Nonpeptidergic neurons suppress mast cells via glutamate to maintain skin homeostasis.

Cutaneous mast cells mediate numerous skin inflammatory processes and have anatomical and functional associations with sensory afferent neurons. We reveal that epidermal nerve endings from a subset of sensory nonpeptidergic neurons expressing MrgprD are reduced by the absence of Langerhans cells. Loss of epidermal innervation or ablation of MrgprD-expressing neurons increased expression of a mast cell gene module, including the activating receptor, Mrgprb2, resulting in increased mast cell degranulation and cutaneous inflammation in multiple disease models. Agonism of MrgprD-expressing neurons reduced expression of module genes and suppressed mast cell responses. MrgprD-expressing neurons released glutamate which was increased by MrgprD agonism. Inhibiting glutamate release or glutamate receptor binding yielded hyperresponsive mast cells with a genomic state similar to that in mice lacking MrgprD-expressing neurons. These data demonstrate that MrgprD-expressing neurons suppress mast cell hyperresponsiveness and skin inflammation via glutamate release, thereby revealing an unexpected neuroimmune mechanism maintaining cutaneous immune homeostasis.

Cutaneous TRPV1+ Neurons Trigger Protective Innate Type 17 Anticipatory Immunity.

Cutaneous TRPV1+ neurons directly sense noxious stimuli, inflammatory cytokines, and pathogen-associated molecules and are required for innate immunity against some skin pathogens. Important unanswered questions are whether TRPV1+ neuron activation in isolation is sufficient to initiate innate immune responses and what is the biological function for TRPV1+ neuron-initiated immune responses. We used TRPV1-Ai32 optogenetic mice and cutaneous light stimulation to activate cutaneous neurons in the absence of tissue damage or pathogen-associated products. We found that TRPV1+ neuron activation was sufficient to elicit a local type 17 immune response that augmented host defense to C. albicans and S. aureus. Moreover, local neuron activation elicited type 17 responses and augmented host defense at adjacent, unstimulated skin through a nerve reflex arc. These data show the sufficiency of TRPV1+ neuron activation for host defense and demonstrate the existence of functional anticipatory innate immunity at sites adjacent to infection that depends on antidromic neuron activation.

Inflammatory thoughts can upset your guts.

Peripheral neurons and immune cells interact to modulate inflammation, but whether the brain can control this process is unknown. In a recent issue of Cell, Koren et al. (2021) show that peripheral inflammation is encoded in the insular cortex and that later re-activation of these neurons triggers inflammation.

ANGPTL8/betatrophin does not control pancreatic beta cell expansion.

Recently, it was reported that angiopoietin-like protein 8 (ANGPTL8) was the long-sought "betatrophin" that could control pancreatic beta cell proliferation. However, studies of Angptl8(?/?) mice revealed profound reduction of triglyceride levels, but no abnormalities in glucose homeostasis. We now report that Angptl8(?/?) mice undergo entirely normal beta cell expansion in response to insulin resistance resulting from either a high-fat diet or from the administration of the insulin receptor antagonist S961. Furthermore, overexpression of ANGPTL8 in livers of mice doubles plasma triglyceride levels, but does not alter beta cell expansion nor glucose metabolism. These data indicate that ANGPTL8 does not play a role in controlling beta cell growth, nor can it be given to induce such expansion. The findings that plasma triglyceride levels are reduced by Angptl8 deletion and increased following ANGPTL8 overexpression support the possibility that inhibition of ANGPTL8 represents a therapeutic strategy for hypertriglyceridemia.

Age-Related Dopaminergic Innervation Augments T Helper 2-Type Allergic Inflammation in the Postnatal Lung.

Young children are more susceptible to developing allergic asthma than adults. As neural innervation of the peripheral tissue continues to develop after birth, neurons may modulate tissue inflammation in an age-related manner. Here we showed that sympathetic nerves underwent a dopaminergic-to-adrenergic transition during post-natal development of the lung in mice and humans. Dopamine signaled through a specific dopamine receptor (DRD4) to promote T helper 2 (Th2) cell differentiation. The dopamine-DRD4 pathway acted synergistically with the cytokine IL-4 by upregulating IL-2-STAT5 signaling and reducing inhibitory histone trimethylation at Th2 gene loci. In murine models of allergen exposure, the dopamine-DRD4 pathway augmented Th2 inflammation in the lungs of young mice. However, this pathway operated marginally after sympathetic nerves became adrenergic in the adult lung. Taken together, the communication between dopaminergic nerves and CD4+ T cells provides an age-related mechanism underlying the susceptibility to allergic inflammation in the early lung.

