Number Of Repeated Measurements Research Articles

Optimal Experimental Design for Parametric Identification of the Electrical Behaviour of Bioelectrodes and Biological Tissues

The electrical behaviour of a system, such as an electrode–tissue interface (ETI) or a biological tissue, can be used for its characterization. One way of accomplishing this goal consists of measuring the electrical impedance, that is, the opposition that a system exhibits to an alternating current flow as a function of frequency. Subsequently, experimental impedance data are fitted to an electrical equivalent circuit (EEC model) whose parameters can be correlated with the electrode processes occurring in the ETI or with the physiological state of a tissue. The EEC used in this paper is a reasonable approach for simple bio-electrodes or cell membranes, assuming ideal capacitances. We use the theory of optimal experimental design to identify the frequencies in which the impedance is measured, as well as the number of measurement repetitions, in such a way that the EEC parameters can be optimally estimated. Specifically, we calculate approximate and exact D-optimal designs by optimizing the determinant of the information matrix by adapting two of the most algorithms that are routinely used nowadays (REX random exchange algorithm and KL exchange algorithm). The D-efficiency of the optimal designs provided by the algorithms was compared with the design commonly used by experimenters and it is shown that the precision of the parameter estimates can be increased.

Application of the DAD method for damage localisation on an existing bridge structure using close-range UAV photogrammetry

A novel damage detection and localisation method, the so-called Deformation Area Difference method for localisation of damages in bridge structures is introduced. The method is based on static load-deflection experiments with the prerequisite of high precise deflection measurement. This study presents the first experiences of applying the DAD method on a real bridge structure. The investigated structure is a prestressed concrete slab bridge with a span of about 27 m, which was built in 2013. The loading on the bridge is applied using six heavy trucks, each weighing up to 32 t. A wide range of the modern measurement technologies were used to achieve high precision measurements of the bridge deflection along the longitudinal axis, namely the photogrammetry using a big size drone, laser scanner, total station, levelling and displacement sensors. The performed load-deflection test was non-destructive since the maximum deformation did not exceed the serviceability limit state. The exercise of the novel damage detection and localisation method on a real structure initiated further optimisation opportunities of the DAD method and the study of its limits. Several boundary conditions and methodical influence factors related to the applicability of the proposed method were analysed, such as impacts of measurement precision, damage degree, the position of damage, and the number of measurement repetitions.

A New Statistical Approach for the Evaluation of Gap-prepulse Inhibition of the Acoustic Startle Reflex (GPIAS) for Tinnitus Assessment.

Background: An increasingly used behavioral paradigm for the objective assessment of a possible tinnitus percept in animal models has been proposed by Turner and coworkers in 2006. It is based on gap-prepulse inhibition (PPI) of the acoustic startle reflex (ASR) and usually referred to as GPIAS. As it does not require conditioning it became the method of choice to study neuroplastic phenomena associated with the development of tinnitus.Objective: It is still controversial if GPIAS is really appropriate for tinnitus screening, as the hypothesis that a tinnitus percept impairs the gap detection ability (“filling-in interpretation” is still questioned. Furthermore, a wide range of criteria for positive tinnitus detection in GPIAS have been used across different laboratories and there still is no consensus on a best practice for statistical evaluation of GPIAS results. Current approaches are often based on simple averaging of measured PPI values and comparisons on a population level without the possibility to perform valid statistics on the level of the single animal.Methods: A total number of 32 animals were measured using the standard GPIAS paradigm with varying number of measurement repetitions. Based on this data further statistical considerations were performed.Results: We here present a new statistical approach to overcome the methodological limitations of GPIAS. In a first step we show that ASR amplitudes are not normally distributed. Next we estimate the distribution of the measured PPI values by exploiting the full combinatorial power of all measured ASR amplitudes. We demonstrate that the amplitude ratios (1-PPI) are approximately lognormally distributed, allowing for parametrical testing of the logarithmized values and present a new statistical approach allowing for a valid and reliable statistical assessment of PPI changes in GPIAS.Conclusion: Based on our statistical approach we recommend using a constant criterion, which does not systematically depend on the number of measurement repetitions, in order to divide animals into a tinnitus and a non-tinnitus group. In particular, we recommend using a constant threshold based on the effect size as criterion, as the effect size, in contrast to the p-value, does not systematically depend on the number of measurement repetitions.

