Writing direction influences the spatial representations of past- and future-tense forms: Evidence from eye tracking.

The present study tests the hypothesis that the directionality of reading habits (left-to-right or right-to-left) impacts individuals' representation of nonspatial events. Using the blank screen paradigm, we examine whether eye movements reflect culture-specific spatial biases in processing temporal information, specifically, grammatical tense in Russian and Hebrew. Sixty-two native speakers of Russian (a language with a left-to-right reading and writing system) and 62 native speakers of Hebrew (a language with a right-to-left reading and writing system) listened to verbs in the past or future tense while their spontaneous gaze positions were recorded. Following the verb, a visual spatial probe appeared in one of the five locations of the screen, and participants responded manually to indicate its position. While participants' response latencies to the spatial probe revealed no significant effects, their gaze positions along the horizontal axis for past- and future-tensed verbs aligned with the reading and writing direction in their language. These results provide novel evidence that eye movements during auditory processing of grammatical tense are influenced by culturally specific reading and writing conventions, shifting leftward or rightward on the horizontal plane depending on the stimuli's time reference (past or future) and the participants' language (Russian or Hebrew). This spatial bias indicates a common underlying cognitive mechanism that uses spatial dimensions to represent temporal constructs.

Pre-supplementary motor area strengthens reward sensitivity in intertemporal choice.

Previous investigations on the causal neural mechanisms underlying intertemporal decision making focused on the dorsolateral prefrontal cortex as neural substrate of cognitive control. However, little is known, about the causal contributions of further parts of the frontoparietal control network to delaying gratification, including the pre-supplementary motor area (pre-SMA) and posterior parietal cortex (PPC). Conflicting previous evidence related pre-SMA and PPC either to evidence accumulation processes, choice biases, or response caution. To disentangle between these alternatives, we combined drift diffusion models of decision making with online transcranial magnetic stimulation (TMS) over pre-SMA and PPC during an intertemporal decision task. While we observed no robust effects of PPC TMS, perturbation of pre-SMA activity reduced preferences for larger over smaller rewards. A drift diffusion model of decision making suggests that pre-SMA increases the weight assigned to reward magnitudes during the evidence accumulation process without affecting choice biases or response caution. Taken together, the current findings reveal the computational role of the pre-SMA in value-based decision making, showing that pre-SMA promotes choices of larger, costly rewards by strengthening the sensitivity to reward magnitudes.

Evolution of gene regulatory networks by means of selection and random genetic drift.

The evolution of a population by means of genetic drift and natural selection operating on a gene regulatory network (GRN) of an individual has not been scrutinized in depth. Thus, the relative importance of various evolutionary forces and processes on shaping genetic variability in GRNs is understudied. In this study, we implemented a simulation framework, called EvoNET, that simulates forward-in-time the evolution of GRNs in a population. The fitness effect of mutations is not constant, rather fitness of each individual is evaluated on the phenotypic level, by measuring its distance from an optimal phenotype. Each individual goes through a maturation period, where its GRN may reach an equilibrium, thus deciding its phenotype. Afterwards, individuals compete to produce the next generation. We examine properties of the GRN evolution, such as robustness against the deleterious effect of mutations and the role of genetic drift. We are able to confirm previous hypotheses regarding the effect of mutations and we provide new insights on the interplay between random genetic drift and natural selection.

Genomic-inferred cross-selection methods for multi-trait improvement in a recurrent selection breeding program.

The major drawback to the implementation of genomic selection in a breeding program lies in long-term decrease in additive genetic variance, which is a trade-off for rapid genetic improvement in short term. Balancing increase in genetic gain with retention of additive genetic variance necessitates careful optimization of this trade-off. In this study, we proposed an integrated index selection approach within the genomic inferred cross-selection (GCS) framework to maximize genetic gain across multiple traits. With this method, we identified optimal crosses that simultaneously maximize progeny performance and maintain genetic variance for multiple traits. Using a stochastic simulated recurrent breeding program over a 40-years period, we evaluated different GCS methods along with other factors, such as the number of parents, crosses, and progeny per cross, that influence genetic gain in a pulse crop breeding program. Across all breeding scenarios, the posterior mean variance consistently enhances genetic gain when compared to other methods, such as the usefulness criterion, optimal haploid value, mean genomic estimated breeding value, and mean index selection value of the superior parents. In addition, we provide a detailed strategy to optimize the number of parents, crosses, and progeny per cross that can potentially maximize short- and long-term genetic gain in a public breeding program.

