Abnormally high content of free glucosamine residues identified in a preparation of commercially available porcine intestinal heparan sulfate

Heparan sulfate (HS) polysaccharides are ubiquitous in animal tissues as components of proteoglycans, and they participate in many important biological processes. HS carbohydrate chains are complex and can contain rare structural components such as N-unsubstituted glucosamine (GlcN). Commercially available HS preparations have been invaluable in many types of research activities. In the course of preparing microarrays to include probes derived from HS oligosaccharides, we found an unusually high content of GlcN residue in a recently purchased batch of porcine intestinal mucosal HS. Composition and sequence analysis by mass spectrometry of the oligosaccharides obtained after heparin lyase III digestion of the polysaccharide indicated two and three GlcN in the tetrasaccharide and hexasaccharide fractions, respectively. (1)H NMR of the intact polysaccharide showed that this unusual batch differed strikingly from other HS preparations obtained from bovine kidney and porcine intestine. The very high content of GlcN (30%) and low content of GlcNAc (4.2%) determined by disaccharide composition analysis indicated that N-deacetylation and/or N-desulfation may have taken place. HS is widely used by the scientific community to investigate HS structures and activities. Great care has to be taken in drawing conclusions from investigations of structural features of HS and specificities of HS interaction with proteins when commercial HS is used without further analysis. Pending the availability of a validated commercial HS reference preparation, our data may be useful to members of the scientific community who have used the present preparation in their studies

Shotgun ion mobility mass spectrometry sequencing of heparan sulfate saccharides

Despite evident regulatory roles of heparan sulfate (HS) saccharides in numerous biological processes, definitive information on the bioactive sequences of these polymers is lacking, with only a handful of natural structures sequenced to date. Here, we develop a “Shotgun” Ion Mobility Mass Spectrometry Sequencing (SIMMS2) method in which intact HS saccharides are dissociated in an ion mobility mass spectrometer and collision cross section values of fragments measured. Matching of data for intact and fragment ions against known values for 36 fully defined HS saccharide structures (from di- to decasaccharides) permits unambiguous sequence determination of validated standards and unknown natural saccharides, notably including variants with 3O-sulfate groups. SIMMS2 analysis of two fibroblast growth factor-inhibiting hexasaccharides identified from a HS oligosaccharide library screen demonstrates that the approach allows elucidation of structure-activity relationships. SIMMS2 thus overcomes the bottleneck for decoding the informational content of functional HS motifs which is crucial for their future biomedical exploitation

A High Speed Particle Phase Discriminator (PPD-HS) for the classification of airborne particles, as tested in a continuous flow diffusion chamber

© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.A new instrument, the High-speed Particle Phase Discriminator (PPD-HS), developed at the University of Hertfordshire, for sizing individual cloud hydrometeors and determining their phase is described herein. PPD-HS performs an in situ analysis of the spatial intensity distribution of near-forward scattered light for individual hydrometeors yielding shape properties. Discrimination of spherical and aspherical particles is based on an analysis of the symmetry of the recorded scattering patterns. Scattering patterns are collected onto two linear detector arrays, reducing the complete 2-D scattering pattern to scattered light intensities captured onto two linear, one-dimensional strips of light sensitive pixels. Using this reduced scattering information, we calculate symmetry indicators that are used for particle shape and ultimately phase analysis. This reduction of information allows for detection rates of a few hundred particles per second. Here, we present a comprehensive analysis of instrument performance using both spherical and aspherical particles generated in a well-controlled laboratory setting using a vibrating orifice aerosol generator (VOAG) and covering a size range of approximately 3-32 μm. We use supervised machine learning to train a random forest model on the VOAG data sets that can be used to classify any particles detected by PPD-HS. Classification results show that the PPD-HS can successfully discriminate between spherical and aspherical particles, with misclassification below 5% for diameters >3μm. This phase discrimination method is subsequently applied to classify simulated cloud particles produced in a continuous flow diffusion chamber setup. We report observations of small, near-spherical ice crystals at early stages of the ice nucleation experiments, where shape analysis fails to correctly determine the particle phase. Nevertheless, in the case of simultaneous presence of cloud droplets and ice crystals, the introduced particle shape indicators allow for a clear distinction between these two classes, independent of optical particle size. From our laboratory experiments we conclude that PPD-HS constitutes a powerful new instrument to size and discriminate the phase of cloud hydrometeors. The working principle of PPD-HS forms a basis for future instruments to study microphysical properties of atmospheric mixed-phase clouds that represent a major source of uncertainty in aerosol-indirect effect for future climate projections..Peer reviewe

Headspace analysis of natural yoghurt using headspace solid phase microextraction : a thesis presented in partial fulfilment of the requirements for the degree of Master of Philosophy in Food Technology at Massey University (Turitea Campus), Palmerston North, New Zealand

