Journal of Drug Targeting最新文献

Carbon nanotubes (CNTs) are allotropes of carbon, composed of carbon atoms forming a tube-like structure. Their high surface area, chemical stability, and rich electronic polyaromatic structure facilitate their drug-carrying capacity. Therefore, CNTs have been intensively explored for several biomedical applications, including as a potential treatment option for cancer. By incorporating smart fabrication strategies, CNTs can be designed to specifically target cancer cells. This targeted drug delivery approach not only maximizes the therapeutic utility of CNTs but also minimizes any potential side effects of free drug molecules. CNTs can also be utilised for photothermal therapy (PTT) which uses photosensitizers to generate reactive oxygen species (ROS) to kill cancer cells, and in immunotherapeutic applications. Regarding the latter, for example, CNT-based formulations can preferentially target intra-tumoural regulatory T-cells. CNTs also act as efficient antigen presenters. With their capabilities for photoacoustic, fluorescent and Raman imaging, CNTs are excellent diagnostic tools as well. Further, metallic nanoparticles, such as gold or silver nanoparticles, are combined with CNTs to create nanobiosensors to measure biological reactions. This review focuses on current knowledge about the theranostic potential of CNT, challenges associated with their large-scale production, their possible side effects and important parameters to consider when exploring their clinical usage.

Dehydrocurvularin (DCV) is a promising lead compound for anti-cancer therapy. Unfortunately, the development of DCV-based drugs has been hampered by its poor solubility and bioavailability. Herein, we prepared a DCV-loaded mPEG-PLGA nanoparticles (DCV-NPs) with improved drug properties and therapeutic efficacy. The spherical and discrete particles of DCV-NPs had a uniform diameter of 101.8 ± 0.45 nm and negative zeta potential of -22.5 ± 1.12 mV (pH = 7.4), and its entrapment efficiency (EE) and drug loading (DL) were ∼53.28 ± 1.12 and 10.23 ± 0.30%, respectively. In vitro the release of DCV-NPs lasted for more than 120 h in a sustained-release pattern, its antiproliferation efficacy towards breast cancer cell lines (MCF-7, MDA-MB-231, and 4T1) was better than that of starting drug DCV, and it could be efficiently and rapidly internalised by breast cancer cells. In vivo DCV-NPs were gradually accumulated in tumour areas of mice and significantly suppressed tumour growth. In summary, loading water-insoluble DCV onto nanoparticles has the potential to be an effective agent for breast cancer therapy with injectable property and tumour targeting capacity.

Efficient brain drug delivery has been a challenge in the treatment of Alzheimer's Disease and other brain disorders as blood-brain barrier (BBB) impedes most drugs to reach brain. To overcome this obstacle, we developed a novel TGN decorated erythrocyte membrane-coated poly (lactic-co-glycolic acid) nanoparticle (TRNNs). The nanoparticle significantly boosted the penetration (7.3 times) in a U-118MG and HCMEC/D3 cell co-culture BBB model in vitro. Living image was performed to assess the TRNNs distribution in vivo. The fluorescence intensity in the isolated brain of TRDNs-treated mice was about 8 times that of the DNs-treated. In the novel object recognition test, the mice after administration of TRDNs showed higher recognition index (0.414 ± 0.016) than the model group (0.275 ± 0.019). A significant increase in the number of dendritic spines from TRNNs administrated mice hippocampi neurons was observed after Golgi stain. This improvement of neurons was also confirmed by the significant high expression of PSD95 protein level in hippocampi. We measured the OD values of Aβ_25-35 induced PC12 cells that pre-treatment with different nanoparticles and concluded that TRNNs had a robust neuroprotection effect. Above all, functional biomimetic nanoparticles could increase the accumulation of naringenin into brain, thereby enable the drug to exert greater therapeutic effects.

