Development and validation of a ultra performance LC-ESI/MS method for analysis of metabolic phenotypes of healthy men in day and night urine samples

Ultra-performance LC coupled to quadrupole TOF/MS (UPLC-QTOF/MS) in positive and negative ESI was developed and validated to analyze metabolite profiles for urine from healthy men during the day and at night. Data analysis using principal components analysis (PCA) revealed differences between metabolic phenotypes of urine in healthy men during the day and at night. Positive ions with mass-to-charge ratio (m/z) 310.24 (5.35 min), 286.24 (4.74 min) and 310.24 (5.63 min) were elevated in the urine from healthy men at night compared to that during the day. Negative ions elevated in day urine samples of healthy men included m/z 167.02 (0.66 min), 263.12 (2.55 min) and 191.03 (0.73 min), whilst ions m/z 212.01 (4.77 min) were at a lower concentration in urine of healthy men during the day compared to that at night. The ions m/z 212.01 (4.77 min), 191.03 (0.73 min) and 310.24 (5.35 min) preliminarily correspond to indoxyl sulfate, citric acid and N-acetylneuraminic acid, providing further support for an involvement of phenotypic difference in urine of healthy men in day and night samples, which may be associated with notably different activities of gut microbiota, velocity of tricarboxylic acid cycle and activity of sialic acid biosynthesis in healthy men as regulated by circadian rhythm of the mammalian bioclock.

Histogram of weighted local directions for gait recognition

In this paper, we explore the effectiveness of patch-based gradient feature extraction methods when applied to appearance-based gait recognition. Extending existing popular feature extraction methods such as HOG and LDP, we propose a novel technique which we term the Histogram of Weighted Local Directions (HWLD). These 3 methods are applied to gait recognition using the GEI feature, with classification performed using SRC. Evaluations on the CASIA and OULP datasets show significant improvements using these patch-based methods over existing implementations, with the proposed method achieving the highest recognition rate for the respective datasets. In addition, the HWLD can easily be extended to 3D, which we demonstrate using the GEV feature on the DGD dataset, observing improvements in performance.

Application of near infrared (NIR) spectroscopy for determining the thickness of articular cartilage

The determination of the characteristics of articular cartilage such as thickness, stiffness and swelling, especially in the form that can facilitate real-time decisions and diagnostics is still a matter for research and development. This paper correlates near infrared spectroscopy with mechanically measured cartilage thickness to establish a fast, non-destructive, repeatable and precise protocol for determining this tissue property. Statistical correlation was conducted between the thickness of bovine cartilage specimens (n = 97) and regions of their near infrared spectra. Nine regions were established along the full absorption spectrum of each sample and were correlated with the thickness using partial least squares (PLS) regression multivariate analysis. The coefficient of determination (R2) varied between 53 and 93%, with the most predictive region (R2 = 93.1%, p < 0.0001) for cartilage thickness lying in the region (wavenumber) 5350–8850 cm−1. Our results demonstrate that the thickness of articular cartilage can be measured spectroscopically using NIR light. This protocol is potentially beneficial to clinical practice and surgical procedures in the treatment of joint disease such as osteoarthritis.

Rapid nutrient determination of sugarcane milling by-products using near infrared spectroscopy

This thesis investigates the use of near infrared (NIR) spectroscopic methods for rapid measurement of nutrient elements in mill mud and mill ash. Adoption of NIR-based analyses for carbon, nitrogen, phosphorus, potassium and silicon will allow Australian sugarcane farmers to comply with recent legislative changes, and act within recommended precision farming frameworks. For these analyses, NIR spectroscopic methods surpass several facets of traditional wet chemistry techniques, dramatically reducing costs, required expertise and chemical exposure, while increasing throughput and access to data. Further, this technology can be applied in various modes, including laboratory, at-line and on-line installations, allowing targeted measurement.

