Dual-targeting liposomes modified with BTP-7 and pHA for combined delivery of TCPP and TMZ to enhance the anti-tumour effect in glioblastoma cells.

AIM: To construct a novel nano-carrier with dual ligands to achieve superior anti-tumour efficacy and lower toxic side effects. METHODS: Liposomes were prepared by thin film hydration method. Ultraviolet, high performance liquid chromatography, nano-size analyser, ultrafiltration centrifugation, dialysis, transmission electron microscope, flow cytometry, Cell Counting Kit-8, confocal laser scanning microscopy, transwell, and tumorsphere assay were used to study the characterisations, cytotoxicity, and in vitro targeting of dg-Bcan targeting peptide (BTP-7)/pHA-temozolomide (TMZ)/tetra(4-carboxyphenyl)porphyrin (TCPP)-Lip. RESULTS: BTP-7/pHA-TMZ/TCPP-Lip was a spheroid with a mean diameters of 143 ± 3.214 nm, a polydispersity index of 0.203 ± 0.025 and a surface charge of -22.8 ± 0.425 mV. The drug loadings (TMZ and TCPP) are 7.40 ± 0.23% and 2.05 ± 0.03% (mg/mg); and the encapsulation efficiencies are 81.43 ± 0.51% and 84.28 ± 1.64% (mg/mg). The results showed that BTP-7/pHA-TMZ/TCPP-Lip presented enhanced targeting and cytotoxicity. CONCLUSION: BTP-7/pHA-TMZ/TCPP-Lip can specifically target the tumour cells to achieve efficient drug delivery, and improve the anti-tumour efficacy and reduces the systemic toxicity.

Research Progress of Nanocarriers for the Treatment of Alzheimer's Disease.

Currently, many therapeutic drugs are difficult to cross the blood-brain barrier (BBB), making it difficult to reach the site of action and thus fail to achieve the desired efficacy. In recent years, researchers and drug designers have increasingly focused on nanotechnology to break through the difficulty of small molecule inhibitors to cross the blood-brain barrier (BBB) and improve the success rate of drug delivery to the central nervous system. Among the common central neurological diseases, such as encephalitis, Parkinson's, Alzheimer's disease, and epilepsy, Alzheimer's disease has attracted much attention from researchers. Alzheimer's disease is a specific neurodegenerative disease, which causes irreversible degeneration of neurons as well as synapses in the brain, resulting in memory and cognitive dysfunction, along with other psychiatric symptoms and behavioral disorders, which seriously affects people's everyday life. Moreover, nanotechnology has excellent potential for application in AD treatment. Studies have shown that nanocarriers can target the delivery of chemotherapeutic drugs, antioxidants, and other therapeutic substances to brain tissue using existing physiological mechanisms, thus effectively alleviating the disease progression of AD. Therefore, various nanoparticles and nanomedicine have been developed and constructed for diagnosing and treating AD in the past decades, such as nanoparticles, bionanoparticles, liposomes, nano-gel, dendrimers, and self-assembled nanoparticles. This study aims to review the applications and results of nanotechnology in the treatment of Alzheimer's disease in recent years and provide some ideas and clues for future research and development of more effective drug delivery systems.

An Evolutionary Multiobjective Route Grouping-Based Heuristic Algorithm for Large-Scale Capacitated Vehicle Routing Problems.

The capacitated vehicle routing problem (CVRP) has been extensively investigated in the past years due to their applications in a variety of real-world scenarios. However, it is still very challenging for most existing algorithms to tackle large-scale CVRPs (LSCVRPs), namely, CVRPs with hundreds or thousands of customers. In this article, we propose a heuristic algorithm, called EMRG-HA, to address LSCVRPs based on the framework of divide and conquer, where an evolutionary multiobjective route grouping (EMRG) method is suggested to decompose an LSCVRP into small subcomponents. The suggested EMRG adopts a multiobjective evolutionary algorithm for route grouping by simultaneously optimizing three well-defined objectives, intragroup distance, intergroup distance, and intergroup balance in size, which can obtain a set of promising decompositions of LSCVRPs. Based on the EMRG, a local search method is suggested to improve the quality of routes in groups, where only routes in one group instead of in all groups are improved which is determined according to the average serving cost of routes in each group. The performance of the proposed EMRG-HA is verified on 42 test instances from three popular benchmark suites. The experimental results show that the EMRG-HA is superior over eight existing algorithms on most test instances of LSCVRPs, in terms of both computational efficiency and solution quality.