Infected wounds are a major threat among diabetic patients. Technological advancements are currently increasing the number of new adjunctive therapies that may be potent agents for speeding recovery, lowering the amputation rate and limiting infection recurrences. A novel formula with promising antibacterial activity, namely sericin/propolis/Amoxicillin nanoparticles, was assessed as a potent treatment of infected wounds in normal and diabetic rats. Skin wound healing efficiency was assessed through wound healing scorings, bacterial load assessment and histological examinations. It was revealed that upon using sericin/propolis/Amoxicillin nanoparticles, complete wound healing was successfully achieved after 10 and 15 days postinjury for nondiabetic and diabetic rats, respectively. However, the bacterial load in the induced infected wounds was extremely low (0–10 CFU/mL) after 15 days post-treatment. The histological studies revealed that the dermis was more organized with new matrix deposition, and mature collagen fibers were observed among the treated animal groups. The present study is the first preclinical study which reported the importance of silk sericin in the form of nano-sericin/propolis loaded with Amoxicillin as an effective treatment against bacterial wound infections.

In this paper, the quasi-elastic scattering (p, n) reactions are studied for a wide range of target nuclei 13C, 14C, 48Ca, 90Zr and 208Pb and different incident energies (35-160 MeV). The phenomenological Optical model potential and density independent approaches are used for these calculations in comparison with density dependent semi-microscopic approach. The density dependent parameters are modified to achieve the best calculations for many targets at different energy levels.

Conclusion:We proposed a novel nomogram model on easily available and inexpensive clinicopathologic features, peripheral blood indicators which is beneficial in individual risk assessment for advanced NSCLC patients before receiving PD-1 inhibitors, and assisting clinicians in accurately determining therapeutic decisions.