Load-unloading response of intact and artificially degraded articular cartilage correlated with near infrared (NIR) absorption spectra

The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been demonstrated to be limited in their capacity to distinguish intact (visually normal) from degraded cartilage samples. In this paper, we explore the correlation between a new mechanical parameter, namely the reswelling of articular cartilage following unloading from a given compressive load, and the near infrared (NIR) spectrum. The capacity to distinguish mechanically intact from proteoglycan-depleted tissue relative to the "reswelling" characteristic was first established, and the result was subsequently correlated with the NIR spectral data of the respective tissue samples. To achieve this, normal intact and enzymatically degraded samples were subjected to both NIR probing and mechanical compression based on a load-unload-reswelling protocol. The parameter δ(r), characteristic of the osmotic "reswelling" of the matrix after unloading to a constant small load in the order of the osmotic pressure of cartilage, was obtained for the different sample types. Multivariate statistics was employed to determine the degree of correlation between δ(r) and the NIR absorption spectrum of relevant specimens using Partial Least Squared (PLS) regression. The results show a strong relationship (R(2)=95.89%, p<0.0001) between the spectral data and δ(r). This correlation of δ(r) with NIR spectral data suggests the potential for determining the reswelling characteristics non-destructively. It was also observed that δ(r) values bear a significant relationship with the cartilage matrix integrity, indicated by its proteoglycan content, and can therefore differentiate between normal and artificially degraded proteoglycan-depleted cartilage samples. It is therefore argued that the reswelling of cartilage, which is both biochemical (osmotic) and mechanical (hydrostatic pressure) in origin, could be a strong candidate for characterizing the tissue, especially in regions surrounding focal cartilage defects in joints.

Risky driving behavior among university students and staff in the Sultanate of Oman

Background: There is a well developed literature on research investigating the relationship between various driving behaviours and road crash involvement. However, this research has predominantly been conducted in developed economies dominated by western types of cultural environments. To date no research has been published that has empirically investigated this relationship within the context of the emerging economies such as Oman. Objective: The present study aims to investigate driving behaviour as indexed in the Driving Behaviour Questionnaire (DBQ) among a group of Omani university students and staff. Methods: A convenience non-probability self- selection sampling approach was utilized with Omani university students and staff. Results: A total of 1003 Omani students (n= 632) and staff (n=371) participated in the survey. Factor analysis of the BDQ revealed four main factors that were errors, speeding violation, lapses and aggressive violation. In the multivariate logistic backward regression analysis, the following factors were identified as significant predictors of being involved in causing at least one crash: driving experience, history of offences and two DBQ components i.e. errors and aggressive violation. Conclusion: This study indicates that errors and aggressive violation of the traffic regulations as well as history of having traffic offences are major risk factors for road traffic crashes among the sample. While previous international research has demonstrated that speeding is a primary cause of crashing, in the current context, the results indicate that an array of factors is associated with crashes. Further research using more rigorous methodology is warranted to inform the development of road safety countermeasures in Oman that improves overall traffic safety culture.

Predicting vitamin D deficiency in older Australian adults

OBJECTIVE There has been a dramatic increase in vitamin D testing in Australia in recent years, prompting calls for targeted testing. We sought to develop a model to identify people most at risk of vitamin D deficiency. DESIGN AND PARTICIPANTS This is a cross-sectional study of 644 60- to 84-year-old participants, 95% of whom were Caucasian, who took part in a pilot randomized controlled trial of vitamin D supplementation. MEASUREMENTS Baseline 25(OH)D was measured using the Diasorin Liaison platform. Vitamin D insufficiency and deficiency were defined using 50 and 25 nmol/l as cut-points, respectively. A questionnaire was used to obtain information on demographic characteristics and lifestyle factors. We used multivariate logistic regression to predict low vitamin D and calculated the net benefit of using the model compared with 'test-all' and 'test-none' strategies. RESULTS The mean serum 25(OH)D was 42 (SD 14) nmol/1. Seventy-five per cent of participants were vitamin D insufficient and 10% deficient. Serum 25(OH)D was positively correlated with time outdoors, physical activity, vitamin D intake and ambient UVR, and inversely correlated with age, BMI and poor self-reported health status. These predictors explained approximately 21% of the variance in serum 25(OH)D. The area under the ROC curve predicting vitamin D deficiency was 0·82. Net benefit for the prediction model was higher than that for the 'test-all' strategy at all probability thresholds and higher than the 'test-none' strategy for probabilities up to 60%. CONCLUSION Our model could predict vitamin D deficiency with reasonable accuracy, but it needs to be validated in other populations before being implemented.

