The Null-Test for peptide identification algorithm in Shotgun proteomics.

The present research proposed general evaluation strategy named Null-Test for peptide identification algorithm in Shotgun proteomics. The Null-Test method based on random matching can be utilized to check whether the algorithm has a tendency to make a mistake or has potential bugs, faultiness, errors etc., and to validate the reliability of the identification algorithm. Unfortunately, none of the five famous identification software could pass the most stringent Null-Test. PatternLab had good performance in both Null-Test and routine search by making a good control on the overfitting with sound design. The fuzzy logics based method presented as another candidate strategy could pass the Null-Test and has competitive efficiency in peptide identification. Filtering the results by appropriate FDR would increase the number of discoveries in an experiment, at the cost of losing control of Type I errors. Thus, it is necessary to utilize some more stringent criteria when someone wants to design or analyze an algorithm/software. The more stringent criteria will facilitate the discovery of latent bugs, faultiness, errors etc. in the algorithm/software. It would be recommended to utilize independent search combining random database with statistics theorem to estimate the accurate FDR of the identified results. BIOLOGICAL SIGNIFICANCE: In the past decades, considerable effort has been devoted to developing a sensitive algorithm for peptide identification in Shotgun proteomics. However, little attention has been paid to controlling the reliability of the identification algorithm at the design stage. The Null-Test based on random matching can be utilized to check whether the algorithm has a tendency to make a mistake or has potential bugs, faultiness, errors etc. However, it turns out that none of the five famous identification software could pass the most stringent Null-Test in the present study, which should be taken into account seriously. Accordingly, a candidate strategy based on fuzzy logics has been demonstrated the possibility that an identification algorithm can pass the Null-Test. PatternLab shows that earlier control on overfitting is valuable for designing an efficient algorithm.

Multi-targeted interference-free determination of ten ß-blockers in human urine and plasma samples by alternating trilinear decomposition algorithm-assisted liquid chromatography-mass spectrometry in full scan mode: comparison with multiple reaction monitoring.

ß-blockers are the first-line therapeutic agents for treating cardiovascular diseases and also a class of prohibited substances in athletic competitions. In this work, a smart strategy that combines three-way liquid chromatography-mass spectrometry (LC-MS) data with second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm was developed for simultaneous determination of ten ß-blockers in human urine and plasma samples. This flexible strategy proved to be a useful tool to solve the problems of overlapped peaks and uncalibrated interferences encountered in quantitative LC-MS, and made the multi-targeted interference-free qualitative and quantitative analysis of ß-blockers in complex matrices possible. The limits of detection were in the range of 2.0×10(-5)-6.2×10(-3) µg mL(-1), and the average recoveries were between 90 and 110% with standard deviations and average relative prediction errors less than 10%, indicating that the strategy could provide satisfactory prediction results for ten ß-blockers in human urine and plasma samples only using liquid chromatography hyphenated single-quadrupole mass spectrometer in full scan mode. To further confirm the feasibility and reliability of the proposed method, the same batch samples were analyzed by multiple reaction monitoring (MRM) method. T-test demonstrated that there are no significant differences between the prediction results of the two methods. Considering the advantages of fast, low-cost, high sensitivity, and no need of complicated chromatographic and tandem mass spectrometric conditions optimization, the proposed strategy is expected to be extended as an attractive alternative method to quantify analyte(s) of interest in complex systems such as cells, biological fluids, food, environment, pharmaceuticals and other complex samples.

Screening of high α-arbutin producing strains and production of α-arbutin by fermentation.

A mutant Xanthomonas maltophilia BT-112 with high α-anomer-selective glycosylation activity was screened by a series of mutation methods including UV light, N-methyl-N-nitro-N-nitroso-guanidine treatment and quick neutron mutation. The α-arbutin titer increased 15-folds compared with the parent strain. The optimal conditions for culture medium and the operational conditions for lab-scale fermenter were investigated. Under optimized conditions, the maximal hydroquinone (HQ) tolerance of cells and yield of α-arbutin were 120 mM and 30.6 g/l, respectively. The molar conversion yield of α-arbutin based on the amount of HQ supplied reached 93.6 %. The product was identified as α-arbutin by (13)C NMR and (1)H NMR analysis. In conclusion, the results in this work provide a one-step and cost-effective method for the large-scale production of α-arbutin.

