Environ Toxicol Chem 2019;38:423–435. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.Discerning potential effects of insecticides on honey bee colonies in field studies conducted under realistic conditions can be challenging because of concurrent interactions with other environmental conditions. Honey bee colony models can control exposures and other environmental factors, as well as assess links among pollen and nectar residues in the landscape, their influx into the colony, and the resulting exposures and effects on bees at different developmental stages. We extended the colony model BEEHAVE to represent exposure to the insecticide clothianidin via residues in pollen from treated cornfields set in real agricultural landscapes in the US Midwest. We assessed their potential risks to honey bee colonies over a 1‐yr cycle. Clothianidin effects on colony strength were only observed if unrealistically high residue levels in the pollen were simulated. The landscape composition significantly impacted the collection of pollen (residue exposure) from the cornfields, resulting in higher colony‐level effects in landscapes with lower proportions of semi‐natural land. The application of the extended BEEHAVE model with a pollen exposure‐effects module provides a case study for the application of a mechanistic honey bee colony model in pesticide risk assessment integrating the impact of a range of landscape compositions.  © 2018 SETACOverview of pollen exposure‐effects module added to BEEHAVE. Insecticides including neonicotinoids are applied to control insect pests in agricultural fields and other contexts. As a result of their toxicity to insects, concerns have been raised about potential impacts on honey bees  to fuel their foraging flights. Pollen is the primary source of protein, lipids, sterols, minerals, and most vitamins for bees Seeley . Young aAddressing exposure and effects relationships on honey bee colonies in field experiments across multiple crops and landscapes in varying geographical regions can be very costly and time consuming. Also, potential impacts from residues of pesticides in nectar and pollen or other routes of exposure to honey bee colonies may be confounded by additional environmental factors. Honey bee colony models can provide tools for colony‐level risk assessments in addition to field studies  pollen to honey bee colonies. The simulated residue levels were 0, 12.2, 39.9, 200, and 2800 ng clothianidin/g pollen. The intermedium level of 39.9 ng/g corresponds to the highest residue concentration of clothianidin measured in corn pollen, and resulted from test fields treated via soil application with clothianidin  in large‐scale fields located in agricultural landscapes of the US Midwest . We added an exposure‐effects module to BEEHAVE that makes it possible to represent fields providing exposed pollen in realistic spatial and temporal landscape contexts. Effects to broods and adult bees in the hive are modeled temporally explicitly and are applied using dose–response relationships for larvae and adult bees derived from clothianidin laboratory toxicity studies. The goal of the application of BEEHAVE with the pollen exposure‐effects module was to assess potential effects of different residue levels in pollen from a central cornfield to colonies over the course of the foraging season into the spring of the following year. In addition, we evaluated the role of landscape composition on pollen collected (residue exposure) from the central cornfield and the resulting effects on colonies in realistic agricultural landscapes of Wisconsin, Minnesota, and South Dakota.In the present case study, we applied BEEHAVE to assess potential effects of different clothianidin residue levels in corn  in the pollen in a given patch and on a given day. When simulated foragers collect pollen, the pollen load brought back to the colony carries the residue level as defined for the patch foraged on. Given that the application method of clothianidin in corn is via soil application and/or seed treatment only, contact exposure of foragers collecting pollen was considered negligible and effects were assumed to exclusively occur because of consumption of pollen containing pesticide residues.Honey bees store pollen in designated cells in the hive. If more pollen is collected than consumed, it is processed into bee bread, and full bee bread cells are capped for later consumption. BEEHAVE does not simulate a temporal  pattern of pollen storage in the colony but assumes homogeneous pollen storage by total weight of pollen present in the colony. Pollen containing pesticide residues would be mixed (diluted) with the complete simulated pollen stores present in the colony. In the conceptual honey bee colony model for pesticide risk assessment proposed by the European Food Safety Authority (2016), it is emphasized that the temporal and spatial storage patterns of pollen in the colony result in variability in residue levels in stored pollen (or bee bread). Pollen stored in some cells could contain high residue levels, whereas other cells may not contain any residues—potentially resulting in different effects on consumers (larvae and adult bees) from average residue levels across the whole pollen stores present in the colony . Pollen is consumed if it is 1 d old or older . Bees in the colony are simulated to consume 1‐d‐old pollen first. Bees shift to ingesting 2‐d‐old pollen if no 1‐d‐old pollen is available, and work their way through the pollen store age cohorts according to availability. The oldest pollen is consumed last. The preference of bees for the consumption of fresh pollen over older pollen originated from the findings of Anderson et al.  and CarrBees in BEEHAVE are denoted as age cohorts from egg stage through the age of first foraging. In the adapted model, each larval age cohort keeps track of the amount of pesticide residue (in nanograms of clothianidin) consumed each day by a larva throughout its development (6 d). On the day of pupation, the cumulative amount of pesticide consumed by a larva in the cohort is applied to a dose–response function for survival. The number of larva entering pupal stage in the age cohort is reduced according to the dose–response relationship.Adult bee cohorts also store the amount of