Preparation And Antibacterial Effects Of Carboxymethyl Chitosan-Modified Photo-Responsive Camellia Sapogenin Derivative Cationic Liposomes

BACKGROUND

Bacterial resistance to antibiotics is a persistent and intractable problem. The sapogenin isolated from the seeds of Camellia oleifera can inhibit antibiotic-resistant bacteria after structural modification.

PURPOSE

This study aims to improve sapogenin's antibacterial activity and avoid bacterial resistance based on nano-preparation with photo responsiveness.

METHODS

The liposome shell material of carboxymethyl chitosan-phosphatidyl ethanolamine (CMC-PE) was prepared using amidation reaction, and photo-responsive cationic (PCC) liposomes containing Camellia sapogenin derivative (CSD) and photosensitizer pheophorbide-a were prepared by film dispersion method. Encapsulation efficiency, drug loading, zeta potential, particle size distribution, morphology and stability of the PCC liposomes were determined by HPLC, particle size analyzer, transmission electron microscopy (TEM) and fluorescence microscopy. Photo-responsive release of CSD in the PCC liposomes was determined by laser (0.5 mW/cm2) at 665 nm. Antibacterial activity of the PCC liposomes with or without irradiation was analyzed by MIC50, MBC, MBIC50, and bacterial morphology to evaluate the antibacterial effects on amoxicillin resistant Escherichia coli and Staphylococcus aureus.

RESULTS

Size distribution, zeta potential, encapsulation efficiency and drug loading of the PCC liposomes were 189.23 ± 2.12 nm, 18.80 ± 1.57 mV, 83.52 ± 1.53% and 2.83 ± 0.05%, respectively. The PCC liposomes had higher storage stability and gastrointestinal stability, and no obvious hemolytic toxicity to rabbit red blood cells and no cytotoxicity after incubation with Hela cells. The photosensitizer pheophorbide-a was uniformly dispersed in the phospholipid layer of the PCC liposomes and increased the CSD release after irradiation. The PCC liposomes could bind to bacteria and impaired their morphology and structure, and had significant bactericidal effect on amoxicillin resistant E. coli and S. aureus.

CONCLUSION

The photo-responsive PCC liposomes are efficient antibacterial agents for avoidance of bacterial resistance against antibiotics.

Fuzzy rules to predict degree of malignancy in brain glioma

The current pre-operative assessment of the degree of malignancy in brain glioma is based on magnetic resonance imaging (MRI) findings and clinical data. 280 cases were studied, of which 111 were high-grade malignancies and 169 were low-grade, so that regular and interpretable patterns of the relationships between glioma MRI features and the degree of malignancy could be acquired. However, as uncertainties in the data and missing values existed, a fuzzy rule extraction algorithm based on a fuzzy min-max neural network (FMMNN) was used. The performance of a multi-layer perceptron network (MLP) trained with the error back-propagation algorithm (BP), the decision tree algorithm ID3, nearest neighbour and the original fuzzy min-max neural network were also evaluated. The results showed that two fuzzy decision rules on only six features achieved an accuracy of 84.6% (89.9% for low-grade and 76.6% for high-grade cases). Investigations with the proposed algorithm revealed that age, mass effect, oedema, postcontrast enhancement, blood supply, calcification, haemorrhage and the signal intensity of the T1-weighted image were important diagnostic factors.