Monitoring Programmes, Multiple Stress Analysis and Decision Support for River Basin Management

The identification of plausible causes for water body status deterioration will be much easier if it can build on available, reliable, extensive and comprehensive biogeochemical monitoring data (preferably aggregated in a database). A plausible identification of such causes is a prerequisite for well-informed decisions on which mitigation or remediation measures to take. In this chapter, first a rationale for an extended monitoring programme is provided; it is then compared to the one required by the Water Framework Directive (WFD). This proposal includes a list of relevant parameters that are needed for an integrated, a priori status assessment. Secondly, a few sophisticated statistical tools are described that subsequently allow for the estiation of the magnitude of impairment as well as the likely relative importance of different stressors in a multiple stressed environment. The advantages and restrictions of these rather complicated analytical methods are discussed. Finally, the use of Decision Support Systems (DSS) is advocated with regard to the specific WFD implementation requirements.

Comprehensive analysis of CpG island methylator phenotype (CIMP)-high, -low, and -negative colorectal cancers based on protein marker expression and molecular features

CpG island methylator phenotype (CIMP) is being investigated for its role in the molecular and prognostic classification of colorectal cancer patients but is also emerging as a factor with the potential to influence clinical decision-making. We report a comprehensive analysis of clinico-pathological and molecular features (KRAS, BRAF and microsatellite instability, MSI) as well as of selected tumour- and host-related protein markers characterizing CIMP-high (CIMP-H), -low, and -negative colorectal cancers. Immunohistochemical analysis for 48 protein markers and molecular analysis of CIMP (CIMP-H: ? 4/5 methylated genes), MSI (MSI-H: ? 2 instable genes), KRAS, and BRAF were performed on 337 colorectal cancers. Simple and multiple regression analysis and receiver operating characteristic (ROC) curve analysis were performed. CIMP-H was found in 24 cases (7.1%) and linked (p < 0.0001) to more proximal tumour location, BRAF mutation, MSI-H, MGMT methylation (p = 0.022), advanced pT classification (p = 0.03), mucinous histology (p = 0.069), and less frequent KRAS mutation (p = 0.067) compared to CIMP-low or -negative cases. Of the 48 protein markers, decreased levels of RKIP (p = 0.0056), EphB2 (p = 0.0045), CK20 (p = 0.002), and Cdx2 (p < 0.0001) and increased numbers of CD8+ intra-epithelial lymphocytes (p < 0.0001) were related to CIMP-H, independently of MSI status. In addition to the expected clinico-pathological and molecular associations, CIMP-H colorectal cancers are characterized by a loss of protein markers associated with differentiation, and metastasis suppression, and have increased CD8+ T-lymphocytes regardless of MSI status. In particular, Cdx2 loss seems to strongly predict CIMP-H in both microsatellite-stable (MSS) and MSI-H colorectal cancers. Cdx2 is proposed as a surrogate marker for CIMP-H.

Proteome analysis in cardiovascular pathophysiology using Dahl rat model

Dahl salt-sensitive (DS) and salt-resistant (DR) inbred rat strains represent a well established animal model for cardiovascular research. Upon prolonged administration of high-salt-containing diet, DS rats develop systemic hypertension, and as a consequence they develop left ventricular hypertrophy, followed by heart failure. The aim of this work was to explore whether this animal model is suitable to identify biomarkers that characterize defined stages of cardiac pathophysiological conditions. The work had to be performed in two stages: in the first part proteomic differences that are attributable to the two separate rat lines (DS and DR) had to be established, and in the second part the process of development of heart failure due to feeding the rats with high-salt-containing diet has to be monitored. This work describes the results of the first stage, with the outcome of protein expression profiles of left ventricular tissues of DS and DR rats kept under low salt diet. Substantial extent of quantitative and qualitative expression differences between both strains of Dahl rats in heart tissue was detected. Using Principal Component Analysis, Linear Discriminant Analysis and other statistical means we have established sets of differentially expressed proteins, candidates for further molecular analysis of the heart failure mechanisms.

Exploring High-resolution Magic Angle Spinning (HR-MAS) NMR Spectroscopy for Metabonomic Analysis of Apples

Classical liquid-state high-resolution (HR) NMR spectroscopy has proved a powerful tool in the metabonomic analysis of liquid food samples like fruit juices. In this paper the application of (1)H high-resolution magic angle spinning (HR-MAS) NMR spectroscopy to apple tissue is presented probing its potential for metabonomic studies. The (1)H HR-MAS NMR spectra are discussed in terms of the chemical composition of apple tissue and compared to liquid-state NMR spectra of apple juice. Differences indicate that specific metabolic changes are induced by juice preparation. The feasibility of HR-MAS NMR-based multivariate analysis is demonstrated by a study distinguishing three different apple cultivars by principal component analysis (PCA). Preliminary results are shown from subsequent studies comparing three different cultivation methods by means of PCA and partial least squares discriminant analysis (PLS-DA) of the HR-MAS NMR data. The compounds responsible for discriminating organically grown apples are discussed. Finally, an outlook of our ongoing work is given including a longitudinal study on apples.

