Yield of TB screening in prisons in Tajikistan.

BACKGROUND: The rate of TB in prison institutions is estimated to be 23 times higher than in the general population. Limited documentation exists regarding TB screening in Tajikistan's prisons. This study aims to report findings from a TB screening conducted in prison facilities in Tajikistan. METHODS: A systematic TB screening was conducted between July 2022 and September 2023, following a locally adapted algorithm based on WHO recommendations. The screening yield was calculated as the proportion of confirmed TB cases, with categorical variables compared using a χ2 test. RESULTS: A total of 7,223 screenings were conducted, identifying 31 TB cases, including 17 drug-susceptible TB cases, eight drug-resistant TB cases, and six clinically diagnosed cases. The overall screening yield was 0.43%. Notably, the screening yield was 3.4% among individuals with at least one TB symptom and 0.03% among those without TB symptoms (P < 0.001). CONCLUSION: The identified rate of TB in these prisons is five times higher than in the general population. Symptomatic individuals had a higher likelihood of TB diagnosis, and using chest X-rays significantly improved screening yield. We recommend increasing the capacity for chest X-ray testing to enhance TB prevention and control within prison settings.

CONTEXTE: On estime que le taux de TB dans les établissements pénitentiaires est 23 fois plus élevé que dans la population générale. Il existe peu de documentation sur le dépistage de la TB dans les prisons du Tadjikistan. Cette étude vise à rendre compte des résultats d'un dépistage de la TB mené dans des établissements pénitentiaires au Tadjikistan. MÉTHODES: Un dépistage systématique de la TB a été réalisé entre juillet 2022 et septembre 2023, selon un algorithme adapté localement et basé sur les recommandations de l'OMS. Le rendement du dépistage a été calculé comme la proportion de cas confirmés de TB, avec des variables catégorielles comparées à l'aide d'un test χ2. RÉSULTATS: Au total, 7 223 dépistages ont été effectués, permettant d'identifier 31 cas de TB, dont 17 cas de TB sensible aux médicaments, 8 cas de TB résistante aux médicaments et 6 cas diagnostiqués cliniquement. Le rendement global du criblage était de 0,43%. Notamment, le rendement du dépistage était de 3,4% chez les personnes présentant au moins un symptôme de la TB et de 0,03% chez celles ne présentant pas de symptômes de la TB (P < 0,001). CONCLUSION: Le taux de TB identifié dans ces prisons est cinq fois plus élevé que dans la population générale. Les personnes symptomatiques avaient une probabilité plus élevée d'être diagnostiquées comme atteintes de TB, et l'utilisation de radiographies pulmonaires améliorait considérablement le rendement du dépistage. Nous recommandons d'augmenter la capacité de dépistage par radiographie thoracique afin d'améliorer la prévention et le contrôle de la TB en milieu carcéral.

A 10-year review of isoniazid-resistant TB management in Uzbekistan 2009-2020.

BACKGROUND: Isoniazid (INH, H) resistance is the most common drug-resistant TB pattern, with treatment success rates lower than those in drug-susceptible TB. The WHO recommends a 6-month regimen of rifampicin (RIF, R), ethambutol (EMB, E), pyrazinamide (PZA, Z), and levofloxacin (Lfx) (6REZLfx) for INH-resistant, RIF-susceptible TB (HRRS-TB). Uzbekistan has a high burden of TB (62/100,000 population) and multidrug-resistant TB (12/100,000 population). METHODS: We conducted a retrospective, descriptive study of microbiologically confirmed HRRS-TB using routinely collected programmatic data from 2009 to 2020. RESULTS: We included 854 HRRS-TB cases. Treatment success was 80.2% overall. For REZLfx, the treatment success rate was 92.0% over a short treatment duration, with no amplifications to RIF or second-line anti-TB drug resistance. We documented 46 regimens with REZLfx plus linezolid (success 87.0%) and 539 regimens using kanamycin or capreomycin (success 76.6%). We identified 37 treatment failures (4.3%), 30 deaths (3.5%), 25 resistance amplifications (2.9%), including eight to RIF (0.9%), and 99 lost to follow-up (LTFU) cases (11.6%). Unsuccessful outcomes were more common with older age, diabetes, chest X-ray cavities, smear positivity, smear-positive persistence, and male sex. LTFU was more common with injection-containing regimens. CONCLUSIONS: REZLfx is a safe and effective first-line treatment for INH-resistant, RIF-susceptible TB. Treatment success was lower and LTFU was higher for injection-containing regimens.

