Novel insight into the therapeutical potential of flavonoids from traditional Chinese medicine against cerebral ischemia/reperfusion injury.

Cerebral ischemia/reperfusion injury (CIRI) is a major contributor to poor prognosis of ischemic stroke. Flavonoids are a broad family of plant polyphenols which are abundant in traditional Chinese medicine (TCM) and have beneficial effects on several diseases including ischemic stroke. Accumulating studies have indicated that flavonoids derived from herbal TCM are effective in alleviating CIRI after ischemic stroke in vitro or in vivo, and exhibit favourable therapeutical potential. Herein, we systematically review the classification, metabolic absorption, neuroprotective efficacy, and mechanisms of TCM flavonoids against CIRI. The literature suggest that flavonoids exert potential medicinal functions including suppressing excitotoxicity, Ca2+ overloading, oxidative stress, inflammation, thrombin's cellular toxicity, different types of programmed cell deaths, and protecting the blood-brain barrier, as well as promoting neurogenesis in the recovery stage following ischemic stroke. Furthermore, we identified certain matters that should be taken into account in future research, as well as proposed difficulties and opportunities in transforming TCM-derived flavonoids into medications or functional foods for the treatment or prevention of CIRI. Overall, in this review we aim to provide novel ideas for the identification of new prospective medication candidates for the therapeutic strategy against ischemic stroke.

No-reflow after recanalization in ischemic stroke: From pathomechanisms to therapeutic strategies.

Endovascular reperfusion therapy is the primary strategy for acute ischemic stroke. No-reflow is a common phenomenon, which is defined as the failure of microcirculatory reperfusion despite clot removal by thrombolysis or mechanical embolization. It has been reported that up to 25% of ischemic strokes suffer from no-reflow, which strongly contributes to an increased risk of poor clinical outcomes. No-reflow is associated with functional and structural alterations of cerebrovascular microcirculation, and the injury to the microcirculation seriously hinders the neural functional recovery following macrovascular reperfusion. Accumulated evidence indicates that pathology of no-reflow is linked to adhesion, aggregation, and rolling of blood components along the endothelium, capillary stagnation with neutrophils, astrocytes end-feet, and endothelial cell edema, pericyte contraction, and vasoconstriction. Prevention or treatment strategies aim to alleviate or reverse these pathological changes, including targeted therapies such as cilostazol, adhesion molecule blocking antibodies, peroxisome proliferator-activated receptors (PPARs) activator, adenosine, pericyte regulators, as well as adjunctive therapies, such as extracorporeal counterpulsation, ischemic preconditioning, and alternative or complementary therapies. Herein, we provide an overview of pathomechanisms, predictive factors, diagnosis, and intervention strategies for no-reflow, and attempt to convey a new perspective on the clinical management of no-reflow post-ischemic stroke.

A deep learning method for predicting metabolite-disease associations via graph neural network.

Metabolism is the process by which an organism continuously replaces old substances with new substances. It plays an important role in maintaining human life, body growth and reproduction. More and more researchers have shown that the concentrations of some metabolites in patients are different from those in healthy people. Traditional biological experiments can test some hypotheses and verify their relationships but usually take a considerable amount of time and money. Therefore, it is urgent to develop a new computational method to identify the relationships between metabolites and diseases. In this work, we present a new deep learning algorithm named as graph convolutional network with graph attention network (GCNAT) to predict the potential associations of disease-related metabolites. First, we construct a heterogeneous network based on known metabolite-disease associations, metabolite-metabolite similarities and disease-disease similarities. Metabolite and disease features are encoded and learned through the graph convolutional neural network. Then, a graph attention layer is used to combine the embeddings of multiple convolutional layers, and the corresponding attention coefficients are calculated to assign different weights to the embeddings of each layer. Further, the prediction result is obtained by decoding and scoring the final synthetic embeddings. Finally, GCNAT achieves a reliable area under the receiver operating characteristic curve of 0.95 and the precision-recall curve of 0.405, which are better than the results of existing five state-of-the-art predictive methods in 5-fold cross-validation, and the case studies show that the metabolite-disease correlations predicted by our method can be successfully demonstrated by relevant experiments. We hope that GCNAT could be a useful biomedical research tool for predicting potential metabolite-disease associations in the future.

