Análise do diâmetro de cones acessórios calibrados por réguas calibradoras / Diameter analysis of accessory cones calibrated by calibrating rulers

O objetivo do presente estudo foi de comparar o diâmetro dos cones acessórios FM EL calibrados por duas réguas calibradoras com seus respectivos diâmetros nominais. Foram calibrados 80 cones de guta percha FM EL (Odous de Deus) utilizando duas réguas calibradoras das seguintes marcas: Prisma e Denco. Os cones foram divididos em 8 grupos (n=10) de acordo com a régua e com o diâmetro em que foram calibrados. Posteriormente, os cones foram fotografados e tiveram seus D0 mensurados através do software ImageJ. Após a realização da análise estatística utilizando-se os testes de Normalidade de Shapiro-Wilk e o teste t Student (Distribuição Normal), obteve-se os seguintes resultados: não houve diferença estatisticamente significativa com o valor de referência na régua prisma nos cones 40, isto é, em todas as outras situações encontrou-se diferença com os valores de referência. Quando foram comparados os valores das medianas e desvio padrão das duas réguas calibradoras também houve diferença estatisticamente significativa (p<0,05) nos cones 25, 35 e 40. Os cones acessórios FM EL (Odous de Deus) calibrados com a régua Denco diferiram dos diâmetros nominais da régua. Assim, deve-se estar atento à exatidão e precisão desses instrumentos a fim de se evitar possíveis erros de mensuração e interpretação capazes de comprometer o êxito da obturação no tratamento endodôntico.

The aim of the present study was to compare the diameter of the FM EL accessory cones calibrated by two calibrating rulers with their respective nominal diameters 80 FM EL gutta percha cones (Odous of God) were calibrated using two calibrating culers of the following brands: Prisma and Denco. The cones were divided in 8 groups (n=10) according to the ruler and the diameter in which they were calibrated. Posteriorly, the cones were photographed and nad their D0 neasured through the software ImageJ. After performing the statistical analysis using the Shapiro- Wilk Normality tests and the Student T test (Normal Distribution), the following results were obtained: there was no stastistically significant difference with the reference value in the prism rule in the cones 40, that is, in all other situations, a difference was found with the reference values. When the median values and standard deviation of the two calibrating rulers were compared, there was also a statistically significant difference (p<0,05) in cones 25, 35 and 40. The FM EL (Odous of God) accessory cones calibrated eita the Denco ruler differed from the nominal diameters of the ruler. Thus, one must pay attention to the accuracy and precision of these instruments in order to avoid possible errors of measurement and interpretation capable of compromising the success of filling in endodontic treatment.

Metrological traceable calibration of organic carbon and elemental carbon based on laboratory-generated reference materials.

Carbonaceous aerosol, including organic carbon (OC) and elemental carbon (EC), has significant influence on human health, air quality and climate change. Accurate measurement of carbonaceous aerosol is essential to reduce the uncertainty of radiative forcing estimation and source apportionment. The accurate separation of OC and EC is controversial due to the charring of OC. Therefore, the development of reference materials (RM) for the validation of OC/EC separation is an important basis for further study. Previous RMs were mainly based on ambient air sampling, which could not provide traceability of OC and EC concentration. To develop traceable RMs with known OC/EC contents, our study applied an improved aerosol generation and mixing technique, providing uniform deposition of particles on quartz filters. To generate OC aerosol with similar pyrolytic property of ambient aerosol, both water soluble organic carbon (WSOC) and water insoluble organic carbon (WIOC) were used, and amorphous carbon was selected for EC surrogate. The RMs were analyzed using different protocols. The homogeneity within the filter was validated, reaching below 2%. The long-term stability of RMs has been validated with RSD ranged from 1.7%-3.2%. Good correlation was observed between nominal concentration of RMs with measured concentration by two protocols, while the difference of EC concentration was within 20%. The results indicated that the newly developed RMs were acceptable for the calibration of OC and EC, which could improve the accuracy of carbonaceous aerosol measurement. Moreover, the laboratory-generated EC-RMs could be suitable for the calibration of equivalent BC concentration by Aethalometers.

