Independent assessment of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) sample preparation quality: A novel statistical approach for quality scoring.

Preparation of samples according to an optimized method is crucial for accurate determination of polymer sample characteristics by Matrix-Assisted Laser Desorption Ionization (MALDI) analysis. Sample preparation conditions such as matrix choice, cationization agent, deposition technique or even the deposition volume should be chosen to suit the sample of interest. Many sample preparation protocols have been developed and employed, yet finding the optimal sample preparation protocol remains a challenge. Because an objective comparison between the results of diverse protocols is not possible, "gut-feeling" or "good enough" is often decisive in the search for an optimum. This implies that sub-optimal protocols are used, leading to a loss of mass spectral information quality. To address this problem a novel analytical strategy based on MALDI imaging and statistical data processing was developed in which eight parameters were formulated to objectively quantify the quality of sample deposition and optimal MALDI matrix composition and finally sum up to an overall quality score of the sample deposition. These parameters can be established in a fully automated way using commercially available mass spectrometry imaging instruments without any hardware adjustments. With the newly developed analytical strategy the highest quality MALDI spots were selected, resulting in more reproducible and more valuable spectra for PEG in a variety of matrices. Moreover, our method enables an objective comparison of sample preparation protocols for any analyte and opens up new fields of investigation by presenting MALDI performance data in a clear and concise way.

Is there a suitable point-of-care glucose meter for tight glycemic control? Evaluation of one home-use and four hospital-use meters in an intensive care unit.

BACKGROUND: Implementation of tight glycemic control (TGC) and avoidance of hypoglycemia in intensive care unit (ICU) patients require frequent analysis of blood glucose. This can be achieved by accurate point-of-care (POC) hospital-use glucose meters. In this study one home-use and four different hospital-use POC glucose meters were evaluated in critically ill ICU patients. METHODS: All patients (n = 80) requiring TGC were included in this study. For each patient three to six glucose measurements (n = 390) were performed. Blood glucose was determined by four hospital-use POC glucose meters, Roche Accu-Check Inform II System, HemoCue Glu201DM, Nova StatStrip, Abbott Precision Xceed Pro, and one home-use POC glucose meter, Menarini GlucoCard Memory PC. The criteria described in ISO 15197, Dutch TNO quality guideline and in NACB/ADA-2011 were applied in the comparisons. RESULTS: According to the ISO 15197, the percentages of the measured values that fulfilled the criterion were 99.5% by Roche, 95.1% by HemoCue, 91.0% by Nova, 96.6% by Abbott, and 63.3% by Menarini. According to the TNO quality guideline these percentages were 96.1% , 91.0% , 81.8% , 94.2% , and 47.7% , respectively. Application of the NACB/ADA guideline resulted in percentages of 95.6%, 89.2%, 77.9%, 93.4%, and 45.4%, respectively. CONCLUSIONS: When ISO 15197 was applied, Roche, HemoCue and Abbott fulfilled the criterion in this patient population, whereas Nova and Menarini did not. However, when TNO quality guideline and NACB/ADA 2011 guideline were applied only Roche fulfilled the criteria.

Alignment and clustering strategies for GC×GC-MS features using a cylindrical mapping.

Comprehensive two-dimensional gas chromatography coupled to mass spectrometry is a powerful tool to analyze complex samples. For application of the technique in studies like biomarker discovery in which large sets of complex samples have to be analyzed, extensive preprocessing is needed to align the data obtained in several injections (analyses). We developed new alignment and clustering algorithms for this type of data. New in the current procedures is the consistent way in which the phenomenon referred to as wrap-around is treated. The data analysis problems associated with this phenomenon are solved by treating the 2D display as the surface of a three-dimensional cylinder. Based on this transformation we developed a new similarity metric for features as a function of both the cylindrical distance (reflecting similarity in chromatographic behavior) and of the mass spectral correlation (reflecting similarity in chemical structure). The concepts are used in warping and clustering, and include a protection against greedy warping. The methods were applied - for the purpose of an example - to the analysis of 11 replicates of a human urine sample concentrated by solid phase extraction. It is shown that the alignment is well protected against greedy warping which is important with respect to analytical qualities as robustness and repeatability. It is also demonstrated that chemically similar features are clustered together. The paper is organized as follows. First a brief introduction is provided addressing the background of the GC×GC-MS data structure followed by a theoretical section with a conceptual description of the procedures and details of the algorithms. Finally an example is given in the experimental section, illustrating the application of the procedures.

Representative drug sampling: sample size calculations revisited.

Calculating the required number of samples to be tested from a consignment of pills suspected of containing drugs can be performed from a Bayesian perspective. Procedures in literature are based on the outstanding work of Aitken. However, in the mathematical treatment of the problem, the limitedness of the consignment is not systematically used. The current Technical Note addresses this problem. A suitable prior distribution for the number of positive pills is derived, being a betabinomial distribution with the consignment size as one of the parameters. A hypergeometric likelihood is used, as sampling generally proceeds without replacement. The betabinomial posterior distribution is mathematically identical to the predictive distribution as reported elsewhere. The currently used large consignment approximation can be derived from the betabinomial posterior, but the quality is not optimal when compared to the exact betabinomial-based results. A new approximation is derived, with better properties, as illustrated in some examples.

