Online 2D-LC-MS/MS Platform for Analysis of Glycated Proteome

Glycated proteins are emerging as good indicators for diabetes and age related diseases. However, the platform for analysis of glycated proteome has been relatively less well established. We here introduce an online 2D-LC-HCD-MS/MS platform for comprehensive glycated peptide quantification. This platform includes a boronate affinity column in the first dimension for enrichment, reversed phase nanoLC column in the second dimension for separation, a benchtop Orbitrap mass spectrometer with HCD-MS/MS for peptide sequencing, and MaxQuant bioinformatics tool for identification and quantification of glycated peptides. This online 2D-LC-HCD-MS/MS platform has high enrichment efficiency with 85% of identified peptides in the enriched fraction as glycated, high sensitivity for detection of glycated peptides with LOD and LOQ at 1.2 and 2.4 pg, respectively, and high reproducibility with interday CVs < 20% for 80% of the glycated peptides. The number of glycated peptides quantified in <i>in vitro</i> glycated human plasma increased more than 3-fold using this platform in comparison to that obtained using 1D-LC-HCD-MS/MS platform without boronate affinity enrichment. Application of this online platform to human plasma identified 376 glycated peptides from 10 μg of protein digests. This highly sensitive and reproducible online 2D platform is promising for glycated protein analysis of complex clinical samples

Online 2D-LC-MS/MS Platform for Analysis of Glycated Proteome

Glycated proteins are emerging as good indicators for diabetes and age related diseases. However, the platform for analysis of glycated proteome has been relatively less well established. We here introduce an online 2D-LC-HCD-MS/MS platform for comprehensive glycated peptide quantification. This platform includes a boronate affinity column in the first dimension for enrichment, reversed phase nanoLC column in the second dimension for separation, a benchtop Orbitrap mass spectrometer with HCD-MS/MS for peptide sequencing, and MaxQuant bioinformatics tool for identification and quantification of glycated peptides. This online 2D-LC-HCD-MS/MS platform has high enrichment efficiency with 85% of identified peptides in the enriched fraction as glycated, high sensitivity for detection of glycated peptides with LOD and LOQ at 1.2 and 2.4 pg, respectively, and high reproducibility with interday CVs < 20% for 80% of the glycated peptides. The number of glycated peptides quantified in <i>in vitro</i> glycated human plasma increased more than 3-fold using this platform in comparison to that obtained using 1D-LC-HCD-MS/MS platform without boronate affinity enrichment. Application of this online platform to human plasma identified 376 glycated peptides from 10 μg of protein digests. This highly sensitive and reproducible online 2D platform is promising for glycated protein analysis of complex clinical samples

An Ensemble Method with Hybrid Features to Identify Extracellular Matrix Proteins

<div><p>The extracellular matrix (ECM) is a dynamic composite of secreted proteins that play important roles in numerous biological processes such as tissue morphogenesis, differentiation and homeostasis. Furthermore, various diseases are caused by the dysfunction of ECM proteins. Therefore, identifying these important ECM proteins may assist in understanding related biological processes and drug development. In view of the serious imbalance in the training dataset, a Random Forest-based ensemble method with hybrid features is developed in this paper to identify ECM proteins. Hybrid features are employed by incorporating sequence composition, physicochemical properties, evolutionary and structural information. The Information Gain Ratio and Incremental Feature Selection (IGR-IFS) methods are adopted to select the optimal features. Finally, the resulting predictor termed IECMP (Identify ECM Proteins) achieves an balanced accuracy of 86.4% using the 10-fold cross-validation on the training dataset, which is much higher than results obtained by other methods (ECMPRED: 71.0%, ECMPP: 77.8%). Moreover, when tested on a common independent dataset, our method also achieves significantly improved performance over ECMPP and ECMPRED. These results indicate that IECMP is an effective method for ECM protein prediction, which has a more balanced prediction capability for positive and negative samples. It is anticipated that the proposed method will provide significant information to fully decipher the molecular mechanisms of ECM-related biological processes and discover candidate drug targets. For public access, we develop a user-friendly web server for ECM protein identification that is freely accessible at <a href="http://iecmp.weka.cc" target="_blank">http://iecmp.weka.cc</a>.</p></div

Controllable Stearic Acid Crystal Induced High Hydrophobicity on Cellulose Film Surface

A novel, highly hydrophobic cellulose composite film (RCS) with biodegradability was fabricated via solvent-vaporized controllable crystallization of stearic acid in the porous structure of cellulose films (RC). The interface structure and properties of the composite films were investigated with wide-angle X-ray diffraction (WAXD), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), FT-IR, solid-state ¹³C NMR, water uptake, tensile testing, water contact angle, and biodegradation tests. The results indicated that the RCS films exhibited high hydrophobicity (water contact angle achieved to 145°), better mechanical properties in the humid state and lower water uptake ratio than RC. Interestingly, the stearic acid crystallization was induced by the pore wall of the cellulose matrix to form a micronano binary structure, resulting in a rough surface. The rough surface with a hierarchical structure containing micronanospace on the RCS film surface could trap abundant air, leading to the high hydrophobicity. Moreover, the RCS films were flexible, biodegradable, and low-cost, showing potential applications in biodegradable water-proof packaging

Prediction results of the original feature set and the optimal feature set.

<p>Prediction results of the original feature set and the optimal feature set.</p

Additional file 3: Table S2. of An interactomics overview of the human and bovine milk proteome over lactation

Alignment between bovine and human co-expression networks. (DOCX 14 kb

Reprogrammable Logic Gate and Logic Circuit Based on Multistimuli-Responsive Raspberry-like Micromotors

In this paper, we report a polymer-based raspberry-like micromotor. Interestingly, the resulting micromotor exhibits multistimuli-responsive motion behavior. Its on–off–on motion can be regulated by the application of stimuli such as H₂O₂, near-infrared light, NH₃, or their combinations. Because of the versatility in motion control, the current micromotor has great potential in the application field of logic gate and logic circuit. With use of different stimuli as the inputs and the micromotor motion as the output, reprogrammable OR and INHIBIT logic gates or logic circuit consisting of OR, NOT, and AND logic gates can be achieved

The numbers of each kind of features in the original and optimal feature set.

<p>The four kinds of features are based on sequence composition, physicochemical properties, evolutionary information, and structural information, respectively.</p

The overall work flow of the proposed method IECMP(Identify ECM Proteins).

<p>(i) The training sequences are mapped into feature vectors. (ii) To reduce the complexity and the feature redundancy, the Information Gain Ratio and Incremental Feature Selection (IGR-IFS) methods are employed. (iii) The training set is divided into 11 training subsets through the undersampling approach. (iv) With the optimal features, the 11 training subsets train Random Forest classifiers, respectively. (v) The predicted class labels of the test set are determined by the majority voting method.</p

Reprogrammable Logic Gate and Logic Circuit Based on Multistimuli-Responsive Raspberry-like Micromotors

In this paper, we report a polymer-based raspberry-like micromotor. Interestingly, the resulting micromotor exhibits multistimuli-responsive motion behavior. Its on–off–on motion can be regulated by the application of stimuli such as H₂O₂, near-infrared light, NH₃, or their combinations. Because of the versatility in motion control, the current micromotor has great potential in the application field of logic gate and logic circuit. With use of different stimuli as the inputs and the micromotor motion as the output, reprogrammable OR and INHIBIT logic gates or logic circuit consisting of OR, NOT, and AND logic gates can be achieved