Methods for the analysis of cannabinoids in biological materials: a review

Various methods for the analysis of cannabinoids in biological materials, including plant and human body materials, are reviewed. Chromatographic methods, such as TLC, GC and HPLC, and non-chromatographic methods, mainly immunoassays, are discussed and compared. Chromatography is most commonly used in the analysis of plant material, with GC apparently offering the most advantages. Immunoassays, such as radioimmunoassay and fluorescence polarisation immunoassay, and enzyme immunoassay methods, such as enzyme multiplied immunoassay technique and enzyme-linked immunosorbent assay, can be used for human body materials; however, GC-MS is still necessary for confirmation and accurate quantification. Preferred methods are suggested for various specific purposes.     

Isolation and detection of Listeria spp, Salmonella spp and Yersinia spp using a simultaneous enrichment step followed by a surface adhesion immunofluorescent technique

There has been a proliferation of techniques and methods reported for analysis of water samples to determine the presence of the protozoan pathogens Cryptosporidium parvum and Giardia lamblia. Many of the proposed methods are presented as complete procedures, which include sampling, processing, staining, or detection steps while other methods are not complete. Some proposed methods have been extensively tested in multi-laboratory settings, however, others are still in the developmental stage. A set of evaluation criteria has been developed to evaluate the many proposed methods. These criteria have been applied as an example, to an existing method. These criteria should be useful to individuals attempting to evaluate methods developed for detecting protozoa in water, and conversely, they should serve as a guideline for individuals interested in developing methods, allowing them to gather data with and about their methods, and present this data in a manner that is both logical and easily evaluated.     

Optical and spectroscopic methods for biofilm examination and monitoring

Optical and spectroscopic methods for biofilmexamination and monitoring are reviewed.Biofilm examination techniques includemicroscopic methods, coupled with imageanalysis and with oligonucleotide ribosomal RNAprobing methods (fluorescence in situhybridization). Microscopic examinationtechniques are especially advantageous inextracting biofilm structural and architecturalparameters, as well as structure-functionrelationships of the biofilm microbialpopulation. Spectroscopic techniques are ableto elicit biofilm chemical and metabolicpatterns, as well as biofilm activity. They areof outstanding importance for on-line,non-invasive biofilm monitoring, especiallywhen coupled with chemometric algorithms forspectra calibration and pattern recognition.The paper emphasises the importance of thecombination of novel and established analyticaltechniques, as well as their integration withpowerful computational methods for theautomation of biofilm monitoring.     

Overview of mycotoxin methods, present status and future needs

This article reviews current requirements for the analysis for mycotoxins in foods and identifies legislative as well as other factors that are driving development and validation of new methods. New regulatory limits for mycotoxins and analytical quality assurance requirements for laboratories to only use validated methods are seen as major factors driving developments. Three major classes of methods are identified which serve different purposes and can be categorized as screening, official and research. In each case the present status and future needs are assessed. In addition to an overview of trends in analytical methods, some other areas of analytical quality assurance such as participation in proficiency testing and reference materials are identified.     

Assessing rbf networks using DELVE

In this paper, different methods for training radial basis function (RBF) networks for regression problems are described and illustrated. Then, using data from the DELVE archive, they are empirically compared with each other and with some other well known methods for machine learning. Each of the RBF methods performs well on at least one DELVE task, but none are as consistent as the best of the other non-RBF methods.     

真菌胞内多糖提取方法的研究进展

归纳了几种常用真菌胞内多糖的提取方法,主要介绍了热水浸提法、酸提法、碱提法、酶提法、超声波辅助法、微波辅助法6种方法提取真菌多糖的原理和近年来的研究进展,总结了各种方法的优缺点,为今后进一步研究真菌胞内多糖的提取工艺提供借鉴。     

Evaluation of residue-residue contact prediction methods: From retrospective to prospective