Speaker diarization : "who spoke when"

Speaker diarization is the process of annotating an input audio with information that attributes temporal regions of the audio signal to their respective sources, which may include both speech and non-speech events. For speech regions, the diarization system also specifies the locations of speaker boundaries and assign relative speaker labels to each homogeneous segment of speech. In short, speaker diarization systems effectively answer the question of ‘who spoke when’. There are several important applications for speaker diarization technology, such as facilitating speaker indexing systems to allow users to directly access the relevant segments of interest within a given audio, and assisting with other downstream processes such as summarizing and parsing. When combined with automatic speech recognition (ASR) systems, the metadata extracted from a speaker diarization system can provide complementary information for ASR transcripts including the location of speaker turns and relative speaker segment labels, making the transcripts more readable. Speaker diarization output can also be used to localize the instances of specific speakers to pool data for model adaptation, which in turn boosts transcription accuracies. Speaker diarization therefore plays an important role as a preliminary step in automatic transcription of audio data. The aim of this work is to improve the usefulness and practicality of speaker diarization technology, through the reduction of diarization error rates. In particular, this research is focused on the segmentation and clustering stages within a diarization system. Although particular emphasis is placed on the broadcast news audio domain and systems developed throughout this work are also trained and tested on broadcast news data, the techniques proposed in this dissertation are also applicable to other domains including telephone conversations and meetings audio. Three main research themes were pursued: heuristic rules for speaker segmentation, modelling uncertainty in speaker model estimates, and modelling uncertainty in eigenvoice speaker modelling. The use of heuristic approaches for the speaker segmentation task was first investigated, with emphasis placed on minimizing missed boundary detections. A set of heuristic rules was proposed, to govern the detection and heuristic selection of candidate speaker segment boundaries. A second pass, using the same heuristic algorithm with a smaller window, was also proposed with the aim of improving detection of boundaries around short speaker segments. Compared to single threshold based methods, the proposed heuristic approach was shown to provide improved segmentation performance, leading to a reduction in the overall diarization error rate. Methods to model the uncertainty in speaker model estimates were developed, to address the difficulties associated with making segmentation and clustering decisions with limited data in the speaker segments. The Bayes factor, derived specifically for multivariate Gaussian speaker modelling, was introduced to account for the uncertainty of the speaker model estimates. The use of the Bayes factor also enabled the incorporation of prior information regarding the audio to aid segmentation and clustering decisions. The idea of modelling uncertainty in speaker model estimates was also extended to the eigenvoice speaker modelling framework for the speaker clustering task. Building on the application of Bayesian approaches to the speaker diarization problem, the proposed approach takes into account the uncertainty associated with the explicit estimation of the speaker factors. The proposed decision criteria, based on Bayesian theory, was shown to generally outperform their non- Bayesian counterparts.

The distribution of construction project bids

This paper describes an analysis of construction project bids to determine (a) the global distribution and (b) factors influencing the distribution of bids. The global distribution of bids was found, by using a battery of ll test statistics, to be approximated by a three-parameter log normal distribution. No global spread parameter was found. A multivariate analysis revealed the year of tender to be the major influencing factor. Consideration of the construction order, tender price and output indices lead to the conclusion that distributional spread reflected the degree of difference in pricing policies between bidders and the skewness of the distributions reflected the degree of competition. The paper concludes with a tentative model of the causal relationships between the factors and distributional characteristics involved.