pesticide ingested on each day of their lives starting on the day of emergence from the pupal stage. At the end of every simulated day, the cumulative amount of pesticide consumed in the previous 2 d is applied to a dose–response function for acute effects on adults; and the cumulative amount of pesticide consumed in the previous 10 d is applied to a dose–response function for chronic effects on adults. The number of adults in each age cohort is reduced accordingly. Dose responses in survival are applied to both worker and drone larva and adult cohorts. Sublethal effects are not simulated in the present study.In BEEHAVE, daily pollen consumption rates assumed for larvae and adult bees show a considerable discrepancy with the daily pollen consumption rates assumed by the US Environmental Protection Agency  for loweDose–response functions were derived from data available from 3 laboratory toxicity studies conducted to assess toxic effects of clothianidin to honey bees following standardized guidelines for chronic larval, and acute and chronic adult studies  to determine the potential exposure to pollinators of the soil‐applied clothianidin product Ampex insecticide. The objective of the Experimental Use Permit was to quantify residues of clothianidin and its metabolites in pollen collected from corn plants after an in‐furrow application to untreated seeds and an in‐furrow application to clothianidin‐treated seeds in 2016 and 2017 . We retrieved data on land cover for 2016 from the Cropland Data Layer , even if they were adjacent to more pixels with corn land cover. The area of each patch was calculated as the sum of the pixels, and the distance to the colony  was measured from the centroid of the patch. Land covers with very low area across all sites (<1 ha at <3 of the 13 sites) and pixels classified as barren, developed, or open water in CDL were not represented in BEEHAVE landscape resource inputs. Crops not providing bee resources according to the classification by the US Department of Agriculture (2). For more information on land covers excluded from BEEHAVE input, refer to Supplemental Data, Table S2.Cropland Data Layer information gives the land cover in every 30 × 30 miculture  were excFor the remaining land covers, nectar and pollen availabilities per meter squared were estimated across the year. For crops, nectar and pollen production per flower were derived from the literature along with nectar sugar concentration, flowering period of the crop, and the flower density, utilizing an approach similar to that of Becher et al. . The necIn semi‐natural land covers, various plant species may be flowering at different times of the year in varying densities. Consequently, bee resource availability cannot be directly derived from nectar and pollen production of single flowers, as it is conducted for crops. Instead, we assigned categories of resource availability to the semi‐natural land covers according to qualitative data from ground surveys of plant species present and their flowering times, and assumed uniformity across each month and land cover. Semi‐natural land covers surrounding the simulated sites included herbaceous wetland, woody wetland, deciduous forest (combined with mixed forest), evergreen forest, shrubland, hay , and pasture . The assignment of resource category and the resource availability assumed for each category are discussed in Supplemental Data, Section 3.3.Weather data were retrieved from the closest weather station for each of the 13 locations in the study for 1 January through 31 December 2016 . Residue levels were assumed constant across the central test cornfield and flowering period. In Table For each combination of scenario, location, and residue level, we conducted 20 repetitions with different random number seeds . Number of adult bees, eggs, larvae and pupae present in the hive, and honey (kilograms) and pollen (grams) stores were collected throughout the simulated period corresponding to 1 January of year 1 through 24 April of year 2. Note that landscape resource and weather inputs from 2016 were used for both simulated years. Overwintering deaths of colonies were not simulated , in contrast to default settings in BEEHAVE where less than 4000 bees present in the colony on 31 December results in colony death. Without the colony size threshold for overwintering, quantitative comparisons of colony size measures in April were possible. With the threshold, the stress scenario would have resulted in high overwinter losses of simulated colonies in control simulations.Colony dynamics were compared between the 2 scenarios applied (baseline and stress) among the simulated residue levels in pollen from the test cornfield and across the 13 sites. Averages and ranges from the sets of 20 repetitions were graphed over time for adult bee and brood numbers, and honey and pollen stores.Of the measures available from BEEHAVE simulations, we chose the number of adult worker bees on 2 dates, 21 October (year 1) and 1 April (year 2), for quantitative analysis of colony‐level effects. Colonies cease foraging and brood‐raising in the fall as temperatures and resource availability decline. Adult bee numbers present in the hive at that time are a measure of colony strength before overwintering. In early spring, adult bee numbers are an indicator of colony growth after onset of foraging and brood‐raising in the new season. In addition, adult worker bees exhibit a higher sensitivity to clothianidin than larvae in toxicity studies . The adult bee counts on the 2 dates for the noncontrol simulations were each divided by the adult bee counts from the control simulations with corresponding scenario, site, and random seed. This percentage of adult bees in exposed versus control simulations was used as the response metric reflective of colony‐level effect.As an indicator of in‐hive exposure to clothianidin, the amount of pollen collected from the central test cornfield was recorded. Pollen from the central test cornfield was only available for collection during corn tasseling (flowering), simulated between 22 July through 4 August and corresponding to days 203 through 216 in the landscape resource input file to BEEHAVE. For each simulation run, the percentage of pollen collected from the central test cornfield