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Heparin and the related glycosaminoglycan, heparan sulfate, are polydisperse linear polysaccharides that mediate numerous biological processes due to their interaction with proteins. Because of the structural complexity and heterogeneity of heparin and heparan sulfate, digestion to produce smaller oligosaccharides is commonly performed prior to separation and analysis. Current techniques used to monitor the extent of heparin depolymerization include UV absorption to follow product formation and size exclusion or strong anion exchange chromatography to monitor the size distribution of the components in the digest solution. In this study, we used 1H nuclear magnetic resonance (NMR) survey spectra and NMR diffusion experiments in conjunction with UV absorption measurements to monitor heparin depolymerization using the enzyme heparinase I. Diffusion NMR does not require the physical separation of the components in the reaction mixture and instead can be used to monitor the reaction solution directly in the NMR tube. Using diffusion NMR, the enzymatic reaction can be stopped at the desired time point, maximizing the abundance of larger oligosaccharides for protein-binding studies or completion of the reaction if the goal of the study is exhaustive digestion for characterization of the disaccharide composition. In this study, porcine intestinal mucosa heparin was depolymerized using the enzyme heparinase I. The unsaturated bond formed by enzymatic cleavage serves as a UV chromophore that can be used to monitor the progress of the depolymerization and for the detection and quantification of oligosaccharides in subsequent separations. The double bond also introduces a unique multiplet with peaks at 5.973, 5.981, 5.990, and 5.998 ppm in the 1H-NMR spectrum downfield of the anomeric region. This multiplet is produced by the proton of the C-4 double bond of the non-reducing end uronic acid at the cleavage site. Changes in this resonance were used to monitor the progression of the enzymatic digestion and compared to the profile obtained from UV absorbance measurements. In addition, in situ NMR diffusion measurements were explored for their ability to profile the different-sized components generated over the course of the digestion. Figure DOSY spectra of intact (blue) and digested (red) heparin illustrating the differences in their diffusion coefficients.

This review discusses recent developments in analytical methods available for the sensitive separation, detection and structural characterization of heparin contaminants. The adulteration of raw heparin with oversulfated chondroitin sulfate (OSCS) in 2007–2008 spawned a global crisis resulting in extensive revisions to the pharmacopeia monographs on heparin and prompting the FDA to recommend the development of additional physicochemical methods for the analysis of heparin purity. The analytical chemistry community quickly responded to this challenge, developing a wide variety of innovative approaches, several of which are reported in this special issue. This review provides an overview of methods of heparin isolation and digestion, discusses known heparin contaminants, including OSCS, and summarizes recent publications on heparin impurity analysis using sensors, near-IR, Raman, and NMR spectroscopy, as well as electrophoretic and chromatographic separations. Figure Schematic illustrating the process for heparin impurity characterization

Determination of the structure of heparin-derived oligosaccharides by 1H NMR is challenging because resonances for all but the anomeric protons cover less than 2 ppm. By taking advantage of increased dispersion of resonances for the anomeric H1 protons at low pD and the superior resolution of band-selective, homonuclear-decoupled (BASHD) two-dimensional 1H NMR, the primary structure of the heparin-derived octasaccharide ∆UA(2S)-[(1 → 4)-GlcNS(6S)-(1 → 4)-IdoA(2S)-]3-(1 → 4)-GlcNS(6S) has been determined, where ∆UA(2S) is 2-O-sulfated ∆4,5-unsaturated uronic acid, GlcNS(6S) is 6-O-sulfated, N-sulfated β-d-glucosamine and IdoA(2S) is 2-O-sulfated α-l-iduronic acid. The spectrum was assigned, and the sites of N- and O-sulfation and the conformation of each uronic acid residue were established, with chemical shift data obtained from BASHD-TOCSY spectra, while the sequence of the monosaccharide residues in the octasaccharide was determined from inter-residue NOEs in BASHD-NOESY spectra. Acid dissociation constants were determined for each carboxylic acid group of the octasaccharide, as well as for related tetra- and hexasaccharides, from chemical shift–pD titration curves. Chemical shift–pD titration curves were obtained for each carboxylic acid group from sub-spectra taken from BASHD-TOCSY spectra that were measured as a function of pD. The pK As of the carboxylic acid groups of the ∆UA(2S) residues are less than those of the IdoA(2S) residues, and the pK As of the carboxylic acid groups of the IdoA(2S) residues for a given oligosaccharide are similar in magnitude. Relative acidities of the carboxylic acid groups of each oligosaccharide were calculated from chemical shift data by a pH-independent method.