Influence of fatty acid structure on fuel properties of algae derived biodiesel

Physical and chemical properties of biofuel are influenced by structural features of fatty acid such as chain length, degree of unsaturation and branching of the chain. A simple and reliable calculation method to estimate fuel property is therefore needed to avoid experimental testing which is difficult, costly and time consuming. Typically in commercial biodiesel production such testing is done for every batch of fuel produced. In this study 9 different algae species were selected that were likely to be suitable for subtropical climates. The fatty acid methyl esters (FAMEs) of all algae species were analysed and the fuel properties like cetane number (CN), cold filter plugging point (CFPP), kinematic viscosity (KV), density and higher heating value (HHV) were determined. The relation of each fatty acid with particular fuel property is analysed using multivariate and multi-criteria decision method (MCDM) software. They showed that some fatty acids have major influences on the fuel properties whereas others have minimal influence. Based on the fuel properties and amounts of lipid content rank order is drawn by PROMETHEE-GAIA which helped to select the best algae species for biodiesel production in subtropical climates. Three species had fatty acid profiles that gave the best fuel properties although only one of these (Nannochloropsis oculata) is considered the best choice because of its higher lipid content.

Oropharyngeal dysphagia in an elderly post-operative hip fracture population : a prospective cohort study

Background: normal ageing processes impact on oropharyngeal swallowing function placing older adults at risk of developing oropharyngeal dysphagia (OD). Anecdotal clinical experience has observed that older patients recovering from hip fracture surgery commonly develop OD post-operatively. Objective: to document the presence of OD following hip fracture surgery, and the factors associated with OD. Methods: one hundred and eighty-one patients with a mean age of 83 years (range: 65–103) admitted to a specialised orthogeriatric unit were assessed for OD post-surgery for hip fracture. Pre-admission, intra-operative and post-operative factors were examined to determine their relationship with the presence of OD. Results: OD was found to be present post-operatively in 34% (n = 61) of the current population. Multivariate logistic regression analyses revealed the presence of pre-existing neurological and respiratory medical co-morbidities, presence of post-operative delirium, age and living in a residential aged care facility prior to hospital admission to be associated with the post-operative OD. Conclusion: these results highlight that OD is present in a large number of the older hip fracture population. Early identification of OD has important implications for the provision of timely dysphagia management that may prevent secondary complications and potentially reduce the hospital length of stay.

Multi-criteria ranking and source apportionment of airborne particulate matter

Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

Analysis of stream cipher based authenticated encryption schemes

Authenticated Encryption (AE) is the cryptographic process of providing simultaneous confidentiality and integrity protection to messages. This approach is more efficient than applying a two-step process of providing confidentiality for a message by encrypting the message, and in a separate pass providing integrity protection by generating a Message Authentication Code (MAC). AE using symmetric ciphers can be provided by either stream ciphers with built in authentication mechanisms or block ciphers using appropriate modes of operation. However, stream ciphers have the potential for higher performance and smaller footprint in hardware and/or software than block ciphers. This property makes stream ciphers suitable for resource constrained environments, where storage and computational power are limited. There have been several recent stream cipher proposals that claim to provide AE. These ciphers can be analysed using existing techniques that consider confidentiality or integrity separately; however currently there is no existing framework for the analysis of AE stream ciphers that analyses these two properties simultaneously. This thesis introduces a novel framework for the analysis of AE using stream cipher algorithms. This thesis analyzes the mechanisms for providing confidentiality and for providing integrity in AE algorithms using stream ciphers. There is a greater emphasis on the analysis of the integrity mechanisms, as there is little in the public literature on this, in the context of authenticated encryption. The thesis has four main contributions as follows. The first contribution is the design of a framework that can be used to classify AE stream ciphers based on three characteristics. The first classification applies Bellare and Namprempre's work on the the order in which encryption and authentication processes take place. The second classification is based on the method used for accumulating the input message (either directly or indirectly) into the into the internal states of the cipher to generate a MAC. The third classification is based on whether the sequence that is used to provide encryption and authentication is generated using a single key and initial vector, or two keys and two initial vectors. The second contribution is the application of an existing algebraic method to analyse the confidentiality algorithms of two AE stream ciphers; namely SSS and ZUC. The algebraic method is based on considering the nonlinear filter (NLF) of these ciphers as a combiner with memory. This method enables us to construct equations for the NLF that relate the (inputs, outputs and memory of the combiner) to the output keystream. We show that both of these ciphers are secure from this type of algebraic attack. We conclude that using a keydependent SBox in the NLF twice, and using two different SBoxes in the NLF of ZUC, prevents this type of algebraic attack. The third contribution is a new general matrix based model for MAC generation where the input message is injected directly into the internal state. This model describes the accumulation process when the input message is injected directly into the internal state of a nonlinear filter generator. We show that three recently proposed AE stream ciphers can be considered as instances of this model; namely SSS, NLSv2 and SOBER-128. Our model is more general than a previous investigations into direct injection. Possible forgery attacks against this model are investigated. It is shown that using a nonlinear filter in the accumulation process of the input message when either the input message or the initial states of the register is unknown prevents forgery attacks based on collisions. The last contribution is a new general matrix based model for MAC generation where the input message is injected indirectly into the internal state. This model uses the input message as a controller to accumulate a keystream sequence into an accumulation register. We show that three current AE stream ciphers can be considered as instances of this model; namely ZUC, Grain-128a and Sfinks. We establish the conditions under which the model is susceptible to forgery and side-channel attacks.

