Reduce Measurement Variability Research Articles

Examining the Dimensions of the Bicipital Groove: A Human Cadaveric Study.

Introduction Understanding the mechanisms and risk factors associated with bicipital groove (BG) morphology is essential for optimizing patient outcomes. Despite interest in the topic of BG morphology, there remains a lack of clarity and consensus on the parameters of BG morphology due tosignificant methodological limitations in the existing research. The purpose of this study is to explore the dimensions of BG morphologywith a methodology rooted in recent research findings to better understand the human anatomy, potentially underpinning various shoulder pathologies. Methods The right shoulders of seventeen cadavers (nine male and eight female; median age of death: 88.0 years; age of death range: 66.0 - 97.0 years) were included in this cadaveric study. Dissection was done by removing the deltoid musculature and reflecting the long head of the biceps tendon to expose the BG. Measurements for BG morphology included BG width (millimeters, mm), depth (mm), and length (mm). Statistical comparisons were done between male and female measurements using the independent-samples Mann-Whitney U test due to the small sample size. Results The median width of the BG at the narrowest point was 4.3mm(mean: 4.7 ± 1.4 mm; range: 3.0 - 7.7 mm) with male cadavers having a significantly wider BG as compared to female cadavers (median: 5.0 mm versus 3.7 mm; p=0.006). The median depth of the BG was 5.1 mm (mean: 5.0 ± 0.7 mm; range: 3.8 - 6.3 mm) with no statistically significant differencebetween male and female cadavers (median: 4.8 mm versus 5.3 mm; p=0.370). The median length of the BG was 25.1 mm (mean: 25.1 ± 3.3 mm; range: 18.1 - 31.3 mm) with no statistically significant differencebetween male and female cadavers (median: 25.4 mm versus 23.9 mm; p=0.673). Conclusion The width of the BG at the narrowest point was significantly larger in male cadavers as compared to female cadavers in this study. However, there was no difference between male and female cadavers in terms of depth and length of the BG.This study contributes to the understanding of BG morphology by exploring the dimensions forwidth, depth, and length of the BG, which may contribute to biceps tendon pathology in clinical practice. Future research should focus on reducing measurement variability and exploring the possible relationship between BG morphology and biceps tendon conditions to further enhance the understanding of this complex relationship.

Do standardization of the procedure reduce measurement variability of the sonographic anterior drawer test of the ankle?

In quantitative ankle stress sonography, different examiners use different techniques, which may cause measurement variability. This study aimed to clarify whether standardizing stress sonography techniques reduces variability in the quantitative measurement of anterior talofibular ligament length change. Fourteen examiners with a mean ultrasound experience of 8.7 years participated in this study. Each examiner performed stress ultrasonography of the ankle using their preferred method on one patient with an intact anterior talofibular ligament (Patient 1) and on two patients with chronic ankle instability (Patient 2 and 3). Changes in the ligament length between the resting and stressed positions were determined. A consensus meeting was then conducted to standardize the sonographic technique, which was used by the examiners during a repeat stress sonography on the same patients. The variance and measured values were compared between the preferred and standardized techniques using F-tests and paired t-tests, respectively. At a consensus meeting, a sonographic technique in which the examiner pushed the lower leg posteriorly against the fixed foot was adopted as the standardized technique. In Patient 1, the change in the anterior talofibular ligament length was 0.4 (range,-2.3-1.3) mm and 0.6 (-0.6-1.7) mm using the preferred and standardized techniques, respectively, with no significant difference in the variance (P=0.51) or the measured value (P=0.52). The length changes in Patient 2 were 2.0 (0.3-4.4) mm and 1.7 (-0.9-3.8) mm using the preferred and standardized techniques, respectively. In Patient 3, the length changes were 1.4 (-2.7-7.1) mm and 0.7 (-2.0-2.3) mm. There were no significant differences between the techniques in either patient group. Variability in the quantitative measurement of ankle stress sonography was not reduced despite the standardization of the technique among examiners. Hence, comparing the measured values between different examiners should be avoided.

