Teratogenicity is more likely a function of primary and secondary pharmacology than caused by chemically reactive metabolites: a critical evaluation of 40 years of scientific research.

The number of therapeutic drugs known to be human teratogens is actually relatively small. This may reflect the rigorous animal testing and well defined labelling. Some of these drugs were identified to have reactive metabolites and this has been postulated, historically, to be their teratogenic mechanism. These drugs include thalidomide, various anticonvulsants and retinoic acid derivatives.Many of these experiments were conducted in a period where chemically reactive metabolites were being intensely investigated and associated with all forms of toxicity. The legacy of this is that these examples are routinely cited as well established mechanisms.Examination of mechanism leads to the conclusion that the teratogenicity in humans of these compounds is likely due to the primary and secondary pharmacology of the parent drug and stable circulating metabolites and that association of reactive metabolites to this toxicity is unwarranted.

Hepatotoxicity of silver nanoparticles: Benchmark concentration modeling of an in vitro transcriptomics study in human iPSC-derived hepatocytes.

Despite two decades of research on silver nanoparticle (AgNP) toxicity, a safe threshold for exposure has not yet been established, albeit being critically needed for risk assessment and regulatory decision-making. Traditionally, a point-of-departure (PoD) value is derived from dose response of apical endpoints in animal studies using either the no-observed-adverse-effect level (NOAEL) approach, or benchmark dose (BMD) modeling. To develop new approach methodologies (NAMs) to inform human risk assessment of AgNPs, we conducted a concentration response modeling of the transcriptomic changes in hepatocytes derived from human induced pluripotent stem cells (iPSCs) after being exposed to a wide range concentration (0.01-25 µg/ml) of AgNPs for 24 h. A plausible transcriptomic PoD of 0.21 µg/ml was derived for a pathway related to the mode-of-action (MOA) of AgNPs, and a more conservative PoD of 0.10 µg/ml for a gene ontology (GO) term not apparently associated with the MOA of AgNPs. A reference dose (RfD) could be calculated from either of the PoDs as a safe threshold for AgNP exposure. The current study illustrates the usefulness of in vitro transcriptomic concentration response study using human cells as a NAM for toxicity study of chemicals that lack adequate toxicity data to inform human risk assessment.

Long-term ozone exposure and all-cause mortality: Cohort evidence in China and global heterogeneity by region.

BACKGROUND: Cohort evidence linking long-term ozone (O3) exposure to mortality remained largely mixed worldwide and was extensively deficient in densely-populated Asia. This study aimed to assess the long-term effects of O3 exposure on all-cause mortality among Chinese adults, as well as to examine potential regional heterogeneity across the globe. METHODS: A national dynamic cohort of 42153 adults aged 16+ years were recruited from 25 provinces across Chinese mainland and followed up during 2010-2018. Annual warm-season (April-September) O3 and year-round co-pollutants (i.e., nitrogen dioxide [NO2] and fine particulate matter [PM2.5]) were simulated through validated spatial-temporal prediction models and were assigned to each enrollee in each calendar year. Cox proportional hazards models with time-varying exposures were employed to assess the O3-mortality association. Concentration-response (C-R) curves were fitted by natural cubic spline function to investigate the potential nonlinear association. Both single-pollutant model and co-pollutant models additionally adjusting for PM2.5 and/or NO2 were employed to examine the robustness of the estimated association. The random-effect meta-analysis was adopted to pool effect estimates from the current and prior population-based cohorts (n = 29), and pooled C-R curves were fitted through the meta-smoothing approach by regions. RESULTS: The study population comprised of 42153 participants who contributed 258921.5 person-years at risk (median 6.4 years), of whom 2382 death events occurred during study period. Participants were exposed to an annual average of 51.4 ppb (range: 22.7-74.4 ppb) of warm-season O3 concentration. In the single-pollutant model, a significantly increased hazard ratio (HR) of 1.098 (95% confidence interval [CI]: 1.023-1.179) was associated with a 10-ppb rise in O3 exposure. Associations remained robust to additional adjustments of co-pollutants, with HRs of 1.099 (95% CI: 1.023-1.180) in bi-pollutant model (+PM2.5) and 1.093 (95% CI: 1.018-1.174) in tri-pollutant model (+PM2.5+NO2), respectively. A J-shaped C-R relationship was identified among Chinese general population, suggesting significant excess mortality risk at high ozone exposure only. The combined C-R curves from Asia (n = 4) and North America (n = 17) demonstrated an overall increased risk of all-cause mortality with O3 exposure, with pooled HRs of 1.124 (95% CI: 0.966-1.307) and 1.023 (95% CI: 1.007-1.039) per 10-ppb rise, respectively. Conversely, an opposite association was observed in Europe (n = 8, HR: 0.914 [95% CI: 0.860-0.972]), suggesting significant heterogeneity across regions (P < 0.01). CONCLUSIONS: This study provided national evidence that high O3 exposure may curtail long-term survival of Chinese general population. Great between-region heterogeneity of pooled O3-mortality was identified across North America, Europe, and Asia.

