Validation of ACB in vitro and in vivo as a biomagnetic method for measuring stomach contraction

Background The aim of this study was to validate a biomagnetic method (alternate current biosusceptometry, ACB) for monitoring gastric wall contractions in rats. Methods In vitro data were obtained to establish the relationship between ACB and the strain-gauge (SG) signal amplitude. In vivo experiments were performed in pentobarbital-anesthetized rats with SG and magnetic markers previously implanted under the gastric serosa or after ingestion of magnetic material. Gastric motility was quantified from the tracing amplitudes and frequency profiles obtained by Fast Fourier Transform. Key Results The correlation between in vitro signal amplitudes was strong (R = 0.989). The temporal cross-correlation coefficient between the ACB and SG signal amplitude was higher (P < 0.0001) in the postprandial (88.3 +/- 9.1 V) than in the fasting state (31.0 +/- 16.9 V). Irregular signal profiles, low contraction amplitudes, and smaller signal-to-noise ratios explained the poor correlation between techniques for fasting-state recordings. When a magnetic material was ingested, there was also strong correlation in the frequency and signal amplitude and a small phase-difference between the techniques. The contraction frequencies using ACB were 0.068 +/- 0.007 Hz (postprandial) and 0.058 +/- 0.007 Hz (fasting) (P < 0.002) and those using SG were 0.066 +/- 0.006 Hz (postprandial) and 0.059 +/- 0.008 Hz (fasting) (P < 0.005). Conclusions & Inferences In summary, ACB is reliable for monitoring gastric wall contractions using both implanted and ingested magnetic materials, and may serve as an accurate and sensitive technique for gastrointestinal motility studies.

The Provisional Paediatric Rheumatology International Trials Organisation/American College of Rheumatology/European League Against Rheumatism disease activity core set for the evaluation of response to therapy in juvenile dermatomyositis: A prospective validation study

Objective. To validate a core set of outcome measures for the evaluation of response to treatment in patients with juvenile dermatomyositis (DM). Methods. In 2001, a preliminary consensus-derived core set for evaluating response to therapy in juvenile DM was established. In the present study, the core set was validated through an evidence-based, large-scale data collection that led to the enrollment of 294 patients from 36 countries. Consecutive patients with active disease were assessed at baseline and after 6 months. The validation procedures included assessment of feasibility, responsiveness, discriminant and construct ability, concordce in the evaluation of response to therapy between physicians and parents, redundancy, internal consistency, and ability to predict a therapeutic response. Results. The following clinical measures were found to be feasible, and to have good construct validity, discriminative ability, and internal consistency; furthermore, they were not redundant, proved responsive to clinically important changes in disease activity, and were associated strongly with treatment outcome and thus were included in the final core set: 1) physician`s global assessment of disease activity, 2) muscle strength, 3) global disease activity measure, 4) parent`s global assessment of patient`s well-being, 5) functional ability, and 6) health-related quality of life. Conclusion. The members of the Paediatric Rheumatology International Trials Organisation, with the endorsement of the American College of Rheumatology and the European Leauge Against Rheumatism, propose a core set of criteria for the evaluation of response of therapy that is scientifically and clinically relevant and statistically validated. The core set will help standardize the conduct and reporting of clinical trials and assist practitioners in deciding whether a child with juvenile DM has responded adequately to therapy.

Validation of the Brazilian version of the quality of life scale for patients with Alzheimer`s disease and their caregivers (QOL-AD)

Quality of life (QOL) has been extensively studied in clinical trials and in research on chronic degenerative diseases and dementia. The aim of this study was to assess the reliability and construct validity of the Brazilian version of the QOL scale in Alzheimer`s disease (AD; QOL-AD). The QOL-AD was administered to 60 patients with mild or moderate AD and to their caregivers. The construct validation was accomplished through correlations amongst total scores of patients` and caregivers` reports on patients` quality of life (PQOL and C-PQOL, respectively), and data related to cognitive impairment, depressive symptoms, functional performance, behavioral disturbances and a generic instrument of quality of life (WHOQOL-brief), as well as correlation of total score of caregivers` reports on their own quality of life (CQOL) with the measurements cited above, QOL-AD patient reports, and depressive symptoms. The reliability was high for PQOL, C-PQOL, and CQOL versions (Cronbach`s alpha = 0.80, 0.83, and 0.86, respectively). We observed significant correlations in the construct validity of all three versions regarding the variables associated with the disease and also with WHOQOL-brief. The scale took, on average, six min for each version. The results indicate reliability and construct validity of the Brazilian version of the QOL-AD in the studied sample.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

Model-based procedure for scale-up of wet, overflow ball mills - Part III: Validation and discussion

A new ball mill scale-up procedure is developed. This procedure has been validated using seven sets of Ml-scale ball mil data. The largest ball mills in these data have diameters (inside liners) of 6.58m. The procedure can predict the 80% passing size of the circuit product to within +/-6% of the measured value, with a precision of +/-11% (one standard deviation); the re-circulating load to within +/-33% of the mass-balanced value (this error margin is within the uncertainty associated with the determination of the re-circulating load); and the mill power to within +/-5% of the measured value. This procedure is applicable for the design of ball mills which are preceded by autogenous (AG) mills, semi-autogenous (SAG) mills, crushers and flotation circuits. The new procedure is more precise and more accurate than Bond's method for ball mill scale-up. This procedure contains no efficiency correction which relates to the mill diameter. This suggests that, within the range of mill diameter studied, milling efficiency does not vary with mill diameter. This is in contrast with Bond's equation-Bond claimed that milling efficiency increases with mill diameter. (C) 2001 Elsevier Science Ltd. All rights reserved.

