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Sensors (Basel, Switzerland) Mar 2021There is conflicting evidence regarding the health implications of high occupational physical activity (PA). Shoe-based accelerometers could provide a feasible solution...
There is conflicting evidence regarding the health implications of high occupational physical activity (PA). Shoe-based accelerometers could provide a feasible solution for PA measurement in workplace settings. This study aimed to develop calibration models for estimation of energy expenditure (EE) from shoe-based accelerometers, validate the performance in a workplace setting and compare it to the most commonly used accelerometer positions. Models for EE estimation were calibrated in a laboratory setting for the shoe, hip, thigh and wrist worn accelerometers. These models were validated in a free-living workplace setting. Furthermore, additional models were developed from free-living data. All sensor positions performed well in the laboratory setting. When the calibration models derived from laboratory data were validated in free living, the shoe, hip and thigh sensors displayed higher correlation, but lower agreement, with measured EE compared to the wrist sensor. Using free-living data for calibration improved the agreement of the shoe, hip and thigh sensors. This study suggests that the performance of a shoe-based accelerometer is similar to the most commonly used sensor positions with regard to PA measurement. Furthermore, it highlights limitations in using the relationship between accelerometer output and EE from a laboratory setting to estimate EE in a free-living setting.
Topics: Accelerometry; Calibration; Energy Metabolism; Exercise; Shoes
PubMed: 33810616
DOI: 10.3390/s21072333 -
European Biophysics Journal : EBJ May 2021Analytical ultracentrifugation (AUC) is based on the concept of recording and analyzing macroscopic macromolecular redistribution that results from a centrifugal force...
Analytical ultracentrifugation (AUC) is based on the concept of recording and analyzing macroscopic macromolecular redistribution that results from a centrifugal force acting on the mass of suspended macromolecules in solution. Since AUC rests on first principles, it can provide an absolute measurement of macromolecular mass, sedimentation and diffusion coefficients, and many other quantities, provided that the solvent density and viscosity are known, and provided that the instrument is properly calibrated. Unfortunately, a large benchmark study revealed that many instruments exhibit very significant systematic errors. This includes the magnification of the optical detection system used to determine migration distance, the measurement of sedimentation time, and the measurement of the solution temperature governing viscosity. We have previously developed reference materials, tools, and protocols to detect and correct for systematic measurement errors in the AUC by comparison with independently calibrated standards. This 'external calibration' resulted in greatly improved precision and consistency of parameters across laboratories. Here we detail the steps required for calibration of the different data dimensions in the AUC. We demonstrate the calibration of three different instruments with absorbance and interference optical detection, and use measurements of the sedimentation coefficient of NISTmAb monomer as a test of consistency. Whereas the measured uncorrected sedimentation coefficients span a wide range from 6.22 to 6.61 S, proper calibration resulted in a tenfold reduced standard deviation of sedimentation coefficients. The calibrated relative standard deviation and mean error of 0.2% and 0.07%, respectively, is comparable with statistical errors and side-by-side repeatability in a single instrument.
Topics: Calibration; Macromolecular Substances; Solvents; Ultracentrifugation; Viscosity
PubMed: 33398460
DOI: 10.1007/s00249-020-01485-2 -
Annals of Laboratory Medicine Jan 2023Calibration is a critical component for the reliability, accuracy, and precision of mass spectrometry measurements. Optimal practice in the construction, evaluation, and... (Review)
Review
BACKGROUND
Calibration is a critical component for the reliability, accuracy, and precision of mass spectrometry measurements. Optimal practice in the construction, evaluation, and implementation of a new calibration curve is often underappreciated. This systematic review examined how calibration practices are applied to liquid chromatography-tandem mass spectrometry measurement procedures.
METHODS
The electronic database PubMed was searched from the date of database inception to April 1, 2022. The search terms used were "calibration," "mass spectrometry," and "regression." Twenty-one articles were identified and included in this review, following evaluation of the titles, abstracts, full text, and reference lists of the search results.
RESULTS
The use of matrix-matched calibrators and stable isotope-labeled internal standards helps to mitigate the impact of matrix effects. A higher number of calibration standards or replicate measurements improves the mapping of the detector response and hence the accuracy and precision of the regression model. Constructing a calibration curve with each analytical batch recharacterizes the instrument detector but does not reduce the actual variability. The analytical response and measurand concentrations should be considered when constructing a calibration curve, along with subsequent use of quality controls to confirm assay performance. It is important to assess the linearity of the calibration curve by using actual experimental data and appropriate statistics. The heteroscedasticity of the calibration data should be investigated, and appropriate weighting should be applied during regression modeling.
CONCLUSIONS
This review provides an outline and guidance for optimal calibration practices in clinical mass spectrometry laboratories.