Association between PM10 pollution and the hospitalization of chronic obstructive pulmonary disease with comorbidity: evidence in 17 cities of Henan, Central China.

Particulate matter (PM10) changes have been confirmed as one of the contributory factors affecting human health, the association between PM10 pollution and the hospitalization of chronic obstructive pulmonary disease (COPD) with comorbidity diseases was rarely reported. The same inpatient more than twice times admissions with COPD illness from January 1, 2016 to December 31, 2021 were identified from hospitals in the 17 cities of Henan, Central China. City-specific associations were firstly estimated using the case time series (CTS) model and then combined to obtain the regional average association. The multivariate meta-analytic model produces pooled estimates of the set of coefficients representing the PM10-COPD hospitalizations association across the 17 cities. Cause-specific hospitalization analyses were performed by COPD patients with different comorbidity combinations. A total of 34,348 elderly (age ≥ 65) subjects were analyzed and with a total of 35,122.35 person-years. These coefficients can be used to compute the linear exposure-response curve expressed as relative risk (RR) in per 10 µg/m3 increase in PM10 at lag03, which was 1.0091 (95% CI 1.0070-1.0112) for COPD with comorbidity, 1.0089 (95% CI 1.0067-1.0110) for COPD with circulatory system diseases, 1.0079 (95% CI 1.0052-1.0105) for COPD with respiratory system diseases, 1.0076 (95% CI 1.0032-1.0121) for COPD with endocrine system diseases, and 1.0087 (95% CI 1.0013-1.0162) for COPD with genitourinary system diseases, respectively. Some heterogeneity was found across cities, with estimates ranging from 1.0227 in the Puyang and Jiaozuo to 1.0053 in Henan Provance, China. The effect of higher PM10, on average, was higher in studies for northern cities, with a steeper raise in risk: per 10 µg/m3 increase in PM10, the RR from 1.0062 (95% CI 1.0030-1.0093) for the 10th percentile of latitude to 1.0124 (95% CI 1.0089-1.0160) for the 90th percentile. Our findings indicated that PM10 exposure may increase the risk of hospitalizations for COPD with comorbidity. Moreover, there might be a higher morbidity risk associated with PM10 in northern latitudes, indicating that stricter air quality standards could potentially reduce PM10-related morbidity among individuals with COPD. These findings have implications for the implementation of effective clean air interventions aligned with national climate policies.

Application of Cell Painting for chemical hazard evaluation in support of screening-level chemical assessments.