Spectral thresholding quantum tomography for low rank states

The estimation of high dimensional quantum states is an important statistical problem arising in current quantum technology applications. A key example is the tomography of multiple ions states, employed in the validation of state preparation in ion trap experiments (Häffner et al 2005 Nature 438 643). Since full tomography becomes unfeasible even for a small number of ions, there is a need to investigate lower dimensional statistical models which capture prior information about the state, and to devise estimation methods tailored to such models. In this paper we propose several new methods aimed at the efficient estimation of low rank states and analyse their performance for multiple ions tomography. All methods consist in first computing the least squares estimator, followed by its truncation to an appropriately chosen smaller rank. The latter is done by setting eigenvalues below a certain ‘noise level’ to zero, while keeping the rest unchanged, or normalizing them appropriately. We show that (up to logarithmic factors in the space dimension) the mean square error of the resulting estimators scales as where r is the rank, is the dimension of the Hilbert space, and N is the number of quantum samples. Furthermore we establish a lower bound for the asymptotic minimax risk which shows that the above scaling is optimal. The performance of the estimators is analysed in an extensive simulations study, with emphasis on the dependence on the state rank, and the number of measurement repetitions. We find that all estimators perform significantly better than the least squares, with the ‘physical estimator’ (which is a bona fide density matrix) slightly outperforming the other estimators.

Measurement of alkali content in Zhundong coal by LIBS method

Serious slagging and ash deposition issues occur in combustion of Zhundong coal in industrial power plants due to its high content of alkali (Na, K). In this study, Zhundong coal was treated by chemical methods to make a lot of coal samples with a large range of Na and K concentrations. The results of Inductively Coupled Plasma Spectroscopy (ICP) were used as known variables for the calibration and prediction of Na and K content using laser-induced breakdown spectrum (LIBS).The results showed the measurements of Na and K by LIBS had high sensitivity, low detection limit and low Root Mean Square Prediction Error (RMSEP). The lower element concentration the sample contained, the greater the RSD was. When the element concentration reached a certain value, the RSD of measurement became stable. A large number of repeated measurements can guarantee the accuracy of LIBS measurement. Because LIBS technology itself has the advantage of fast measurement，LIBS could be a valid method to achieve online measurement of alkali content in coal.

A Sensitive Replicate RQ-PCR of BCR ABL Transcripts Suggests That A Large Portion of Long Term Post Allogeneic SCT CML Patients Are in Deep MR and May Therefore Be Cured From Their Disease