People construct simplified mental representations to plan.

One of the most striking features of human cognition is the ability to plan. Two aspects of human planning stand out-its efficiency and flexibility. Efficiency is especially impressive because plans must often be made in complex environments, and yet people successfully plan solutions to many everyday problems despite having limited cognitive resources1-3. Standard accounts in psychology, economics and artificial intelligence have suggested that human planning succeeds because people have a complete representation of a task and then use heuristics to plan future actions in that representation4-11. However, this approach generally assumes that task representations are fixed. Here we propose that task representations can be controlled and that such control provides opportunities to quickly simplify problems and more easily reason about them. We propose a computational account of this simplification process and, in a series of preregistered behavioural experiments, show that it is subject to online cognitive control12-14 and that people optimally balance the complexity of a task representation and its utility for planning and acting. These results demonstrate how strategically perceiving and conceiving problems facilitates the effective use of limited cognitive resources.

Local and systemic responses to SARS-CoV-2 infection in children and adults.

It is not fully understood why COVID-19 is typically milder in children1-3. Here, to examine the differences between children and adults in their response to SARS-CoV-2 infection, we analysed paediatric and adult patients with COVID-19 as well as healthy control individuals (total n = 93) using single-cell multi-omic profiling of matched nasal, tracheal, bronchial and blood samples. In the airways of healthy paediatric individuals, we observed cells that were already in an interferon-activated state, which after SARS-CoV-2 infection was further induced especially in airway immune cells. We postulate that higher paediatric innate interferon responses restrict viral replication and disease progression. The systemic response in children was characterized by increases in naive lymphocytes and a depletion of natural killer cells, whereas, in adults, cytotoxic T cells and interferon-stimulated subpopulations were significantly increased. We provide evidence that dendritic cells initiate interferon signalling in early infection, and identify epithelial cell states associated with COVID-19 and age. Our matching nasal and blood data show a strong interferon response in the airways with the induction of systemic interferon-stimulated populations, which were substantially reduced in paediatric patients. Together, we provide several mechanisms that explain the milder clinical syndrome observed in children.

The ubiquitin E3 ligase BFAR promotes degradation of PNPLA3.

A missense variant in patatin-like phospholipase domain-containing protein 3 [PNPLA3(I148M)] is the most impactful genetic risk factor for fatty liver disease (FLD). We previously showed that PNPLA3 is ubiquitylated and subsequently degraded by proteasomes and autophagosomes and that the PNPLA3(148M) variant interferes with this process. To define the machinery responsible for PNPLA3 turnover, we used small interfering (si)RNAs to inactivate components of the ubiquitin proteasome system. Inactivation of bifunctional apoptosis regulator (BFAR), a membrane-bound E3 ubiquitin ligase, reproducibly increased PNPLA3 levels in two lines of cultured hepatocytes. Conversely, overexpression of BFAR decreased levels of endogenous PNPLA3 in HuH7 cells. BFAR and PNPLA3 co-immunoprecipitated when co-expressed in cells. BFAR promoted ubiquitylation of PNPLA3 in vitro in a reconstitution assay using purified, epitope-tagged recombinant proteins. To confirm that BFAR targets PNPLA3, we inactivated Bfar in mice. Levels of PNPLA3 protein were increased twofold in hepatic lipid droplets of Bfar-/- mice with no associated increase in PNPLA3 mRNA levels. Taken together these data are consistent with a model in which BFAR plays a role in the post-translational degradation of PNPLA3. The identification of BFAR provides a potential target to enhance PNPLA3 turnover and prevent FLD.

Having multiple selves helps learning agents explore and adapt in complex changing worlds.