Availability of a rapid, accurate, and reliable point-of-care (POC) device for detection of infectious agents and pandemic pathogens, such as swine-origin influenza A (H1N1) virus, is crucial for effective patient management and outbreak prevention. Due to its ease of use, rapid processing, and minimal power and laboratory equipment requirements, the lateral-flow (immuno)assay (LFA) has gained much attention in recent years as a possible solution. However, since the sensitivity of LFA has been shown to be inferior to that of the gold standards of pathogen detection, namely cell culture and real-time PCR, LFA remains an ineffective POC assay for preventing pandemic outbreaks. A practical solution for increasing the sensitivity of LFA is to concentrate the target agent in a solution prior to the detection step. In this study, an aqueous two-phase micellar system comprised of the nonionic surfactant Triton X-114 was investigated for concentrating a model virus, namely bacteriophage M13 (M13), prior to LFA. The volume ratio of the two coexisting micellar phases was manipulated to concentrate M13 in the top, micelle-poor phase. The concentration step effectively improved the M13 detection limit of the assay by tenfold from 5 × 108 plaque forming units (pfu)/mL to 5 × 107 pfu/mL. In the future, the volume ratio can be further manipulated to yield a greater concentration of a target virus and further decrease the detection limits of the LFA. Figure A schematic representation of concentrating viruses with an aqueous two-phase micellar system containing Triton X-114 surfactant prior to the detection of the virus through the lateral-flow immunoassay

This paper describes a Bayesian approach to prevalence estimation based on pooled samples that accommodates variation in pool size and adjusts for test imperfection. A logistic model was developed for pooled fecal culture (PFC) sensitivity as a function of pool size and a logistic mixed model for ovine Johne’s disease (OJD) prevalence as a function of covariates that were found significant in a recent OJD risk factor study conducted in Australia. Available data on these factors and prior information about prevalence and sensitivity were incorporated into a Bayesian model to estimate OJD prevalence from PFC data. Overall, posterior cohort OJD prevalence was estimated to be 0.16 (range of prevalences across cohorts 0.002 to 0.72). The average prevalence was higher in wethers than ewes. PFC sensitivities for pool sizes 10, 30 and 50 were estimated to be 0.91 (95% probability intervals 0.80, 0.96), 0.85 (0.80, 0.90) and 0.77 (0.65, 0.88), respectively. Posterior specificity of PFC was almost perfect though based primarily on the prior. Results suggest the Bayesian model successfully estimated the animal-level prevalence after accounting for variable pool size and imperfect test parameters. The method can be easily adapted for other conditions and diseases where pooled samples are collected. WinBugs code for the article is available online.

Two-class neutral zone classifiers were recently proposed for use in microbial community profiling applications. These classifiers allow a region of neutrality for cases where probe hybridization outcomes are too ambiguous to have adequate confidence in assigning a “binding” or “no binding” result. In this paper, we generalize the idea of neutral zone classifiers to an arbitrary number of classes and apply it to improve the process of microbial community profiling by considering a third class for the outcome of probe hybridization experiments, “partial binding.” We introduce a family of class distributions that uses a mixture of Gaussian distributions as a model for a Box–Cox power transformation of the raw intensity measurements. Stratified cross-validation analyses are used to assess the efficacy of the proposed three-class neutral zone classifier. This article has supplementary material online.

Analysis of naturally occurring isotopic variations is a promising tool for investigating Zn transport and cycling in geological and biological settings. Here, we present the recently installed double-spike (DS) technique at the MAGIC laboratories at Imperial College London. The procedure improves on previous published DS methods in terms of ease of measurement and precisions obtained. The analytical method involves addition of a 64Zn–67Zn double-spike to the samples prior to digestion, separation of Zn from the sample matrix by ion exchange chromatography, and isotopic analysis by multiple-collector inductively coupled plasma mass spectrometry. The accuracy and reproducibility of the method were validated by analyses of several in-house and international elemental reference materials. Multiple analyses of pure Zn standard solutions consistently yielded a reproducibility of about ±0.05‰ (2 SD) for δ66Zn, and comparable precisions were obtained for analyses of geological and biological materials. Highly fractionated Zn standards analyzed by DS and standard sample bracketing yield slightly varying results, which probably originate from repetitive fractionation events during manufacture of the standards. However, the δ66Zn values (all reported relative to JMC Lyon Zn) for two less fractionated in-house Zn standard solutions, Imperial Zn (0.10 ± 0.08‰: 2 SD) and London Zn (0.08 ± 0.04‰), are within uncertainties to data reported with different mass spectrometric techniques and instruments. Two standard reference materials, blend ore BCR 027 and ryegrass BCR 281, were also measured, and the δ66Zn were found to be 0.25 ± 0.06‰ (2 SD) and 0.40 ± 0.09‰, respectively. Taken together, these standard measurements ascertain that the double-spike methodology is suitable for accurate and precise Zn isotope analyses of a wide range of natural samples. The newly installed technique was consequently applied to soil samples and soil leachates to investigate the isotopic signature of plant available Zn. We find that the isotopic composition is heavier than the residual, indicating the presence of loosely bound Zn deposited by atmospheric pollution, which is readily available to plants. Figure Zinc isotope ratio pools of bulk soil and the associated acid leach (estimated plant available pool) as measured by double-spike MC-ICPMS. δxZnLyon-JMC=(Rsample/RJMC-Lyon -1)x103, where Rsample and RJMC-Lyon denote the xZn/64Zn isotope ratio of the sample and standard (JMC-Lyon), respectively, and where x denotes either 66 or 68.

