Studies on the biodegradation of fosfomycin: Synthesis of 13C-labeled intermediates, feeding experiments with rhizobium huakuii PMY1, and Isolation of Labeled Amino Acids from Cell Mass by HPLC

Racemic (1R*,2R*)-1,2-dihydroxy-[1- ^{13C ₁]propylphosphonic acid and 1-hydroxy-[1- 13C ₁]acetone were synthesized and fed to R. huakuii PMY1. Alanine and a mixture of valine and methionine were isolated as their N-acetyl derivatives from the cell hydrolysate by reversed-phase HPLC and analyzed by NMR spectroscopy. It was found that the carbon atoms of the respective carboxyl groups were highly 13C-labeled (up to 65 %). Hydroxyacetone is therefore considered an obligatory intermediate of the biodegradation of fosfomycin by R. huakuii PMY1.}

The discrepancy between social isolation and loneliness as a clinically meaningful metric: findings from the Irish and English longitudinal studies of ageing (TILDA and ELSA)

Objective
Scant evidence is available on the discordance between loneliness and social isolation among older adults. We aimed to investigate this discordance and any health implications that it may have.

Method
Using nationally representative datasets from ageing cohorts in Ireland (TILDA) and England (ELSA), we created a metric of discordance between loneliness and social isolation, to which we refer as Social Asymmetry. This metric was the categorised difference between standardised scores on a scale of loneliness and a scale of social isolation, giving categories of: Concordantly Lonely and Isolated, Discordant: Robust to Loneliness, or Discordant: Susceptible to Loneliness. We used regression and multilevel modelling to identify potential relationships between Social Asymmetry and cognitive outcomes.

Results
Social Asymmetry predicted cognitive outcomes cross-sectionally and at a two-year follow-up, such that Discordant: Robust to Loneliness individuals were superior performers, but we failed to find evidence for Social Asymmetry as a predictor of cognitive trajectory over time.

Conclusions
We present a new metric and preliminary evidence of a relationship with clinical outcomes. Further research validating this metric in different populations, and evaluating its relationship with other outcomes, is warranted.

NEUROPEPTIDE-Y AND NEUROPEPTIDE-Y 3-36 - ISOLATION FROM HUMAN PANCREATIC ENDOCRINE TUMORS

Using an antiserum raised to the C-terminal region of neuropeptide Y (NPY) which does not cross-react with pancreatic polypeptide (PP), immunoreactivity has been detected in two different endocrine tumours of the human pancreas in concentrations permitting isolation and structural analysis. In a clinically-typical gastrinoma, resected from the head of pancreas, the concentration of NPY immunoreactivity was 3.4 nmol/g. Reverse phase HPLC analysis of extracts of this tumour resolved a single immunoreactive peptide coeluting with synthetic human NPY. The molecular mass of the isolated peptide, determined by mass spectroscopy, was 4270 Da, which was in close agreement with that derived from the deduced primary structure of human tumour NPY (4271.7 Da), obtained by gas-phase sequencing. A somatostatinoma, resected from the region of the ampulla of Vater, contained 3.8 nmol/g of NPY immunoreactivity and isolation of this immunoreactive peptide followed by structural analyses, indicated a molecular structure consistent with NPY 3-36. These data suggest that NPY immunoreactivity detected in human pancreatic endocrine tumours is molecularly heterogenous, a finding which may be of relevance in the symptomatology of such tumours as attenuation of the N-terminus of this peptide generates receptor selectivity.

PLS modelling and fault detection on the Tennessee Eastman benchmark

This paper describes the application of multivariate regression techniques to the Tennessee Eastman benchmark process for modelling and fault detection. Two methods are applied : linear partial least squares, and a nonlinear variant of this procedure using a radial basis function inner relation. The performance of the RBF networks is enhanced through the use of a recently developed training algorithm which uses quasi-Newton optimization to ensure an efficient and parsimonious network; details of this algorithm can be found in this paper. The PLS and PLS/RBF methods are then used to create on-line inferential models of delayed process measurements. As these measurements relate to the final product composition, these models suggest that on-line statistical quality control analysis should be possible for this plant. The generation of `soft sensors' for these measurements has the further effect of introducing a redundant element into the system, redundancy which can then be used to generate a fault detection and isolation scheme for these sensors. This is achieved by arranging the sensors and models in a manner comparable to the dedicated estimator scheme of Clarke et al. 1975, IEEE Trans. Pero. Elect. Sys., AES-14R, 465-473. The effectiveness of this scheme is demonstrated on a series of simulated sensor and process faults, with full detection and isolation shown to be possible for sensor malfunctions, and detection feasible in the case of process faults. Suggestions for enhancing the diagnostic capacity in the latter case are covered towards the end of the paper.