CONTEXTE: La résistance à l'isoniazide (INH, H) est la forme de TB pharmacorésistante la plus courante, avec des taux de réussite thérapeutique inférieurs à ceux de la TB pharmacosensible. L'OMS recommande un traitement de six mois à base de rifampicine (RIF, R), d'éthambutol (EMB, E), de pyrazinamide (PZA, Z) et de lévofloxacine (LFx) (6REZLfx) pour la TB résistante à l'INH et sensible au RIF (HRRS-TB). En Ouzbékistan, la prévalence de la TB est élevée, avec un taux de 62 cas pour 100 000 habitants, ainsi que de la TB multirésistante, avec un taux de 12 cas pour 100 000 habitants. MÉTHODES: Une étude rétrospective et descriptive de la HRRS-TB confirmée microbiologiquement a été réalisée en utilisant des données programmatiques collectées de manière routinière de 2009 à 2020. RÉSULTATS: Nous avons inclus 854 cas de HRRS-TB. Le taux de réussite du traitement global était de 80,2%. Pour le traitement avec REZLfx, le taux de réussite était de 92,0% sur une courte durée, sans résistance au RIF ni aux médicaments antituberculeux de deuxième ligne. Nous avons observé 46 schémas thérapeutiques associant REZLfx et linézolide avec un taux de réussite de 87,0%, ainsi que 539 schémas thérapeutiques utilisant la kanamycine ou la capréomycine avec un taux de réussite de 76,6 %. Nous avons enregistré 37 échecs thérapeutiques (4,3%), 30 décès (3,5%), 25 cas de résistance amplifiée (2,9%), dont huit au RIF (0,9%), et 99 cas de perte de suivi (LTFU, pour l'anglais « loss to follow-up ¼) (11,6%). Les échecs étaient plus fréquents chez les patients âgés, diabétiques, présentant des cavités à la radiographie thoracique, un frottis positif persistant et de sexe masculin. La prolongation de la durée d'utilisation était plus fréquente avec les schémas contenant des injections. CONCLUSIONS: REZLfx est un traitement de première intention sûr et efficace contre la TB résistante à l'INH et sensible aux RIF. Le succès du traitement était plus faible et le nombre de LTFU était plus élevé pour les schémas contenant des injections.

Enhanced identification of endocrine disruptors through integration of science-based regulatory practices and innovative methodologies: The MERLON Project.

The prevalence of hormone-related health issues caused by exposure to endocrine disrupting chemicals (EDCs) is a significant, and increasing, societal challenge. Declining fertility rates together with rising incidence rates of reproductive disorders and other endocrine-related diseases underscores the urgency in taking more action. Addressing the growing threat of EDCs in our environment demands robust and reliable test methods to assess a broad variety of endpoints relevant for endocrine disruption. EDCs also require effective regulatory frameworks, especially as the current move towards greater reliance on non-animal methods in chemical testing puts to test the current paradigm for EDC identification, which requires that an adverse effect is observed in an intact organism. Although great advances have been made in the field of predictive toxicology, disruption to the endocrine system and subsequent adverse health effects may prove particularly difficult to predict without traditional animal models. The MERLON project seeks to expedite progress by integrating multispecies molecular research, new approach methodologies (NAMs), human clinical epidemiology, and systems biology to furnish mechanistic insights and explore ways forward for NAM-based identification of EDCs. The focus is on sexual development and function, from foetal sex differentiation of the reproductive system through mini-puberty and puberty to sexual maturity. The project aims are geared towards closing existing knowledge gaps in understanding the effects of EDCs on human health to ultimately support effective regulation of EDCs in the European Union and beyond.

Utility of PSMA PET/CT in Staging and Restaging of Renal Cell Carcinoma: A Systematic Review and Metaanalysis.