'Cell Painting' is an imaging-based high-throughput phenotypic profiling (HTPP) method in which cultured cells are fluorescently labeled to visualize subcellular structures (i.e., nucleus, nucleoli, endoplasmic reticulum, cytoskeleton, Golgi apparatus / plasma membrane and mitochondria) and to quantify morphological changes in response to chemicals or other perturbagens. HTPP is a high-throughput and cost-effective bioactivity screening method that detects effects associated with many different molecular mechanisms in an untargeted manner, enabling rapid in vitro hazard assessment for thousands of chemicals. Here, 1201 chemicals from the ToxCast library were screened in concentration-response up to ∼100 µM in human U-2 OS cells using HTPP. A phenotype altering concentration (PAC) was estimated for chemicals active in the tested range. PACs tended to be higher than lower bound potency values estimated from a broad collection of targeted high-throughput assays, but lower than the threshold for cytotoxicity. In vitro to in vivo extrapolation (IVIVE) was used to estimate administered equivalent doses (AEDs) based on PACs for comparison to human exposure predictions. AEDs for 18/412 chemicals overlapped with predicted human exposures. Phenotypic profile information was also leveraged to identify putative mechanisms of action and group chemicals. Of 58 known nuclear receptor modulators, only glucocorticoids and retinoids produced characteristic profiles; and both receptor types are expressed in U-2 OS cells. Thirteen chemicals with profile similarity to glucocorticoids were tested in a secondary screen and one chemical, pyrene, was confirmed by an orthogonal gene expression assay as a novel putative GR modulating chemical. Most active chemicals demonstrated profiles not associated with a known mechanism-of-action. However, many structurally related chemicals produced similar profiles, with exceptions such as diniconazole, whose profile differed from other active conazoles. Overall, the present study demonstrates how HTPP can be applied in screening-level chemical assessments through a series of examples and brief case studies.

Identifying alert concentrations using a model-based bootstrap approach.

The determination of alert concentrations, where a pre-specified threshold of the response variable is exceeded, is an important goal of concentration-response studies. The traditional approach is based on investigating the measured concentrations and attaining statistical significance of the alert concentration by using a multiple t-test procedure. In this paper, we propose a new model-based method to identify alert concentrations, based on fitting a concentration-response curve and constructing a simultaneous confidence band for the difference of the response of a concentration compared to the control. In order to obtain these confidence bands, we use a bootstrap approach which can be applied to any functional form of the concentration-response curve. This particularly offers the possibility to investigate also those situations where the concentration-response relationship is not monotone and, moreover, to detect alerts at concentrations which were not measured during the study, providing a highly flexible framework for the problem at hand.

Mortality attributable to ambient fine particulate matter and nitrogen dioxide in Switzerland in 2019: Use of two-pollutant effect estimates.

INTRODUCTION: Air pollution health risk assessments have traditionally used single-pollutant effect estimates for one proxy ambient air pollutant such as PM2.5. Two-pollutant effect estimates, i.e. adjusted for another correlated pollutant, theoretically enable the aggregation of pollutant-specific health effects minimizing double-counting. Our study aimed at estimating the adult mortality in Switzerland in 2019 attributable to PM2.5 from a single-pollutant effect estimate and to the sum of PM2.5 and NO2 from two-pollutant estimates; comparing the results with those from alternative global, European and Swiss effect estimates. METHODS: For the single-pollutant approach, we used a PM2.5 summary estimate of European cohorts from the project ELAPSE, recommended by the European Respiratory Society and International Society for Environmental Epidemiology (ERS-ISEE). To derive the two-pollutant effect estimates, we applied ELAPSE-based conversion factors to ERS-ISEE PM2.5 and NO2 single-pollutant effect estimates. Additionally, we used World Health Organization 2021 Air Quality Guidelines as counterfactual scenario, exposure model data from 2019 and Swiss lifetables. RESULTS: The single-pollutant effect estimate for PM2.5 (1.118 [1.060; 1.179] per 10 µg/m3) resulted in 2240 deaths (21,593 years of life lost). Using our derived two-pollutant effect estimates (1.023 [1.012; 1.035] per 10 µg/m3 PM2.5 adjusted for NO2 and 1.040 [1.023; 1.058] per 10 µg/m3 NO2 adjusted for PM2.5), we found 1977 deaths (19,071 years of life lost) attributable to PM2.5 and NO2 together (23% from PM2.5). Deaths using alternative effect estimates ranged from 1042 to 5059. DISCUSSION: Estimated premature mortality attributable to PM2.5 alone was higher than to both PM2.5 and NO2 combined. Furthermore, the proportion of deaths from PM2.5 was lower than from NO2 in the two-pollutant approach. These seemingly paradoxical results, also found in some alternative estimates, are due to statistical imprecisions of underlying correction methods. Therefore, using two-pollutant effect estimates can lead to interpretation challenges in terms of causality.