Journeys into the unknown: shared schooling and social change in Quebec and Northern Ireland

This article compares experiences of shared schooling in societies with 2 distinctive traits: first, a history of intercommunity conflict and isolation; and second, a segregated school system. Drawing on Parekh’s (2006) reconceptualisation of multiculturalism, this article analyses issues arising from experiences of intercommunity contact in shared schools in Quebec and Northern Ireland—in one case, bringing Anglophones and Francophones together and, in the other, Protestants and Catholics. Research data from both contexts is drawn upon to reflect on how this experience is lived. The metaphor of a journey is used to capture what it represents for those involved. A need to clarify, recognize, and exploit the potential of shared schooling for the transformation of divided societies is identified.

Isolation basin records of late Quaternary sea-level change, central mainland British Columbia, Canada.

Isolation basin records from the Seymour-Belize Inlet Complex, a remote area of central mainland British Columbia, Canada are used to constrain post-glacial sea-level changes and provide a preliminary basis for testing geophysical model predictions of relative sea-level (RSL) change. Sedimentological and diatom data from three low-lying (<4 m elevation) basins record falling RSLs in late-glacial times and isolation from the sea by ~11,800–11,200 14C BP. A subsequent RSL rise during the early Holocene (~8000 14C BP) breached the 2.13 m sill of the lowest basin (Woods Lake), but the two more elevated basins (sill elevations of ~3.6 m) remained isolated. At ~2400 14C BP, RSL stood at 1.49 ± 0.34 m above present MTL. Falling RSLs in the late Holocene led to the final emergence of the Woods Lake basin by 1604 ± 36 14C BP. Model predictions generated using the ICE-5G model partnered with a small number of different Earth viscosity models generally show poor agreement with the observational data, indicating that the ice model and/or Earth models considered can be improved upon. The best data-model fits were achieved with relatively low values of upper mantle viscosity (5 × 1019 Pa s), which is consistent with previous modelling results from the region. The RSL data align more closely with observational records from the southeast of the region (eastern Vancouver Island, central Strait of Georgia), than the immediate north (Bella Bella–Bella Coola and Prince Rupert-Kitimat) and areas to the north-west (Queen Charlotte Sound, Hecate Strait), underlining the complexity of the regional response to glacio-isostatic recovery.

40-70 GHz 13 Gbps 1-dB loss SPST and SPDT differential switches in 0.35 μm SiGe technology

This paper presents the design and characterization of ultrafast wideband low-loss single-pole single-throw (SPST) and single-pole double-throw (SPDT) differential switches. The SPDT switch exhibits insertion loss of lower than 1.25 dB from 42 to 70 GHz and isolation of better than 20 dB from 40 to 65 GHz. Similar low-loss and broadband characteristics are also observed from the measured SPST switch. The proposed switch topologies adopting current-steering technique and implemented in 0.35 µm SiGe bipolar technology result in a switching time of only 75 ps. This suggests a maximum switching speed of 13 Gbps, the fastest ever reported at V-band.

The application of metabolomic biomarker screening tools for improved Bovine Respiratory Disease diagnosis and management

Bovine Respiratory Disease (BRD) is considered to be one of the most significant causes of economic loss in cattle worldwide. The disease has multifactorial aetiology, where viral induced respiratory damage can predispose animals to developing secondary bacterial infections. Accurate identification of viral infected animals prior to the onset of bacterial infection is necessary to reduce the overuse of antimicrobial treatments and minimize further economic losses from reduced production capacity and death. This research focuses on Bovine Parainfluenza Virus Type 3 (BPIV-3), one of the viruses involved in generating BRD. Vaccination measures for BPIV-3 can induce a level of immunity preventing disease progression, however, not all animals respond equally and immunization can complicate disease diagnosis. Alternative diagnostic approaches are required to identify animals which fail to respond to vaccination during infection outbreaks and are therefore likely to be more susceptible to secondary bacterial infections. Mass spectrometry based metabolomics was employed to identify plasma markers capable of differentiating between vaccinated and non-vaccinated calves after challenge with BPIV-3. Differentiation of vaccinated and non-vaccinated study groups (n=6) was possible as early as day 2 post-BPIV-3 challenge up until day 20 using a panel of potential metabolite markers. This study illustrates the potential for metabolomics to provide more detailed information on animal vaccination status that could be used to develop tools for improved herd health management, reduce economic loss through rapid identification and isolation of animals without immune protection (improving herd level immunity) and help reduce the usage of antimicrobial therapeutic treatments in animals.

