Determination of Xenoestrogenic Compounds Using a Nanostructured Biosensing Device

A ternary composite material based on Prussian blue, single‐walled carbon nanotubes and 1‐butyl‐3‐methylimidazolium hexafluorophosphate was prepared and tested for electrochemical detection of H₂O₂. The sensor allows amperometric detection of H₂O₂ at ?0.05 V, with a sensitivity of 137 mA M^?1?cm^?2. The nanocomposite provides a favorable microenvironment for immobilization of horseradish peroxidase (HRP). Determination of xenoestrogenic compounds was performed by enzymatic oxidation at the surface of modified screen printed biosensor in the presence of H₂O₂. The developed electrochemical biosensors exhibited high sensitivity, low detection limits, good operational and storage stability, for detection of 4‐t‐butylphenol, 4‐t‐octylphenol, 4‐n‐nonylphenol and 4‐n‐nonylphenol ethoxylate.     

Synergistic effect of mediator–carbon nanotube composites for dehydrogenases and peroxidases based biosensors

Very sensitive, low cost and reliable NADH and H₂O₂ sensors were realised and used for development of enzyme based biosensors. The active surface of the electrodes was modified with a nanocomposite obtained by modification of SWNT with a proper mediator: Meldola Blue (for NADH) and Prussian Blue (for H₂O₂). Low applied potential of − 50 mV vs. Ag/AgCl reference electrode proved the synergistic effect of nanocomposite materials towards NADH and H₂O₂ detection. Biosensors for malic acid and alkylphenols have been developed, using mediator-functionalised-SWNT-based electrodes and two different classes of enzymes: NAD⁺-dependent dehydrogenases and peroxidases. Immobilization of the enzymes was realised using a series of different procedures — adsorption, Nafion membrane, sol–gel and glutaraldehyde, in order to find the best configuration for a good operational stability. A higher sensitivity comparing with other reported biosensors of about 12.41 mA/M·cm² was obtained for l-malic acid biosensor with enzyme immobilised in Nafion membrane. Phenol, 4-t-octylphenol and 4-n-nonylphenol were used as standard compounds for HRP based biosensor. Fast biosensor response and comparable detection limit with HPLC methods were achieved.     

LC/MS and LC/MS/MS based protocol for identification of dyes in historic textiles

Identification of dyes in historic textiles was until recently only based on reversed phase liquid chromatography and diode-array detection (RPLC–DAD). Although in the last years mass spectrometry (MS) is increasingly used as a detection system for liquid chromatography, most applications in the field are directed to identification of the molecular ions or in studies dedicated to degradation products which may be used as markers in RPLC–DAD. In the present work, an analytical protocol for the identification of dyes using RPLC/ESI/MS is presented. Atmospheric pressure electrospray ionization (ESI) was applied, in the negative ion monitoring mode. Both single stage and tandem MS (MS/MS) approaches were considered. An ion trap was used as mass analyzer. Experiments are based on the characterization of standards (natural dyes and/or dyed fibers) with the mass spectrometer sequentially working in the following modes: single MS/full scan, followed by plotting chromatograms through ion extraction (IEC) according to mass/charge ratios corresponding to molecular ions; single MS/selected ion monitoring (SIM) mode; tandem MS/single reaction monitoring (SRM) mode; tandem MS/multiple reactions monitoring (MRM) or product ion scanning modes. A faster chromatographic separation could be applied as MS detection readily balanced the selectivity of the analytical process. In a case study, 11 dyes from 3 biological sources were detected in a 0.5 mg historic sample.     

Cell state change dynamics in cellular automata

Cellular automata are discrete dynamical systems having the ability to generate highly complex behaviour starting from a simple initial configuration and set of update rules. The discovery of rules exhibiting a high degree of global self-organization is of major importance in the study and understanding of complex systems. This task is not easily achieved since coordinated global information processing must rise from the interactions of simple components with local information and communication. In this paper, a fast supporting heuristic of linear complexity is proposed to encourage the development of rules characterized by increased dynamics with regard to cell state changes. This heuristic is integrated in an evolutionary approach to the density classification task. Computational experiments emphasize the ability of the proposed approach to facilitate an efficient exploration of the search space leading to the discovery of complex rules situated beyond the simple block-expanding rules.     