Concordant inter-laboratory derived concentrations of ceramides in human plasma reference materials via authentic standards.

In this community effort, we compare measurements between 34 laboratories from 19 countries, utilizing mixtures of labelled authentic synthetic standards, to quantify by mass spectrometry four clinically used ceramide species in the NIST (National Institute of Standards and Technology) human blood plasma Standard Reference Material (SRM) 1950, as well as a set of candidate plasma reference materials (RM 8231). Participants either utilized a provided validated method and/or their method of choice. Mean concentration values, and intra- and inter-laboratory coefficients of variation (CV) were calculated using single-point and multi-point calibrations, respectively. These results are the most precise (intra-laboratory CVs ≤ 4.2%) and concordant (inter-laboratory CVs < 14%) community-derived absolute concentration values reported to date for four clinically used ceramides in the commonly analyzed SRM 1950. We demonstrate that calibration using authentic labelled standards dramatically reduces data variability. Furthermore, we show how the use of shared RM can correct systematic quantitative biases and help in harmonizing lipidomics. Collectively, the results from the present study provide a significant knowledge base for translation of lipidomic technologies to future clinical applications that might require the determination of reference intervals (RIs) in various human populations or might need to estimate reference change values (RCV), when analytical variability is a key factor for recall during multiple testing of individuals.

External validation of the parsimonious EuroLung risk models: analysis of the Brazilian Lung Cancer Registry.

OBJECTIVE: The purpose of this study was to assess performance in the Brazilian Lung Cancer Registry Database by using the parsimonious EuroLung risk models for morbidity and mortality. METHODS: The EuroLung1 and EuroLung2 models were tested and evaluated through calibration (calibration plot, Brier score, and the Hosmer-Lemeshow test) and discrimination (ROC AUCs), in a national multicenter registry of 1,031 patients undergoing anatomic lung resection. RESULTS: The evaluation of performance in Brazilian health care facilities utilizing risk-adjustment models, specifically EuroLung1 and EuroLung2, revealed substantial miscalibration, as evidenced by calibration plots and Hosmer-Lemeshow tests in both models. In terms of calibration, EuroLung1 exhibited a calibration plot with overlapping points, characterized by a slope of 1.11 and a Brier score of 0.15; the Hosmer-Lemeshow test yielded a statistically significant p-value of 0.015; and the corresponding ROC AUC was 0.678 (95% CI: 0.636-0.721). The EuroLung2 model displayed better calibration, featuring fewer overlapping points in the calibration plot, with a slope of 1.22, with acceptable discrimination, as indicated by a ROC AUC of 0.756 (95% CI: 0.670-0.842). Both models failed to accurately predict morbidity and mortality outcomes in this specific health care context. CONCLUSIONS: Discrepancies between the EuroLung model predictions and outcomes in Brazil underscore the need for model refinement and for a probe into inefficiencies in the Brazilian health care system.

Calibrating tumor growth and invasion parameters with spectral spatial analysis of cancer biopsy tissues.

The reaction-diffusion equation is widely used in mathematical models of cancer. The calibration of model parameters based on limited clinical data is critical to using reaction-diffusion equation simulations for reliable predictions on a per-patient basis. Here, we focus on cell-level data as routinely available from tissue biopsies used for clinical cancer diagnosis. We analyze the spatial architecture in biopsy tissues stained with multiplex immunofluorescence. We derive a two-point correlation function and the corresponding spatial power spectral distribution. We show that this data-deduced power spectral distribution can fit the power spectrum of the solution of reaction-diffusion equations that can then identify patient-specific tumor growth and invasion rates. This approach allows the measurement of patient-specific critical tumor dynamical properties from routinely available biopsy material at a single snapshot in time.

Subject-Independent Wearable P300 Brain-Computer Interface Based on Convolutional Neural Network and Metric Learning.

