Li-Mediated Electrochemical Nitrogen Fixation: Key Advances and Future Perspectives.

The electrochemical nitrogen reduction reaction holds great potential for ammonia production using electricity generated from renewable energy sources and is sustainable. The low solubility of nitrogen in aqueous media, poor kinetics, and intrinsic competition by the hydrogen evolution reaction result in meager ammonia production rates. Attributing measured ammonia as a valid product, not an impurity, is challenging despite rigorous analytical experimentation. In this regard, Li-mediated electrochemical nitrogen reduction is a proven method providing significant ammonia yields. Herein, fundamental advances and insights into the Li-mediated strategy are summarized, emphasizing the role of lithium, reaction parameters, cell designs, and mechanistic evaluation. Challenges and perspectives are presented to highlight the prospects of this strategy as a continuous, stable, and modular approach toward sustainable ammonia production.

Nucleic acid hybridization on an electrically reconfigurable network of gold-coated magnetic nanoparticles enables microRNA detection in blood.

There is intense interest in quantifying the levels of microRNA because of its importance as a blood-borne biomarker. The challenge has been to develop methods that can monitor microRNA expression both over broad concentration ranges and in ultralow amounts directly in a patient's blood. Here, we show that, through electric-field-induced reconfiguration of a network of gold-coated magnetic nanoparticles modified by probe DNA (DNA-Au@MNPs), it is possible to create a highly sensitive sensor for direct analysis of nucleic acids in samples as complex as whole blood. The sensor is the first to be able to detect concentrations of microRNA from 10 aM to 1 nM in unprocessed blood samples. It can distinguish small variations in microRNA concentrations in blood samples of mice with growing tumours. The ultrasensitive and direct detection of microRNA using an electrically reconfigurable DNA-Au@MNPs network makes the reported device a promising tool for cancer diagnostics.

Classification of weathered petroleum oils by multi-way analysis of gas chromatography-mass spectrometry data using PARAFAC2 parallel factor analysis.

The application of multi-way parallel factor analysis (PARAFAC2) is described for the classification of different kinds of petroleum oils using GC-MS. Oils were subjected to controlled weathering for 2, 7 and 15 days and PARAFAC2 was applied to the three-way GC-MS data set (MSxGCxsample). The classification patterns visualized in scores plots and it was shown that fitting multi-way PARAFAC2 model to the natural three-way structure of GC-MS data can lead to the successful classification of weathered oils. The shift of chromatographic peaks was tackled using the specific structure of the PARAFAC2 model. A new preprocessing of spectra followed by a novel use of analysis of variance (ANOVA)-least significant difference (LSD) variable selection method were proposed as a supervised pattern recognition tool to improve classification among the highly similar diesel oils. This lead to the identification of diagnostic compounds in the studied diesel oil samples.

Identification of the geometrical isomers of α-linolenic acid using gas chromatography/mass spectrometry with a binary decision tree.

Gas chromatography, using a highly polar column, low energy (30 eV) electron ionization mass spectrometry and multivariate curve resolution, are combined to obtain the mass spectra of all eight geometrical isomers of α-linolenic acid. A step by step Student's t-test is performed on the m/z 50-294 to identify the m/z by which the geometries of the double bonds could be discriminated. The most intense peak discriminates between cis (m/z 79) and trans (m/z 95) at the central (carbon 12) position. The configuration at carbon 15 is then distinguished by m/z 68 and 236, and finally the geometry at carbon 9 is determined by m/z 93, 173, 191 and 236. A three-question binary tree is developed based on the normalized intensities of these ions by which the identity of any given isomer of α-linolenic is accurately determined. Application of Bayes theorem to data from independent samples shows that the complete configuration is determined correctly with a minimum probability of 87%.

Bio-activity of natural polymers from the genus Pistacia: a validated model for their antimicrobial action.

The polymers from mastic gum of Pistacia lentiscose and subspecies of Pistacia atlantica, (sp. kurdica, mutica and cabolica) have been isolated and characterised by gel permeation chromatography (GPC) and 13C NMR spectroscopy as cis-1,4-poly-?-myrcenes. They were screened against Helicobacter pylori and other Gram-negative and Gram-positive bacteria to evaluate their antimicrobial action. In order to further test their hypothesised mode of action, two polymer types were synthesized: one from myrcene, and four from polyvinyl alcohols of different molecular weights, derivatised with p-hydroxybenzoate. The anti-microbial activity of these polymers, evaluated through their 'kill' kinetics, was found to be related to their functional groups, their molecular weight and their solubility.