Periodic breathing during ascent to extreme altitude quantified by spectral analysis of the respiratory volume signal

High altitude periodic breathing (PB) shares some common pathophysiologic aspects with sleep apnea, Cheyne-Stokes respiration and PB in heart failure patients. Methods that allow quantifying instabilities of respiratory control provide valuable insights in physiologic mechanisms and help to identify therapeutic targets. Under the hypothesis that high altitude PB appears even during physical activity and can be identified in comparison to visual analysis in conditions of low SNR, this study aims to identify PB by characterizing the respiratory pattern through the respiratory volume signal. A number of spectral parameters are extracted from the power spectral density (PSD) of the volume signal, derived from respiratory inductive plethysmography and evaluated through a linear discriminant analysis. A dataset of 34 healthy mountaineers ascending to Mt. Muztagh Ata, China (7,546 m) visually labeled as PB and non periodic breathing (nPB) is analyzed. All climbing periods within all the ascents are considered (total climbing periods: 371 nPB and 40 PB). The best crossvalidated result classifying PB and nPB is obtained with Pm (power of the modulation frequency band) and R (ratio between modulation and respiration power) with an accuracy of 80.3% and area under the receiver operating characteristic curve of 84.5%. Comparing the subjects from 1(st) and 2(nd) ascents (at the same altitudes but the latter more acclimatized) the effect of acclimatization is evaluated. SaO(2) and periodic breathing cycles significantly increased with acclimatization (p-value < 0.05). Higher Pm and higher respiratory frequencies are observed at lower SaO(2), through a significant negative correlation (p-value < 0.01). Higher Pm is observed at climbing periods visually labeled as PB with > 5 periodic breathing cycles through a significant positive correlation (p-value < 0.01). Our data demonstrate that quantification of the respiratory volume signal using spectral analysis is suitable to identify effects of hypobaric hypoxia on control of breathing.

How does spatial extent of fMRI datasets affect independent component analysis decomposition?

Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

Determination of histopathological tumor grade in neuroepithelial brain tumors by using spectral pattern analysis of in vivo spectroscopic data

OBJECT: In this study, 1H magnetic resonance (MR) spectroscopy was prospectively tested as a reliable method for presurgical grading of neuroepithelial brain tumors. METHODS: Using a database of tumor spectra obtained in patients with histologically confirmed diagnoses, 94 consecutive untreated patients were studied using single-voxel 1H spectroscopy (point-resolved spectroscopy; TE 135 msec, TE 135 msec, TR 1500 msec). A total of 90 tumor spectra obtained in patients with diagnostic 1H MR spectroscopy examinations were analyzed using commercially available software (MRUI/VARPRO) and classified using linear discriminant analysis as World Health Organization (WHO) Grade I/II, WHO Grade III, or WHO Grade IV lesions. In all cases, the classification results were matched with histopathological diagnoses that were made according to the WHO classification criteria after serial stereotactic biopsy procedures or open surgery. Histopathological studies revealed 30 Grade I/II tumors, 29 Grade III tumors, and 31 Grade IV tumors. The reliability of the histological diagnoses was validated considering a minimum postsurgical follow-up period of 12 months (range 12-37 months). Classifications based on spectroscopic data yielded 31 tumors in Grade I/II, 32 in Grade III, and 27 in Grade IV. Incorrect classifications included two Grade II tumors, one of which was identified as Grade III and one as Grade IV; two Grade III tumors identified as Grade II; two Grade III lesions identified as Grade IV; and six Grade IV tumors identified as Grade III. Furthermore, one glioblastoma (WHO Grade IV) was classified as WHO Grade I/II. This represents an overall success rate of 86%, and a 95% success rate in differentiating low-grade from high-grade tumors. CONCLUSIONS: The authors conclude that in vivo 1H MR spectroscopy is a reliable technique for grading neuroepithelial brain tumors.

