Characterization of acyl chain position in unsaturated phosphatidylcholines using differential mobility-mass spectrometry

Glycerophospholipids (GPs) that differ in the relative position of the two fatty acyl chains on the glycerol backbone (i.e., sn-positional isomers) can have distinct physicochemical properties. The unambiguous assignment of acyl chain position to an individual GP represents a significant analytical challenge. Here we describe a workflow where phosphatidylcholines (PCs) are subjected to ESI for characterization by a combination of differential mobility spectrometry and MS (DMS-MS). When infused as a mixture, ions formed from silver adduction of each phospholipid isomer {e.g., [PC (16:0/18:1) + Ag]+ and [PC (18:1/16:0) + Ag]+} are transmitted through the DMS device at discrete compensation voltages. Varying their relative amounts allows facile and unambiguous assignment of the sn-positions of the fatty acyl chains for each isomer. Integration of the well-resolved ion populations provides a rapid method (< 3 min) for relative quantification of these lipid isomers. The DMS-MS results show excellent agreement with established, but time-consuming, enzymatic approaches and also provide superior accuracy to methods that rely on MS alone. The advantages of this DMS-MS method in identification and quantification of GP isomer populations is demonstrated by direct analysis of complex biological extracts without any prior fractionation.

Studies of Brisbane municipal water quality using Inductively Coupled Plasma - Mass Spectrometry and Chemometrics

This research established innovative methods and a predictive model to evaluate water quality using the trace element and heavy metal concentrations of drinking water from the greater Brisbane area. Significantly, the combined use of Inductively Coupled Plasma - Mass Spectrometry and Chemometrics can be used worldwide to provide comprehensive, rapid and affordable analyses of elements in drinking water that can have a considerable impact on human health.

A high performance liquid chromatography and electrospray ionization mass spectrometry method for the analysis of the natural medicine, Forsythia suspensa

Samples of Forsythia suspensa from raw (Laoqiao) and ripe (Qingqiao) fruit were analyzed with the use of HPLC-DAD and the EIS-MS techniques. Seventeen peaks were detected, and of these, twelve were identified. Most were related to the glucopyranoside molecular fragment. Samples collected from three geographical areas (Shanxi, Henan and Shandong Provinces), were discriminated with the use of hierarchical clustering analysis (HCA), discriminant analysis (DA), and principal component analysis (PCA) models, but only PCA was able to provide further information about the relationships between objects and loadings; eight peaks were related to the provinces of sample origin. The supervised classification models-K-nearest neighbor (KNN), least squares support vector machines (LS-SVM), and counter propagation artificial neural network (CP-ANN) methods, indicated successful classification but KNN produced 100% classification rate. Thus, the fruit were discriminated on the basis of their places of origin.

Quantitative characterization of kaolinite dispersibility in styrene–butadiene rubber composites by fractal dimension

A fractal method was introduced to quantitatively characterize the dispersibility of modified kaolinite (MK) and precipitated silica (PS) in styrene–butadiene rubber (SBR) matrix based on the lower magnification transmission electron microscopic images. The fractal dimension (FD) is greater, and the dispersion is worse. The fractal results showed that the dispersibility of MK in the latex blending sample is better than that in the mill blending samples. With the increase of kaolinite content, the FD increases from 1.713 to 1.800, and the dispersibility of kaolinite gradually decreases. There is a negative correlation between the dispersibility and loading content. With the decrease of MK and increase of PS, the FD significantly decreases from 1.735 to 1.496 and the dipersibility of kaolinite remarkably increases. The hybridization can improve the dispersibility of fillers in polymer matrix. The FD can be used to quantitatively characterize the aggregation and dispersion of kaolinite sheets in rubber matrix.

Prospective ten-month exercise intervention in premenarcheal girls: Positive effects on bone and lean mass

Enhancement of bone mineral acquisition during growth may be a useful preventive strategy against osteoporosis. The aim of this study was to explore the lean mass, strength, and bone mineral response to a 10-month, high-impact, strength-building exercise program in 71 premenarcheal girls, aged 9–10 years. Lean body mass, total body (TB), lumbar spine (LS), proximal femur (PF), and femoral neck (FN) bone mineral were measured using the Hologic QDR 2000+ bone densitometer. Strength was assessed using a grip dynamometer and the Cybex isokinetic dynamometer (Cybex II). At baseline, no significant difference in body composition, pubertal development, calcium intake, physical activity, strength, or bone mineral existed between groups. At completion, there were again no differences in height, total body mass, pubertal development, calcium intake, or external physical activity. In contrast, the exercise group gained significantly more lean mass, less body fat content, greater shoulder, knee and grip strength, and greater TB, LS, PF, and FN BMD (exercise: TB 3.5%, LS 4.8%, PF 4.5%, and FN 12.0%) compared with the controls (controls: TB 1.2%, LS 1.2%, PF 1.3%, and FN 1.7%). TB bone mineral content (BMC), LS BMC, PF BMC, FN BMC, LS bone mineral apparent density (BMAD), and FN bone area also increased at a significantly greater rate in the exercise group compared with the controls. In multiple regression analysis, change in lean mass was the primary determinant of TB, FN, PF, and LS BMD accrual. Although a large proportion of bone mineral accrual in the premenarcheal skeleton was related to growth, an osteogenic effect was associated with exercise. These results suggest that high-impact, strength building exercise is beneficial for premenarcheal strength, lean mass gains, and bone mineral acquisition.

