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Inspired by the popular h‐index in bibliometrics, the h‐accuracy index (HAI) was suggested as a new indicator to evaluate and compare errors in analytical chemistry. The HAI simultaneously considers the "trueness" of analytical measurements and the frequency of measurements with high "trueness". The HAI was defined as if the "trueness" of at most M% of the total measurements is no less than M%, the value of HAI will be M%, where a specific definition of "trueness" was given to compute the HAI. The range of the HAI was between zero and one. The HAI was applied to two examples as a new error index: (1) to evaluate and compare the analytical results by different methods/labs and (2) to evaluate and compare the prediction performances of different multivariate calibration models. Data analysis indicated that the HAI was a reasonable, robust, easy‐to‐compute, and comprehensive index for evaluating and comparing errors in analytical chemistry. Moreover, the HAI could provide the information about how many measurements are good. [ABSTRACT FROM AUTHOR]

In this computer simulation study, we examine four different statistical approaches of linearity assessment, including two variants of deviation from linearity (individual (IDL) and averaged (AD)), along with detection capabilities of residuals of linear regression (individual and averaged). From the results of the simulation, the following broad suggestions are provided to laboratory practitioners when performing linearity assessment. A high imprecision can challenge linearity investigations by producing a high false positive rate or low power of detection. Therefore, the imprecision of the measurement procedure should be considered when interpreting linearity assessment results. In the presence of high imprecision, the results of linearity assessment should be interpreted with caution. Different linearity assessment approaches examined in this study performed well under different analytical scenarios. For optimal outcomes, a considered and tailored study design should be implemented. With the exception of specific scenarios, both ADL and IDL methods were suboptimal for the assessment of linearity compared. When imprecision is low (3 %), averaged residual of linear regression with triplicate measurements and a non-linearity acceptance limit of 5 % produces <5 % false positive rates and a high power for detection of non-linearity of >70 % across different types and degrees of non-linearity. Detection of departures from linearity are difficult to identify in practice and enhanced methods of detection need development. [ABSTRACT FROM AUTHOR]

The nature of modern organizations needs to be increasingly adaptive, since they are dealing with a constant demand to respond to stimuli derived from the dynamic environments they operate in. Changing their capabilities is a common response, and this makes capability management a vital aspect of organizational survivability. To date, there are no approaches specifically designed to address this specific situation. KYKLOS and Compass are two interlinked approaches of different complexity, a DSML and a canvas, developed to support capability change. As recently developed methods, they lacked formal demonstration and evaluation; therefore, the goal of this article is to present the demonstration and evaluation of the two approaches by their stakeholders, in particular, business and modeling experts. A case study in a Swedish company in the ERP system consulting domain that is undergoing changes in its sales and consulting capabilities related to evolving customer requirements has been used to demonstrate and evaluate the two approaches. The process consisted of two evaluation cycles. The first cycle concerned KYKLOS and used two categories of evaluators, the business experts and the modeling experts. While the modeling experts evaluated positively the method, the business experts had difficulties associated with its ease of use and adoption. This resulted in the development of Compass, which was evaluated by business experts during the second evaluation cycle. Compass was evaluated more positively in terms of the difficult aspects, but the challenge is ongoing and motivates further future research. [ABSTRACT FROM AUTHOR]

Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (β coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks. [Display omitted] Systematic evaluation of polygenic scoring methods in 1.2 million individuals across five biobanks finds that no single method performs best. Performance varied more between biobanks than between methods, suggesting that future research should address between-biobank variability. Ensembles provided high, robust, and transferable performance. Workflow and results browser are open source. [ABSTRACT FROM AUTHOR]

The current study was designed to evaluate the analytical performance of the new Mindray highly sensitive cardiac troponin I (hs-cTnI) chemiluminescent immunoassay on Mindray CL-1200i, as a thorough validation of novel hs-cTnI methods is required before introduction into clinical practice. The evaluation of the analytical performance of this hs-cTnI immunoassay encompassed the calculation of the limit of blank (LOB), limit of detection (LOD), functional sensitivity, imprecision, linearity, 99th percentile upper reference limit (URL) and concordance with another previously validated hs-cTnI chemiluminescent immunoassay. The LOB and LOD were 0.32 and 0.35 ng/L, whilst the functional sensitivity (expressed as cTnI value with <10 % imprecision), was 0.35 ng/L. The linearity was excellent throughout a wide range of clinically measurable values (r=1.00 between 0.8 and 9,726.9 ng/mL). The intra-assay, inter-assay and total imprecision were 1.1–1.3 %, 5.5–8.1 % and 5.6–8.2 %, respectively. The 99th percentile URL calculated using residual plasma from 246 ostensibly healthy blood donors was 9.2 ng/L (4.3 ng/L in women vs. 12.3 ng/L in men). The Spearman's correlation between Mindray hs-cTnI and Access hs-TnI was 0.97, with mean bias of 7.2 % (95 % CI, 2.6–11.9 %). Although we failed to confirm the very optimistic analytical characteristics previously reported for this method, our evaluation of the novel Mindray hs-cTnI immunoassay on CL-1200i demonstrated that the overall performance is comparable to that of other commercially available hs-cTnI techniques, making it a viable alternative to other methods. [ABSTRACT FROM AUTHOR]

Abstract Metataxonomic studies of ecosystem microbiotas require the simultaneous processing of samples with contrasting physical and biochemical traits. However, there are no published studies of comparisons of different DNA extraction kits to characterize the microbiotas of the main components of terrestrial ecosystems. Here, and to our knowledge for the first time, five DNA extraction kits were used to investigate the composition and diversity of the microbiota of a subset of samples typically studied in terrestrial ecosystems such as bulk soil, rhizosphere soil, invertebrate taxa and mammalian feces. DNA extraction kit was associated with changes in the relative abundance of hundreds of ASVs, in the same samples, resulting in significant differences in alpha and beta diversity estimates of their microbiotas. Importantly, the impact of DNA extraction kit on sample diversity varies according to sample type, with mammalian feces and soil samples showing the most and least consistent diversity estimates across DNA extraction kits, respectively. We show that the MACHEREY–NAGEL NucleoSpin® Soil kit was associated with the highest alpha diversity estimates, providing the highest contribution to the overall sample diversity, as indicated by comparisons with computationally assembled reference communities, and is recommended to be used for any large-scale microbiota study of terrestrial ecosystems.

