Antibacterial Activity of Juglone Revealed in a Wound Model of Staphylococcus aureus Infection.

A serious problem currently facing the field of wound healing is bacterial infection, especially Staphylococcus aureus (S. aureus) infection. Although the application of antibiotics has achieved good effects, their irregular use has resulted in the emergence of drug-resistant strains. It is thus the purpose of this study to analyze whether the naturally extracted phenolic compound, juglone, can inhibit S. aureus in wound infection. The results show that the minimum inhibitory concentration (MIC) of juglone against S. aureus was 1000 µg/mL. Juglone inhibited the growth of S. aureus by inhibiting membrane integrity and causing protein leakage. At sub-inhibitory concentrations, juglone inhibited biofilm formation, the expression of α-hemolysin, the hemolytic activity, and the production of proteases and lipases of S. aureus. When applied to infected wounds in Kunming mice, juglone (50 µL juglone with a concentration of 1000 µg/mL) significantly inhibited the number of S. aureus and had a significant inhibitory effect on the expression of inflammatory mediators (TNF-α, IL-6 and IL-1ß). Moreover, the juglone-treated group promoted wound healing. At the same time, in animal toxicity experiments, juglone had no obvious toxic effects on the main tissues and organs of mice, indicating that juglone has good biocompatibility and has the potential to be used in the treatment of wounds infected with S. aureus.

Lysine Inhibits Hemolytic Activity of Staphylococcus aureus and Its Application in Food Model Contaminated with Staphylococcus aureus.

Alpha-hemolysin (Hla) is one of the important exotoxins of Staphylococcus aureus (S. aureus) and can be used as a target to reduce the virulence of S. aureus. This study explored the inhibitory effect of Lysine (Lys) on Hla and its application in food safety. Lys significantly inhibited the expression of Hla at sub-inhibitory concentrations and directly interacted with Hla to interfere with its oligomerization and thus significantly inhibited its hemolytic activity. Notably, Lys attenuated S. aureus damage to mouse small intestine and Caco-2 cells and delayed mouse mortality. In the food model, Lys inhibited the expression of Hla of S. aureus and had no significant effect on the sensory score. Moreover, Lys had no obvious damage effect on the main organs of mice, which indicated that Lys has good biocompatibility and has the potential to be used in the food industry as an anti-S. aureus preparation.

Using stacked deep learning models based on PET/CT images and clinical data to predict EGFR mutations in lung cancer.

Purpose: To determine whether stacked deep learning models based on PET/CT images and clinical data can help to predict epidermal growth factor receptor (EGFR) mutations in lung cancer. Methods: We analyzed data from two public datasets of patients who underwent 18F-FDG PET/CT. Three PET deep learning ResNet models and one CT deep learning ResNet model were trained as low-level predictors based on PET and CT images, respectively. A high-level Support Vector Machine model (Stack PET/CT and Clinical model) was trained using the prediction results of the low-level predictors and clinical data. The clinical data included sex, age, smoking history, SUVmax and SUVmean of the lesion. Fivefold cross-validation was used in this study to validate the prediction performance of the models. The predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves. The area under the curve (AUC) was calculated. Results: One hundred forty-seven patients were included in this study. Among them, 37/147 cases were EGFR mutations, and 110/147 cases were EGFR wild-type. The ROC analysis showed that the Stack PET/CT & Clinical model had the best performance (AUC = 0.85 ± 0.09), with 0.76, 0.85 and 0.83 in sensitivity, specificity and accuracy, respectively. Three ResNet PET models had relatively higher AUCs (0.82 ± 0.07, 0.80 ± 0.08 and 0.79 ± 0.07) and outperformed the CT model (AUC = 0.58 ± 0.12). Conclusion: Using stack generalization, the deep learning model was able to efficiently combine the anatomic and biological imaging information gathered from PET/CT images with clinical data. This stacked deep learning model showed a strong ability to predict EGFR mutations with high accuracy.

The diagnostic value of 18F-FDG PET/CT in identifying the causes of fever of unknown origin.

BACKGROUND: This study investigated the clinical significance of 18F-fluorodeoxyglucose positron emission tomography / computed tomography (18F-FDG PET/CT) in identifying the causes of fever of unknown origin (FUO). METHODS: Patients with a fever who received an 18F-FDG PET/CT examination were retrospectively selected. The means of the two groups were compared using an independent-samples t-test. RESULTS: Among the 89 included patients, 66 were diagnosed using 18F-FDG PET/CT. The sensitivity, specificity and diagnostic accuracy of 18F-FDG PET/CT for the diagnosis of patients with FUO were 84.5%, 25.8%, and 64.0%, respectively. The detection rates of 18F-FDG PET/CT for neoplastic diseases, infectious diseases and non-infectious inflammatory diseases were 100%, 61.3%, and 75%, respectively. The difference in C-reactive protein (CRP) levels between the two groups was statistically significant. CONCLUSIONS: 18F-FDG PET/CT has great clinical importance in diagnosing and identifying causes of FUO and improves the accuracy of FUO diagnosis when combined with serum CRP levels.

Combination Antibiotic Exposure Selectively Alters the Development of Vancomycin Intermediate Resistance in Staphylococcus aureus.

Invasive methicillin-resistant Staphylococcus aureus (MRSA) treated with vancomycin (VAN) is associated with reduced VAN susceptibility and treatment failure. VAN combination therapy is one strategy to improve response, but comprehensive assessments of combinations to prevent resistance are limited. This study identifies optimal combinations to prevent the emergence of VAN-intermediate Staphylococcus aureus (VISA). Two standard MRSA and two heterogeneous VISA (hVISA) strains were exposed for 28 days in vitro to VAN alone, VAN with cefazolin (CFZ), fosfomycin, gentamicin, meropenem, rifampin, piperacillin-tazobactam (TZP), or trimethoprim-sulfamethoxazole. In addition to VAN susceptibility testing, cell wall thickness (CWT), carotenoid content, and membrane fluidity were determined for Mu3. VAN plus any ß-lactam limited the VAN MIC increase to 1 to 4 mg/liter throughout the 28-day exposure, with CFZ and TZP being the most effective agents (VAN MIC = 1 to 2 mg/liter). Similar MIC trends occurred with the lipo-/glycopeptide agents daptomycin and telavancin, where ß-lactam combinations with VAN prevented MIC increases to these agents as well. Combinations with non-ß-lactams were ineffective in preventing VAN MIC increases with VAN MICs of 4 to 16 mg/liter emerging during weeks 2 to 4 of treatment. VAN plus ß-lactam decreased CWT significantly, whereas VAN plus other antibiotics significantly increased the CWT. No correlation was observed between carotenoid content or membrane fluidity and antibiotic exposure. Only the combination exposures of VAN plus ß-lactam suppress the development of VISA. Rational selection of VAN plus ß-lactam should be further explored as a long-term combination treatment of MRSA infections due to their ability to suppress VAN resistance.