Crowdsourcing Subjective Annotations Using Pairwise Comparisons Reduces Bias and Error Compared to the Majority-vote Method

How to better reduce measurement variability and bias introduced by subjectivity in crowdsourced labelling remains an open question. We introduce a theoretical framework for understanding how random error and measurement bias enter into crowdsourced annotations of subjective constructs. We then propose a pipeline that combines pairwise comparison labelling with Elo scoring, and demonstrate that it outperforms the ubiquitous majority-voting method in reducing both types of measurement error. To assess the performance of the labelling approaches, we constructed an agent-based model of crowdsourced labelling that lets us introduce different types of subjectivity into the tasks. We find that under most conditions with task subjectivity, the comparison approach produced higher f1 scores. Further, the comparison approach is less susceptible to inflating bias, which majority voting tends to do. To facilitate applications, we show with simulated and real-world data that the number of required random comparisons for the same classification accuracy scales log-linearly O(N log N) with the number of labelled items. We also implemented the Elo system as an open-source Python package.

Laser Fluence Dependent Modulation of Single Walled Carbon Nanotube Photoluminescence

Single-walled carbon nanotubes (SWCNT) have a unique, non-photobleaching, bandgap photoluminescence (PL) that has been of interest for sensor development. Take advantage of these properties, colloidal dispersions of single SWCNTs in aqueous solvents are often formed by creating a surface corona phase (CP) using amphiphilic materials. As SWCNT PL emission following photoexcitation can be significantly dependent on its local environment, the CP can be used to tune its photophysical properties, often as a design parameter for sensor development. Recent sensor experiments have shown that reporting and controlling laser excitation can be a method to significantly reduce measurement variability. In this work, we study this phenomenon of excitation fluence (EF) (mW/area) dependent PL modulation for aqueous dispersed SWCNTs. By using a continuously stirred chamber excited at a single location, the stirring rate can be a means of controlling SWCNT excitation exposure. SWCNT wrapped in both DNA and SDS SWCNT CPs showed a decreased quantum yield of nearly 40% with increasing EF while those with sodium cholate and phospholipid-PEG CPs remain invariant. Through spectroscopy and heat transfer modeling, we determined that the observed effect is unlikely to have a significant direct local solution heating contribution from SWNCT photoabsorption. Finally, we used previously studied SWCNT sensor constructs, for ascorbic acid and dopamine, to show how EF can affect calibration and eventual sensor applications. This work highlights the importance of measuring, testing, reporting and controlling for EF while developing SWCNT based photophysical sensors. This newly characterized property can also serve as a unique parameter to tune optical responsivity.

Deep Learning-Based CT Reconstruction Kernel Conversion in the Quantification of Interstitial Lung Disease: Effect on Reproducibility

The effect of different computed tomography (CT) reconstruction kernels on the quantification of interstitial lung disease (ILD) has not been clearly demonstrated. The study aimed to investigate the effect of reconstruction kernels on the quantification of ILD on CTand determine whether deep learning-based kernel conversion can reduce the variability of automated quantification results between different CT kernels. Patients with ILD or interstitial lung abnormality who underwent noncontrast high-resolution CT between June 2022 and September 2022 were retrospectively included. Images were reconstructed with three different kernels: B30f, B50f, and B60f. B60f was regarded as the reference standard for quantification, and B30f and B50f images were converted to B60f images using a deep learning-based algorithm. Each disease pattern of ILD and the fibrotic score were quantified using commercial software. The effect of kernel conversion on measurement variability was estimated using intraclass correlation coefficient (ICC) and Bland-Altman method. A total of 194 patients were included in the study. Application of different kernels induced differences in the quantified extent of each pattern. Reticular opacity and honeycombing were underestimated on B30f images and overestimated on B50f images. After kernel conversion, measurement variability was reduced (mean difference, from -2.0 to 3.9 to -0.3 to 0.4%, and 95% limits of agreement [LOA], from [-5.0, 12.7] to [-2.7, 2.1]). The fibrotic score for converted B60f from B50f images was almost equivalent to the original B60f (ICC, 1.000; mean difference, 0.0; and 95% LOA[-0.4, 0.4]). Quantitative CT analysis of ILD was affected by the application of different kernels, but deep learning-based kernel conversion effectively reduced measurement variability, improving the reproducibility of quantification.