Computational drug repositioning, which involves identifying new indications for existing drugs, is an increasingly attractive research area due to its advantages in reducing both overall cost and development time. As a result, a growing number of computational drug repositioning methods have emerged. Heterogeneous network-based drug repositioning methods have been shown to outperform other approaches. However, there is a dearth of systematic evaluation studies of these methods, encompassing performance, scalability and usability, as well as a standardized process for evaluating new methods. Additionally, previous studies have only compared several methods, with conflicting results. In this context, we conducted a systematic benchmarking study of 28 heterogeneous network-based drug repositioning methods on 11 existing datasets. We developed a comprehensive framework to evaluate their performance, scalability and usability. Our study revealed that methods such as HGIMC, ITRPCA and BNNR exhibit the best overall performance, as they rely on matrix completion or factorization. HINGRL, MLMC, ITRPCA and HGIMC demonstrate the best performance, while NMFDR, GROBMC and SCPMF display superior scalability. For usability, HGIMC, DRHGCN and BNNR are the top performers. Building on these findings, we developed an online tool called HN-DREP (http://hn-drep.lyhbio.com/) to facilitate researchers in viewing all the detailed evaluation results and selecting the appropriate method. HN-DREP also provides an external drug repositioning prediction service for a specific disease or drug by integrating predictions from all methods. Furthermore, we have released a Snakemake workflow named HN-DRES (https://github.com/lyhbio/HN-DRES) to facilitate benchmarking and support the extension of new methods into the field. [ABSTRACT FROM AUTHOR]

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The escalating prevalence of diabetes worldwide has resulted in a dramatic increase in the number of people who need testing, which in turn necessitates faster HbA1c measurement. The Tosoh GR01 addresses the need for fast turnaround times of whilst offering pragmatic steps to maintain result accuracy in a single instrument by offering two distinct operating modes: Short Mode (SM) and Long Mode (LM). The aim of this study was to evaluate all relevant aspects of the performance of the Tosoh GR01 with a view to accepting the instrument as a future Secondary Reference Measurement Procedure (SRMP) for the IFCC. Certified Clinical & Laboratory Standards Institute (CLSI) Evaluation Protocols (EP) were used to evaluate precision (EP-5), accuracy (EP-9), linearity (EP-6), carry-over (EP-10) and the effect of hemoglobin variants and other potential interferences. Both modes demonstrated CVs <0.6 % in SI units and <0.4 % in NGSP units at 46 mmol/mol (6.4 %) and 75 mmol/mol (9.0 %) and passed both National Glycohemoglobin Standardization Program (NGSP) and International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) certification procedures when compared with 7 IFCC Certified Secondary Reference Measurement Procedures (SRMP). Sigma for both modes was >6 when using the results of EP-5 and EP-9 at an HbA1c concentration of 50 mmol/mol (6.7 %). Neither mode showed any interference with common Hb-variants except for HbAE when HbA1c was >65 mmol/mol. In the SM HbAS, HbAD and HbAC were recognized but no result was reported. There is a good balance between speed and accuracy for determining HbA1c with the Tosoh GR01 in both analytical modes and the device is suitable for use as an IFCC SRMP. [ABSTRACT FROM AUTHOR]

A One Health approach has been key to monitoring the COVID-19 pandemic, as human and veterinary medical professionals jointly met the demands for an extraordinary testing effort for SARS-CoV-2. Veterinary diagnostic laboratories continue to monitor SARS-CoV-2 infection in animals, furthering the understanding of zoonotic transmission dynamics between humans and animals. A RT-PCR assay is a primary animal screening tool established within validation and verification guidelines provided by the American Association of Veterinary Laboratory Diagnosticians (AAVLD), World Organisation for Animal Health (WOAH), and the U.S. Food and Drug Administration (FDA). However, differences in sample matrices, RNA extraction methods, instrument platforms, gene targets, and cutoff values may affect test outcomes. Therefore, targeted validation for a new sample matrix used in any PCR assay is critical. We evaluated a COVID-19 assay for the detection of SARS-CoV-2 in feline and canine lung homogenates and oral swab samples. We used the commercial Applied Biosystems MagMAX Viral/Pathogen II (MVP II) nucleic acid isolation kit and TaqPath COVID-19 Combo kit, which are validated for a variety of human samples, including nasopharyngeal and oropharyngeal swab samples. Our masked test showed a high detection rate and no false-positive or false-negative results, supporting sample extension to include feline oral swab samples. Our study is a prime example of One Health, illustrating how a COVID-19 assay designed for human testing can be adapted and used to detect SARS-CoV-2 in oral swab samples from cats and likely dogs, but not lung homogenates. [ABSTRACT FROM AUTHOR]

Objective: Dietary assessment tools should be designed for the target population. We developed an FFQ designed to assess diet in South Asian women in Norway. The study objective was to evaluate this FFQ using 24-h dietary recalls as reference method. Design: Approximately 3 weeks after the participants (n 40) had filled in the FFQ, the first of three non-consecutive 24-h dietary recalls was completed. The recalls were telephone-based, unannounced and performed by a trained dietitian, with 2–3 weeks between each interview. Setting: The DIASA 1 study, in Oslo, Norway. Participants: Women of South Asian ethnic origin participating in the DIASA 1 study were invited to participate in the evaluation study. Results: The WebFFQasia significantly overestimated the absolute intake of energy, protein, fat and carbohydrates compared with the 24-h dietary recalls. Absolute intakes of sugar, starch and fibre did not differ significantly between the methods. For energy percentages (E%), there were no significant differences, except for monounsaturated fat. Correlations were strong for E% from sugar and saturated fat and moderate for E% from fibre, carbohydrate, total fat and protein. Fourteen food groups out of twenty three were not significantly different compared with the reference method, and sixteen groups showed strong to moderate correlations. Conclusion: The WebFFQasia may be used to assess E% from habitual diet and can adequately estimate intakes and rank participants according to nutrient intake and main food categories at group level. [ABSTRACT FROM AUTHOR]