Prostate-specific membrane antigen (PSMA) is expressed in the neovasculature of multiple solid tumors, including renal cell carcinoma (RCC). Studies have demonstrated promising results on the utility of PSMA-targeted PET/CT imaging in RCC. This report aims to provide a systematic review and metaanalysis on the utility and detection rate of PSMA PET/CT imaging in staging or evaluation of primary RCC and restaging of metastatic or recurrent RCC. Methods: Searches were performed in PubMed, Embase, and abstract proceedings (last updated, August 2023). Studies that provided a lesion-level detection rate of PSMA radiotracers in staging or restaging of RCC were included in the metaanalysis. The overall pooled detection rate with a 95% CI was estimated, and subgroup analysis was performed when feasible. Results: Nine studies comprising 152 patients (133 clear cell RCC [ccRCC], 19 other RCC subtypes) were included in the metaanalysis. The pooled detection rate of PSMA PET/CT in evaluation of primary or metastatic RCC was estimated to be 0.83 (95% CI, 0.67-0.92). Subgroup analysis showed a pooled PSMA detection rate of 0.74 (95% CI, 0.57-0.86) in staging or evaluation of primary RCC lesions and 0.87 (95% CI, 0.73-0.95) in restaging of metastatic or recurrent RCC. Analysis based on the type of radiotracer showed a pooled detection rate of 0.85 (95% CI, 0.62-0.95) for 68Ga-based PSMA tracers and 0.92 (95% CI, 0.76-0.97) for 18F-DCFPyL PET/CT. Furthermore, in metastatic ccRCC, the available data support a significantly higher detection rate for 18F-DCFPyL PET/CT than for conventional imaging modalities (2 studies). Conclusion: Our preliminary results show that PSMA PET/CT could be a promising alternative imaging modality for evaluating RCC, particularly metastatic ccRCC. Large prospective studies are warranted to confirm clinical utility in the staging and restaging of RCC.

Development of a probabilistic risk model for pharmaceuticals in the environment under population and wastewater treatment scenarios.

Preparing for future environmental pressures requires projections of how relevant risks will change over time. Current regulatory models of environmental risk assessment (ERA) of pollutants such as pharmaceuticals could be improved by considering the influence of global change factors (e.g., population growth) and by presenting uncertainty more transparently. In this article, we present the development of a prototype object-oriented Bayesian network (BN) for the prediction of environmental risk for six high-priority pharmaceuticals across 36 scenarios: current and three future population scenarios, combined with infrastructure scenarios, in three Norwegian counties. We compare the risk, characterized by probability distributions of risk quotients (RQs), across scenarios and pharmaceuticals. Our results suggest that RQs would be greatest in rural counties, due to the lower development of current wastewater treatment facilities, but that these areas consequently have the most potential for risk mitigation. This pattern intensifies under higher population growth scenarios. With this prototype, we developed a hierarchical probabilistic model and demonstrated its potential in forecasting the environmental risk of chemical stressors under plausible demographic and management scenarios, contributing to the further development of BNs for ERA. Integr Environ Assess Manag 2024;20:1715-1735. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Quantitative brain 18F-FDG PET/CT analysis in seronegative autoimmune encephalitis.

OBJECTIVE: Brain 18F-FDG PET/CT is a useful diagnostic in evaluating patients with suspected autoimmune encephalitis (AE). Specific patterns of brain dysmetabolism have been reported in anti-NMDAR and anti-LGI1 AE, and the degree of dysmetabolism may correlate with clinical functional status.18FDG-PET/CT abnormalities have not yet been described in seronegative AE. METHODS: We conducted a cross-sectional analysis of brain18FDG-PET/CT data in people with seronegative AE treated at the Johns Hopkins Hospital. Utilizing NeuroQ™ software, the Z-scores of 47 brain regions were calculated relative to healthy controls, then visually and statistically compared for probable and possible AE per clinical consensus diagnostic criteria to previous data from anti-NMDAR and anti-LGI1 cohorts. RESULTS: Eight probable seronegative AE and nine possible seronegative AE were identified. The group only differed in frequency of abnormal brain MRI, which was seen in all of the probable seronegative AE patients. Both seronegative groups had similar overall patterns of brain dysmetabolism. A common pattern of frontal lobe hypometabolism and medial temporal lobe hypermetabolism was observed in patients with probable and possible seronegative AE, as well as anti-NMDAR and anti-LGI1 AE as part of their respective characteristic patterns of dysmetabolism. Four patients had multiple brain18FDG-PET/CT scans, with changes in number and severity of abnormal brain regions mirroring clinical status. CONCLUSIONS: A18FDG-PET/CT pattern of frontal lobe hypometabolism and medial temporal lobe hypermetabolism could represent a common potential biomarker of AE, which along with additional clinical data may facilitate earlier diagnosis and treatment.