relative to all pollen collected during the same time period was calculated.Pollen collection from test cornfield was graphed against colony‐level effects.Landscape compositions surrounding the 13 simulated colonies were quantified to explain variability in results from one site to the next. Land covers represented in the landscape resource input file as providing bee resources were grouped into 3 categories: alfalfa/buckwheat, other bee‐attractive crops, and semi‐natural land covers. Alfalfa and buckwheat are classified as highly attractive to honey bees with respect to both nectar and pollen, and were separated from other bee crops  characterized as less attractive to honey bees  to avoid interactions of residue effects on foraging. Percentages of land cover categories  present surrounding simulated colonies were graphed against percentages of pollen collected from test cornfields in control simulations.Linear mixed‐effects regression models statistically tested these relationships while accounting for replicates within sites by setting site as the random effect variable  when exposure via collection of pollen from the test cornfield began. At that time, the 2 highest residue levels became distinct from the controls. For the most extreme residue level simulated (2800 ng clothianidin/g pollen), the sharpest drop in adult bee numbers was observed. Adult bee numbers remained lower than in controls for the duration of the modeled period. The total brood numbers were also suppressed, and did not grow at the same rate as in controls during the spring after exposure (simulated year 2). Honey stores reached a lower maximum than in control, and less honey and pollen were consumed over time . For the simulated residue level of 200 ng clothianidin/g pollen, a decrease in adult bee numbers was also observed, but colonies recovered before the end of the foraging season (November). When a realistic maximum residue level of 39.9 ng clothianidin/g pollen  was simulated, adult bee numbers showed a small decrease compared with controls during August in the baseline scenario. For the residue levels of 19 and 12.2 ng clothianidin/g pollen , no differences in colony dynamics compared with controls were found. Similar dynamics with varying magnitudes were observed in simulations of the other 12 sites .Percentages of adult bees on 21 October (year 1) relative to control simulations were used as a measure of colony‐level effects. Across all sites, simulated control colonies had on average 10 732 adult bees in the baseline scenario , and 5598 in the stress scenario . Simulations with a residue level of 2800 ng clothianidin/g pollen from test cornfields resulted in the greatest decrease in adult bee numbers compared with the control runs . To examine this variability among simulations, the colony‐level effects on 21 October were graphed against the percentage of pollen collected during corn tasseling. In Figure Colony‐level effects from the 2 unrealistically high corn pollen residue levels simulated varied considerably among sites Figure . Simulatp = 0.00045 other crop; p = 0.00074 semi‐natural), and approximately 1.8% more pollen collected from the test cornfield on average in the stress scenario . The percentage of alfalfa/buckwheat in a landscape was insignificant (p = 0.83), as visible in its flat slopes . For the percentage area of semi‐natural land cover, the opposite was found: colonies collected less pollen from the test cornfields in sites with more semi‐natural land. Observed tendencies were stronger in the baseline scenario than in the stress scenario. The trends were quantified by applying linear mixed‐effects models Table . An incrMechanistic effects models are increasingly recognized as valuable tools to assess risks of pesticides to nontarget organisms and communities because they can combine information on the biology of the modeled system with exposure and effects, and judge risks on the level of organization of interest  or in the following spring (early April) were observed if simulated residue levels in pollen from the central cornfield were 39.9 ng clothianidin/g pollen or lower. The tested residue level of 39.9 ng clothianidin/g pollen was found to be the maximum residue level measured in an unpublished residue study conducted by Valent U.S.A. with corn treated with the soil‐applied clothianidin product Ampex insecticide . In a recent preliminary risk assessment, the following maximum concentrations of clothianidin in corn pollen were measured: 27.9 ng clothianidin/g pollen from soil‐treated corn , and 23.8 ng clothianidin/g pollen from seed‐treated corn  does not capture all variability in resource availability surrounding a hive. For instance, floral resources in roadsides and utility rights‐of‐way have been identified as potentially beneficial for pollinators  and results within the colony  causing reduced foraging efficiency or queen productivity. In the present approach, we simulate exposure via residues in pollen from a single, treated field in a realistic landscape context. Effects occur as the result of consumption of pollen, whereby bee stage‐specific consumption rates and dose responses are measured.Given that clothianidin is only applied in corn via soil application or seed treatment—and that corn only produces pollen—in the present case study the pollen exposure‐effects module used in BEEHAVE does not address exposures through nectar or other routes such as direct spray. The simulation results presented assume a single, treated field as the closest resource patch to the colony. However, because of the patch‐ and day‐specific representation of bee resources in the landscape, multiple exposures from various sources  at different times of the year could be simulated with the extended version of BEEHAVE. For the present case study of corn treated with clothianidin via soil application and/or treated seeds, the extended model gave an estimate of colony‐level risk, taking into account realistic landscape‐level and in‐hive exposures and the impacts on colony dynamics over time. Sizes of simulated colonies before and after the overwintering period  were compared with control colonies, capturing long‐term, colony‐level effects of clothianidin bee exposure during corn flowering between late July and early