Topics: Calibration; Chromatography, Liquid; Humans; Mass Spectrometry; Reference Standards; Reproducibility of Results
PubMed: 36045052
DOI: 10.3343/alm.2023.43.1.5 -
PloS One 2023We propose a novel methodology for general multi-class classification in arbitrary feature spaces, which results in a potentially well-calibrated classifier. Calibrated...
We propose a novel methodology for general multi-class classification in arbitrary feature spaces, which results in a potentially well-calibrated classifier. Calibrated classifiers are important in many applications because, in addition to the prediction of mere class labels, they also yield a confidence level for each of their predictions. In essence, the training of our classifier proceeds in two steps. In a first step, the training data is represented in a latent space whose geometry is induced by a regular (n - 1)-dimensional simplex, n being the number of classes. We design this representation in such a way that it well reflects the feature space distances of the datapoints to their own- and foreign-class neighbors. In a second step, the latent space representation of the training data is extended to the whole feature space by fitting a regression model to the transformed data. With this latent-space representation, our calibrated classifier is readily defined. We rigorously establish its core theoretical properties and benchmark its prediction and calibration properties by means of various synthetic and real-world data sets from different application domains.
Topics: Calibration; Datasets as Topic
PubMed: 36649243
DOI: 10.1371/journal.pone.0279876 -
PLoS Computational Biology Oct 2022Spatiotemporal models that account for heterogeneity within microbial communities rely on single-cell data for calibration and validation. Such data, commonly collected... (Review)
Review
Spatiotemporal models that account for heterogeneity within microbial communities rely on single-cell data for calibration and validation. Such data, commonly collected via microscopy and flow cytometry, have been made more accessible by recent advances in microfluidics platforms and data processing pipelines. However, validating models against such data poses significant challenges. Validation practices vary widely between modelling studies; systematic and rigorous methods have not been widely adopted. Similar challenges are faced by the (macrobial) ecology community, in which systematic calibration approaches are often employed to improve quantitative predictions from computational models. Here, we review single-cell observation techniques that are being applied to study microbial communities and the calibration strategies that are being employed for accompanying spatiotemporal models. To facilitate future calibration efforts, we have compiled a list of summary statistics relevant for quantifying spatiotemporal patterns in microbial communities. Finally, we highlight some recently developed techniques that hold promise for improved model calibration, including algorithmic guidance of summary statistic selection and machine learning approaches for efficient model simulation.
Topics: Biota; Calibration; Machine Learning; Microbiota; Microscopy
PubMed: 36227846
DOI: 10.1371/journal.pcbi.1010533 -
Journal of Orthopaedic Research :... Jul 2022Radiostereometric analysis (RSA) is an accurate and precise radiographic method that can be used to measure micromotion of implants and study joint kinematics in vivo. A...
Radiostereometric analysis (RSA) is an accurate and precise radiographic method that can be used to measure micromotion of implants and study joint kinematics in vivo. A calibration cage with radiopaque markers is used to calibrate the RSA images; however, the thickness (250 mm) of the calibration cage restricts the available area for the patient and equipment during RSA recordings. A thinner calibration cage would increase the recording area, facilitate handling of the cage, and ease integration of the cage with the RSA system. We developed a thinner calibration cage without compromise of accuracy and precision. First, we performed numerical simulations of an RSA system, and showed that the calibration cage thickness could be decreased to 140 mm maintaining accuracy and precision using 40 fiducial and 30 control markers. Second, we constructed a new calibration cage (NRT cage) according to the simulation results. Third, we validated the new calibration cage against two state-of-the-art calibration cages (Umeaa cage and Leiden cage) in a phantom study. All cages performed similar for marker-based analysis, except for y-rotation, where the Umeaa cage (SD = 0.064 mm) was less precise compared to the NRT (SD = 0.038 mm) and Leiden cages (0.042 mm) (p = .01). For model-based analysis the NRT cage had superior precision for translations (SD ≤ 0.054 mm) over the Leiden cage (SD ≤ 0.118 mm) and Umeaa cage (SD ≤ 0.093 mm) (p < .01). The combined study confirmed that the new and thinner calibration cage maintained accuracy and precision at the level of existing thicker calibration cages.
Topics: Biomechanical Phenomena; Calibration; Humans; Phantoms, Imaging; Radiostereometric Analysis; Rotation
PubMed: 34664740
DOI: 10.1002/jor.25193 -
Mathematical Biosciences and... Jan 2022A Susceptible Infective Recovered (SIR) model is usually unable to mimic the actual epidemiological system exactly. The reasons for this inaccuracy include observation...
A Susceptible Infective Recovered (SIR) model is usually unable to mimic the actual epidemiological system exactly. The reasons for this inaccuracy include observation errors and model discrepancies due to assumptions and simplifications made by the SIR model. Hence, this work proposes calibration and prediction methods for the SIR model with a one-time reported number of infected cases. Given that the observation errors of the reported data are assumed to be heteroscedastic, we propose two predictors to predict the actual epidemiological system by modeling the model discrepancy through a Gaussian Process model. One is the calibrated SIR model, and the other one is the discrepancy-corrected predictor, which integrates the calibrated SIR model with the Gaussian Process predictor to solve the model discrepancy. A wild bootstrap method quantifies the two predictors' uncertainty, while two numerical studies assess the performance of the proposed method. The numerical results show that, the proposed predictors outperform the existing ones and the prediction accuracy of the discrepancy-corrected predictor is improved by at least 49.95%.