Deep Semisupervised Transfer Learning for Fully Automated Whole-Body Tumor Quantification and Prognosis of Cancer on PET/CT.

Automatic detection and characterization of cancer are important clinical needs to optimize early treatment. We developed a deep, semisupervised transfer learning approach for fully automated, whole-body tumor segmentation and prognosis on PET/CT. Methods: This retrospective study consisted of 611 18F-FDG PET/CT scans of patients with lung cancer, melanoma, lymphoma, head and neck cancer, and breast cancer and 408 prostate-specific membrane antigen (PSMA) PET/CT scans of patients with prostate cancer. The approach had a nnU-net backbone and learned the segmentation task on 18F-FDG and PSMA PET/CT images using limited annotations and radiomics analysis. True-positive rate and Dice similarity coefficient were assessed to evaluate segmentation performance. Prognostic models were developed using imaging measures extracted from predicted segmentations to perform risk stratification of prostate cancer based on follow-up prostate-specific antigen levels, survival estimation of head and neck cancer by the Kaplan-Meier method and Cox regression analysis, and pathologic complete response prediction of breast cancer after neoadjuvant chemotherapy. Overall accuracy and area under the receiver-operating-characteristic (AUC) curve were assessed. Results: Our approach yielded median true-positive rates of 0.75, 0.85, 0.87, and 0.75 and median Dice similarity coefficients of 0.81, 0.76, 0.83, and 0.73 for patients with lung cancer, melanoma, lymphoma, and prostate cancer, respectively, on the tumor segmentation task. The risk model for prostate cancer yielded an overall accuracy of 0.83 and an AUC of 0.86. Patients classified as low- to intermediate- and high-risk had mean follow-up prostate-specific antigen levels of 18.61 and 727.46 ng/mL, respectively (P < 0.05). The risk score for head and neck cancer was significantly associated with overall survival by univariable and multivariable Cox regression analyses (P < 0.05). Predictive models for breast cancer predicted pathologic complete response using only pretherapy imaging measures and both pre- and posttherapy measures with accuracies of 0.72 and 0.84 and AUCs of 0.72 and 0.76, respectively. Conclusion: The proposed approach demonstrated accurate tumor segmentation and prognosis in patients across 6 cancer types on 18F-FDG and PSMA PET/CT scans.

Big Question to Developing Solutions: A Decade of Progress in the Development of Aquatic New Approach Methodologies from 2012 to 2022.

In 2012, 20 key questions related to hazard and exposure assessment and environmental and health risks of pharmaceuticals and personal care products in the natural environment were identified. A decade later, this article examines the current level of knowledge around one of the lowest-ranking questions at that time, number 19: "Can nonanimal testing methods be developed that will provide equivalent or better hazard data compared with current in vivo methods?" The inclusion of alternative methods that replace, reduce, or refine animal testing within the regulatory context of risk and hazard assessment of chemicals generally faces many hurdles, although this varies both by organism (human-centric vs. other), sector, and geographical region or country. Focusing on the past 10 years, only works that might reasonably be considered to contribute to advancements in the field of aquatic environmental risk assessment are highlighted. Particular attention is paid to methods of contemporary interest and importance, representing progress in (1) the development of methods which provide equivalent or better data compared with current in vivo methods such as bioaccumulation, (2) weight of evidence, or (3) -omic-based applications. Evolution and convergence of these risk assessment areas offer the basis for fundamental frameshifts in how data are collated and used for the protection of taxa across the breadth of the aquatic environment. Looking to the future, we are at a tipping point, with a need for a global and inclusive approach to establish consensus. Bringing together these methods (both new and old) for regulatory assessment and decision-making will require a concerted effort and orchestration. Environ Toxicol Chem 2024;43:559-574. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Using a Bayesian Network Model to Predict Risk of Pesticides on Aquatic Community Endpoints in a Rice Field-A Southern European Case Study.