The Solid Phase Microextraction (SPME) method was originally developed to extract volatile and semivolatile compounds from wastewater samples but has since been applied to flavour compounds in foods and beverages. Research using the HS-SPME in related areas such as cheese and skim milk powder has been carried out but, to date, no work has been done on yoghurt flavours. The main objective of this study was to devise a methodology for the Headspace Solid Phase Microextraction (HS-SPME) technique to investigate and quantify six flavour analytes in natural, set yoghurts made from recombined milk. The relevant literature was reviewed and from it, a research proposal for this work on yoghurts was drawn. The first step in analysing and quantifying the yoghurt volatiles was to set up a working methodology for the HS-SPME method. The 100 μm polydimethylsiloxane (PDMS) fibre was chosen along with 20 minutes being the optimum fibre adsorption time. General equipment, materials and methods used throughout this thesis are also detailed. The external standard (ES) method was used to calibrate the GC and quantify the analyte concentrations in this study. The internal standard (IS) method was not used as a quantitative tool in this study. Once the HS-SPME methodology had been set up for the analysis of yoghurts, the classical Static Headspace (SH) method was compared with the HS-SPME method for extraction efficiency. The results suggested that the two methods were complementary in that the SH method extracted the more volatile compounds (acetaldehyde, acetone and 2-butanone) whereas, the HS-SPME method extracted the semi- to non-volatile compounds (ethanol, diacetyl and acetoin) more readily. However, the HS-SPME was found to be the more sensitive and effective method of the two techniques tested. The next step in the thesis was to investigate the presence of the six analytes in milk and cultured yoghurt. The effects of the sample matrix, fat levels and incubation on the volatile concentrations were also examined. The results suggested that the six analytes were inherently present in milks but at low concentrations. No conclusive effects were found for the sample matrix, fat levels and incubation. However, it was evident that fermentation of the milks using bacterial starter cultures resulted in a large increase in some of the volatiles being investigated. Following this, the effects of fat levels, storage time and storage temperature on the six volatiles in yoghurts were examined. The results indicated that significant fat level effects were only seen for diacetyl and acetoin, while temperature effects were only observed for ethanol. In both trials, only general trends for the analytes concentrations were drawn because the data varied from day to day. The results suggested that most of the compounds decreased with time except for diacetyl, which seemed to increase. The final part of this study looked at applying the devised HS-SPME methodology to a series of commercial yoghurts as a preliminary trial, with a view to investigating a potential application for the HS-SPME method. Fourteen commercial yoghurts were analysed and the six analytes quantified. The data obtained was analysed using Principle Component Analysis (PCA), which divided the yoghurts into groups based on their analyte concentrations. From these groupings, eight yoghurts were selected and fresh samples were analysed using HS-SPME and PCA. This was carried out parallel with an untrained consumer panel, which had to distinguish differences between the yoghurts in a series of triangle tests by smelling the headspace on opening the yoghurt containers. The conclusions drawn were that, unlike the HS-SPME method with PCA, the average consumer could not differentiate the yoghurts based on smell alone. PCA also showed that the HS-SPME results obtained were fairly reproducible. In conclusion, the HS-SPME method was shown to be a useful analytical technique, which can be used to analyse and quantify flavour compounds in natural, set yoghurts. This area of investigation has a lot of scope, with the results from this study providing a basis or starting point for further investigations in this area. Future studies may lead to potential applications for the HS-SPME method, one of which may be quality control where correlation of sensory data with HS-SPME analytical data is required

Magnetic Phase Diagram of GdNi2B2C: Two-ion Magnetoelasticity and Anisotropic Exchange Couplings

Extensive magnetization and magnetostriction measurements were carried out on a single crystal of GdNi2B2C along the main tetragonal axes. Within the paramagnetic phase, the magnetic and strain susceptibilities revealed a weak anisotropy in the exchange couplings and two-ion tetragonal-preserving alpha-strain modes. Within the ordered phase, magnetization and magnetostriction revealed a relatively strong orthorhombic distortion mode and rich field-temperature phase diagrams. For H//(100) phase diagram, three field-induced transformations were observed, namely, at: Hd(T), related to the domain alignment; Hr(T), associated with reorientation of the moment towards the c-axis; and Hs(T), defining the saturation process wherein the exchange field is completely counterbalanced. On the other hand, For H//(001) phase diagram, only two field-induced transformations were observed, namely at: Hr(T) and Hs(T). For both phase diagrams, Hs(T) follows the relation Hs[1-(T/Tn)^2]^(1/2)kOe with Hs(T-->0)=128.5(5) kOe and Tn(H=0)=19.5 K. In contrast, the thermal evolution of Hr(T) along the c-axis (much simpler than along the a-axis) follows the relation Hr[1-T/Tr]^(1/3) kOe where Hr(T-->0)=33.5(5) kOe and Tr(H=0)=13.5 K. It is emphasized that the magnetoelastic interaction and the anisotropic exchange coupling are important perturbations and therefore should be explicitly considered if a complete analysis of the magnetic properties of the borocarbides is desired

Clinicopathological characteristics of histiocytic sarcoma affecting the central nervous system in dogs.