The calibration procedure for a wearable P300 brain-computer interface (BCI) greatly impact the user experience of the system. Each user needs to spend additional time establishing a decoder adapted to their own brainwaves. Therefore, achieving subject independent is an urgent issue for wearable P300 BCI needs to be addressed. A dataset of electroencephalogram (EEG) signals was constructed from 100 individuals by conducting a P300 speller task with a wearable EEG amplifier. A framework is proposed that initially improves cross- subject consistency of EEG features through a common feature extractor. Subsequently, a simple and compact convolutional neural network (CNN) architecture is employed to learn an embedding sub-space, where the mapped EEG features are maximally separated, while pursuing the minimum distance within the same class and the maximum distance between different classes. Finally, the model's generalization capability was further optimized through fine-tuning. Results: The proposed method significantly boosts the average accuracy of wearable P300 BCI to 73.23±7.62 % without calibration and 78.75±6.37 % with fine-tuning. The results demonstrate the feasibility and excellent performance of our dataset and framework. A calibration-free wearable P300 BCI system is feasible, suggesting significant potential for practical applications of the wearable P300 BCI system.

Calibrating dimension reduction hyperparameters in the presence of noise.

The goal of dimension reduction tools is to construct a low-dimensional representation of high-dimensional data. These tools are employed for a variety of reasons such as noise reduction, visualization, and to lower computational costs. However, there is a fundamental issue that is discussed in other modeling problems that is often overlooked in dimension reduction-overfitting. In the context of other modeling problems, techniques such as feature-selection, cross-validation, and regularization are employed to combat overfitting, but rarely are such precautions taken when applying dimension reduction. Prior applications of the two most popular non-linear dimension reduction methods, t-SNE and UMAP, fail to acknowledge data as a combination of signal and noise when assessing performance. These methods are typically calibrated to capture the entirety of the data, not just the signal. In this paper, we demonstrate the importance of acknowledging noise when calibrating hyperparameters and present a framework that enables users to do so. We use this framework to explore the role hyperparameter calibration plays in overfitting the data when applying t-SNE and UMAP. More specifically, we show previously recommended values for perplexity and n_neighbors are too small and overfit the noise. We also provide a workflow others may use to calibrate hyperparameters in the presence of noise.

An interactive R-based custom quantification program for semi-quantitative analysis of triacylglycerols in bovine milk.

The R programming language, RStudio, and open-source software solutions for analysis of liquid chromatography-mass spectrometry (LC-MS) data have been used with user-written R-based custom quantification programs (CQP) for semi-quantification of triacylglycerols (TAGs) in bovine milk lipid extracts. Using the peak-finding capabilities of the package "xcms" in RStudio, peaks were integrated, and retention times aligned, normalized, and then used for semi-quantitative analysis of a custom set of four extraction internal standards (EISs) and 29 TAG regioisomers using the choice of four analytical internal standards (AISs). Alternating stereospecific numbering (sn) 1,3 TAG regioisomers (standards 1, 3, and 5 of six calibration standards) and sn-1,2 TAG regioisomers (standards 2, 4, and 6 of six standards) were used to make a set of six calibration standards, which were used for quantification using a linear fit model, polynomial fit model, power fit model, level-bracketed linear fit, replicate-bracketed polynomial fit, replicate-bracketed power fit, and replicate- and level-bracketed linear fit and response factors. For example, the linear fit for EIS1 gave an unacceptable coefficient of determination (CoD), r2 = 0.9616, whereas the polynomial fit gave r2 = 0.9908 and the power fit gave r2 = 0.9928, while the double-bracketed linear fit gave CoDs of r2 = 0.9960, 0.9848, and 0.9781 for the three brackets, yet gave the least % difference to known calibration concentrations. For unparalleled transparency, the CQP produced webpages that allowed every step in the data processing and quantification sequence to be verified and reproduced, and contained interactive figures. The data are publicly available using a digital object identifier (DOI). The R code can be downloaded and used with the downloadable data to reproduce the results, to modify the code and further customize the results, or to copy and paste and adapt the code to other quantification applications.

Updating and calibrating the Real-World Progression In Diabetes (RAPIDS) model in a non-Veterans Affairs population.