The role of admission blood glucose in outcome prediction of surviving patients with multiple injuries

BACKGROUND: Recent literature demonstrates hyperglycemia to be common in patients with trauma and associated with poor outcome in patients with traumatic brain injury and critically ill patients. The goal of this study was to analyze the impact of admission blood glucose on the outcome of surviving patients with multiple injuries. METHODS: Patients' charts (age >16) admitted to the emergency room of the University Hospital of Berne, Switzerland, between January 1, 2002, and December 31, 2004, with an Injury Severity Score >or=17 and more than one severely injured organ system were reviewed retrospectively. Outcome measurements included morbidity, intensive care unit, and hospital length of stay. RESULTS: The inclusion criteria were met by 555 patients, of which 108 (19.5%) patients died. After multiple regression analysis, admission blood glucose proved to be an independent predictor of posttraumatic morbidity (p < 0.0001), intensive care unit, and hospital length of stay (p < 0.0001), despite intensified insulin therapy on the intensive care unit. CONCLUSIONS: In this population of patients with multiple injuries, hyperglycemia on admission was strongly associated with increased morbidity, especially infections, prolonged intensive care unit, and hospital length of stay independent of injury severity, gender, age, and various biochemical parameters.

Comparison of pain-resilient working individuals to population-based case controls with/without momentary low back pain

Background: Few studies have examined the 20% of individuals who never experience an episode of low back pain (LBP). To date, no investigation has been undertaken that examines a group who claim to have never experienced LBP in their lifetime in comparison to two population-based case–control groups with and without momentary LBP. This study investigates whether LBP-resilient workers between 50 and 65 years had better general health, demonstrated more positive health behaviour and were better able to achieve routine activities compared with both case–control groups. Methods: Forty-two LBP-resilient participants completed the same pain assessment questionnaire as a population-based LBP sample from a nationwide, large-scale cross-sectional survey in Switzerland. The LBP-resilient participants were pairwise compared to the propensity score-matched case controls by exploring differences in demographic and work characteristics, and by calculating odds ratios (ORs) and effect sizes. A discriminant analysis explored group differences, while the multiple logistic regression analysis specified single indicators which accounted for group differences. Results: LBP-resilient participants were healthier than the case controls with momentary LBP and achieved routine activities more easily. Compared to controls without momentary LBP, LBP-resilient participants had a higher vitality, a lower workload, a healthier attitude towards health and behaved more healthily by drinking less alcohol. Conclusions: By demonstrating a difference between LBP-resilient participants and controls without momentary LBP, the question that arises is what additional knowledge can be attained. Three underlying traits seem to be relevant about LBP-resilient participants: personality, favourable work conditions and subjective attitudes/attributions towards health. These rationales have to be considered with respect to LBP prevention.

The Coin Rotation Task: A Valid Test for Manual Dexterity in Multiple Sclerosis

BACKGROUND: Impaired manual dexterity is frequent and disabling in patients with multiple sclerosis (MS). Therefore, convenient, quick and validated tests for manual dexterity in MS patients are needed. OBJECTIVE: The aim of this study was to validate the Coin Rotation task (CRT) to examine manual dexterity in patients with MS. DESIGN: Cross-sectional study. METHODS: 101 outpatients with MS were assessed with the CRT, the Expanded Disability Status Scale (EDSS), the Scale for the assessment and rating of ataxia (SARA), the Modified Ashworth Scale (MAS), and their muscle strength and sensory deficits of the hands were noted. Concurrent validity and diagnostic accuracy of the CRT were determined by comparison with the Nine Hole Peg Test (9HPT). Construct validity was determined by comparison with a valid dexterity questionnaire. Multiple regression analysis was done to explore correlations of the CRT with the EDSS, SARA, MAS, muscle strength and sensory deficits. RESULTS: The CRT correlated significantly with the 9HPT (r=.73, p<.0001) indicating good concurrent validity. The cut-off values for the CRT relative to the 9HPT were 18.75 seconds for the dominant (sensitivity: 81.5%; specificity 80.0%) and 19.25 seconds for the non-dominant hand (sensitivity: 90.3%; specificity: 81.8%) demonstrating good diagnostic accuracy. Furthermore, the CRT correlated significantly with the dexterity questionnaire (r=-.49, p<.0001) indicating moderate construct validity. Multiple regression analyses revealed that the EDSS was the strongest predictor for impaired dexterity. LIMITATIONS: Mostly relapsing-remitting MS patients with an EDSS up to 7 were examined. CONCLUSIONS: This study validates the CRT as a test that can be used easily and quickly to evaluate manual dexterity in patients with MS.