Coexpression of epidermal growth factor receptor with related factors is associated with a poor prognosis in non-small-cell lung cancer

The epidermal growth factor receptor (EGFR) is commonly expressed in non-small-cell lung cancer (NSCLC) and promotes a host of mechanisms involved in tumorigenesis. However, EGFR expression does not reliably predict prognosis or response to EGFR-targeted therapies. The data from two previous studies of a series of 181 consecutive surgically resected stage I-IIIA NSCLC patients who had survived in excess of 60 days were explored. Of these patients, tissue was available for evaluation of EGFR in 179 patients, carbonic anhydrase (CA) IX in 177 patients and matrix metalloproteinase-9 (MMP-9) in 169 patients. We have previously reported an association between EGFR expression and MMP-9 expression. We have also reported that MMP-9 (P=0.001) and perinuclear (p)CA IX (P=0.03) but not EGFR expression were associated with a poor prognosis. Perinuclear CA IX expression was also associated with EGFR expression (P<0.001). Multivariate analysis demonstrated that coexpression of MMP-9 with EGFR conferred a worse prognosis than the expression of MMP-9 alone (P<0.001) and coexpression of EGFR and pCA IX conferred a worse prognosis than pCA IX alone (P=0.05). A model was then developed where the study population was divided into three groups: group 1 had expression of EGFR without coexpression of MMP-9 or pCA IX (number=21); group 2 had no expression of EGFR (number=75); and group 3 had coexpression of EGFR with pCA IX or MMP-9 or both (number=70). Group 3 had a worse prognosis than either groups 1 or 2 (P=0.0003 and 0.027, respectively) and group 1 had a better prognosis than group 2 (P=0.036). These data identify two cohorts of EGFR-positive patients with diametrically opposite prognoses. The group expressing either EGFR and or both MMP-9 and pCA IX may identify a group of patients with activated EGFR, which is of clinical relevance with the advent of EGFR-targeted therapies. © 2004 Cancer Research UK.

Carbonic anhydrase IX expression, a novel surrogate marker of tumor hypoxia, is associated with a poor prognosis in non-small-cell lung cancer

Purpose To evaluate carbonic anhydrase (CA) IX as a surrogate marker of hypoxia and investigate the prognostic significance of different patterns of expression in non-small-cell lung cancer (NSCLC). Methods Standard immunohistochemical techniques were used to study CA IX expression in 175 resected NSCLC tumors. CA IX expression was determined by Western blotting in A549 cell lines grown under normoxic and hypoxic conditions. Measurements from microvessels to CA IX positivity were obtained. Results CA IX immunostaining was detected in 81.8% of patients. Membranous (m) (P = .005), cytoplasmic (c) (P = .018), and stromal (P < .001) CA IX expression correlated with the extent of tumor necrosis (TN). The mean distance from vascular endothelium to the start of tumor cell positivity was 90 μm, which equates to an oxygen pressure of 5.77 mmHg. The distance to blood vessels from individual tumor cells or tumor cell clusters was greater if they expressed mCA IX than if they did not (P < .001). Hypoxic exposure of A549 cells for 16 hours enhanced CAIX expression in the nuclear and cytosolic extracts. Perinuclear (p) CA IX (P = .035) was associated with a poor prognosis. In multivariate analysis, pCA IX (P = .004), stage (P = .001), platelet count (P = .011), sex (P = .027), and TN (P = .035) were independent poor prognostic factors. Conclusion These results add weight to the contention that mCA IX is a marker of tumor cell hypoxia. The absence of CA IX staining close to microvessels suggests that these vessels are functionally active. pCA IX expression is representative of an aggressive phenotype. © 2003 by American Society of Clinical Oncology.

Past 140-year environmental record in the northern South China Sea : evidence from coral skeletal trace metal variations

About 140-year changes in the trace metals in Porites coral samples from two locations in the northern South China Sea were investigated. Results of PCA analyses suggest that near the coast, terrestrial input impacted behavior of trace metals by 28.4%, impact of Sea Surface Temperature (SST) was 19.0%, contribution of war and infrastructure were 14.4% and 15.6% respectively. But for a location in the open sea, contribution of War and SST reached 33.2% and 16.5%, while activities of infrastructure and guano exploration reached 13.2% and 14.7%. While the spatiotemporal change model of Cu, Cd and Pb in seawater of the north area of South China Sea during 1986–1997 were reconstructed. It was found that in the sea area Cu and Cd contaminations were distributed near the coast while areas around Sanya, Hainan had high Pb levels because of the well-developed tourism related activities.

