Designs for the simultaneous inference of concentration-response curves.

BACKGROUND: An important problem in toxicology in the context of gene expression data is the simultaneous inference of a large number of concentration-response relationships. The quality of the inference substantially depends on the choice of design of the experiments, in particular, on the set of different concentrations, at which observations are taken for the different genes under consideration. As this set has to be the same for all genes, the efficient planning of such experiments is very challenging. We address this problem by determining efficient designs for the simultaneous inference of a large number of concentration-response models. For that purpose, we both construct a D-optimality criterion for simultaneous inference and a K-means procedure which clusters the support points of the locally D-optimal designs of the individual models. RESULTS: We show that a planning of experiments that addresses the simultaneous inference of a large number of concentration-response relationships yields a substantially more accurate statistical analysis. In particular, we compare the performance of the constructed designs to the ones of other commonly used designs in terms of D-efficiencies and in terms of the quality of the resulting model fits using a real data example dealing with valproic acid. For the quality comparison we perform an extensive simulation study. CONCLUSIONS: The design maximizing the D-optimality criterion for simultaneous inference improves the inference of the different concentration-response relationships substantially. The design based on the K-means procedure also performs well, whereas a log-equidistant design, which was also included in the analysis, performs poorly in terms of the quality of the simultaneous inference. Based on our findings, the D-optimal design for simultaneous inference should be used for upcoming analyses dealing with high-dimensional gene expression data.

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.

No inflammatory effects after acute inhalation of barium sulfate particles in human volunteers.

BACKGROUND: Most threshold limit values are based on animal experiments. Often, the question remains whether these data reflect the situation in humans. As part of a series of investigations in our exposure lab, this study investigates whether the results on the inflammatory effects of particles that have been demonstrated in animal models can be confirmed in acute inhalation studies in humans. Such studies have not been conducted so far for barium sulfate particles (BaSO4), a substance with very low solubility and without known substance-specific toxicity. Previous inhalation studies with zinc oxide (ZnO), which has a substance-specific toxicity, have shown local and systemic inflammatory respones. The design of these human ZnO inhalation studies was adopted for BaSO4 to compare the effects of particles with known inflammatory activity and supposedly inert particles. For further comparison, in vitro investigations on inflammatory processes were carried out. METHODS: Sixteen healthy volunteers were exposed to filtered air and BaSO4 particles (4.0 mg/m3) for two hours including one hour of ergometric cycling at moderate workload. Effect parameters were clinical signs, body temperature, and inflammatory markers in blood and induced sputum. In addition, particle-induced in vitro-chemotaxis of BaSO4 was investigated with regard to mode of action and differences between in vivo and in vitro effects. RESULTS: No local or systemic clinical signs were observed after acute BaSO4 inhalation and, in contrast to our previous human exposure studies with ZnO, no elevated values of biomarkers of inflammation were measured after the challenge. The in vitro chemotaxis induced by BaSO4 particles was minimal and 15-fold lower compared to ZnO. CONCLUSION: The results of this study indicate that BaSO4 as a representative of granular biopersistent particles without specific toxicity does not induce inflammatory effects in humans after acute inhalation. Moreover, the in vitro data fit in with these in vivo results. Despite the careful and complex investigations, limitations must be admitted because the number of local effect parameters were limited and chronic toxicity could not be studied.

Health effects after inhalation of micro- and nano-sized zinc oxide particles in human volunteers.

Inhalation of ZnO particles can cause inflammation of the airways and metal fume fever. It is unclear if different sizes of the particles alter these effects. However, various studies report higher biological activity of other nano-sized particles compared to microparticles. No effects at all were observed after inhalation of micro- and nano-sized zinc oxide (ZnO) particle concentrations of 0.5 mg/m3. Studies with different particle sizes of ZnO at higher exposures are not available. Accordingly, we hypothesized that inhalation of nano-sized ZnO particles induces stronger health effects than the inhalation of the same airborne mass concentration of micro-sized ZnO particles. 16 healthy volunteers (eight men, eight women) were exposed to filtered air and ZnO particles (2.0 mg/m3) for 2 h (one session with nano- and one with micro-sized ZnO) including 1 h of cycling at moderate workload. Effect parameters were symptoms, body temperature, inflammatory markers in blood and in induced sputum. Induced sputum was obtained at baseline examination, 22 h after exposure and at the end of the final test. The effects were assessed before, immediately after, about 22 h after, as well as two and three days after each exposure. Neutrophils, monocytes and acute-phase proteins in blood increased 22 h after micro- and nano-sized ZnO exposure. Effects were generally stronger with micro-sized ZnO particles. Parameters in induced sputum showed partial increases on the next day, but the effect strengths were not clearly attributable to particle sizes. The hypothesis that nano-sized ZnO particles induce stronger health effects than micro-sized ZnO particles was not supported by our data. The stronger systemic inflammatory responses after inhalation of micro-sized ZnO particles can be explained by the higher deposition efficiency of micro-sized ZnO particles in the respiratory tract and a substance-specific mode of action, most likely caused by the formation of zinc ions.