Bayesian network (BN) models are increasingly used as tools to support probabilistic environmental risk assessments (ERAs), because they can better account for uncertainty compared with the simpler approaches commonly used in traditional ERA. We used BNs as metamodels to link various sources of information in a probabilistic framework, to predict the risk of pesticides to aquatic communities under given scenarios. The research focused on rice fields surrounding the Albufera Natural Park (Valencia, Spain), and considered three selected pesticides: acetamiprid (an insecticide), 2-methyl-4-chlorophenoxyacetic acid (MCPA; a herbicide), and azoxystrobin (a fungicide). The developed BN linked the inputs and outputs of two pesticide models: a process-based exposure model (Rice Water Quality [RICEWQ]), and a probabilistic effects model (Predicts the Ecological Risk of Pesticides [PERPEST]) using case-based reasoning with data from microcosm and mesocosm experiments. The model characterized risk at three levels in a hierarchy: biological endpoints (e.g., molluscs, zooplankton, insects, etc.), endpoint groups (plants, invertebrates, vertebrates, and community processes), and community. The pesticide risk to a biological endpoint was characterized as the probability of an effect for a given pesticide concentration interval. The risk to an endpoint group was calculated as the joint probability of effect on any of the endpoints in the group. Likewise, community-level risk was calculated as the joint probability of any of the endpoint groups being affected. This approach enabled comparison of risk to endpoint groups across different pesticide types. For example, in a scenario for the year 2050, the predicted risk of the insecticide to the community (40% probability of effect) was dominated by the risk to invertebrates (36% risk). In contrast, herbicide-related risk to the community (63%) resulted from risk to both plants (35%) and invertebrates (38%); the latter might represent (in the present study) indirect effects of toxicity through the food chain. This novel approach combines the quantification of spatial variability of exposure with probabilistic risk prediction for different components of aquatic ecosystems. Environ Toxicol Chem 2024;43:182-196. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Incorporating climate projections in the environmental risk assessment of pesticides in aquatic ecosystems.

Global climate change will significantly impact the biodiversity of freshwater ecosystems, both directly and indirectly via the exacerbation of impacts from other stressors. Pesticides form a prime example of chemical stressors that are expected to synergize with climate change. Aquatic exposures to pesticides might change in magnitude due to increased runoff from agricultural fields, and in composition, as application patterns will change due to changes in pest pressures and crop types. Any prospective chemical risk assessment that aims to capture the influence of climate change should properly and comprehensively account for the variabilities and uncertainties that are inherent to projections of future climate. This is only feasible if they probabilistically propagate extensive ensembles of climate model projections. However, current prospective risk assessments typically make use of process-based models of chemical fate that do not typically allow for such high-throughput applications. Here, we describe a Bayesian network model that does. It incorporates a two-step univariate regression model based on a 30-day antecedent precipitation index, circumventing the need for computationally laborious mechanistic models. We show its feasibility and application potential in a case study with two pesticides in a Norwegian stream: the fungicide trifloxystrobin and herbicide clopyralid. Our analysis showed that variations in pesticide application rates as well as precipitation intensity lead to variations in in-stream exposures. When relating to aquatic risks, the influence of these processes is reduced and distributions of risk are dominated by effect-related parameters. Predicted risks for clopyralid were negligible, but the probability of unacceptable future environmental risks due to exposure to trifloxystrobin (i.e., a risk quotient >1) was 8%-12%. This percentage further increased to 30%-35% when a more conservative precautionary factor of 100 instead of 30 was used. Integr Environ Assess Manag 2024;20:384-400. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Evaluating the effects of climate change and chemical, physical, and biological stressors on nearshore coral reefs: A case study in the Great Barrier Reef, Australia.

An understanding of the combined effects of climate change (CC) and other anthropogenic stressors, such as chemical exposures, is essential for improving ecological risk assessments of vulnerable ecosystems. In the Great Barrier Reef, coral reefs are under increasingly severe duress from increasing ocean temperatures, acidification, and cyclone intensities associated with CC. In addition to these stressors, inshore reef systems, such as the Mackay-Whitsunday coastal zone, are being impacted by other anthropogenic stressors, including chemical, nutrient, and sediment exposures related to more intense rainfall events that increase the catchment runoff of contaminated waters. To illustrate an approach for incorporating CC into ecological risk assessment frameworks, we developed an adverse outcome pathway network to conceptually delineate the effects of climate variables and photosystem II herbicide (diuron) exposures on scleractinian corals. This informed the development of a Bayesian network (BN) to quantitatively compare the effects of historical (1975-2005) and future projected climate on inshore hard coral bleaching, mortality, and cover. This BN demonstrated how risk may be predicted for multiple physical and biological stressors, including temperature, ocean acidification, cyclones, sediments, macroalgae competition, and crown of thorns starfish predation, as well as chemical stressors such as nitrogen and herbicides. Climate scenarios included an ensemble of 16 downscaled models encompassing current and future conditions based on multiple emission scenarios for two 30-year periods. It was found that both climate-related and catchment-related stressors pose a risk to these inshore reef systems, with projected increases in coral bleaching and coral mortality under all future climate scenarios. This modeling exercise can support the identification of risk drivers for the prioritization of management interventions to build future resilient reefs. Integr Environ Assess Manag 2024;20:401-418. © 2023 Norwegian Institute for Water Research and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Lake browning counteracts cyanobacteria responses to nutrients: Evidence from phytoplankton dynamics in large enclosure experiments and comprehensive observational data.