A statistical approach to assess analytical sensitivity of diagnostic assays in the presence of false-positive results.

Analytical sensitivity is one of the performance characteristics of diagnostic tests. As always, a subtle balance has to be found between sensitivity and specificity, but given the clinical setting and the intended use of the diagnostic system, a less than 100% specificity can be perfectly acceptable. Probit analysis is a wide-spread statistical technique used to assess the concentrations corresponding to pre-set hit rates, but this technique assumes a 100% specificity. The current paper describes a statistical procedure, derived from the standard probit technique, to deal with the incidence of false-positive results in the assessment of the analytical sensitivity.

Sensitivity studies for quantitative assays: use of censored data analysis.

Probit regression analysis is frequently used to study the relation between the concentration of an analyte in a sample and the probability that the assay used yields a positive test result. For these analyses only the qualitative classification 'positive' or 'negative' is used, whereas, particularly in the case where the assay is quantitative in nature, the results contain more information. In the current paper, we propose an alternative method, in which the negative test results are treated as being (left) censored. As such, more efficient use is made of the information in the data. The procedures are illustrated using two generations of NucliSens assays (BioMérieux), which are designed to quantify the viral load of HIV-1 in blood samples. Computer simulations are used to illustrate some properties of the estimated parameters.

Stochastic processes defining sensitivity and variability of internally calibrated quantitative NASBA-based viral load assays.

For quantitative assessment of virus particles in patient plasma samples various assays are commercially available. Typical performance characteristics for such assays are sensitivity, precision and the range of linearity. In order to assess these properties it is common practice to divide the range of inputs into subranges in order to apply different statistical models to evaluate these properties separately. We developed a general statistical model for internally calibrated amplification based viral load assays that combines these statistical properties in one powerful analysis. Based on the model an unambiguous definition of the lower limit of the linear range can be given. The proposed method of analysis was illustrated by a successful application to data generated by the NucliSens EasyQ HIV-1 assay.

Mathematic modeling of the risk of HBV, HCV, and HIV transmission by window-phase donations not detected by NAT.

BACKGROUND: Blood transfusion centers around the world have introduced minipool NAT to reduce the risk of HBV, HCV, and HIV transmission by blood donations drawn in the infectious window phase. What would be the reduction in the residual risk when minipool NAT would be replaced by single-donation NAT? STUDY DESIGN AND METHODS: A mathematic model was developed to estimate the probability of virus transmission by blood transfusion when NAT screening methods are used for virologic safety testing. The major assumptions used are threefold: 1) The viral nucleic acid concentrations in the early window phase of infection double in 2.8 (HBV), 0.74 (HCV), and 0.90 (HIV) days. 2) The detectability of low copy numbers of viral DNA or RNA by the screening assay can be described with a probit model. 3) The probability of infection depends linearly on the logarithm of the administered dose, with 50-percent infectivity rates at 10 (HBV and HCV) or 1000 (HIV) viral nucleic acid copies per transfusion unit (estimates based on NAT studies with samples of known infectivity in chimpanzees). RESULTS: A reasonably simple equation was obtained that allows studying the effect of the sensitivity of the NAT assay and of the pool size used for screening on the residual risk of transfusion-transmitted infection. The computations are illustrated by using observed sensitivity estimates of various NAT methods. By using epidemiologic data among European donors over 1997 as baseline, the calculations predict that the incidence of virus transmission per 10-million RBC transfusions reduces with the following numbers when lowering the test pool size from 96 to 1 (single-donation testing): HBV from 11 to 13 to 3.3 to 5.1, HCV from 1.7 to 2.0 to 0.5 to 0.8, and HIV from 0.47 to 0.62 to 0.010 to 0.045 (ranges for the different NAT screening methods). CONCLUSION: A proper mathematic model for the calculation of residual infection risk by blood transfusion helps understand the impact of introducing new NAT methods for blood safety testing.

Principles of quantitation of viral loads using nucleic acid sequence-based amplification in combination with homogeneous detection using molecular beacons.

For quantitative NASBA-based viral load assays using homogeneous detection with molecular beacons, such as the NucliSens EasyQ HIV-1 assay, a quantitation algorithm is required. During the amplification process there is a constant growth in the concentration of amplicons to which the beacon can bind while generating a fluorescence signal. The overall fluorescence curve contains kinetic information on both amplicon formation and beacon binding, but only the former is relevant for quantitation. In the current paper, mathematical modeling of the relevant processes is used to develop an equation describing the fluorescence curve as a function of the amplification time and the relevant kinetic parameters. This equation allows reconstruction of RNA formation, which is characterized by an exponential increase in concentrations as long as the primer concentrations are not rate limiting and by linear growth over time after the primer pool is depleted. During the linear growth phase, the actual quantitation is based on assessing the amplicon formation rate from the viral RNA relative to that from a fixed amount of calibrator RNA. The quantitation procedure has been successfully applied in the NucliSens EasyQ HIV-1 assay.