Preoperative fasting improves survival after 90% hepatectomy

OBJECTIVE: To assess whether alterations in preoperative fatty acid oxidation and gluconeogenesis induced by fasting will affect survival and liver regeneration following 90% hepatectomy in the rat. DESIGN: In a randomized, controlled trial, Wistar rats (N = 157) were separated into two groups. Rats in the first group fasted for 24 hours. Rats in the second group were allowed to eat ad libitum until the time of operation. These groups were further randomized to receive either 20% glucose or tap water ad libitum postoperatively. INTERVENTIONS: Ninety percent hepatectomy; 24-hour fast; 5% glucose feeding. MAIN OUTCOME MEASURES: Survival, DNA synthesis in the hepatic remnant along with glucokinase activity (GKA) and glycogen content, serum ketone bodies (KB), free fatty acid (FFA), glucose, and ad libitum glucose consumption (GC) were serially quantified. RESULTS: Fasting rats that were offered glucose (fasted/glucose) after hepatectomy demonstrated better survival at 48 hours than the rats that were fed before the procedure and given glucose following hepatectomy (fed/glucose), 95% vs 52% (P < .05). The fasted/glucose group also had a greater peak rate of DNA synthesis (550 +/- 110 vs 275 +/- 40 disintegrations per minute per 0.001 mg of DNA, P < .05). Survival was poor in both groups when only tap water was offered to the animals after hepatectomy (31% vs 12%). In the fasted/glucose group, GC 1 hour after hepatectomy was greater than that for fed rats (1.3 +/- 0.175 vs 0.73 +/- 0.176 g/h, P < .05), yet GKA was suppressed (3.4 +/- 0.42 vs 8.05 +/- 2.77 nmol/min per milligrams of protein, P < .05). Fasting before hepatectomy and consuming glucose after causes elevations in both FFA (1.26 +/- 0.19 vs 0.82 +/- 0.13 mol/mL., P < .05) and KB (18.96 +/- 2.82 vs 11.4 +/- 3.94 mmol/mL, P < .05). Normal glucose was maintained in the fasted/glucose group, but fell to 63 +/- 14 mg/dL at 8 hours after hepatectomy in the fed/glucose group. CONCLUSIONS: Fasting before hepatectomy shifts energy utilization to fat oxidation and gluconeogenesis, which appears to ameliorate liver failure after hepatectomy in this severe model of hepatic resection.     

In vitro mutagenic and anti‐mutagenic properties of green synthesised silver nanoparticles

This study is aimed at determining the mutagenic and anti‐mutagenic properties of silver nanoparticles (AgNPs) biosynthesised from Streptomyces griseorubens AU2. To the authors’ knowledge, this is the first study about the investigation of these properties for biogenic AgNPs bacterially synthesised. The mutagenic and anti‐mutagenic potencies were determined by the Ames Salmonella /microsome mutagenicity test using Salmonella typhimurium TA98 and TA100 strains. After determining the cytotoxic dose of green synthesised AgNPs against S. typhimurium TA98 and TA100 strains, subcytotoxic doses (250, 100 and 50 µg/plate) were used in the assays. Biogenic AgNPs at the tested concentrations exhibited no mutagenic effects in the mutagenicity test conducted with the test strains. Moderate anti‐mutagenic effects were observed at high test concentrations. The concentration of 250 µg/plate showed the strongest anti‐mutagenic activity on S. typhimurium TA98. The results did not indicate any mutagenic effect against either of the strains used for screening the mutagenicity of the biogenic AgNPs as they were found to be genotoxically safe. It can be concluded that biogenic AgNPs showed great anti‐mutagenic attributes, standing as a significant factor with respect to medical, pharmaceutical and cosmetic industries.Inspec keywords: biomedical materials, microorganisms, nanomedicine, nanoparticles, silver, toxicologyOther keywords: in vitro mutagenic properties, in vitro antimutagenic properties, green synthesised silver nanoparticles, Streptomyces griseorubens AU2, biogenic silver nanoparticle biosynthesis, microsome mutagenicity test, Salmonella typhimurium TA98 strains, Salmonella typhimurium TA100 strains, subcytotoxic doses, medical industries, pharmaceutical industries, cosmetic industries, Ag     

Polypyrrole doped graphene nanocomposites as advanced positive electrodes for vanadium redox flow battery

Obtaining high catalytic activity and cycling stability of electrodes play a crucial role in vanadium redox flow batteries (VRFBs). However, some limitations, such as cost and required multiple synthesis procedures force us as an alternative solution; polypyrrole–sulfur-doped graphenes (PPy–SGs) are synthesized with a user-friendly electrochemical method and applied as a positive electrode for VRFB for the first time in the literature. Polypyrrole and sulfur-doped graphenes are formed on the graphite electrodes simultaneously in a 0.001 M pyrrole and 1.0 M H₂SO₄ solution at room temperature by a single-step cyclic voltammetry (CV) process. The electrode surface modification parameters such as the amount of S-doping, defect, and functionality rate of polymers and graphene are controlled by changing the cycle numbers at the scanned in a specific potential range. FTIR, Raman, XPS, SEM, and CV methods show the formation of PPy and sulfur-doped graphene layers on graphite electrode surfaces. The effects of PPy–SGs were investigated in VRFB for VO⁺²/VO₂⁺ redox reactions. The electrochemical measurements of the PPy–SGs are carried out by CV and electrochemical impedance spectroscopy (EIS) analysis. According to CV results, PPy–SG20 demonstrates the best performance as a positive electrode material of the VRFB. This can be attributed to the significant improvement in the electrochemical kinetics by polypyrrole decorating graphene and enhancing active sites.

