Primary activity measurements with a 4πβ-4πγ coincidence counting system.

The radioactive concentrations of (166m)Ho, (134)Cs and (133)Ba solutions have been standardised using a 4πβ-4πγ coincidence counting system we have recently set up. The detection in the beta channel is performed using various geometries of a UPS-89 plastic scintillator optically coupled to a selected low-noise 1in. diameter photomultiplier tube. The light-tight thin capsule that encloses this beta detector is housed within the well of a 5in.×5in. NaI(Tl) monocrystal detector. The beta detection efficiency can be varied either by optical filtering or electronic discrimination when the electrons loose all their energy in the plastic scintillator. This 4πβ-4πγ coincidence system improves on our 4πβ(PC)-γ system in that its sample preparation is less labour intensive, it yields larger beta- and gamma-counting efficiencies thus enabling the standardisation of low activity sources with good statistics in reasonable time, and it makes standardising short-lived radionuclides easier. The resulting radioactive concentrations of (166m)Ho, (134)Cs and (133)Ba are found to agree with those measured with other primary measurement methods thus validating our 4πβ-4πγ coincidence counting system.

A validated assay for measuring doxorubicin in biological fluids and tissues in an isolated lung perfusion model: matrix effect and heparin interference strongly influence doxorubicin measurements.

Doxorubicin is an antineoplasic agent active against sarcoma pulmonary metastasis, but its clinical use is hampered by its myelotoxicity and its cumulative cardiotoxicity, when administered systemically. This limitation may be circumvented using the isolated lung perfusion (ILP) approach, wherein a therapeutic agent is infused locoregionally after vascular isolation of the lung. The influence of the mode of infusion (anterograde (AG): through the pulmonary artery (PA); retrograde (RG): through the pulmonary vein (PV)) on doxorubicin pharmacokinetics and lung distribution was unknown. Therefore, a simple, rapid and sensitive high-performance liquid chromatography method has been developed to quantify doxorubicin in four different biological matrices (infusion effluent, serum, tissues with low or high levels of doxorubicin). The related compound daunorubicin was used as internal standard (I.S.). Following a single-step protein precipitation of 500 microl samples with 250 microl acetone and 50 microl zinc sulfate 70% aqueous solution, the obtained supernatant was evaporated to dryness at 60 degrees C for exactly 45 min under a stream of nitrogen and the solid residue was solubilized in 200 microl of purified water. A 100 microl-volume was subjected to HPLC analysis onto a Nucleosil 100-5 microm C18 AB column equipped with a guard column (Nucleosil 100-5 microm C(6)H(5) (phenyl) end-capped) using a gradient elution of acetonitrile and 1-heptanesulfonic acid 0.2% pH 4: 15/85 at 0 min-->50/50 at 20 min-->100/0 at 22 min-->15/85 at 24 min-->15/85 at 26 min, delivered at 1 ml/min. The analytes were detected by fluorescence detection with excitation and emission wavelength set at 480 and 550 nm, respectively. The calibration curves were linear over the range of 2-1000 ng/ml for effluent and plasma matrices, and 0.1 microg/g-750 microg/g for tissues matrices. The method is precise with inter-day and intra-day relative standard deviation within 0.5 and 6.7% and accurate with inter-day and intra-day deviations between -5.4 and +7.7%. The in vitro stability in all matrices and in processed samples has been studied at -80 degrees C for 1 month, and at 4 degrees C for 48 h, respectively. During initial studies, heparin used as anticoagulant was found to profoundly influence the measurements of doxorubicin in effluents collected from animals under ILP. Moreover, the strong matrix effect observed with tissues samples indicate that it is mandatory to prepare doxorubicin calibration standard samples in biological matrices which would reflect at best the composition of samples to be analyzed. This method was successfully applied in animal studies for the analysis of effluent, serum and tissue samples collected from pigs and rats undergoing ILP.

What kind of relationships between the evolution of pain, beliefs and bio-psycho-social complexity after a locomotor traumatism?

