Therefore, multiplexing detection of tumor-suppressor genes (p16, p21 and p53) could be readily realized by using size-encoded magnetic microbeads pre-functionalized with corresponding probe DNA illustrating the potential of this method in multiplexing bioassay applications. Ion mobility spectrometry is an important rapid analysis method. However, it is difficult to achieve quantitative analysis when spectral peaks overlap. A new method for analyzing ion mobility spectra is presented here. The method achieves quantitative analysis by combining the advantages of the peak model (in terms of optimal physical and chemical interpretation of the system of interest) and the multiscale orthogonal matching pursuit algorithm (in terms of extracting characteristic peaks).  https://www.selleckchem.com/products/rin1.html  A simulated data set, constructed using the peak model, containing overlapping peaks was analyzed to demonstrate the ability of the multiscale orthogonal matching pursuit algorithm to decompose overlapping peaks. Real data sets for methyl salicylate and a mixture of acetone and methyl salicylate at sixteen concentrations were generated using a vapor generator (using permeation tubes). The characteristic peaks were extracted using the multiscale orthogonal matching pursuit algorithm. Univariate calibrations using the peak area and peak height were prepared to allow quantitative analyses to be performed. Multivariate calibrations using partial-least-squares and poly-partial-least-squares were prepared and the results were compared with the univariate calibration results. Markedly better or similar predictions were made using the univariate calibration models involving physical and chemical interpretations than using the multivariate calibration models. V.A sparse coefficients wavelength selection and regression (SCWR) method is proposed in the present study. SCWR can rapidly and simultaneously operate regression and select wavelengths on NIR datasets with multiple response variables without any random procedure and cross-validation in the model. The method expresses a normal spectral calibration as a form of least absolute shrinkage and selection operator (LASSO), then the problem is reformulated into the alternative direction multiplier method (ADMM) form. Sparse coefficients wavelength selection (SCWS) method is developed by planting a positive-negative counteract strategy into SCWR, it can select a specified number of wavelengths. A specified number SCWR (NSCWR) is also suggested in order to perform regression using a specified number of wavelengths. SCWR methods have been tested on three NIR datasets (potato, corn, and soil), and these methods have better performance and use fewer feature wavelengths than existing simultaneous regression and wavelength selection methods on predicting almost all attributes in these datasets. Results indicate that SCWR-based methods could select wavelengths with more useful information. For the determination of hyperparameters in SCWR, manual adjustment of hyperparameters is available on sparsity control because the regression performance of SCWR is robustness and insensitive when hyperparameters are in proper ranges. A novel soft strategy for combination and partition of mass spectra data recorded at different fragmentor voltages in full scan mode of a mass spectrometer was developed to generate abundant multi-way data. It is the first time that non-linear four-way and combined three-way LC-MS data have been obtained simultaneously in a single chromatographic run. This strategy ensures that each analyte can be ionized and detected at the most appropriate MS conditions (ionization modes, fragmentor voltages) and avoids a hard chromatographic segmentation in subsequent chemometric analysis. Two different experimental datasets were analyzed to validate the feasibility and applicability of this strategy. Some simple pretreatments were carried out before LC-MS analysis to prevent potential matrix effects. Proper chemometric tools were used to resolve three-way (partitioned data) and enhanced three-way LC-MS (combined data) data, respectively. The method was assessed by comparing the analytical results obtained from the same chemometric algorithm with both combined and partitioned datasets (1) the combined data provided the best global overall resolution, higher sensitivity and more reliable results, (2) the partitioned data provided higher selectivity for some specific analytes. The results showed that the developed method could be a soft and ingenious tool to handle the unordered but information-rich raw LC-MS data. Moreover, the proposed strategy could take extra analytical advantages in terms of higher sensitivity and more reliable quantitative results when compared with LC-MS (with single fragmentor voltage) strategy and showed nearly the same capability in analytical quality as classic LC-MS/MS method. Colorimetric platform using the aggregation of gold nanoparticles (AuNPs) is a pretty simple method for biosensing, but advanced instruments such as specterophotometer is still needed to achieve accurately quantitative readout. Aggregated AuNPs exhibit excellent photothermal properties under near-infrared laser irradiation, which is significantly different from non-aggregated AuNPs. Herein, given the different photothermal effect, we translated the AuNPs-based colorimetric assay into a photothermal assay for the quantitative detection of adenosine using a thermometer as readout. Short single-stranded DNA (ssDNA, adenosine aptamer) was adsorbed on the surface of AuNPs and hence prevented the aggregation of AuNPs under high ionic concentration. The presence of adenosine caused the structural change of ssDNA and the AuNPs became aggregated. The enhanced temperature under NIR-laser irradiation has a linear response to the concentration of adenosine in the range of 2.0-50.0 μM. The detection limit was 1.7 μM. This proposed method is portable, easy and applicable to the quantitative assay of other targets by simply replacing of the sequence of ssDNA. Bioselenols are important substances for the maintenance of physiological balance and offer anticancer properties; however, their causal mechanisms and effectiveness have not been assessed. One way to explore their physiological functions is the in vivo detection of bioselenols at the molecular level, and one of the most efficient ways to do so is to use fluorescent probes. Various types of bioselenol-specific fluorescent probes have been synthesized and optimized using chemical simulations and by improving biothiol fluorescent probes. Here, we review recent advances in bioselenol-specific fluorescent probes for selenocysteine (Sec), thioredoxin reductase (TrxR), and hydrogen selenide (H2Se). In particular, the molecular design principles of different types of bioselenols, their corresponding sensing mechanisms, and imaging applications are summarized. V.