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People with epilepsy (PWE) are at higher risk of psychiatric disorders (PD), disability, and reduced quality of life than the general population, especially in childhood and adolescence and when seizures originate from the temporal lobe. Temporal Lobe Epilepsy (TLE) is the most common type of focal epilepsy and can be due to structural abnormalities, or non-lesional causes, such as genetic variants. The prevalence of PD is approximately 20%-30% in people with epilepsy in general, and from 40% up to 80% in people with TLE. A higher rate of anxiety and depression disorders has been observed in association with TLE than with extra-temporal epilepsy, or idiopathic generalized epilepsy, or other chronic diseases such as diabetes. However, while the association between psychopathology and TLE has been extensively assessed in adults, only a few studies have focused on its expression in children and adolescents. In this review, we describe the prevalence, characteristics, and risk factors for PD in people with epilepsy in general and with TLE, with a specific focus on the pediatric age. In addition, we provide insights into the current knowledge of the pathophysiological bases of psychiatric symptoms in children and adolescents with TLE. PLAIN LANGUAGE SUMMARY: This review examines the frequency and characteristics of psychiatric disorders in people with temporal lobe epilepsy, with a focus on children and adolescents. Similarly to adults, younger people with epilepsy have higher rates of psychiatric disorders, such as depression and anxiety, than healthy peers or children with other chronic illnesses such as diabetes and asthma. Contributing risk factors include epilepsy duration and severity, and the effects of antiseizure medications, as well as psychological challenges, sociocultural influences, and family dynamics. Psychiatric disorders associated with temporal lobe epilepsy are relatively frequent, probably in relation to the critical role that some limbic structures in the temporal lobe, such as the amygdala and hippocampus, play in regulating emotions and behavior., (© 2024 The Author(s). Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

The regulation of populations through density dependence (DD) has long been a central tenet of studies of ecological systems. As an important factor in regulating populations, DD is also crucial for understanding risks to populations from stressors, including its incorporation into population models applied for this purpose. However, study of density-dependent regulation is challenging because it can occur through various mechanisms, and their identification in the field, as well as the quantification of the consequences on individuals and populations, can be difficult. We conducted a targeted literature review specifically focusing on empirical laboratory or field studies addressing negative DD in freshwater fish and small rodent populations, two vertebrate groups considered in pesticide Ecological Risk Assessment (ERA). We found that the most commonly recognized causes of negative DD were food (63% of 19 reviewed fish studies, 40% of 25 mammal studies) or space limitations (32% of mammal studies). In addition, trophic interactions were reported as causes of population regulation, with predation shaping mostly small mammal populations (36% of the mammal studies) and cannibalism impacting freshwater fish (26%). In the case of freshwater fish, 63% of the studies were experimental (i.e., with a length of weeks or months). They generally focused on the individual-level causes and effects of DD, and had a short duration. Moreover, DD affected mostly juvenile growth and survival of fish (68%). On the other hand, studies on small mammals were mainly based on time series analyzing field population properties over longer timespans (68%). Density dependence primarily affected survival in subadult and adult mammal stages and, to a lesser extent, reproduction (60% vs. 36%). Furthermore, delayed DD was often observed (56%). We conclude by making suggestions on future research paths, providing recommendations for including DD in population models developed for ERA, and making the best use of the available data. Integr Environ Assess Manag 2024;20:1225-1236. © 2023 Syngenta Crop Protection. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2023 Syngenta Crop Protection. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

The use of mechanistic population models as research and decision-support tools in ecology and ecological risk assessment (ERA) is increasing. This growth has been facilitated by advances in technology, allowing the simulation of more complex systems, as well as by standardized approaches for model development, documentation, and evaluation. Mechanistic population models are particularly useful for simulating complex systems, but the required model complexity can make them challenging to communicate. Conceptual diagrams that summarize key model elements, as well as elements that were considered but not included, can facilitate communication and understanding of models and increase their acceptance as decision-support tools. Currently, however, there are no consistent standards for creating or presenting conceptual model diagrams (CMDs), and both terminology and content vary widely. Here, we argue that greater consistency in CMD development and presentation is an important component of good modeling practice, and we provide recommendations, examples, and a free web app (pop-cmd.com) for achieving this for population models used for decision support in ERAs. Integr Environ Assess Manag 2024;20:1566-1574. © 2023 SETAC., (© 2023 SETAC.)