August.Baseline and stress scenarios of conditions encountered by the colonies were simulated. Effects of pesticides could potentially interact with other stressors affecting colonies, leading to the suggestion that stressed colonies would provide a more conservative setting for pesticide risk assessments (Thorbek et al. In the present study, we did not consider potential sublethal effects from exposure to the neonicotinoid. In laboratory studies, effects of neonicotinoids on development time, proboscis extension reflex, locomotor activity, and memory in bees were observed, and orientation and activity of foragers may be affected. Concentrations causing sublethal effects fall into a range comparable with lethal effects (Blacquière et al. Honey bee colony models have been identified as tools that could potentially be useful in pesticide risk assessments (European Food Safety Authority 2016; Sponsler and Johnson The presented pollen exposure‐effects module shows that the extension of BEEHAVE to include detailed exposure and effects assumptions makes the model a potentially useful mechanistic tool applicable in pesticide risk assessment. Additional exposure routes including nectar, water, and direct exposure of foragers, as well as sublethal effects, would need to be considered. Calibration and validation of the model with data from honey bee colony field research would increase the reliability in applications.The Supplemental Data are available on the Wiley Online Library at DOI: 10.1002/etc.4314.This article includes online‐only Supplemental Data.Supporting Data S1.Click here for additional data file.Supporting Data S2.Click here for additional data file.


Interpersonal discrimination experience has been associated with adverse birth outcomes. Limited research has evaluated this relationship within multicultural contexts outside the United States where the nature and salience of discrimination experiences may differ. Such research is important in order to help identify protective and risk factors that may mediate the relationship between discrimination experience and adverse birth outcomes.N = 1653).Evaluated the relationship between perceived discrimination, as measured in pregnancy, with birth weight and gestation length among Māori, Pacific, and Asian women from Aotearoa New Zealand  and in acquiring housing (β = − 146 g) were associated with lower birth weight when compared to Māori women not experiencing these types of discrimination, while an ethnically motivated physical attack (β = − 1.06 week), and unfair treatment in the workplace (β = − 0.95 week), in the criminal justice system (β = − 0.55 week), or in banking (β = − 0.73 week) were associated with significantly shorter gestation.Despite a high prevalence of discrimination experience among women from all ethnic groups, discrimination experience was a strong predictor of lower birth weight and shorter gestation length among indigenous Māori women only. Additional research is needed to better understand the risk and protective factors that may moderate the relationship between discrimination experience and adverse birth outcomes among women from different ethnic groups. Aotearoa New Zealand, like many other developed countries, has substantial inequities in health, with lower rates of morbidity and mortality among white New Zealanders , compared particularly to those of indigenous (Māori) ethnicity , 2. One In addition to experiences of discrimination shaping individual health, there is increasing evidence that experiencing discrimination in prior generations can impact biology and health in subsequent generations –23. For Maternal experiences of discrimination may influence fetal development and timing of parturition through impacts on stress physiology functioning. For example, we have previously reported that the stress hormone cortisol is higher in pregnant women reporting discrimination experience in Aotearoa New Zealand . MaternaGiven this background, the purpose of this paper is to understand whether maternal experience of ethnic discrimination predicts birth outcomes among a large and ethnically diverse cohort of women in Aotearoa New Zealand, where measures were collected longitudinally – both before and after birth. The results of this analysis are important for understanding whether the previously documented relationship between interpersonal discrimination experience and adverse birth outcomes may differ based on cultural context of those experiences.n = 6822) and the resulting main cohort of their 6853 children are generally comparable to New Zealand national birth statistics in relation to maternal age, ethnicity, parity and indicators of socioeconomic position [Data for this paper come from the Growing Up in New Zealand (GUINZ) longitudinal cohort study. Using multiple strategies, pregnant women were invited to participate in GUINZ if they had an estimated birth date between 25 April 2009 and 25 March 2010, and were living within a geographic area defined by the Auckland, Counties-Manukau, or Waikato District Health Board regions in the North Island of Aotearoa New Zealand . The recposition . The samIn the antenatal questionnaire .In the antenatal questionnaire, women were asked “which ethnic group or groups do you belong to?” Those women that identified more than one ethnic group  were the2), yearly household income ; 2 = 20,000–29,999NZD; 3 = 30,000–49,999NZD; 4 = 50,000–69,999NZD; 5 = 70,000–99,999NZD; 6 = 100,000–149,999NZD; 7 ≥ 150,000NZD), maternal education , mother’s relationship status in pregnancy (with or without partner), and smoking in pregnancy (yes/no) were assessed during the antenatal questionnaire and were included as covariates in our multivariate regression models. Offspring sex  was collected at the 6 week questionnaire and was also included as a covariate in multivariate models. Women with incomplete data for any covariates were excluded from the analysis, resulting in a final sample size of 1653.Maternal age in pregnancy (years), maternal body mass index (BMI) (kilograms/meterWe first performed a univariate analysis to describe sample characteristics, both within the entire sample and stratified by ethnicity. We next evaluated bivariate associations between all study variables by calculating Pearson correlation