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BODIPY analogs are promising photosensitizers for molecular phototherapy; however, they exhibit high dark cytotoxicity and limited singlet oxygen generation capacity. In this study, we developed self-assembled core-shell nanophotosensitizers by linking a bipyridine group to BODIPY (Bpy-BODIPY) and promoting J-aggregation on gold nanourchins. This design enhances photostability and reduces the energy gap between the lowest singlet excited state and the lower triplet state, facilitating efficient singlet oxygen production. Notably, Bpy-BODIPY@Au significantly suppresses tau protein aggregation and enhances neuroprotective action, even in the presence of a phosphatase inhibitor. This work broadens the application of BODIPY chemistry to nanoagents for neuroprotective therapy.
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The development of durable photosensitizers is pivotal for advancing phototherapeutic applications in biomedicine. Here, we introduce a core-shell azobenzene-spiropyran structure on gold nanoparticles, engineered to enhance singlet oxygen generation. These nano-photosensitizers exhibit increased structural stability and thermal resistance, as demonstrated by slowed O-N-C bond recombination dynamics via in-situ Raman spectroscopy. Notably, the in-situ formation of merocyanine and a light-induced compact shell arrangement extend its half-life from 47 minutes to over 154 hours, significantly boosting singlet oxygen output. The nano-photosensitizer also shows high biocompatibility and notably inhibits tau protein aggregation in neural cells, even with phosphatase inhibitors. Further, it promotes dendritic growth in neuro cells, doubling typical lengths. This work not only advances chemical nanotechnology but also sets a foundation for developing long-lasting phototherapy agents for treating neurodegenerative diseases.
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Stimuli-responsive polymeric micelles have emerged as a revolutionary approach for enhancing the in vivo stability, biocompatibility, and targeted delivery of functional nanoparticles (FNPs) in biomedicine. This article comprehensively reviews the preparation methods of these polymer micelles, detailing the innovative strategies employed to introduce stimulus responsiveness and surface modifications essential for precise targeting. We delve into the breakthroughs in utilizing these micelles to selectively deliver various FNPs including magnetic nanoparticles, upconversion nanoparticles, gold nanoparticles, and quantum dots, highlighting their transformative impact in the biomedical realm. Concluding, we present an insight into the current research landscape, addressing the challenges at hand, and envisioning the future trajectory in this burgeoning domain. Join us as we navigate the exciting confluence of polymer science and nanotechnology in reshaping biomedical solutions.
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Micelas , Humanos , Nanopartículas/química , Polímeros Responsivos a Estímulos/química , Polímeros/química , Animais , Sistemas de Liberação de Medicamentos , Portadores de Fármacos/química , Pontos Quânticos/químicaRESUMO
The determination of water quality heavily depends on the selection of parameters recorded from water samples for the water quality index (WQI). Data-driven methods, including machine learning models and statistical approaches, are frequently used to refine the parameter set for four main reasons: reducing cost and uncertainty, addressing the eclipsing problem, and enhancing the performance of models predicting the WQI. Despite their widespread use, there is a noticeable gap in comprehensive reviews that systematically examine previous studies in this area. Such reviews are essential to assess the validity of these objectives and to demonstrate the effectiveness of data-driven methods in achieving these goals. This paper sets out with two primary aims: first, to provide a review of the existing literature on methods for selecting parameters. Second, it seeks to delineate and evaluate the four principal motivations for parameter selection identified in the literature. This manuscript categorizes existing studies into two methodological groups for refining parameters: one focuses on preserving information within the dataset, and another ensures consistent prediction using the full set of parameters. It characterizes each group and evaluates how effectively each approach meets the four predefined objectives. The study presents that the minimal WQI approach, common to both categories, is the only approach that has successfully reduced recording costs. Nonetheless, it notes that simply reducing the number of parameters does not guarantee cost savings. Furthermore, the group of studies classified as preserving information within the dataset has demonstrated potential to decrease the eclipsing problem, whereas studies in the consistent prediction group have not been able to mitigate this issue. Additionally, since data-driven approaches still rely on the initial parameters chosen by experts, they do not eliminate the need for expert judgment. The study further points out that the WQI formula is a straightforward and expedient tool for assessing water quality. Consequently, the paper argues that employing machine learning solely to reduce the number of parameters to enhance WQI prediction is not a standalone solution. Rather, this objective should be integrated with a more comprehensive set of research goals. The critical analysis of research objectives and the characterization of previous studies lay the groundwork for future research. This groundwork will enable subsequent studies to evaluate how their proposed methods can effectively achieve these objectives.
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Qualidade da Água , Aprendizado de Máquina , Monitoramento Ambiental/métodos , Modelos TeóricosRESUMO
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.
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Nanopartículas , Nanoestruturas , Engenharia Tecidual , Nanoestruturas/química , Materiais Biocompatíveis/química , Peptídeos/químicaRESUMO
RNA interference (RNAi) technology has been a promising treatment strategy for combating intractable diseases. However, the applications of RNAi in clinical are hampered by extracellular and intracellular barriers. To overcome these barriers, various siRNA delivery systems have been developed in the past two decades. The first approved RNAi therapeutic, Patisiran (ONPATTRO) using lipids as the carrier, for the treatment of amyloidosis is one of the most important milestones. This has greatly encouraged researchers to work on creating new functional siRNA carriers. In this review, the recent advances in siRNA carriers consisting of lipids, polymers, and polymer-modified inorganic particles for cancer therapy are summarized. Representative examples are presented to show the structural design of the carriers in order to overcome the delivery hurdles associated with RNAi therapies. Finally, the existing challenges and future perspective for developing RNAi as a clinical modality will be discussed and proposed. It is believed that the addressed contributions in this review will promote the development of siRNA delivery systems for future clinical applications.