Normalization of Flow-mediated Dilation to Brachial Artery Material Property: A Feasibility Study.

Endothelial reactivity (ER) is widely measured using flow-mediated dilation (FMD) of brachial artery. Conventional measurement of FMD is influenced by factors such as input shear stress, arterial transmural pressure, diameter and thereby arterial material properties (ε). Thus, for a reliable interpretation of FMD, it has to be normalized with respect to the above confounding factors. Normalization of FMD with shear stress at the time of measurement has been reported to reduce measurement variability. However, its widespread usage among the research community is limited. In this work, we examine the feasibility of normalizing the brachial FMD index (FMD%) to ε : extrema (εp), baseline (εb) and extrema change (∆ε) post-ischemia using its inter-day variability against FMD. In-vivo measurements were performed on 10 participants for 2 consecutive days and simultaneous pressure-diameter cycles were collected to estimate the material properties during reactive hyperemia (RH). The box-whisker plot reveals differences in the mean and deviation of FMD to FMD|εb. A significant value for repeatability (ICC ≥ 0.6) was obtained for normalized FMD (FMD|εb) for specific stiffness index (β), pressure-strain elastic modulus (Ep), and local pulse wave velocity (PWV) as compared to FMD. Hence, normalization of FMD% to arterial ε can potentially improve the measurement reliability of ER assessment.Clinical Relevance- This pilot study demonstrates the feasibility of brachial artery stiffness assessment during FMD and its potential use for normalizing the standard FMD measurement.

Your Vestibular Thresholds May Be Lower Than You Think: Cognitive Biases in Vestibular Psychophysics.

Recently, there has been a surge of interest in measuring vestibular perceptual thresholds, which quantify the smallest motion that a subject can reliably perceive, to study physiology and pathophysiology. These thresholds are sensitive to age, pathology, and postural performance. Threshold tasks require decisions to be made in the presence of uncertainty. Since humans often rely on past information when making decisions in the presence of uncertainty, we hypothesized that (a) perceptual responses are affected by their preceding trial; (b) perceptual responses tend to be biased opposite of the "preceding response" because of cognitive biases but are not biased by the "preceding stimulus"; and (c) when fits do not account for this cognitive bias, thresholds are overestimated. To our knowledge, these hypotheses are unaddressed in vestibular and direction-recognition tasks. Results in normal subjects supported each hypothesis. Subjects tended to respond opposite of their preceding response (not the preceding stimulus), indicating a cognitive bias, and this caused an overestimation of thresholds. Using an enhanced model (MATLAB code provided) that considered these effects, average thresholds were lower (5.5% for yaw, 7.1% for interaural). Since the results indicate that the magnitude of cognitive bias varies across subjects, this enhanced model can reduce measurement variability and potentially improve the efficiency of data collection.

Interlaboratory Study on Brake Particle Emissions Part II: Particle Number Emissions

The Particle Measurement Programme (PMP) informal working group co-ordinated a global interlaboratory study (ILS) on brake wear particle emissions with the participation of 16 laboratories in 2021. Two articles present the results of the ILS: (I) particulate matter mass (PM) and (II) particle number (PN) emissions. The test matrix covered different brake systems, including ECE and NAO pad materials with grey cast iron discs and a drum brake. Regarding PN, the study measured the total particle number from approximately 10 nm to 2.5 µm (TPN). Some testing facilities measured solid particle number emissions (SPN) in parallel. The mean TPN concentrations ranged from 9.1 × 108 #/km/brake to 1.1 × 1010 #/km/brake. TPN and SPN emission levels were comparable, except for one lab that measured very high volatile particle emissions for one brake system. The minimum and maximum SPN emissions for a given brake differed by a factor of 2.5 ± 0.5, comparable to data from exhaust SPN ILS measurements. This article provides an overview of lessons learned and subsequent measures incorporated in an upcoming global technical regulation to reduce measurement variability when sampling and measuring brake particle emissions for light-duty vehicles up to 3.5 t.