Prospective independent validation of APACHE III models in an Australian tertiary adult intensive care unit

Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995-1999.

Determination of regional flow by use of intravascular PET tracers: Microvascular theory and experimental validation for pig livers

Today, the standard approach for the kinetic analysis of dynamic PET studies is compartment models, in which the tracer and its metabolites are confined to a few well-mixed compartments. We examine whether the standard model is suitable for modern PET data or whether theories including more physiologic realism can advance the interpretation of dynamic PET data. A more detailed microvascular theory is developed for intravascular tracers in single-capillary and multiple-capillary systems. The microvascular models, which account for concentration gradients in capillaries, are validated and compared with the standard model in a pig liver study. Methods: Eight pigs underwent a 5-min dynamic PET study after O-15-carbon monoxide inhalation. Throughout each experiment, hepatic arterial blood and portal venous blood were sampled, and flow was measured with transit-time flow meters. The hepatic dual-inlet concentration was calculated as the flow-weighted inlet concentration. Dynamic PET data were analyzed with a traditional single-compartment model and 2 microvascular models. Results: Microvascular models provided a better fit of the tissue activity of an intravascular tracer than did the compartment model. In particular, the early dynamic phase after a tracer bolus injection was much improved. The regional hepatic blood flow estimates provided by the microvascular models (1.3 +/- 0.3 mL min(-1) mL(-1) for the single-capillary model and 1.14 +/- 0.14 min(-1) mL(-1) for the multiple-capillary model) (mean +/- SEM mL of blood min(-1) mL of liver tissue(-1)) were in agreement with the total blood flow measured by flow meters and normalized to liver weight (1.03 +/- 0.12 mL min(-1) mL(-1)). Conclusion: Compared with the standard compartment model, the 2 microvascular models provide a superior description of tissue activity after an intravascular tracer bolus injection. The microvascular models include only parameters with a clear-cut physiologic interpretation and are applicable to capillary beds in any organ. In this study, the microvascular models were validated for the liver and provided quantitative regional flow estimates in agreement with flow measurements.

Promiscuous CTL recognition of viral epitopes on multiple human leukocyte antigens: Biological validation of the proposed HLA A24 supertype

Multiple HLA class I alleles can bind peptides with common sequence motifs due to structural similarities in the peptide binding cleft, and these groups of alleles have been classified into supertypes. Nine major HLA supertypes have been proposed, including an A24 supertype that includes A*2301, A*2402, and A*3001. Evidence for this A24 supertype is limited to HLA sequence homology and/or similarity in peptide binding motifs for the alleles. To investigate the immunological relevance of this proposed supertype, we have examined two viral epitopes (from EBV and CMV) initially defined as HLA-A*2301-binding peptides. The data clearly demonstrate that each peptide could be recognized by CTL clones in the context of A*2301 or A*2402; thus validating the inclusion of these three alleles within an A24 supertype. Furthermore, CTL responses to the EBV epitope were detectable in both A*2301(+) and A*2402(+) individuals who had been previously exposed to this virus. These data substantiate the biological relevance of the A24 supertype, and the identification of viral epitopes with the capacity to bind promiscuously across this supertype could aid efforts to develop CTL-based vaccines or immunotherapy. The degeneracy in HLA restriction displayed by some T cells in this study also suggests that the dogma of self-MHC restriction needs some refinement to accommodate foreign peptide recognition in the context of multiple supertype alleles.

Quality of life assessment in the community-dwelling elderly: Validation of the Assessment of Quality of Life (AQoL) Instrument and comparison with the SF-36

Measurement of Health-Related Quality of Life (HRQoL) of the elderly requires instruments with demonstrated sensitivity, reliability, and validity, particularly with the increasing proportion of older people entering the health care system. This article reports the psychometric properties of the 12-item Assessment of Quality of Life (AQoL) instrument in chronically ill community-dwelling elderly people with an 18-month follow-up. Comparator instruments included the SF-36 and the OARS. Construct validity of the AQoL was strong when examined via factor analysis and convergent and divergent validity against other scales. Receiver Operator Characteristic (ROC) curve analyses and relative efficiency estimates indicated the AQoL is sensitive, responsive, and had the strongest predicative validity for nursing home entry. It was also sensitive to economic prediction over the follow-up. Given these robust psychometric properties and the brevity of the scale, AQoL appears to be a suitable instrument for epidemiologic studies where HRQoL and utility data are required from elderly populations. (C) 2003 Elsevier Science Inc. All rights reserved.

Geostatistical Mapping of Outfall Plume Dispersion Data gathered with an autonomous underwater vehicle

The main purpose of this study was to examine the applicability of geostatistical modeling to obtain valuable information for assessing the environmental impact of sewage outfall discharges. The data set used was obtained in a monitoring campaign to S. Jacinto outfall, located off the Portuguese west coast near Aveiro region, using an AUV. The Matheron’s classical estimator was used the compute the experimental semivariogram which was fitted to three theoretical models: spherical, exponential and gaussian. The cross-validation procedure suggested the best semivariogram model and ordinary kriging was used to obtain the predictions of salinity at unknown locations. The generated map shows clearly the plume dispersion in the studied area, indicating that the effluent does not reach the near by beaches. Our study suggests that an optimal design for the AUV sampling trajectory from a geostatistical prediction point of view, can help to compute more precise predictions and hence to quantify more accurately dilution. Moreover, since accurate measurements of plume’s dilution are rare, these studies might be very helpful in the future for validation of dispersion models.

Cluster Analysis of Business Data

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Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

Clustering an interval data set : are the main partitions similar to a priori partition?

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