A review on recent advances in polymeric microneedle loading cells: Design strategies, fabrication technologies, transdermal application and challenges.

Microneedle systems (MNs) loading living cells are a powerful platform to treat various previously incurable diseases in the era of precision medicine. Herein, an overview of recent advances in MN-based strategies for cell delivery is summarized, including material selection, design of morphological structures, and processing methods. We also systematically outlined the law of microstructural design relative to the structure-effective/function relationship in transdermal delivery or precision medicine and the design principles of cell microneedle (CMN).

Ionic conducting hydrogels as biomedical materials: classification, design strategies, and skin tissue engineering applications.

Ionically conductive hydrogels (ICHs) are considered promising flexible electronic devices and various wearable sensors due to the integration of the conductive performance and soft nature of human tissue-like materials with mechanical and sensory traits. Recently, substantial progress has been made in the research of ICHs, including high conductivity, solution processability, strong adhesion, high stretchability, high self-healing ability, and good biocompatibility. These advanced researches also promote their excellent application prospects in medical monitoring, sports health, smart wear, and other fields.

The Importance of Expert Knowledge for Automatic Modulation Open Set Recognition.

Automatic modulation classification (AMC) is an important technology for the monitoring, management, and control of communication systems. In recent years, machine learning approaches are becoming popular to improve the effectiveness of AMC for radio signals. However, the automatic modulation open-set recognition (AMOSR) scheme that aims to identify the known modulation types and recognize the unknown modulation signals is not well studied.

Deep Reinforcement Learning Based Decision Making for Complex Jamming Waveforms.

With the development of artificial intelligence, intelligent communication jamming decision making is an important research direction of cognitive electronic warfare. In this paper, we consider a complex intelligent jamming decision scenario in which both communication parties choose to adjust physical layer parameters to avoid jamming in a non-cooperative scenario and the jammer achieves accurate jamming by interacting with the environment. However, when the situation becomes complex and large in number, traditional reinforcement learning suffers from the problems of failure to converge and a high number of interactions, which are fatal and unrealistic in a real warfare environment.

Epileptic Seizure Detection with Hybrid Time-Frequency EEG Input: A Deep Learning Approach.

The precise detection of epileptic seizure helps to prevent the serious consequences of seizures. As the electroencephalogram (EEG) reflects the brain activity of patients effectively, it has been widely used in epileptic seizure detection in the past decades. Recently, deep learning-based detection methods which automatically learn features from the EEG signals have attracted much attention.

CLPVG: Circular limited penetrable visibility graph as a new network model for time series.

A visibility graph transforms time series into graphs, facilitating signal processing by advanced graph data mining algorithms. In this paper, based on the classic limited penetrable visibility graph method, we propose a novel mapping method named circular limited penetrable visibility graph, which replaces the linear visibility line in limited penetrable visibility graph with nonlinear visibility arc for pursuing more flexible and reasonable mapping of time series. Tests on degree distribution and some common network features of the generated graphs from typical time series demonstrate that our circular limited penetrable visibility graph can effectively capture the important features of time series and show higher robust classification performance than the traditional limited penetrable visibility graph in the presence of noise.

Do short chain fatty acids and phenolic metabolites of the gut have synergistic anti-inflammatory effects? - New insights from a TNF-α-induced Caco-2 cell model.

Fermentation of dietary fiber and metabolism of polyphenols by the gut microbiota produce short chain fatty acids (SCFAs) and some simple phenolic acids, both of which have been independently shown to have anti-inflammatory effects and to improve gut health. While synergistic interactions between the two colonic metabolite groups have been speculated, direct evidence on whether and how these compounds work together towards collective anti-inflammatory effect and gut health remain unclear. In this study, the most important SCFA butyric acid (BtA) and three phenolic metabolites benzoic acid (BzA), phenylacetic acid (PAA) and phenylpropionic acid (PPA) were selected and assessed for the anti-inflammatory effects and the underlying mechanisms in a TNF-α-induced Caco-2 cell model.

Synergistic antioxidant effects of petunidin and lycopene in H9c2 cells submitted to hydrogen peroxide: Role of Akt/Nrf2 pathway.