Objective: To assess seizure and developmental outcomes, their predictors, and complications in 160 children who, between 1998 and 2022, underwent surgery for lesional epilepsy with curative intent before the age of 3 years. To compare trends in epilepsy surgery in this age group before and after the year 2014., Methods: Retrospective multicenter study. Descriptive and univariate analyses, and multivariable models for all outcomes., Results: These 160 patients (76 F; 47.5%) underwent 169 surgeries (age at surgery 20.4 ± 9.4 months). At the last follow-up (77 ± 57.4 months), 121 patients (75.6%) were in Engel class I, 106 (66.2%) of whom were in Engel class Ia. Antiseizure medications were stopped in 84 patients (52.5%). Complications requiring reoperations were observed in 16 patients (10%; 9.5% of surgeries) and unexpected permanent deficits in 12 (7.5%; 7.1% of surgeries). Postoperative cognitive functions remained unchanged in 56 patients (44.4%), improved in 51 (40.5%), and worsened in 19 (15.1%). Multivariable analyses showed that the probability of achieving Engel class Ia was lower when the duration of epilepsy was longer, patients underwent preoperative video-EEG, and unexpected postoperative permanent deficits occurred. Cognitive improvement after surgery was associated with lower preoperative seizure frequency, better preoperative developmental level, and a longer postoperative follow-up. FCDII and tumors were the histopathologies carrying a higher probability of achieving seizure freedom, while polymicrogyria was associated with a lower probability of cognitive improvement. The number of patients operated on after 2014 was higher than before (61.3% vs. 38.7%), with stable outcomes., Significance: Epilepsy surgery is effective and safe in infants and toddlers, although the complication rate is higher than seen in older patients. Shorter duration of epilepsy, lower seizure frequency, no need for video-EEG, tumors, and some malformations of cortical development are robust predictors of seizure and cognitive outcome that may be exploited to increase earlier referral., Plain Language Summary: This study analyzed the results of epilepsy surgery in 160 children who had been operated on before the age of 3 years at four Italian centers between 1998 and 2022. At the last follow-up (77 ± 57.4 months), 121 patients (75.6%) were free from disabling seizures, of which 106 (66.2%) were completely seizure-free since surgery. Major surgical complications occurred in 28 patients (17.5%), which is higher than observed with epilepsy surgery in general, but similar to hemispheric/multilobar surgery. Postoperative cognitive function remained unchanged in 56 patients (44.4%), improved in 51 (40.5%), and worsened in 19 (15.1%). Epilepsy surgery is effective and safe in infants and toddlers., (© 2024 The Author(s). Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Several racial and ethnic identities are widely understood to be under-represented within academia, however, actual quantification of this under-representation is surprisingly limited. Challenges include data availability, demographic inertia and identifying comparison points. We use de-aggregated data from the U.S. National Science Foundation to construct a null model of ethnic and racial representation in one of the world's largest academic communities. Making comparisons between our model and actual representation in academia allows us to measure the effects of retention (while controlling for recruitment) at different academic stages. We find that, regardless of recruitment, failed retention contributes to mis-representation across academia and that the stages responsible for the largest disparities differ by race and ethnicity: for Black and Hispanic scholars this occurs at the transition from graduate student to postdoctoral researcher whereas for Native American/Alaskan Native and Native Hawaiian/Pacific Islander scholars this occurs at transitions to and within faculty stages. Even for Asian and Asian-Americans, often perceived as well represented, circumstances are complex and depend on choice of baseline. Our findings demonstrate that while recruitment continues to be important, retention is also a pervasive barrier to proportional representation. Therefore, strategies to reduce mis-representation in academia must address retention. Although our model does not directly suggest specific strategies, our framework could be used to project how representation in academia might change in the long-term under different scenarios., Competing Interests: The authors have declared that no competing interests exist.