OBJECTIVES: To present the Real-World Progression In Diabetes (RAPIDS) 2.0 Risk Engine, the only simulation model to study the long-term trajectories of outcomes arising from dynamic sequences of glucose-lowering treatments in type 2 diabetes (T2DM). RESEARCH DESIGN AND METHODS: The RAPIDS model's risk equations were re-estimated using a Least Absolute Shrinkage and Selection Operator (LASSO)-based regularization of features that spanned baseline data from the last two quarters of current time and interactions with age. These equations were supplemented with estimates for the impact of dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists, and sodium-glucose cotransporter-2 inhibitor classes of drugs as monotherapies and their combinations with metformin based on newer trial data and comprehensive meta-analyses. The probabilistic RAPIDS 2.0 model was calibrated (N = 25 000) and validated (N = 263 816) using electronic medical records (EMR) data between 2008 and 2021 from a national network of US healthcare organizations. RESULTS: The EMR-based cohort had a mean age of 61 years at baseline, with 50% women, 70% non-Hispanic White individuals and 20% non-Hispanic Black individuals, and was followed for 17.5 quarters (range: 3-50). The final RAPIDS 2.0 risk engine accurately predicted the long-term trajectories of all nine biomarkers and nine outcomes in the hold-out validation sample. Similar accuracies in predictions were observed in each of the 14 subgroups studied. CONCLUSION: The RAPIDS 2.0 model demonstrated valid long-term predictions of outcomes in individuals with T2DM in the United States as a function of dynamic sequences of treatment use patterns. This highlights its potential to project long-term comparative effectiveness between alternative sequences of glucose-lowering treatment uses in the United States.

Calibrating Observational Health Record Data Against a Randomized Trial.

Importance: The conditions required for health record data sources to accurately assess treatment effectiveness remain unclear. Emulation of randomized clinical trials (RCTs) with health record data and subsequent calibration of the results can help elucidate this. Objective: To pilot an emulation of the KEYNOTE-189 RCT using a commercially available electronic health record (EHR) data source. Design, Setting, and Participants: This retrospective cohort study used an EHR database spanning from April 2007 to February 2023. Follow-up began on treatment initiation and proceeded until an outcome event, loss to follow-up, end of data, or end of study period (640 days). The population-based cohort was ascertained from EHRs provided by 52 health systems across the US. Eligibility criteria were defined as closely as possible to the benchmark RCT. Patients with non-small cell lung cancer initiating first-line treatment for metastatic disease were included. Patients with evidence of squamous non-small cell lung cancer, primary nonlung malignant neoplasms, or identified EGFR/ALK variations were excluded. Data were analyzed from June to October 2023. Exposures: Initiation of first-line pembrolizumab and chemotherapy and chemotherapy alone. Chemotherapy in both groups was defined as a combination of pemetrexed and platinum-based (carboplatin or cisplatin) therapy. Main Outcomes and Measures: Outcomes of interest were 12-month survival probability and mortality hazard ratio (HR). Results: A total of 1854 patients (mean [SD] age, 63.7 [9.6] years; 971 [52.4%] men) were eligible, including 589 patients who initiated pembrolizumab and chemotherapy and 1265 patients who initiated chemotherapy only. The cohort included 364 Black patients (19.6%) and 1445 White patients (77.9%). The 12-month survival probabilities were 0.60 (95% CI, 0.54-0.65) in the pembrolizumab group and 0.58 (95% CI, 0.55-0.62) in the chemotherapy-only group, compared with 0.69 (95% CI, 0.64-0.74) in the KEYNOTE-189 pembrolizumab group and 0.49 (95% CI, 0.42-0.56) in the KEYNOTE-189 chemotherapy-only group. The mortality HR was 0.95 (95% CI, 0.78-1.16), compared with 0.49 (95% CI, 0.38-0.64) in the KEYNOTE-189 RCT. Conclusions and Relevance: In this cohort study piloting an RCT emulation, results were incongruous with the benchmark trial. Differences in patient treatment and data capture between the RCT and EHR populations, confounding by indication, treatment crossover, and accuracy of captured diagnoses may explain these findings. Future feasibility assessments will require data sources to have important oncology-specific measures curated.

A preliminary application and its error estimates of a simple stereo-camera measure system for the far-sea fishery of Pacific saury.