Bearing Witness to the 'Pain of Others': Researching Power, Violence and Resistance in a Women's Prison

Addressing the dynamics of interpersonal violence, institutionalised abuses and prisoner isolation, this article consolidates critical analyses as challenges to the essentially liberal constructions and interpretations of prisoner agency and penal reformism. Grounded in long-term research with women in prison in the North of Ireland, it connects embedded, punitive responses that undermine women prisoners’ self-esteem and mental health to the brutalising manifestations of formal and informal punishments, including lockdowns and isolation. It argues that critical social research into penal policy and prison regimes has a moral duty, an ethical obligation and a political responsibility to investigate abuses of power, seek out the ‘view from below’. Challenging the revisionism implicit within the ‘healthy prison’ discourse, it argues for alternatives to prison as the foundation of decarceration and abolition.

Speaking Out Online:The Benefits and Risks of Speaking About Sexual Violence for Young People

Speaking out about sexual violence has been a fundamental part of feminist politics since the 1970s. The practice of narrating experiences of violence, either publicly or to friends and family aims to combat the culture of silence and stigmatisation that surrounds sexual violence while also helping individuals to gain a sense of empowerment and connect with other survivors. However, speaking out also contains inherent risks, especially for young people. Survivors may meet with stigmatising or disbelieving responses, and they may lose control over who knows their story and the way in which it is told and retold.
These risks and benefits are altered, and potentially exacerbated, in an online environment. While social media may increase survivors’ ability to contact and connect with others with similar experiences it also makes it harder to control when and how their story is shared. The disjuncture between online and offline environments may also increase feelings of stigmatisation and isolation.
There is a need to explore the specific risks and benefits of speaking out online given both young people’s extensive use of social media for social interactions and the increasing tendency for support and educational services targeted at young people to make use of social media and online environments. This paper draws on literature and some preliminary research to consider both risks and benefits of speaking out online and to open a conversation about the creation of supportive spaces and mechanisms for young people to speak about sexual violence in online environments.

Fault Diagnosis in Internal Combustion Engines Using Nonlinear Multivariate Statistics

This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce nonlinear relationships between the recorded engine variables, the paper proposes the use of nonlinear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new nonlinear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady-state operating conditions. More precisely, nonlinear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (i) an enhanced identification of potential root causes of abnormal events and (ii) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, whilst the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 Litre diesel engine mounted on an experimental engine test bench facility.

2,4-dinitrophenol as an activating reagent in a facile preparation of cyclic phosphate trimesters

Abstract 2,4-Dinitrophenol was employed with benzyloxy-bis-(diisopropylamino)phosphine to synthesise the cyclic phosphate derivatives of a series of alkane diols (HO–(CH2)n–OH, n=2–6) in good isolated yields. Tetrazole and DNP were compared by 31P NMR spectroscopy for their ability to catalyse the cyclisation at the P(III) stage. Investigation of the phosphate triester stability under various oxidation and chromatographic conditions resulted in the optimisation of the isolation procedures of the chemically unstable cyclic compounds. Conditions for debenzylation were developed to yield the corresponding cyclic phosphodiesters quantitatively. The methodology was further applied to the preparation and isolation of the cyclic phosphate derivative of a carbohydrate.

Conventional free radical polymerization in room temperature ionic liquids: a green approach to commodity polymers with practical advantages

Free-radical polymerization of methyl methacrylate and styrene using conventional organic initiators in the room temperature ionic liquid, 1-butyl-3-methylimidazolium hexafluorophosphate ([ C(4)mim][PF6]) is rapid and produces polymers with molecular weights up to 10x higher than from benzene; both polymerization and isolation of products were achieved without using VOCs, offering economic as well as environmental advantages.

Improved Process Monitoring Using Nonlinear Principal Component Models

This paper presents two new approaches for use in complete process monitoring. The firstconcerns the identification of nonlinear principal component models. This involves the application of linear
principal component analysis (PCA), prior to the identification of a modified autoassociative neural network (AAN) as the required nonlinear PCA (NLPCA) model. The benefits are that (i) the number of the reduced set of linear principal components (PCs) is smaller than the number of recorded process variables, and (ii) the set of PCs is better conditioned as redundant information is removed. The result is a new set of input data for a modified neural representation, referred to as a T2T network. The T2T NLPCA model is then used for complete process monitoring, involving fault detection, identification and isolation. The second approach introduces a new variable reconstruction algorithm, developed from the T2T NLPCA model. Variable reconstruction can enhance the findings of the contribution charts still widely used in industry by reconstructing the outputs from faulty sensors to produce more accurate fault isolation. These ideas are illustrated using recorded industrial data relating to developing cracks in an industrial glass melter process. A comparison of linear and nonlinear models, together with the combined use of contribution charts and variable reconstruction, is presented.