Potential for Machine Learning to Address Data Gaps in Human Toxicity and Ecotoxicity Characterization

Machine Learning (ML) is increasingly applied to fill data gaps in assessments to quantify impacts associated with chemical emissions and chemicals in products. However, the systematic application of ML-based approaches to fill chemical data gaps is still limited, and their potential for addressing a wide range of chemicals is unknown. We prioritized chemical-related parameters for chemical toxicity characterization to inform ML model development based on two criteria: (1) each parameter's relevance to robustly characterize chemical toxicity described by the uncertainty in characterization results attributable to each parameter and (2) the potential for ML-based approaches to predict parameter values for a wide range of chemicals described by the availability of chemicals with measured parameter data. We prioritized 13 out of 38 parameters for developing ML-based approaches, while flagging another nine with critical data gaps. For all prioritized parameters, we performed a chemical space analysis to assess further the potential for ML-based approaches to predict data for diverse chemicals considering the structural diversity of available measured data, showing that ML-based approaches can potentially predict 8-46% of marketed chemicals based on 1-10% with available measured data. Our results can systematically inform future ML model development efforts to address data gaps in chemical toxicity characterization.

An (Eco)Toxicity Life Cycle Impact Assessment Framework for Per- And Polyfluoroalkyl Substances

A framework for characterizing per- and polyfluoroalkyl substances (PFASs) in life cycle impact assessment (LCIA) is proposed. Thousands of PFASs are used worldwide, with special properties imparted by the fluorinated alkyl chain. Our framework makes it possible to characterize a large part of the family of PFASs by introducing transformation fractions that translate emissions of primary emitted PFASs into the highly persistent terminal degradation products: the perfluoroalkyl acids (PFAAs). Using a PFAA-adapted characterization model, human toxicity as well as marine and freshwater aquatic ecotoxicity characterization factors are calculated for three PFAAs, namely perfluorooctanoic acid (PFOA) perfluorohexanoic acid (PFHxA) and perfluorobutanesulfonic acid (PFBS). The model is evaluated to adequately capture long-term fate, where PFAAs are predicted to accumulate in open oceans. The characterization factors of the three PFAAs are ranked among the top 5% for marine ecotoxicity, when compared to 3104 chemicals in the existing USEtox results databases. Uncertainty analysis indicates potential for equally high ranks for human health impacts. Data availability constitutes an important limitation creating uncertainties. Even so, a life cycle assessment (LCA) case study illustrates practical application of our proposed framework, demonstrating that even low emissions of PFASs can have large effects on LCA results.

Toward harmonizing ecotoxicity characterization in life cycle impact assessment

Ecosystem quality is an important area of protection in life cycle impact assessment (LCIA). Chemical pollution has adverse impacts on ecosystems on a global scale. To improve methods for assessing ecosystem impacts, the Life Cycle Initiative hosted by the United Nations Environment Programme established a task force to evaluate the state-of-the-science in modeling chemical exposure of organisms and the resulting ecotoxicological effects for use in LCIA. The outcome of the task force work will be global guidance and harmonization by recommending changes to the existing practice of exposure and effect modeling in ecotoxicity characterization. These changes will reflect the current science and ensure the stability of recommended practice. Recommendations must work within the needs of LCIA in terms of 1) operating on information from any inventory reporting chemical emissions with limited spatiotemporal information, 2) applying best estimates rather than conservative assumptions to ensure unbiased comparison with results for other impact categories, and 3) yielding results that are additive across substances and life cycle stages and that will allow a quantitative expression of damage to the exposed ecosystem. We describe the current framework and discuss research questions identified in a roadmap. Primary research questions relate to the approach toward ecotoxicological effect assessment, the need to clarify the method's scope and interpretation of its results, the need to consider additional environmental compartments and impact pathways, and the relevance of effect metrics other than the currently applied geometric mean of toxicity effect data across species. Because they often dominate ecotoxicity results in LCIA, we give metals a special focus, including consideration of their possible essentiality and changes in environmental bioavailability. We conclude with a summary of key questions along with preliminary recommendations to address them as well as open questions that require additional research efforts. Environ Toxicol Chem 2018;37:2955-2971. © 2018 SETAC.