Expert range maps (ExpRMs) are frequently used to inform species distributions, but often incomplete or missing for many species, particularly among plants and invertebrates. Many species without ExpRMs also have too few occurrence records for reliable application of species distribution models (SDMs). Here we evaluate the performance of commonly used range surrogates and recommend tools that can help fill this significant knowledge gap across a wide range of understudied taxa. Specifically, we explore an alternative range surrogate (ecoregional range maps; EcoRMs), assess its performance versus traditional approaches for 624 North American butterfly species, and outline its use alone and as part of SDMs. As an alternative range estimate, we use terrestrial ecoregions that represent a regionalization of biogeographical zones and we suggest geographical filters and simplifications that improve their performance. We show that consistently across different spatial scales and both in comparison with ExpRMs and SDMs, EcoRMs have an exceptionally high sensitivity and generally a high mean performance. Particularly for species with fewer than 100 occurrence records, EcoRMs outperform other range surrogates. The congruence of species richness patterns was also similar for all approaches. The use of EcoRMs as substitute for data‐poor species without ExpRMs will strongly boost taxonomic coverage of range maps. Additionally, integrating EcoRMs as domains/masks/offsets into SDMs promises significant improvements to model accuracy. For butterflies alone, EcoRMs would thereby provide new range information for 17% and improve basic range information for 43% of all approximately nineteen thousand species. Other technical advantages of generating EcoRMs may also help to overcome issues of the availability, updateability, reproducibility, and circularity of ExpRMs, SDMs and minimum convex hulls (MCVs). In summary, ecoregion‐based range maps offer a versatile tool for ecology and conservation of terrestrial taxa and the application of the EcoRM approach may prove similarly useful for freshwater and marine ecoregions. [ABSTRACT FROM AUTHOR]

Abstract Background Non-experimental studies (also known as observational studies) are valuable for estimating the effects of various medical interventions, but are notoriously difficult to evaluate because the methods used in non-experimental studies require untestable assumptions. This lack of intrinsic verifiability makes it difficult both to compare different non-experimental study methods and to trust the results of any particular non-experimental study. Methods We introduce TrialProbe, a data resource and statistical framework for the evaluation of non-experimental methods. We first collect a dataset of pseudo “ground truths” about the relative effects of drugs by using empirical Bayesian techniques to analyze adverse events recorded in public clinical trial reports. We then develop a framework for evaluating non-experimental methods against that ground truth by measuring concordance between the non-experimental effect estimates and the estimates derived from clinical trials. As a demonstration of our approach, we also perform an example methods evaluation between propensity score matching, inverse propensity score weighting, and an unadjusted approach on a large national insurance claims dataset. Results From the 33,701 clinical trial records in our version of the ClinicalTrials.gov dataset, we are able to extract 12,967 unique drug/drug adverse event comparisons to form a ground truth set. During our corresponding methods evaluation, we are able to use that reference set to demonstrate that both propensity score matching and inverse propensity score weighting can produce estimates that have high concordance with clinical trial results and substantially outperform an unadjusted baseline. Conclusions We find that TrialProbe is an effective approach for probing non-experimental study methods, being able to generate large ground truth sets that are able to distinguish how well non-experimental methods perform in real world observational data.

Abstract Background Oxford Nanopore Technologies (ONT) offers an accessible platform for long-read sequencing, which improves the reconstruction of genomes and helps to resolve complex genomic contexts, especially in the case of metagenome analysis. To take the best advantage of long-read sequencing, DNA extraction methods must be able to isolate pure high molecular weight (HMW) DNA from complex metagenomics samples, without introducing any bias. New methods released on the market, and protocols developed at the research level, were specifically designed for this application and need to be assessed. Results In this study, with different bacterial cocktail mixes, analyzed as pure or spiked in a synthetic fecal matrix, we evaluated the performances of 6 DNA extraction methods using various cells lysis and purification techniques, from quick and easy, to more time-consuming and gentle protocols, including a portable method for on-site application. In addition to the comparison of the quality, quantity and purity of the extracted DNA, the performance obtained when doing Nanopore sequencing on a MinION flow cell was also tested. From the obtained results, the Quick-DNA HMW MagBead Kit (Zymo Research) was selected as producing the best yield of pure HMW DNA. Furthermore, this kit allowed an accurate detection, by Nanopore sequencing, of almost all the bacterial species present in a complex mock community. Conclusion Amongst the 6 tested methods, the Quick-DNA HMW MagBead Kit (Zymo Research) was considered as the most suitable for Nanopore sequencing and would be recommended for bacterial metagenomics studies using this technology.

Abstract Objective: Dietary assessment tools should be designed for the target population. We developed an FFQ designed to assess diet in South Asian women in Norway. The study objective was to evaluate this FFQ using 24-h dietary recalls as reference method. Design: Approximately 3 weeks after the participants (n 40) had filled in the FFQ, the first of three non-consecutive 24-h dietary recalls was completed. The recalls were telephone-based, unannounced and performed by a trained dietitian, with 2–3 weeks between each interview. Setting: The DIASA 1 study, in Oslo, Norway. Participants: Women of South Asian ethnic origin participating in the DIASA 1 study were invited to participate in the evaluation study. Results: The WebFFQasia significantly overestimated the absolute intake of energy, protein, fat and carbohydrates compared with the 24-h dietary recalls. Absolute intakes of sugar, starch and fibre did not differ significantly between the methods. For energy percentages (E%), there were no significant differences, except for monounsaturated fat. Correlations were strong for E% from sugar and saturated fat and moderate for E% from fibre, carbohydrate, total fat and protein. Fourteen food groups out of twenty three were not significantly different compared with the reference method, and sixteen groups showed strong to moderate correlations. Conclusion: The WebFFQasia may be used to assess E% from habitual diet and can adequately estimate intakes and rank participants according to nutrient intake and main food categories at group level.

Boundary handling is an important aspect of fluid simulation, and several boundary handling approaches exist in smoothed particle hydrodynamics (SPH), which have individual strengths and weaknesses. However, comparing different boundary handling approaches is challenging as there is no common basis for evaluations, that is, no universal set of experiments with quantitative evaluation across different methods, especially within computer animation where many evaluations rely mainly on visual perception. This article proposes a set of experiments to aid the evaluation of the main categories of fluid‐boundary interactions that are important in computer animation, that is, no motion (resting) fluid, tangential and normal motion of a fluid with respect to the boundary, and a fluid impacting a corner. We propose ten experiments, comprising experimental setup and quantitative evaluation with optional visual inspections, that are arranged in four groups which focus on one of the main category of fluid‐boundary interactions. We use these experiments to evaluate three particle‐based boundary handling methods, that is, pressure mirroring, pressure boundaries, and moving least squares pressure extrapolation, in combination with two incompressible SPH fluid simulation methods, namely IISPH and DFSPH, to establish a quantifiable relation between different combinations of boundary handling with simulation approaches and the main categories of fluid‐boundary interactions. Finally, we summarize all results in a rating table and show how our experiments can be used to determine the promising method for specific requirements regarding a given constellation of fluid‐boundary interaction. [ABSTRACT FROM AUTHOR]