Lakes worldwide are affected by multiple stressors, including climate change. This includes massive loading of both nutrients and humic substances to lakes during extreme weather events, which also may disrupt thermal stratification. Since multi-stressor effects vary widely in space and time, their combined ecological impacts remain difficult to predict. Therefore, we combined two consecutive large enclosure experiments with a comprehensive time-series and a broad-scale field survey to unravel the combined effects of storm-induced lake browning, nutrient enrichment and deep mixing on phytoplankton communities, focusing particularly on potentially toxic cyanobacterial blooms. The experimental results revealed that browning counteracted the stimulating effect of nutrients on phytoplankton and caused a shift from phototrophic cyanobacteria and chlorophytes to mixotrophic cryptophytes. Light limitation by browning was identified as the likely mechanism underlying this response. Deep-mixing increased microcystin concentrations in clear nutrient-enriched enclosures, caused by upwelling of a metalimnetic Planktothrix rubescens population. Monitoring data from a 25-year time-series of a eutrophic lake and from 588 northern European lakes corroborate the experimental results: Browning suppresses cyanobacteria in terms of both biovolume and proportion of the total phytoplankton biovolume. Both the experimental and observational results indicated a lower total phosphorus threshold for cyanobacterial bloom development in clearwater lakes (10-20 µg P L-1 ) than in humic lakes (20-30 µg P L-1 ). This finding provides management guidance for lakes receiving more nutrients and humic substances due to more frequent extreme weather events.

Integrating climate model projections into environmental risk assessment: A probabilistic modeling approach.

The Society of Environmental Toxicology and Chemistry (SETAC) convened a Pellston workshop in 2022 to examine how information on climate change could be better incorporated into the ecological risk assessment (ERA) process for chemicals as well as other environmental stressors. A major impetus for this workshop is that climate change can affect components of ecological risks in multiple direct and indirect ways, including the use patterns and environmental exposure pathways of chemical stressors such as pesticides, the toxicity of chemicals in receiving environments, and the vulnerability of species of concern related to habitat quality and use. This article explores a modeling approach for integrating climate model projections into the assessment of near- and long-term ecological risks, developed in collaboration with climate scientists. State-of-the-art global climate modeling and downscaling techniques may enable climate projections at scales appropriate for the study area. It is, however, also important to realize the limitations of individual global climate models and make use of climate model ensembles represented by statistical properties. Here, we present a probabilistic modeling approach aiming to combine projected climatic variables as well as the associated uncertainties from climate model ensembles in conjunction with ERA pathways. We draw upon three examples of ERA that utilized Bayesian networks for this purpose and that also represent methodological advancements for better prediction of future risks to ecosystems. We envision that the modeling approach developed from this international collaboration will contribute to better assessment and management of risks from chemical stressors in a changing climate. Integr Environ Assess Manag 2024;20:367-383. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Incorporating climate change model projections into ecological risk assessments to help inform risk management and adaptation strategies: Synthesis of a SETAC Pellston Workshop®.