Introduction: Pain and beliefs have an influence on the patient's course in rehabilitation, pain causes fears and fears influence pain perception. The aim of this study is to understand pain and beliefs evolutions during rehabilitation taking into account of bio-psycho-social complexity.Patients and methods: 631 consecutive patients admitted in rehabilitation after a musculoskeletal traumatism were included and assessed at admission and at discharge. Pain was measured by VAS (Visual Analogical Scale), bio-psycho-social complexity by Intermed scale, and beliefs by judgement on Lickert scales. Four kinds of beliefs were evaluated: fear of a severe origin of pain, fear of movement, fear of pain and feeling of distress (loss of control). The association between the changes in pain and beliefs during the hospitalization was assessed by linear regressions.Results: After adjustment for gender, age, education and native language, patients with a decrease in pain during rehabilitation have higher probability of decreasing their fears. For the distress feeling, this relationship is weaker among bio-psycho-socially complex patients (odds-ratio 1.22 for each decreasing of 10mm/100 VAS) than among non-complex patients (OR 1.47). Patients with a pain decrease of 30% or more during hospitalization have higher probability of seeing their fears decrease, this relationship being stronger in complex patient for fear of a severe origin of pain.Discussion: The relationships between evolution of pain and beliefs move in the same direction. The higher a patient feels pain, the less they could be able to modify their dysfunctional beliefs. When the pain diminishes of 30% or more, the probability to challenge the beliefs is increased. The prognostic with regard to feeling of distress and fear of a severe origin of pain, is worse among bio-psycho-socially complex patients.

Comparison of the polynomial model against explicit measurements of noise components for different mammography systems.

Given the adverse impact of image noise on the perception of important clinical details in digital mammography, routine quality control measurements should include an evaluation of noise. The European Guidelines, for example, employ a second-order polynomial fit of pixel variance as a function of detector air kerma (DAK) to decompose noise into quantum, electronic and fixed pattern (FP) components and assess the DAK range where quantum noise dominates. This work examines the robustness of the polynomial method against an explicit noise decomposition method. The two methods were applied to variance and noise power spectrum (NPS) data from six digital mammography units. Twenty homogeneously exposed images were acquired with PMMA blocks for target DAKs ranging from 6.25 to 1600 µGy. Both methods were explored for the effects of data weighting and squared fit coefficients during the curve fitting, the influence of the additional filter material (2 mm Al versus 40 mm PMMA) and noise de-trending. Finally, spatial stationarity of noise was assessed.Data weighting improved noise model fitting over large DAK ranges, especially at low detector exposures. The polynomial and explicit decompositions generally agreed for quantum and electronic noise but FP noise fraction was consistently underestimated by the polynomial method. Noise decomposition as a function of position in the image showed limited noise stationarity, especially for FP noise; thus the position of the region of interest (ROI) used for noise decomposition may influence fractional noise composition. The ROI area and position used in the Guidelines offer an acceptable estimation of noise components. While there are limitations to the polynomial model, when used with care and with appropriate data weighting, the method offers a simple and robust means of examining the detector noise components as a function of detector exposure.

Changing healthcare: stakeholder perceptions of the burden of chronic disease and the value of teams, measurements and communication.

Canadian healthcare is changing. Over the course of the past decade, the Health Care in Canada Survey (HCIC) has annually measured the reactions of the public and professional stakeholders to many of these change forces. In HCIC 2008, for the first time, the public's perception of their health status and all stakeholders' views of the burden and effective management of chronic diseases were sought. Overall, Canadians perceive themselves as healthy, with 84% of adults reporting good-to-excellent health. However, good health decreased with age as the occurrence of chronic illness rose, from 12% in the age group 18-24 to 65% for the population =65 years. More than 70% of all stakeholders were strongly or somewhat supportive of the implementation of coordinated care, or disease management programs, to improve the care of patients with chronic illnesses. Concordant support was also expressed for key disease management components, including coordinated interventions to improve home, community and self-care; increased wellness promotion; and increased use of clinical measurements and feedback to all stakeholders. However, there were also important areas of non-concordance. For example, the public and doctors consistently expressed less support than other stakeholders for the value of team care, including the use of non-physician professionals to provide patient care; increased patient involvement in decision-making; and the use of electronic health records to facilitate communication. The actual participation in disease management programs averaged 34% for professionals and 25% for the public. We conclude that chronic diseases are common, age-related and burdensome in Canada. Disease management or coordinated intervention often delivered by teams is also relatively common, despite its less-than-universal acceptance by all stakeholders. Further insights are needed, particularly into the variable perceptions of the value and efficacy of team-delivered healthcare and its important components.

Variability in urinary oxalate measurements between six international laboratories.