Meta-Analysis of Long-Term Land Management Effect on Soil Organic Carbon (SOC) in Ethiopia

The role of Soil Organic Carbon (SOC) in mitigating climate change, indicating soil quality and ecosystem function has created research interested to know the nature of SOC at landscape level. The objective of this study was to examine variation and distribution of SOC in a long-term land management at a watershed and plot level. This study was based on meta-analysis of three case studies and 128 surface soil samples from Ethiopia. Three sites (Gununo, Anjeni and Maybar) were compared after considering two Land Management Categories (LMC) and three types of land uses (LUT) in quasi-experimental design. Shapiro-Wilk tests showed non-normal distribution (p = 0.002, a = 0.05) of the data. SOC median value showed the effect of long-term land management with values of 2.29 and 2.38 g kg-1 for less and better-managed watersheds, respectively. SOC values were 1.7, 2.8 and 2.6 g kg-1 for Crop (CLU), Grass (GLU) and Forest Land Use (FLU), respectively. The rank order for SOC variability was FLU>GLU>CLU. Mann-Whitney U and Kruskal-Wallis test showed a significant difference in the medians and distribution of SOC among the LUT, between soil profiles (p<0.05, confidence interval 95%, a = 0.05) while it is not significant (p>0.05) for LMC. The mean and sum rank of Mann Whitney U and Kruskal Wallis test also showed the difference at watershed and plot level. Using SOC as a predictor, cross-validated correct classification with discriminant analysis showed 46 and 49% for LUT and LMC, respectively. The study showed how to categorize landscapes using SOC with respect to land management for decision-makers.

Investigation of different apple cultivars by high resolution magic angle spinning NMR. A feasibility study

(1)H HR-MAS NMR spectroscopy was applied to apple tissue samples deriving from 3 different cultivars. The NMR data were statistically evaluated by analysis of variance (ANOVA), principal component analysis (PCA), and partial least-squares-discriminant analysis (PLS-DA). The intra-apple variability of the compounds was found to be significantly lower than the inter-apple variability within one cultivar. A clear separation of the three different apple cultivars could be obtained by multivariate analysis. Direct comparison of the NMR spectra obtained from apple tissue (with HR-MAS) and juice (with liquid-state HR NMR) showed distinct differences in some metabolites, which are probably due to changes induced by juice preparation. This preliminary study demonstrates the feasibility of (1)H HR-MAS NMR in combination with multivariate analysis as a tool for future chemometric studies applied to intact fruit tissues, e.g. for investigating compositional changes due to physiological disorders, specific growth or storage conditions.

Effect of pulsatility on the mathematical modeling of rotary blood pumps

In this study, the effect of time derivatives of flow rate and rotational speed was investigated on the mathematical modeling of a rotary blood pump (RBP). The basic model estimates the pressure head of the pump as a dependent variable using measured flow and speed as predictive variables. Performance of the model was evaluated by adding time derivative terms for flow and speed. First, to create a realistic working condition, the Levitronix CentriMag RBP was implanted in a sheep. All parameters from the model were physically measured and digitally acquired over a wide range of conditions, including pulsatile speed. Second, a statistical analysis of the different variables (flow, speed, and their time derivatives) based on multiple regression analysis was performed to determine the significant variables for pressure head estimation. Finally, different mathematical models were used to show the effect of time derivative terms on the performance of the models. In order to evaluate how well the estimated pressure head using different models fits the measured pressure head, root mean square error and correlation coefficient were used. The results indicate that inclusion of time derivatives of flow and speed can improve model accuracy, but only minimally.

Vitrectomy for juvenile uveitis: prognostic factors for the long-term functional outcome

PURPOSE: This study evaluated the long-term effect of pars plana vitrectomy (PPV) in children and adolescents with chronic uveitis on visual function, anatomical outcome, and the requirement of systemic treatment. Further, predictive preoperative factors associated with a beneficial visual outcome were assessed. METHODS: Retrospective review of 29 eyes of 23 consecutive paediatric and juvenile patients below 20 years of age with chronic uveitis who underwent a PPV for visually significant opacities in 25 eyes, vitreous haemorrhage in three eyes, and retinal detachment in one eye. The clinical diagnosis was chronic intermediate uveitis in 22 eyes and retinal vasculitis of different origin in seven eyes. RESULTS: LogMAR visual acuity improved from an average of 0.91 to 0.33 (P<0.001). Cystoid macular oedema (CME) was significantly reduced in eight of 10 eyes postoperatively (P=0.021). In the multiple regression analysis, a low preoperative logMAR visual acuity and the presence of a CME had a negative influence on the final logMAR visual acuity. Furthermore, the appearance of chronic uveitis relapses was significantly reduced from 15 eyes before to seven eyes after surgery (P=0.042). CONCLUSIONS: PPV has a beneficial effect on the course and the complications of chronic uveitis in paediatric and juvenile patients with respect to the anatomical and visual outcome. Preoperative logMAR visual acuity and clinically significant CME were the most accurate predictors for the functional outcome.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.