The assimilation of population models into ecological risk assessment (ERA) has been hindered by their range of complexity, uncertainty, resource investment, and data availability. Likewise, ensuring that the models address risk assessment objectives has been challenging. Recent research efforts have begun to tackle these challenges by creating an integrated modeling framework and decision guide to aid the development of population models with respect to ERA objectives and data availability. In the framework, the trade-offs associated with the generality, realism, and precision of an assessment are used to guide the development of a population model commensurate with the protection goal. The decision guide provides risk assessors with a stepwise process to assist them in developing a conceptual model that is appropriate for the assessment objective and available data. We have merged the decision guide and modeling framework into a comprehensive approach, Population modeling Guidance, Use, Interpretation, and Development for Ecological risk assessment (Pop-GUIDE), for the development of population models for ERA that is applicable across regulatory statutes and assessment objectives. In Phase 1 of Pop-GUIDE, assessors are guided through the trade-offs of ERA generality, realism, and precision, which are translated into model objectives. In Phase 2, available data are assimilated and characterized as general, realistic, and/or precise. Phase 3 provides a series of dichotomous questions to guide development of a conceptual model that matches the complexity and uncertainty appropriate for the assessment that is in concordance with the available data. This phase guides model developers and users to ensure consistency and transparency of the modeling process. We introduce Pop-GUIDE as the most comprehensive guidance for population model development provided to date and demonstrate its use through case studies using fish as an example taxon and the US Federal Insecticide Fungicide and Rodenticide Act and Endangered Species Act as example regulatory statutes. Integr Environ Assess Manag 2021;17:767-784. © 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA., (© 2020 SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.)

Population models can provide valuable tools for ecological risk assessment (ERA). A growing amount of work on model development and documentation is now available to guide modelers and risk assessors to address different ERA questions. However, there remain misconceptions about population models for ERA, and communication between regulators and modelers can still be hindered by a lack of clarity in the underlying formalism, implementation, and complexity of different model types. In particular, there is confusion about differences among types of models and the implications of including or ignoring interactions of organisms with each other and their environment. In this review, we provide an overview of the key features represented in population models of relevance for ERA, which include density dependence, spatial heterogeneity, external drivers, stochasticity, life-history traits, behavior, energetics, and how exposure and effects are integrated in the models. We differentiate 3 broadly defined population model types (unstructured, structured, and agent-based) and explain how they can represent these key features. Depending on the ERA context, some model features will be more important than others, and this can inform model type choice, how features are implemented, and possibly the collection of additional data. We show that nearly all features can be included irrespective of formalization, but some features are more or less easily incorporated in certain model types. We also analyze how the key features have been used in published population models implemented as unstructured, structured, and agent-based models. The overall aim of this review is to increase confidence and understanding by model users and evaluators when considering the potential and adequacy of population models for use in ERA. Integr Environ Assess Manag 2021;17:521-540. © 2020 SETAC., (© 2020 SETAC.)

Understanding the interactions among multiple stressors is a crucial issue for ecological risk assessment and ecosystem management. However, it is often impractical, or impossible, to collect empirical data concerning all the interactions at any scale because the type of interaction differs across species and levels of biological organization. We applied an agent-based model to simulate the effects of a hypothetical chemical stressor and inter-specific competition (both alone and together) on greenback cutthroat trout (GCT), a listed species under the US Endangered Species Act, in two temperature scenarios. The trout life cycle is modeled using the Dynamic Energy Budget theory. The chemical stressor is represented by a reduction in ingestion efficiency, and competition is implemented by introducing a population of brown trout. Results show that chemical exposure is the major stressor in the colder temperature scenario, whereas competition mostly affected the GCT population in the warmer environment. Moreover, the effects of the stressors at the individual level were not predictive of the type of interactions between stressors (additive, antagonistic, synergistic) at the population level, which differed between the two-temperature scenarios. We conclude that mechanistic models can help to identify generalities about interactions among environmental and stressor properties, create in-silico experiments to provide different scenarios for conservation purposes, and explore multiple-exposure consequences at higher levels of biological organization. In this way they can provide useful tools for improving ecological risk assessment and informing management decisions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Despite widespread acceptance of the utility of population modeling and advocacy of this approach for a more ecologically relevant perspective, it is not routinely incorporated in ecological risk assessments (ERA). A systematic framework for situation-specific model development is one of the major challenges to broadly adopting population models in ERA. As risk assessors confront the multitude of species and chemicals requiring evaluation, an adaptable stepwise guide for model parameterization would facilitate this process. Additional guidance on interpretation of model output and evaluating uncertainty would further contribute to establishing consensus on good modeling practices. We build on previous work that created a framework and decision guide for developing population models for ERA by focusing on data types, model structure, and extrinsic stressors relevant to anuran amphibians. Anurans have a unique life cycle with varying habitat requirements and high phenotypic plasticity. These species belong to the amphibian class, which is facing global population decline in large part due to anthropogenic stressors, including chemicals. We synthesize information from databases and literature relevant to amphibian risks to identify traits that influence exposure likelihood, inherent sensitivity, population vulnerability, and environmental constraints. We link these concerns with relevant population modeling methods and structure in order to evaluate pesticide effects with appropriate scale and parameterization. A standardized population modeling approach, with additional guidance for anuran ERA, offers an example method for quantifying population risks and evaluating long-term impacts of chemical stressors to populations. Integr Environ Assess Manag 2020;16:223-233. © 2019 SETAC., (© 2019 SETAC.)