Satisfying a variety of conflicting needs in a changing environment is a fundamental challenge for any adaptive agent. Here, we show that designing an agent in a modular fashion as a collection of subagents, each dedicated to a separate need, powerfully enhanced the agent's capacity to satisfy its overall needs. We used the formalism of deep reinforcement learning to investigate a biologically relevant multiobjective task: continually maintaining homeostasis of a set of physiologic variables. We then conducted simulations in a variety of environments and compared how modular agents performed relative to standard monolithic agents (i.e., agents that aimed to satisfy all needs in an integrated manner using a single aggregate measure of success). Simulations revealed that modular agents a) exhibited a form of exploration that was intrinsic and emergent rather than extrinsically imposed; b) were robust to changes in nonstationary environments, and c) scaled gracefully in their ability to maintain homeostasis as the number of conflicting objectives increased. Supporting analysis suggested that the robustness to changing environments and increasing numbers of needs were due to intrinsic exploration and efficiency of representation afforded by the modular architecture. These results suggest that the normative principles by which agents have adapted to complex changing environments may also explain why humans have long been described as consisting of "multiple selves."

Effort Foraging Task reveals positive correlation between individual differences in the cost of cognitive and physical effort in humans.

Effort-based decisions, in which people weigh potential future rewards against effort costs required to achieve those rewards involve both cognitive and physical effort, though the mechanistic relationship between them is not yet understood. Here, we use an individual differences approach to isolate and measure the computational processes underlying effort-based decisions and test the association between cognitive and physical domains. Patch foraging is an ecologically valid reward rate maximization problem with well-developed theoretical tools. We developed the Effort Foraging Task, which embedded cognitive or physical effort into patch foraging, to quantify the cost of both cognitive and physical effort indirectly, by their effects on foraging choices. Participants chose between harvesting a depleting patch, or traveling to a new patch that was costly in time and effort. Participants' exit thresholds (reflecting the reward they expected to receive by harvesting when they chose to travel to a new patch) were sensitive to cognitive and physical effort demands, allowing us to quantify the perceived effort cost in monetary terms. The indirect sequential choice style revealed effort-seeking behavior in a minority of participants (preferring high over low effort) that has apparently been missed by many previous approaches. Individual differences in cognitive and physical effort costs were positively correlated, suggesting that these are perceived and processed in common. We used canonical correlation analysis to probe the relationship of task measures to self-reported affect and motivation, and found correlations of cognitive effort with anxiety, cognitive function, behavioral activation, and self-efficacy, but no similar correlations with physical effort.

Toward a Rational and Mechanistic Account of Mental Effort.

In spite of its familiar phenomenology, the mechanistic basis for mental effort remains poorly understood. Although most researchers agree that mental effort is aversive and stems from limitations in our capacity to exercise cognitive control, it is unclear what gives rise to those limitations and why they result in an experience of control as costly. The presence of these control costs also raises further questions regarding how best to allocate mental effort to minimize those costs and maximize the attendant benefits. This review explores recent advances in computational modeling and empirical research aimed at addressing these questions at the level of psychological process and neural mechanism, examining both the limitations to mental effort exertion and how we manage those limited cognitive resources. We conclude by identifying remaining challenges for theoretical accounts of mental effort as well as possible applications of the available findings to understanding the causes of and potential solutions for apparent failures to exert the mental effort required of us.

Multimodal evidence for cerebellar influence on cortical development in autism: structural growth amidst functional disruption.

Despite perinatal damage to the cerebellum being one of the highest risk factors for later being diagnosed with autism spectrum disorder (ASD), it is not yet clear how the cerebellum might influence the development of cerebral cortex and whether this co-developmental process is distinct between neurotypical and ASD children. Leveraging a large structural brain MRI dataset of neurotypical children and those diagnosed with ASD, we examined whether structural variation in cerebellar tissue across individuals was correlated with neocortical variation during development, including the thalamus as a coupling factor. We found that the thalamus plays a distinct role in moderating cerebro-cerebellar structural coordination in ASD. Notably, structural coupling between cerebellum, thalamus, and neocortex was strongest in younger childhood and waned by early adolescence, mirroring a previously undescribed trajectory of behavioral development between ASD and neurotypical children. Complementary functional connectivity analyses likewise revealed atypical connectivity between cerebellum and neocortex in ASD. This relationship was particularly prominent in a model of cerebellar structure predicting functional connectivity, where ASD and neurotypical children showed divergent patterns. Interestingly, these functional-structural relationships became more prominent with age, while structural effects were most prominent earlier in childhood, and showed significant lateralization. This pattern may suggest a developmental sequence where early uncoordinated structural growth amongst regions is followed by increasingly atypical functional synchronization. These findings provide multimodal evidence in the living brain for a cerebellar diaschisis model of autism, where both increased cerebellar-cerebral structural coupling and altered functional connectivity in cerebro-cerebellar pathways contribute to the ontogeny of this neurodevelopmental disorder.

