Combination therapy based on dual-target biomimetic nano-delivery system for overcoming cisplatin resistance in hepatocellular carcinoma.

Strategies to overcome toxicity and drug resistance caused by chemotherapeutic drugs for targeted therapy against hepatocellular carcinoma (HCC) are urgently needed. Previous studies revealed that high oxidored-nitro domain-containing protein 1(NOR1) expression in HCC was associated with cisplatin (DDP) resistance. Herein, a novel dual-targeting nanocarrier system AR-NADR was generated for the treatment of DDP resistance in HCC. The core of the nanocarrier system is the metal-organic frameworks (MOF) modified with nuclear location sequence (NLS), which loading with DDP and NOR1 shRNA (R). The shell is an A54 peptide inserted into the erythrocyte membrane (AR). Our results show that AR-NADR efficiently internalized by tumor cells due to its specific binding to the A54 receptors that are abundantly expressed on the surface of HCC cells and NLS peptide-mediated nuclear entry. Additionally, DDP is more likely to be released due to the degradation of Ag-MOF in the acidic tumor microenvironment. Moreover, by acting as a vector for gene delivery, AR-NADR effectively inhibits tumor drug resistance by suppressing the expression of NOR1, which induces intracellular DDP accumulation and makes cells sensitive to DDP. Finally, the anti-HCC efficacy and mechanisms of AR-NADR were systematically elucidated by a HepG2/DDP cell model as well as a tumor model. Therefore, AR-NADR constitutes a key strategy to achieve excellent gene silencing and antitumor efficacy, which provides effective gene therapy and precise treatment strategies for cisplatin resistance in HCC.

Erythrocyte membrane-camouflaged DNA-functionalized upconversion nanoparticles for tumor-targeted chemotherapy and immunotherapy.

A synergistic combination of treatment with immunogenic cell death (ICD) inducers and immunoadjuvants may be a practical way to boost the anticancer response and successfully induce an immune response. The use of HR@UCNPs/CpG-Apt/DOX, new biomimetic drug delivery nanoparticles generated to combat breast cancer, is reported here as a unique strategy to produce immunogenicity and boost cancer immunotherapy. HR@UCNPs/CpG-Apt/DOX (HR-UCAD) consists of two parts. The core is composed of an immunoadjuvant CpG (a toll-like receptor 9 agonist) fused with a dendritic cell-specific aptamer sequence (CpG-Apt) to decorate upconversion nanoparticles (UCNPs) with the successful intercalation of doxorubicin (DOX) into the consecutive base pairs of Apt-CpG to construct an immune nanodrug UCNPs@CpG-Apt/DOX. The targeting molecule hyaluronic acid (HA) was inserted into a red blood cell membrane (RBCm) to form the shell (HR). HR-UCAD possessed a strong capacity to specifically induce ICD. Following DOX-induced ICD of cancer cells, sufficient exposure to tumor antigens and UCNPs@CpG-Apt (UCA) activated the tumor-specific immune response and reversed the immunosuppressive tumor microenvironment. In addition, HR-UCAD has good biocompatibility and increases the active tumor-targeting effect. Furthermore, HR-UCAD exhibits excellent near-infrared upconversion luminescence emission at 804 nm under irradiation with a 980 nm laser, which has great potential in biomedical imaging. Thus, the RBCm-camouflaged drug delivery system is a promising targeted chemotherapy and immunotherapy nanocomplex that could be used for effective targeted breast cancer treatment.

Study on the Role of an Erythrocyte Membrane-Coated Nanotheranostic System in Targeted Immune Regulation of Alzheimer's Disease.

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases in the elderly population. Despite significant advances in studies of the pathobiology on AD, there is still no effective treatment. Here, an erythrocyte membrane-camouflaged nanodrug delivery system (TR-ZRA) modified with transferrin receptor aptamers that can be targeted across the blood-brain barrier to ameliorate AD immune environment is established. Based on metal-organic framework (Zn-CA), TR-ZRA is loaded with CD22shRNA plasmid to silence the abnormally high expression molecule CD22 in aging microglia. Most importantly, TR-ZRA can enhance the ability of microglia to phagocytose Aß and alleviate complement activation, which can promote neuronal activity and decrease inflammation level in the AD brain. Moreover, TR-ZRA is also loaded with Aß aptamers, which allow rapid and low-cost monitoring of Aß plaques in vitro. After treatment with TR-ZRA, learning, and memory abilities are enhanced in AD mice. In conclusion, the biomimetic delivery nanosystem TR-ZRA in this study provides a promising strategy and novel immune targets for AD therapy.

Combined Microbiome and Metabolome Analysis Reveals a Novel Interplay Between Intestinal Flora and Serum Metabolites in Lung Cancer.

