TARGETED DELIVERY OF ANTICANCER AGENTS TO CANCER

Our research focuses on developing dual functional polymeric micelles for the targeted delivery of anticancer agents to tumors. We first developed a poly(ethylene) glycol (PEG)-derivatized anticancer agent-Embelin (EB) (PEG-EB2) as an effective nanomicellar carrier for the delivery of Paclitaxel (PTX) to tumors. Our data demonstrated that PEG-EB2 retained similar biological effect as EB. Surprisingly, it can self-assemble into micelles (~20 nm) in aqueous solution and was also efficient in delivering the Paclitaxel (PTX) to cancers with enhanced antitumor activity. Further, folate (FA), a tumor specific ligand, was anchored into PEG5K-EB2 micelles (FA-PEG5K-EB2) to realize the active tumor targeting. The intracellular uptake of Doxorubicin (DOX) was markedly improved when incorporated into FA-PEG5K-EB2 over the one without FA, resulting in the significant higher level in inhibiting tumor growth. Moreover, structure activity relationship (SAR) study was performed in PEG-derivatized Vitamin E (PEG-VE), in which our data has shown that PEG-VE with longer PEG length (5K) and double VE chains (PEG5K-VE2) garnered significant better PTX loading, stability and improved antitumor efficacy. Additionally, aiming to improve the DOX loading and stability, a drug-interactive motif-Fmoc was placed in the interfacial region of the PEG5K-VE2 (PEG5K-Fmoc-VE2). The data suggested that introduction of Fmoc to PEG5K-VE2 brought about dramatic augmentation in DOX loading and formulation stability, which consequently led to an enhanced inhibition on tumor development. Another finding in my research is to formulate Camptothecin (CPT), a highly lipophilic antineoplastic drug, in an innovative fashion. CPT was conjugated with VE at its hydroxyl group via carbonate ester bond (CPT-VE) or disulfide linkage (CPT-S-S-VE), which can self-assemble into nanofiber upon stabilized by PEG5K-Fmoc-VE2. VE-derivatized CPT prodrugs significantly buttressed the stability of CPT due to the additional steric hindrance to the lactone ring on CPT. Meanwhile, compared to CPT-VE, CPT-S-S-VE can more readily liberate CPT at tumors in a controlled manner (high GSH conc. in tumor), leading to the superior tumor growth suppression in vivo. To reiterate, our data demonstrated that PEG-derivatized anticancer agents can serve as effective nanocarriers for the targeted delivery of chemotherapeutics. Additionally, incorporation of Fmoc into the interfacial region of dual functional carriers led to significantly increased drug loading and formulation stability, resulting in improved antitumor activity. Furthermore, coupling of VE to anticancer drugs may represent a novel platform in ameliorating their compatibility with utilized carrier

Grassland Degradation and Recovery Based on Remote Sensing and GIS in Inner Mongolia

Original Pape

An Improved D-α-Tocopherol-Based Nanocarrier for Targeted Delivery of Doxorubicin with Reversal of Multidrug Resistance

Nanocarriers have recently emerged as an attractive platform for delivery of various types of therapeutics including anticancer agents. Previously, we developed an improved TPGS delivery system (PEG5K-VE2) which demonstrated improved colloidal stability and greater in vivo antitumor activity. Nevertheless, the application of this system is still limited by a relatively low drug loading capacity (DLC). In this study we report that incorporation of a fluorenylmethyloxycarbonyl (Fmoc) motif at the interfacial region of PEG5K-VE2 led to significant improvement of the system through the introduction of an additional mechanism of drug/carrier interaction. Doxorubicin (DOX) could be effectively loaded into PEG5K-Fmoc-VE2 micelles at a DLC of 39.9%, which compares favorably to most reported DOX nanoformulations. In addition, PEG5K-Fmoc-VE2/DOX mixed micelles showed more sustained release of DOX in comparison to the counterpart without Fmoc motif. MTT assay showed that PEG5K-Fmoc-VE2/DOX exerted significantly higher levels of cytotoxicity over DOX, Doxil as well as PEG5K-VE2/DOX in PC-3 and 4T1.2 cells. Cytotoxicity assay with NCI/ADR-RES, a drug resistant cell line, suggested that PEG5K-Fmoc-VE2 may have a potential to reverse the multidrug resistance, which was supported by its inhibition on P-gp ATPase. Pharmacokinetics (PK) and biodistribution studies showed an increased half-life in blood circulation and more effective tumor accumulation for DOX formulated in PEG5K-Fmoc-VE2 micelles. More importantly, DOX-loaded PEG5K-Fmoc-VE2 micelles showed an excellent safety profile with a MTD (~30 mg DOX/kg) that is about 3 times as much as that for free DOX. Finally, superior antitumor activity was demonstrated for PEG5K-Fmoc-VE2/DOX in both drug-sensitive (4T1.2 and PC-3) and drug-resistant (KB 8-5) tumor models compared to DOX, Doxil, and PEG5K-VE2/DOX