     

Diabetes Prediction Algorithm Using Recursive Ridge Regression L2

At present, the prevalence of diabetes is increasing because the human body cannot metabolize the glucose level. Accurate prediction of diabetes patients is an important research area. Many researchers have proposed techniques to predict this disease through data mining and machine learning methods. In prediction, feature selection is a key concept in preprocessing. Thus, the features that are relevant to the disease are used for prediction. This condition improves the prediction accuracy. Selecting the right features in the whole feature set is a complicated process, and many researchers are concentrating on it to produce a predictive model with high accuracy. In this work, a wrapper-based feature selection method called recursive feature elimination is combined with ridge regression (L2) to form a hybrid L2 regulated feature selection algorithm for overcoming the overfitting problem of data set. Overfitting is a major problem in feature selection, where the new data are unfit to the model because the training data are small. Ridge regression is mainly used to overcome the overfitting problem. The features are selected by using the proposed feature selection method, and random forest classifier is used to classify the data on the basis of the selected features. This work uses the Pima Indians Diabetes data set, and the evaluated results are compared with the existing algorithms to prove the accuracy of the proposed algorithm. The accuracy of the proposed algorithm in predicting diabetes is 100%, and its area under the curve is 97%. The proposed algorithm outperforms existing algorithms.     

A study of some equation‐of‐state parameters of poly(methylhydrosiloxane‐co‐dimethylsiloxane) with some solvents by gas chromatography

Trace amount of methyl acetate, ethyl acetate, tert‐butyl acetate, pentane, hexane, and heptane were passed through the chromatographic column loaded with poly(methylhydrosiloxane‐co‐dimethylsiloxane) coated on Chromosorb W. The retention diagrams of the solvents on the copolymer were plotted by means of specific retention volumes at temperatures between 40 and 80°C by inverse gas chromatography technique. In this study, some thermodynamic interaction parameters such as Flory–Huggins polymer–solvent interaction parameter, equation‐of‐state polymer–solvent interaction parameter, effective exchange energy parameter, and weight fraction activity coefficients at infinite dilution of the solvent were determined. Then, the exchange enthalpy parameter and entropy parameter were determined by using a relation for the enthalpy interaction parameter of the equation‐of‐state theory, which is arranged for the inverse gas chromatography conditions. Later, the partial molar heat of sorption and the partial molar heat of mixing were obtained. The solubility parameter of this copolymer was determined as 6.64 (cal/cm³)^1/2 at room temperature. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 1627–1631, 2007     

Scalable fabrication of high-performance graphene/polyamide 66 nanocomposites with controllable surface chemistry by melt compounding

Scalable and ease fabrication of high-performance graphene reinforced polyamide 66 (PA66) nanocomposites by melt-mixing were achieved by selecting ideal graphene reinforcement having high C/O ratio. In this study, single-layer amine functionalized reduced graphene oxide and multi-layer thermally exfoliated graphene oxide (TEGO) were used to investigate the influence of surface chemistry and dispersion state on crystallization behaviors, mechanical, and thermal properties of graphene reinforced PA66 nanocomposites. Both types of graphenes acted as nucleating agent but TEGO showed the better performance due to its intercalated structure formation mechanism and efficient viscous flow during melting. Mechanical results indicated that 0.5 wt% TEGO based PA66 nanocomposite showed the highest tensile properties by increasing tensile modulus and tensile strength up to 45% and 16.1%, respectively. In addition, TEGO reinforced nanocomposites showed more stable viscoelastic behavior by reaching a plateau at high temperatures and restraining long-range motion of polymer chains.     

Polymerization of pyrrole derivatives on polyacrylonitrile matrix,FTIR–ATR and dielectric spectroscopic characterization of composite thin films

Oxidative polymerization of acrylonitrile (AN) initiated by Ce(IV)–oxalic acid redox system in the aqueous medium was performed and polyacrylonitrile (PAN)/polypyrrole (PPy) composite thin films were prepared by polymerization of pyrrole on polyacrylonitrile matrix. Effect of concentration of pyrrole derivatives on the resulting polymeric film properties was investigated. The influence of the pyrrole derivative type and content on the dielectric permittivity, dielectric loss and electrical properties of the composite films were analyzed in the frequency range from 0.05 Hz to 10 MHz. For a selected concentration of 200 μl of composite films at 10⁷ Hz, the conductivity was found to be in the following order: PAN–PPy < PAN–PNMPy < PAN–PNPhPy. Dielectric constant increase of the composite films was more obvious when the quantity of n-phenyl pyrrole was increased. A linear relationship was observed between the absorbances (FTIR–ATR) and conductivities (dielectric spectroscopy).     

Effect of Applied Current Density on Morphological and Structural Properties of Electrodeposited Fe-Cu Films

A detailed study has been carried out to investigate the effect of applied current density on the composition, crystallographic structure, grain size, and surface morphology of Fe-Cu films. X-ray diffraction (XRD) results show that the films consist of a mixture of face-centered cubic (fcc) Cu and body centered cubic (bcc) α-Fe phases. The average crystalline size of both Fe and Cu particles decreases as the applied current density becomes more negative. Compositional analysis of Fe-Cu films indicates that the Fe content within the films increases with decreasing current density towards more negative values. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) have been used to investigate the surface morphology of Fe-Cu films. It is observed that the surface morphology of the films changes from dendritic structure to a cauliflower structure as the applied current density becomes more negative. The surface roughness and grain size of the Fe-Cu films decrease with decreasing applied current density towards more negative values.