Perpetual step-like restructuring of hippocampal circuit dynamics.

Representation of the environment by hippocampal populations is known to drift even within a familiar environment, which could reflect gradual changes in single-cell activity or result from averaging across discrete switches of single neurons. Disambiguating these possibilities is crucial, as they each imply distinct mechanisms. Leveraging change point detection and model comparison, we find that CA1 population vectors decorrelate gradually within a session. In contrast, individual neurons exhibit predominantly step-like emergence and disappearance of place fields or sustained changes in within-field firing. The changes are not restricted to particular parts of the maze or trials and do not require apparent behavioral changes. The same place fields emerge, disappear, and reappear across days, suggesting that the hippocampus reuses pre-existing assemblies, rather than forming new fields de novo. Our results suggest an internally driven perpetual step-like reorganization of the neuronal assemblies.

Longitudinal registration of thoracic CT images with radiation-induced lung diseases: A divide-and-conquer approach based on component structure wise registration using coherent point drift.

BACKGROUND AND OBJECTIVE: Registration of pulmonary computed tomography (CT) images with radiation-induced lung diseases (RILD) was essential to investigate the voxel-wise relationship between the formation of RILD and the radiation dose received by different tissues. Although various approaches had been developed for the registration of lung CTs, their performances remained clinically unsatisfactory for registration of lung CT images with RILD. The main difficulties arose from the longitudinal change in lung parenchyma, including RILD and volumetric change of lung cancers, after radiation therapy, leading to inaccurate registration and artifacts caused by erroneous matching of the RILD tissues. METHODS: To overcome the influence of the parenchymal changes, a divide-and-conquer approach rooted in the coherent point drift (CPD) paradigm was proposed. The proposed method was based on two kernel ideas. One was the idea of component structure wise registration. Specifically, the proposed method relaxed the intrinsic assumption of equal isotropic covariances in CPD by decomposing a lung and its surrounding tissues into component structures and independently registering the component structures pairwise by CPD. The other was the idea of defining a vascular subtree centered at a matched branch point as a component structure. This idea could not only provide a sufficient number of matched feature points within a parenchyma, but avoid being corrupted by the false feature points resided in the RILD tissues due to globally and indiscriminately sampling using mathematical operators. The overall deformation model was built by using the Thin Plate Spline based on all matched points. RESULTS: This study recruited 30 pairs of lung CT images with RILD, 15 of which were used for internal validation (leave-one-out cross-validation) and the other 15 for external validation. The experimental results showed that the proposed algorithm achieved a mean and a mean of maximum 1 % of average surface distances <2 and 8 mm, respectively, and a mean and a maximum target registration error <2 mm and 5 mm on both internal and external validation datasets. The paired two-sample t-tests corroborated that the proposed algorithm outperformed a recent method, the Stavropoulou's method, on the external validation dataset (p < 0.05). CONCLUSIONS: The proposed algorithm effectively reduced the influence of parenchymal changes, resulting in a reasonably accurate and artifact-free registration.

The protein domains of vertebrate species in which selection is more effective have greater intrinsic structural disorder.

The nearly neutral theory of molecular evolution posits variation among species in the effectiveness of selection. In an idealized model, the census population size determines both this minimum magnitude of the selection coefficient required for deleterious variants to be reliably purged, and the amount of neutral diversity. Empirically, an 'effective population size' is often estimated from the amount of putatively neutral genetic diversity and is assumed to also capture a species' effectiveness of selection. A potentially more direct measure of the effectiveness of selection is the degree to which selection maintains preferred codons. However, past metrics that compare codon bias across species are confounded by among-species variation in %GC content and/or amino acid composition. Here, we propose a new Codon Adaptation Index of Species (CAIS), based on Kullback-Leibler divergence, that corrects for both confounders. We demonstrate the use of CAIS correlations, as well as the Effective Number of Codons, to show that the protein domains of more highly adapted vertebrate species evolve higher intrinsic structural disorder.