Background: Non-experimental studies (also known as observational studies) are valuable for estimating the effects of various medical interventions, but are notoriously difficult to evaluate because the methods used in non-experimental studies require untestable assumptions. This lack of intrinsic verifiability makes it difficult both to compare different non-experimental study methods and to trust the results of any particular non-experimental study. Methods: We introduce TrialProbe, a data resource and statistical framework for the evaluation of non-experimental methods. We first collect a dataset of pseudo "ground truths" about the relative effects of drugs by using empirical Bayesian techniques to analyze adverse events recorded in public clinical trial reports. We then develop a framework for evaluating non-experimental methods against that ground truth by measuring concordance between the non-experimental effect estimates and the estimates derived from clinical trials. As a demonstration of our approach, we also perform an example methods evaluation between propensity score matching, inverse propensity score weighting, and an unadjusted approach on a large national insurance claims dataset. Results: From the 33,701 clinical trial records in our version of the ClinicalTrials.gov dataset, we are able to extract 12,967 unique drug/drug adverse event comparisons to form a ground truth set. During our corresponding methods evaluation, we are able to use that reference set to demonstrate that both propensity score matching and inverse propensity score weighting can produce estimates that have high concordance with clinical trial results and substantially outperform an unadjusted baseline. Conclusions: We find that TrialProbe is an effective approach for probing non-experimental study methods, being able to generate large ground truth sets that are able to distinguish how well non-experimental methods perform in real world observational data. [ABSTRACT FROM AUTHOR]

Douglas maple (Acer glabrum Torr. var. Douglasii (Hook.) Dippel [Aceraceae]) has potential for habitat development in urban landscapes. Efficacious micropropagation methodology would enhance the value of this seed recalcitrant species. Three light intensities—6.6, 16.8, and 36.6 μmols•m-2•s-1 (0.65, 1.58, and 3.44 μmols•ft-2•s-1, respectively) PPFD—were tested for their effect on Douglas maple chlorophyll content, shoot length, number of nodes, and mean dry weight. Visually, plants appeared darker green under lower light intensity. However, mean dry weight of cultured microcuttings was significantly higher at higher light intensity. We tested in vitro and ex vitro rooting procedures for their ability to produce healthy roots on established microcuttings. IBA concentration (0, 1, 2, 4, and 8 μΜ) and the length of the initial microcutting propagule (2.0 to 3.0 cm [0.79–1.18 in]) or 3.5 to 4.5 cm [1.38–1.77 in]) were evaluated for enhancing in vitro rooting. Initial microcutting length as a covariate and concentrations of IBA (0.1% and 0.3%) in a talcum powder formulation were evaluated for enhancement of ex vitro rooting. Rooting treatments were assessed by measuring overall survival rate of plantlets after rooting and acclimatization. Greatest survival (92%) occurred with ex vitro rooting with a 0.1% IBA talcum powder treatment. In comparison, the best in vitro rooting treatment (1 μΜ IBA regardless of microcutting length) yielded just 75% survival after rooting and acclimatization. We verified efficacy of the ex vitro rooting protocol (100% rooting and acclimatization) using a second Douglas maple genotype (treated with 0.1% IBA talcum powder). [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to evaluate the analytical performance of a new transcutaneous bilirubin (TcB) device - BiliCareTM (Gerium Medical, Yavne, Israel). Methods: The neonatal TcB measurements were compared between BiliCareTM and the existing BiliChekTM systems (n = 40). TcB measured by BiliCareTM were also compared with total serum bilirubin (TSB) using a Roche Cobas702 chemistry analyzer (n = 31) and whole blood bilirubin using a Radiometer ABL 835 (n = 11). Reproducibility was assessed by repeating TcB measurements with 2 BiliCareTM devices on a normal neonate, two with borderline jaundice, and one with overt jaundice 10 to 20 times respectively within 30 minutes. Results: Compared with BiliChekTM, BiliCareTM demonstrated an average bias of -35.9 µmol/L (-20.6%) (BiliCareTM = 0.6724 BiliChekTM +20.984, r = 0.8414). BiliCareTM had a better agreement with Cobas702 (BiliCareTM = 0.8356 Cobas702 +31.884, r = 0.8576, average bias 8.0 µmol/L (5.3%)). Similarly, BiliCareTM had a -12.7 µmol/L (- 7.2%) average bias compared with ABL835 (BiliCareTM = 0.6166 ABL835 +54.464, r = 0.8287). At TcB 94.5, 155.2, 182.7, and 269.3 µmol/l levels, BiliCareTM had demonstrated imprecision as 8.9%, 9.8%, 5.4%, and 6.9% respectively. Conclusions: The new BiliCareTM correlates with total serum bilirubin as measured on laboratory chemistry analyzer Cobas702 and is acceptable for neonatal transcutaneous bilirubin testing. [ABSTRACT FROM AUTHOR]

In systems biology, the analysis of complex nonlinear systems faces many methodological challenges. For the evaluation and comparison of the performances of novel and competing computational methods, one major bottleneck is the availability of realistic test problems. We present an approach for performing realistic simulation studies for analyses of time course data as they are typically measured in systems biology. Since the design of experiments in practice depends on the process of interest, our approach considers the size and the dynamics of the mathematical model which is intended to be used for the simulation study. To this end, we used 19 published systems biology models with experimental data and evaluated the relationship between model features (e.g., the size and the dynamics) and features of the measurements such as the number and type of observed quantities, the number and the selection of measurement times, and the magnitude of measurement errors. Based on these typical relationships, our novel approach enables suggestions of realistic simulation study designs in the systems biology context and the realistic generation of simulated data for any dynamic model. The approach is demonstrated on three models in detail and its performance is validated on nine models by comparing ODE integration, parameter optimization, and parameter identifiability. The presented approach enables more realistic and less biased benchmark studies and thereby constitutes an important tool for the development of novel methods for dynamic modeling.

Abstract Microplastics are small ( 70% of the time. While cotton and semi-synthetic fiber results were less consistently identified ( 90% of microplastics that we selected from environmental samples (water, sediment) were confirmed by Raman microscopy. It is recommended that researchers assess their hot needle test methods against known standards of both target microplastics and background materials like natural fibers, report the response criteria used in their studies and optimally include spectroscopic verification of results for higher confidence.