As the leading cause of cancer death, lung cancer seriously endangers human health and quality of life. Although many studies have reported the intestinal microbial composition of lung cancer, little is known about the interplay between intestinal microbiome and metabolites and how they affect the development of lung cancer. Herein, we combined 16S ribosomal RNA (rRNA) gene sequencing and liquid chromatography-mass spectrometry (LC-MS) technology to analyze intestinal microbiota composition and serum metabolism profile in a cohort of 30 lung cancer patients with different stages and 15 healthy individuals. Compared with healthy people, we found that the structure of intestinal microbiota in lung cancer patients had changed significantly (Adonis, p = 0.021). In order to determine how intestinal flora affects the occurrence and development of lung cancer, the Spearman rank correlation test was used to find the connection between differential microorganisms and differential metabolites. It was found that as thez disease progressed, L-valine decreased. Correspondingly, the abundance of Lachnospiraceae_UCG-006, the genus with the strongest association with L-valine, also decreased in lung cancer groups. Correlation analysis showed that the gut microbiome and serum metabolic profile had a strong synergy, and Lachnospiraceae_UCG-006 was closely related to L-valine. In summary, this study described the characteristics of intestinal flora and serum metabolic profiles of lung cancer patients with different stages. It revealed that lung cancer may be the result of the mutual regulation of L-valine and Lachnospiraceae_UCG-006 through the aminoacyl-tRNA biosynthesis pathway, and proposed that L-valine may be a potential marker for the diagnosis of lung cancer.

Corrigendum: Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery.

[This corrects the article DOI: 10.3389/fcvm.2021.771246.].

Corrigendum: Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery.

[This corrects the article DOI: 10.3389/fcvm.2021.771246.].

Novel Multifunctional Silver Nanocomposite Serves as a Resistance-Reversal Agent to Synergistically Combat Carbapenem-Resistant Acinetobacter baumannii.

In the face of the abundant production of various types of carbapenemases, the antibacterial efficiency of imipenem, seen as "the last line of defense", is weakening. Following, the incidence of carbapenem-resistant Acinetobacter baumannii (CRAB), which can generate antibiotic-resistant biofilms, is increasing. Based on the superior antimicrobial activity of silver nanoparticles against multifarious bacterial strains compared with common antibiotics, we constructed the IPM@AgNPs-PEG-NOTA nanocomposite (silver nanoparticles were coated with SH-PEG-NOTA as well as loaded by imipenem) whose core was a silver nanoparticle to address the current challenge, and IPM@AgNPs-PEG-NOTA was able to function as a novel smart pH-sensitive nanodrug system. Synergistic bactericidal effects of silver nanoparticles and imipenem as well as drug-resistance reversal via protection of the ß-ring of carbapenem due to AgNPs-PEG-NOTA were observed; thus, this nanocomposite confers multiple advantages for efficient antibacterial activity. Additionally, IPM@AgNPs-PEG-NOTA not only offers immune regulation and accelerates tissue repair to improve therapeutic efficacy in vivo but also can prevent the interaction of pathogens and hosts. Compared with free imipenem or silver nanoparticles, this platform significantly enhanced antibacterial efficiency while increasing reactive oxygen species (ROS) production and membrane damage, as well as affecting cell wall formation and metabolic pathways. According to the results of crystal violet staining, LIVE/DEAD backlight bacterial viability staining, and real-time quantitative polymerase chain reaction (RT-qPCR), this silver nanocomposite downregulated the levels of ompA expression to prevent formation of biofilms. In summary, this research demonstrated that the IPM@AgNPs-PEG-NOTA nanocomposite is a promising antibacterial agent of security, pH sensitivity, and high efficiency in reversing resistance and synergistically combatting carbapenem-resistant A. baumannii. In the future, various embellishments and selected loads for silver nanoparticles will be the focus of research in the domains of medicine and nanotechnology.

Machine Learning for the Prediction of Complications in Patients After Mitral Valve Surgery.