Rate coefficients for the gas-phase reaction of OH radicals with dimethyl sulfide: temperature and O2 partial pressure dependence

Rate coefficients for the gas-phase reaction of hydroxyl (OH) radicals with dimethyl sulfide (CH(3)SCH(3), DMS) have been determined using a relative rate technique. The experiments were performed under different conditions of temperature (250-299 K) and O(2) partial pressure (approximately 0 Torr O(2)-380 Torr O(2)), at a total pressure of 760 Torr bath gas (N(2) + O(2)), in a 336 l reaction chamber, using long path in situ Fourier transform (FTIR) absorption spectroscopy to monitor the disappearance rates of DMS and the reference compounds (ethene, propene and 2-methylpropene). OH was produced by the photolysis of H(2)O(2). The following Arrhenius expressions adequately describe the rate coefficients as a function of temperature (units are cm(3) molecule(-1) s(-1)): k = (1.56 +/- 0.20) x 10(-12) exp[(369 +/- 27)/T], for approximately 0 Torr O(2); (1.31 +/- 0.08) x 10(-14) exp[(1910 +/- 69)/T], for 155 Torr O(2); (5.18 +/- 0.71) x 10(-14) exp[(1587 +/- 24)/T], for 380 Torr O(2). The results are compared with previous investigations.     

AutoPPI: An Ensemble of Deep Autoencoders for Protein–Protein Interaction Prediction

Proteins are essential molecules, that must correctly perform their roles for the good health of living organisms. The majority of proteins operate in complexes and the way they interact has pivotal influence on the proper functioning of such organisms. In this study we address the problem of protein–protein interaction and we propose and investigate a method based on the use of an ensemble of autoencoders. Our approach, entitled AutoPPI, adopts a strategy based on two autoencoders, one for each type of interactions (positive and negative) and we advance three types of neural network architectures for the autoencoders. Experiments were performed on several data sets comprising proteins from four different species. The results indicate good performances of our proposed model, with accuracy and AUC values of over 0.97 in all cases. The best performing model relies on a Siamese architecture in both the encoder and the decoder, which advantageously captures common features in protein pairs. Comparisons with other machine learning techniques applied for the same problem prove that AutoPPI outperforms most of its contenders, for the considered data sets.     

Thermal behaviour studies of procaine and benzocaine

The analysed substances, procaine and benzocaine, are two anaesthetic agents currently being administered in tablet form, also in the topical (cream, gel, balm) and injectable dosage forms. The TG/DTG/DTA curves were obtained in air at different heating rates. For determination of the heat effects, the DTA curves (in μV) were changed with the heat flow curves (in mW), so that the peak area corresponds to an energy in J g^?1 or kJ mol^?1. The non-isothermal experiments are preformed to investigate the thermal degradation process of these active substances, both as a solid and are performed in a dynamic atmosphere of air at different heating rates, by heating from room temperature to 500 °C. The kinetic analysis was performed using the TG data in air for the first step of substance’s decomposition at four heating rates: 7, 10, 12 and 15 °C min^?1. The data were processed according to an appropriate strategy to the following kinetic methods: Kissinger–Akahira–Sunose, Flynn–Wall–Ozawa, Friedman and NPK, to obtain realistic kinetic parameters, even if the decomposition process is a complex one. Thermal analysis was supplemented using Fourier Transform infrared spectroscopy coupled with the TG device to identify the anaesthetics with any products which may have formed (EGA—the evolved gas analysis).     

Natural Preparations Based on Orange,Bergamot and Clove Essential Oils and Their Chemical Compounds as Antimicrobial Agents

Since ancient times complementary therapies have been based on the use of medicinal plants, natural preparations and essential oils in the treatment of various diseases. Their use in medical practice is recommended in view of their low toxicity, pharmacological properties and economic impact. This paper aims to test the antimicrobial effect of natural preparation based on clove, orange and bergamot essential oils on a wide range of microorganisms that cause infections in humans including: Streptococcus pyogenes, Staphylococcus aureus, Shigella flexneri, Candida parapsilosis, Candida albicans, Pseudomonas aeruginosa, Escherichia coli, Salmonella typhimurium and Haemophilus influenza. Three natural preparations such as one-component emulsions: clove (ECEO), bergamote (EBEO), and orange (EOEO), three binary: E(BEO/CEO), E(BEO/OEO), E(CEO/OEO) and a tertiary emulsion E(OEO/BEO/CEO) were obtained, characterized and tested for antimicrobial effects. Also, the synergistic/antagonistic effects, generated by the presence of the main chemical compounds, were studied in order to recommend a preparation with optimal antimicrobial activity. The obtained results underline the fact that the monocomponent emulsion ECEO shows antimicrobial activity, while EOEO and EBEO do not inhibit the development of the analyzed strains. In binary or tertiary emulsions E(BEO/CEO), E(CEO/OEO) and E(OEO/ BEO/CEO) the antimicrobial effect of clove oil is potentiated due to the synergism exerted by the chemical compounds of essential oils.