There is strong interest to improve the therapeutic potential of gold nanoparticles (GNPs) while ensuring their safe development. The utility of GNPs in medicine requires a molecular-level understanding of how GNPs interact with biological systems. Despite considerable research efforts devoted to monitoring the internalisation of GNPs, there is still insufficient understanding of the factors responsible for the variability in GNP uptake in different cell types. Data-driven models are useful for identifying the sources of this variability. Here, we trained multiple machine learning models on 2077 data points for 193 individual nanoparticles from 59 independent studies to predict cellular uptake level of GNPs and compared different algorithms for their efficacies of prediction. The five ensemble learners (Xgboost, random forest, bootstrap aggregation, gradient boosting, light gradient boosting machine) made the best predictions of GNP uptake, accounting for 80-90% of the variance in the test data. The models identified particle size, zeta potential, GNP concentration and exposure duration as the most important drivers of cellular uptake. We expect this proof-of-concept study will foster the more effective use of accumulated cellular uptake data for GNPs and minimise any methodological bias in individual studies that may lead to under- or over-estimation of cellular internalisation rates.

We have previously demonstrated that messenger RNA (mRNA) lipoplexes composed of N-hexadecyl-N,N-dimethylhexadecan-1-aminium bromide (DC-1-16), 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), and polyethylene glycol-cholesteryl ether (PEG-Chol) exhibited high protein expression in the lungs and spleen of mice after intravenous injection and induced high levels of antigen-specific IgG1 upon immunisation. In this study, we optimised PEG modification in mRNA lipoplexes to reduce mRNA accumulation in the lungs and evaluated the suppression of tumour growth in mice bearing mouse lymphoma E.G7-ovalbumin (OVA) tumours by immunising them with an intravenous injection of OVA mRNA lipoplexes. PEGylation of mRNA lipoplexes with 3 mol% PEG-Chol (LP-DC-1-16-3PCL) prevented agglutination of erythrocytes and reduced accumulation in the lungs. Intravenous injection of LP-DC-1-16-3PCL lipoplexes containing OVA mRNA into mice induced high levels of anti-OVA IgG1 (83,000 mU/mL) in serum, and exhibited a high cytotoxic activity (97%) against E.G7-OVA cells by the splenocytes of mice. Furthermore, immunisation with LP-DC-1-16-3PCL lipoplexes containing OVA mRNA suppressed E.G7-OVA tumour growth compared to control mRNA. Based on these results, LP-DC-1-16-3PCL lipoplexes may be an effective mRNA vaccine for inducing antibody- and cytotoxic cell-mediated immune responses to tumours through intravenous injection.

Background: Dry eye disease (DED) is often secondary to diabetes mellitus (DM).Purpose: This study is to explore the action of Wilms tumor 1-associated protein (WTAP) in DM-DED via lncRNA NEAT1 m6A methylation.Methods: DM-DED mouse models were treated with sh-WTAP/sh-NEAT1, followed by assessment of corneal epithelial damage/histopathological changes. HCE-2 cells were exposed to hyperosmotic conditions to establish in vitro DED models and treated with oe-NEAT1/sh-NEAT1/sh-WTAP/nigericin (an NLRP3 inflammasome inducer). Cell viability/apoptosis were evaluated by CCK-8/TUNEL. Levels of WTAP/NEAT1/inflammatory factors/NLRP3 inflammasome- and apoptosis-related markers were determined. m6A modification was examined by MeRIP-qPCR and NEAT1 stability was also detected.Results: DM-DED mice exhibited up-regulated WTAP/NEAT1 expression and severe corneal damage, whereas WTAP/NEAT1 knockdown alleviated inflammation/corneal damage. In hyperosmolarity-induced HCE-2 cells, NEAT1 aggravated inflammation and apoptosis, while NEAT1 knockdown suppressed NLRP3 inflammasome activation and ameliorated cell injury. Hyperosmolarity-induced WTAP expression increased m6A modification and NEAT1 mRNA stability. WTAP mediated m6A methylation of NEAT1 and NLRP3 inflammasome activation in DM-DED mice.