Evolution is the process through which populations change over time, starting with mutations in the genetic sequence of an organism. Many of these mutations harm the survival and reproduction of an organism, but only by a very small amount. Some species, especially those with large populations, can purge these slightly harmful mutations more effectively than other species. This fact has been used by the 'drift barrier theory' to explain various profound differences amongst species, including differences in biological complexity. In this theory, the effectiveness of eliminating slightly harmful mutations is specified by an 'effective' population size, which depends on factors beyond just the number of individuals in the population. Effective population size is normally calculated from the amount of time a 'neutral' mutation (one with no effect at all) stays in the population before becoming lost or taking over. Estimating this time requires both representative data for genetic diversity and knowledge of the mutation rate. A major limitation is that these data are unavailable for most species. A second limitation is that a brief, temporary reduction in the number of individuals has an oversized impact on the metric, relative to its impact on the number of slighly harmful mutations accumulated. Weibel, Wheeler et al. developed a new metric to more directly determine how effectively a species purges slightly harmful mutations. Their approach is based on the fact that the genetic code has 'synonymous' sequences. These sequences code for the same amino acid building block, with one of these sequences being only slightly preferred over others. The metric by Weibel, Wheeler et al. quantifies the proportion of the genome from which less preferred synonymous sequences have been effectively purged. It judges a population to have a higher effective population size when the usage of synonymous sequences departs further from the usage predicted from mutational processes. The researchers expected that natural selection would favour 'ordered' proteins with robust three-dimensional structures, i.e., that species with a higher effective population size would tend to have more ordered versions of a protein. Instead, they found the opposite: species with a higher effective population size tend to have more disordered versions of the same protein. This changes our view of how natural selection acts on proteins. Why species are so different remains a fundamental question in biology. Weibel, Wheeler et al. provide a useful tool for future applications of drift barrier theory to a broad range of ways that species differ.

One or two things we know about concept drift-a survey on monitoring in evolving environments. Part B: locating and explaining concept drift.

In an increasing number of industrial and technical processes, machine learning-based systems are being entrusted with supervision tasks. While they have been successfully utilized in many application areas, they frequently are not able to generalize to changes in the observed data, which environmental changes or degrading sensors might cause. These changes, commonly referred to as concept drift can trigger malfunctions in the used solutions which are safety-critical in many cases. Thus, detecting and analyzing concept drift is a crucial step when building reliable and robust machine learning-driven solutions. In this work, we consider the setting of unsupervised data streams which is highly relevant for different monitoring and anomaly detection scenarios. In particular, we focus on the tasks of localizing and explaining concept drift which are crucial to enable human operators to take appropriate action. Next to providing precise mathematical definitions of the problem of concept drift localization, we survey the body of literature on this topic. By performing standardized experiments on parametric artificial datasets we provide a direct comparison of different strategies. Thereby, we can systematically analyze the properties of different schemes and suggest first guidelines for practical applications. Finally, we explore the emerging topic of explaining concept drift.

Submarine canyon development controlled by slope failure and oceanographic process interactions.

The southeastern Australian margin hosts a series of submarine canyons. Although the origin and evolution of canyons within the northwestern segment of the margin is relatively well studied, their quantitative morphology, interaction with longshore drift currents and slope failure remain poorly understood in the southeastern region. In this study, high-resolution bathymetry and 3D seismic reflection datasets revealed five main submarine canyons present in the central offshore Otway Basin. The canyons have V-shaped, evolving to U-shaped morphology downslope with sedimentary infill characterized by medium-high amplitudes, recognizable stratal pattern and localized chaotic seismic reflections. Analysis reveals these canyons were initiated by retrogressive slope failure on the continental slope, that once the shelf edge was reached and subsequently incised, development of the canyon heads was influenced by the shelf parallel Zeehan Current, active on the continental shelf of the region. The heads of the shelf-incised canyons preferentially migrate northwestward and were infilled by laterally accreting sedimentary packages characterized by southeast dipping seismic reflections. These indicate an early erosive phase followed by a period of deposition, a result of the prevalent eastward flowing Zeehan Current. These results have important implications for understanding of the mechanisms that control initiation and development of submarine canyons, and their morphology, both offshore southeastern Australia, and similar settings on continental margins worldwide.

Electronic Noses: From Gas-Sensitive Components and Practical Applications to Data Processing.