Accuracy of in vivo microCT imaging in assessing the microstructural properties of the mouse tibia subchondral bone.

Osteoarthritis (OA) is one of the most common musculoskeletal diseases. OA is characterized by degeneration of the articular cartilage as well as the underlying subchondral bone. Post-traumatic osteoarthritis (PTOA) is a subset of OA caused by mechanical trauma. Mouse models, such as destabilization of the medial meniscus (DMM), are useful to study PTOA. Ex vivo micro-Computed Tomography (microCT) imaging is the predominant technique used to scan the mouse knee in OA studies. Nevertheless, in vivo microCT enables the longitudinal assessment of bone microstructure, reducing measurement variability and number of animals required. The effect of image resolution in measuring subchondral bone parameters was previously evaluated only for a limited number of parameters. The aim of this study was to evaluate the ability of in vivo microCT imaging in measuring the microstructural properties of the mouse tibia trabecular and cortical subchondral bone, with respect to ex vivo high resolution imaging, in a DMM model of PTOA. Sixteen male C57BL/6J mice received DMM surgery or sham operation at 14 weeks of age (N=8 per group). The right knee of each mouse was microCT scanned in vivo (10.4μm voxel size) and ex vivo (4.35μm voxel size) at the age of 26 weeks. Each image was aligned to a reference image using rigid registration. The subchondral cortical bone plate thickness was measured at the lateral and medial condyles. Standard morphometric parameters were measured in the subchondral trabecular bone. In vivo microCT imaging led to significant underestimation of bone volume fraction (-14%), bone surface density (-3%) and trabecular number (-16%), whereas trabecular thickness (+3%) and separation (+5%) were significantly overestimated. Nevertheless, most trabecular parameters measured in vivo were well correlated with ex vivo measurements (R2 = 0.69-0.81). Degree of anisotropy, structure model index and connectivity density were measured in vivo with lower accuracy. Excellent accuracy was found for cortical thickness measurements. In conclusion, this study identified what bone morphological parameters can be reliably measured by in vivo microCT imaging of the subchondral bone in the mouse tibia. It highlights that this approach can be used to study longitudinal effects of diseases and treatments on the subchondral cortical bone and on most subchondral trabecular bone parameters, but systematic over- or under-estimations should be considered when interpreting the results.

Measuring ammonia concentrations by an infrared photo-acoustic multi-gas analyser in an open dairy barn: Repetitions planning strategy

The infrared photoacoustic spectroscopy is a common gas sensing technique used for research activities to perform continuous measurement of gas concentrations. Few research works have investigated how to collect data and obtain reliable measurements in open and semi-open dairy houses for gas concentration estimation.In the present study, measurements of ammonia (NH3) concentrations were carried out in a semi-open free-stall dairy barn by using a commercial photo-acoustic spectroscopy system (INNOVA by LumaSense Technologies A/S, Denmark), widely used for scientific purposes. Several repetitions for each sampling location (SLs) were investigated in in-field conditions to study the variability of the measurement in each repetition. Based on acquired data, one-way analyses of variance (ANOVA) were carried out for different groups of data. The achieved results showed that the measurement strategy depended on the number of repetitions with effect on the variability of each measurement. In detail, the number of repetitions performed had a significant influence on data collection (P < 0.001). From the outcomes of the research, it is recommended to: perform three repetitions, or at most, four repetitions for each SLs; exclude the first repetition from the data analyses because it reduces measurement variability; consider the mean value of the second and third repetitions as the NH3 concentration value determined at each SL; up to four repetitions (that would take a five-minutes acquisition) are recommended because measurement changed in time when a higher number of repetitions were carried out. The measurement design should be planned based on the number of repetitions and the number of SLs in order to perform more than one SL measurement cycle within an hour. Since the measurement cycles are strictly related to the number of SLs in the barn, they depend on the barn typology and dimensions.The application of a specific measurement strategy is valuable to obtain reliable data that could be used in the research activities focused on estimation of gas concentrations for monitoring air quality, improving animal welfare, assessing mitigation strategies, or estimating emissions in open and semi-open free-stall dairy barns.