coefficients. We then used multivariate regression to evaluate the relationship between each of the discrimination variables and birth weight and gestation length, respectively, while adjusting for covariates. Multivariate models were run separately for each of the three ethnic groups.Summary statistics are provided in Table Bivariate analyses of the entire sample Table  demonstrWomen who had more education and higher income were significantly more likely to report having experienced a verbal attack, and higher education was associated with being significantly more likely to report any unfair treatment. Physical attack in pregnancy was associated with significantly shorter gestation length in the entire sample.Table The relationships between ethnic discrimination measures and gestation length after adjusting for covariates are presented in Table In this study we aimed to understand the association between maternal experience of ethnic discrimination and birth outcomes among a large and ethnically diverse cohort of women and their children in Aotearoa New Zealand. We find that a very high prevalence of women reported experiencing discrimination. Women with higher education and income were more likely to report having experienced verbal attacks. While there was an overall association between physical attack experience and shorter gestation weight, multivariate analyses stratified by ethnicity demonstrated that lower birth weight and shorter gestation length were associated with discrimination experience only among Māori women. Specifically, Māori women reporting discrimination in response to unfair treatment at work and in acquiring housing were more likely to have lower birth weight babies than Māori women who did not report experiencing these types of ethnic discrimination. In addition, Māori women reporting a physical attack or experiencing unfair treatment because of their ethnicity in the workplace, in the criminal justice system, or in banking all had significantly shorter gestation length than Māori women who did not report these experiences. The effect sizes were also relatively large, with unfair treatment at work predicting a 243 g reduction in birth weight, and physical attacks in pregnancy being associated with a week shorter gestation length among Māori women. These effects were independent of maternal socioeconomic status and individual health behaviors that impact birth weight, such as smoking. Interestingly, this relationship did not exist for women within the broad Pacific ethnic group, and among Asian women those reporting discrimination because of their ethnicity in the housing market actually had higher birth weight infants.The finding of discrimination experience being associated with adverse birth outcomes among Māori women is consistent with prior research that has predominately been conducted among African Americans in the United States . ConsistThe inverse relationship between housing discrimination and birth weight among Asian women was unexpected. Since women of Asian ethnicity had the lowest birth weights overall, higher birth weight within this group may reflect a less healthy birth weight. In addition, many studies find a j-shaped relationship between discrimination experience and health outcomes, with individuals who do not report having experienced discrimination actually having worse outcomes than those reporting moderate amounts of discrimination , 44, 45.In addition to suggesting that the impacts of discrimination on birth outcomes may differ depending on ethnicity and cultural context, these results also suggest that discrimination may impact birth outcomes through pathways beyond the commonly described impacts on stress physiology. For example, increased birth weight associated with discrimination experience could reflect differences in diet or physical activity levels in pregnancy. These results highlight the need to evaluate the relationship between discrimination and birth outcomes in diverse cohorts in order to understand both how the context of discrimination experience affects internalization of these exposures, as well as the different physiological and behavioral pathways that mediate these effects.Our analysis adjusted for several confounders, including smoking in pregnancy. Smoking is strongly associated with a reduction in fetal growth . SmokingDespite the strengths of this study, which includes a large sample size and longitudinal study design, there are several limitations to consider. While the sample is ethnically representative of the New Zealand population, there is nevertheless a potential for bias with respect to women for whom all data are available for analysis. In particular, a large number of women were missing information for pre-pregnancy weight, and therefore were excluded from the analysis due to the inability to adjust for maternal size. Another potential limitation of this study is that there were no follow up questions that asked about how women perceived their discrimination experiences. While many women were able to describe and recognize having had a discriminatory experience, it would be informative to know their affective responses to such experiences, such as whether or not it elicited anger or made them feel upset. Differences in affective responses could affect internalization of these experiences . Future We found the expected relationship between discrimination experience and adverse birth outcomes, but only among Māori women. The results of this analysis suggest that ethnic discrimination can have important impacts on health for Māori, particularly since lower birth weight offspring and infants born with shorter gestational age are more likely to experience adverse health outcomes across the life course. Since this finding was not present for Pacific and Asian women it suggests that it is important to understand the cultural context within which discrimination experience is taking place, as there could be differences in additional risk or protective factors that moderate the relationship between discrimination and health. More research in multi-ethnic contexts is therefore needed to fully understand the pathways through which discrimination may impact health.Additional file 1. Antenatal Questionnaire; Description: Questionnaire instrument.