Guidance for statistical design and analysis of toxicological dose-response experiments, based on a comprehensive literature review.

The analysis of dose-response, concentration-response, and time-response relationships is a central component of toxicological research. A major decision with respect to the statistical analysis is whether to consider only the actually measured concentrations or to assume an underlying (parametric) model that allows extrapolation. Recent research suggests the application of modelling approaches for various types of toxicological assays. However, there is a discrepancy between the state of the art in statistical methodological research and published analyses in the toxicological literature. The extent of this gap is quantified in this work using an extensive literature review that considered all dose-response analyses published in three major toxicological journals in 2021. The aspects of the review include biological considerations (type of assay and of exposure), statistical design considerations (number of measured conditions, design, and sample sizes), and statistical analysis considerations (display, analysis goal, statistical testing or modelling method, and alert concentration). Based on the results of this review and the critical assessment of three selected issues in the context of statistical research, concrete guidance for planning, execution, and analysis of dose-response studies from a statistical viewpoint is proposed.

On the supra-linearity of the relationship between air pollution, mortality and hospital admission in 18 French cities.

PURPOSE: Understanding the relationship between an environmental determinant and a given health outcome is key to inform public health policies. The short-term mortality and morbidity responses to outdoor air pollutants are traditionally assessed as a log-linear relationship, but few studies suggest a possible deviation from linearity. This paper investigates the shape of the relationship between ozone, NO2 and fine particulate matter (PM10 and PM2.5), mortality and hospital admissions in 18 French cities between 2000 and 2017. METHOD: A multi-centric time series design, using quasi-Poisson generalized additive models, was used. Four approaches were compared to model concentration-response curves (log-linear, piecewise-linear with a priori defined breakpoints, piecewise-linear with no a priori breakpoint and cubic spline). RESULTS: All the models indicated evidence of supra-linearity between PM10, PM2.5, NO2, mortality and hospital admissions. For instance, with a log-linear model, a 10 µg/m3 increase in PM2.5 was associated with a 0.4% [95% CI 0.2; 0.7] increase in non-accidental mortality. When using a piecewise model with a priori set breakpoint at 10 µg/m3, the mortality increase was 3.8% [4.4; 6.3] below 10 µg/m3, and 0.3% [0; 0.6] above. Non-significant impacts of ozone were found for concentrations below 90 µg/m3 to 120 µg/m3, with some variability in the identified threshold across the heath indicator studied. CONCLUSION: The supra-linearity of the relationship between PM10, PM2.5, NO2, mortality and hospital admissions supports the need to further reduce air pollution concentrations well below regulatory values.

An investigation of non-informative priors for Bayesian dose-response modeling.

Toxicology analyses are built around dose-response modeling, and increasingly these methodologies utilize Bayesian estimation techniques. Bayesian estimation is unique because it includes prior distributional information in the analysis, which may impact the dose-response estimate meaningfully. As such analyses are often used for human health risk assessment, the practitioner must understand the impact of adding prior information to the dose-response study. One proposal in the literature is the use of the flat uniform prior distribution, which places a uniform prior probability over the dose-response model's parameters for a chosen range of values. Though the motivation of such a prior distribution is laudable in that it is most like maximum likelihood estimation seeking unbiased estimates of the dose-response, one can show that such priors add information and may introduce unexpected biases into the analysis. This manuscript shows through numerous empirical examples why prior distributions that are non-informative across all endpoints of interest do not exist for dose-response models; that is, other quantities of interest will be informed by choosing one inferential quantity not informed.

Pitavastatin and Lovastatin Exhibit Calcium Channel Blocking Activity Which Potentiate Vasorelaxant Effects of Amlodipine: A New Futuristic Dimension in Statin's Pleiotropy.