Internal auditory canal volume in normal and malformed inner ears

PurposeA narrow bony internal auditory canal (IAC) may be associated with a hypoplastic cochlear nerve and poorer hearing performances after cochlear implantation. However, definitions for a narrow IAC vary widely and commonly, qualitative grading or two-dimensional measures are used to characterize a narrow IAC. We aimed to refine the definition of a narrow IAC by determining IAC volume in both control patients and patients with inner ear malformations (IEMs).MethodsIn this multicentric study, we included high-resolution CT (HRCT) scans of 128 temporal bones (85 with IEMs: cochlear aplasia, n = 11; common cavity, n = 2; cochlear hypoplasia type, n = 19; incomplete partition type I/III, n = 8/8; Mondini malformation, n = 16; enlarged vestibular aqueduct syndrome, n = 19; 45 controls). The IAC diameter was measured in the axial plane and the IAC volume was measured by semi-automatic segmentation and three-dimensional reconstruction.ResultsIn controls, the mean IAC diameter was 5.5 mm (SD 1.1 mm) and the mean IAC volume was 175.3 mm3 (SD 52.6 mm3). Statistically significant differences in IAC volumes were found in cochlear aplasia (68.3 mm3, p < 0.0001), IPI (107.4 mm3, p = 0.04), and IPIII (277.5 mm3, p = 0.0004 mm3). Inter-rater reliability was higher in IAC volume than in IAC diameter (intraclass correlation coefficient 0.92 vs. 0.77).ConclusionsVolumetric measurement of IAC in cases of IEMs reduces measurement variability and may add to classifying IEMs. Since a hypoplastic IAC can be associated with a hypoplastic cochlear nerve and sensorineural hearing loss, radiologic assessment of the IAC is crucial in patients with severe sensorineural hearing loss undergoing cochlear implantation.

Algorithmic Correction of MOS Gas Sensor for Ambient Temperature and Relative Humidity Fluctuations

In ambient conditions, uncontrolled fluctuations of ambient temperature and relative humidity significantly reduce the accuracy of metal oxide semiconductor-based gas sensors. The main innovation of the work is an algorithmic self-correction method that employs a response from an auxiliary temperature sensor and a multivariable polynomial regression model to minimize the effect of such environmental fluctuations. Tin oxide (SnO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) MOS gas sensors were chosen for a sample study due to their fast response times and high resolution. Using the developed correction method, the study analyzes sensor accuracy while measuring a typical pollutant gas (carbon monoxide) over a temperature range from −10 to 40°C at relative humidity intervals of 35%, 65%, and 95%. On average, the corrected sensors measured a 40 ppm CO gas sample with 11 times more accuracy when compared to uncorrected sensors placed in the same variable ambient conditions. Corroborating ANOVA tests demonstrated that the prescribed correction algorithm reduced measurement variability with statistical significance. In the presence of CO2, CH4, ethanol, LPG, or smoke interference gas samples, sensors applying the correction method and temperature-based selectivity distinguished and measured CO concentrations with a maximum error of only ±2.0 ppm. Thus, the proposed technical solution is attractive for highly variable environments and field applications where low-cost drift stabilization is necessary.

Deep Learning Automation of Kidney, Liver, and Spleen Segmentation for Organ Volume Measurements in Autosomal Dominant Polycystic Kidney Disease.