Background: Oxford Nanopore Technologies (ONT) offers an accessible platform for long-read sequencing, which improves the reconstruction of genomes and helps to resolve complex genomic contexts, especially in the case of metagenome analysis. To take the best advantage of long-read sequencing, DNA extraction methods must be able to isolate pure high molecular weight (HMW) DNA from complex metagenomics samples, without introducing any bias. New methods released on the market, and protocols developed at the research level, were specifically designed for this application and need to be assessed. Results: In this study, with different bacterial cocktail mixes, analyzed as pure or spiked in a synthetic fecal matrix, we evaluated the performances of 6 DNA extraction methods using various cells lysis and purification techniques, from quick and easy, to more time-consuming and gentle protocols, including a portable method for on-site application. In addition to the comparison of the quality, quantity and purity of the extracted DNA, the performance obtained when doing Nanopore sequencing on a MinION flow cell was also tested. From the obtained results, the Quick-DNA HMW MagBead Kit (Zymo Research) was selected as producing the best yield of pure HMW DNA. Furthermore, this kit allowed an accurate detection, by Nanopore sequencing, of almost all the bacterial species present in a complex mock community. Conclusion: Amongst the 6 tested methods, the Quick-DNA HMW MagBead Kit (Zymo Research) was considered as the most suitable for Nanopore sequencing and would be recommended for bacterial metagenomics studies using this technology. [ABSTRACT FROM AUTHOR]

Method evaluation is one of the critical components of the quality system that ensures the ongoing quality of a clinical laboratory. As part of implementing new methods or reviewing best practices, the peer-reviewed published literature is often searched for guidance. From the outset, Clinical Chemistry and Laboratory Medicine (CCLM) has a rich history of publishing methods relevant to clinical laboratory medicine. An insight into submissions, from editors' and reviewers' experiences, shows that authors still struggle with method evaluation, particularly the appropriate requirements for validation in clinical laboratory medicine. Here, we consider through a series of discussion points an overview of the status, challenges, and needs of method evaluation from the perspective of clinical laboratory medicine. We identify six key high-level aspects of clinical laboratory method evaluation that potentially lead to inconsistency. 1. Standardisation of terminology, 2. Selection of analytical performance specifications, 3. Experimental design of method evaluation, 4. Sample requirements of method evaluation, 5. Statistical assessment and interpretation of method evaluation data, and 6. Reporting of method evaluation data. Each of these areas requires considerable work to harmonise the practice of method evaluation in laboratory medicine, including more empirical studies to be incorporated into guidance documents that are relevant to clinical laboratories and are freely and widely available. To further close the loop, educational activities and fostering professional collaborations are essential to promote and improve the practice of method evaluation procedures. [ABSTRACT FROM AUTHOR]

Analytical performance specifications, lot-to-lot variation, measurement uncertainty, method evaluation, CLSI-ep26 Keywords: analytical performance specifications; CLSI-ep26; lot-to-lot variation; measurement uncertainty; method evaluation EN analytical performance specifications CLSI-ep26 lot-to-lot variation measurement uncertainty method evaluation e218 e220 3 10/03/23 20231001 NES 231001 To the Editor, We appreciate the attention that Bayat et al. have paid to our paper proposing an approach for determining allowable between reagent lot variation [[1]]. [Extracted from the article]

BackgroundPropensity score adjustment is a popular approach for confounding control in observational studies. Reliable frameworks are needed to determine relative propensity score performance in large-scale studies, and to establish optimal propensity score model selection methods.MethodsWe detail a propensity score evaluation framework that includes synthetic and real-world data experiments. Our synthetic experimental design extends the 'plasmode' framework and simulates survival data under known effect sizes, and our real-world experiments use a set of negative control outcomes with presumed null effect sizes. In reproductions of two published cohort studies, we compare two propensity score estimation methods that contrast in their model selection approach: L1-regularized regression that conducts a penalized likelihood regression, and the 'high-dimensional propensity score' (hdPS) that employs a univariate covariate screen. We evaluate methods on a range of outcome-dependent and outcome-independent metrics.ResultsL1-regularization propensity score methods achieve superior model fit, covariate balance and negative control bias reduction compared with the hdPS. Simulation results are mixed and fluctuate with simulation parameters, revealing a limitation of simulation under the proportional hazards framework. Including regularization with the hdPS reduces commonly reported non-convergence issues but has little effect on propensity score performance.ConclusionsL1-regularization incorporates all covariates simultaneously into the propensity score model and offers propensity score performance superior to the hdPS marginal screen.

As to EQA control materials measured by ligand binding assays, the mean biases were -5.21% (Roche), -2.41% (Mindray), -6.63% (DiaSorin), and 14.98% (Siemens). Keywords: 25-hydroxyvitamin D; ligand binding assays; liquid chromatography-tandem mass spectrometry; method evaluation; pregnant women EN 25-hydroxyvitamin D ligand binding assays liquid chromatography-tandem mass spectrometry method evaluation pregnant women e29 e32 4 12/22/22 20230201 NES 230201 To the Editor, Vitamin D deficiency in pregnancy is associated with the increased incidence of preeclampsia, gestational diabetes mellitus, and other maternal-fetal outcomes [[1]]. [Extracted from the article]

Background: Major surgery entails the risk of severe hemorrhage, and an optimized substitution with red blood cell (RBC) and platelet (PLT) transfusions necessitate rapid test results for RBCs/hemoglobin (HGB)/hematocrit (HCT), and PLTs. The HemoScreen (PixCell Medical, Yokneam Ilit, Israel) is an automated point-of-care hematology analyzer employing image analysis and single-use cuvettes. This study aimed to investigate the correspondence between the HemoScreen and standard laboratory testing (SLT) using the Sysmex XN-9000 in patients undergoing major surgery and to evaluate the feasibility in the operating theater. Methods: A total of 145 blood samples from 91 adult patients were sampled during abdominal and orthopedic surgery and analyzed on both cell counters. Coefficient of variation (CV) was calculated, Passing-Boblok regression analysis was performed, and Bland-Altman plots were constructed. User experience was assessed through a questionnaire. Results: The HemoScreen showed imprecision with a CV below 5%. Passing-Boblok regression showed positive proportional and negative constant errors for HGB and HCT, a positive proportional error for PLTs, but no difference for RBCs. Bias in the Bland-Altman plots with limits of agreement: RBCs 0.09 x 1012/L (± 0.20 x 1012/L, HGB 1.1 g/L (±8.4 g/L), HCT 0.4 % (±2.6%), and PLTs 28.8 x 109/L (±33 x 109/L). The analyzer was scored easy to use with shorter turnaround times compared to SLT. Conclusions: The HemoScreen is feasible and provides rapid test results with acceptable accuracy for the evaluated application but the two methods cannot be regarded as interchangeable based on the results in this study. [ABSTRACT FROM AUTHOR]