Technological adoption and use after mass market displacement: The case of the LP record

This paper investigates the reasons why some technologies, defying general expectations and the established models of technological change, may not disappear from the market after having been displaced from their once-dominant status. Our point of departure is that the established models of technological change are not suitable to explain this as they predominantly focus on technological dominance, giving attention to the technologies that display highest performance levels and gain greatest market share. And yet, technological landscapes are rife with technological designs that do not fulfil these conditions. Using the LP record as an empirical case, we propose that the central mechanism at play in the continuing market presence of once-dominant technologies is the recasting of their technological features from the functional-utilitarian to the aesthetic realm, with an additional element concerning communal interaction among users. The findings that emerge from our quantitative textual analysis of over 200,000 posts on a prominent online LP-related discussion forum (between 2002 and 2010) also suggest that the post-dominance technology adopters and users appear to share many key characteristics with the earliest adopters of new technologies, rather than with late-stage adopters which precede them.

Speed-based diagnostics of aerodynamic and mass imbalance in large wind turbines

Any kind of imbalance in the operation of a wind turbine has adverse effect on the downstream torsional components as well as tower structure. It is crucial to detect imbalance at its very inception. The identification of the type of imbalance is also required so that appropriate measures of fault accommodation can be performed in the control system. In particular, it is important to distinguish between mass and aerodynamic imbalance. While the former is gradually caused by a structural anomaly (e.g. ice deposition, moisture accumulation inside blade), the latter is generally associated to a fault in the pitch control system. This paper proposes a technique for the detection and identification of imbalance fault in large scale wind turbines. Unlike most other existing method it requires only the rotor speed signal which is readily available in existing turbines. Signature frequencies have been proposed in this work to identify imbalance type based on their physical phenomenology. The performance of this technique has been evaluated by simulations using an existing benchmark model. The effectiveness of the proposed method has been confirmed by the simulation results.

COL1A1 C-propeptide cleavage site mutation causes high bone mass, bone fragility and jaw lesions: A new cause of gnathodiaphyseal dysplasia?

Gnathodiaphyseal dysplasia (GDD) is a rare autosomal dominant condition characterized by bone fragility, irregular bone mineral density (BMD) and fibro-osseous lesions in the skull and jaw. Mutations in Anoctamin-5 (ANO5) have been identified in some cases. We aimed to identify the causative mutation in a family with features of GDD but no mutation in ANO5, using whole exome capture and massive parallel sequencing (WES). WES of two affected individuals (a mother and son) and the mother's unaffected parents identified a mutation in the C-propeptide cleavage site of COL1A1. Similar mutations have been reported in individuals with osteogenesis imperfecta (OI) and paradoxically increased BMD. C-propeptide cleavage site mutations in COL1A1 may not only cause 'high bone mass OI', but also the clinical features of GDD, specifically irregular sclerotic BMD and fibro-osseous lesions in the skull and jaw. GDD patients negative for ANO5 mutations should be assessed for mutations in type I collagen C-propeptide cleavage sites.

Maternal pregravid body mass index and child hospital admissions in the first 5 years of life: results from an Australian birth cohort

Objectives: To examine the association of maternal pregravid body mass index (BMI) and child offspring, all-cause hospitalisations in the first 5 years of life. Methods: Prospective birth cohort study. From 2006 to 2011, 2779 pregnant women (2807 children) were enrolled in the Environments for Healthy Living: Griffith birth cohort study in South-East Queensland, Australia. Hospital delivery record and self-report baseline survey of maternal, household and demographic factors during pregnancy were linked to the Queensland Hospital Admitted Patients Data Collection from 1 November 2006 to 30 June 2012, for child admissions. Maternal pregravid BMI was classified as underweight (<18.5 kg m−2), normal weight (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2) or obese (30 kg m−2). Main outcomes were the total number of child hospital admissions and ICD-10-AM diagnostic groupings in the first 5 years of life. Negative binomial regression models were calculated, adjusting for follow-up duration, demographic and health factors. The cohort comprised 8397.9 person years (PYs) follow-up. Results: Children of mothers who were classified as obese had an increased risk of all-cause hospital admissions in the first 5 years of life than the children of mothers with a normal BMI (adjusted rate ratio (RR) =1.48, 95% confidence interval 1.10–1.98). Conditions of the nervous system, infections, metabolic conditions, perinatal conditions, injuries and respiratory conditions were excessive, in both absolute and relative terms, for children of obese mothers, with RRs ranging from 1.3–4.0 (PYs adjusted). Children of mothers who were underweight were 1.8 times more likely to sustain an injury or poisoning than children of normal-weight mothers (PYs adjusted). Conclusion: Results suggest that if the intergenerational impact of maternal obesity (and similarly issues related to underweight) could be addressed, a significant reduction in child health care use, costs and public health burden would be likely.

