocompatibles/química , Péptidos/química
3.
Biomicrofluidics ; 16(6): 061502, 2022 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-36389273

RESUMEN

The liver is the largest internal organ in the human body with largest mass of glandular tissue. Modeling the liver has been challenging due to its variety of major functions, including processing nutrients and vitamins, detoxification, and regulating body metabolism. The intrinsic shortfalls of conventional two-dimensional (2D) cell culture methods for studying pharmacokinetics in parenchymal cells (hepatocytes) have contributed to suboptimal outcomes in clinical trials and drug development. This prompts the development of highly automated, biomimetic liver-on-a-chip (LOC) devices to simulate native liver structure and function, with the aid of recent progress in microfluidics. LOC offers a cost-effective and accurate model for pharmacokinetics, pharmacodynamics, and toxicity studies. This review provides a critical update on recent developments in designing LOCs and fabrication strategies. We highlight biomimetic design approaches for LOCs, including mimicking liver structure and function, and their diverse applications in areas such as drug screening, toxicity assessment, and real-time biosensing. We capture the newest ideas in the field to advance the field of LOCs and address current challenges.

4.
Biomater Sci ; 10(24): 6862-6892, 2022 Dec 06.
Artículo en Inglés | MEDLINE | ID: mdl-36222758

RESUMEN

Gene therapy has shown great potential in the treatment of many diseases by downregulating the expression of certain genes. The development of gene vectors as a vehicle for gene therapy has greatly facilitated the widespread clinical application of nucleic acid materials (DNA, mRNA, siRNA, and miRNA). Currently, both viral and non-viral vectors are used as delivery systems of nucleic acid materials for gene therapy. However, viral vector-based gene therapy has several limitations, including immunogenicity and carcinogenesis caused by the exogenous viral vectors. To address these issues, non-viral nanocarrier-based gene therapy has been explored for superior performance with enhanced gene stability, high treatment efficiency, improved tumor-targeting, and better biocompatibility. In this review, we discuss various non-viral vector-mediated gene therapy approaches using multifunctional biodegradable or non-biodegradable nanocarriers, including polymer-based nanoparticles, lipid-based nanoparticles, carbon nanotubes, gold nanoparticles (AuNPs), quantum dots (QDs), silica nanoparticles, metal-based nanoparticles and two-dimensional nanocarriers. Various strategies to construct non-viral nanocarriers based on their delivery efficiency of targeted genes will be introduced. Subsequently, we discuss the cellular uptake pathways of non-viral nanocarriers. In addition, multifunctional gene therapy based on non-viral nanocarriers is summarized, in which the gene therapy can be combined with other treatments, such as photothermal therapy (PTT), photodynamic therapy (PDT), immunotherapy and chemotherapy. We also provide a comprehensive discussion of the biological toxicity and safety of non-viral vector-based gene therapy. Finally, the present limitations and challenges of non-viral nanocarriers for gene therapy in future clinical research are discussed, to promote wider clinical applications of non-viral vector-based gene therapy.


Asunto(s)
Nanopartículas del Metal , Nanotubos de Carbono , Ácidos Nucleicos , Oro , Terapia Genética
5.
Neural Netw ; 154: 246-254, 2022 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-35908374

RESUMEN

Convolutional Neural Networks have achieved state-of-the-art performance in image classification. Their lack of ability to recognise the spatial relationship between features, however, leads to misclassification of the variants of the same image. Capsule Networks were introduced to address this issue by incorporating the spatial information of image features into neural networks. In this paper, we are interested in showcasing the digit recognition task on CAPTCHA images, widely considered a challenge for computers in relation to human capabilities. Our intention is to provide a rigorous empirical regime in which we can compare the competitive performance of Capsule Networks against the Convolutional Neural Networks. Indeed since CAPTCHA distorts images, by adjusting the spatial positioning of features, we aim to demonstrate the advantages and limitations of Capsule Networks architecture. We train the Capsule Networks with Dynamic Routing version and the convolutional-neural-network-based deep-CAPTCHA baseline model to predict the digit sequences on numerical CAPTCHAs, investigate the performance results and propose two improvements to the Capsule Networks model.


Asunto(s)
Redes Neurales de la Computación , Reconocimiento en Psicología , Humanos
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