Organ volume measurements are a key metric for managing ADPKD (the most common inherited renal disease). However, measuring organ volumes is tedious and involves manually contouring organ outlines on multiple cross-sectional MRI or CT images. The automation of kidney contouring using deep learning has been proposed, as it has small errors compared to manual contouring. Here, a deployed open-source deep learning ADPKD kidney segmentation pipeline is extended to also measure liver and spleen volumes, which are also important. This 2D U-net deep learning approach was developed with radiologist labeled T2-weighted images from 215 ADPKD subjects (70% training = 151, 30% validation = 64). Additional ADPKD subjects were utilized for prospective (n = 30) and external (n = 30) validations for a total of 275 subjects. Image cropping previously optimized for kidneys was included in training but removed for the validation and inference to accommodate the liver which is closer to the image border. An effective algorithm was developed to adjudicate overlap voxels that are labeled as more than one organ. Left kidney, right kidney, liver and spleen labels had average errors of 3%, 7%, 3%, and 1%, respectively, on external validation and 5%, 6%, 5%, and 1% on prospective validation. Dice scores also showed that the deep learning model was close to the radiologist contouring, measuring 0.98, 0.96, 0.97 and 0.96 on external validation and 0.96, 0.96, 0.96 and 0.95 on prospective validation for left kidney, right kidney, liver and spleen, respectively. The time required for manual correction of deep learning segmentation errors was only 19:17 min compared to 33:04 min for manual segmentations, a 42% time saving (p = 0.004). Standard deviation of model assisted segmentations was reduced to 7, 5, 11, 5 mL for right kidney, left kidney, liver and spleen respectively from 14, 10, 55 and 14 mL for manual segmentations. Thus, deep learning reduces the radiologist time required to perform multiorgan segmentations in ADPKD and reduces measurement variability.

Assessing the Variability of Cell-Associated HIV DNA Quantification through a Multicenter Collaborative Study.

ABSTRACTReliable and accurate quantification of cell-associated HIV DNA (CA HIV DNA) is critical for early infant diagnosis, clinical management of patients under therapy, and to inform new therapeutics efficacy. The present study assessed the variability of CA HIV DNA quantification obtained from various assays and the value of using reference materials to help harmonize the measurements. Using a common set of reagents, our multicenter collaborative study highlights significant variability of CA HIV DNA quantification and lower limit of quantification across assays. The quantification of CA HIV DNA from a panel of infected PBMCs can be harmonized through cross-subtype normalization but assay calibration with the commonly used 8E5 cell line failed to reduce quantification variability between assays, demonstrating the requirement to thoroughly evaluate reference material candidates to help improve the comparability of CA HIV DNA diagnostic assay performance.IMPORTANCE Despite a global effort, HIV remains a major public health burden with an estimated 1.5 million new infections occurring in 2020. HIV DNA is an important viral marker, and its monitoring plays a critical role in the fight against HIV: supporting diagnosis in infants and underpinning clinical management of patients under therapy. Our study demonstrates that HIV DNA measurement of the same samples can vary significantly from one laboratory to another, due to heterogeneity in the assay, protocol, and reagents used. We show that when carefully selected, reference materials can reduce measurement variability and harmonize HIV DNA quantification across laboratories, which will help contribute to improved diagnosis and clinical management of patients living with HIV.

Application of computer-aided diagnosis for Lung-RADS categorization in CT screening for lung cancer: effect on inter-reader agreement.

To evaluate the effects of computer-aided diagnosis (CAD) on inter-reader agreement in Lung Imaging Reporting and Data System (Lung-RADS) categorization. Two hundred baseline CT scans covering all Lung-RADS categories were randomly selected from the National Lung Cancer Screening Trial. Five radiologists independently reviewed the CT scans and assigned Lung-RADS categories without CAD and with CAD. The CAD system presented up to five of the most risk-dominant nodules with measurements and predicted Lung-RADS category. Inter-reader agreement was analyzed using multirater Fleiss κ statistics. The five readers reported 139-151 negative screening results without CAD and 126-142 with CAD. With CAD, readers tended to upstage (average, 12.3%) rather than downstage Lung-RADS category (average, 4.4%). Inter-reader agreement of five readers for Lung-RADS categorization was moderate (Fleiss kappa, 0.60 [95% confidence interval, 0.57, 0.63]) without CAD, and slightly improved to substantial (Fleiss kappa, 0.65 [95% CI, 0.63, 0.68]) with CAD. The major cause for disagreement was assignment of different risk-dominant nodules in the reading sessions without and with CAD (54.2% [201/371] vs. 63.6% [232/365]). The proportion of disagreement in nodule size measurement was reduced from 5.1% (102/2000) to 3.1% (62/2000) with the use of CAD (p < 0.001). In 31 cancer-positive cases, substantial management discrepancies (category 1/2 vs. 4A/B) between reader pairs decreased with application of CAD (pooled sensitivity, 85.2% vs. 91.6%; p = 0.004). Application of CAD demonstrated a minor improvement in inter-reader agreement of Lung-RADS category, while showing the potential to reduce measurement variability and substantial management change in cancer-positive cases. • Inter-reader agreement of five readers for Lung-RADS categorization was minimally improved by application of CAD, with a Fleiss kappa value of 0.60 to 0.65. • The major cause for disagreement was assignment of different risk-dominant nodules in the reading sessions without and with CAD (54.2% vs. 63.6%). • In 31 cancer-positive cases, substantial management discrepancies between reader pairs, referring to a difference in follow-up interval of at least 9 months (category 1/2 vs. 4A/B), were reduced in half by application of CAD (32/310 to 16/310) (pooled sensitivity, 85.2% vs. 91.6%; p = 0.004).