Multifunctional silica nanocomposites prime tumoricidal immunity for efficient cancer immunotherapy.

The tumor immune microenvironment (TIME) has been demonstrated to be the main cause of cancer immunotherapy failure in various malignant tumors, due to poor immunogenicity and existence of immunosuppressive factors. Thus, establishing effective treatments for hostile TIME remodeling has considerable potential to enhance immune response rates for durable tumor growth retardation. This study aims to develop a novel nanocomposite, polyethyleneimine-modified dendritic mesoporous silica nanoparticles loaded with microRNA-125a (DMSN-PEI@125a) to synergistically enhance immune response and immunosuppression reversion, ultimately generating a tumoricidal environment. Our results showed that DMSN-PEI@125a exhibited excellent ability in cellular uptake by murine macrophages and the cervical cancer cell line TC-1, repolarization of tumor associated macrophages (TAMs) to M1 type in a synergistic manner, and promotion of TC-1 immunogenic death. Intratumor injection of DMSN-PEI@125a facilitated the release of more damage-related molecular patterns and enhanced the infiltration of natural killer and CD8+ T cells. Meanwhile, repolarized TAMs could function as a helper to promote antitumor immunity, thus inhibiting tumor growth in TC-1 mouse models in a collaborative manner. Collectively, this work highlights the multifunctional roles of DMSN-PEI@125a in generating an inflammatory TIME and provoking antitumor immunity, which may serve as a potential agent for cancer immunotherapy.

Layer-Number-Dependent Effects of Graphene Oxide on the Pluripotency of Mouse Embryonic Stem Cells Through the Regulation of the Interaction Between the Extracellular Matrix and Integrins.

INTRODUCTION: Embryonic stem cells (ESCs) possess great application prospects in biological research and regenerative medicine, so it is important to obtain ESCs with excellent and stable cellular states during in vitro expansion. The feeder layer culture system with the addition of leukemia inhibitory factor (LIF) is currently applied in ESC cultures, but it has a series of disadvantages that could influence the culture efficiency and quality of the ESCs. With the development of nanotechnology, many studies have applied nanomaterials to optimize the stem cell culture system and regulate the fate of stem cells. In this study, we investigated the layer-number-dependent biofunction of graphene oxide (GO) on the pluripotency of ESCs from mice (mESCs). METHODS: Single-layer GO (SGO) and multi-layer GO (MGO) were characterized and their effects on the cytotoxicity and self-renewal of mESCs were detected in vitro. The differentiation potentials of mESCs were identified through the formation of embryoid bodies and teratomas. The regulatory mechanism of GO was verified by blocking the target receptors on the surface of mESCs using antibodies. RESULTS: Both SGO and MGO were biocompatible with mESCs, but only MGO effectively sustained their self-renewal and differentiation potential. In addition, GO influenced the cellular activities of mESCs by regulating the interactions between extracellular matrix proteins and integrins. CONCLUSION: This work demonstrates the layer-number-dependent effects of GO on regulating the cell behavior of mESCs and reveals the extracellular regulatory mechanism of this process.

Trifunctional Graphene Quantum Dot@LDH Integrated Nanoprobes for Visualization Therapy of Gastric Cancer.

Visualization technology has become a trend in tumor therapy in recent years. The superior optical properties of graphene quantum dots (GQDs) make them suitable candidates for tumor diagnosis, but their tumor targeting and drug-carrying capacities are still not ideal for treatment. Sulfur-doped graphene quantum dots (SGQDs) with stable fluorescence are prepared in a previous study. A reliable strategy by associating layered double hydroxides (LDHs) and etoposide (VP16) is designed for precise visualization therapy. Trifunctional LDH@SGQD-VP16 integrated nanoprobes can simultaneously achieve targeted aggregation, fluorescence visualization, and chemotherapy. LDH@SGQD-VP16 can accumulate in the tumor microenvironment, owing to pH-sensitive properties and long-term photostability in vivo, which can provide a basis for cancer targeting, real-time imaging, and effect tracking. The enhanced therapeutic and attenuated side effects of VP16 are demonstrated, and the apoptosis caused by LDH@SGQD-VP16 is ≈2.7 times higher than that of VP16 alone, in HGC-27 cells. This work provides a theoretical and experimental basis for LDH@SGQD-VP16 as a potential multifunctional agent for visualization therapy of gastric cancer.