Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions

Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.

A Near-Infrared Reflectance Spectroscopy Method for Direct Analysis of Several Chemical Components and Properties of Fruit, for Example, Chinese Hawthorn

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.

Inelastic finite element analysis of composite beams on the basis of the plastic hinge approach

This paper emphasizes material nonlinear effects on composite beams with recourse to the plastic hinge method. Numerous combinations of steel and concrete sections form arbitrary composite sections. Secondly, the material properties of composite beams vary remarkably across its section from ductile steel to brittle concrete. Thirdly, concrete is weak in tension, so composite section changes are dependent on load distribution. To this end, the plastic zone approach is convenient for inelastic analysis of composite sections that can evaluate member resistance, including material nonlinearities, by routine numerical integration with respect to every fiber across the composite section. As a result, many researchers usually adopt the plastic zone approach for numerical inelastic analyses of composite structures. On the other hand, the plastic hinge method describes nonlinear material behaviour of an overall composite section integrally. Consequently, proper section properties for use in plastic hinge spring stiffness are required to represent the material behaviour across the arbitrary whole composite section. In view of numerical efficiency and convergence, the plastic hinge method is superior to the plastic zone method. Therefore, based on the plastic hinge approach, how to incorporate the material nonlinearities of the arbitrary composite section into the plastic hinge stiffness formulation becomes a prime objective of the present paper. The partial shear connection in this paper is by virtue of the effective flexural rigidity as AISC 1993 [American Institute of Steel Construction (AISC). Load and resistance factor design specifications. 2nd ed., Chicago; 1993]. Nonlinear behaviour of different kinds of composite beam is investigated in this paper, including two simply supported composite beams, a cantilever and a two span continuous composite beam.

The optimal duration and delay of first aid treatment for deep partial thickness burn injuries

Using our porcine model of deep dermal partial thickness burn injury, various durations (10min, 20min, 30min or 1h) and delays (immediate, 10min, 1h, 3h) of 15 degrees C running water first aid were applied to burns and compared to untreated controls. The subdermal temperatures were monitored during the treatment and wounds observed weekly for 6 weeks, for re-epithelialisation, wound surface area and cosmetic appearance. At 6 weeks after the burn, tissue biopsies were taken of the scar for histological analysis. Results showed that immediate application of cold running water for 20min duration is associated with an improvement in re-epithelialisation over the first 2 weeks post-burn and decreased scar tissue at 6 weeks. First aid application of cold water for as little as 10min duration or up to 1h delay still provides benefit.

A porcine deep dermal partial thickness burn model with hypertrophic scarring

We developed a reproducible model of deep dermal partial thickness burn injury in juvenile Large White pigs. The contact burn is created using water at 92 degrees C for 15s in a bottle with the bottom replaced with plastic wrap. The depth of injury was determined by a histopathologist who examined tissue sections 2 and 6 days after injury in a blinded manner. Upon creation, the circular wound area developed white eschar and a hyperaemic zone around the wound border. Animals were kept for 6 weeks or 99 days to examine the wound healing process. The wounds took between 3 and 5 weeks for complete re-epithelialisation. Most wounds developed contracted, purple, hypertrophic scars. On measurement, the thickness of the burned skin was approximately 1.8 times that of the control skin at week 6 and approximately 2.2 times thicker than control skin at 99 days after injury. We have developed various methods to assess healing wounds, including digital photographic analysis, depth of organising granulation tissue, immunohistochemistry, electron microscopy and tensiometry. Immunohistochemistry and electron microscopy showed that our porcine hypertrophic scar appears similar to human hypertrophic scarring. The development of this model allows us to test and compare different treatments on burn wounds.

Burn healing is dependent on burn site : a quantitative analysis from a porcine burn model

This retrospective review examines healing in different sites on a porcine burn model; 24 pairs of burns on 18 pigs from other animal trials were selected for analysis. Each pair of burns was located on the either the cranial or the caudal part of the thoracic ribs region, on the same side of the animal. The burns were 40-50 cm(2) in size and of uniform deep-dermal partial thickness. Caudal burns healed significantly better than cranial burns, demonstrated by earlier closure of wounds, less scar formation and better cosmesis. To our knowledge, this is the first detailed study reporting that burn healing is affected by location on a porcine burn model. We recommend that similar symmetrical burns should be used for future comparative assessments of burn healing.

Laser-to-radar sensing redundancy for resilient perception in adverse environmental conditions

This paper presents an approach to promote the integrity of perception systems for outdoor unmanned ground vehicles (UGV) operating in challenging environmental conditions (presence of dust or smoke). The proposed technique automatically evaluates the consistency of the data provided by two sensing modalities: a 2D laser range finder and a millimetre-wave radar, allowing for perceptual failure mitigation. Experimental results, obtained with a UGV operating in rural environments, and an error analysis validate the approach.

Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model

Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

STEM education for sustainable development : a sociotechnical analysis

It is debated that for sustainable STEM education and knowledge investment, human centered learning design approach is critical and important. Sustainability in this context is enduring maintenance of technological trajectories for productive economical and social interactions by demonstrating life critical scenarios through life critical system development and life experiences. Technology influences way of life and the learning and teaching process. Social software application development is more than learning of how to program a software application and extracting information from the Internet. Hence, our research challenge is, how do we attract learners to STEM social software application development? Our realisation processes begin with comparing Science and Technology education in developed (e.g., Australia) and developing (e.g., Sri Lanka) countries with distinction on final year undergraduates’ industry ready training programmes. Principal components analysis was performed to separate patterns of important factors. To measure behavioural intention of perceived usefulness and attitudes of the training, the measurement model was analysed to test its validity and reliability using partial least square (PLS) analysis of structural equation modelling (SEM). Our observation is that the relationship is more complex than we argue for. Our initial conclusions were that life critical system development and life experience trajectories as determinant factors while technological influences were unavoidable. A further investigation should involve correlations between human centered learning design approach and economical development in the long run.

Heat transfer analysis of viscous incompressible fluid by combined natural convection and radiation in an open cavity

The effect of radiation on natural convection of Newtonian fluid contained in an open cavity is investigated in this study. The governing partial differential equations are solved numerically using the Alternate Direct Implicit method together with the Successive Over Relaxation method. The study is focused on studying the flow pattern and the convective and radiative heat transfer rates are studied for different values of radiation parameters namely, the optical thickness of the fluid, scattering albedo, and the Planck number. It was found that in the optically thin limit, an increase in the optical thickness of the fluid raises the temperature and radiation heat transfer of the fluid. However, a further increase in the optical thickness decreases the radiative heat transfer rate due to increase in the energy level of the fluid, which ultimately reduces the total heat transfer rate within the fluid.

The use of phospholipid fatty acid analysis to measure impact of acid rock drainage on microbial communities in sediments

The impact of acid rock drainage (ARD) and eutrophication on microbial communities in stream sediments above and below an abandoned mine site in the Adelaide Hills, South Australia, was quantified by PLFA analysis. Multivariate analysis of water quality parameters, including anions, soluble heavy metals, pH, and conductivity, as well as total extractable metal concentrations in sediments, produced clustering of sample sites into three distinct groups. These groups corresponded with levels of nutrient enrichment and/or concentration of pollutants associated with ARD. Total PLFA concentration, which is indicative of microbial biomass, was reduced by >70% at sites along the stream between the mine site and as far as 18 km downstream. Further downstream, however, recovery of the microbial abundance was apparent, possibly reflecting dilution effect by downstream tributaries. Total PLFA was >40% higher at, and immediately below, the mine site (0-0.1 km), compared with sites further downstream (2.5-18 km), even after accounting for differences in specific surface area of different sediment samples. The increased microbial population in the proximity of the mine source may be associated with the presence of a thriving iron-oxidizing bacteria community as a consequence of optimal conditions for these organisms while the lower microbial population further downstream corresponded with greater sediments' metal concentrations. PCA of relative abundance revealed a number of PLFAs which were most influential in discriminating between ARD-polluted sites and the rest of the sites. These PLFA included the hydroxy fatty acids: 2OH12:0, 3OH12:0, 2OH16:0; the fungal marker: 18:2ω6; the sulfate-reducing bacteria marker 10Me16:1ω7; and the saturated fatty acids 12:0, 16:0, 18:0. Partial constrained ordination revealed that the environmental parameters with the greatest bearing on the PLFA profiles included pH, soluble aluminum, total extractable iron, and zinc. The study demonstrated the successful application of PLFA analysis to rapidly assess the toxicity of ARD-affected waters and sediments and to differentiate this response from the effects of other pollutants, such as increased nutrients and salinity.

Aligning off-balance sheet risk, on-balance sheet risk and audit fees: a PLS path modelling analysis

This study focuses on using the partial least squares (PLS) path modelling technique in archival auditing research by replicating the data and research questions from prior bank audit fee studies. PLS path modelling allows for inter-correlations among audit fee determinants by establishing latent constructs and multiple relationship paths in one simultaneous PLS path model. Endogeneity concerns about auditor choice can also be addressed with PLS path modelling. With a sample of US bank holding companies for the period 2003-2009, we examine the associations among on-balance sheet financial risks, off-balance sheet risks and audit fees, and also address the pervasive client size effect, and the effect of the self-selection of auditors. The results endorse the dominating effect of size on audit fees, both directly and indirectly via its impacts on other audit fee determinants. By simultaneously considering the self-selection of auditors, we still find audit fee premiums on Big N auditors, which is the second important factor on audit fee determination. On-balance-sheet financial risk measures in terms of capital adequacy, loan composition, earnings and asset quality performance have positive impacts on audit fees. After allowing for the positive influence of on-balance sheet financial risks and entity size on off-balance sheet risk, the off-balance sheet risk measure, SECRISK, is still positively associated with bank audit fees, both before and after the onset of the financial crisis. The consistent results from this study compared with prior literature provide supporting evidence and enhance confidence on the application of this new research technique in archival accounting studies.