An alternative quadrilinear decomposition algorithm for four-way calibration with application to analysis of four-way fluorescence excitation-emission-pH data array.

A novel quadrilinear decomposition algorithm for four-way calibration (third-order tensor calibration), which was called as regularized self-weighted alternating quadrilinear decomposition (RSWAQLD), has been developed in this work. It originates from the alternating trilinear decomposition (ATLD) algorithm, inherits the philosophy behind self-weighting operation from the self-weighted alternating trilinear decomposition (SWATLD) algorithm. The RSWAQLD algorithm is based on a nearby least-squares scheme, in which two extra terms are added to each loss function, making it more stable and flexible. Experiment shows that RSWAQLD has the features of fast convergence and being insensitive to the excess estimated factors in the model. Owing to its unique optimizing approach, RSWAQLD is much more efficient than four-way PARAFAC. Moreover, the performance of RSWAQLD is quit stable as the number of factors used in calculation varies (as long as it is no less than the true number of factors). Such a feature will simplify the analysis of four-way data arrays, since it is unnecessary to spend a lot of time and effort on accurately determining the appropriate number of factors in the matrix. In addition, the result of four-way fluorescence excitation-emission-pH data, as well as that of simulated data, illustrated that RSWAQLD can not only remain the "higher-order advantage" but also provide a satisfying result even in high collinear systems.

[Epitopic multiple antigen peptide from α-fetoprotein elicit antitumor immune response in vitro and ex vivo].

OBJECTIVE: To explore the antitumor effects of multiple antigen peptide (MAP) vaccine from α-fetoprotein (AFP) through AFP-specific cytotoxic T lymphocyte (CTL) against hepatoma in vitro and ex vivo. METHODS: Dendritic cells (DC) were generated from human peripheral blood mononuclear cells (PBMC) and HLA-A2.1-transgenic murine bone marrow. The AFP-specific CTL were induced by MAP-loaded DC and the corresponding linear peptides from human AFP. The lysis rate of effectors to hepatoma cells were tested by 4 h (51)Cr release assay. And enzyme-linked immunosorbent spot (ELISPOT) was used to test the interferon (IFN)-γ release of effector cells. RESULTS: The specific lysis rate of effectors induced by AFP epitopic MAP vaccines to Hep3B cells (AFP(+), HLA-A2.1(+)) at the highest effector/target (E/T) ratio was significantly higher than linear peptide vaccine (73.5% ± 7.9% vs 45.6% ± 6.9%, P < 0.01). The effectors induced by AFP epitopic MAP vaccine and linear peptide vaccine could not lysis the AFP-negative PLC/PRF/5 liver cancer cells versus the negative control group at the highest E/T (9.3% ± 3.9%, 8.1% ± 2.8% vs 8.3% ± 2.6%, both P > 0.05). But the effectors induced by AFP epitopic MAP vaccine and linear peptide vaccine could lyse PLC/PRF/5 liver cancer cells transfected with cDNA of AFP versus the negative control group (74.8% ± 10.5%, 51.4% ± 12.6% vs 4.2% ± 1.3%, both P < 0.01). And the specific lysis rate of effectors induced by AFP epitopic MAP vaccines was significantly higher than the corresponding linear peptide vaccine (P < 0.01). Compared with the negative control group, the effectors could not lyse HepG2 liver cancer cells, a HLA-A2.1 negative cell line (both P > 0.05). But the effectors could lyse HepG2 cells transfected with cDNA of HLA-A2.1 (71.8% ± 8.6%, 46.5% ± 6.5% vs 4.1% ± 1.1%, both P < 0.01). And the specific lysis rate of effectors induced by MAP vaccine was significantly higher than the corresponding linear peptide vaccine (P < 0.01). ELISPOT test showed that the capability of enhancing IFN-γ release of human AFP MAPs was stronger than that of the AFP linear peptides. The spots count of MAP vaccine group ((158 ± 23) spots/10(5) cells) or linear peptide vaccine group ((78 ± 12) spots/10(5) cells) were significantly higher than the negative control group ((3 ± 1) spots/10(5) cells) (all P < 0.01). The spots count of the positive control group ((166 ± 32) spots/10(5) cells) showed no significant difference with the AFP MAP vaccine group (P > 0.05). And the spots count of MAP vaccine group were significantly higher than the corresponding linear peptide vaccine group ((78 ± 12) spots/10(5) cells, P < 0.01). CONCLUSIONS: AFP multiple antigen peptides elicit not only more powerful specific anti-tumor immune responses but also stronger non-specific anti-tumor immune activities than their corresponding linear peptides. These findings will provide theoretical rationales for their clinical applications.