Phenolics and carotenoids coexist in fruits and vegetables and could possess interaction effects after consumption. The present study aims to elucidate the possible mechanisms of the antioxidant interactions between anthocyanins and carotenoids using petunidin and lycopene as examples in hydrogen peroxide (H O )-induced heart myofibroblast cell (H9c2) line model. The results revealed that petunidin and lycopene showed antioxidant effects and petunidin in a larger proportion mixed with lycopene, for example, petunidin: lycopene = 9:1 significantly protected against the loss of the cell viability (8.

The Phenolic Compounds, Metabolites, and Antioxidant Activity of Propolis Extracted by Ultrasound-Assisted Method.

The influences of ultrasound-assisted, pharmacopeia, and supercritical fluid extraction methods on bioactive compounds and biological activities of propolis were evaluated. Results showed that propolis extracted by ultrasound-assisted method contained more phenolic compounds, and showed the highest total phenolic content (245.84 ± 6.

Daily Dietary Antioxidant Interactions Are Due to Not Only the Quantity but Also the Ratios of Hydrophilic and Lipophilic Phytochemicals.

The hydrophilic extracts of mulberry (HEM) and blueberry (HEB) and lipophilic extracts of mango (LEM) and watermelon (LEW) were mixed in different ratios to assess the antioxidant interactions by chemical-based (DPPH and ABTS assays) and H9c2 cell-based models. There were both synergistic and antagonistic antioxidant interactions among these fruits. Some groups with combinational extracts showed stronger synergistic antioxidant effects than the individual groups, and others (HEM-LEW F1/10, LEW-LEM F5/10, and HEB-LEM F3/10) showed stronger antagonistic effects than the individual groups based on the indicators [the values of DPPH, ABTS, and MTT; the expression of superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), catalase (CAT), and malondialdehyde (MDA); the release of lactate dehydrogenase (LDH); and the quantification of cellular antioxidant activity].

Implication of the Significance of Dietary Compatibility: Based on the Antioxidant and Anti-Inflammatory Interactions with Different Ratios of Hydrophilic and Lipophilic Antioxidants among Four Daily Agricultural Crops.

The hydrophilic extracts of eggplant peel (HEEP) and purple sweet potato (HEPP) and lipophilic extracts of tomato (LET) and carrot (LEC) were mixed in different ratios to assess the significance of the compatibility of aliments, based on their antioxidant and anti-inflammatory interactions in H9c2 cells. The results indicated that groups of some combinational extracts (HEPP-HEEP F1/10, LEC-HEEP F3/10, LEC-HEPP F3/10) showed stronger synergistic antioxidant and anti-inflammatory effects than individual groups. For example, the glutathione peroxidase (GPx) activity of the LEC-HEEP (F3/10) group (86.

Octyl Ester of Ginsenoside Rh2 Induces Apoptosis and G1 Cell Cycle Arrest in Human HepG2 Cells by Activating the Extrinsic Apoptotic Pathway and Modulating the Akt/p38 MAPK Signaling Pathway.

Ginsenoside Rh2 is a potential active metabolite of ginseng that has antitumor activity against a variety of tumor cells. Previously, we reported that Rh2-O, an octyl ester derivative of ginsenoside Rh2, had a higher anticancer activity than Rh2 through activating the intrinsic apoptotic pathway. In this study, we found that the extrinsic apoptotic pathway was also involved in Rh2-O-induced HepG2 cells apoptosis as evidenced by the up-regulation of Fas, FasL, TNFR1, and TNF-α as well as the cleavage of caspase 8.

Esterification of Ginsenoside Rh2 Enhanced Its Cellular Uptake and Antitumor Activity in Human HepG2 Cells.

Our previous research had indicated that the octyl ester derivative of ginsenoside Rh2 (Rh2-O) might have a higher bioavailability than Rh2 in the Caco-2 cell line. The aim of this study was to investigate the cellular uptake and antitumor effects of Rh2-O in human HepG2 cells as well as its underlying mechanism compared with Rh2. Results showed that Rh2-O exhibited a higher cellular uptake (63.