The within- and between-laboratories reproducibility and predictive capacity of Amino acid Derivative Reactivity Assay using 4 mM test chemical solution: Results of ring study implemented at five participating laboratories.

Amino acid derivative reactivity assay (ADRA) for skin sensitization was adopted as an alternative method in the 2019 OECD Guideline for the Testing of Chemicals (OECD TG 442C). The molar ratio of the nucleophilic reagent to the test chemicals in the reaction solution was set to 1:50. Imamura et al. reported that changing this molar ratio from 1:50 to 1:200 reduced in false negatives and improved prediction accuracy. Hence, a ring study using ADRA with 4 mM of a test chemical solution (ADRA, 4 mM) was conducted at five different laboratories to verify within- and between-laboratory reproducibilities (WLR and BLR, respectively). In this study, we investigated the WLR and BLR using 14 test chemicals grouped into three classes: (1) eight proficiency substances, (2) four test chemicals that showed false negatives in the ADRA with 1 mM test chemical solution (ADRA, 1 mM), but correctly positive in ADRA (4 mM), and (3) current positive control (phenylacetaldehyde) and a new additional positive control (squaric acid diethyl ester). The results showed 100% reproducibility and 100% accuracy for skin sensitization. Hence, it is clear that the ADRA (4 mM) is an excellent test method in contrast to the currently used ADRA (1 mM). We plan to resubmit the ADRA (4 mM) test method to the OECD Test Guideline Group in the near future so that OECD TG 442C could be revised for the convenience and benefit of many ADRA users.

Cardiotoxicity Hazard and Risk Characterization of ToxCast Chemicals Using Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes from Multiple Donors.

Heart disease remains a significant human health burden worldwide with a significant fraction of morbidity attributable to environmental exposures. However, the extent to which the thousands of chemicals in commerce and the environment may contribute to heart disease morbidity is largely unknown, because in contrast to pharmaceuticals, environmental chemicals are seldom tested for potential cardiotoxicity. Human induced pluripotent stem cell (iPSC)-derived cardiomyocytes have become an informative in vitro model for cardiotoxicity testing of drugs with the availability of cells from multiple individuals allowing in vitro testing of population variability. In this study, we hypothesized that a panel of iPSC-derived cardiomyocytes from healthy human donors can be used to screen for the potential cardiotoxicity hazard and risk of environmental chemicals. We conducted concentration-response testing of 1029 chemicals (drugs, pesticides, flame retardants, polycyclic aromatic hydrocarbons (PAHs), plasticizers, industrial chemicals, food/flavor/fragrance agents, etc.) in iPSC-derived cardiomyocytes from 5 donors. We used kinetic calcium flux and high-content imaging to derive quantitative measures as inputs into Bayesian population concentration-response modeling of the effects of each chemical. We found that many environmental chemicals pose a hazard to human cardiomyocytes in vitro with more than half of all chemicals eliciting positive or negative chronotropic or arrhythmogenic effects. However, most of the tested environmental chemicals for which human exposure and high-throughput toxicokinetics data were available had wide margins of exposure and, thus, do not appear to pose a significant human health risk in a general population. Still, relatively narrow margins of exposure (<100) were estimated for some perfuoroalkyl substances and phthalates, raising concerns that cumulative exposures may pose a cardiotoxicity risk. Collectively, this study demonstrated the value of using a population-based human in vitro model for rapid, high-throughput hazard and risk characterization of chemicals for which little to no cardiotoxicity data are available from guideline studies in animals.

Clinical Significance of Low Serum Cryptococcal Antigen Titers by Lateral Flow Assay in Immunocompromised Patients: a Retrospective Case-Control Study.