Sequence-based residue contact prediction plays a crucial role in protein structure reconstruction. In recent years, the combination of evolutionary coupling analysis (ECA) and deep learning (DL) techniques has made tremendous progress for residue contact prediction, thus a comprehensive assessment of current methods based on a large-scale benchmark data set is very needed. In this study, we evaluate 18 contact predictors on 610 non-redundant proteins and 32 CASP13 targets according to a wide range of perspectives. The results show that different methods have different application scenarios: (1) DL methods based on multi-categories of inputs and large training sets are the best choices for low-contact-density proteins such as the intrinsically disordered ones and proteins with shallow multi-sequence alignments (MSAs). (2) With at least 5L (L is sequence length) effective sequences in the MSA, all the methods show the best performance, and methods that rely only on MSA as input can reach comparable achievements as methods that adopt multi-source inputs. (3) For top L/5 and L/2 predictions, DL methods can predict more hydrophobic interactions while ECA methods predict more salt bridges and disulfide bonds. (4) ECA methods can detect more secondary structure interactions, while DL methods can accurately excavate more contact patterns and prune isolated false positives. In general, multi-input DL methods with large training sets dominate current approaches with the best overall performance. Despite the great success of current DL methods must be stated the fact that there is still much room left for further improvement: (1) With shallow MSAs, the performance will be greatly affected. (2) Current methods show lower precisions for inter-domain compared with intra-domain contact predictions, as well as very high imbalances in precisions between intra-domains. (3) Strong prediction similarities between DL methods indicating more feature types and diversified models need to be developed. (4) The runtime of most methods can be further optimized.     

Assessing the correlation of microscopy‐based and volumetry‐based measurements for resin swelling in a range of potential greener solvents for SPPS

The degree of resin swelling in a particular solvent system is one of the critical parameters for solid‐phase peptide synthesis (SPPS) and for solid‐phase synthesis in general. Methods used for measuring the degree of resin swelling include microscopy‐based and volumetry‐based methods. This study describes and compares the use of both methods for a number of commercially available resins commonly used in SPPS, with a range of solvents, which have been identified in the literature as ‘greener’ than DCM, DMF and NMP. The results were analysed by statistical methods, and a significant correlation between the two distinct methods has been demonstrated for the first time. The results will likely be used, in conjunction with other literature methods, to help in choosing both the resin and solvent system for greener SPPS, as well as for continuous flow SPPS, which is of growing importance.     

Comparing and predicting between several methods of measurement

In studies designed to compare different methods of measurement where more than two methods are compared or replicate measurements by each method are available, standard statistical approaches such as computation of limits of agreement are not directly applicable. A model is presented for comparing several methods of measurement in the situation where replicate measurements by each method are available. Measurements are viewed as classified by method, subject and replicate. Models assuming exchangeable as well as non-exchangeable replicates are considered. A fitting algorithm is presented that allows the estimation of linear relationships between methods as well as relevant variance components. The algorithm only uses methods already implemented in most statistical software.     

Orthogonal HPLC methods for quantitating related substances and degradation products of pramlintide

Pramlintide is a 37-amino acid peptide that is being evaluated as a drug candidate for treating people with type 1 and insulin-using type 2 diabetes. Two high-performance liquid chromatography (HPLC) methods were developed for quantitating related substance impurities in pramlintide drug substance as well as degradation products of pramlintide formulated for parenteral administration. The methods differ with respect to separation mode and therefore provide orthogonal information concerning related substances and degradation products. One method uses a reverse phase (RP) separation mode, and the other involves a strong cation exchange (SCX) separation. Method performance testing showed that the RP- and SCX-HPLC methods both afford a high degree of selectivity, accuracy, precision, and sensitivity. The limit of quantitation for determining spiked authentic samples of degradation products was shown to be approximately 0.1% (relative to intact pramlintide) for both methods. Relative retention times for known pramlintide degradation products were determined for both the RP- and SCX-HPLC methods, demonstrating the selectivities of the 2 methods as well as the orthogonality of the information. The methods were also shown to be diastereospecific with respect to separating pramlintide from authentic samples of D-isomers at Ala⁵, Ala⁸, Ala⁵-Ala⁸, and Leu¹². The methods did not resolve pramlintide, however, from diastereomers with D-isomers near the C- and N-termini, namely Lys¹,Cys², and Tyr³⁷.     

