Diagnostic protein discovery using liquid chromatography/mass spectrometry for proteolytic peptide targeting

A peptide targeting method has been developed for diagnostic protein discovery, which combines proteolytic digestion of fractionated plasma proteins and liquid chromatography coupled to electrospray time-of-flight mass spectrometry (LC/ESI-TOFMS) profiling. Proteolysis prior to profiling overcomes molecular weight limitations and compensates for the poor sensitivity of matrix-assisted laser desorption/ionization (MALDI) protein profiling. LC/MS increases the peak capacity compared to crude fractionation techniques or single sample MALDI analysis. Differentially expressed peptides are targeted in the mass chromatograms using bioinformatic techniques and subsequently sequenced with MALDI tandem MS. In a model study comparing pancreatic cancer patients to controls, 74% of the peptide targets were successfully sequenced. This profiling method was superior to previous experiments using single sample MALDI analysis for protein profiling or proteolytic peptide profiling, because more potential protein markers were identified.     

Preparation of hydrogel from green polymer

A new method was used for the production of hydrogels from green polymer with a higher swelling ratio. These hydrogels were synthesized first by graft copolymerization between acrylamide (AM) and poly(vinyl alcohol) (PVA) with alkaline or kraft lignin (AM‐PVA‐g‐lignin) and then by mixing with acrylamide monomer. The kraft and alkaline lignins were isolated from pulping liquor and characterized using UV and FT‐IR spectroscopy, and the formed hydrogels were characterized using FT‐IR spectroscopy and scanning electron microscopy (SEM). Compared with kraft lignin hydrogel, the alkaline lignin hydrogel had very high swelling ratios and slower water uptake and deswelling rates attributed to its compatible network structure. The hydrogels formed were used also to study the influence of sodium chloride on the absorption capacity at room temperature and swelling ratios at different temperatures. Copyright © 2004 John Wiley & Sons, Ltd.     

Molecular packing of functionalized fluorinated lipids in Langmuir monolayers

Fluorinated amphipaths are a fascinating class of compounds, which, despite significant challenges associated with their syntheses, have found use across a number of areas of biotechnology. Applications range from the in vitro stabilization of membrane proteins to the development of enhanced stability intravenous drug and gene delivery systems. More recently, monolayer-forming fluorinated lipids have found use in the 2D crystallization of detergent-solubilized hydrophobic or partially hydrophobic proteins at the air-water interface. In this study, we investigate the surface properties of a novel suite of monolayer forming, partially fluorinated lipids. These modular lipid structures contain a densely fluorinated insertion in the hydrocarbon tail and a synthetically modifiable headgroup. Analyses of surface-pressure area isotherms and X-ray reflectometry profiles reveal that the lipids spread into fluid monolayers and are more compressible than their non-fluorinated counterparts. Furthermore, the data support a model whereby the partially fluorinated chains of the lipid tails form a film which is fundamentally incompatible with detergents and other destabilizing amphipaths.     

Optimization and Validation of an LC Method for the Determination of Cefdinir in Dosage Form and Human Urine

A simple and reliable liquid chromatographic method has been developed and validated for the determination of cefdinir in human urine and capsule samples. A chromatographic separation was achieved on a C₁₈ column using a mobile phase consisting of potassium dihydrogen phosphate (10 mM, pH 4.5)–acetonitrile (90:10, v/v). Quantitation was achieved with UV detection at 285 nm, based on peak area with linear calibration curve at a concentration range of 0.7–39 µg mL^?1. This method was successfully applied for the establishment of an urinary excretion pattern after oral dose.     

Variable ranking based on the estimated degree of separation for two distributions of data by the length of the receiver operating characteristic curve

Variable responses are fundamental for all experiments, and they can consist of information-rich, redundant, and low signal intensities. A dataset can consist of a collection of variable responses over multiple classes or groups. Usually some of the variables are removed in a dataset that contain very little information. Sometimes all the variables are used in the data analysis phase. It is common practice to discriminate between two distributions of data; however, there is no formal algorithm to arrive at a degree of separation (DS) between two distributions of data. The DS is defined herein as the average of the sum of the areas from the probability density functions (PDFs) of A and B that contain a ≥ percentage of A and/or B. Thus, DS90 is the average of the sum of the PDF areas of A and B that contain ≥90% of A and/or B. To arrive at a DS value, two synthesized PDFs or very large experimental datasets are required. Experimentally it is common practice to generate relatively small datasets. Therefore, the challenge was to find a statistical parameter that can be used on small datasets to estimate and highly correlate with the DS90 parameter. Established statistical methods include the overlap area of the two data distribution profiles, Welch’s t-test, Kolmogorov–Smirnov (K–S) test, Mann–Whitney–Wilcoxon test, and the area under the receiver operating characteristics (ROC) curve (AUC). The area between the ROC curve and diagonal (ACD) and the length of the ROC curve (LROC) are introduced. The established, ACD, and LROC methods were correlated to the DS90 when applied on many pairs of synthesized PDFs. The LROC method provided the best linear correlation with, and estimation of, the DS90. The estimated DS90 from the LROC (DS90–LROC) is applied to a database, as an example, of three Italian wines consisting of thirteen variable responses for variable ranking consideration. An important highlight of the DS90–LROC method is utilizing the LROC curve methodology to test all variables one-at-a-time with all pairs of classes in a dataset.     

Mechanistic Insight into Binding of Huperzine A with Human Serum Albumin: Computational and Spectroscopic Approaches

Human serum albumin (HSA) is the most abundant protein in plasma synthesized by the liver and the main modulator of fluid distribution between body compartments. It has an amazing capacity to bind with multiple ligands, offering a store and transporter for various endogenous and exogenous compounds. Huperzine A (HpzA) is a natural sesquiterpene alkaloid found in Huperzia serrata and used in various neurological conditions, including Alzheimer’s disease (AD). This study elucidated the binding of HpzA with HSA using advanced computational approaches such as molecular docking and molecular dynamic (MD) simulation followed by fluorescence-based binding assays. The molecular docking result showed plausible interaction between HpzA and HSA. The MD simulation and principal component analysis (PCA) results supported the stable interactions of the protein–ligand complex. The fluorescence assay further validated the in silico study, revealing significant binding affinity between HpzA and HSA. This study advocated that HpzA acts as a latent HSA binding partner, which may be investigated further in AD therapy in experimental settings.     

A Generalized Spatial Modulation System Using Massive MIMO Space Time Coding Antenna Grouping

Massive multiple input multiple output (MIMO), also known as a very large-scale MIMO, is an emerging technology in wireless communications that increases capacity compared to MIMO systems. The massive MIMO communication technique is currently forming a major part of ongoing research. The main issue for massive MIMO improvements depends on the number of transmitting antennas to increase the data rate and minimize bit error rate (BER). To enhance the data rate and BER, new coding and modulation techniques are required. In this paper, a generalized spatial modulation (GSM) with antenna grouping space time coding technique (STC) is proposed. The proposed GSM-STC technique is based on space time coding of two successive GSM-modulated data symbols on two subgroups of antennas to improve data rate and to minimize BER. Moreover, the proposed GSM-STC system can offer spatial diversity gains and can also increase the reliability of the wireless channel by providing replicas of the received signal. The simulation results show that GSM-STC achieves better performance compared to conventional GSM techniques in terms of data rate and BER, leading to good potential for massive MIMO by using subgroups of antennas.