A PEG-Fmoc conjugate as a nanocarrier for paclitaxel

We report here that a simple, well-defined, and easy-to-scale up nanocarrier, PEG5000-lysyl-(α-Fmoc-ε-t-Boc-lysine)2 conjugate (PEG-Fmoc), provides high loading capacity, excellent formulation stability and low systemic toxicity for paclitaxel (PTX), a first-line chemotherapeutic agent for various types of cancers. 9-Fluorenylmethoxycarbonyl (Fmoc) was incorporated into the nanocarrier as a functional building block to interact with drug molecules. PEG-Fmoc was synthesized via a three-step synthetic route, and it readily interacted with PTX to form mixed nanomicelles of small particle size (25–30 nm). The PTX loading capacity was about 36%, which stands well among the reported micellar systems. PTX entrapment in this micellar system is achieved largely via an Fmoc/PTX π-π stacking interaction, which was demonstrated by fluorescence quenching studies and 13C-NMR. PTX formulated in PEG-Fmoc micelles demonstrated sustained release kinetics, and in vivo distribution study via near infrared fluorescence imaging demonstrated an effective delivery of Cy5.5-labled PTX to tumor sites. The maximal tolerated dose for PTX/PEG-Fmoc (MTD > 120 mg PTX/kg) is higher than those for most reported PTX formulations, and in vivo therapeutic study exhibited a significantly improved antitumor activity than Taxol, a clinically used formulation of PTX. Our system may hold promise as a simple, safe, and effective delivery system for PTX with a potential for rapid translation into clinical study

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Research progress on the role of NLRP3 inflammasome in the treatment of ischemia-reperfusion injury

NOD-like receptor protein 3(NLRP3) inflammasome, as a protein complex that constitutes the innate immune system, can mediate inflammatory responses by regulating the maturation and release of IL-1β and IL-18, which are the basic for multiple pathological injury. A variety of injury factors generated during ischemia-reperfusion injury (I/RI) can activate the NLRP3 inflammasome, resulting in the excessive release of IL-1β and IL-18, which in turn leads to an inflammatory cascade to aggravate the damage of various tissues and organs. Inhibition of NLRP3 inflammasome activation has become an effective method to alleviate organ I/RI. Therefore, exploring the detailed mechanism of NLRP3 inflammasome-mediated I/RI can provide a theoretical basis for the prevention and treatment of organ I/RI

Clinical effects of piribedil in adjuvant treatment of Parkinson’s Disease: A meta-analysis

Objective. To evaluate the clinical effects of piribedil in adjuvant treatment of Parkinson’s Disease (PD) by pooling previously openly published studies. Methods. The related electronic databases of Medline (1960~2017.5), Cochrane central register of controlled trials (CENTRAL), EMBASE (1980~2017.5) and Wanfang (1986~20175.5) were searched by two reviewers (Lu Peihua and Wang Jianqian) independently for publications including the topic of prospective randomized controlled trials about clinical effects of piribedil in adjuvant treatment of PD. The data of each included study was extracted and pooled by Stata11.0 software (for meta-analysis). The statistical heterogeneity across the studies was evaluated by I2 test and the publication bias was calculated by begg’s funnel plot and Egger’s line regression test. Results. After searching the related electronic databases of Medline, CENTRAL, EMBSE and Wanfang databases, 11 clinical studies were included in this meta-analysis. The pooled RR (random effect model) of clinical efficacy was 1.29 (95%CI:1.18~1.41, P=4×10-3) indicating the clinical efficacy of piribedil group was signficat higher than those of control group. The standard mean difference (SMD) for UPDRS score changed before and after treatment was pooled by random effect model. The combined SMD was -0.41 (95%CI:-0.75~-0.06). For piribedil related side effects, the combined data indicated that there was no statistical difference for nausea and vomiting (RR=0.43, 95%CI:0.41~1.69, P=0.61), mental disorders (RR=0.85, 95%CI:0.45~1.59, P=0.61) and other toxicities (RR=0.32, 95%CI:0.09~1.16, P=0.08). Conclusion. Piribedil combined with Levodopa in adjuvant treatment of PD is more effective than Levodopa alone without increasing the drug related toxicity

PM2.5 Concentration Forecasting over the Central Area of the Yangtze River Delta Based on Deep Learning Considering the Spatial Diffusion Process

Precise PM2.5 concentration forecasting is significant to environmental management and human health. Researchers currently add various parameters to deep learning models for PM2.5 concentration forecasting, but most of them ignore the problem of PM2.5 concentration diffusion. To address this issue, a deep learning model-based PM2.5 concentration forecasting method considering the diffusion process is proposed in this paper. We designed a spatial diffuser to express the diffusion process of gaseous pollutants; that is, the concentration of PM2.5 in four surrounding directions was taken as the explanatory variable. The information from the target and associated stations was then employed as inputs and fed into the model, together with meteorological features and other pollutant parameters. The hourly data from 1 January 2019 to 31 December 2019, and the central area of the Yangtze River Delta, were used to conduct the experiment. The results showed that the forecasting performance of the method we proposed is superior to that of ignoring diffusion, with an average RMSE = 8.247 &mu;g/m3 and average R2 = 0.922 in three different deep learning models, RNN, LSTM, and GRU, in which RMSE decreased by 10.52% and R2 increased by 2.22%. Our PM2.5 concentration forecasting method, which was based on an understanding of basic physical laws and conformed to the characteristics of data-driven models, achieved excellent performance