A Multi-year Beneficial Effect of Seed Priming with Gibberellic Acid-3 (GA3) on Plant Growth and Production in a Perennial Grass, Leymus chinensis.

Seed priming is a widely used technique in crops to obtain uniform germination and high-quality seedlings. In this study, we found a long-term effect of seed priming with gibberellic acid-3 (GA3) on plant growth and production in Leymus chinensis. Seeds were germinated on agar plates containing 0-200 µM GA3, and the germinated seedlings were transplanted to clay planting pots and grown for about one year. The clonal tillers grown from the mother plants were transplanted to field conditions in the second year. Results showed that GA3 treatment significantly increased seed germination rate by 14-27%. GA3 treatment also promoted subsequent plant growth and biomass production, as shown by a significant increase in plant height, tiller number, and fresh and dry weight in both pot (2016) and field (2017) conditions. It is particularly noteworthy that the growth-promoting effect of a single seed treatment with GA3 lasted for at least two years. In particular, GA3 treatment at 50 µM increased aboveground fresh and dry weight by 168.2% and 108.9% in pot-grown conditions, and 64.5% and 126.2% in field-grown conditions, respectively. These results imply a transgenerational transmission mechanism for the GA-priming effect on clonal offspring growth and biomass production in L. chinensis.

Enrichment of serum biomarkers by magnetic metal-organic framework composites.

Highly efficient extraction of peptides from serum is critical for finding serum biomarkers using mass spectrometry, which still remains a great challenge. Currently, a bottom-up proteomics approach has been applied to discover serum biomarkers. However, the approach was labor intensive, time and cost consuming, and cannot meet the requirements for clinical application. In this work, Fe3O4/C@MIL-100 composites were synthesized to efficiently capture peptides from microwave-assisted formic acid digests of BSA and human serum prior to MALDI-TOF MS analysis. Fe3O4/C@MIL-100 composites exhibited size-selective adsorption performance, thus providing a rapid and convenient approach to enrich low-abundance peptides. Notably, the peptides' mass fingerprinting of serum digestions between type 2 diabetes mellitus (T2DM) and healthy persons were distinguishable, which indicated the potential ability of this technique for T2DM diagnosis and rapid biomarker discovery. Graphical Abstract Efficient extraction and identification of serum biomarkers using Fe3O4/C@MIL-100 composites from acid hydrolysate.

Rapid Isolation of Phenol Degrading Bacteria by Fourier Transform Infrared (FTIR) Spectroscopy.

Phenol is an important chemical engineering material and ubiquitous in industry wastewater, its existence has become a thorny issue in many developed and developing country. More and more stringent standards for effluent all over the world with human realizing the toxicity of phenol have been announced. Many advanced biological methods are applied to industrial wastewater treatment with low cost, high efficiency and no secondary pollution, but the screening of function microorganisms is certain cumbersome process. In our study a rapid procedure devised for screening bacteria on solid medium can degrade phenol coupled with attenuated total reflection fourier transform infrared (ATR-FTIR) which is a detection method has the characteristics of efficient, fast, high fingerprint were used. Principal component analysis (PCA) is a method in common use to extract fingerprint peaks effectively, it couples with partial least squares (PLS) statistical method could establish a credible model. The model we created using PCA-PLS can reach 99. 5% of coefficient determination and validation data get 99. 4%, which shows the promising fitness and forecasting of the model. The high fitting model is used for predicting the concentration of phenol at solid medium where the bacteria were grown. The highly consistent result of two screening methods, solid cultural with ATR-FTIR detected and traditional liquid cultural detected by GC methods, suggests the former can rapid isolate the bacteria which can degrade substrates as well as traditional cumbersome liquid cultural method. Many hazardous substrates widely existed in industry wastewater, most of them has specialize fingerprint peaks detected by ATR-FTIR, thereby this detected method could be used as a rapid detection for isolation of functional microorganisms those can degrade many other toxic substrates.

Biocompatible chiral monolithic stationary phase synthesized via atom transfer radical polymerization for high performance liquid chromatographic analysis.

Novel biocompatible chiral monolithic stationary phase was prepared by reverse and direct atom transfer radical polymerization (ATRP) methods. By taking advantages of the controlled/living property of ATRP method, the chiral monolith was prepared by reverse ATRP (RATRP) firstly. An attractive feature of RATRP is the prepared polymer containing a terminal radically transferable atom that can initiate another post-polymerization reaction by direct ATRP. Then, the biocompatible poly(hydroxyethyl methacrylate) (PHEMA) was grafted on the surface of the chiral monolith by direct ATRP as a diffusion barrier for proteins. This biocompatible chiral monolith was successfully used as restricted access stationary phase for determination of enantiomers in biological samples with direct injection by high-performance liquid chromatography (HPLC).

Emerging enantiomeric resolution materials with homochiral nano-fabrications.