Pacific saury is one of the most economically important species in the northwestern Pacific Ocean. The management of this resource relies on precise input of biological data such as body length and is often hindered by a lack of such data on captured fish. This study explores the potential of electronic monitoring (EM) using off-the-shelf stereo cameras to overcome the challenges of collecting and measuring saury body length from the Pacific saury fishery. Using a calibrated WEEVIEW SID WV3000 3D camera, a total of 252 paired images with different shooting angles and distances were obtained for further measurement using Sebastes Stereo Image Analysis Software (SSIAS). The treatments for the measurement distance (MD) were 30 cm, 60 cm, and 100 cm, for the depression angle (DA) were 30°, 60°, and 90°, and for the position angle (PA) were 0°, 45°, and 315° (- 45°). An assistant calibration (AC) in the form of a 16 cm black ruler was also added used. The SSIAS measurement results indicated that the best measurement was obtained with 0° position angle, 90° depression angle, and 30 cm distance from the target fish. The use of AC in the SSIAS + AC measurement was proven to reduce the measurement error from 2.45 to 8.64% to - 1.86 to 0.01%. This study set the baseline for the application of EM on collecting saury body length and the use of AC has been proven to increase the measurement accuracy.

In-shoe plantar shear stress sensor design, calibration and evaluation for the diabetic foot.

Plantar shear stress may have an important role in the formation of a Diabetic Foot Ulcer, but its measurement is regarded as challenging and has limited research. This paper highlights the importance of anatomical specific shear sensor calibration and presents a feasibility study of a novel shear sensing system which has measured in-shoe shear stress from gait activity on both healthy and diabetic subjects. The sensing insole was based on a strain gauge array embedded in a silicone insole backed with a commercial normal pressure sensor. Sensor calibration factors were investigated using a custom mechanical test rig with indenter to exert both normal and shear forces. Indenter size and location were varied to investigate the importance of both loading area and position on measurement accuracy. The sensing insole, coupled with the calibration procedure, was tested one participant with diabetes and one healthy participant during two sessions of 15 minutes of treadmill walking. Calibration with different indenter areas (from 78.5 mm2 to 707 mm2) and different positions (up to 40 mm from sensor centre) showed variation in measurements of up to 80% and 90% respectively. Shear sensing results demonstrated high repeatability (>97%) and good accuracy (mean absolute error < ±18 kPa) in bench top mechanical tests and less than 21% variability within walking of 15-minutes duration. The results indicate the importance of mechanical coupling between embedded shear sensors and insole materials. It also highlights the importance of using an appropriate calibration method to ensure accurate shear stress measurement. The novel shear stress measurement system presented in this paper, demonstrates a viable method to measure accurate and repeatable in-shoe shear stress using the calibration procedure described. The validation and calibration methods outlined in this paper could be utilised as a standardised approach for the research community to develop and validate similar measurement technologies.

Heparin-Calibrated Anti-Factor Xa Assay for the Measurement of Direct Anticoagulants such as Apixaban, Rivaroxaban, and Edoxaban.

BACKGROUND: The first purpose of this study was to determine whether a measurement of the level of direct oral anticoagulants (DOACs) was possible with heparin-calibrated chromogenic anti-factor Xa activity (AXA). The second purpose of this study was to evaluate whether the antidote treatment decision level (30 or 50 ng/mL of DOAC) can be determined by unfractionated heparin (UHF)/low molecular weight heparin (LMWH)-calibrated AXA. METHODS: AXA was measured by using two reagents and dedicated analyzers (Sysmex CS-5100 analyzer and STA R Max3). Four types of calibrators were used: 1) Stago DOAC (rivaroxaban, edoxaban, and apixaban)-specific calibrator, 2) Stago LMWH calibrator, 3) Sysmex UHF calibrator, and 4) Sysmex LMWH calibrator. Regression analysis was used between assays. Receiver operating characteristic (ROC) curves were performed, and the concordance rate was calculated. RESULTS: The correlation coefficients were in the range of 0.75 - 0.91 for rivaroxaban and 0.81 - 0.94 for apixaban. The correlation coefficient between edoxaban-calibrated AXA and Sysmex LMWH/Sysmex UHF calibrator-calibrated AXA was low (r = 0.47). Overall correlation between DOAC-calibrated AXA and Stago LMWH-calibrated AXA was linear, at only low concentration in all three DOACs. The concordance rate (89.3 - 100%) is good for de-termining the antidote management level by UFH/LMWH-calibrated AXA, compared with those of DOAC-calibrated AXA in rivaroxaban and apixaban. The concordance rate ranged from 63% to 67% between Sysmex UFH/ LMWH-calibrated AXA and edoxaban-calibrated AXA. CONCLUSIONS: The findings of our study suggest limitations in calculating accurate concentrations, when using UFH/LMWH-calibrated AXA to measure DOAC. This study demonstrates that UFH/LMWH-calibrated AXA may be useful in determining the presence of DOACs at the cutoff level for the antidote treatment in rivarovaban and apixaban. However, in edoxaban, UFH/LMWH-calibrated AXA could not accurately measure the presence of DOACs at the cutoff for antidote treatment.

