A semi-quantitative and quantitative multi-immunochromatographic (ICA) strip detection assay was developed for the simultaneous detection of twenty types of mycotoxins from five classes, including zearalenones (ZEAs), deoxynivalenols (DONs), T-2 toxins (T-2s), aflatoxins (AFs), and fumonisins (FBs), in cereal food samples. Sensitive and specific monoclonal antibodies were selected for this assay. The semi-quantitative results were obtained within 20 min by the naked eye, with visual limits of detection for ZEAs, DONs, T-2s, AFs and FBs of 0.1-0.5, 2.5-250, 0.5-1, 0.25-1 and 2.5-10 μg kg(-1), and cut-off values of 0.25-1, 5-500, 1-10, 0.5-2.5 and 5-25 μg kg(-1), respectively. The quantitative results were obtained using a hand-held strip scan reader, with the calculated limits of detection for ZEAs, DONs, T-2s, AFs and FBs of 0.04-0.17, 0.06-49, 0.15-0.22, 0.056-0.49 and 0.53-1.05 μg kg(-1), respectively. The analytical results of spiked samples were in accordance with the accurate content in the simultaneous detection analysis. This newly developed ICA strip assay is suitable for the on-site detection and rapid initial screening of mycotoxins in cereal samples, facilitating both semi-quantitative and quantitative determination.

Fast calculation and correct depth cue are crucial issues in the calculation of computer-generated hologram (CGH) for high quality three-dimensional (3-D) display. An angular-spectrum based algorithm for layer-oriented CGH is proposed. Angular spectra from each layer are synthesized as a layer-corresponded sub-hologram based on the fast Fourier transform without paraxial approximation. The proposed method can avoid the huge computational cost of the point-oriented method and yield accurate predictions of the whole diffracted field compared with other layer-oriented methods. CGHs of versatile formats of 3-D digital scenes, including computed tomography and 3-D digital models, are demonstrated with precise depth performance and advanced image quality.

A sensitive class-specific monoclonal antibody against tetracyclines (TCs) was generated and used to develop an enzyme-linked immunosorbent assay (ELISA) and an immunochromatographic assay for TC, oxytetracycline (OTC), and chlortetracycline (CTC) detection in milk and honey samples. The dynamic range of detection for TC in ELISA was 0.26-2.00 μg L −1 with an IC 50 of 0.72 μg L −1 . The IC 50 value of OTC and CTC was 3.2 and 6.4 μg L −1 , respectively. The recovery of TC, OTC, and CTC in milk samples was 82-102, 91-105, and 90-101 %, respectively, and 88-101, 89-101, and 89-95 % in honey samples, respectively. In the immunochromatographic assay, the cutoff values for TC, OTC, and CTC were 15, 15, and 50 μg L −1 in milk, respectively, and 40, 40, and 40 μg L −1 in honey, respectively. The results revealed that ELISA and the immunochromatographic assay can be applied for the rapid and sensitive detection of TC, OTC, and CTC in milk and honey samples.

The article is a response to a recent opinion piece that log concentration values should not be applied in analytical chemistry. An essential aim in the development of analytical chemistry methods is to obtain more sensitive and accurate detection values. For the application of chemical analysis methods, the obtained experiment data need to fit with the mathematical functions in the first place. As influenced by different detection principles and analytical methods, data can be displayed in a coordinate system with two linear axes for linear function fitting, or the data can first be taken through a logarithmic transformation and then for function fitting. Using raw data or data after logarithmic transformation primarily depends on analytical principles, without special rules of data formats. For example, ultraviolet− visible spectrophotometric data are more suitable for direct linear fitting. However, enzyme-catalyzed reaction or electrochemical data in logarithmic form are more appropriate for function fitting. This transformation of data form will not affect the soundness of fit statistics; rather, it simplifies the complexity of function analysis and calculation, which are the essence of analytical chemistry. In this brief article, we provide justification and legitimacy of the application of logarithmic processing in various fields of quantitative analytical chemistry.