Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features

BACKGROUND: Ion mobility-mass spectrometry (IMMS), an analytical technique which combines the features of ion mobility spectrometry (IMS) and mass spectrometry (MS), can rapidly separates ions on a millisecond time-scale. IMMS becomes a powerful tool to analyzing complex mixtures, especially for the analysis of peptides in proteomics. The high-throughput nature of this technique provides a challenge for the identification of peptides in complex biological samples. As an important parameter, peptide drift time can be used for enhancing downstream data analysis in IMMS-based proteomics. RESULTS: In this paper, a model is presented based on least square support vectors regression (LS-SVR) method to predict peptide ion drift time in IMMS from the sequence-based features of peptide. Four descriptors were extracted from peptide sequence to represent peptide ions by a 34-component vector. The parameters of LS-SVR were selected by a grid searching strategy, and a 10-fold cross-validation approach was employed for the model training and testing. Our proposed method was tested on three datasets with different charge states. The high prediction performance achieve demonstrate the effectiveness and efficiency of the prediction model. CONCLUSIONS: Our proposed LS-SVR model can predict peptide drift time from sequence information in relative high prediction accuracy by a test on a dataset of 595 peptides. This work can enhance the confidence of protein identification by combining with current protein searching techniques

A surface-enhanced Raman scattering (SERS)-active optical fiber sensor based on a three-dimensional sensing layer

AbstractTo fabricate a new surface-enhanced Raman scattering (SERS)-active optical fiber sensor, the design and preparation of SERS-active sensing layer is one of important topics. In this study, we fabricated a highly sensitive three-dimensional (3D) SERS-active sensing layer on the optical fiber terminal via in situ polymerizing a porous polymer material on a flat optical fiber terminal through thermal-induced process, following with the photochemical silver nanoparticles growth. The polymerized polymer formed a 3D porous structure with the pore size of 0.29–0.81μm, which were afterward decorated with abundant silver nanoparticles with the size of about 100nm, allowing for higher SERS enhancement. This SERS-active optical fiber sensor was applied for the determination of 4-mercaptopyridine, crystal violet and maleic acid The enhancement factor of this SERS sensing layer can be reached as about 108. The optical fiber sensor with high sensitive SERS-active porous polymer is expected for online analysis and environment detection

Locked Nucleic Acid Pentamers as Universal PCR Primers for Genomic DNA Amplification

Background: Multiplexing technologies, which allow for simultaneous detection of multiple nucleic acid sequences in a single reaction, can save a lot of time, cost and labor compared to traditional single reaction detection methods. However, the multiplexing method currently used requires precise handiwork and many complicated steps, making a new, simpler technique desirable. Oligonucleotides containing locked nucleic acid residues are an attractive tool because they have strong affinities for their complementary targets, they have been used to avoid dimer formation and mismatch hybridization and to enhance efficient priming. In this study, we aimed to investigate the use of locked nucleic acid pentamers for genomic DNA amplification and multiplex genotyping. Results: We designed locked nucleic acid pentamers as universal PCR primers for genomic DNA amplification. The locked nucleic acid pentamers were able to prime amplification of the selected sequences within the investigated genomes, and the resulting products were similar in length to those obtained by restriction digest. In Real Time PCR of genomic DNA from three bacterial species, locked nucleic acid pentamers showed high priming efficiencies. Data from bias tests demonstrated that locked nucleic acid pentamers have equal affinities for each of the six genes tested from the Klebsiella pneumoniae genome. Combined with suspension array genotyping, locked nucleic acid pentamer-based PCR amplification was able to identify a total of 15 strains, including 3 species of bacteria, by gene- and species-specific probes. Among the 32 specie

Double-stepped adaptive control for hybrid systems with unknown Markov jumps and stochastic noises

This paper is concerned with the sampled-data based adaptive linear quadratic (LQ) control of hybrid systems with both unmeasurable Markov jump processes and stochastic noises. By the least matching error estimation algorithm, parameter estimates are presented. By a double-step (DS) sampling approach and the certainty equivalence principle, a sampled-data based adaptive LQ control is designed. The DS-approach is characterized by a comparatively large estimation step for parameter estimation and a sufficient small control step for control updating. Under mild conditions, the closed-loop system is shown to be stable. It is found that the key factor determining the performance index is the estimation step rather than the control step. When the estimation step becomes too small, the system performance will become worse. When the estimation step is fixed, the system performance can indeed be improved by reducing the control step, but cannot reach the optimal value. The index difference between the sampled-data based adaptive LQ control and the conventional LQ optimal control is asymptotically bounded by a constant depending on the estimation step and the priori information of the parameter set