Research Priorities for the Environmental Risk Assessment of Per- and Polyfluorinated Substances.

Per- and polyfluorinated substances (PFAS) are a group of thousands of ubiquitously applied persistent industrial chemicals. The field of PFAS environmental research is developing rapidly, but suffers from substantial biases toward specific compounds, environmental compartments, and organisms. The aim of our study was therefore to highlight current developments and to identify knowledge gaps and subsequent research needs that would contribute to a comprehensive environmental risk assessment for PFAS. To this end, we consulted the open literature and databases and found that knowledge of the environmental fate of PFAS is based on the analysis of <1% of the compounds categorized as PFAS. Moreover, soils and suspended particulate matter remain largely understudied. The bioavailability, bioaccumulation, and food web transfer studies of PFAS also focus on a very limited number of compounds and are biased toward aquatic biota, predominantly fish, and less frequently aquatic invertebrates and macrophytes. The available ecotoxicity data revealed that only a few PFAS have been well studied for their environmental hazards, and that PFAS ecotoxicity data are also strongly biased toward aquatic organisms. Ecotoxicity studies in the terrestrial environment are needed, as well as chronic, multigenerational, and community ecotoxicity research, in light of the persistency and bioaccumulation of PFAS. Finally, we identified an urgent need to unravel the relationships among sorption, bioaccumulation, and ecotoxicity on the one hand and molecular descriptors of PFAS chemical structures and physicochemical properties on the other, to allow predictions of exposure, bioaccumulation, and toxicity. Environ Toxicol Chem 2023;42:2302-2316. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Guided internet-based cognitive-behavioral therapy for patients with chronic pain: A meta-analytic review.

Background: Chronic pain has a large individual and societal burden. Previous reviews have shown that internet-based cognitive-behavioral therapy (iCBT) can support patients' pain coping. However, factors related to participant experience of iCBT and effective and safe iCBT delivery for chronic pain have not recently been summarized. Objective: The aim of this review was to give an overview of the efficacy of guided iCBT for chronic pain on psychological, physical, and impact on daily life outcomes, including factors that inform optimal delivery. Methods: Cochrane, Emcare, Web of Science, PubMed, PsycINFO, and Embase were systematically searched from inception to 11 February 2022. Randomized controlled trials on guided iCBTs for adults with chronic pain were included with a broad range of outcomes. Results: The search yielded 7406 studies of which 33 studies were included totaling 5133 participants. ICBT was more effective than passive control conditions for psychological (ES = 0.34-0.47), physical (ES = 0.26-0.29), and impact outcomes (ES = 0.38-0.41). ICBT was more effective than active control conditions for distress (ES = 0.40), pain acceptance (ES = 0.15), and pain interference after outlier removal (ES = 0.30). Longer treatments were associated with larger effects for anxiety and quality of life than shorter treatments. Mode of therapist contact (synchronous, asynchronous or a mix of both) was not related to differences in effect sizes in most outcomes. However, studies with mixed and synchronous contact modes had higher effects on pain self-efficacy than studies with asynchronous contact modes. Treatment satisfaction was high and adverse events were minor. Dropout was related to time, health, technical issues, and lack of computer skills. Conclusions: Guided iCBT is an effective and potentially safe treatment for chronic pain. Future research should more consistently report on iCBT safety and detail the effectiveness of individual treatment components to optimize iCBT in clinical practice.

A Survey of Deep Learning-Based Image Restoration Methods for Enhancing Situational Awareness at Disaster Sites: The Cases of Rain, Snow and Haze.

This survey article is concerned with the emergence of vision augmentation AI tools for enhancing the situational awareness of first responders (FRs) in rescue operations. More specifically, the article surveys three families of image restoration methods serving the purpose of vision augmentation under adverse weather conditions. These image restoration methods are: (a) deraining; (b) desnowing; (c) dehazing ones. The contribution of this article is a survey of the recent literature on these three problem families, focusing on the utilization of deep learning (DL) models and meeting the requirements of their application in rescue operations. A faceted taxonomy is introduced in past and recent literature including various DL architectures, loss functions and datasets. Although there are multiple surveys on recovering images degraded by natural phenomena, the literature lacks a comprehensive survey focused explicitly on assisting FRs. This paper aims to fill this gap by presenting existing methods in the literature, assessing their suitability for FR applications, and providing insights for future research directions.