Differences in cells’ functions arise from differential activity of regulatory elements, including enhancers. Enhancers are cis-regulatory elements that cooperate with promoters through transcription factors to activate the expression of one or several genes by getting physically close to them in the 3D space of the nucleus. There is increasing evidence that genetic variants associated with common diseases are enriched in enhancers active in cell types relevant to these diseases. Identifying the enhancers associated with genes and conversely, the sets of genes activated by each enhancer (the so-called enhancer/gene or E/G relationships) across cell types, can help understanding the genetic mechanisms underlying human diseases. There are three broad approaches for the genome-wide identification of E/G relationships in a cell type: 1) genetic link methods or eQTL, 2) functional link methods based on 1D functional data such as open chromatin, histone mark or gene expression and 3) spatial link methods based on 3D data such as HiC. Since 1) and 3) are costly, the current strategy is to develop functional link methods and to use data from 1) and 3) as reference to evaluate them. However, there is still no consensus on the best functional link method to date, and method comparison remain seldom. Here, we compared the relative performances of three recent methods for the identification of enhancer-gene links, TargetFinder, Average-Rank, and the ABC model, using the three latest benchmarks from the field: a reference that combines 3D and eQTL data, called BENGI, and two genetic screening references, called CRiFF and CRiSPRi. Overall, none of the three methods performed best on the three references. CRiFF and CRISPRi reference sets are likely more reliable, but CRiFF is not genome-wide and CRiFF and CRISPRi are mostly available on the K562 cancer cell line. The BENGI reference set is genome-wide but likely contains many false positives. This study therefore calls for new reliable and genome-wide E/G reference data rather than new functional link E/G identification methods.

ABSTRACT Bacteria can be associated with male infertility. Antibacterial substances (e.g., zinc-containing proteins, antimicrobial peptides) in ejaculates might impair the growth of bacteria in culture. We therefore wanted to test if removing antibacterial substances by washing the ejaculate could improve the detection of bacteria in culture. All ejaculates from patients ≥18 years old, which were obtained for routine diagnostics to assess male infertility were included in this study (no exclusion criteria were applied). Test samples were diluted with 2 mL sterile 0.45% saline, vortexed, and centrifuged (5 min; 7.5 × g). After the removal of 2 mL of the supernatant and resuspension, 10 μL of the pellet was used for aerobic and anaerobic culture. Control samples were cultured identically but without washing. Species identification was done with matrix-assisted laser desorption ionization–time of flight mass spectrometry. A total of 186 samples were included. The data set was stratified into five groups (Gram-negative rods [GNR], anaerobes [AN], Enterococcus spp. [EC], coagulase-negative staphylococci [CNS], and viridans streptococci [VS]). Compared to the control arm, the test arm revealed significant lower proportions for CNS (59.1% versus 44.6%, P < 0.01) and VS (53.8% versus 41.9%, P = 0.03). Similarly, slightly lower proportions of GNR (16.1% versus 15.1%, P = 0.89), AN (19.9% versus 17.2%, P = 0.5), and EC (25.3% versus 23.1%, P = 0.63) were observed. The medians of CFU were lower in test samples compared to the control samples (6.5 × 103 versus 2.5 × 103, P < 0.01) for any bacterial growth. Lower colony counts were also observed for individual bacterial groups. In conclusion, preculture washing of ejaculates results in a decrease in total bacteria count and culture-positive samples. IMPORTANCE This study compares two methods for processing ejaculate samples from men undergoing investigations for infertility. The method of sample washing and centrifugation was compared to the standard method of direct inoculation and culture. The study hypothesis was that preprocessing of samples may increase bacterial yield by removing bactericidal substances from semen. However, we found that washing ejaculate samples before microbiological culture did not improve the detection of bacteria and led to a reduction in colony counts.

Simple models continue to be important for continental‐scale floodwater depth mapping due to the prohibitively expensive cost of calibrating and applying hydrodynamic models. This paper investigates the accuracy of three simple models for floodwater depth estimation from remote sensing derived water extent and/or Digital Elevation Models (DEMs) in semiarid regions. The three models are Height Above Nearest Drainage (HAND; Nobre et al., 2011, https://doi.org/10.1016/j.jhydrol.2011.03.051), Teng Vaze Dutta (TVD; Teng et al., 2013, http://hdl.handle.net/102.100.100/97033?index=1), and Floodwater Depth Estimation Tool (FwDET; Cohen, Brakenridge, et al., 2018, https://doi.org/10.1111/1752-1688.12609). The model accuracy and nature of errors are established using industry's best practice hydrodynamic models as benchmarks in three regions in eastern Australia. The overall results show that FwDET tends to underestimate (by 0.32 m at 50th percentile) while HAND and TVD overestimate floodwater depth for almost all floods (by 0.97 and 0.98 m, respectively). We quantify how switching DEM from 5 m LiDAR to national or global data sets DEM‐H (Gallant et al., 2011, https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search#/metadata/72759), MERIT (Yamazaki et al., 2019, https://doi.org/10.1029/2019WR024873), or FABDEM (Hawker et al., 2022, https://doi.org/10.1088/1748-9326/ac4d4f) can affect different models differently; and we evaluate model performance against reach geomorphology and magnitude of flood events. The findings emphasize the importance of choosing a model that is fit for the intended application. By describing the applicability, advantages, and limitations of these models, this paper assists practitioners to choose the most appropriate model based on characteristics of their study area, type of problems they try to solve, and data availability. Plain Language Summary: We have assessed the performance of three simple models for estimating floodwater depth by evaluating their accuracy against different Digital Elevation Model inputs, characteristics of study area, and magnitude of flood events. Our results emphasize that selection of an appropriate model depends on the circumstances. This study provides recommendations for future studies that enhance remote sensing‐based flood maps with water depth, making use of the growing number of publicly available remote sensing water extent and digital elevation data sets globally. All the methods have been coded in Python and are freely available at https://github.com/csiro-hydroinformatics/water-depth-estimation. Key Points: We assessed three simple models for estimating floodwater depth by comparing their results with those of hydrodynamic modelsThe model performance was evaluated against reach geomorphology, magnitude of flood events, and different Digital Elevation Model inputsThe results emphasize that a model should be chosen for the intended application. Guidelines provided for possible applications [ABSTRACT FROM AUTHOR]