A guide for kernel generalized regression methods for genomic-enabled prediction

The primary objective of this paper is to provide a guide on implementing Bayesian generalized kernel regression methods for genomic prediction in the statistical software R. Such methods are quite efficient for capturing complex non-linear patterns that conventional linear regression models cannot. Furthermore, these methods are also powerful for leveraging environmental covariates, such as genotype × environment (G×E) prediction, among others. In this study we provide the building process of seven kernel methods: linear, polynomial, sigmoid, Gaussian, Exponential, Arc-cosine 1 and Arc-cosine L. Additionally, we highlight illustrative examples for implementing exact kernel methods for genomic prediction under a single-environment, a multi-environment and multi-trait framework, as well as for the implementation of sparse kernel methods under a multi-environment framework. These examples are followed by a discussion on the strengths and limitations of kernel methods and, subsequently by conclusions about the main contributions of this paper.Subject terms: Genomics, Plant sciences     

Comparison of methods for the analysis of therapeutic immunoglobulin G Fc-glycosylation profiles—Part 1: Separation-based methods

Immunoglobulin G (IgG) crystallizable fragment (Fc) glycosylation is crucial for antibody effector functions, such as antibody-dependent cell-mediated cytotoxicity, and for their pharmacokinetic and pharmacodynamics behavior. To monitor the Fc-glycosylation in bioprocess development, as well as product characterization and release analytics, reliable techniques for glycosylation analysis are needed. A wide range of analytical methods has found its way into these applications. In this study, a comprehensive comparison was performed of separation-based methods for Fc-glycosylation profiling of an IgG biopharmaceutical. A therapeutic antibody reference material was analyzed 6-fold on 2 different days, and the methods were compared for precision, accuracy, throughput and other features; special emphasis was placed on the detection of sialic acid-containing glycans. Seven, non-mass spectrometric methods were compared; the methods utilized liquid chromatography-based separation of fluorescent-labeled glycans, capillary electrophoresis-based separation of fluorescent-labeled glycans, or high-performance anion exchange chromatography with pulsed amperometric detection. Hydrophilic interaction liquid chromatography-ultra high performance liquid chromatography of 2-aminobenzamide (2-AB)-labeled glycans was used as a reference method. All of the methods showed excellent precision and accuracy; some differences were observed, particularly with regard to the detection and quantitation of minor glycan species, such as sialylated glycans.     

Comparison of methods for the analysis of therapeutic immunoglobulin G Fc-glycosylation profiles—Part 1: Separation-based methods

Immunoglobulin G (IgG) crystallizable fragment (Fc) glycosylation is crucial for antibody effector functions, such as antibody-dependent cell-mediated cytotoxicity, and for their pharmacokinetic and pharmacodynamics behavior. To monitor the Fc-glycosylation in bioprocess development, as well as product characterization and release analytics, reliable techniques for glycosylation analysis are needed. A wide range of analytical methods has found its way into these applications. In this study, a comprehensive comparison was performed of separation-based methods for Fc-glycosylation profiling of an IgG biopharmaceutical. A therapeutic antibody reference material was analyzed 6-fold on 2 different days, and the methods were compared for precision, accuracy, throughput and other features; special emphasis was placed on the detection of sialic acid-containing glycans. Seven, non-mass spectrometric methods were compared; the methods utilized liquid chromatography-based separation of fluorescent-labeled glycans, capillary electrophoresis-based separation of fluorescent-labeled glycans, or high-performance anion exchange chromatography with pulsed amperometric detection. Hydrophilic interaction liquid chromatography-ultra high performance liquid chromatography of 2-aminobenzamide (2-AB)-labeled glycans was used as a reference method. All of the methods showed excellent precision and accuracy; some differences were observed, particularly with regard to the detection and quantitation of minor glycan species, such as sialylated glycans.     

Determination of absolute configuration--an overview related to this special issue

Rapid progress in asymmetric synthesis stimulated a further development of methods and techniques for the determination of absolute configuration of chiral molecules. In recent years the direct methods, i.e. X-ray diffraction analysis, circular dichroism (vibrational and electronic), Raman optical activity, optical rotation measurements, as well as indirect methods for relative configuration assignment with the use of NMR spectroscopy or enzymatic transformations, are receiving increasing attention not only by specialists in the field but also by synthetic and structural chemists alike. This paper provides a short overview of the methods currently used, as well as references to contributions collected in this Thematic Issue of Chirality.     