Studies of the off-field behaviours of sportspeople : are sponsors' objectives at risk?

The research reported here addresses the problem of athlete off-field behaviours as they influence sports’ sponsors, particularly the achievement of sponsorship objectives. The question arises because of incidents of sponsorship contract cancellation following news-media reporting of athletes’ off-field behaviours. Two studies are used to investigate the research question; the first establishes the content of news-media reports, and the second tests the effects of news’ reports on athlete, team and sponsor evaluations using an experimental design. Key assumptions of the research are that sponsorship objectives are principally consumer-based and mediated. Models of sponsorship argue that sponsors aim to reach and influence consumers through sponsees. Assuming this pathway exists is central to sponsorship activities. A corollary is that other mediators, in this case the news-media, may also communicate (uncontrollable) messages such that a consumer audience may be told of negative news that may then be associated with the sponsor. When sponsors cancel contracts it is assumed that their goal is to control the links between their brand and a negative referent. Balance theory is used to discuss the potential effects of negative off-field behaviours of athletes on sponsor’s objectives. Heider’s balance theory (1958) explains that individuals prefer to evaluate linked individuals or entities consistently. In the sponsorship context this presents the possibility that a negative evaluation of the athlete’s behaviour will contribute to correspondingly negative evaluations of the athlete’s team and sponsors. A content analysis (Study 1) was used to survey the types of athlete off-field behaviours commonly reported in a newspaper. In order to provide a local context for the research, articles from the Courier Mail were sampled and teams in the National Rugby League (NRL) competition were the focus of the research. The study identified nearly 2000 articles referring to the NRL competition; 258 of those refer to off-field incidents involving athletes. The various types of behaviours reported include assault, sexual assault allegations, driving under the influence of alcohol, illicit drug use, breaches of club rules, and positive off-field activities (i.e., charitable activities). An experiment (Study 2) tested three news’ article stimuli developed from the behaviours identified in Study 1 in a between-subjects design. A measure of Identification with the Team was used as a covariate variable in the Multivariate Analysis of Covariance analysis. Social identity theory suggests that when an individual identifies with a group, their attitudes and behaviours towards both in- and out-group members are modified. Use of Identification with the Team as a covariate acknowledges that respondents will evaluate behaviours differently according to the attribution of those behaviours to an in- or out-group member. Findings of the research suggest that the news’ article stimuli have significant, large effects on evaluations of athlete off-field behaviour and athlete Likability. Consistent with pretest results, charitable fundraising is regarded as extremely positive; the athlete, correspondingly, is likable. Assault is evaluated as extremely negative, and the athlete as unlikable. DUI scores reveal that the athlete’s behaviour is very negative; however, the athlete’s likability was evaluated as neutral. Treatment group does not produce any significant effects on team or sponsor variables. This research also finds that Identification with the Team has significant, large effects on team variables (Attitude toward the Brand and Corporate Image). Identification also has a significant large effect on athlete Likability, but not on Attitude toward the Act. Identification with the Team does not produce any significant effects on sponsor variables. The results of this research suggest that sponsor’s consumer-based objectives are not threatened by newspaper reports linking athlete off-field behaviour with their brand. Evaluations of sponsor variables (Attitude toward the Sponsor’s Brand and Corporate Image) were consistently positive. Variance in that data, however, cannot be attributed to experimental stimuli or Identification with the Team. These results argue that respondents may regard sponsorships, in principle, as good. Although it is good news for sponsors that negative evaluations of athletes will not produce correspondingly negative evaluations of consumer-based sponsorship objectives, the results indicate problems for sponsorship managers. The failure of Identification with the Team to explain sponsor variable variance indicates that the sponsor has not been evaluated as a linked entity in a relationship with the sporting team and athlete in this research. This result argues that the sponsee-mediated affective communication path that sponsors aim use to communicate with desirable publics is not necessarily a path available to them.