Artificial olfaction, also known as an electronic nose, is a gas identification device that replicates the human olfactory organ. This system integrates sensor arrays to detect gases, data acquisition for signal processing, and data analysis for precise identification, enabling it to assess gases both qualitatively and quantitatively in complex settings. This article provides a brief overview of the research progress in electronic nose technology, which is divided into three main elements, focusing on gas-sensitive materials, electronic nose applications, and data analysis methods. Furthermore, the review explores both traditional MOS materials and the newer porous materials like MOFs for gas sensors, summarizing the applications of electronic noses across diverse fields including disease diagnosis, environmental monitoring, food safety, and agricultural production. Additionally, it covers electronic nose pattern recognition and signal drift suppression algorithms. Ultimately, the summary identifies challenges faced by current systems and offers innovative solutions for future advancements. Overall, this endeavor forges a solid foundation and establishes a conceptual framework for ongoing research in the field.

Anterior cingulate cortex lesions impair multiple facets of task engagement not mediated by dorsomedial striatum neuron firing.

The anterior cingulate cortex (ACC) has been implicated across multiple highly specialized cognitive functions-including task engagement, motivation, error detection, attention allocation, value processing, and action selection. Here, we ask if ACC lesions disrupt task performance and firing in dorsomedial striatum (DMS) during the performance of a reward-guided decision-making task that engages many of these cognitive functions. We found that ACC lesions impacted several facets of task performance-including decreasing the initiation and completion of trials, slowing reaction times, and resulting in suboptimal and inaccurate action selection. Reductions in movement times towards the end of behavioral sessions further suggested attenuations in motivation, which paralleled reductions in directional action selection signals in the DMS that were observed later in recording sessions. Surprisingly, however, beyond altered action signals late in sessions-neural correlates in the DMS were largely unaffected, even though behavior was disrupted at multiple levels. We conclude that ACC lesions result in overall deficits in task engagement that impact multiple facets of task performance during our reward-guided decision-making task, which-beyond impacting motivated action signals-arise from dysregulated attentional signals in the ACC and are mediated via downstream targets other than DMS.

Epigenetic patterns, accelerated biological aging, and enhanced epigenetic drift detected 6 months following COVID-19 infection: insights from a genome-wide DNA methylation study.

BACKGROUND: The epigenetic status of patients 6-month post-COVID-19 infection remains largely unexplored. The existence of long-COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), suggests potential long-term changes. Long-COVID includes symptoms like fatigue, neurological issues, and organ-related problems, regardless of initial infection severity. The mechanisms behind long-COVID are unclear, but virus-induced epigenetic changes could play a role. METHODS AND RESULTS: Our study explores the lasting epigenetic impacts of SARS-CoV-2 infection. We analyzed genome-wide DNA methylation patterns in an Italian cohort of 96 patients 6 months after COVID-19 exposure, comparing them to 191 healthy controls. We identified 42 CpG sites with significant methylation differences (FDR < 0.05), primarily within CpG islands and gene promoters. Dysregulated genes highlighted potential links to glutamate/glutamine metabolism, which may be relevant to PASC symptoms. Key genes with potential significance to COVID-19 infection and long-term effects include GLUD1, ATP1A3, and ARRB2. Furthermore, Horvath's epigenetic clock showed a slight but significant age acceleration in post-COVID-19 patients. We also observed a substantial increase in stochastic epigenetic mutations (SEMs) in the post-COVID-19 group, implying potential epigenetic drift. SEM analysis identified 790 affected genes, indicating dysregulation in pathways related to insulin resistance, VEGF signaling, apoptosis, hypoxia response, T-cell activation, and endothelin signaling. CONCLUSIONS: Our study provides valuable insights into the epigenetic consequences of COVID-19. Results suggest possible associations with accelerated aging, epigenetic drift, and the disruption of critical biological pathways linked to insulin resistance, immune response, and vascular health. Understanding these epigenetic changes could be crucial for elucidating the complex mechanisms behind long-COVID and developing targeted therapeutic interventions.

Investigating the use of comprehensive motion monitoring for intrafraction 3D drift assessment of hypofractionated prostate cancer patients on a 1.5T magnetic resonance imaging radiotherapy system.

This work investigates the use of a multi-2D cine magnetic resonance imaging-based comprehensive motion monitoring (CMM) system for the assessment of prostate intrafraction 3D drifts. The data of six healthy volunteers were analyzed and the values of a clinically-relevant registration quality factor metric exported by CMM were presented. Additionally, the CMM-derived prostate motion was compared to a 3D-based reference and the 2D-3D tracking agreement was reported. Due to the low quality of SI motion tracking (often > 2 mm tracking mismatch between anatomical planes) we conclude that further improvements are desirable prior to clinical introduction of CMM for prostate drift corrections.