Background and Objectives: We have recently reported that Fluvastatin, Atorvastatin, Simvastatin and Rosuvastatin have calcium channel antagonistic activities using rabbits' intestinal preparations. The current study is focused on the effects of Pitavastatin and Lovastatin for possible inhibition of vascular L-Type calcium channels, which may have vasorelaxant effect(s). Combined effects of Pitavastatin and Lovastatin in the presence of Amlodipine were also tested for vasorelaxation. Materials and Methods: Possible relaxing effects of Pitavastatin and Lovastatin on 80 mM Potassium chloride (KCL)-induced contractions and on 1 µM norepinephrine (N.E)-induced contractions were studied in isolated rabbit's aortic strips preparations. Relaxing effects on 80 mM KCL-induced vascular contractions were further verified by constructing Calcium Concentration Response Curves (CCRCs), in the absence and presence of three different concentrations of Pitavastatin and Lovastatin using CCRCs as negative control. Verapamil was used as a standard drug that has L-Type calcium channel binding activity. In other series of experiments, we studied drug interaction(s) among Pitavastatin, Lovastatin, and amlodipine. Results: The results of this study imply that Lovastatin is more potent than Pitavastatin for having comparatively lower EC50 (7.44 × 10-5 ± 0.16 M) in intact and (4.55 × 10-5 ± 0.10 M) in denuded aortae for KCL-induced contractions. Lovastatin amplitudes in intact and denuded aortae for KCL-induced contractions were, respectively, 24% and 35.5%; whereas amplitudes for Pitavastatin in intact and denuded aortae for KCL-induced contractions were 34% and 40%, respectively. A left shift in the EC50 values for the statins was seen when we added amlodipine in EC50 (Log Ca++ M). Right shift for CCRCs state that Pitavastatin and Lovastatin have calcium channel antagonistic effects. Lovastatin in test concentration (6.74 × 10-7 M) produced a right shift in relatively lower EC50 (-2.5 ± 0.10) Log Ca++ M as compared to Pitavastatin, which further confirms that lovastatin is relatively more potent. The right shift in EC50 resembles the right shift of Verapamil. Additive effect of Pitavastatin and Lovastatin was noted in presence of amlodipine (p < 0.05). Conclusions: KCL (80 mM)-induced vascular contractions were relaxed by Pitavastatin and Lovastatin via inhibitory effects on L-Type voltage-gated calcium channels. Lovastatin and Pitavastatin also relaxed Norepinephrine (1 µM)-induced contractions giving an insight for involvement of dual mode of action of Pitavastatin and Lovastatin.

Combining phenotypic profiling and targeted RNA-Seq reveals linkages between transcriptional perturbations and chemical effects on cell morphology: Retinoic acid as an example.

The United States Environmental Protection Agency has proposed a tiered testing strategy for chemical hazard evaluation based on new approach methods (NAMs). The first tier includes in vitro profiling assays applicable to many (human) cell types, such as high-throughput transcriptomics (HTTr) and high-throughput phenotypic profiling (HTPP). The goals of this study were to: (1) harmonize the seeding density of U-2 OS human osteosarcoma cells for use in both assays; (2) compare HTTr- versus HTPP-derived potency estimates for 11 mechanistically diverse chemicals; (3) identify candidate reference chemicals for monitoring assay performance in future screens; and (4) characterize the transcriptional and phenotypic changes in detail for all-trans retinoic acid (ATRA) as a model compound known for its adverse effects on osteoblast differentiation. The results of this evaluation showed that (1) HTPP conducted at low (400 cells/well) and high (3000 cells/well) seeding densities yielded comparable potency estimates and similar phenotypic profiles for the tested chemicals; (2) HTPP and HTTr resulted in comparable potency estimates for changes in cellular morphology and gene expression, respectively; (3) three test chemicals (etoposide, ATRA, dexamethasone) produced concentration-dependent effects on cellular morphology and gene expression that were consistent with known modes-of-action, demonstrating their suitability for use as reference chemicals for monitoring assay performance; and (4) ATRA produced phenotypic changes that were highly similar to other retinoic acid receptor activators (AM580, arotinoid acid) and some retinoid X receptor activators (bexarotene, methoprene acid). This phenotype was observed concurrently with autoregulation of the RARB gene. Both effects were prevented by pre-treating U-2 OS cells with pharmacological antagonists of their respective receptors. Thus, the observed phenotype could be considered characteristic of retinoic acid pathway activation in U-2 OS cells. These findings lay the groundwork for combinatorial screening of chemicals using HTTr and HTPP to generate complementary information for the first tier of a NAM-based chemical hazard evaluation strategy.