A longitudinal study of grieving in family caregivers of people with dementia

A longitudinal study of grieving in family caregivers of people with dementia Recent research into dementia has identified the long term impact that the role of care giving for a relative with dementia has on family members This is largely due to the cognitive decline that characterises dementia and the losses that can be directly attributed to this. These losses include loss of memories, relationships and intimacy, and are often ambiguous so that the grief that accompanies them is commonly not recognised or acknowledged. The role and impact of pre-death or anticipatory grief has not previously been widely considered as a factor influencing health and well-being of family caregivers. Studies of grief in caregivers of a relative with dementia have concluded that grief is one of the greatest barriers to care giving and is a primary determinant of caregiver well-being. The accumulation of losses, in conjunction with experiences unique to dementia care giving, place family caregivers at risk of complicated grief. This occurs when integration of the death does not take place following bereavement and has been associated with a range of negative health outcomes. The aim of this research was to determine the influence of grief, in addition to other factors representing both positive and negative aspects of the role, on the health related quality of life of family caregivers of people with dementia, prior to and following the death of their relative with dementia. An exploratory research project underpinned by a conceptual framework of caregivers’ adaptation in the context of subjective appraisal of the strains and gains in their role was undertaken. The research comprised three studies. Study 1 was a scoping study that involved a series of semi-structured interviews with thirteen participants who were family caregivers of people with severe dementia or whose relative with dementia had died in the previous twelve months. The results of this study in conjunction with factors identified in the literature informed data collection for the further studies. Study 2 was a cross sectional survey of fifty caregivers recruited when their relative was in the moderate to severe stage of dementia. This study provided the baseline data for Study 3, a prospective cohort follow up study. Study 3 consisted of seventeen participants followed up at two time points after the death of their relative with dementia: six weeks and then six months following the death of the relative with dementia. The scoping study indicated that differences in appraisal of the care giving role and encounters with health professionals were related to levels of grief of caregivers prior to and following the death of the relative with dementia. This was supported in the baseline and follow up studies. In the baseline study, after adjusting for all variables in multivariate regression models, subjective appraisal of burden was found to make a significant contribution (p<.05) to mental health related quality of life. The two dependent variables, anticipatory grief and mental health related quality of life, were significantly (p<.01) correlated at a bivariate level. In the follow up study, linear mixed modelling and multiple regression analysis of data found that subjective appraisal of burden and resilience were significantly associated (p<.05 and p<.01, respectively) with mental health related quality of life over time. In addition, bereavement and complicated grief were significantly associated (p<.05) with mental health following the death of the relative. In this study social support and satisfaction with end of life care were found to be statistically associated (p<.05) with physical health related quality of life over time. The strong relationship between grief of caregivers and their health related quality of life over the entire care giving trajectory and period following the death of their relative highlights the urgent need for further research and interventions in this area. Overall results indicate that addressing the risk and protective factors including subjective appraisal of their care giving role, resilience, social support and satisfaction with end of life care of their relative, has the potential to both ameliorate negative health outcomes and to promote improved health for these caregivers. This research provides important information for development of targeted and appropriate interventions that aim to promote resilience and reduce the personal burden on caregivers of people with dementia.