AbstractAbstract 1690RQ-PCR has become the major method for the follow up of CML pts in the tyrosine kinase inhibitor (TKI) era. In CML pts undergoing allogeneic SCT (Allo-SCT) it has been shown that successive increase in quantitative BCR ABL transcript levels is in correlation with the clinical outcome and may serve as an early sign of disease relapse and an indication for a therapeutic intervention such as the addition of a TKI or DLI. However, the sensitivity of current RQ-PCR methods which is limited to approximately 10−4 in the majority of routine clinical laboratories, do not allow for the detection of very low BCR ABL transcript levels, and therefore RQ-PCR negativity cannot be regarded as CMR in the majority of pts. Studies of replicate RQ-PCR (rRQ-PCR) have shown that the number of measurement repetitions is relevant in the detection of rare transcripts and rRQ-PCR was found to be more sensitive than conventional RQ-PCR in TKI treated CML pts. We evaluated the role of rRQ-PCR in the detection of MRD in a cohort of long term post Allo-SCT CML patients. Samples from 12 CML pts (M=7, F=5), median age 43 y, at a median time of 85 months after SCT (range 28–136) were tested. SCT was myeloablative (n=6) or with RIC (n=6), from a matched sibling (n=7) or a MUD (n=5), in first chronic phase (CP1) (n=8) or at a later phase (n=4). rRQ-PCR was done in 82 replicates using the same conditions of conventional RQ-PCR. Results of rRQ-PCR are given in Table 1. 75% of the patients had negative RQ-PCR in all 82 wells, while 3 patients had positive results in 1 (1.2%), 2 (2.4%) and 6 (7.3%) wells, respectively, which was above the background determined in normal PB samples (6/901 positive wells, 0.66%). The sensitivity of rRQ-PCR was 10−5.5 or higher in all patients. Negative rRQ-PCR result was not related to the phase at SCT (CP1 vs. others), conditioning regimen (myeloablative vs. RIC), donor type (sibling vs. MUD) or the presence of GVHD. Median time from diagnosis to SCT was borderline longer in patients with positive rRQ-PCR results (61 vs. 25 months, p=0.08).Higher sensitivity RQ-PCR methods are able to further define subgroups of post BMT CML pts and allow for a more accurate follow up of MRD. We will present update clinical data at 1 year after rRQ-PCR determination.Table 1Results of rRQ-PCR.Patient numberDisease status at SCTConditioningTime from diagnosis to SCT (months)Time from SCT to rRQ-PCR (months)rRQ-PCR resultBCR ABL/ABL1 (IS)Total quantity of ABL transcriptsLevel of MR1APRIC97570575034.8MR5.52CP2MA6300.0000862705622.33CP2MA273480.0007393563237.54CP1RIC4520997521.8MR65CP1MA16340555768.9MR5.56CP1MA39300700630.1MR5.57CP1MA6400874247.9MR5.58CP1RIC61680.000048410673539CP1RIC33460938046.4MR5.510CP1RIC185801467748MR611APRIC6280776271.9MR5.512CP2MA3230860350.6MR5.5RIC reduced intensity conditioning; MA myeloablative conditioning; MR molecular response.1Average result of positive wells normalized to the international standard.PCR positive in 12, 63 and 24 wells of 82 tested. Disclosures:No relevant conflicts of interest to declare.

Determination of the electrokinetic potential of Rhizobium leguminosarum bv trifolii Rt24.2 using Laser Doppler Velocimetry — A methodological study

Electrokinetic potential ( ζ, zeta potential) is one of the parameters which characterize the physicochemical properties of the bacterial cell envelope. The term is often used in the context of adhesiveness of bacteria and biofilm formation. This work presents the methodological aspects of zeta potential determination in strain Rt24.2 of Rhizobium leguminosarum using Laser Doppler Velocimetry combined with Phase Analysis Light Scattering and changed electric field techniques. The influence of media (0.9% NaCl, 0.2% NaCl, TY, GYM, 79CA, 20E and M1), temperature of measurement, number of measurement repetitions, phase of culture, concentration of bacteria, and storage at low temperature on the value of electrokinetic potential was investigated and a comparison was drawn between live and dead bacteria. All of those factors modified the zeta potential, showing that these parameters should be precisely specified in studies of bacterial electrokinetic potential, which is not always done. The obtained results also indicated that the zeta potential of Rhizobium leguminosarum should be determined directly in samples without storage at a defined bacterial density. The measurement should be done only once in a sample inserted into the cell of a measuring device to eliminate changes occurring in the sample (increase of electrolytic conductivity) under the electric field used.

Accuracy criteria for measuring carbon and nitrogen concentrations in forest soil and litter samples