Concentration-response relationships of dolutegravir and efavirenz with weight change after starting antiretroviral therapy.

Dolutegravir is associated with more weight gain than efavirenz in people starting antiretroviral therapy (ART). We investigated the concentration-response relationships of efavirenz and dolutegravir with weight gain. We determined concentration-response relationships of dolutegravir and efavirenz (both combined with tenofovir disoproxil fumarate and emtricitabine) with changes in weight and fat distribution, derived from dual-energy x-ray absorptiometry scans, in a nested study of ART-naïve participants from a randomised controlled trial. Pharmacokinetic parameters used in analyses were efavirenz mid-dosing interval concentrations and estimated dolutegravir area under the concentration-time curve using a population pharmacokinetic model developed in the study population. Study outcomes were percentage changes from baseline to week 48 in weight, and visceral and subcutaneous adipose tissue mass. Pharmacokinetic data were available for 158 and 233 participants in the efavirenz arm and dolutegravir arms respectively; 57.0% were women. On multivariable linear regression there were independent negative associations between efavirenz concentrations and changes in both weight (P < .001) and subcutaneous adipose tissue mass (P = .002). Estimated dolutegravir area under the concentration-time curve up to 24 hours was not associated with change in weight (P = .109) but was negatively associated with change in visceral adipose tissue mass (P = .025). We found an independent negative concentration-response relationship between efavirenz concentrations and weight change in ART-naïve participants. Dolutegravir concentrations were not independently associated with weight change. These findings suggest that weight gain differences between efavirenz and dolutegravir are driven by efavirenz toxicity impairing weight gain rather than by off-target effects of dolutegravir causing weight gain.

Designing health impact functions to assess marginal changes in outdoor fine particulate matter.

Estimating health benefits from improvements in ambient air quality requires the characterization of the magnitude and shape of the association between marginal changes in exposure and marginal changes in risk, and its uncertainty. Several attempts have been made to do this, each requiring different assumptions. These include the Log-Linear(LL), IntegratedExposure-Response(IER), and GlobalExposureMortalityModel(GEMM). In this paper we develop an improved relative risk model suitable for use in health benefits analysis that incorporates features of existing models while addressing limitations in each model. We model the derivative of the relative risk function within a meta-analytic framework; a quantity directly applicable to benefits analysis, incorporating a Fusion of algebraic functions used in previous models. We assume a constant derivative in concentration over low exposures, like the LL model, a declining derivative over moderate exposures observed in cohort studies, and a derivative declining as the inverse of concentration over high global exposures in a similar manner to the GEMM. The model properties are illustrated with examples of fitting it to data for the six specific causes of death previously examined by the GlobalBurdenofDisease program with ambient fine particulate matter (PM2.5). In a test case analysis assuming a 1% (benefits analysis) or 100% (burden analysis), reduction in country-specific fine particulate matter concentrations, corresponding estimated global attributable deaths using the Fusion model were found to lie between those of the IER and LL models, with the GEMM estimates similar to those based on the LL model.

Concentration-Response Model of Immediate Release Oxycodone Drug Liking by Different Routes of Abuse.

OBJECTIVE: To understand the correlation between oxycodone concentration and drug liking response for immediate-release formulations as they relate to different doses and different routes of administration following manipulation involved in opioid misuse and nontherapeutic use. METHODS: Concentration-response and noncompartmental analyses of drug liking and plasma oxycodone data from Category 3 human abuse potential studies (n = 15-29 per study) were conducted, using Phoenix 6.0 software. Time to onset of a set threshold of subjective effects (Tonset) and offset of subjective effects (Toffset) were estimated based on a baseline pharmacodynamic response set at 50 on a bipolar Drug Liking visual analog scale of 0-100 and the threshold for drug liking set at ≥65, based on study qualification criteria. Partial Area Under the Concentration (AUCTonset-Toffset) and Effect (AUETonset-Toffset) profiles were calculated and their correlation with individual partial AUE vs partial AUC was assessed. RESULTS: The oxycodone concentration-response (drug liking) was best described by a sigmoidal-effect Emax model (S-shaped). Using a defined threshold, drug liking was closely associated with the rate of rise in concentration and the onset of action for oxycodone administered via oral or intranasal route. Partial AUCTonset-Toffset and AUETonset-Toffset showed a strong linear correlation. CONCLUSIONS: Results indicate that oxycodone concentration-response and duration of drug liking following manipulation via different routes of administration may be an approach for further exploring drug liking effects of opioids.