BACKGROUND: Hyperoxaluria is a major risk factor for kidney stone formation. Although urinary oxalate measurement is part of all basic stone risk assessment, there is no standardized method for this measurement. METHODS: Urine samples from 24-h urine collection covering a broad range of oxalate concentrations were aliquoted and sent, in duplicates, to six blinded international laboratories for oxalate, sodium and creatinine measurement. In a second set of experiments, ten pairs of native urine and urine spiked with 10 mg/L of oxalate were sent for oxalate measurement. Three laboratories used a commercially available oxalate oxidase kit, two laboratories used a high-performance liquid chromatography (HPLC)-based method and one laboratory used both methods. RESULTS: Intra-laboratory reliability for oxalate measurement expressed as intraclass correlation coefficient (ICC) varied between 0.808 [95% confidence interval (CI): 0.427-0.948] and 0.998 (95% CI: 0.994-1.000), with lower values for HPLC-based methods. Acidification of urine samples prior to analysis led to significantly higher oxalate concentrations. ICC for inter-laboratory reliability varied between 0.745 (95% CI: 0.468-0.890) and 0.986 (95% CI: 0.967-0.995). Recovery of the 10 mg/L oxalate-spiked samples varied between 8.7 ± 2.3 and 10.7 ± 0.5 mg/L. Overall, HPLC-based methods showed more variability compared to the oxalate oxidase kit-based methods. CONCLUSIONS: Significant variability was noted in the quantification of urinary oxalate concentration by different laboratories, which may partially explain the differences of hyperoxaluria prevalence reported in the literature. Our data stress the need for a standardization of the method of oxalate measurement.

DNA fingerprinting of glioma cell lines and considerations on similarity measurements.

Glioma cell lines are an important tool for research in basic and translational neuro-oncology. Documentation of their genetic identity has become a requirement for scientific journals and grant applications to exclude cross-contamination and misidentification that lead to misinterpretation of results. Here, we report the standard 16 marker short tandem repeat (STR) DNA fingerprints for a panel of 39 widely used glioma cell lines as reference. Comparison of the fingerprints among themselves and with the large DSMZ database comprising 9 marker STRs for 2278 cell lines uncovered 3 misidentified cell lines and confirmed previously known cross-contaminations. Furthermore, 2 glioma cell lines exhibited identity scores of 0.8, which is proposed as the cutoff for detecting cross-contamination. Additional characteristics, comprising lack of a B-raf mutation in one line and a similarity score of 1 with the original tumor tissue in the other, excluded a cross-contamination. Subsequent simulation procedures suggested that, when using DNA fingerprints comprising only 9 STR markers, the commonly used similarity score of 0.8 is not sufficiently stringent to unambiguously differentiate the origin. DNA fingerprints are confounded by frequent genetic alterations in cancer cell lines, particularly loss of heterozygosity, that reduce the informativeness of STR markers and, thereby, the overall power for distinction. The similarity score depends on the number of markers measured; thus, more markers or additional cell line characteristics, such as information on specific mutations, may be necessary to clarify the origin.

Calibration of high-resolution geophysical data with tracer test measurements to improve hydrological predictions

Relationships between porosity and hydraulic conductivity tend to be strongly scale- and site-dependent and are thus very difficult to establish. As a result, hydraulic conductivity distributions inferred from geophysically derived porosity models must be calibrated using some measurement of aquifer response. This type of calibration is potentially very valuable as it may allow for transport predictions within the considered hydrological unit at locations where only geophysical measurements are available, thus reducing the number of well tests required and thereby the costs of management and remediation. Here, we explore this concept through a series of numerical experiments. Considering the case of porosity characterization in saturated heterogeneous aquifers using crosshole ground-penetrating radar and borehole porosity log data, we use tracer test measurements to calibrate a relationship between porosity and hydraulic conductivity that allows the best prediction of the observed hydrological behavior. To examine the validity and effectiveness of the obtained relationship, we examine its performance at alternate locations not used in the calibration procedure. Our results indicate that this methodology allows us to obtain remarkably reliable hydrological predictions throughout the considered hydrological unit based on the geophysical data only. This was also found to be the case when significant uncertainty was considered in the underlying relationship between porosity and hydraulic conductivity.

Chest pulse-wave velocity: a novel approach to assess arterial stiffness.

Pulse-wave velocity (PWV) is considered as the gold-standard method to assess arterial stiffness, an independent predictor of cardiovascular morbidity and mortality. Current available devices that measure PWV need to be operated by skilled medical staff, thus, reducing the potential use of PWV in the ambulatory setting. In this paper, we present a new technique allowing continuous, unsupervised measurements of pulse transit times (PTT) in central arteries by means of a chest sensor. This technique relies on measuring the propagation time of pressure pulses from their genesis in the left ventricle to their later arrival at the cutaneous vasculature on the sternum. Combined thoracic impedance cardiography and phonocardiography are used to detect the opening of the aortic valve, from which a pre-ejection period (PEP) value is estimated. Multichannel reflective photoplethysmography at the sternum is used to detect the distal pulse-arrival time (PAT). A PTT value is then calculated as PTT = PAT - PEP. After optimizing the parameters of the chest PTT calculation algorithm on a nine-subject cohort, a prospective validation study involving 31 normo- and hypertensive subjects was performed. 1/chest PTT correlated very well with the COMPLIOR carotid to femoral PWV (r = 0.88, p < 10 (-9)). Finally, an empirical method to map chest PTT values onto chest PWV values is explored.