To establish accuracy criteria for measurements of carbon and nitrogen concentrations in forest litter and mineral soil, we examined the change in the coefficient of variance (CV) with the number of measurement repetitions, the distribution of CVs and the effect of analytical error on the variation of CV to suggest a threshold for detecting outliers. We analyzed the measurement values of 266 soil samples and 73 litter samples collected from various forests throughout Japan. The CV changed with the number of measurement values for soil samples, but not for litter samples. This finding suggested that the accuracy criterion of the CV of two measurement values should be applied only to CVs calculated from two measurement values. When the CV was calculated from two measurement values, variation in the CV did not differ among carbon concentration classes of soil samples; however, the variation did differ among carbon concentration classes of litter samples and nitrogen concentration classes of litter and soil samples. These differences suggested that accuracy criterion should be independently decided in each carbon and nitrogen concentration class. Variation in the CV was not strongly affected by the analytical error because variation in the blank value was very small compared with variation in the CV. The distribution of the CV did not differ from the normal distribution for litter samples, but it did differ for soil samples. Thus, we used the robust Huber’s m-estimator outlier test to decide a threshold to represent the accuracy criterion. The threshold value was almost constant among carbon concentration classes both for soil and litter samples, with mean values of 3.6% and 2.6%, respectively. Conversely, the threshold of outliers of soil and litter samples varied among nitrogen concentration classes. This suggested using different thresholds for each nitrogen concentration class. Moreover, by applying the calculated thresholds we showed that outliers accounted for approximately 30% of the data in almost all carbon and nitrogen concentration classes for soil samples and less than 20% in almost all carbon and nitrogen concentration classes for litter samples.

Do we need to know body anthropomorphic data whilst measuring abdominal pressure?

We read with interest the article byBecker et al. [1] looking at the cor-relation between directintraabdominal pressure (IAP) andpressures in the stomach obtained viaa balloon-tipped catheter in tenpatients with cirrhosis. We agree thatthe CiMON system needs to be clin-ically validated. However, we feel theauthors misinterpret their data statingthat the CiMON device cannot beregarded as a reliable substitute forstandard IAP measurement tech-niques, for the simple reason that nogold standard IAP technique wasused. The sample size is small, andthere are issues about themethodology.First, the statistical linear regres-sion analysis used suffers from anessential misconception. On average,approximately nine repeated sets ofmeasurements were collected fromten patients, giving a total of 90paired measurements. This meansthat there were two sources of varia-tion that have to be distinguished: thebetween-patients variation and thewithin-patients variation. This paperdeals mainly with the second kind ofvariation in view of the small samplesize and the (high) number ofrepeated measurements. However,instead of analysing the within-patients variation, the data weretreated as if they came from onepatient. Although it is not sure thatthis was the case, this kind of analysismay produce erroneous results [2, 3].Second, the major drawback isthat no clinically acceptable goldstandard method for IAP measure-ment like bladder pressure was used.We don’t agree with the statementthat the gold standard in experimen-tal studies is direct monitoring ofintraperitoneal pressure. This mayhold true for animal research; how-ever, this is not in accordance withthe latest recommendations for clin-ical research [4–6].Third, the population under studyis not homogeneous since somepatients were mechanically venti-lated, while others were not, and thedemographics were only brieflydescribed. The patient sample wasprobably more convenient than a realcohort sample, which is not a fair wayto validate a new measurementmethod [7]. The evolution ofabdominal wall compliance (Cab)could have been calculated as shownin Table 1 and Fig. 1.Finally, although the authors cor-rectly state some limitations of theirstudy, they try to explain the observeddifferences by alluding to the relativeposition of the probes. This suggeststhey do not consider the abdomen tobe primarily fluid in character, hencenot following the laws of Pascal. Isthis the case? Decramer [8] reportedindeed that gastric pressure swings indogs were not simply hydrostatic.This study found the abdomen notbehaving as a hydraulic system orliquid-filled container. However, theIAP differences observed in the dogsdisappeared when the abdominalcavity was filled with 2 l of saline.9] measuredpressures in the abdomen next to theventral abdominal wall and within thestomach of anaesthetised dogs, andconcluded there were three factorsaffecting IAP: gravity, uniform com-pression and shear deformation. In1996, Tzelepis [10] re-established theconcept that the abdomen behaves asa hydraulic system. Based on theavailable data, we hypothesise theimpact of the above-mentioned threefactors on the measurement of IAP isprobably not significant in the fullysedated mechanically ventilatedpatient with sepsis, capillary leak anda positive fluid balance, with orwithout neuromuscular blockingagents [11]. Therefore, in situationsof large amounts of intraperitonealfluid (as was the case in the presentstudy), the abdomen does probablybehave as a hydraulic container, and

Biological variation in inflammatory and hemostatic markers.