Fast and reliable ethanol assays analysis are used in a clinical context for patients suspected of ethanol intoxication. Mostly, automated systems using an enzymatic reaction based on ethanol dehydrogenase are used. The manuscript focusses on the evaluation of the performance of these assays. Data included 30 serum samples used in the Belgian EQA scheme from 2019 to 2021 and concentrations ranged from 0.13 to 3.70 g/L. A regression line between target concentrations and reported values was calculated to evaluate outliers, bias, variability and measurement uncertainty. A total of 1,611 results were taken into account. Bias was the highest for Alinity c over the whole concentration range and the lowest for Vitros for low concentrations and Cobas 8000 using the c702 module for high concentrations. The Architect and Cobas c501/c502 systems showed the lowest variability over the whole concentration range. Highest variability was observed for Cobas 8000 using the 702 module, Thermo Scientific and Alinity c. Cobas 8000 using the c702 module showed the highest measurement uncertainty for lower concentrations. For higher concentrations, Alinity c, Thermo Scientific and Vitros were the methods with the highest measurement uncertainty. The bias of the enzymatic techniques is nearly negligible for all methods except Alinity c. Variability differs strongly between measurement procedures. This study shows that the Alinity c has a worse measurement uncertainty than other systems for concentrations above 0.5 g/L. Overall, we found the differences in measurement uncertainty to be mainly influenced by the differences in variability. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to evaluate the performance of chemiluminescence immunoassays for anti-GAD65 and anti-insulin antibodies following user verification guidelines. Methods: The analytical performance of anti-GAD65 and anti-insulin antibodies using a MAGLUMI 2000 analyzer was verified following user verification guidelines by the Clinical and Laboratory Standards Institute. Results: Performance specifications including precision, linearity, carry-over, cutoffs for positive results, reference intervals, and comparability with pre-existing commercially available radioimmunoassays using patient specimens and certified reference material were verified (coefficients of variation for precision of anti-GAD65 and anti-insulin antibodies were 2.6% and 3.4%, respectively). Comparability assessed using clinical serum specimens showed overall agreement with radioimmunoassay of 87.2% (95% confidence interval 74.8% - 94.0%) for the anti-GAD65 antibody assay and 85.4% (95% confidence interval 71.6% - 93.1%) for the anti-insulin antibody assay. Conclusions: The results of this study verified the analytical performance of MAGLUMI anti-GAD65 and anti-insulin antibody assays for clinical use. [ABSTRACT FROM AUTHOR]

Estimates of accumulated quantities and qualities (Q&Q) of faecal sludge are essential for developing city-wide management plans. However, standardized approaches are lacking, and examples in scientific literature make use of diverse methodologies and parameters, making their comparability and transferability difficult. This study field-tested an approach for estimating Q&Q in Sircilla, India, and compared three methods for measuring accumulated sludge: (1) faecal sludge accumulation rate from in situ measurement with a core sampler; (2) faecal sludge accumulation rate with volume emptied by desludging truck; and (3) sludge blanket accumulation rate in situ with a core sampler. Measurements were taken at households and commercial establishments, samples were analysed for characteristics, and demographic, environmental, and technical data were collected with a questionnaire. The median total solids (TS), volatile solids (VS), and chemical oxygen demand (COD) concentrations for all containments were 26.8, 17.8, and 32.0 g/L, respectively. The median faecal sludge accumulation rate estimated with the core sampler and truck were 53 and 96 L/cap·year, respectively. The median sludge blanket accumulation rate was 17 L/cap·year. Continued data collection in this fashion will lead to a better understanding of what is accumulating in onsite containments at regional levels. HIGHLIGHTS Comparison of methodologies to estimate the total faecal sludge and sludge blanket accumulation rate.; The selection of Q&Q measurement methods should be based on defined objectives and available resources.; Q&Q studies conducted in this fashion will lead to more locally relevant accumulation rates than standard values.;

Qualitative Comparative Analysis (QCA) is a relatively young method of causal inference that continues to diffuse across the social sciences. However, recent methodological research has found the conservative (QCA-CS) and the intermediate solution type (QCA-IS) of QCA to fail fundamental tests of correctness. Even under conditions otherwise ideal for causal discovery, both solution types frequently committed causal fallacies by presenting inferences that were in direct disagreement with the underlying data-generating structure to be discovered by QCA. None of these problems affected the parsimonious solution type (QCA-PS). These findings conflict with conventional wisdom in the QCA literature, which has it that QCA-CS uses empirical information only and that QCA-IS is preferable to both QCA-CS and QCA-PS. The present article resolves these contradictions. It shows that QCA-CS and QCA-IS systematically supplement empirical data with matching artificial data. These artificial data, however, regularly induce causal fallacies of severe magnitude. Researchers who employ QCA-CS or QCA-IS in empirical analyses thus always risk moving further away from the truth rather than closer to it. [ABSTRACT FROM AUTHOR]

The main objective of the qualitative comparative analysis is to find solutions that display sufficient configurations of causal conditions leading to the presence of an outcome. These solutions should be less complex than the original observed configurations, as parsimonious as possible, without sacrificing the sufficiency requirement. Sufficiency and parsimony are two requirements that act in opposition, and an optimal solution is one that accommodates both. There are different search strategies that lead to different types of solutions, with an ongoing debate about which solution type is closest to the true, underlying causal structure. This article presents the different logics behind each simplification system in order to explain how and why they lead to different results and introduces the concept of "robust sufficiency" to clear the debate. It analyses the correctness ratios for the different solution type and provides an improved set of procedures to measure correctness that captures the best features from each system. Out of the competition between the conservative and the parsimonious search strategies, the intermediate solution emerges as the best hybrid that is suitable for causal analysis, outperforming the parsimonious solution in recovering a known (even parsimonious) causal structure. [ABSTRACT FROM AUTHOR]

Limitations of microwave processing due to inhomogeneities of power input and energy absorption have been widely described. Over‐ and underheated product areas influence reproducibility, product quality, and possibly safety. Although a broad range of methods is available for temperature measurement and evaluation of time/temperature effects, none of them is sufficiently able to detect temperature differences and thermally induced effects within the product caused by inhomogeneous heating. The purpose of this review is to critically assess different methods of temperature measurement for their suitability for different microwave applications, namely metallic temperature sensors, thermal imaging, pyrometer measurement, fiber optic sensors, microwave radiometry, magnetic resonance imaging, liquid crystal thermography, thermal paper, and biological and chemical time‐temperature indicators. These methods are evaluated according to their advantages and limitations, method characteristics, and potential interference with the electric field. Special attention is given to spatial resolution, accuracy, handling, and purpose of measurement, that is, development work or online production control. Differences of methods and examples of practical application and failure in microwave‐assisted food processing are discussed with a special focus on microwave pasteurization and microwave‐assisted drying. Based on this assessment, it is suggested that infrared cameras for measuring temperature distribution at the product surface and partially inside the product in combination with a chemical time/temperature indicator (e.g., Maillard reaction, generating heat‐induced color variations, depending on local energy absorption) appear to be the most appropriate system for future practical application in microwave food process control, microwave system development, and product design. Reliable detection of inhomogeneous heating is a prerequisite to counteracte inhomogeneity by a targeted adjustment of process and product parameters in microwave applications. [ABSTRACT FROM AUTHOR]

