Deduction of a facile method to construct Antheraea mylitta silk fibroin/gelatin blend films for prospective biomedical applications

Blend films of two types (I and II) were prepared by mixing Antheraea mylitta silk fibroin (AMF) and gelatin solution in various blend ratios via the solution casting method. Two different crosslinkers, namely glutaraldehyde and genipin, were used during blend preparation. The structural characteristics and thermal properties of the blend films were examined by Fourier transform infrared (FTIR) spectroscopy, X‐ray diffraction (XRD), Thermogravimetric analysis (TGA) and Diffrential scanning calorimetery (DSC). The FTIR spectra showed conformational alterations in type I blend films while type II films attained high β‐sheet crystallinity. The XRD diffractograms presented a high degree of crystallinity in type II blend films compared to type I, which showed an almost amorphous structure. Further, thermal and biological studies were conducted on type II films. According to the TGA thermograms, the degradation temperature of the crosslinked blend films shifted compared to pure gelatin and pure AMF films. Partial miscibility of the two components was indicated by DSC thermograms of the blends. The high water uptake capacity of type II blend films was found to imitate hydrogel behaviour. The blend films did not show any toxicity in 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyl tetrazolium bromide (MTT) assay and supported L929 fibroblast cell spreading and proliferation. The biodegradation of the blend films was significantly faster than the pure silk film. © 2020 Society of Industrial Chemistry     

Pull-Down of Metalloproteins in Their Native States by Using Desthiobiotin-Based Probes

One-third of all proteins are estimated to require metals for structural stability and/or catalytic activity. Desthiobiotin probes containing metal binding groups can be used to capture metalloproteins with exposed active-site metals under mild conditions so as to prevent changes in metallation state. The proof-of-concept was demonstrated with carbonic anhydrase (CA), an open active site, Zn²⁺-containing protein. CA was targeted by using sulfonamide derivatives. Linkers of various lengths and structures were screened to determine the optimal structure for capture of the native protein. The optimized probes could selectively pull down CA from red blood cell lysate and other protein mixtures. Pull-down of differently metallated CAs was also investigated.     

Catechol-O-methyltransferase-deficient mice exhibit sexually dimorphic changes in catecholamine levels and behavior

Catechol-O-methyltransferase (COMT) is one of the major mammalian enzymes involved in the metabolic degradation of catecholamines and is considered a candidate for several psychiatric disorders and symptoms, including the psychopathology associated with the 22q11 microdeletion syndrome. By means of homologous recombination in embryonic stem cells, a strain of mice in which the gene encoding the COMT enzyme has been disrupted was produced. The basal concentrations of brain catecholamines were measured in the striatum, frontal cortex, and hypothalamus of adult male and female mutants. Locomotor activity, anxiety-like behaviors, sensorimotor gating, and aggressive behavior also were analyzed. Mutant mice demonstrated sexually dimorphic and region-specific changes of dopamine levels, notably in the frontal cortex. In addition, homozygous COMT-deficient female (but not male) mice displayed impairment in emotional reactivity in the dark/light exploratory model of anxiety. Furthermore, heterozygous COMT-deficient male mice exhibited increased aggressive behavior. Our results provide conclusive evidence for an important sex- and region-specific contribution of COMT in the maintenance of steady-state levels of catecholamines in the brain and suggest a role for COMT in some aspects of emotional and social behavior in mice.     

Oxidant damage to erythrocyte membrane in glucose-6-phosphate dehydrogenase deficiency: correlation with in vivo reduced glutathione concentration and membrane protein oxidation

Chronic nonspherocytic hemolytic anemia has been observed in a recently described glucose-6-phosphate dehydrogenase (G6PD) variant, G6PDWayne. The mechanical properties of these erythrocytes and other G6PD variants were examined. The deformability of G6PD-deficient erythrocytes was normal, as determined by osmotic scan ektacytometry, and was not significantly affected by hemolytic crisis. In the common varieties of G6PD deficiency, the mechanical stability of the red blood cell (RBC) membrane was greater than normal, but G6PDWayne membranes were abnormally susceptible to shear-induced fragmentation. There was no evidence for a concurrent genetic defect in spectrin, because self-association constants and tryptic digests were normal. The fragility of G6PDWayne membranes appeared to be a consequence of oxidative damage to membrane thiol groups associated with a low glutathione (GSH) level in these RBCs. Associations among GSH level, thiol oxidation, and membrane instability were also found when a larger group of G6PD-deficient RBCs were examined. In normal erythrocytes, 1-chloro-2,4-dinitrobenzene was used to reduce GSH levels by 50%. Membrane thiol oxidation and membrane fragility both increased when these cells were kept at 4 degrees C for 3 to 5 days. Our findings suggest that chronic depletion of GSH leads to the destabilization of membrane skeleton through oxidation of membrane protein thiols.     