Helicobacter pylori gastritis and is rarely associated with other conditions including lymphoma. LG is of clinical importance since its recognition should prompt further clinical evaluation for other disorders.Lymphocytic gastritis (LG) is uncommon and presents histologically with a nonspecific inflammatory pattern. It is most often associated with celiac disease and  Helicobacter pylori infection, and rarely with other conditions including lymphoma.Lymphocytic gastritis (LG) is associated with celiac disease and A 50‐year‐old female presented with a 2‐week history of epigastric pain, nausea, vomiting, and weight loss. An abdominal CT scan and endoscopy were unremarkable. A gastric biopsy was obtained.The biopsy revealed a moderately dense lymphocytic infiltrate involving the lamina propria. In addition, the surface epithelial cells and gastric pit demonstrated markedly increased intraepithelial lymphocytes (IELs) with >25 IELs/100 epithelial cells. The IELs were predominantly small lymphocytes, including many with a halo appearance . Antibiotic therapy for KC: served as the primary author and is responsible for this literature review and construction of the manuscript. WNR: served as the hematopathologist on the case and was responsible for the histopathological work‐up and final diagnosis as well as senior author managing the construction and edits of the manuscript and guiding the primary author through the submission process.


Numerous frameworks for supporting, evaluating and reporting patient and public involvement in research exist. The literature is diverse and theoretically heterogeneous.To identify and synthesize published frameworks, consider whether and how these have been used, and apply design principles to improve usability.Keyword search of six databases; hand search of eight journals; ancestry and snowball search; requests to experts.Published, systematic approaches (frameworks) designed to support, evaluate or report on patient or public involvement in health‐related research.Data were extracted on provenance; collaborators and sponsors; theoretical basis; lay input; intended user(s) and use(s); topics covered; examples of use; critiques; and updates. We used the Canadian Centre for Excellence on Partnerships with Patients and Public (CEPPP) evaluation tool and hermeneutic methodology to grade and synthesize the frameworks. In five co‐design workshops, we tested evidence‐based resources based on the review findings.Our final data set consisted of 65 frameworks, most of which scored highly on the CEPPP tool. They had different provenances, intended purposes, strengths and limitations. We grouped them into five categories: power‐focused; priority‐setting; study‐focused; report‐focused; and partnership‐focused. Frameworks were used mainly by the groups who developed them. The empirical component of our study generated a structured format and evidence‐based facilitator notes for a “build your own framework” co‐design workshop.The plethora of frameworks combined with evidence of limited transferability suggests that a single, off‐the‐shelf framework may be less useful than a menu of evidence‐based resources which stakeholders can use to co‐design their own frameworks. Other authors have summarized a diverse literature on this topic  perspectives represented by the above literature, it is clear that improving patient and public involvement in research is a high priority for research policymakers,As a multi‐stakeholder research collaboration based in one of the UK's leading medical and biotechnology research regions, we had a strong commitment to strengthening patient and public input to our research. When we began this study, the UK National Institute for Health Research had recently put out for consultation its draft benchmarks for patient involvement in research.An initial browsing search identified numerous potential frameworks in both academic and grey literature, many of which appeared to have been carefully researched and some formally validated and field tested. Different groups had produced different frameworks, drawing on different principles, applying different theories and prioritizing different potential use cases. It was clear that developing a new framework from scratch was almost certainly unnecessary, but that the existing literature could benefit from a taxonomy and improved accessibility.process of running workshops aimed at generating and adapting and operationalizing frameworks for involving patients and lay people in research.Accordingly, we set out to achieve three objectives. First, to identify, critically examine, summarize and synthesize existing tools, frameworks, benchmarks, guidelines and critical appraisal checklists for patient and lay involvement in research. Second, to determine which of the frameworks were actually used and why (and explain why others were not used). Third, to work with patient and lay groups and designers to adapt, simplify and annotate existing frameworks and improve their aesthetic appeal and usability. As the study unfolded (and for reasons explained in the results section below), this last aim evolved to incorporate a major focus on optimizing the 22.1Narrative systematic review, drawing on the principles of hermeneutic review,2.2Health Expectations, BMC Research Involvement and Engagement, International Journal of Consumer Studies, International Journal of Technology Assessment in Health Care, Health Research Policy and Systems, BMC Health Services Research, International Journal of Healthcare Quality Assurance and BMJ Open) from January 2008 to December 2018.We searched six databases  to end 2018 using the following concepts and key words , collated sources already known to the authors and put out requests to our professional networks . When we identified papers that met our inclusion criteria, we checked the references of those papers and also put the title into Google Scholar to subsequent citations of it . Largely for practical purposes, grey literature was limited to publications from national or international organizations .We included any published, systematic approach designed to inform, evaluate or report on patient and public involvement in health‐related research. There were no language restrictions. The main exclusion criteria were as follows: not a framework, not about research or lacking provenance . We excluded frameworks that were focused only on communication or engagement (defined as explaining