Cryptococcus species are associated with invasive fungal infections in immunosuppressed individuals. The clinical significance of low-titer cryptococcal antigen (CrAg) by lateral flow assay is frequently uncertain. We investigated the correlation of low CrAg titers with disease in an immunocompromised patient population. Patients with first-time positive CrAg results with low serum titers (≤1:10) at two medical centers (Los Angeles, CA) from April 2014 to July 2018 were included. Age-matched controls with high (≥1:20) and negative titers were selected. We extracted medical records for pertinent clinical, radiologic, and laboratory data for cryptococcal disease. From 2,196 serum samples submitted for CrAg testing, 96 cases were included (32 each in low-titer, high-titer, and negative-titer groups). One or more immunocompromising condition was identified in 95% of patients, including HIV infection (45%), solid organ transplant (26%), and cirrhosis (22%). Pulmonary cryptococcosis was diagnosed in 9 (28%) low-titer and 8 (25%) high-titer patients (P = 1.00). Disseminated cryptococcosis occurred in 7 (22%) low-titer and 15 (47%) high-titers cases (P = 0.064). Titers ≤1:10 more frequently represented isolated antigenemia in HIV-positive than non-HIV, immunocompromised patients (P < 0.001). Follow-up testing in patients with ≤1:5 titers (n = 21) showed persistently low titers in 6 of 12 instances and increased titers in 2 cases. Twenty-seven patients with low CrAg titers were treated with antifungal therapy and 22 (81%) responded well clinically. Low-serum CrAg titers (≤1:10) correlated with cryptococcal disease in a substantial proportion of non-HIV immunocompromised patients and should prompt careful clinical workup for cryptococcal infection.

Hospital physicians' experiences with procalcitonin - implications for antimicrobial stewardship; a qualitative study.

BACKGROUND: Procalcitonin is an inflammatory biomarker that is sensitive for bacterial infections and a promising clinical decision aid in antimicrobial stewardship programs. However, there are few studies of physicians' experiences concerning the use of PCT. The objective of this study was to investigate whether hospital physicians' experience with procalcitonin after 18 months of use can inform the PCT implementation in antimicrobial stewardship programs. MATERIALS/METHODS: We deployed a qualitative approach using semi-structured interviews with 14 hospital physicians who had experience with procalcitonin in clinical practice. Interviews were audio-taped, transcribed verbatim and analysed using thematic analysis. RESULTS: Physicians reported a knowledge gap, which made them uncertain about the appropriate procalcitonin use, interpretation, and trustworthiness. Simultaneously, the physicians experienced procalcitonin as a useful clinical decision aid but emphasised that their clinical evaluation of the patient was the most important factor when deciding on antibiotic treatment. CONCLUSIONS: Procalcitonin was regarded a helpful clinical tool, but the physicians called for more knowledge about its appropriate uses. Active implementation of unambiguous procalcitonin algorithms and physician education may enhance the utility of the test as an antimicrobial stewardship adjunct.

A curve similarity approach to parallelism testing in bioassay.

Potency determination via bioassay is a relative measure that requires an evaluation of parallelism between the dose-response relationships of a reference standard and a sample material. Typical approaches for assessing parallelism include difference ([Formula: see text]-value) and equivalence tests. These traditional methods rely on a statistical assessment of model parameters as opposed to direct evaluation of the similarity of the dose-response curves. We propose a simple curve similarity approach that tests the hypothesis that the sample material is a dilution or concentration of the reference standard. The test is achieved by quantifying and normalizing the total area between the two curves and provides a single composite measure of parallelism. Both a frequentist and a Bayesian approach to the test are provided. We show through a simulation study that the curve similarity approach overcomes the drawbacks of the traditional methods and is effective at detecting parallelism and non-parallelism for bioassays.

Comparisons of outlier tests for potency bioassays.

Potency bioassays are used to measure biological activity. Consequently, potency is considered a critical quality attribute in manufacturing. Relative potency is measured by comparing the concentration-response curves of a manufactured test batch with that of a reference standard. If the curve shapes are deemed similar, the test batch is said to exhibit constant relative potency with the reference standard, a critical requirement for calibrating the potency of the final drug product. Outliers in bioassay potency data may result in the false acceptance/rejection of a bad/good sample and, if accepted, may yield a biased relative potency estimate. To avoid these issues, the USP<1032> recommends the screening of bioassay data for outliers prior to performing a relative potency analysis. In a recently published work, the effects of one or more outliers, outlier size, and outlier type on similarity testing and estimation of relative potency were thoroughly examined, confirming the USP<1032> outlier guidance. As a follow-up, several outlier detection methods, including those proposed by the USP<1010>, are evaluated and compared in this work through computer simulation. Two novel outlier detection methods are also proposed. The effects of outlier removal on similarity testing and estimation of relative potency were evaluated, resulting in recommendations for best practice.