PITX2 and non-canonical Wnt pathway interaction in metastatic prostate cancer

The non-canonical Wnt pathway, a regulator of cellular motility and morphology, is increasingly implicated in cancer metastasis. In a quantitative PCR array analysis of 84 Wnt pathway associated genes, both non-canonical and canonical pathways were activated in primary and metastatic tumors relative to normal prostate. Expression of the Wnt target gene PITX2 in a prostate cancer (PCa) bone metastasis was strikingly elevated over normal prostate (over 2,000-fold) and primary prostate cancer (over 200-fold). The elevation of PITX2 protein was also evident on tissue microarrays, with strong PITX2 immunostaining in PCa skeletal and, to a lesser degree, soft tissue metastases. PITX2 is associated with cell migration during normal tissue morphogenesis. In our studies, overexpression of individual PITX2A/B/C isoforms stimulated PC-3 PCa cell motility, with the PITX2A isoform imparting a specific motility advantage in the presence of non-canonical Wnt5a stimulation. Furthermore, PITX2 specific shRNA inhibited PC-3 cell migration toward bone cell derived chemoattractant. These experimental results support a pivotal role of PITX2A and non-canonical Wnt signaling in enhancement of PCa cell motility, suggest PITX2 involvement in homing of PCa to the skeleton, and are consistent with a role for PITX2 in PCa metastasis to soft and bone tissues. Our findings, which significantly expand previous evidence that PITX2 is associated with risk of PCa biochemical recurrence, indicate that variation in PITX2 expression accompanies and may promote prostate tumor progression and metastasis.

The effect of nitroxides on swarming motility and biofilms, multicellular behaviors in Pseudomonas aeruginosa

The ability of NO to induce biofilm dispersion has been well established. Here we investigated the effect of nitroxides (sterically hindered nitric oxide analogues) on biofilm formation and swarming motility in Pseudomonas aeruginosa. A transposon mutant unable to produce nitric oxide endogenously (nirS) was deficient in swarming motility relative to wild type and the complemented strain. Moreover, expression of the nirS gene was up-regulated by 9.65-fold in wild type swarming cells when compared to planktonic cells. Wild type swarming levels were substantially restored upon exogenous addition of nitroxide containing compounds, consistent with the hypothesis that NO is necessary for swarming motility. Here, we showed that nitroxides not only mimicked the dispersal activity of NO, but also prevented biofilms from forming in flow cell chambers. In addition, a nirS transposon mutant was deficient in biofilm formation relative to wild type and the complemented strain, thus implicating NO in the formation of biofilms. Intriguingly despite its stand alone action in inhibiting biofilm formation and promoting dispersal, a nitroxide partially restored the ability of a nirS mutant to form biofilms.

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.

Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. 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Paracrine interactions between LNCaP prostate cancer cells and bioengineered bone in 3D in vitro culture reflect molecular changes during bone metastasis

As microenvironmental factors such as three-dimensionality and cell–matrix interactions are increasingly being acknowledged by cancer biologists, more complex 3D in vitro models are being developed to study tumorigenesis and cancer progression. To better understand the pathophysiology of bone metastasis, we have established and validated a 3D indirect co-culture model to investigate the paracrine interactions between prostate cancer (PCa) cells and human osteoblasts. Co-culture of the human PCa, LNCaP cells embedded within polyethylene glycol hydrogels with human osteoblasts in the form of a tissue engineered bone construct (TEB), resulted in reduced proliferation of LNCaP cells. LNCaP cells in both monoculture and co-culture were responsive to the androgen analog, R1881, as indicated by an increase in the expression (mRNA and/or protein induction) of androgen-regulated genes including prostate specific antigen and fatty acid synthase. Microarray gene expression analysis further revealed an up-regulation of bone markers and other genes associated with skeletal and vasculature development and a significant activation of transforming growth factor β1 downstream genes in LNCaP cells after co-culture with TEB. LNCaP cells co-cultured with TEB also unexpectedly showed similar changes in classical androgen-responsive genes under androgen-deprived conditions not seen in LNCaP monocultures. The molecular changes of LNCaP cells after co-culturing with TEBs suggest that osteoblasts exert a paracrine effect that may promote osteomimicry and modulate the expression of androgen-responsive genes in LNCaP cells. Taken together, we have presented a novel 3D in vitro model that allows the study of cellular and molecular changes occurring in PCa cells and osteoblasts that are relevant to metastatic colonization of bone. This unique in vitro model could also facilitate cancer biologists to dissect specific biological hypotheses via extensive genomic or proteomic assessments to further our understanding of the PCa-bone crosstalk.