research to the public) as opposed to 2.4We used an Excel spreadsheet to summarize key aspects of each study . For each framework, data were extracted on the rationale for its development; provenance (including funding/sponsorship); patient/public input; theoretical basis (if any); orientation ; fields and topics covered; format and accessibility; intended user(s) and purpose(s); examples of use; and critiques. Three reviewers  undertook data extraction; each study was looked at by two reviewers with disagreements resolved by discussion. We attempted to contact lead authors of all papers to ask whether and by whom the framework had been used since its publication.scientific rigour ;incorporation of patient/public perspective ;comprehensiveness ; andusability .Using data from these domains, we applied the Canadian Centre for Excellence on Partnerships with Patients and the Public (CEPPP) evaluation tool, which assesses four aspects of a tool or framework2.5Using the iterative hermeneutic methodology developed by Boell and Cecez‐Kecmanovic,As an example of our approach, our hand search turned up a paper by Staniszewska et alWe synthesized a preliminary set of resources based on the frameworks in our data set. To inform the practical workshops, rather than reproduce all the frameworks (since many covered similar ground), we worked with lay colleagues to select the “best‐in‐class” from different categories in our data set. In this process, we were guided by three questions: (a) did the framework score well using the CEPPP tool (see above)? (b) does it make sense to patients and lay people as well as researchers—and is it potentially usable by both? and (c) will it allow valid measurement and iterative improvement of patient and public involvement work by research teams?2.6We shared our preliminary set of 12 “best‐in‐class” resources in two preliminary 2‐hour development workshops attended by a total of 16 participants recruited from three local pre‐existing academic‐lay research partnerships . We adapted the interactive and participatory methodology described by previous authors.The workshop materials, suggested format, resources and facilitator notes produced in the two development workshops were refined through three further pilot workshops in contrasting clinical and research settings: a long‐established patient participation group for a specialist research group in blood disorders; a recently established lay partner group for a community‐based mental health research programme; and an academic‐lay‐industry partnership seeking to establish working principles and evaluation methods for lay participation in industry‐led clinical trials. Full details of these workshops will be presented in a separate paper.33.1The study flow chart is shown in Figure The included publications described toolkits, tools, frameworks, checklists, benchmarks or maps for informing, guiding, assessing or reporting on patient and/or public involvement in research. A total of 56 frameworks were written up in 55 academic papers.The data extraction and scoring spreadsheet for the 65 frameworks is available from the authors. Almost all frameworks in our sample scored moderately or very highly on the CEPPP tool for scientific rigour (our scoring acknowledged a wide range of study designs). Most frameworks had been developed using a systematic approach with substantial input from patients or lay people, though approaches used varied considerably. Some groups had used primary qualitative researchPower‐focused: designed to surface, explore and overcome researcher‐lay power imbalances;Priority‐setting: designed to involve patients and lay people in setting research priorities;Study‐focused: designed to maximize recruitment and retention to clinical trials , thereby improving the quality and efficiency of research and/or maximizing its societal impact;Report‐focused: designed to guide writing up and critical appraisal of research reports;Partnership‐focused: designed to assure transparency and public accountability in researcher‐lay collaborations.Four papers proposed a “framework of frameworks” taxonomy of approaches to patient and public involvement in research (see Discussion for details).In the first and last of these, the presumed unit of analysis was a partnership . In the middle three, the presumed unit of analysis was a research study . In Table The number of publications per year in our sample is shown in Figure 3.2Thirteen frameworks ; what could they potentially do ; and what did they feel —and a corresponding research context perspective—comprising research relationships, ways of doing research and research structures , an arms‐length government organization (and leading funder of patient involvement research) whose main goal is ensuring that comparative effectiveness studies address outcomes relevant to patients. One paper described a framework for extending such research with the principles of community‐based participatory research, with a view to building relationships with underserved communities.3.3Eight frameworks, from Canada,In 2003, Lomas et alThese six steps were refined and extended in a later synthesis by Viergever et al,The UK‐based James Lind Alliance developed a framework for topic‐focused priority‐setting partnerships oriented mainly to the design of new clinical trials in 2008 and updated in 2013  methods to set research priorities, including an early consultation phase to “enable patients to develop their own voice and agenda [and prepare] for broader collaboration with other stakeholder groups” (page 160).Whilst the James Lind Alliance drew on the principles of power‐sharing developed by Oliver et al,3.4Of 19 frameworks in this category from UK,, 14 wereMost studies in this category were funded by bodies that sponsor clinical trials and/or seek to ensure patient input to such trials. These include the UK National Institute for Health Research (NIHR) Research Design Service Figure ,51 PCORIAll publications in this category emphasized that, in the view of the authors, patient and lay input throughout a clinical trial would make the trial more relevant, more appealing to potential participants, more likely to reach its target recruitment, more likely to retain participants and more likely to generate and disseminate high‐quality research knowledge.ongoing relationship with lay partners . Some offered tools to work systematically through procedural and process aspects of patient and lay involvement .Whilst