Factors affecting salivary α-amylase levels measured with a handheld biosensor and a standard laboratory assay.

OBJECTIVES: A handheld biosensor for measuring salivary α-amylase (sAA) was developed for convenient on-site measurement. Previous studies reported some discrepancies in sAA levels measured with a biosensor and a standard assay. This study aimed to compare sAA levels measured with three different methods and the factors affecting its levels. METHODS: Thirty-eight participants collected saliva two times for three measurements. First, the collector strip was placed under the tongue for 2 minutes, then the strip was used to measure sAA level on-site immediately (intraoral biosensor; method 1). Then, a participant pooled the saliva for 4 minutes and collected the saliva into the tube which was aliquoted to measure in a laboratory with a handheld biosensor (extraoral biosensor; method 2) and with a standard enzyme kinetic assay (EKA; method 3). Additional experiments were carried out to compare the levels of sAA measured with differences in pooling time and positioning of the collector strip. RESULTS: A high correlation of sAA levels between an extraoral and an EKA measurement (r = 0.989) was observed, while sAA levels measured with an intraoral method showed a significant but weaker correlation with either an EKA (r = 0.475) or an extraoral method (r = 0.436). Saliva pooling time and positioning of the collector strip significantly affected sAA levels. CONCLUSIONS: A handheld biosensor is valid to measure sAA levels extraorally. For an intraoral measurement, pooling time and positioning of the collector strip need to be taken into account.

A fast and reliable test for parallelism in bioassay.

Parallelism in bioassay is a synonym of similarity between two concentration-response curves. Before the determination of relative potency in bioassays, it is necessary to test for and claim parallelism between the pair of concentration-response curves of reference standard and test sample. Methods for parallelism testing include p-value-based significance tests and interval-based equivalence tests. Most of the latter approaches make statistical inference about the equivalence of parameters of the concentration-response curve models. An apparent drawback of such methods is that equivalence in model parameters does not guarantee similarity between the reference and test sample. In contrast, a Bayesian method was recently proposed that directly tests the parallelism hypothesis that the concentration-response curve of the test sample is a horizontal shift of that of the reference. In other words, the testing sample is a dilution or concentration of the reference standard. The Bayesian approach is shown to protect against type I error and provides sufficient statistical power for parallelism testing. In practice, however, it is challenging to implement the method as it requires both specialized Bayesian software and a relatively long run time. In this paper, we propose a frequentist version of the test with split-second run time. The empirical properties of the frequentist parallelism test method are evaluated and compared with the original Bayesian method. It is demonstrated that the frequentist method is both fast and reliable for parallelism testing for a variety of concentration-response models.

Measuring precision in bioassays: Rethinking assay validation.

The m:n:θb procedure is often used for validating an assay for precision, where m levels of an analyte are measured with n replicates at each level, and if all m estimates of coefficient of variation (CV) are less than θb , then the assay is declared validated for precision. The statistical properties of the procedure are unknown so there is no clear statistical statement of precision upon passing. Further, it is unclear how to modify the procedure for relative potency assays in which the constant standard deviation (SD) model fits much better than the traditional constant CV model. We use simple normal error models to show that under constant CV across the m levels, the probability of passing when the CV is θb is about 10% to 20% for some recommended implementations; however, for extreme heterogeniety of CV when the largest CV is θb , the passing probability can be greater than 50%. We derive 100q% upper confidence limits on the CV under constant CV models and derive analogous limits for the SD under a constant SD model. Additionally, for a post-validation assay output of y, we derive 68.27% confidence intervals on either the mean or log geometric mean of the assay output using either y±s (for the constant SD model) or log(y)±rG (for the constant CV model), where s and rG are constants that do not depend on y. We demonstrate the methods on a growth inhibition assay used to measure biologic activity of antibodies against the malaria parasite.

A Bayesian analysis of quantal bioassay experiments incorporating historical controls via Bayes factors.