The impacts of global climate change are not yet well integrated with the estimates of the impacts of chemicals on the environment. This is evidenced by the lack of consideration in national or international reports that evaluate the impacts of climate change and chemicals on ecosystems and the relatively few peer-reviewed publications that have focused on this interaction. In response, a 2011 Pellston Workshop® was held on this issue and resulted in seven publications in Environmental Toxicology and Chemistry. Yet, these publications did not move the field toward climate change and chemicals as important factors together in research or policy-making. Here, we summarize the outcomes of a second Pellston Workshop® on this topic held in 2022 that included climate scientists, environmental toxicologists, chemists, and ecological risk assessors from 14 countries and various sectors. Participants were charged with assessing where climate models can be applied to evaluating potential exposure and ecological effects at geographical and temporal scales suitable for ecological risk assessment, and thereby be incorporated into adaptive risk management strategies. We highlight results from the workshop's five publications included in the special series "Incorporating Global Climate Change into Ecological Risk Assessments: Strategies, Methods and Examples." We end this summary with the overall conclusions and recommendations from participants. Integr Environ Assess Manag 2024;20:359-366. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Predicting Environmental Risks of Pharmaceuticals from Wholesale Data: An Example from Norway.

Environmental risk assessment (ERA) of pharmaceuticals relies on available measured environmental concentrations, but often such data are sparse. Predicted environmental concentrations (PECs), calculated from sales weights, are an attractive alternative but often cover only prescription sales. We aimed to rank, by environmental risk in Norway, approximately 200 active pharmaceutical ingredients (APIs) over 2016-2019, based on sales PECs. To assess the added value of wholesale and veterinary data, we compared exposure and risk predictions with and without these additional sources. Finally, we aimed to characterize the persistence, mobility, and bioaccumulation of these APIs. We compared our PECs to available Norwegian measurements, then, using public predicted-no-effect concentrations, we calculated risk quotients (RQs) and appended experimental and predicted persistence and bioaccumulation. Our approach overestimated environmental concentrations compared with measurements for 18 of 20 APIs with comparable predictions and measurements. Seventeen APIs had mean RQs >1, indicating potential risk, while the mean RQ was 2.05 and the median 0.001, driven by sex hormones, antibiotics, the antineoplastic abiraterone, and common painkillers. Some high-risk APIs were also potentially persistent or bioaccumulative (e.g., levonorgestrel [RQ = 220] and ciprofloxacin [RQ = 56]), raising the possibility of impacts beyond their RQs. Exposure and risk were also calculated with and without over-the-counter sales, showing that prescriptions explained 70% of PEC magnitude. Likewise, human sales, compared with veterinary, explained 85%. Sales PECs provide an efficient option for ERA, designed to overestimate compared with analytical techniques and potentially held back by limited data availability and an inability to quantify uncertainty but, nevertheless, an ideal initial approach for identification and ranking of risks. Environ Toxicol Chem 2023;42:2253-2270. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Primary bedaquiline resistance in Karakalpakstan, Uzbekistan.

BACKGROUND: Bedaquiline (BDQ) is widely used in the treatment of rifampicin-resistant TB (RR-TB). However, resistance to BDQ is now emerging. There are no standardised regimens for BDQ-resistant TB. This study aims to share experience in managing primary BDQ-resistant TB.METHODS: We performed a retrospective study of patients treated for RR-TB in Karakalpakstan, Uzbekistan, from January 2017 to March 2022. We identified patients with resistance to BDQ with no history of BDQ exposure. We describe baseline characteristics, treatment and follow-up of these patients.RESULTS: Twelve of the 1,930 patients (0.6%) had baseline samples resistant to BDQ with no history of BDQ exposure, 75% (9/12) of whom had been previously treated for TB. Ten (83.3%) were resistant to fluoroquinolones; respectively 66% and 50% had culture conversion by Month 3 and Month 6. The interim treatment outcomes were as follows: unfavourable treatment outcomes (3/12, 25%), favourable outcomes (2/12, 17%); the remaining seven (58%) were continuing treatment.CONCLUSIONS: A large proportion of the cases had previously been treated for TB and had TB resistant to quinolone. Both patients who had not experienced culture conversion by Month 3 had an unfavourable treatment outcome. Therefore, we recommend monthly monitoring of culture status for patients on treatment regimens for BDQ resistance.

Influence of climate change and pesticide use practices on the ecological risks of pesticides in a protected Mediterranean wetland: A Bayesian network approach.