Apoptosis and tissue thinning contribute to symmetric cell division in the developing mouse epidermis in a nonautonomous way.

Mitotic spindle orientation (SO) is a conserved mechanism that governs cell fate and tissue morphogenesis. In the developing epidermis, a balance between self-renewing symmetric divisions and differentiative asymmetric divisions is necessary for normal development. While the cellular machinery that executes SO is well characterized, the extrinsic cues that guide it are poorly understood. Here, we identified the basal cell adhesion molecule (BCAM), a ß1 integrin coreceptor, as a novel regulator of epidermal morphogenesis. In utero RNAi-mediated depletion of Bcam in the mouse embryo did not hinder ß1 integrin distribution or cell adhesion and polarity. However, Bcam depletion promoted apoptosis, thinning of the epidermis, and symmetric cell division, and the defects were reversed by concomitant overexpression of the apoptosis inhibitor Xiap. Moreover, in mosaic epidermis, depletion of Bcam or Xiap induced symmetric divisions in neighboring wild-type cells. These results identify apoptosis and epidermal architecture as extrinsic cues that guide SO in the developing epidermis.

Deep-Learning-Based Screening and Ancillary Testing for Thyroid Cytopathology.

Thyroid cancer is the most common malignant endocrine tumor. The key test to assess preoperative risk of malignancy is cytologic evaluation of fine-needle aspiration biopsies (FNABs). The evaluation findings can often be indeterminate, leading to unnecessary surgery for benign post-surgical diagnoses. We have developed a deep-learning algorithm to analyze thyroid FNAB whole-slide images (WSIs). We show, on the largest reported data set of thyroid FNAB WSIs, clinical-grade performance in the screening of determinate cases and indications for its use as an ancillary test to disambiguate indeterminate cases. The algorithm screened and definitively classified 45.1% (130/288) of the WSIs as either benign or malignant with risk of malignancy rates of 2.7% and 94.7%, respectively. It reduced the number of indeterminate cases (N = 108) by reclassifying 21.3% (N = 23) as benign with a resultant risk of malignancy rate of 1.8%. Similar results were reproduced using a data set of consecutive FNABs collected during an entire calendar year, achieving clinically acceptable margins of error for thyroid FNAB classification.

Hydroxychloroquine in recurrent pregnancy loss: data from a French prospective multicenter registry.