Daylight is an important component in maintaining human health and wellbeing and plays a key role in physiological, psychological, and behavioural regulation. Understanding the complexity of daylight perception is vital since the degree of satisfaction with daylight conditions could greatly impact individual mood, behaviour and cognitive performance. This paper aims at (1) presenting an overview of current knowledge on methods for assessing daylight perception and (2) establishing a methodology for assessing daylight perception in the context of cultural background. An experiment was conducted with 50 students who were instructed to select the best and worst seats, describe the best desks' daylight conditions and draw boundary lines between perceived daylit and non-daylit spaces in a library. The study showed that subjective rating and seat preference methods were consistent with actual daylight levels. However, participants' boundary lines did not represent the actual daylight availability in the space. The study suggests that individual daylight perception in the context of cultural background can be assessed using the subjective rating and seat preference methods. [ABSTRACT FROM AUTHOR]

A method for the determination of 21 perfluorinated and 10 polyfluorinated alkyl substances (PFAS) was developed for application in different food matrices. Acetonitrile was used as the extraction solvent with solid phase extraction weak anion-exchange (SPE-WAX) clean up, with LC-MS/MS analysis using both surrogate and performance standards to correct for losses during sample preparation and matrix effects. The method has been evaluated in four different matrices (fish, pizza, chicken nuggets and spinach). Originally, the focus was to develop a method for foods commonly thought to be a source of PFASs (e.g. fish). It was expanded to include foods where PFAS exposure would be possible through their presence in grease-proof food packaging (e.g. pizza, chicken nuggets). Vegetables (lettuce) and fruit (tomato) have recently been considered as part of proficiency testing programmes, so the inclusion of some testing in a vegetable matrix (i.e. spinach) was also added to the testing. Limits of quantification ranged from 0.018 ng g−1 (L-PFDS) to 5.28 ng g−1 (FHEA), although method quantification limits for PFBA (12.4 ng g−1), 6:2 PAP (8.96 ng g−1) and 8:2 PAP (3.49 ng g−1) were elevated above instrumental limits owing to their consistent detection in reagent blank samples. PFAS analyses were strongly impacted by matrix, therefore the use of isotopically labelled internal standards was critical to the development of accurate results. The accuracy of the method using numerous proficiency testing schemes or interlaboratory comparison studies has shown the developed method to be successful with z-scores for all concerned analytes in all test matrices remaining within ±2.0, with the exception of PFBA in wheat flour which was −2.4. [ABSTRACT FROM AUTHOR]

Objectives: To summarize and assess the literature on the performances of methods beyond the Friedewald formula (FF) used in routine practice to determine low-density lipoprotein cholesterol (LDL-C).Methods: A literature review was performed by searching the PubMed database. Many peer-reviewed articles were assessed.Results: The examined methods included direct homogeneous LDL-C assays, the FF, mathematical equations derived from the FF, the Martin-Hopkins equation (MHE), and the Sampson equation. Direct homogeneous assays perform inconsistently across manufacturers and disease status, whereas most FF-derived methods exhibit variable levels of performance across populations. The MHE consistently outperforms the FF but cannot be applied in the setting of severe hypertriglyceridemia. The Sampson equation shows promise against both the FF and MHE, especially in severe hypertriglyceridemia, but data are still limited on its validation in various settings, including disease and therapeutic states.Conclusions: There is still no consensus on a universal best method to estimate LDL-C in routine practice. Further studies are needed to assess the performance of the Sampson equation. [ABSTRACT FROM AUTHOR]

Daylight is an important component in maintaining human health and wellbeing and plays a key role in physiological, psychological, and behavioural regulation. Understanding the complexity of daylight perception is vital since the degree of satisfaction with daylight conditions could greatly impact individual mood, behaviour and cognitive performance. This paper aims at (1) presenting an overview of current knowledge on methods for assessing daylight perception and (2) establishing a methodology for assessing daylight perception in the context of cultural background. An experiment was conducted with 50 students who were instructed to select the best and worst seats, describe the best desks’ daylight conditions and draw boundary lines between perceived daylit and non-daylit spaces in a library. The study showed that subjective rating and seat preference methods were consistent with actual daylight levels. However, participants’ boundary lines did not represent the actual daylight availability in the space. The study suggests that individual daylight perception in the context of cultural background can be assessed using the subjective rating and seat preference methods.

Keywords: biotin; ECLIA; immunoassay; method evaluation; thyroglobulin EN biotin ECLIA immunoassay method evaluation thyroglobulin e46 e49 4 01/07/22 20220115 NES 220115 To the Editor, Biotin interference in immunoassays is well-known and researched [[1]]. Exogenous biotin disturbs this interaction, potentially causing falsely decreased results for sandwich immunoassays, such as the Elecsys SP ® sp thyroglobulin (Tg) assay (Roche Diagnostics, Switzerland) [[4]]. Plasma peak concentrations induced by OTC supplements (53-141 ng/mL) or by treatment with high biotin doses (up to 1,160 ng/mL plasma levels) do not exceed the biotin threshold of the Tg2New assay insert or our experimentally confirmed threshold [[1]]. [Extracted from the article]

Background: Serum protein electrophoresis is one of the core investigations for screening for monoclonal proteins. Among the available capillary systems, the Helena V8 system has been evaluated in a limited number of studies. Methods: In total, 310 sera samples were assessed on the Helena V8 system and compared with the Sebia Capillarys instrument. Abnormalities suggestive of monoclonal proteins were confirmed by immunofixation. Imprecision studies and reference intervals were determined. Results: The imprecision of the Helena V8 was inferior or equal to 5.8%. The mean bias of Helena V8 vs Sebia Capillarys was about −0.9 g/L for albumin; −0.2 g/L for alpha-1; 1.1 g/L for alpha-2; −0.2 g/L for beta; 0.3 g/L for gamma; −0.5 g/L for monoclonal protein in beta; and 0.3 g/L for monoclonal protein in gamma. Among the 56 samples with monoclonal proteins confirmed by immunofixation, all were seen on both methods, with only 1 discordant result at a cutoff of 5.0 g/L. Reference intervals were statistically different between the 2 analyzers, except for the beta fraction. Conclusions: Our evaluation confirms the good analytical performance of the Helena V8 analyzer as a suitable alternative to the Sebia Capillarys instrument. [ABSTRACT FROM AUTHOR]