The maintenance of the second-order advantage: second-order calibration of excitation-emission matrix fluorescence for quantitative analysis of herbicide napropamide in various environmental samples.

A rapid non-separative spectrofluorometric method based on the second-order calibration of excitation-emission matrix (EEM) fluorescence was proposed for the determination of napropamide (NAP) in soil, river sediment, and wastewater as well as river water samples. With 0.10 mol L(-1) sodium citrate-hydrochloric acid (HCl) buffer solution of pH 2.2, the system of NAP has a large increase in fluorescence intensity. To handle the intrinsic fluorescence interferences of environmental samples, the alternating penalty trilinear decomposition (APTLD) algorithm as an efficient second-order calibration method was employed. Satisfactory results have been achieved for NAP in complex environmental samples. The limit of detection obtained for NAP in soil, river sediment, wastewater and river water samples were 0.80, 0.24, 0.12, 0.071 ng mL(-1), respectively. Furthermore, in order to fully investigate the performance of second-order calibration method, we test the second-order calibration method using different calibration approaches including the single matrix model, the intra-day various matrices model and the global model based on the APTLD algorithm with nature environmental datasets. The results showed the second-order calibration methods also enable one or more analyte(s) of interest to be determined simultaneously in the samples with various types of matrices. The maintenance of second-order advantage has been demonstrated in simultaneous determinations of the analyte of interests in the environmental samples of various matrices.

Interference-free determination of and in plant samples using excitation-emission matrix fluorescence based on oxidationderivatization coupled with second-order calibration methods.

A sensitive excitation-emission fluorescence method with a second-order calibration strategy is proposed to simultaneously determine abscisic acid (ABA) and gibberellin (GA) contents in extracts of leaves and buds of ginkgo. The methodology is based on the alternating normalization-weighed error (ANWE) and the parallel factor analysis (PARAFAC) algorithms, which make it possible that the ABA and GA concentration can be attained in extract of plants even in the presence of unknown interference from potential interfering matrix contaminants introduced during the simple pretreatment procedure. Satisfactory recoveries were obtained although the excitation and emission profiles of the analytes were heavily overlapped with each other and the background in the extracts. The limits of detection obtained for GA and ABA in leaf samples were 9.6 and 6.9 ng mL-1, respectively, which were in the concentration range (from hundreds to several ng g-1) for GA and ABA in leaves in different periods. Furthermore, in order to investigate the performance of the developed method, some statistical parameters and figures of merit of ANWE and PARAFAC are evaluated. The method proposed lights a new avenue to determine quantitatively phytohormones in extracts of plants with a simple pretreatment procedure, and may hold potential to be extended as a promising alternative for more practical applications in plant growth processes.

Seasonal variation of nitrogen-concentration in the surface water and its relationship with land use in a catchment of northern China.

Surface waters can be contaminated by human activities in two ways: (1) by point sources, such as sewage treatment discharge and storm-water runoff; and (2) by non-point sources, such as runoff from urban and agricultural areas. With point-source pollution effectively controlled, non-point source pollution has become the most important environmental concern in the world. The formation of non-point source pollution is related to both the sources such as soil nutrient, the amount of fertilizer and pesticide applied, the amount of refuse, and the spatial complex combination of land uses within a heterogeneous landscape. Land-use change, dominated by human activities, has a significant impact on water resources and quality. In this study, fifteen surface water monitoring points in the Yuqiao Reservoir Basin, Zunhua, Hebei Province, northern China, were chosen to study the seasonal variation of nitrogen concentration in the surface water. Water samples were collected in low-flow period (June), high-flow period (July) and mean-flow period (October) from 1999 to 2000. The results indicated that the seasonal variation of nitrogen concentration in the surface water among the fifteen monitoring points in the rainfall-rich year is more complex than that in the rainfall-deficit year. It was found that the land use, the characteristics of the surface river system, rainfall, and human activities play an important role in the seasonal variation of N-concentration in surface water.