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.

Interleukin-6 is a potent inducer of S100P, which is up-regulated in androgen-refractory and metastatic prostate cancer

Elevated circulating interleukin-6 (IL6) and up-regulated S100P in prostate cancer (PCa) specimens correlate independently with progression to androgen-independent and metastatic PCa. The cause of up-regulated S100P levels in advanced PCa remains to be determined. We investigated the possibility that IL6 is an inducer of S100P. Determination of mRNA and protein levels by real-time PCR and Western blotting revealed that IL6 is a more potent inducer of S100P than the synthetic androgen, R1881, in the LNCaP/C4-2B model of PCa progression. IL6 did not require androgen to induce S100P in these cells, which express a functional androgen receptor (AR). Like R1881, IL6 was unable to induce S100P in PC3 cells that lack a functional AR. IL6 did not strongly induce the AR-dependent genes PSA and KLK2 and, contrary to R1881, down-regulated Cyr61/CCN1, a potential marker that is down-regulated in PCa. Epidermal growth factor (EGF), which like IL6 is a non-androgen activator of the AR, did not induce S100P. The data identifies a unique gene-induction profile for IL6 and suggests that IL6 may require a functional AR for S100P induction. A link between elevated IL6 and up-regulated S100P in androgen-refractory and metastatic PCa is postulated.

Label-free SERS for natural product provenance

Introduction Natural product provenance is important in the food, beverage and pharmaceutical industries, for consumer confidence and with health implications. Raman spectroscopy has powerful molecular fingerprint abilities. Surface Enhanced Raman Spectroscopy’s (SERS) sharp peaks allow distinction between minimally different molecules, so it should be suitable for this purpose. Methods Naturally caffeinated beverages with Guarana extract, coffee and Red Bull energy drink as a synthetic caffeinated beverage for comparison (20 µL ea.) were reacted 1:1 with Gold nanoparticles functionalised with anti-caffeine antibody (ab15221) (10 minutes), air dried and analysed in a micro-Raman instrument. The spectral data was processed using Principle Component Analysis (PCA). Results The PCA showed Guarana sourced caffeine varied significantly from synthetic caffeine (Red Bull) on component 1 (containing 76.4% of the variance in the data). See figure 1. The coffee containing beverages, and in particular Robert Timms (instant coffee) were very similar on component 1, but the barista espresso showed minor variance on component 1. Both coffee sourced caffeine samples varied with red Bull on component 2, (20% of variance). ************************************************************ Figure 1 PCA comparing a naturally caffeinated beverage containing Guarana with coffee. ************************************************************ Discussion PCA is an unsupervised multivariate statistical method that determines patterns within data. Figure 1 shows Caffeine in Guarana is notably different to synthetic caffeine. Other researchers have revealed that caffeine in Guarana plants is complexed with tannins. Naturally sourced/ lightly processed caffeine (Monster Energy, Espresso) are more inherently different than synthetic (Red Bull) /highly processed (Robert Timms) caffeine, in figure 1, which is consistent with this finding and demonstrates this technique’s applicability. Guarana provenance is important because it is still largely hand produced and its demand is escalating with recognition of its benefits. This could be a powerful technique for Guarana provenance, and may extend to other industries where provenance / authentication are required, e.g. the wine or natural pharmaceuticals industries.