An efficient neural-network model for real-time fault detection in industrial machine

Neural Computing and Applications - Induction machines have extensive demand in industries as they are used for large-scale production and, therefore, vulnerable to both electrical and mechanical...     

Modeling of poly(ethylene terephthalate) reactors. IX. Solid state polycondensation process

A mathematical model for simulation of industrial process of solid state polycondensation of poly(ethylene terephthalate) (PET) has been developed. The model eliminates errors evident in the earlier models by proper formulation. The model results have been validated by experimental data in the literature. It enables prediction of the influence of particle shape, size, temperature, etc. on the polycondensation process correctly in all different regimes of operation, apart from bringing out the importance of gas-side resistance, influence of carrier gas, etc. for the first time.     

On the Black-Box Complexity of Sperner’s Lemma

We present several results on the complexity of various forms of Sperner’s Lemma in the black-box model of computing. We give a deterministic algorithm for Sperner problems over pseudo-manifolds of arbitrary dimension. The query complexity of our algorithm is linear in the separation number of the skeleton graph of the manifold and the size of its boundary. As a corollary we get an deterministic query algorithm for the black-box version of the problem 2D-SPERNER, a well studied member of Papadimitriou’s complexity class PPAD. This upper bound matches the deterministic lower bound of Crescenzi and Silvestri. The tightness of this bound was not known before. In another result we prove for the same problem an lower bound for its probabilistic, and an lower bound for its quantum query complexity, showing that all these measures are polynomially related. Research supported by the European Commission IST Integrated Project Qubit Application (QAP) 015848, the OTKA grants T42559 and T46234, and by the ANR Blanc AlgoQP grant of the French Research Ministry.     

Implicit Continuous User Authentication for Mobile Devices based on Deep Reinforcement Learning

The predominant method for smart phone accessing is confined to methods directing the authentication by means of Point-of-Entry that heavily depend on physiological biometrics like, fingerprint or face. Implicit continuous authentication initiating to be loftier to conventional authentication mechanisms by continuously confirming users’ identities on continuing basis and mark the instant at which an illegitimate hacker grasps dominance of the session. However, divergent issues remain unaddressed. This research aims to investigate the power of Deep Reinforcement Learning technique to implicit continuous authentication for mobile devices using a method called, Gaussian Weighted Cauchy Kriging-based Continuous Czekanowski’s (GWCK-CC). First, a Gaussian Weighted Non-local Mean Filter Preprocessing model is applied for reducing the noise present in the raw input face images. Cauchy Kriging Regression function is employed to reduce the dimensionality. Finally, Continuous Czekanowski’s Classification is utilized for proficient classification between the genuine user and attacker. By this way, the proposed GWCK-CC method achieves accurate authentication with minimum error rate and time. Experimental assessment of the proposed GWCK-CC method and existing methods are carried out with different factors by using UMDAA-02 Face Dataset. The results confirm that the proposed GWCK-CC method enhances authentication accuracy, by 9%, reduces the authentication time, and error rate by 44%, and 43% as compared to the existing methods.     

Hybrid Recommender System Using Systolic Tree for Pattern Mining

A recommender system is an approach performed by e-commerce for increasing smooth users’ experience. Sequential pattern mining is a technique of data mining used to identify the co-occurrence relationships by taking into account the order of transactions. This work will present the implementation of sequence pattern mining for recommender systems within the domain of e-commerce. This work will execute the Systolic tree algorithm for mining the frequent patterns to yield feasible rules for the recommender system. The feature selection's objective is to pick a feature subset having the least feature similarity as well as highest relevancy with the target class. This will mitigate the feature vector's dimensionality by eliminating redundant, irrelevant, or noisy data. This work presents a new hybrid recommender system based on optimized feature selection and systolic tree. The features were extracted using Term Frequency-Inverse Document Frequency (TF-IDF), feature selection with the utilization of River Formation Dynamics (RFD), and the Particle Swarm Optimization (PSO) algorithm. The systolic tree is used for pattern mining, and based on this, the recommendations are given. The proposed methods were evaluated using the MovieLens dataset, and the experimental outcomes confirmed the efficiency of the techniques. It was observed that the RFD feature selection with systolic tree frequent pattern mining with collaborative filtering, the precision of 0.89 was achieved.     

Bridging the gap: effect of text query reformulation in multimodal retrieval

Multimedia Tools and Applications - Multimodal Retrieval provides new paradigms and methods aimed at effectively searching through the enormous volume of data. Multimodal retrieval is a well...