Health effects of exposure to sulfur dioxide, nitrogen dioxide, ozone, and carbon monoxide between 1980 and 2019: A systematic review and meta-analysis.

The burden of disease attributed to the indoor exposure to sulfur dioxide (SO2 ), nitrogen dioxide (NO2 ), ozone (O3 ), and carbon monoxide (CO) is not clear, and the quantitative concentration-response relationship is a prerequisite. This is a systematic review to summarize the quantitative concentration-response relationships by screening and analyzing the polled effects of population-based epidemiological studies. After collecting literature published between 1980 and 2019, a total of 19 health outcomes in 101 studies with 182 health risk estimates were recruited. By meta-analysis, the leave-one-out sensitivity analysis and Egger's test for publication bias, the robust and reliable effects were found for SO2 (per 10 µg/m3 ) with chronic obstructive pulmonary diseases (COPD) (pooled relative risks [RRs] 1.016, 95% CI: 1.012-1.021) and cardiovascular diseases (CVD) (RR 1.012, 95%CI: 007-1.018), respectively. NO2 (per 10 µg/m3 ) had the pooled RRs for childhood asthma, preterm birth, lung cancer, diabetes, and COPD by 1.134 (1.084-1.186), 1.079 (1.007-1.157), 1.055 (1.010-1.101), 1.019 (1.009-1.029), and 1.016 (1.012-1.120), respectively. CO (per 1 mg/m3 ) was significantly associated with Parkinson's disease (RR 1.574, 95% CI: 1.069-2.317) and CVD (RR 1.024, 95% CI: 1.011-1.038). No robust effects were observed for O3 . This study provided evidence and basis for further estimation of the health burden attributable to the four gaseous pollutants.

Tetrabromobisphenol A Disturbs Brain Development in Both Thyroid Hormone-Dependent and -Independent Manners in Xenopus laevis.

Although tetrabromobisphenol A (TBBPA) has been well proven to disturb TH signaling in both in vitro and in vivo assays, it is still unclear whether TBBPA can affect brain development due to TH signaling disruption. Here, we employed the T3-induced Xenopus metamorphosis assay (TIXMA) and the spontaneous metamorphosis assay to address this issue. In the TIXMA, 5-500 nmol/L TBBPA affected T3-induced TH-response gene expression and T3-induced brain development (brain morphological changes, cell proliferation, and neurodifferentiation) at premetamorphic stages in a complicated biphasic concentration-response manner. Notably, 500 nmol/L TBBPA treatment alone exerted a stimulatory effect on tadpole growth and brain development at these stages, in parallel with a lack of TH signaling activation, suggesting the involvement of other signaling pathways. As expected, at the metamorphic climax, we observed inhibitory effects of 50-500 nmol/L TBBPA on metamorphic development and brain development, which was in agreement with the antagonistic effects of higher concentrations on T3-induced brain development at premetamorphic stages. Taken together, all results demonstrate that TBBPA can disturb TH signaling and subsequently interfere with TH-dependent brain development in Xenopus; meanwhile, other signaling pathways besides TH signaling could be involved in this process. Our study improves the understanding of the effects of TBBPA on vertebrate brain development.

Evaluation of the Effect of Contezolid (MRX-I) on the Corrected QT Interval in a Randomized, Double-Blind, Placebo- and Positive-Controlled Crossover Study in Healthy Chinese Volunteers.