Unveiling the potential of a novel portable air quality platform for assessment of fine and coarse particulate matter: in-field testing, calibration, and machine learning insights.

Although low-cost air quality sensors facilitate the implementation of denser air quality monitoring networks, enabling a more realistic assessment of individual exposure to airborne pollutants, their sensitivity to multifaceted field conditions is often overlooked in laboratory testing. This gap was addressed by introducing an in-field calibration and validation of three PAQMON 1.0 mobile sensing low-cost platforms developed at the Mining and Metallurgy Institute in Bor, Republic of Serbia. A configuration tailored for monitoring PM2.5 and PM10 mass concentrations along with meteorological parameters was employed for outdoor measurement campaigns in Bor, spanning heating (HS) and non-heating (NHS) seasons. A statistically significant positive linear correlation between raw PM2.5 and PM10 measurements during both campaigns (R > 0.90, p ≤ 0.001) was observed. Measurements obtained from the uncalibrated NOVA SDS011 sensors integrated into the PAQMON 1.0 platforms exhibited a substantial and statistically significant correlation with the GRIMM EDM180 monitor (R > 0.60, p ≤ 0.001). The calibration models based on linear and Random Forest (RF) regression were compared. RF models provided more accurate descriptions of air quality, with average adjR2 values for air quality variables in the range of 0.70 to 0.80 and average NRMSE values between 0.35 and 0.77. RF-calibrated PAQMON 1.0 platforms displayed divergent levels of accuracy across different pollutant concentration ranges, achieving a data quality objective of 50% during both measurement campaigns. For PM2.5, uncertainty ( U r ) was below 50% for concentrations between 9.06 and 34.99 µg/m3 in HS and 5.75 and 17.58 µg/m3 in NHS, while for PM10, it stayed below 50% from 19.11 to 51.13 µg/m3 in HS and 11.72 to 38.86 µg/m3 in NHS.

Analysis of doxorubicin and fullerenol in rat serum by micellar electrokinetic capillary chromatography.

A new micellar electrokinetic capillary chromatographic (MEKC) method has been developed and optimized for simultaneous quantitation of doxorubicin (Dox) and fullerenol (Frl) in rat serum. The separation was carried out in a capillary (48.5-40 cm to the detector - 50 µm id fused-silica capillary with bubble cell, 150 µm) at an applied voltage of 25 kV and temperature of 25 °C. For the background electrolyte 10 mmol L- 1 borate buffer pH 9.3 plus 15 mmol L-1 phosphate buffer pH 7.0 (with the final pH of the mixture adjusted to 7.0 with HCl), with added 10 % (V/V) methanol, and 15 mmol L-1 sodium dodecyl sulfate as a surfactant, were used. The hydrodynamic injection was carried out at 5.0 kPa during the period of 100 s. Linear calibration curves were established over the concentration range 0.5-500.0 mg L- 1 for Dox and 10.0-500.0 mg L- 1 for Frl (at 234 nm). The proposed MEKC procedure was fully validated and applied for the deter mination of Dox and Frl in Wistar rats after intra pe ritoneal administration of both molecules.