STUDY QUESTION: What are the outcomes of pregnancies exposed to hydroxychloroquine (HCQ) in women with a history of recurrent pregnancy loss (RPL), and what factors predict the course of these pregnancies beyond the first trimester? SUMMARY ANSWER: In our cohort of pregnancies in women with a history of RPL exposed to HCQ early in pregnancy, we found that the only factor determining the success of these pregnancies was the number of previous miscarriages. WHAT IS KNOWN ALREADY: Dysregulation of the maternal immune system plays a role in RPL. HCQ, with its dual immunomodulating and vascular protective effects, is a potential treatment for unexplained RPL. STUDY DESIGN, SIZE, DURATION: The FALCO (Facteurs de récidive précoce des fausses couches) registry is an ongoing French multicenter infertility registry established in 2017 that includes women (aged from 18 to 49 years) with a history of spontaneous RPL (at least three early miscarriages (≤12 weeks of gestation (WG)) recruited from several university hospitals. PARTICIPANTS/MATERIALS, SETTING, METHODS: Spontaneous pregnancies enrolled in the FALCO registry with an exposure to HCQ (before conception or at the start of pregnancy) were included. Pregnancies concomitantly exposed to tumor necrosis factor inhibitors, interleukin-1 and -2 inhibitors, intravenous immunoglobulin, and/or intravenous intralipid infusion, were excluded. Concomitant treatment with low-dose aspirin (LDA), low-molecular weight heparin (LMWH), progesterone, and/or prednisone was allowed. All patients underwent the recommended evaluations for investigating RPL. Those who became pregnant received obstetric care in accordance with French recommendations and were followed prospectively. The main endpoint was the occurrence of a pregnancy continuing beyond 12 WG, and the secondary endpoint was the occurrence of a live birth. MAIN RESULTS AND THE ROLE OF CHANCE: One hundred pregnancies with HCQ exposure in 74 women were assessed. The mean age of the women was 34.2 years, and the median number of previous miscarriages was 5. Concomitant exposure was reported in 78 (78%) pregnancies for prednisone, 56 (56%) pregnancies for LDA, and 41 (41%) pregnancies for LMWH. Sixty-two (62%) pregnancies ended within 12 WG, the other 38 (38%) continuing beyond 12 WG. The risk of experiencing an additional early spontaneous miscarriage increased with the number of previous miscarriages, but not with age. The distributions of anomalies identified in RPL investigations and of exposure to other drugs were similar between pregnancies lasting ≤12 WG and those continuing beyond 12WG. The incidence of pregnancies progressing beyond 12 WG was not higher among pregnancies with at least one positive autoantibody (Ab) (i.e. antinuclear Ab titer ≥1:160, ≥1 positive conventional and/or non-conventional antiphospholipid Ab, and/or positive results for ≥1 antithyroid Ab) without diminished ovarian reserve (18/51, 35.3%) than among those without such autoantibody (18/45, 40.0%) (P = 0.63). Multivariate analysis showed that having ≤4 prior miscarriages was the only factor significantly predictive for achieving a pregnancy > 12 WG, after adjustment for age and duration of HCQ use prior to conception (adjusted odds ratio (OR) = 3.13 [1.31-7.83], P = 0.01). LIMITATIONS, REASONS FOR CAUTION: Our study has limitations, including the absence of a control group, incomplete data for the diagnostic procedure for RPL in some patients, and the unavailability of results from endometrial biopsies, as well as information about paternal age and behavioral factors. Consequently, not all potential confounding factors could be considered. WIDER IMPLICATIONS OF THE FINDINGS: Exposure to HCQ in early pregnancy for women with a history of RPL does not seem to prevent further miscarriages, suggesting limited impact on mechanisms related to the maternal immune system. STUDY FUNDING/COMPETING INTEREST(S): The research received no specific funding, and the authors declare no competing interests. TRIAL REGISTRATION NUMBER: clinicaltrial.gov NCT05557201.

Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology.

BACKGROUND AND AIMS: The American Society for Gastrointestinal Endoscopy (ASGE) AI Task Force along with experts in endoscopy, technology space, regulatory authorities, and other medical subspecialties initiated a consensus process that analyzed the current literature, highlighted potential areas, and outlined the necessary research in artificial intelligence (AI) to allow a clearer understanding of AI as it pertains to endoscopy currently. METHODS: A modified Delphi process was used to develop these consensus statements. RESULTS: Statement 1: Current advances in AI allow for the development of AI-based algorithms that can be applied to endoscopy to augment endoscopist performance in detection and characterization of endoscopic lesions. Statement 2: Computer vision-based algorithms provide opportunities to redefine quality metrics in endoscopy using AI, which can be standardized and can reduce subjectivity in reporting quality metrics. Natural language processing-based algorithms can help with the data abstraction needed for reporting current quality metrics in GI endoscopy effortlessly. Statement 3: AI technologies can support smart endoscopy suites, which may help optimize workflows in the endoscopy suite, including automated documentation. Statement 4: Using AI and machine learning helps in predictive modeling, diagnosis, and prognostication. High-quality data with multidimensionality are needed for risk prediction, prognostication of specific clinical conditions, and their outcomes when using machine learning methods. Statement 5: Big data and cloud-based tools can help advance clinical research in gastroenterology. Multimodal data are key to understanding the maximal extent of the disease state and unlocking treatment options. Statement 6: Understanding how to evaluate AI algorithms in the gastroenterology literature and clinical trials is important for gastroenterologists, trainees, and researchers, and hence education efforts by GI societies are needed. Statement 7: Several challenges regarding integrating AI solutions into the clinical practice of endoscopy exist, including understanding the role of human-AI interaction. Transparency, interpretability, and explainability of AI algorithms play a key role in their clinical adoption in GI endoscopy. Developing appropriate AI governance, data procurement, and tools needed for the AI lifecycle are critical for the successful implementation of AI into clinical practice. Statement 8: For payment of AI in endoscopy, a thorough evaluation of the potential value proposition for AI systems may help guide purchasing decisions in endoscopy. Reliable cost-effectiveness studies to guide reimbursement are needed. Statement 9: Relevant clinical outcomes and performance metrics for AI in gastroenterology are currently not well defined. To improve the quality and interpretability of research in the field, steps need to be taken to define these evidence standards. Statement 10: A balanced view of AI technologies and active collaboration between the medical technology industry, computer scientists, gastroenterologists, and researchers are critical for the meaningful advancement of AI in gastroenterology. CONCLUSIONS: The consensus process led by the ASGE AI Task Force and experts from various disciplines has shed light on the potential of AI in endoscopy and gastroenterology. AI-based algorithms have shown promise in augmenting endoscopist performance, redefining quality metrics, optimizing workflows, and aiding in predictive modeling and diagnosis. However, challenges remain in evaluating AI algorithms, ensuring transparency and interpretability, addressing governance and data procurement, determining payment models, defining relevant clinical outcomes, and fostering collaboration between stakeholders. Addressing these challenges while maintaining a balanced perspective is crucial for the meaningful advancement of AI in gastroenterology.