Contezolid (MRX-I), a new oxazolidinone, is an antibiotic in development for treating complicated skin and soft tissue infections caused by resistant Gram-positive bacteria. This was a thorough QT study conducted in 52 healthy subjects who were administered oral contezolid at a therapeutic (800 mg) dose, a supratherapeutic (1,600 mg) dose, placebo, and oral moxifloxacin at 400 mg in four separate treatment periods. The pharmacokinetic profile of contezolid was also evaluated. Time point analysis indicated that the upper bounds of the two-sided 90% confidence interval (CI) for placebo-corrected change-from-baseline QTc (ΔΔQTc) were <10 ms for the contezolid therapeutic dose at each time point. The upper bound of the 90% CI for ΔΔQTc was slightly more than 10 ms with the contezolid supratherapeutic dose at 3 and 4 h postdose, and the prolongation effect on the QT/QTc interval was less than that of the positive control, moxifloxacin, at 400 mg. At 3 and 4 h after the moxifloxacin dose, the moxifloxacin group met the assay sensitivity criteria outlined in ICH Guidance E14 by having a lower confidence bound of ≥5 ms. The results of a linear exposure-response model which were similar to that of a time point analysis demonstrated a slightly positive relationship between contezolid plasma levels and ΔQTcF interval with a slope of 0.227 ms per mg/liter (90% CI, 0.188 to 0.266). In summary, contezolid did not prolong the QT interval at a therapeutic dose and may have a slight effect on QT interval prolongation at a supratherapeutic dose.

Handling deviating control values in concentration-response curves.

In cell biology, pharmacology and toxicology dose-response and concentration-response curves are frequently fitted to data with statistical methods. Such fits are used to derive quantitative measures (e.g. EC[Formula: see text] values) describing the relationship between the concentration of a compound or the strength of an intervention applied to cells and its effect on viability or function of these cells. Often, a reference, called negative control (or solvent control), is used to normalize the data. The negative control data sometimes deviate from the values measured for low (ineffective) test compound concentrations. In such cases, normalization of the data with respect to control values leads to biased estimates of the parameters of the concentration-response curve. Low quality estimates of effective concentrations can be the consequence. In a literature study, we found that this problem occurs in a large percentage of toxicological publications. We propose different strategies to tackle the problem, including complete omission of the controls. Data from a controlled simulation study indicate the best-suited problem solution for different data structure scenarios. This was further exemplified by a real concentration-response study. We provide the following recommendations how to handle deviating controls: (1) The log-logistic 4pLL model is a good default option. (2) When there are at least two concentrations in the no-effect range, low variances of the replicate measurements, and deviating controls, control values should be omitted before fitting the model. (3) When data are missing in the no-effect range, the Brain-Cousens model sometimes leads to better results than the default model.

Using Uncertainty Analysis to Improve Consistency in Regulatory Assessments of Criteria Pollutant Standards.

Regulatory impact analyses (RIAs), required for new major federal regulations, are often criticized for not incorporating epistemic uncertainties into their quantitative estimates of benefits and costs. "Integrated uncertainty analysis," which relies on subjective judgments about epistemic uncertainty to quantitatively combine epistemic and statistical uncertainties, is often prescribed. This article identifies an additional source for subjective judgment regarding a key epistemic uncertainty in RIAs for National Ambient Air Quality Standards (NAAQS)-the regulator's degree of confidence in continuation of the relationship between pollutant concentration and health effects at varying concentration levels. An illustrative example is provided based on the 2013 decision on the NAAQS for fine particulate matter (PM2.5 ). It shows how the regulator's justification for setting that NAAQS was structured around the regulator's subjective confidence in the continuation of health risks at different concentration levels, and it illustrates how such expressions of uncertainty might be directly incorporated into the risk reduction calculations used in the rule's RIA. The resulting confidence-weighted quantitative risk estimates are found to be substantially different from those in the RIA for that rule. This approach for accounting for an important source of subjective uncertainty also offers the advantage of establishing consistency between the scientific assumptions underlying RIA risk and benefit estimates and the science-based judgments developed when deciding on the relevant standards for important air pollutants such as PM2.5 .