Aligning off-balance sheet risk, on-balance sheet risk and audit fees: a PLS path modelling analysis

This study focuses on using the partial least squares (PLS) path modelling methodology in archival auditing research by replicating the data and research questions from prior bank audit fee studies. PLS path modelling allows for inter-correlations among audit fee determinants by establishing latent constructs and multiple relationship paths in one simultaneous PLS path model. Endogeneity concerns about auditor choice can also be addressed with PLS path modelling. With a sample of US bank holding companies for the period 2003-2009, we examine the associations among on-balance sheet financial risks, off-balance sheet risks and audit fees, and also address the pervasive client size effect, and the effect of the self-selection of auditors. The results endorse the dominating effect of size on audit fees, both directly and indirectly via its impacts on other audit fee determinants. By simultaneously considering the self-selection of auditors, we still find audit fee premiums on Big N auditors, which is the second important factor on audit fee determination. On-balance-sheet financial risk measures in terms of capital adequacy, loan composition, earnings and asset quality performance have positive impacts on audit fees. After allowing for the positive influence of on-balance sheet financial risks and entity size on off-balance sheet risk, the off-balance sheet risk measure, SECRISK, is still positively associated with bank audit fees, both before and after the onset of the financial crisis. The consistent results from this study compared with prior literature provide supporting evidence and enhance confidence on the application of this new research technique in archival accounting studies.

Genome-wide analysis in a murine Dnmt1 knockdown model identifies epigenetically silenced genes in primary human pituitary tumors

DNA methylation at promoter CpG islands (CGI) is an epigenetic modification associated with inappropriate gene silencing in multiple tumor types. In the absence of a human pituitary tumor cell line, small interfering RNA-mediated knockdown of the maintenance methyltransferase DNA methyltransferase (cytosine 5)-1 (Dnmt1) was used in the murine pituitary adenoma cell line AtT-20. Sustained knockdown induced reexpression of the fully methylated and normally imprinted gene neuronatin (Nnat) in a time-dependent manner. Combined bisulfite restriction analysis (COBRA) revealed that reexpression of Nnat was associated with partial CGI demethylation, which was also observed at the H19 differentially methylated region. Subsequent genome-wide microarray analysis identified 91 genes that were significantly differentially expressed in Dnmt1 knockdown cells (10% false discovery rate). The analysis showed that genes associated with the induction of apoptosis, signal transduction, and developmental processes were significantly overrepresented in this list (P < 0.05). Following validation by reverse transcription-PCR and detection of inappropriate CGI methylation by COBRA, four genes (ICAM1, NNAT, RUNX1, and S100A10) were analyzed in primary human pituitary tumors, each displaying significantly reduced mRNA levels relative to normal pituitary (P < 0.05). For two of these genes, NNAT and S100A10, decreased expression was associated with increased promoter CGI methylation. Induced expression of Nnat in stable transfected AtT-20 cells inhibited cell proliferation. To our knowledge, this is the first report of array-based "epigenetic unmasking" in combination with Dnmt1 knockdown and reveals the potential of this strategy toward identifying genes silenced by epigenetic mechanisms across species boundaries.

Molecular analysis of the acinetobacter baumannii biofilm-associated protein

Acinetobacter baumannii is a multidrug-resistant pathogen associated with hospital outbreaks of infection across the globe, particularly in the intensive care unit. The ability of A. baumannii to survive in the hospital environment for long periods is linked to antibiotic resistance and its capacity to form biofilms. Here we studied the prevalence, expression, and function of the A. baumannii biofilm-associated protein (Bap) in 24 carbapenem-resistant A. baumannii ST92 strains isolated from a single institution over a 10-year period. The bap gene was highly prevalent, with 22/24 strains being positive for bap by PCR. Partial sequencing of bap was performed on the index case strain MS1968 and revealed it to be a large and highly repetitive gene approximately 16 kb in size. Phylogenetic analysis employing a 1,948-amino-acid region corresponding to the C terminus of Bap showed that BapMS1968 clusters with Bap sequences from clonal complex 2 (CC2) strains ACICU, TCDC-AB0715, and 1656-2 and is distinct from Bap in CC1 strains. By using overlapping PCR, the bapMS1968 gene was cloned, and its expression in a recombinant Escherichia coli strain resulted in increased biofilm formation. A Bap-specific antibody was generated, and Western blot analysis showed that the majority of A. baumannii strains expressed an ∼200-kDa Bap protein. Further analysis of three Bap-positive A. baumannii strains demonstrated that Bap is expressed at the cell surface and is associated with biofilm formation. Finally, biofilm formation by these Bap-positive strains could be inhibited by affinity-purified Bap antibodies, demonstrating the direct contribution of Bap to biofilm growth by A. baumannii clinical isolates.