Development of American Society for Gastrointestinal Endoscopy standards for training in advanced endoscopy within dedicated advanced endoscopy fellowship programs.

BACKGROUND AND AIMS: Training in interventional endoscopy is offered by nonaccredited advanced endoscopy fellowship programs (AEFPs). The number of these programs has increased dramatically with a concurrent increase in the breadth and complexity of interventional endoscopy procedures. Accreditation is governed by competency-based education, yet what constitutes a "high-quality" nonaccredited AEFP has not been defined. Using an evidence-based consensus process, we aimed to establish standards for AEFPs. METHODS: The RAND UCLA appropriateness method, a well-described modified Delphi process to develop quality indicators, was used. A task force established by the American Society for Gastrointestinal Endoscopy drafted potential quality indicators (structure, process, and outcome) in 6 categories: activity preceding training; structure of AEFPs; training in ERCP, EUS, and EMR; and luminal stent placement. Three rounds of iterative feedback from 20 experts were conducted. Round 0 involved discussion of project details. In round 1, experts independently ranked proposed quality indicators on a 9-point interval scale ranging from highly inappropriate (1) to highly appropriate (9). Next, proposed quality indicators were discussed and reworded in a group meeting followed by round 2, in which experts independently reranked proposed quality indicators and provided benchmarks (when applicable). The median score for each quality indicator was calculated. Mean absolute deviation from the median was calculated, and appropriateness of potential quality indicators was assessed using the BIOMED concerted action on appropriateness definition, P value method, and interpercentile range adjusted for symmetry definition. A quality indicator was deemed appropriate if the median score was ≥7 and met criteria for appropriateness using all 3 defined statistical methods. RESULTS: Of 89 proposed quality indicators, 37 statements met criteria as appropriate for a quality indicator (activity preceding training, 2; structure of AEFPs, 10; training in ERCP, 7; training in EUS, 8; training in EMR, 7; luminal stent placement, 3). Minimum thresholds were defined for 19 relevant quality indicators for number of trainers, procedures during fellowship, and procedures before assessment of competence. Among the final appropriate quality indicators were that all trainees should undergo qualitative and quantitative competence assessments using validated tools at least quarterly with documented feedback throughout the training period and that trainees should track outcomes and relevant quality metrics for specific procedures. CONCLUSIONS: This consensus process using validated methodology established standards for an AEFP in an effort to ensure adequate training in the most commonly taught interventional endoscopic procedures (ERCP, EUS, EMR, and luminal stent placement) during fellowship. An important component of an AEFP is the use of competency-based assessments that are compliant with the Accreditation Council for Graduate Medical Education's Next Accreditation System, with the goal of ensuring that trainees achieve specific milestones in their progression to achieving cognitive and technical competency.