Spectral intensity drift correction of Spark Mapping Analysis for large-size metal materials.

BACKGROUND: Spectral intensity drift is a frequent issue in analytical processes, especially in long time excitation scanning for large size metal materials, which can significantly adversely impact the accuracy and stability of analysis results. Spectral intensity drift correction is the process of preprocessing spectral data using mathematical algorithms in order to facilitate the subsequent qualitative and quantitative analysis of spectra, especially in combination with stoichiometric methods. Up to now, spectral intensity drift correction within prolonged excitation has not been reported yet. RESULTS: We propose an intensity drift correction method for element content of large-size samples using the Spark Mapping Analysis for Large Samples (SMALS) technique. By considering the row-by-row and column-by-column mapping modes of the SMALS, this includes curve fitting baseline correction for in-row and in-column correction, as well as total average value correction for inter-row and inter-column correction. The final measurement values are derived by coupling rows with columns. The careful implementation of correction steps can enhance baseline correction performance, effectively reducing measurement errors a drift errors. Application of this method to characterize the cross and longitudinal sections of an oversized steel billet indicates high agreement with composition distribution obtained by micro-beam X-ray fluorescence (µ-XRF). The corrected longitudinal and cross-sectional data also exhibit strong alignment. Comparison of statistical analysis results pre- and post-correction demonstrates significant improvements in the clarity of elements segregation pattern. SIGNIFICANCE: This intensity drift correction method not only enhances the spectral quality but also improves the accuracy and robustness of quantitative and qualitative spectral analysis. This study contributes to establishing a robust foundation for component characterization of large-size metal materials using the SMALS technique. The novel spectral intensity correction method shows theoretical significance and practical value for large-scale, long-duration excitation scanning analysis.

Planetary Health: A New Approach to Healing the Anthropocene.

The Anthropocene is a proposed geological epoch reflecting large-scale impact of human activity on the Earth's natural systems. This era is also characterized other significant threats to ecological wellbeing that are less evident in the sedimentary records. Extensive environmental changes with industrialization and urbanization have also contributed to declining biodiversity and microbial dysbiosis in essential ecosystems-the original and foundational lifeforms that continue to sustain virtually all ecosystems today, including our own. These changes, along with numerous other social and ecological disruptions at all scales are implicated in the rising rates of physical and mental ill-health, particularly the immune dysregulation and noncommunicable diseases that characterize the Anthropocene. This narrative review considers how urgent structural changes in how we live are essential for the future of human health and flourishing of all of life on Earth. It explores planetary health as a solutions-oriented, transdisciplinary field and social movement aimed at addressing these interconnected these global challenges through integrated ecological approaches. Planetary health considers not only the vital biophysical "planetary boundaries" required to support human flourishing, but also the upstream social, political, and economic ecosystems that support (or undermine) wellbeing at all scales. The value systems and the worldviews that have contributed to our global challenges are a central consideration in the planetary health agenda- emphasizing the imperative to address structural inequalities, injustices, and the social, emotional, and spiritual dimensions of unrealized human potential. Promoting these inner assets is essential for human flourishing and for fostering the cultural capacities necessary to ensure sustainable planetary health.

Sailing Too Close to the Wind? How Harnessing Patient Voice Can Identify Drift towards Boundaries of Acceptable Performance.

This opinion paper investigates how healthcare organizations identify and act upon different types of risk signals. These signals may generally be acknowledged, but we also often see with hindsight that they might not be because they have become a part of normal practice. Here, we detail how risk signals from patients and families should be acknowledged as system-level safety critical information and as a way of understanding and changing safety culture in healthcare. We discuss how healthcare organizations could work more proactively with patient experience data in identifying risks and improving system safety.

The reciprocal relationships between economic status and mental health: Investigating the between-person and within-person effects in a three-wave longitudinal study.