Background: This study intended to use a machine learning model to identify critical preoperative and intraoperative variables and predict the risk of several severe complications (myocardial infarction, stroke, renal failure, and hospital mortality) after cardiac valvular surgery. Study Design and Methods: A total of 1,488 patients undergoing cardiac valvular surgery in eight large tertiary hospitals in China were examined. Fifty-four perioperative variables, such as essential demographic characteristics, concomitant disease, preoperative laboratory indicators, operation type, and intraoperative information, were collected. Machine learning models were developed and validated by 10-fold cross-validation. In each fold, Recursive Feature Elimination was used to select key variables. Ten machine learning models and logistic regression were developed. The area under the receiver operating characteristic (AUROC), accuracy (ACC), Youden index, sensitivity, specificity, F1-score, positive predictive value (PPV), and negative predictive value (NPV) were used to compare the prediction performance of different models. The SHapley Additive ex Planations package was applied to interpret the best machine learning model. Finally, a model was trained on the whole dataset with the merged key variables, and a web tool was created for clinicians to use. Results: In this study, 14 vital variables, namely, intraoperative total input, intraoperative blood loss, intraoperative colloid bolus, Classification of New York Heart Association (NYHA) heart function, preoperative hemoglobin (Hb), preoperative platelet (PLT), age, preoperative fibrinogen (FIB), intraoperative minimum red blood cell volume (Hct), body mass index (BMI), creatinine, preoperative Hct, intraoperative minimum Hb, and intraoperative autologous blood, were finally selected. The eXtreme Gradient Boosting algorithms (XGBOOST) algorithm model presented a significantly better predictive performance (AUROC: 0.90) than the other models (ACC: 81%, Youden index: 70%, sensitivity: 89%, specificity: 81%, F1-score:0.26, PPV: 15%, and NPV: 99%). Conclusion: A model for predicting several severe complications after cardiac valvular surgery was successfully developed using a machine learning algorithm based on 14 perioperative variables, which could guide clinical physicians to take appropriate preventive measures and diminish the complications for patients at high risk.

Intestinal Flora Disruption and Novel Biomarkers Associated With Nasopharyngeal Carcinoma.

Background: Nasopharyngeal carcinoma (NPC) is a malignant nasopharyngeal disease with a complicated etiology that occurs mostly in southern China. Intestinal flora imbalance is believed to be associated with a variety of organ malignancies. Current studies revealed that the destruction of intestinal flora is associated with NPC, and many studies have shown that intestinal flora can be used as a biomarker for many cancers and to predict cancer. Methods: To compare the differences in intestinal flora compositions and biological functions among 8 patients with familial NPC (NPC_F), 24 patients with sporadic NPC (NPC_S), and 27 healthy controls (NOR), we compared the intestinal flora DNA sequencing and hematological testing results between every two groups using bioinformatic methods. Results: Compared to the NOR group, the intestinal flora structures of the patients in the NPC_F and NPC_S groups showed significant changes. In NPC_F, Clostridium ramosum, Citrobacter spp., Veillonella spp., and Prevotella spp. were significantly increased, and Akkermansia muciniphila and Roseburia spp. were significantly reduced. In NPC_S, C. ramosum, Veillonella parvula, Veillonella dispar, and Klebsiella spp. were significantly increased, and Bifidobacterium adolescentis was significantly reduced. A beta diversity analysis showed significant difference compared NPC_F with NOR based on Bray Curtis (P = 0.012) and Unweighted UniFrac (P = 0.0045) index, respectively. The areas under the ROC curves plotted were all 1. Additionally, the concentrations of 5-hydroxytryptamine (5-HT) in NPC_F and NPC_S were significantly higher than those of NOR. C. ramosum was positively correlated with 5-HT (rcm: 0.85, P < 0.001). A functional analysis of the intestinal flora showed that NPC_F was associated with Neurodegenerative Diseases (P = 0.023) and that NPC_S was associated with Neurodegenerative Diseases (P = 0.045) as well. Conclusion: We found that NPC was associated with structural imbalances in the intestinal flora, with C. ramosum that promoted the elevation of 5-HT and opportunistic pathogens being significantly increased, while probiotics significantly decreased. C. ramosum can be used as a novel biomarker and disease prediction models should be established for NPC. The new biomarkers and disease prediction models may be used for disease risk prediction and the screening of high-risk populations, as well as for the early noninvasive diagnosis of NPC.

Systematic Assessment of the Toxicity and Potential Mechanism of Graphene Derivatives In Vitro and In Vivo.

Graphene is a two-dimensional crystal that is stripped from pristine graphite and made of single layer of carbon atoms. Containing numerous functional groups, graphene derivatives (GDs) could be easily modified and have aroused great attention for potential applications in biomedicine. However, pristine graphene and graphene oxide (GO) could arouse cell and animal toxicity. To screen GDs with high biocompatibility applied for biomedicine, general comparison was performed about the toxicities of six GDs with diverse types of surface modification, size, and redox state, including GO, reduced GO (rGO), graphene quantum dot (GQD), aminated GQD (GQD-NH2), carboxyl GQD (GQD-COOH), and graphene oxide quantum dot (GOQD). In contrast, it was found that large particle size, oxidation state, high concentration, and long exposure time were unfavorable factors affecting the cell viability. We further explored the mechanism of different toxicity, which could be contribute to cell membrane destruction by sharpened edges of GDs (LDH release, hemolysis), ROS production, immuno-inflammatory responses, and activation of apoptotic pathways (IKK/IκBα/NF-κB and BAX/BCL-2). Overall, our combined data primarily explored the related biochemical and molecular mechanism underlying the biological behaviors and toxicity of GDs, and we also identified GQD, GQD-NH2, GQD-COOH, and GOQD could be safely used for biomedical application as drug carriers.