Photophysiological cycles in Arctic krill are entrained by weak midday twilight during the Polar Night.

Light plays a fundamental role in the ecology of organisms in nearly all habitats on Earth and is central for processes such as vision and the entrainment of the circadian clock. The poles represent extreme light regimes with an annual light cycle including periods of Midnight Sun and Polar Night. The Arctic Ocean extends to the North Pole, and marine light extremes reach their maximum extent in this habitat. During the Polar Night, traditional definitions of day and night and seasonal photoperiod become irrelevant since there are only "twilight" periods defined by the sun's elevation below the horizon at midday; we term this "midday twilight." Here, we characterize light across a latitudinal gradient (76.5° N to 81° N) during Polar Night in January. Our light measurements demonstrate that the classical solar diel light cycle dominant at lower latitudes is modulated during Arctic Polar Night by lunar and auroral components. We therefore question whether this particular ambient light environment is relevant to behavioral and visual processes. We reveal from acoustic field observations that the zooplankton community is undergoing diel vertical migration (DVM) behavior. Furthermore, using electroretinogram (ERG) recording under constant darkness, we show that the main migratory species, Arctic krill (Thysanoessa inermis) show endogenous increases in visual sensitivity during the subjective night. This change in sensitivity is comparable to that under exogenous dim light acclimations, although differences in speed of vision suggest separate mechanisms. We conclude that the extremely weak midday twilight experienced by krill at high latitudes during the darkest parts of the year has physiological and ecological relevance.

Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning.

The ability to acquire abstract knowledge is a hallmark of human intelligence and is believed by many to be one of the core differences between humans and neural network models. Agents can be endowed with an inductive bias towards abstraction through meta-learning, where they are trained on a distribution of tasks that share some abstract structure that can be learned and applied. However, because neural networks are hard to interpret, it can be difficult to tell whether agents have learned the underlying abstraction, or alternatively statistical patterns that are characteristic of that abstraction. In this work, we compare the performance of humans and agents in a meta-reinforcement learning paradigm in which tasks are generated from abstract rules. We define a novel methodology for building "task metamers" that closely match the statistics of the abstract tasks but use a different underlying generative process, and evaluate performance on both abstract and metamer tasks. We find that humans perform better at abstract tasks than metamer tasks whereas common neural network architectures typically perform worse on the abstract tasks than the matched metamers. This work provides a foundation for characterizing differences between humans and machine learning that can be used in future work towards developing machines with more human-like behavior.

Meta-analysis of soil and dust ingestion studies.

The ingestion of soil and dust by children and adults is a potential source of exposure to environmental contaminants. To advance beyond the simple averaging of estimates used in the U.S. EPA's Exposure Factors Handbook (EFH), we describe a novel meta-analysis of all available studies that provided soil or dust ingestion estimates for children or adults conducted in the United States and Canada. Using meta-analytic techniques, we estimate the mean total soil plus dust ingestion rates and confidence intervals (CIs) for eleven age groups (0 - <1 month (m), 1 - <3 m, 3 - <6 m, 6 - <12 m, 1 - <2 years (y), 2 - <3 y, 3 - <6 y, 6 - <11 y, 11 - <16 y, 16 - <21 y, and 21+ y). These age groups were selected for consistency with the EFH update to Chapter 5 and the U.S. EPA's Age Grouping Guidance. For each age group, we calculated best estimates for the three main types of ingestion studies: tracer studies based on the aluminum tracer, biokinetic studies, and activity pattern (modeling) studies, as well as overall estimates for all three study types combined. Our meta-analysis combined study estimates using the alternative statistical approaches of the fixed effect method (inverse variance method, "I-V") and two random effects methods, DerSimonian and Laird's method of moments ("DSL") and the restricted maximum likelihood method ("MIXED"). For each approach, the mean total soil plus dust ingestion rate estimates for each study type generally aligned well with the EFH, ranging from 36 to 68 mg/day for infants, 56-72 mg/day for young children, and 12-32 mg/day for adolescents and adults. When all three study types were combined, the upper bounds of the 95% CI were generally the lowest for the I-V method and the highest for the MIXED method. The estimates produced here can be used for stochastic risk assessments and provide a better estimate of soil and dust ingestion rates across age groups.