Cell separation and sorting are essential steps in cell biology research and in many diagnostic and therapeutic methods. Recently, there has been interest in methods which avoid the use of biochemical labels; numerous intrinsic biomarkers have been explored to identify cells including size, electrical polarizability, and hydrodynamic properties. This review highlights microfluidic techniques used for label-free discrimination and fractionation of cell populations. Microfluidic systems have been adopted to precisely handle single cells and interface with other tools for biochemical analysis. We analyzed many of these techniques, detailing their mode of separation, while concentrating on recent developments and evaluating their prospects for application. Furthermore, this was done from a perspective where inertial effects are considered important and general performance metrics were proposed which would ease comparison of reported technologies. Lastly, we assess the current state of these technologies and suggest directions which may make them more accessible. Figure A wide range of microfluidic technologies have been developed to separate and sort cells by taking advantage of differences in their intrinsic biophysical properties

The Southern Ocean (SO) transports heat towards Antarctica and plays an important role in determining the heat budget of the Antarctic climate system. A global ocean data synthesis product at eddy-permitting resolution from the Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) project is used to estimate the meridional heat transport (MHT) in the SO and to analyze its mechanisms. Despite the intense eddy activity, we demonstrate that most of the poleward MHT in the SO is due to the time-mean fields of the meridional velocity, V, and potential temperature, θ. This is because the mean circulation in the SO is not strictly zonal. The Antarctic Circumpolar Current carries warm waters from the region south of the Agulhas Retroflection to the lower latitudes of the Drake Passage and the Malvinas Current carries cold waters northward along the Argentinian shelf. Correlations between the time-varying fields of V and θ (defined as transient processes) significantly contribute to the horizontal-gyre heat transport, but not the overturning heat transport. In the highly energetic regions of the Agulhas Retroflection and the Brazil-Malvinas Confluence the contribution of the horizontal transient processes to the total MHT exceeds the contribution of the mean horizontal flow. We show that the southward total MHT is mainly maintained by the meridional excursion of the mean geostrophic horizontal shear flow (i.e., deviation from the zonal average) associated with the Antarctic Circumpolar Current that balances the equatorward MHT due to the Ekman transport and provides a net poleward MHT in the SO. The Indian sector of the SO serves as the main pathway for the poleward MHT.

Across many environments, nitrate ( $\mbox{NO}_{3}^-$ ) is an important form of N available for microorganisms and photosynthetic organisms. Accurate $\mbox{NO}_{3}^-$ measurements are important for examining N cycling and retention in terrestrial and aquatic ecosystems, but a common method of $\mbox{NO}_{3}^-$ analysis can underestimate $\mbox{NO}_{3}^-$ concentrations when soluble iron is present (iron > 10 mg L − 1). The basic method is robust, using copperized cadmium to reduce $\mbox{NO}_{3}^-$ and then diazotizing the resulting $\mbox{NO}_{2}^-$ in a two-step process to form an easily measured colored product. We show that iron interference is unique to using an NH4Cl and ethylenediaminetetraacetic acid (EDTA) buffer. We hypothesize that interference is through iron-catalyzed reduction of the intermediate color product, a diazonium ion. We examine three historical buffers as alternatives to NH4Cl/EDTA and recommend replacement of EDTA with diethylenetriaminepentaacetic acid, which chelates metals much like EDTA, but unlike EDTA, it does not cause interference in the presence of iron.

Quantitative multistage carcinogenesis models are used in radiobiology to estimate cancer risks and latency periods (time from exposure to clinical cancer). Steps such as initiation, promotion and transformation have been modeled in detail. However, progression, a later step during which malignant cells can develop into clinical symptomatic cancer, has often been approximated simply as a fixed lag time. This approach discounts important stochastic mechanisms in progression and evidence on the high prevalence of dormant tumors. Modeling progression more accurately is therefore important for risk assessment. Unlike models of earlier steps, progression models can readily utilize not only experimental and epidemiological data but also clinical data such as the results of modern screening and imaging. Here, a stochastic progression model is presented. We describe, with minimal parameterization: the initial growth or extinction of a malignant clone after formation of a malignant cell; the likely dormancy caused, for example, by nutrient and oxygen deprivation; and possible escape from dormancy resulting in a clinical cancer. It is shown, using cohort simulations with parameters appropriate for lung adenocarcinomas, that incorporating such processes can dramatically lengthen predicted latency periods. Such long latency periods together with data on timing of radiation-induced cancers suggest that radiation may influence progression itself.