BACKGROUND: Social drift/selection (i.e., mental health symptoms cause low economic status) and social causation theories (i.e., low economic status causes mental health symptoms) specify reciprocal relationships between economic status and mental health. Little is known regarding the disaggregation of within-person and between-person effects in the relationship between economic status and mental health in the long run. The current study sought to examine the reciprocal relationships between economic status and mental health over 20 years of adulthood, disaggregating within-person and between-person effects. METHODS: Data were from three waves (7108 participants) of the Midlife Development in the United States study. Participants reported information about objective and subjective measures of economic status as well as a wide range of indicators of mental health on the positive dimension, including subjective, social, and psychological well-being, and on the negative side, depression, anxiety, panic attack, anhedonia, somatic amplification, alcohol abuse, and negative affect. Cross-lagged panel models were estimated. RESULTS: At between-person levels, both social drift/selection and social causation hypotheses were confirmed when considering subjective measures of economic status. When using objective measures of economic status (i.e., income), the results showed decreased support for social drift/selection and social causation hypotheses. At within-person levels, social drift/selection and social causation hypotheses were generally not supported, with some notable exceptions. LIMITATIONS: Restriction of the sample to one country limits the generalizability of the findings. CONCLUSIONS: Social causation and social drift/selection processes act simultaneously mainly at a population level, but much less when considering individual changes. Policy and programs should be targeted at addressing inequality in income and mental health within a nation or a community.

When Games Influence Words: Gaming Addiction among College Students Increases Verbal Aggression through Risk-Biased Drifting in Decision-Making.

Increased aggression due to gaming addiction is a widespread and highly publicized problem. The underlying processes by which verbal aggression, a more harmful and persistent subcategory of aggression, is affected by gaming addiction may differ from other types of aggression. In this study, data came from 252 randomly recruited current university students (50.79% male, mean age 19.60 years, SD: 1.44 years, range 17 to 29 years). Participants reported gaming addiction and different types of aggression through questionnaires. In addition, two important explanatory processes, inhibitory control, and risk preference, were measured through behavioral experiments. A Bayesian hierarchical drift-diffusion model was employed to interpret the data from the risk preference task. In contrast to previous work, the study found that inhibitory control did not significantly correlate with either gaming addiction or any form of aggression However, the drift rate, a measure of decision-making inclination under risk, partially mediates the relationship between gaming addiction and verbal aggression (but not other forms of aggression). The findings illuminate risk preference under adverse conditions as a key predictor of verbal aggression, offering avenues for early intervention and suggesting game design modifications to mitigate verbal aggression by adjusting reward mechanisms.

Treatment Comparisons in Adaptive Platform Trials Adjusting for Temporal Drift.

An adaptive platform trial (APT) is a multi-arm trial in the context of a single disease where treatment arms are allowed to enter or leave the trial based on some decision rule. If a treatment enters the trial later than the control arm, there exist non-concurrent controls who were not randomized between the two arms under comparison. As APTs typically take long periods of time to conduct, temporal drift may occur, which requires the treatment comparisons to be adjusted for this temporal change. Under the causal inference framework, we propose two approaches for treatment comparisons in APTs that account for temporal drift, both based on propensity score weighting. In particular, to address unmeasured confounders, one approach is doubly robust in the sense that it remains valid so long as either the propensity score model is correctly specified or the time effect model is correctly specified. Simulation study shows that our proposed approaches have desirable operating characteristics with well controlled type I error rates and high power with or without unmeasured confounders.

Simulated Herbicide Drift Effects on Seed Germination, Seedling Emergence, and Seedling Growth of Native Plants of the Northern Great Plains.

Small concentrations of herbicide, such as those found in drift, can affect nontarget plants at different life-history stages including seed germination and seedling emergence as well as seedling growth. Fragmented landscapes, such as those in the northern Great Plains, lead to increased proximity of ecological restoration sites to agricultural lands using herbicides. Germination, emergence, and growth are crucial life-history stages leading to ecological restoration success, but these stages are sensitive to impacts from external factors such as herbicide exposure. A lab germination experiment and a greenhouse emergence experiment were performed to examine the effect of herbicides (2,4-dichlorophenoxyacetic acid [2,4-D], atrazine, and trifluralin) on species used in ecological restorations in the northern Great Plains. Seed germination, seedling emergence, and seedling growth of many study species decreased with exposure to herbicides at different concentrations representative of herbicide drift. At concentrations as low as 0.1% recommended application rate 2,4-D elicited broad effects on final seed germination percentage and germination rate. Atrazine affected seedling emergence and growth for a number of study species at concentrations as low as 10% recommended application rate. Trifluralin affected germination, emergence, and growth of the fewest number of study species. The information gained from these experiments can be used to inform restoration practitioners of best practices and recommended species to use when implementing ecological restoration adjacent to agricultural lands. Environ Toxicol Chem 2024;00:1-11. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.