BackgroundHistiocytic sarcoma affecting the central nervous system (CNS HS) in dogs may present as primary or disseminated disease, often characterized by inflammation. Prognosis is poor, and imaging differentiation from other CNS tumors can be problematic.ObjectiveTo characterize the clinicopathological inflammatory features, breed predisposition, and survival in dogs with CNS HS.AnimalsOne hundred two dogs with HS, 62 dogs with meningioma.MethodsRetrospective case series. Records were reviewed for results of cerebrospinal fluid (CSF) analysis, CBC, treatment, and outcome data.ResultsPredisposition for CNS HS was seen in Bernese Mountain Dogs, Golden Retrievers, Rottweilers, Corgis, and Shetland Sheepdogs (P ≤ .001). Corgis and Shetland Sheepdogs had predominantly primary tumors; Rottweilers had exclusively disseminated tumors. Marked CSF inflammation was characteristic of primary rather than disseminated HS, and neoplastic cells were detected in CSF of 52% of affected dogs. Increased neutrophil to lymphocyte ratios were seen in all groups relative to controls (P <.008) but not among tumor subtypes. Definitive versus palliative treatment resulted in improved survival times (P < .001), but overall prognosis was poor.Conclusions and clinical importanceClinicopathological differences between primary and disseminated HS suggest that tumor biological behavior and origin may be different. Corgis and Shetland Sheepdogs are predisposed to primary CNS HS, characterized by inflammatory CSF. High total nucleated cell count and the presence of neoplastic cells support the use of CSF analysis as a valuable diagnostic test. Prognosis for CNS HS is poor, but further evaluation of inflammatory mechanisms may provide novel therapeutic opportunities

Feeding practices and growth among young children during two seasons in rural Ethiopia

BACKGROUND: The use of indices of infant and young child feeding practices to predict growth has generated inconsistent results, possibly through age and seasonal confounding. The aim of this study was to evaluate the association of a dietary diversity score (DDS) and infant and child feeding index (ICFI) with growth among young children in a repeated cross-sectional and a follow-up study in two distinct seasons in rural southwest Ethiopia. METHODS: We used a repeated cross-sectional design comparing child feeding practices to nutritional status in 6–12 month old children during harvest (HS; n = 320) and pre-harvest season (PHS; n = 312). In addition, 6–12 month old children from the HS were reassessed 6 months later during PHS. In addition to child anthropometry, child feeding practices were collected using 24-h and 7-day dietary recalls. RESULTS: The mean (±SD) length-for-age z-score (LAZ) of the 6–12 month old children was −0.77 (±1.4) and −1.0 (±1.3) in HS and PHS, respectively, while the mean (±SD) of the follow-up children in PHS was −1.0 (±1.3). The median DDS (IQR) was 2.0 (1.0, 3.0.), 2.0 (2.0, 3.0) and 3.0 (2.0, 4.0) for the children in HS, PHS and the follow-up children in PHS, respectively. The DDS in HS was positively associated with LAZ at follow-up (β = 0.16; 95% CI: 0.01, 0.30; P = 0.03) after controlling for confounding factors. ICFI and DDS were not associated with mean LAZ, weight-for-height z-score and weight-for-age z-score within season. However, the odds of being stunted when having a DDS ≤ 2 was 2.3 times (95% CI: 1.10, 4.78; P = 0.03) higher compared to a DDS > 2 child in HS and 1.7 times (95% CI: 1.04, 2.71; P = 0.04) higher for the pooled sample of 6–12 months old children in HS and PHS. CONCLUSIONS: The DDS was found to be an indicator for child stunting during the Ethiopian harvest season. The DDS can be an appropriate tool to evaluate the association of child feeding practices with child growth irrespective of season. Inclusion of other dimensions in the construction of ICFI should be considered in future analysis as we found no association with growth

Hilbert space renormalization for the many-electron problem

Renormalization is a powerful concept in the many-body problem. Inspired by the highly successful density matrix renormalization group (DMRG) algorithm, and the quantum chemical graphical representation of configuration space, we introduce a new theoretical tool: Hilbert space renormalization, to describe many-electron correlations. While in DMRG, the many-body states in nested Fock subspaces are successively renormalized, in Hilbert space renormalization, many-body states in nested Hilbert subspaces undergo renormalization. This provides a new way to classify and combine configurations. The underlying wavefunction ansatz, namely the Hilbert space matrix product state (HS-MPS), has a very rich and flexible mathematical structure. It provides low-rank tensor approximations to any configuration interaction (CI) space through restricting either the 'physical indices' or the coupling rules in the HS-MPS. Alternatively, simply truncating the 'virtual dimension' of the HS-MPS leads to a family of size-extensive wave function ansaetze that can be used efficiently in variational calculations. We make formal and numerical comparisons between the HS-MPS, the traditional Fock-space MPS used in DMRG, and traditional CI approximations. The analysis and results shed light on fundamental aspects of the efficient representation of many-electron wavefunctions through the renormalization of many-body states.Comment: 23 pages, 14 figures, The following article has been submitted to The Journal of Chemical Physic