Analyzing the causes of method-to-method variability among Rubisco kinetic traits: from the first to the current measurements.

Due to the importance of Rubisco in the biosphere, its kinetic parameters have been measured by different methodologies in a large number of studies over the last 60 years. These parameters are essential to characterize the natural diversity in the catalytic properties of the enzyme and they are also required for photosynthesis and cross-scale crop modeling. The present compilation of Rubisco kinetic parameters in model species revealed a wide intraspecific laboratory-to-laboratory variability, which was partially solved by making corrections to account for differences in the assay buffer composition and in the acidity constant of dissolved CO2, as well as for differences in the CO2 and O2 solubilities. Part of the intraspecific variability was also related to the different analytical methodologies used. For instance, significant differences were found between the two main methods for the determination of the specificity factor (Sc/o), and also between Rubisco quantification methods, Rubisco purification versus crude extracts, and single-point versus CO2 curve measurements for the carboxylation turnover rate (kcatc) determination. Causes of the intraspecific laboratory-to-laboratory variability for Rubisco catalytic traits are discussed. This study provides a normalized kinetic dataset for model species to be used by the scientific community. Corrections and recommendations are also provided to reduce measurement variability, allowing the comparison of kinetic data obtained in different laboratories using different assay conditions.

Assessing the comfort of earplugs: development and validation of the French version of the COPROD questionnaire

Earplugs are a common form of protection for workers exposed to hazardous noise levels. Their comfort directly impacts the effective protection by influencing their consistent and correct use. Nevertheless, comfort definition may vary according to the studies. Thus, a previous review of the literature has shown that to improve our understanding of perceived comfort and to reduce measurement variability, it is advisable to consider comfort through a multidimensional construct (physical, acoustical, functional and psychological). On this basis, the COPROD (COnfort des PROtections auDitives/COmfort of hearing PROtection Devices) questionnaire was developed. It is intended for people working in noisy environments. Nine earplug models were evaluated by 118 participants over a six-week period. This paper presents the successive analyses that were used to validate the structure of the questionnaire and confirm the relevance of the proposed dimensions and of the addressed items. First results suggest a preference for custom moulded earplugs. Practitioner Summary: Earplugs comfort conditions the hearing protection of the users. As the definition of comfort can vary between studies, the COPROD questionnaire was developed to jointly evaluate all its dimensions. Nine earplugs models were evaluated by 118 participants during six weeks. This paper presents the validation process of the questionnaire. Abbreviations: COPROD: COnfort des PROtections auDitives/COmfort of hearing PROtection Devices; HPD: hearing protection devices; SEM: structural equation modeling; CFA: confirmatory factor analysis; GOF: goodness of fit; RMSEA: root mean square error of approximation; CFI: comparison fit index; SRMR: standardised root mean square residual

Using 3D image registration to maximize the reproducibility of longitudinal bone strength assessment by HR-pQCT and finite element analysis

