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Bioactive wound dressings from poly(vinyl alcohol) (PVA) and zein nanoparticles (NPs) loaded with diclofenac (DLF) were prepared successfully by the single jet electrospinning method. DLF‐loaded zein NPs with an average diameter of ∼228 nm were prepared using anti‐solvent precipitation method. The formulation of zein:DLF 1:1 exhibited optimum encapsulation efficiency of 47.80%. The NPs were characterized by dynamic light scattering, zeta‐potential measurement, and differential scanning calorimetry. In vitro, drug release profiles of the DLF‐loaded zein NPs, and PVA–zein NPs were also studied within 120 h and showed the release efficiency of nearly 80% from zein NPs. A more controlled release of DLF was achieved by embedding the zein NPs in the PVA nanofibers. Fourier transform infrared spectroscopy was used to analyze possible interactions between different components of the fabricated dressings. The mechanical properties of the developed dressings were also evaluated using uniaxial tensile testing. Young's modulus (E) of the dressings decreased after inclusion of zein NPs within the PVA nanofibers. Moreover, fibroblast culturing experiments proved that the composite dressings supported better cell attachment and proliferation compared to PVA nanofibers, by exhibiting moderate hydrophilicity. The results suggested that the electrospun composite dressing of PVA nanofibers and zein NPs is a promising topical drug‐delivery system and have a great potential for wound healing application. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018, 135, 46643.

With the rapid growth of different massive applications and parallel flow requests in Data Center Networks (DCNs), today's providers are confronting challenges in flow forwarding decisions. Since Software Defined Networking (SDN) provides fine granular control, it can be intelligently programmed to distinguish between flow requirements. The present article proposes a knapsack model in which the link bandwidth and incoming flows are modeled as a knapsack capacity and items, respectively. Furthermore, each flow consists of two size and value aspects, acquired through flow size extraction and the type of service value assigned by the SDN controller decision. Indeed, the current work splits the incoming flow size range into Type of Service (ToS) decimal value numbers. The lower the flow size category, the higher the value dedicated to the flow. Particle Swarm Optimization (PSO) optimizes the knapsack problem and first forwards the selected-flows by KP-PSO, and the non-selectedflows second. To address the shortcomings of these methods in the event of dense parallel flow detection, the present study puts the link under the threshold of a 70% load by simultaneous requests. Experimental results indicate that the proposed method outperforms Sonum, Hedera, and ECMP in terms of flow completion time, packet loss rate, and goodput regarding flow size requirements.

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MicroRNAs (miRNAs) have shown great potential to be used as biomarkers for the screening and clinical diagnosis of cancer. In this study, an electrochemical biosensor based on graphene-modified glassy carbon electrode was developed for the detection of miRNA-21, a well-known biomarker for the early stage of prostate cancer. A novel molecular tethering agent was used for immobilization of single-stranded probe DNA onto the electrode surface. Different parameters related to biosensor fabrication and experimental conditions were optimized to obtain the highest biosensor response. Electrochemical impedance spectroscopy was employed to achieve a sensitive and label-free detection method for miRNA-21 through measuring the change in charge-transfer resistance (Rct) before and after hybridization. Under the optimal conditions, the biosensor showed a linear impedimetric response between ΔRct and logarithm of miRNA-21 concentration ranging from 10−14 to 10−8 M with a correlation coefficient of 0.972 and a detection limit of 3 fM. The selectivity of the biosensor was examined against non-complementary miRNA-141. The biosensor showed acceptable reproducibility, regeneration ability and stability as well as remarkable response (recoveries 90%–116%) in real plasma samples. The results indicated that the proposed biosensor could be used as a promising alternative to conventional methods in early clinical and point-of-care cancer diagnosis.

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