Topics: Calibration; Epidemiological Models; Uncertainty
PubMed: 35240807
DOI: 10.3934/mbe.2022128 -
Scientific Reports Apr 2022Electrochemical aptamer-based (EAB) sensors support the real-time, high frequency measurement of pharmaceuticals and metabolites in-situ in the living body, rendering...
Electrochemical aptamer-based (EAB) sensors support the real-time, high frequency measurement of pharmaceuticals and metabolites in-situ in the living body, rendering them a potentially powerful technology for both research and clinical applications. Here we explore quantification using EAB sensors, examining the impact of media selection and temperature on measurement performance. Using freshly-collected, undiluted whole blood at body temperature as both our calibration and measurement conditions, we demonstrate accuracy of better than ± 10% for the measurement of our test bed drug, vancomycin. Comparing titrations collected at room and body temperature, we find that matching the temperature of calibration curve collection to the temperature used during measurements improves quantification by reducing differences in sensor gain and binding curve midpoint. We likewise find that, because blood age impacts the sensor response, calibrating in freshly collected blood can improve quantification. Finally, we demonstrate the use of non-blood proxy media to achieve calibration without the need to collect fresh whole blood.
Topics: Aptamers, Nucleotide; Calibration; Vancomycin
PubMed: 35365672
DOI: 10.1038/s41598-022-09070-7 -
Sensors (Basel, Switzerland) Sep 2022Low-cost sensors can provide inaccurate data as temperature and humidity affect sensor accuracy. Therefore, calibration and data correction are essential to obtain...
Low-cost sensors can provide inaccurate data as temperature and humidity affect sensor accuracy. Therefore, calibration and data correction are essential to obtain reliable measurements. This article presents a training and testing method used to calibrate a sensor module assembled from SO2 and NO2 electrochemical sensors (Alphasense B4 and B43F) alongside air temperature (T) and humidity (RH) sensors. Field training and testing were conducted in the industrialized coastal area of Quintero Bay, Chile. The raw responses of the electrochemical (mV) and T-RH sensors were subjected to multiple linear regression (MLR) using three data segments, based on either voltage (SO2 sensor) or temperature (NO2). The resulting MLR equations were used to estimate the reference concentration. In the field test, calibration improved the performance of the sensors after adding T and RH in a linear model. The most robust models for NO2 were associated with data collected at T < 10 °C (R2 = 0.85), while SO2 robust models (R2 = 0.97) were associated with data segments containing higher voltages. Overall, this training and testing method reduced the bias due to T and HR in the evaluated sensors and could be replicated in similar environments to correct raw data from low-cost electrochemical sensors. A calibration method based on training and sensor testing after relocation is presented. The results show that the SO2 sensor performed better when modeled for different segments of voltage data, and the NO2 sensor model performed better when calibrated for different temperature data segments.
Topics: Air Pollutants; Calibration; Environmental Monitoring; Humidity; Nitrogen Dioxide
PubMed: 36236383
DOI: 10.3390/s22197281 -
Philosophical Transactions of the Royal... Jul 2016Evolutionary timescales have mainly used fossils for calibrating molecular clocks, though fossils only really provide minimum clade age constraints. In their place,... (Review)
Review
Evolutionary timescales have mainly used fossils for calibrating molecular clocks, though fossils only really provide minimum clade age constraints. In their place, phylogenetic trees can be calibrated by precisely dated geological events that have shaped biogeography. However, tectonic episodes are protracted, their role in vicariance is rarely justified, the biogeography of living clades and their antecedents may differ, and the impact of such events is contingent on ecology. Biogeographic calibrations are no panacea for the shortcomings of fossil calibrations, but their associated uncertainties can be accommodated. We provide examples of how biogeographic calibrations based on geological data can be established for the fragmentation of the Pangaean supercontinent: (i) for the uplift of the Isthmus of Panama, (ii) the separation of New Zealand from Gondwana, and (iii) for the opening of the Atlantic Ocean. Biogeographic and fossil calibrations are complementary, not competing, approaches to constraining molecular clock analyses, providing alternative constraints on the age of clades that are vital to avoiding circularity in investigating the role of biogeographic mechanisms in shaping modern biodiversity.This article is part of the themed issue 'Dating species divergences using rocks and clocks'.
Topics: Biological Evolution; Calibration; Evolution, Molecular; Fossils; Geology; Paleontology; Time
PubMed: 27325840
DOI: 10.1098/rstb.2016.0098