This paper addresses model-based Bayesian inference in the analysis of data arising from bioassay experiments. In such experiments, increasing doses of a chemical substance are given to treatment groups (usually rats or mice) for a fixed period of time (usually 2 years). The goal of such an experiment is to determine whether an increased dosage of the chemical is associated with increased probability of an adverse effect (usually presence of adenoma or carcinoma). The data consists of dosage, survival time, and the occurrence of the adverse event for each unit in the study. To determine whether such relationship exists, this paper proposes using Bayes factors to compare two probit models, the model that assumes increasing dose effects and the model that assumes no dose effect. These models account for the survival time of each unit through a Poly-k type correction. In order to increase statistical power, the proposed approach allows the incorporation of information from control groups from previous studies. The proposed method is able to handle data with very few occurrences of the adverse event. The proposed method is compared with a variation of the Peddada test via simulation and is shown to have higher power. We demonstrate the method by applying it to the two bioassay experiment datasets previously analyzed by other authors. Copyright © 2017 John Wiley & Sons, Ltd.

Rational use of Xpert testing in patients with presumptive TB: clinicians should be encouraged to use the test-treat threshold.

BACKGROUND: A recently published Ugandan study on tuberculosis (TB) diagnosis in HIV-positive patients with presumptive smear-negative TB, which showed that out of 90 patients who started TB treatment, 20% (18/90) had a positive Xpert MTB/RIF (Xpert) test, 24% (22/90) had a negative Xpert test, and 56% (50/90) were started without Xpert testing. Although Xpert testing was available, clinicians did not use it systematically. Here we aim to show more objectively the process of clinical decision-making. First, we estimated that pre-test probability of TB, or the prevalence of TB in smear-negative HIV infected patients with signs of presumptive TB in Uganda, was 17%. Second, we argue that the treatment threshold, the probability of disease at which the utility of treating and not treating is the same, and above which treatment should be started, should be determined. In Uganda, the treatment threshold was not yet formally established. In Rwanda, the calculated treatment threshold was 12%. Hence, one could argue that the threshold was reached without even considering additional tests. Still, Xpert testing can be useful when the probability of disease is above the treatment threshold, but only when a negative Xpert result can lower the probability of disease enough to cross the treatment threshold. This occurs when the pre-test probability is lower than the test-treat threshold, the probability of disease at which the utility of testing and the utility of treating without testing is the same. We estimated that the test-treatment threshold was 28%. Finally, to show the effect of the presence or absence of arguments on the probability of TB, we use confirming and excluding power, and a log10 odds scale to combine arguments. CONCLUSION: If the pre-test probability is above the test-treat threshold, empirical treatment is justified, because even a negative Xpert will not lower the post-test probability below the treatment threshold. However, Xpert testing for the diagnosis of TB should be performed in patients for whom the probability of TB was lower than the test-treat threshold. Especially in resource constrained settings clinicians should be encouraged to take clinical decisions and use scarce resources rationally.

A simple method for optimising transformation of non-parametric data: an illustration by reference to cortisol assays.

Neuroendocrine data are typically positively skewed and rarely conform to the expectations of a Gaussian distribution. This can be a problem when attempting to analyse results within the framework of the general linear model, which relies on assumptions that residuals in the data are normally distributed. One frequently used method for handling violations of this assumption is to transform variables to bring residuals into closer alignment with assumptions (as residuals are not directly manipulated). This is often attempted through ad hoc traditional transformations such as square root, log and inverse. However, Box and Cox (Box & Cox, ) observed that these are all special cases of power transformations and proposed a more flexible method of transformation for researchers to optimise alignment with assumptions. The goal of this paper is to demonstrate the benefits of the infinitely flexible Box-Cox transformation on neuroendocrine data using syntax in spss. When applied to positively skewed data typical of neuroendocrine data, the majority (~2/3) of cases were brought into strict alignment with Gaussian distribution (i.e. a non-significant Shapiro-Wilks test). Those unable to meet this challenge showed substantial improvement in distributional properties. The biggest challenge was distributions with a high ratio of kurtosis to skewness. We discuss how these cases might be handled, and we highlight some of the broader issues associated with transformation. Copyright © 2016 John Wiley & Sons, Ltd.

Testing for parallelism in the heteroscedastic four-parameter logistic model.