Pollution by agricultural pesticides is one of the most important pressures affecting Mediterranean coastal wetlands. Pesticide risks are expected to be influenced by climate change, which will result in an increase of temperatures and a decrease in annual precipitation. On the other hand, pesticide dosages are expected to change given the increase in pest resistance and the implementation of environmental policies like the European ´Farm-to-Fork` strategy, which aims for a 50 % reduction in pesticide usage by 2030. The influence of climate change and pesticide use practices on the ecological risks of pesticides needs to be evaluated making use of realistic environmental scenarios. This study investigates how different climate change and pesticide use practices affect the ecological risks of pesticides in the Albufera Natural Park (Valencia, Spain), a protected Mediterranean coastal wetland. We performed a probabilistic risk assessment for nine pesticides applied in rice production using three climatic scenarios (for the years 2008, 2050 and 2100), three pesticide dosage regimes (the recommended dose, and 50 % increase and 50 % decrease), and their combinations. The scenarios were used to simulate pesticide exposure concentrations in the water column of the rice paddies using the RICEWQ model. Pesticide effects were characterized using acute and chronic Species Sensitivity Distributions built with toxicity data for aquatic organisms. Risk quotients were calculated as probability distributions making use of Bayesian networks. Our results show that future climate projections will influence exposure concentrations for some of the studied pesticides, yielding higher dissipation and lower exposure in scenarios dominated by an increase of temperatures, and higher exposure peaks in scenarios where heavy precipitation events occur right after pesticide application. Our case study shows that pesticides such as azoxystrobin, difenoconazole and MCPA are posing unacceptable ecological risks for aquatic organisms, and that the implementation of the ´Farm-to-Fork` strategy is crucial to reduce them.

Comparison of piecewise structural equation modeling and Bayesian network for de novo construction of a quantitative adverse outcome pathway network.

Quantitative adverse outcome pathway network (qAOPN) is gaining momentum due to its predictive nature, alignment with quantitative risk assessment, and great potential as a computational new approach methodology (NAM) to reduce laboratory animal tests. The present work aimed to demonstrate two advanced modeling approaches, piecewise structural equation modeling (PSEM) and Bayesian network (BN), for de novo qAOPN model construction based on routine ecotoxicological data. A previously published AOP network comprised of four linear AOPs linking excessive reactive oxygen species production to mortality in aquatic organisms was employed as a case study. The demonstrative case study intended to answer: Which linear AOP in the network contributed the most to the AO? Can any of the upstream KEs accurately predict the AO? What are the advantages and limitations of PSEM or BN in qAOPN development? The outcomes from the two approaches showed that both PSEM and BN are suitable for constructing a complex qAOPN based on limited experimental data. Besides quantification of response-response relationships, both approaches could identify the most influencing linear AOP in a complex network and evaluate the predictive ability of the AOP, albeit some discrepancies in predictive ability were identified for the two approaches using this specific dataset. The advantages and limitations of the two approaches for qAOPN construction are discussed in detail, and suggestions on optimal workflows of PSEM and BN are provided to guide future qAOPN development.

Weight of evidence tools in the prediction of acute fish toxicity.

Acute fish toxicity (AFT) is a key endpoint in nearly all regulatory implementations of environmental hazard assessments of chemicals globally. Although it is an early tier assay, the AFT assay is complex and uses many juvenile fish each year for the registration and assessment of chemicals. Thus, it is imperative to seek animal alternative approaches to replace or reduce animal use for environmental hazard assessments. A Bayesian Network (BN) model has been developed that brings together a suite of lines of evidence (LoEs) to produce a probabilistic estimate of AFT without the testing of additional juvenile fish. Lines of evidence include chemical descriptors, mode of action (MoA) assignment, knowledge of algal and daphnid acute toxicity, and animal alternative assays such as fish embryo tests and in vitro fish assays (e.g., gill cytotoxicity). The effort also includes retrieval, assessment, and curation of quality acute fish toxicity data because these act as the baseline of comparison with model outputs. An ideal outcome of this effort would be to have global applicability, acceptance and uptake, relevance to predominant fish species used in chemical assessments, be expandable to allow incorporation of future knowledge, and data to be publicly available. The BN model can be conceived as having incorporated principles of tiered assessment and whose outcomes will be directed by the available evidence in combination with prior information. We demonstrate that, as additional evidence is included in the prediction of a given chemical's ecotoxicity profile, both the accuracy and the precision of the predicted AFT can increase. Ultimately an improved environmental hazard assessment will be achieved. Integr Environ Assess Manag 2023;19:1220-1234. © 2022 SETAC.