Concentrations of inflammatory and hemostatic variables are influenced by biological variation, which is the natural within-subject variation over time. The aim of this study was to determine fibrinogen, C-reactive protein (CRP), platelet aggregation, thrombin generation and prothrombin time (PT): (i) the number of repeated measurements needed to obtain the true habitual concentration of an individual; (ii) the recommended analytical imprecision for diagnosis and monitoring; (iii) the recommended analytical bias; (iv) the contribution of analytical imprecision to test result variability; (v) the index of individuality; (vi) the reference change value; and (vii) the seasonal variation. We collected 520 blood samples over a 1-year period from 40 healthy individuals, and determined the between-subject, within-subject and seasonal variation in fibrinogen, CRP, platelet aggregation, thrombin generation and PT. One or two repeated measurements were sufficient to establish the true habitual concentration, except for platelet aggregation and peak thrombin generation, where at least four and nine repeated measurements were needed, respectively. For diagnosis, the maximal recommended coefficient of analytical variation (CV) was 4%-27%, except for CRP (77.7%). For monitoring, these CVs were on average 3% lower. Recommended analytical bias varied between 1.7% and 33.2%. Finally, seasonal variation was observed in concentrations of fibrinogen and thrombin generation, which could explain approximately 11% of their total variation. This study provides insights into the biological variability of selected inflammatory and hemostatic markers, which can be used for sample size calculations and to determine the analytical quality specifications for their respective assays.

Differences in precision in bone mineral density measured by SXA and DXA: the NOREPOS study

The aims were to compare the precision (reliability) in single X-ray (SXA) and dual X-ray (DXA) absorptiometry, and to compare smallest detectable difference (SDD). An additional aim was to examine determinants for precision in bone mineral density (BMD). BMD was measured by SXA (DTX-100, Osteometer) in the forearm and by DXA (Lunar Expert) in the forearm and in the hip. Two measurements were performed at each site/method, and 195 of 207 participants had complete datasets. Participants were aged 47-49 and 71-74 years. The precision was estimated by Root Mean Square Standard Deviation (RMS SD) with 95% Confidence Interval (95%CI) and the corresponding coefficients of variation (CV%). Determinants (age, gender, BMD) were analysed by multiple linear regression with log (SD) and log (CV) as dependent variables. RMS SD tended to be largest in older women and in those with low BMD. RMS SD for SXA and DXA forearm was 4.6 (4.2-5.1) and 6.8 (6.1-7.4) and the corresponding CVs 1.0% and 1.4%. RMS SD for DXA hip was 11.0 (9.9-12.0) with CV 1.2%. To detect a 3% change in BMD one would need two repeated measurements by DXA in the distal forearm at each of two consultations, but only one measurement by SXA in the distal forearm and also only one measurement by DXA in the hip. Precision differed by type of densitometer affecting the number of repeated measurements needed to detect a given BMD difference.

Signal-to-noise ratio (SNR) as a measure of reproducibility: design, estimation, and application

This paper proposes the use of signal-to-noise ratio (SNR) as another index of a measurement’s reproducibility. We derive its maximum likelihood estimation and discuss confidence interval construction within the framework of the one-way random effect model. We investigate the validity of the approximate normal confidence interval by Monte-Carlo simulations. The paper also derives the optimal allocation for the number of subject and the number of repeated measurements needed to minimize the variance of the maximum likelihood estimator of the SNR. We discuss efficiency in estimation and cost considerations for the optimal allocation of the sample resources. The approach is illustrated on two examples: one from MRI data and the other on the WHO immunization coverage data.

Just how much data need to be collected for reliable bootstrap DT‐MRI?

