Novel electrospun chitosan/polyvinyl alcohol/zinc oxide nanofibrous mats with antibacterial and antioxidant properties for diabetic wound healing

Non-healing wound is a serious complication of diabetes, associated with extremely slow wound closure, and a high rate of infection, resulting in amputation or losses of limbs, high health care cost and poor quality of patient's life. In the present study, we hypothesized that nanofiber mats composed of a combination of chitosan, polyvinyl alcohol (PVA) and Zinc oxide (ZnO) could be an effective option for faster healing of diabetic wounds due to the wound healing activities of chitosan-PVA nanofibers and antibacterial properties of ZnO. Nanofiber mats of chitosan, PVA and ZnO were synthesized using electrospinning technique. The developed nanofibrous mats were characterized by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), antibacterial and antioxidant assays as well as in vivo wound healing experiments in rabbits. The results revealed that chitosan/PVA/ZnO nanofibrous membranes possessed higher antibacterial potential against E. coli, P. aeruginosa, B. subtilis and S. aureus compared to chitosan/PVA nanofibrous membranes. Moreover, chitosan/PVA/ZnO nanofibrous membranes exhibited higher antioxidant potential compared to chitosan/PVA nanofibrous mats. The in vivo wound healing studies showed that chitosan/PVA/ZnO nanofibrous membranes resulted in accelerated wound healing as compared to chitosan/PVA nanofibers. The current study, thus, reveals that chitosan/PVA/ZnO electrospun scaffolds could be effectively helpful in dressings for diabetic wounds.ThisarticlewasmadepossiblebytheNPRP9-144-3-021grantfundedbyQatarNationalResearchFund(apartofQatarFoundation).Thestatementsmadeherearetotallyresponsibilityofauthors.TheauthorsalsothankfullyacknowledgeMirpurUniversityofScienceandTechnology(MUST),Mirpur,AJK,Pakistanforprovidingtheirfacilitiesneededforcompletionofcurrentstudy.Scopu

Anesthetic considerations in Leigh disease: Case report and literature review

Leigh disease is an extremely rare disorder, characterized by a progressive neurodegenerative course, with subacute necrotizing encephalomyelopathy. It usually presents in infancy with developmental delay, seizures, dysarthria, and ataxia. These patients may also develop episodes of lactic acidosis that usually lead to respiratory failure and death. Due to the rarity of the condition, the most appropriate anesthetic plan remains unclear. We present a patient with Leigh disease, who required general anesthesia. The pathogenesis of the disease is discussed and previous reports of perioperative care from the literature are reviewed

Application of SARIMA model to forecasting monthly flows in Waterval River, South Africa

Knowledge of future river flow information is fundamental for development and management of a river system. In this study, Waterval River flow was forecasted by SARIMA model using GRETL statistical software. Mean monthly flows from 1960 to 2016 were used for modelling and forecasting. Different unit root and Mann–Kendall trend analysis proved the stationarity of the observed flow time series. Based on seasonally differenced correlogram characteristics, different SARIMA models were evaluated; their parameters were optimized, and diagnostic check up of forecasts was made using white noise and heteroscedasticity tests. Finally, based on minimum Akaike Information (AI) and Hannan–Quinn (HQ) criteria, SARIMA (3, 0, 2) x (3, 1, 3)12 model was selected for Waterval River flow forecasting. Comparison of forecast performance of SARIMA models with that of computational intelligent forecasting techniques was recommended for future study.Znajomość przyszłego przepływu wody w rzece jest istotna dla rozwoju i zarządzania w systemie rzecznym. W badaniach prezentowanych w niniejszym artykule prognozowano przepływ w rzece Waterval w Republice Południowej Afryki, używając modelu SARIMA i programu statystycznego GRETL. Do modelowania i budowania prognoz wykorzystano średnie miesięczne przepływy z lat 1960–2016. Różne pierwiastki jednostkowe i analiza trendu Manna–Kendalla dowiodły stacjonarności obserwowanych szeregów czasowych przepływu. Na podstawie sezonowo zróżnicowanych charakterystyk korelogramu oceniono różne modele SARIMA zoptymalizowano ich parametry i wykonano diagnostyczne sprawdzenie prognoz za pomocą białego szumu i testów heteroscedastyczności. Na podstawie minimum AI i kryteriów Hannana–Quinna (HQ), wybrano model SARIMA (3, 0, 2) x (3, 1, 3)12 do prognozowania przepływu w rzece Waterval. W dalszych badaniach proponuje się porównanie prognozowania za pomocą modeli SARIMA i technik komputerowych