Deep Raman Spectroscopy in the analytical forensic investigation of concealed substances

Deep Raman Spectroscopy is a domain within Raman spectroscopy consisting of techniques that facilitate the depth profiling of diffusely scattering media. Such variants include Time-Resolved Raman Spectroscopy (TRRS) and Spatially-Offset Raman Spectroscopy (SORS). A recent study has also demonstrated the integration of TRRS and SORS in the development of Time-Resolved Spatially-Offset Raman Spectroscopy (TR-SORS). This research demonstrates the application of specific deep Raman spectroscopic techniques to concealed samples commonly encountered in forensic and homeland security at various working distances. Additionally, the concepts behind these techniques are discussed at depth and prospective improvements to the individual techniques are investigated. Qualitative and quantitative analysis of samples based on spectral data acquired from SORS is performed with the aid of multivariate statistical techniques. By the end of this study, an objective comparison is made among the techniques within Deep Raman Spectroscopy based on their capabilities. The efficiency and quality of these techniques are determined based on the results procured which facilitates the understanding of the degree of selectivity for the deeper layer exhibited by the individual techniques relative to each other. TR-SORS was shown to exhibit an enhanced selectivity for the deeper layer relative to TRRS and SORS whilst providing spectral results with good signal-to-noise ratio. Conclusive results indicate that TR-SORS is a prospective deep Raman technique that offers higher selectivity towards deep layers and therefore enhances the non-invasive analysis of concealed substances from close range as well as standoff distances.

Role of land use and seasonal factors in water quality degradation

Surface water and groundwater are the most important water sources in the natural environment. Land use and seasonal factors play an important role in influencing the quality of these water sources. An in-depth understanding of the role of these two influential factors can help to implement an effective catchment management strategy for the protection of these water sources. This paper discusses the outcomes of an extensive research study which investigated the role of land use and seasonal factors on surface water and groundwater pollution in a mixed land use coastal catchment. The study confirmed that the influence exerted on the water environment by seasonal factors is secondary to that of land use. Furthermore, the influence of land use and seasonal factors on surface water and groundwater quality varies with the pollutant species. This highlights the need to specifically take into consideration the targeted pollutants and the key influential factors for the effective protection of vulnerable receiving water environments.

Advantages of tandem LC-MS for the rapid assessment of tissue-specific metabolic complexity using a pentafluorophenylpropyl stationary phase

In this study, a tandem LC-MS (Waters Xevo TQ) MRM-based MS method was developed for rapid, broad profiling of hydrophilic metabolites from biological samples, in either positive or negative ion modes without the need for an ion pairing reagent, using a reversed-phase pentafluorophenylpropyl (PFPP) column. The developed method was successfully applied to analyze various biological samples from C57BL/6 mice, including urine, duodenum, liver, plasma, kidney, heart, and skeletal muscle. As result, a total 112 of hydrophilic metabolites were detected within 8 min of running time to obtain a metabolite profile of the biological samples. The analysis of this number of hydrophilic metabolites is significantly faster than previous studies. Classification separation for metabolites from different tissues was globally analyzed by PCA, PLS-DA and HCA biostatistical methods. Overall, most of the hydrophilic metabolites were found to have a "fingerprint" characteristic of tissue dependency. In general, a higher level of most metabolites was found in urine, duodenum, and kidney. Altogether, these results suggest that this method has potential application for targeted metabolomic analyzes of hydrophilic metabolites in a wide ranges of biological samples.

Metabolic urinary profiling of alcohol hepatotoxicity and intervention effects of Yin Chen Hao Tang in rats using ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry

This paper was designed to study metabonomic characters of the hepatotoxicity induced by alcohol and the intervention effects of Yin Chen Hao Tang (YCHT), a classic traditional Chinese medicine formula for treatment of jaundice and liver disorders in China. Urinary samples from control, alcohol- and YCHT-treated rats were analyzed by ultra-performance liquid chromatography/electrospray ionization quadruple time-of-flight mass spectrometry (UPLC/ESI-QTOF-MS) in positive ionization mode. The total ion chromatograms obtained from the control, alcohol- and YCHT-treated rats were easily distinguishable using a multivariate statistical analysis method such as the principal components analysis (PCA). The greatest difference in metabolic profiling was observed from alcohol-treated rats compared with the control and YCHT-treated rats. The positive ions m/z 664.3126 (9.00 min) was elevated in urine of alcohol-treated rats, whereas, ions m/z 155.3547 (10.96 min) and 708.2932 (9.01 min) were at a lower concentration compared with that in urine of control rats, however, these ions did not indicate a statistical difference between control rats and YCHT-treated rats. The ion m/z 664.3126 was found to correspond to ceramide (d18:1/25:0), providing further support for an involvement of the sphingomyelin signaling pathway in alcohol hepatotoxicity and the intervention effects of YCHT.