Fractal and multifractal properties of a family of fractal networks

In this work, we study the fractal and multifractal properties of a family of fractal networks introduced by Gallos et al (2007 Proc. Nat. Acad. Sci. USA 104 7746). In this fractal network model, there is a parameter e which is between 0 and 1, and allows for tuning the level of fractality in the network. Here we examine the multifractal behavior of these networks, the dependence relationship of the fractal dimension and the multifractal parameters on parameter e. First, we find that the empirical fractal dimensions of these networks obtained by our program coincide with the theoretical formula given by Song et al (2006 Nature Phys. 2 275). Then from the shape of the τ(q) and D(q) curves, we find the existence of multifractality in these networks. Last, we find that there exists a linear relationship between the average information dimension 〈D(1)〉 and the parameter e.

Determination of dimethyl sulfide in gas samples by single photon ionization time of flight mass spectrometry

It is difficult to determine sulfur-containing volatile organic compounds in the atmosphere because of their reactivity. Primary off-line techniques may suffer losses of analytes during the transportation from field to laboratory and sample preparation. In this study, a novel method was developed to directly measure dimethyl sulfide at parts-per-billion concentration levels in the atmosphere using vacuum ultraviolet single photon ionization time-of-flight mass spectrometry. This technique offers continuous sampling at a response rate of one measurement per second, or cumulative measurements over longer time periods. Laboratory prepared samples of different concentrations of dimethyl sulfide in pure nitrogen gas were analyzed at several sampling frequencies. Good precision was achieved using sampling periods of at least 60 seconds with a relative standard deviation of less than 25%. The detection limit for dimethyl sulfide was below the 3 ppb olfactory threshold. These results demonstrate that single photon ionization time-of-flight mass spectrometry is a valuable tool for rapid, real-time measurements of sulfur-containing organic compounds in the air.

Fractal and complex network analyses of protein molecular dynamics

Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h(q)h(q) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h(2)h(2) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H≈0.5H≈0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h(2)h(2) of MF-DFA on the time series, exponent λλ of the exponential degree distribution and fractal dimension dBdB of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈h(2)〉〈h(2)〉 (from MF-DFA on time series) and 〈dB〉〈dB〉 of the converted HVGs for different energy, pressure and volume.

Topological properties and fractal analysis of a recurrence network constructed from fractional Brownian motions

Many studies have shown that we can gain additional information on time series by investigating their accompanying complex networks. In this work, we investigate the fundamental topological and fractal properties of recurrence networks constructed from fractional Brownian motions (FBMs). First, our results indicate that the constructed recurrence networks have exponential degree distributions; the average degree exponent 〈λ〉 increases first and then decreases with the increase of Hurst index H of the associated FBMs; the relationship between H and 〈λ〉 can be represented by a cubic polynomial function. We next focus on the motif rank distribution of recurrence networks, so that we can better understand networks at the local structure level. We find the interesting superfamily phenomenon, i.e., the recurrence networks with the same motif rank pattern being grouped into two superfamilies. Last, we numerically analyze the fractal and multifractal properties of recurrence networks. We find that the average fractal dimension 〈dB〉 of recurrence networks decreases with the Hurst index H of the associated FBMs, and their dependence approximately satisfies the linear formula 〈dB〉≈2-H, which means that the fractal dimension of the associated recurrence network is close to that of the graph of the FBM. Moreover, our numerical results of multifractal analysis show that the multifractality exists in these recurrence networks, and the multifractality of these networks becomes stronger at first and then weaker when the Hurst index of the associated time series becomes larger from 0.4 to 0.95. In particular, the recurrence network with the Hurst index H=0.5 possesses the strongest multifractality. In addition, the dependence relationships of the average information dimension 〈D(1)〉 and the average correlation dimension 〈D(2)〉 on the Hurst index H can also be fitted well with linear functions. Our results strongly suggest that the recurrence network inherits the basic characteristic and the fractal nature of the associated FBM series.