Recent progresses in the application of machine learning approach for predicting protein functional class independent of sequence similarity

Protein sequence contains clues to its function. Functional prediction from sequence presents a challenge particularly for proteins that have low or no sequence similarity to proteins of known function. Recently, machine learning methods have been explored for predicting functional class of proteins from sequence-derived properties independent of sequence similarity, which showed promising potential for low- and non-homologous proteins. These methods can thus be explored as potential tools to complement alignment- and clustering-based methods for predicting protein function. This article reviews the strategies, current progresses, and underlying difficulties in using machine learning methods for predicting the functional class of proteins. The relevant software and web-servers are described. The reported prediction performances in the application of these methods are also presented, which need to be interpreted with caution as they are dependent on such factors as datasets used and choice of parameters.     

Assessment of a method for immunochemical detection of antigen on nitrocellulose membranes

Immunoblotting techniques are widely used for detection of antigen immobilized on nitrocellulose membranes. There are many immunolabeling methods and staining methods available to disclose the presence of antigen in such techniques. Five common staining methods each for alkaline phosphatase and horseradish peroxidase were examined. The staining methods with the highest sensitivity and the lowest background were selected for studies comparing five immunological labeling methods using human IgG as a model antigen. Results were evaluated on the basis of the least amount of detectable antigen and background staining. The most sensitive dot-blot method was then tested for its applicability to Western blots. For both dot-blots and Western blots, the immunoalkaline phosphatase methods are more sensitive than the corresponding immunoperoxidase methods. The use of biotinylated secondary antibodies and an avidin-enzyme conjugate is recommended. Disclosure of alkaline phosphate is best achieved with naphthol AS phosphate as substrate and fast blue BB as chromogen. Peroxidase is best stained using H2O2 and diaminobenzidine (DAB). Potential endogenous enzyme activities are demonstrable by blotting methods but can be inhibited by including levamisole in the disclosure reaction medium for calf intestinal alkaline phosphatase indicators, or by incubation of blots with sodium azide and hydrogen peroxide before immunolabeling when using horseradish peroxidase indicators.     

Advances in the analysis of protein phosphorylation

Phosphorylation is one of the most relevant and ubiquitous post-translational modifications. Despite its relevance, the analysis of protein phosphorylation has been revealed as one of the most challenging tasks due to its highly dynamic nature and low stoichiometry. However, the development and introduction of new analytical methods are modifying rapidly and substantially this field. Especially important has been the introduction of more sensitive and specific methods for phosphoprotein and phosphopeptide purification as well as the use of more sensitive and accurate MS-based analytical methods. The integration of both approaches has enabled large-scale phosphoproteome studies to be performed, an unimaginable task few years ago. Additionally, methods originally developed for differential proteomics have been adapted making the study of the highly dynamic nature of protein phosphorylation feasible. This review aims at offering an overview on the most frequently used methods in phosphoprotein and phosphopeptide enrichment as well as on the most recent MS-based analysis strategies. Current strategies for quantitative phosphoproteomics and the study of the dynamics of protein phosphorylation are highlighted.     

Biospecific chromatography of lipolytic enzymes and methods for determining their activity

The review concerns application of affinity chromatography for isolation of phospholipases and lipases, as well as the methods for determining their activities. Main emphasis is laid on the preparation of biospecific supports with lipid ligands as well as on development of new methods for assaying lipolytic activity.     

Current directions of studies for development of methods for specific diagnostics of allergic diseases in vitro

Results of studies as well as perspectives for development and use of modern in vitro methods of allergic diseases diagnostics are presented. High prevalence of allergic diseases dictates the need of high-quality etiologic diagnosis for conducting relevant etiopathogenetic treatment - allergen-specific immunotherapy and prophylactic measures. Interest to in vitro diagnostic methods due to their high specificity and commonality is rising. They are directed to identification of various elements of "material substrate" of allergic reaction - specific antibodies, cell elements, cytokines as well as genes, which encode them. Intensively developing methods based on immunoenzyme, immunofluorescent, and immunochemiluminescent reactions are widely used now. Methods based on the use of various monoclonal antibodies for identification of lymphocytic markers, cytokines, antigen-presenting cells by laser flowcytometry are also very promising. ELISPOT technology is also intensively used for diagnostics of allergic diseases. From immunogenetic methods great potential belongs to molecular biologic methods of assessment of genome specificity characterizing sensitization to given antigen.