We developed and validated a finite element (FE) approach for longitudinal high-resolution peripheral quantitative computed tomography (HR-pQCT) studies using 3D rigid-body registration (3DR) to maximize reproducibility by accounting for misalignment between images. In our proposed approach, we used the full common bone volume defined by 3DR to estimate standard FE parameters. Using standard HR-pQCT imaging protocols, we validated the 3DR approach with ex vivo samples of the distal radius (n = 10, four repeat scans) by assessing whether 3DR can reduce measurement variability from repositioning error. We used in vivo data (n = 40, five longitudinal scans) to assess the sensitivity of 3DR to detect changes in bone strength at the distal radius by the standard deviation of the rate of change (σ), where the ideal value of σ is minimized to define true change. FE estimates by 3DR were compared to estimates by no registration (NR) and slice-matching (SM). Group-wise comparisons of ex vivo variation (CVRMS, %) found that FE measurement precision was improved by SM (CVRMS < 0.80%) and 3DR (CVRMS < 0.62%) compared to NR (CVRMS~2%), and 3DR was advantageous as repositioning error increased. Longitudinal in vivo reproducibility was minimized by 3DR for failure load estimates (σ = 0.008 kN/month). Although 3D registration cannot negate motion artifacts, it plays an important role in detecting and reducing variability in FE estimates for longitudinal HR-pQCT data and is well suited for estimating effects of interventions in in vivo longitudinal studies of bone strength.

Sampling plan designs for gluten estimation in oat flour by discrete and composite sampling

Heterogeneous gluten distribution in certain food commodities, such as oat flour, warrants a sound sampling plan to reduce measurement variability and the risk associated with lot misclassification. Ten lots of oat flour, 45 kg each, with varying gluten content were produced in a pilot-scale hammer mill to evaluate various sampling plans for gluten in oat flour. Thirty-two samples from each lot were collected during milling to study the effect of discrete (individual samples taken from the lot) and composite (samples taken from a bulk sample prepared by compositing several individual samples) sampling methods. A 5 g test sample was manually taken from each of the 32 samples, extracted with a cocktail extraction buffer, and gluten content was estimated using ELISA by analyzing duplicate aliquots of the extract. The total variance (Vt) from gluten measurements was partitioned into variance between samples (Vs) and aliquots analyzed (Va). Regression analysis revealed a linear relationship between the log of all three variances and the log of gluten concentration, which can be explained by the power equation for discrete and composite sampling methods. The Vt and Vs for discrete sampling tended to be higher than those for composite sampling at a given gluten concentration. A log-normal distribution was found suitable to characterize the distribution of measured gluten in oat flour samples from a test procedure. Operating characteristic (OC) curves plotted to evaluate various sampling plans for gluten in oat flour showed reduced risk of misclassification for composite sampling, as compared to the discrete sampling method for a given sampling plan. Examples are shown for the change in OC curves depending on the sampling method, sample size, number of samples analyzed, and accept/reject limit.

The Current and Future Role of Echocardiography for the Detection of Cardiotoxicity Related to Cancer Therapy

The purpose of this review is to outline the role of echocardiography in identifying patients at increased cardiovascular risk for cancer treatment-associated cardiotoxicity. With a wide array of cancer therapeutics, a variety echocardiographic cardiotoxicity phenotypes have been identified. Recent consensus statements from several professional societies have provided a framework for risk assessment prior to cancer therapy that involves assessment and optimization of cardiac risk factors but also involves echocardiographic evaluation of left ventricular (LV) function at baseline, during, and after treatment. While newer echocardiographic techniques such as global longitudinal strain are key to detecting subclinical cardiotoxicity, it is as yet unclear if strain-directed initiation of cardioprotective medications will result in better outcomes. This is the subject of an ongoing clinical trial, the results of which are eagerly awaited. Given the serial nature of echocardiographic assessments in the cancer population, the application of automated techniques for ejection fraction and strain may have the potential to further reduce measurement variability and are also subjects of ongoing research. Echocardiography is the preferred imaging modality for the detection of cardiotoxicity related to cancer therapy. Our expanded understanding of the cardiac side effects of cancer therapy and optimal surveillance strategies for those at risk is predicated on the ascertainment of cardiac outcomes in future clinical trials, for which echocardiography will undoubtedly play a pivotal role.