Properties, performance and associated hazards of state-of-the-art durable water repellent (DWR) chemistry for textile finishing

Following the phase-out of long-chain per- and polyfluoroalkyl substances (PFASs), the textile industry had to find alternatives for side-chain fluorinated polymer based durable water repellent (DWR) chemistries that incorporated long perfluoroalkyl side chains. This phase-out and subsequent substitution with alternatives has resulted in a market where both fluorinated and non-fluorinated DWRs are available. These DWR alternatives can be divided into four broad groups that reflect their basic chemistry: side-chain fluorinated polymers, silicones, hydrocarbons and other chemistries (includes dendrimer and inorganic nanoparticle chemistries). In this critical review, the alternative DWRs are assessed with regards to their structural properties and connected performance, loss and degradation processes resulting in diffuse environmental emissions, and hazard profiles for selected emitted substances. Our review shows that there are large differences in performance between the alternative DWRs, most importantly the lack of oil repellence of non-fluorinated alternatives. It also shows that for all alternatives, impurities and/or degradation products of the DWR chemistries are diffusively emitted to the environment. Our hazard ranking suggests that hydrocarbon based DWR is the most environmentally benign, followed by silicone and side-chain fluorinated polymer-based DWR chemistries. Industrial commitments to reduce the levels of impurities in silicone based and side-chain fluorinated polymer based DWR formulations will lower the actual risks. There is a lack of information on the hazards associated with DWRs, in particular for the dendrimer and inorganic nanoparticle chemistries, and these data gaps must be filled. Until environmentally safe alternatives, which provide the required performance, are available our recommendation is to choose DWR chemistry on a case-by-case basis, always weighing the benefits connected to increased performance against the risks to the environment and human health.

Review of Environmental Assessment Case Studies Blending Elements of Risk Assessment and Life Cycle Assessment

Risk assessment (RA) and life cycle assessment (LCA) are two analytical tools used to support decision making in environmental management. This study reviewed 30 environmental assessment case studies that claimed an integration, combination, hybridization, or complementary use of RA and LCA. The focus of the analysis was on how the respective case studies evaluated emissions of chemical pollutants and pathogens. The analysis revealed three clusters of similar case studies. Yet, there seemed to be little consensus as to what should be referred to as RA and LCA, and when to speak of combination, integration, hybridization, or complementary use of RA and LCA. This paper provides clear recommendations toward a more stringent and consistent use of terminology. Blending elements of RA and LCA offers multifaceted opportunities to adapt a given environmental assessment case study to a specific decision making context, but also requires awareness of several implications and potential pitfalls, of which six are discussed in this paper. To facilitate a better understanding and more transparent communication of the nature of a given case study, this paper proposes a "design space" (i.e., identification framework) for environmental assessment case studies blending elements of RA and LCA. Thinking in terms of a common design space, we postulate, can increase clarity and transparency when communicating the design and results of a given assessment together with its potential strengths and weaknesses.

Radiographic prediction of failure after fixation of cervical hip fracture

During 1984-1985, 410 patients with cervical hip fracture were randomized between 2 methods of internal fixation--a single nail (Rydell) or 2 LIH hook pins (LIH). The patients were followed-up prospectively for at least 2 years. Radiographs were taken after 1 week, 1, 3, 6, 12, and 24 months. The radiographs of the 295 patients alive 2 years postoperatively were examined by one of the authors. The sliding and the diversion of the pins and the nail in the anteroposterior projection and the diversion in the lateral projection were measured. In the failure group (non-union, late segmental collapse), the greatest sliding was noted within 1 month postoperatively and the diversion increased up to 3 months. Significant differences between the failure and the non-failure groups could be seen even after 1 week. We also found that the degree of sliding of the LIH pins and the Rydell nail 1 month postoperatively is comparable to the scintigraphic pattern 2 weeks postoperatively in predicting failure after internal fixation of cervical hip fractures.