The major scientific challenge of enantiomeric separation is to develop simple, rapid, and sensitive routine analytical methods. Generally, enantio-resolution is still based on "three-point interaction" theory, which indicates that homochiral sites are needed for enantio-selective interaction. However, in recent years, advanced materials with precise homochiral fabrication at the nanoscale have been synthesized, and have shown great potential in development of high-throughput enantio-resolution methods. This tutorial review summarizes fabrication and applications of homochiral materials for enantio-selective recognition and separation. These materials, which include intrinsic and restructured chiral metal surfaces, plasmonic nanostructures, coordination polymers, organic polymer sensors, and molecularly imprinted polymers, have been applied as sensors or chiral stationary phases (CSPs) for efficient enantio-resolution.

Synthesis of magnetic framework composites for the discrimination of Escherichia coli at the strain level.

Rapid and efficient characterization and identification of pathogens at the strain level is of key importance for epidemiologic investigations, which still remains a challenge. In this work, solvothermically Fe3O4-COOH@MIL-101 composites were fabricated by in situ crystallization approach. The composites combine the excellent properties of both chromium (III) terephthalate (MIL-101) and carboxylic-functionalized magnetite (Fe3O4-COOH) particles and possess the efficient peptides/proteins enrichment properties and magnetic responsiveness. Fe3O4-COOH@MIL-101 composites as magnetic solid phase extraction materials were used to increase the discriminatory power of MALDI-TOF MS profiles. BSA tryptic peptides at a low concentration of 0.25 fmol µL(-1) could be detected by MALDI-TOF MS. In addition, Fe3O4-COOH@MIL-101 composites were successfully applied in the selective enrichment of the protein biomarkers from bacterial cell lysates and discrimination of Escherichia coli at the strain level. This work provides the possibility for wide applications of magnetic MOFs to discriminate pathogens below the species level.

Restricted access chiral stationary phase synthesized via reversible addition-fragmentation chain-transfer polymerization for direct analysis of biological samples by high performance liquid chromatography.

Novel hydrophilic microparticles containing ß-cyclodextrin (ß-CD) were prepared via one-pot synthesis using reversible addition-fragmentation chain-transfer (RAFT) precipitation polymerization, a "controlled/living" radical polymerization technique. The polymerization was initiated by hydrophilic macromolecular chain-transfer agent [poly(2-hydroxyethyl methacrylate), PHEMA]. The hydrophilic PHEMA on the surface of microparticles can well improve their surface hydrophilicity and lead to their biological compatibility. As chiral restricted access material (RAM), the hydrophilic microparticles can be used for determination of enantiomers in biological samples with direct injection via HPLC analysis.

[Application of SVR in quantitative analysis of wines].

Fourier transform infrared spectroscopy has been widely used in some related fields, thus induces the rapid development of quantitative analysis method based on Lambert-Beer's Law and chemometrics in recent years. The selection of appropriate pre-processing method and calibration model is extremely crucial to the quantitative analysis. The present paper selected 30 wine samples and used infrared spectroscopy combined with vector regression algorithm SVR quantitative analysis model with standard normal variate, baseline correction and outliers elimination to analyze four representative components of wine. Satisfactory results were gained while the relative errors were limited to less than 5%. This method can be applied to the wine representative quantitative analysis for the material content.

[SVM-based qualitative analysis of Muscat Hamburg wine produced in Tianjin region].

The purpose was to achieve the identification of Muscat Hamburg wines produced in Tianjin region through scanning and analyzing dry white wine samples of different grape varieties and regions by infrared spectroscopy technology. A support vector machine (SVM) based method was introduced to analyze infrared spectra of dry white wines. The pretreatment processes of the IR spectra were also elaborated, including baseline adjustment, noise Elimination, standard normalization and eliminating the main component of abnormal sample points. The authors selected great quantity of dry white wine samples of different grape regions including 511 Muscat Hamburg wine samples, 438 Italian Riesling wine samples, 307 Chardonnay wine samples, 29 Ugni Blanc wine samples, 44 Rkatsiteli wine samples, 31 longan wine samples and 79 ZeHong wine samples. According to different classification problems, 80% of IR spectra of the wine samples were used to establish discrimination models with SVM-based method, and the remaining 20% of IR spectra were used for the validation of the discrimination models. Experimental results showed that the proposed method is effective, since high classification accuracy, identification rate and rejecting rate were achieved: over 97% for the white wine samples of different grape varieties, meanwhile over 98% for the Muscat Hamburg wine samples produced in different regions. So the method developed in this paper played a good role in the qualitative classification and discrimination of Muscat Hamburg wines produced in Tianjin region. This novel method has a considerable potential and a rosy application future due to the expeditiousness, stability and easy-operation of FTIR method, as well as the veracity and credibility of SVM method.

[Analysis of liquor flavor spectra and pattern recognition computation].

Chinese liquor is a complex mixture and contains a large amount of microconstituents, which affects the quality and flavor of liquor. In order to discriminate liquor flavors rapidly, the spectra of liquors were obtained by FTIR and employed as the input patterns of pattern classification algorithms, then liquor flavor discrimination models were built. This paper introduces liquor flavor pattern recognition algorithms comprehensively and systematically for the first time, and the algorithms contain statistical classifications (linear discriminant function, quadratic discriminant function, regularized discriminant analysis, and K nearest neighbor), prototype learning algorithm (learning vector quantization), support vector machine and adaboost algorithm. Experimental results show that the liquor flavor classification algorithms demonstrate good performance and achieve high accuracy, recognition rate and rejection rate.