For bioassay data in drug discovery and development, it is often important to test for parallelism of the mean response curves for two preparations, such as a test sample and a reference sample in determining the potency of the test preparation relative to the reference standard. For assessing parallelism under a four-parameter logistic model, tests of the parallelism hypothesis may be conducted based on the equivalence t-test or the traditional F-test. However, bioassay data often have heterogeneous variance across dose levels. Specifically, the variance of the response may be a function of the mean, frequently modeled as a power of the mean. Therefore, in this article we discuss estimation and tests for parallelism under the power variance function. Two examples are considered to illustrate the estimation and testing approaches described. A simulation study is also presented to compare the empirical properties of the tests under the power variance function in comparison to the results from ordinary least squares fits, which ignore the non-constant variance pattern.

Statistical considerations for a chronic bioassay study: Exposure to Decamethylcyclopentasiloxane (D5) and incidence of uterine endometrial adenocarcinomas in a 2-year inhalation study with Fischer rats.

Decamethylcyclopentasiloxane (D5) is a cyclic siloxane used in the production of industrial and consumer products. Four groups of 60 Fischer-344 female rats were analyzed for uterine endometrial adenocarcinoma (inhalation study with exposure levels in ppm/number of observed cases: 0/0, 10/1, 40/0, and 160/5) by exact regression (logistic, Poisson), the max poly-3 trend test, and a random effects probit model. When comparing the 160 ppm group to controls after 24 months, the incidence of adenocarcinomas was elevated (borderline significant); it was significant when all exposure levels were included. Four sets of (historical) control groups were formed, with varying heterogeneity. The effect of D5 was either significant or borderline significant when comparing all control sets to the 160 ppm group. When considering all exposure groups using any of the analysis methods, a significant effect was observed when the high dose group was included in the analysis; the effect was not significant when the high dose group was not included. The evidence tends to support the conclusion that D5 at the highest dose level (160 ppm) results in an increased incidence of adenocarcinomas. However, it is important to verify any potential effect through a biological investigation.

[The waterpipe (shisha) - indoor air quality, human biomonitoring, and health effects]. / Die Wasserpfeife (Shisha) ­ Innenraumluftqualität, Human-Biomonitoring und Gesundheitseffekte.

Waterpipe (WP) smoking, also known as shisha or hookah smoking, is growing in western countries as an alternative to cigarette smoking, especially in younger age groups. A majority of smokers mistakenly believe that shisha smoking is a social entertainment practice that leads to more social behavior and relaxation and that this type of smoking is safe or less harmful and less addictive than cigarette smoking.In reality, WP smokers are exposed to hundreds of toxic substances that include well-known carcinogens. High exposures to carbon monoxide and nicotine are major health threats. There is growing evidence that WP smoke causes adverse effects on the pulmonary and cardiovascular systems and there are indications that WP smoke is associated with cancer. Persons exposed to secondhand WP smoke are also at risk.More research on the health effects of WP is urgently needed and more preventive measures for public health protection. Moreover, public WP facilities should be implemented under specific nonsmoker protection laws and consequently controlled.This review summarizes recent data on exposure to WP smoking in indoor environments, the results of biomonitoring data, and the known health effects based on currently available toxicological or epidemiological studies.

Outlier robust nonlinear mixed model estimation.

In standard analyses of data well-modeled by a nonlinear mixed model, an aberrant observation, either within a cluster, or an entire cluster itself, can greatly distort parameter estimates and subsequent standard errors. Consequently, inferences about the parameters are misleading. This paper proposes an outlier robust method based on linearization to estimate fixed effects parameters and variance components in the nonlinear mixed model. An example is given using the four-parameter logistic model and bioassay data, comparing the robust parameter estimates with the nonrobust estimates given by SAS(®).

Pitfalls in the diagnosis of heparin-Induced thrombocytopenia: A 6-year experience from a reference laboratory.

