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Amino acids are widely distributed in biological fluids and involved in many biological processes, such as the synthesis of proteins, fatty acids, and ketone bodies. The altered levels of amino acids in biological fluids have been found to be closely related to several diseases, such as type 2 diabetes, kidney disease, liver disease, and cancer. Therefore, the development of analytical methods to measure amino acid concentrations in biological samples can contribute to research on the physiological actions of amino acids and the prediction, diagnosis and understanding of diseases. This review describes the analytical methods reported in 2012–2016 that utilized liquid chromatography and capillary electrophoresis coupled with ultraviolet, fluorescence, mass spectrometry, and electrochemical detection. Additionally, the relationship between amino acid concentrations and several diseases is also summarized.

Nonnegative matrix factorization (NMF) has been proved to be a powerful data representation method, and has shown success in applications such as data representation and document clustering. However, the non-negative constraint alone is not able to capture the underlying properties of the data. In this paper, we present a framework to enforce general subspace constraints into NMF by augmenting the original objective function with two additional terms. One on constraints of the basis, the other on preserving the structural properties of the original data. This framework is general as it can be used to regularize NMF with a wide variety of subspace constraints that can be formulated into a certain form such as PCA, Fisher LDA and LPP. In addition, we present an iterative optimization algorithm to solve the general subspace constrained non-negative matrix factorization (GSC NMF). We show that the resulting subspace has enriched representation power as shown in our experiments.

Dispersive liquid–liquid microextraction (DLLME) based on Fe3O4 magnetic nanoparticle-assisted in situ ionic liquid was developed as a novel method for the pretreatment of pyrethroid pesticides (flumethrin, bifenthrin and silafluofen) in urine samples. [N4,4,4,4]Cl and Na[N(CN)2] formed a ionic liquid ([N4,4,4,4][N(CN)2]), which provides an alternative to highly toxic solvents; moreover, high extraction recoveries and enrichment factors were achieved. The extraction parameters affecting the extraction recoveries were investigated. Under optimum conditions, the analytical method showed a good linear response, with correlation coefficient (R2) values ranging from 0.9994 to 0.9996. The enrichment factor, limit of detection and recovery were 108–125, 2.7–5.0 μg L−1 and 88.0–101.1%, respectively. Therefore, this green and simple method is suitable for the microextraction of pyrethroid pesticides in urine samples. It is valuable to establish a sensitive method for monitoring trace levels of pyrethroids, which could contribute to the use of rapid and green sample preparation procedures in urine samples.

Octahedral Cu 2 O particles were prepared on an indium-tin oxide glass via electrodeposition and were employed in the catalytic degradation of p -nitrophenol in the presence of H 2 O 2 . Under irradiation of a warm visible-light source, tungsten halogen lamp, Cu 2 O particles not only acted as a photocatalyst, but might also act as a thermal-catalyst to induce the decomposition of H 2 O 2 and produce O 2 at higher temperatures. The photogenerated electrons and holes could react with H 2 O 2 , O 2 , and H 2 O to produce abundant OH radicals, resulting in the effective oxidation of p -nitrophenol. High-performance liquid chromatography measurements of degradation intermediates showed that p -nitrophenol was first decomposed into hydroquinone and benzoquinone and then mineralized. The degradation efficiency was dependent on electrodeposition time, light intensity, H 2 O 2 amount, and solution temperature. This catalyst could be easily recycled and used in the efficient degradation of other phenolic compounds.