Balance Assessment Using a Handheld Smartphone with Principal Component Analysis for Anatomical Calibration.

Most balance assessment studies using inertial measurement units (IMUs) in smartphones use a body strap and assume the alignment of the smartphone with the anatomical axes. To replace the need for a body strap, we have used an anatomical alignment method that employs a calibration maneuver and Principal Component Analysis (PCA) so that the smartphone can be held by the user in a comfortable position. The objectives of this study were to determine if correlations existed between angular velocity scores derived from a handheld smartphone with PCA functional alignment vs. a smartphone placed in a strap with assumed alignment, and to analyze acceleration score differences across balance poses of increasing difficulty. The handheld and body strap smartphones exhibited moderately to strongly correlated angular velocity scores in the calibration maneuver (r = 0.487-0.983, p < 0.001). Additionally, the handheld smartphone with PCA functional calibration successfully detected significant variance between pose type scores for anteroposterior, mediolateral, and superoinferior acceleration data (p < 0.001).

Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the Science.

This study presents a fit-for-purpose lab and field evaluation of commercially available portable sensor systems for PM, NO2, and/or BC. The main aim of the study is to identify portable sensor systems that are capable of reliably quantifying dynamic exposure gradients in urban environments. After an initial literature and market study resulting in 39 sensor systems, 10 sensor systems were ultimately purchased and benchmarked under laboratory and real-word conditions. We evaluated the comparability to reference analyzers, sensor precision, and sensitivity towards environmental confounders (temperature, humidity, and O3). Moreover, we evaluated if the sensor accuracy can be improved by applying a lab or field calibration. Because the targeted application of the sensor systems under evaluation is mobile monitoring, we conducted a mobile field test in an urban environment to evaluate the GPS accuracy and potential impacts from vibrations on the resulting sensor signals. Results of the considered sensor systems indicate that out-of-the-box performance is relatively good for PM (R2 = 0.68-0.9, Uexp = 16-66%, BSU = 0.1-0.7 µg/m3) and BC (R2 = 0.82-0.83), but maturity of the tested NO2 sensors is still low (R2 = 0.38-0.55, Uexp = 111-614%) and additional efforts are needed in terms of signal noise and calibration, as proven by the performance after multilinear calibration (R2 = 0.75-0.83, Uexp = 37-44%)). The horizontal accuracy of the built-in GPS was generally good, achieving <10 m accuracy for all sensor systems. More accurate and dynamic exposure assessments in contemporary urban environments are crucial to study real-world exposure of individuals and the resulting impacts on potential health endpoints. A greater availability of mobile monitoring systems capable of quantifying urban pollutant gradients will further boost this line of research.

Sequential Injection Analysis Method for the Determination of Glutathione in Pharmaceuticals.

A sequential injection analysis method for the determination of glutathione (GSH) in pharmaceuticals has been developed. It is based on the reduction of the Cu(II)-neocuproine complex by GSH and the formation of an orange-yellow colored Cu(I)-neocuproine complex with maximum absorbance at 458 nm. Under optimal conditions the method is characterized by a linear calibration range of 6.0 × 10-7-8.0 × 10-5 mol L-1 (Amax = 3270 CGSH - 0.0010; R2 = 0.9983), limit of detection of 2.0 × 10-7 mol L-1, limit of quantification of 6.7 × 10-7 mol L-1, repeatability (expressed as relative standard deviation) of 3.8%, and sampling rate of 60 h-1. The newly developed method has been successfully applied to the determination of GSH in pharmaceutical samples with no statistically significant difference between the results obtained and those produced by the standard Pharmacopoeia method.

The Utility of Calibrating Wearable Sensors before Quantifying Infant Leg Movements.

While interest in using wearable sensors to measure infant leg movement is increasing, attention should be paid to the characteristics of the sensors. Specifically, offset error in the measurement of gravitational acceleration (g) is common among commercially available sensors. In this brief report, we demonstrate how we measured the offset and other errors in three different off-the-shelf wearable sensors available to professionals and how they affected a threshold-based movement detection algorithm for the quantification of infant leg movement. We describe how to calibrate and correct for these offsets and how conducting this improves the reproducibility of results across sensors.