The aim of this study was to measure permeation of the herbicide dichlobenil in Casoron 4G through disposable and chemically protective nitrile gloves using an American Society for Testing and Materials-type permeation cell and a closed-loop system employing two different solvents (hexane and water) and two different challenge situations (aqueous emulsion and solid formulation). Capillary gas chromatography–mass spectrometry was used for quantification purposes. The chemically protective glove did not allow any permeation up to 8 h for the solid-formulation and water-collection challenges, but permeation was detected in all other challenges. The disposable glove allowed the most permeation, and the solid-formulation challenge with water collection necessitated that a dichlobenil equivalent be calculated because of the presence of its hydrolysis degradation product 2,6-dichlorobenzamide. Permeation from the solid formulation was detectable by hexane collection for both the disposable and chemically protective gloves and by water collection for the disposable glove. It was concluded that hexane-solvent collection was not valid for the disposable glove at 4 and 8 h of permeation in the solid Casoron challenge or for the aqueous emulsion challenge at 8 h relative to the water-collection solvent data. The hexane-solvent collection for the chemically protective glove was valid for the 8-h solid-formulation challenge but not for the 8-h aqueous-solution challenge. All water-solvent collections were valid; however, dichlobenil usually permeated the gloves.

Concentrations of polychlorinated biphenyls (PCBs) as well as the expression patterns of cytochrome P450 (CYP) enzymes and glutathione-S-transferase (GST) activities were measured in livers of loggerhead (Caretta caretta), green (Chelonia mydas), and olive ridley (Lepidocheyls olivacea) sea turtles from the Baja California peninsula of Mexico. The mean concentrations of total PCBs were 18.1, 10.5, and 15.2 ng/g wet weight (ww) respectively for the three species and PCB 153 was the dominant congener in all samples. Total PCB concentrations were dominated by penta- and hexa-chlorinated biphenyls. The mean estimated TEQs were 42.8, 22.9, and 10.4 pg/g (ww) for loggerhead, green, and olive ridley, respectively, and more than 70% was accounted for by non-ortho PCBs. Western blots revealed the presence of hepatic microsomal proteins that cross-reacted with anti-CYP2K1 and anti-CYP3A27 antibodies but not with anti-CYP1A antibody. There were no significant differences in GST activities between species. Grouping congeners based on structure–activity relationships for CYP isoenzymes suggested limited activity of CYP1A contribution to PCB biotransformation in sea turtles. These results suggest potential accumulation of PCBs that are CYP1A substrates and provide evidence for biotransformation capacity, which differs from known animal models, highlighting the need for further studies in reptiles, particularly those threatened with extinction.

As the number of cancer survivors grows, prediction of radiotherapy-induced second cancer risks becomes increasingly important. Because the latency period for solid tumors is long, the risks of recently introduced radiotherapy protocols are not yet directly measurable. In the accompanying article, we presented a new biologically based mathematical model, which, in principle, can estimate second cancer risks for any protocol. The novelty of the model is that it integrates, into a single formalism, mechanistic analyses of pre-malignant cell dynamics on two different time scales: short-term during radiotherapy and recovery; long-term during the entire life span. Here, we apply the model to nine solid cancer types (stomach, lung, colon, rectal, pancreatic, bladder, breast, central nervous system, and thyroid) using data on radiotherapy-induced second malignancies, on Japanese atomic bomb survivors, and on background US cancer incidence. Potentially, the model can be incorporated into radiotherapy treatment planning algorithms, adding second cancer risk as an optimization criterion.

Mathematical models of radiation carcinogenesis are important for understanding mechanisms and for interpreting or extrapolating risk. There are two classes of such models: (1) long-term formalisms that track pre-malignant cell numbers throughout an entire lifetime but treat initial radiation dose–response simplistically and (2) short-term formalisms that provide a detailed initial dose–response even for complicated radiation protocols, but address its modulation during the subsequent cancer latency period only indirectly. We argue that integrating short- and long-term models is needed. As an example of this novel approach, we integrate a stochastic short-term initiation/inactivation/repopulation model with a deterministic two-stage long-term model. Within this new formalism, the following assumptions are implemented: radiation initiates, promotes, or kills pre-malignant cells; a pre-malignant cell generates a clone, which, if it survives, quickly reaches a size limitation; the clone subsequently grows more slowly and can eventually generate a malignant cell; the carcinogenic potential of pre-malignant cells decreases with age.