Diffusion tensor MRI (DT-MRI) can provide estimates of fiber orientation derived from the orientational dependence of the diffusivity of water molecules, enabling the reconstruction of white matter fiber pathways using tractography methods. However, noise arising from various sources can introduce uncertainty into the estimates of the elements of the diffusion tensor, resulting in errors in fiber orientation estimates such that tractography reconstructions of fiber pathways potentially can be imprecise and inaccurate. Recently, attempts have been made to characterize the uncertainty in DT-MRI-derived parameters using the bootstrap method; however, several questions remain open regarding the number of repeat measurements and bootstraps required to accurately and precisely reconstruct the probability distributions of the DT-MRI parameters. This study investigates the accuracy and precision of the bootstrap method for characterizing distributions of DT-MRI parameters. A number of experimental bootstrap designs and sampling schemes containing different numbers of isotropically distributed gradient vectors are considered, using an idealized system where the true variability in each parameter is known. This study demonstrates that for most DT-MRI experiments, robust results will be obtained if the minimum number of bootstraps is approximately 500, and that at least five repeat samples of each diffusion-weighted intensity should be used for bootstrapping.

Functional linear regression analysis for longitudinal data

We propose nonparametric methods for functional linear regression which are designed for sparse longitudinal data, where both the predictor and response are functions of a covariate such as time. Predictor and response processes have smooth random trajectories, and the data consist of a small number of noisy repeated measurements made at irregular times for a sample of subjects. In longitudinal studies, the number of repeated measurements per subject is often small and may be modeled as a discrete random number and, accordingly, only a finite and asymptotically nonincreasing number of measurements are available for each subject or experimental unit. We propose a functional regression approach for this situation, using functional principal component analysis, where we estimate the functional principal component scores through conditional expectations. This allows the prediction of an unobserved response trajectory from sparse measurements of a predictor trajectory. The resulting technique is flexible and allows for different patterns regarding the timing of the measurements obtained for predictor and response trajectories. Asymptotic properties for a sample of n subjects are investigated under mild conditions, as n→∞, and we obtain consistent estimation for the regression function. Besides convergence results for the components of functional linear regression, such as the regression parameter function, we construct asymptotic pointwise confidence bands for the predicted trajectories. A functional coefficient of determination as a measure of the variance explained by the functional regression model is introduced, extending the standard R2 to the functional case. The proposed methods are illustrated with a simulation study, longitudinal primary biliary liver cirrhosis data and an analysis of the longitudinal relationship between blood pressure and body mass index.

Some statistical aspects of food intake assessment.

To present the results of the statistical working group of the EFCOSUM project on estimating the minimum sample size for a pan-European dietary survey. Numerous statistical issues are involved when planning a nutritional survey aimed at evaluating various indicators, especially if it will be carried out in different countries. The plenary workshop of the EFCOSUM project has chosen four relevant statistical topics: the sample size estimation for dietary surveys, the number of repeated measurements needed to estimate usual intake for each individual; the statistical presentation of data; and the statistical procedures for estimating the usual intake distribution from a limited number of days of observation. This article deals with the first three topics mentioned. The participants of the EFCOSUM project answered a small questionnaire in order to get agreement on the method of estimating a minimum sample size in the context of a monitoring of dietary indicators. Data on the variability of dietary indicators of interest was also collected, in order to calculate a minimum sample size. The main result was that a minimum sample size of 2000 adults in each European country will be needed in order to identify trends in the mean intake of the most relevant foods and nutrients in Europe. This sample size should be higher if trends have to be indentified for socio-demographic subgroups.

Test di permutazione multidimensionali per misure ripetute: applicazioni alle curve di crescita tumorali in modelli animali

This paper deals with an application of non parametric multivariate permutation methods (Pesarin, 1992, 1997, 1999) for the comparison of cancer growth patterns in animal models. The analyzed data come from an experiment whose purpose consists of revealing the anticancer activity of a new taxol synthetic drug. We are interested in testing if the growth inhibition effect due to treatment is statistically significant. To compare treated with untreated growths we face some multivariate testing problems related with repeated measures. A parametric approach for the solution of these hypotheses testing problems is not possible because in our case the number of observed units is less then the number of repeated measures.