In this paper, we applied an individual-based model to study the population-level impacts of sub-lethal stressors affecting the metabolic pathways of three closely related trout species: Oncorhynchus mykiss (rainbow trout, RT), Salmo trutta (brown trout, BT) and Oncorhynchus calrki stomias (greenback cutthroat trout, GCT). Both RT and BT are well-studied species, and the former is widely used as a standard cold-water test species. These species are known to outcompete GCT, which is listed as threatened under the US Endangered Species Act. Our goal was to understand the extent to which stressor effects, which are often measured at the individual level, on taxonomically-related (i.e., surrogate) species can be informative of impacts on population dynamics in species that cannot be tested (e.g., listed species). When comparing stressor effects among species, we found that individual-level responses to each stressor were qualitatively comparable. Individual lengths and number of eggs decreased by similar percentages with respect to baseline, even if small quantitative differences were present depending on the physiological mode of action of the stressor. Individual-level effects in GCT were slightly greater when ingestion efficiency decreased, whereas effects in GCT and RT were greater when maintenance costs increased, and effects in BT were slightly greater when costs of growth increased. In contrast, results at the population level differed markedly among species with GCT the most impacted by sub-lethal stress effects on individual metabolism. Our findings suggest that using non-listed species to assess the risks of stressors to listed species populations may be misleading, even if the species are closely related and show similar individual-level responses. Mechanistic population models that incorporate species life history and ecology can improve inter-species extrapolation of stressor effects., (Copyright © 2019 Elsevier B.V. All rights reserved.)

We demonstrate how mechanistic modeling can be used to predict whether and how biological responses to chemicals at (sub)organismal levels in model species (i.e., what we typically measure) translate into impacts on ecosystem service delivery (i.e., what we care about). We consider a hypothetical case study of two species of trout, brown trout (Salmo trutta; BT) and greenback cutthroat trout (Oncorhynchus clarkii stomias; GCT). These hypothetical populations live in a high-altitude river system and are exposed to human-derived estrogen (17α‑ethinyl estradiol, EE2), which is the bioactive estrogen in many contraceptives. We use the individual-based model inSTREAM to explore how seasonally varying concentrations of EE2 could influence male spawning and sperm quality. Resulting impacts on trout recruitment and the consequences of such for anglers and for the continued viability of populations of GCT (the state fish of Colorado) are explored. inSTREAM incorporates seasonally varying river flow and temperature, fishing pressure, the influence of EE2 on species-specific demography, and inter-specific competition. The model facilitates quantitative exploration of the relative importance of endocrine disruption and inter-species competition on trout population dynamics. Simulations predicted constant EE2 loading to have more impacts on GCT than BT. However, increasing removal of BT by anglers can enhance the persistence of GCT and offset some of the negative effects of EE2. We demonstrate how models that quantitatively link impacts of chemicals and other stressors on individual survival, growth, and reproduction to consequences for populations and ecosystem service delivery, can be coupled with ecosystem service valuation. The approach facilitates interpretation of toxicity data in an ecological context and gives beneficiaries of ecosystem services a more explicit role in management decisions. Although challenges remain, this type of approach may be particularly helpful for site-specific risk assessments and those in which tradeoffs and synergies among ecosystem services need to be considered., (Copyright © 2018 Elsevier B.V. All rights reserved.)