Heparin-induced thrombocytopenia (HIT) is caused by platelet-activating antibodies against complexes of platelet factor 4 (PF4) and heparin. The diagnosis of HIT is contingent on accurate and timely laboratory testing. Recently, alternative anticoagulants for the treatment of HIT have been introduced along with algorithms for better HIT diagnosis. However, the increased reliance on immunoassays for the diagnosis of HIT may have harmful consequences due to the high rate of false positive results. To compare trends and implications of current HIT testing approaches, we analyzed results over a six-year period from the McMaster University Platelet Immunology Reference Laboratory. From 2008 to 2013, 8,546 samples were investigated for HIT using both an in-house IgG-specific anti-PF4/heparin enzyme immunoassay (EIA) and the serotonin-release assay (SRA). Of 8,546 samples tested, 13.4% were true-positives (positive in both assays); 65.6% were true-negatives (negative in both assays); 20.9% were presumed false positive for HIT (EIA-positive/SRA-negative); and 0.2% were EIA-negative/SRA-positive. The frequency of EIA-positive/SRA-negative results increased over time (from 12.9% in 2008 to 22.9% in 2013). We found that the number of SRA-negative samples was reduced from referring centers that used an immunoassay as an initial screen; however, 41% of those samples tested negative in the immunoassay and in the SRA at the reference laboratory. The suspicion of HIT continues at a high rate and the agreement between the EIA and SRA test results remains problematic.

Time dependent analysis of assay comparability: a novel approach to understand intra- and inter-site variability over time.

We demonstrate here a novel use of statistical tools to study intra- and inter-site assay variability of five early drug metabolism and pharmacokinetics in vitro assays over time. Firstly, a tool for process control is presented. It shows the overall assay variability but allows also the following of changes due to assay adjustments and can additionally highlight other, potentially unexpected variations. Secondly, we define the minimum discriminatory difference/ratio to support projects to understand how experimental values measured at different sites at a given time can be compared. Such discriminatory values are calculated for 3 month periods and followed over time for each assay. Again assay modifications, especially assay harmonization efforts, can be noted. Both the process control tool and the variability estimates are based on the results of control compounds tested every time an assay is run. Variability estimates for a limited set of project compounds were computed as well and found to be comparable. This analysis reinforces the need to consider assay variability in decision making, compound ranking and in silico modeling.

The use of plant-based bioassays in homeopathic basic research.

OBJECTIVES: The objective was to evaluate homeopathic basic research studies that use plant-based bioassays. With this in view, a compilation was made of the findings of three systematic literature reviews covering plant-based bioassays in the three fields of healthy, abiotically, or biotically stressed plants. This compilation focused on investigations using advanced experimental methods and detailed descriptions, also with the aim of supporting the design of future experiments. METHODS: Publications included had to report on studies into the effects of homeopathic preparations on whole plants, seeds, plant parts and cells. Outcomes had to be measured by established procedures and statistically evaluated. A Manuscript Information Score (MIS) was applied using predefined criteria to identify publications with sufficient information for adequate interpretation (MIS ≥ 5). Additional evaluation focused on the use of adequate controls to investigate specific effects of homeopathic preparations, and on the use of systematic negative control (SNC) experiments to ensure the stability of the bioassay. Only a fraction of the studies reported here were performed with 'ultra high' dilutions, whereas other studies were performed with moderate or high dilutions. RESULTS: A total of 157 publications were identified, describing a total of 167 experimental studies. 84 studies included statistics and 48 had a MIS ≥ 5, thus allowing adequate interpretation. 29 studies had adequate controls to identify specific effects of homeopathic preparations, and reported significant effects of decimal and centesimal homeopathic potencies, including dilution levels beyond Avogadro's number. 10 studies reported use of SNC experiments, yielding evidence for the stability of the experimental set-up. CONCLUSION: Plant models appear to be a useful approach for investigating basic research questions relating to homeopathic preparations, but more independent replication trials are needed in order to verify the results found in single experiments. Adequate controls and SNC experiments should be implemented on a routine basis to exclude false-positive results.

The utility of yeast as a tool for cell-based, target-directed high-throughput screening.

Many Neglected Tropical Diseases (NTDs) have recently been subject of increased focus, particularly with relation to high-throughput screening (HTS) initiatives. These vital endeavours largely rely of two approaches, in vitro target-directed screening using biochemical assays or cell-based screening which takes no account of the target or targets being hit. Despite their successes both of these approaches have limitations; for example, the production of soluble protein and a lack of cellular context or the problems and expense of parasite cell culture. In addition, both can be challenging to miniaturize for ultra (u)HTS and expensive to utilize. Yeast-based systems offer a cost-effective approach to study and screen protein targets in a direct-directed manner within a eukaryotic cellular context. In this review, we examine the utility and limitations of yeast cell-based, target-directed screening. In particular we focus on the currently under-explored possibility of using such formats in uHTS screening campaigns for NTDs.