Metabolic heterogeneity is one of the characteristics of tumour cells. In order to adapt to the tumour microenvironment of hypoxia, acidity and nutritional deficiency, tumour cells have undergone extensive metabolic reprogramming. Metabolites involved in tumour cell metabolism are also very different from normal cells, such as a large number of lactate and adenosine. Metabolites play an important role in regulating the whole tumour microenvironment. Taking metabolites as the target, it aims to change the metabolic pattern of tumour cells again, destroy the energy balance it maintains, activate the immune system, and finally kill tumour cells. In this paper, the regulatory effects of metabolites such as lactate, glutamine, arginine, tryptophan, fatty acids and adenosine were reviewed, and the related targeting strategies of nano-medicines were summarised, and the future therapeutic strategies of nano-drugs were discussed. The abnormality of tumour metabolites caused by tumour metabolic remodelling not only changes the energy and material supply of tumour, but also participates in the regulation of tumour-related signal pathways, which plays an important role in the survival, proliferation, invasion and metastasis of tumour cells. Regulating the availability of local metabolites is a new aspect that affects tumour progress. (The graphical abstract is by Figdraw).

Niclosamide (NCL) is repurposed to treat inflammatory bowel disease due to its anti-inflammatory properties and potential to reduce oxidative stress. This therapeutic activity remains challenging if administered directly due to its low solubility and high recrystallization tendency in gastric pH. Solid dispersions using pH-dependent polymer will be a better idea to improve the solubility, dissolution and targeted delivery at the colon. Hot melt extrusion was used to formulate a solid dispersion with 30% NCL utilising hydroxypropyl methylcellulose acetate succinate as a pH-dependent polymer. In vitro drug release studies revealed formulation (F1) containing 10%w/w Tween 80 showed minimal release (2.06%) at the end of 2 h, followed by 47.87% and 82.15% drug release at 6 h and 14 h, respectively, indicating the maximum amount of drug release in the colon. The drug release from the formulations containing no plasticiser and 5%w/w plasticiser was comparable to the pure crystalline drug (approximately 25%). Solid-state analysis confirmed particle conversion of crystalline NCL to amorphous form, and the optimised formulation was stable for 6 months without significant changes in dissolution profile. In contrast to pure NCL, the F1 formulation substantially reduced the disease activity index, colonic inflammation, histological alterations and oxidative damage in colitis mice. These findings reveal that the prepared formulation can potentially deliver the drug locally at the colon, making it an effective tool in treating ulcerative colitis.

Botulinum toxin is a protein toxin secreted by Clostridium botulinum that is strongly neurotoxic. Due to its characteristics of being super toxic, quick acting, and difficult to prevent, the currently reported antiviral studies focusing on monoclonal antibodies have limited effectiveness. Therefore, for the sake of effectively prevention and treatment of botulism and to maintain country biosecurity as well as the health of the population, in this study, we intend to establish a single chain antibody (scFv) targeting the carboxyl terminal binding functional domain of the botulinum neurotoxin heavy chain (BONT/AHc) of botulinum neurotoxin type A, and explore the value of a new passive immune method in antiviral research which based on adeno-associated virus (AAV) mediated vector immunoprophylaxis (VIP) strategy. The scFv small-molecular single-chain antibody sequenced, designed, constructed, expressed and purified by hybridoma has high neutralising activity and affinity level, which can lay a good foundation for the modification and development of antibody engineering drugs. In vivo experiments, AAV-mediated scFv engineering drug has good anti-BONT/A toxin neutralisation ability, has advantages of simple operation, stable expression and good efficacy, and may be one of the effective treatment strategies for long-term prevention and protection of BONT/A botulinum neurotoxin.

Background: Machine learning algorithms that can quickly and easily estimate skin permeability (Kp) are increasingly being used in drug delivery research. The linear free energy relationship (LFER) developed by Abraham is a practical technique for predicting Kp. The permeability coefficients and Abraham solute descriptor values for 175 organic compounds have been documented in the scientific literature.Purpose: The purpose of this project was to use a publicly available dataset to make skin permeability predictions using the random forest and XBoost regression techniques.Methods: We employed Pandas-based methods in JupyterLab to predict permeability coefficient (Kp) from solute descriptors (excess molar refraction [E], combined dipolarity/polarizability [S], overall solute hydrogen bond acidity and basicity [A and B], and the McGowan's characteristic molecular volume [V]).Results: The random forest and XG Boost regression models established statistically significant association between the descriptors and the skin permeability coefficient.