study‐focused frameworks differed in detail, common features included the need to: (a) assess and understand the local context and nature of the proposed study; (b) plan ahead and resource each step adequately; (c) go beyond tokenism ; (d) address inclusivity ; (e) address human aspects ; and (f) develop and nurture an One paper proposed a set of “ethical” questions to ask about user involvement in relation to a clinical trialTwo studies from UK had usedAnother paper proposed an economic model for estimating the financial value of patient involvement in the clinical development of oncology drugs.Two recently published study‐focused frameworks included an additional dimension of measuring the impact of such involvement.3.5Four frameworks, all from UK, offered a checklist for critically appraising a published study for the quality and comprehensiveness of patient and lay involvement. Three covered primary studies3.6Seventeen frameworks  was one of the first groups to propose some core principles underpinning research partnerships with patients and the public: transparency, balance, exclusion of conflicts of interest, and audit.Boote et alA number of academic‐lay partnerships have produced similar frameworks, typically as a result of hybrid funding from academic, service and patient organizations.The above themes featured prominently, for example, in a UK‐based consortium's “UK PPI Standards for public involvement in research” , published in March 2018.3.7The only dimension of the CEPPP tool on which a high proportion of frameworks scored poorly was usability . Power‐focused frameworks were rarely used directly, but they informed and underpinned subsequent work on more applied categories of framework.In only one example 3.8Following our two preliminary development workshops, the three co‐design workshops involved a total of 30 participants . Each workshop unfolded differently, with participants drawing on the resources in different ways. The workshop resources and facilitator notes .Finally, we have refined a provisional format and set of resources for an evidence‐based “develop your own framework” workshop to be run adaptively by researcher‐lay partnerships.Whilst the frameworks in our data set were developed in different ways and for diverse reasons and use cases, the similarities among them were as striking as their differences. Almost all authors warned about the dangers of tokenism and tick‐box approaches; encouraged efforts to extend the diversity and representativeness of patient and lay input; emphasized that democratic values and principles must be underpinned by leadership, good governance and attention to training and practicalities; and recommended ongoing evaluation to feed into organizational learning and quality improvement. The empirical component of our study illustrated that a common set of evidence‐based resources can, when used to support facilitated design, produce different kinds of framework to suit the needs of different groups.4.2Four previous “framework of frameworks” publications offered a taxonomy of published approaches to patient and lay involvement in health research, though each took a narrower focus than our own review. In an early non‐systematic review (written when only six of the frameworks in our sample had been published), Savory arranged previous literature broadly along two axes: focus of involvement  and purpose of participation .participants ;influence on knowledge ; andinfluence on process of implementation .influence on the The emerging literature on the use of practical workshops in knowledge creation helps explain why our focus on building one's own framework appeared to be more successful than inviting groups to use off‐the‐shelf frameworks. This literature includes reviews of approaches to co‐creation of knowledgeThe shift in our focus from identifying published frameworks to supporting local co‐design of frameworks reflects an emerging philosophical shift in the way knowledge is conceptualized: from a highly objective view of knowledge  and a more subjective view  to a hands‐on view of knowledge (known as performative and defined as something that is brought into being in and through human action).Ours is not the first study to grapple with the tension between an academic ideal and a local, pragmatic solution. Deborah Ghate recently described an attempt to co‐produce a parenting programme that was both “evidence‐based”  and “home‐grown” .4.3To our knowledge, this is the most comprehensive and systematic summary of patient and lay involvement frameworks yet published. The literature search was extensive and used multiple methods  to amass an extensive primary data set. Through detailed data extraction and theoretical analysis, we have produced a new taxonomy into which future studies can be classified—and which has the potential to be extended if other groups develop new approaches to exploring the field. This is also the first systematic review on this topic to have gone beyond an academic synthesis: we produced, and empirically tested, a set of resources intended for use in practical workshops, allowing different researcher‐lay partnerships to draw on them in different ways through evidence‐informed serious play.One limitation of this review is that few primary studies were based in low‐ or middle‐income settings. A reviewer of an earlier draft of this paper suggested that not all countries or settings have a strong culture of patient involvement in research, so frameworks or framework‐building activities that implicitly assume such a culture may have limited success.Another key limitation of this study is that the empirical component reported here was preliminary. We tested the practical resources on only three researcher‐lay partnerships, all of which were linked to the University of Oxford and did not represent the potential range of diversity of such partnerships. Whilst we believe we have demonstrated proof of concept for our “co‐design your own framework” approach, we invite other groups to explore their use of our workshop resources and facilitator guides in a wider range of target groups and settings. We have made these resources available free for download from the Health Expectations website to those using them in non‐profit initiatives.5This study has shown that numerous published frameworks for supporting and evaluating patient and public involvement in research already exist. They have different provenances, intended purposes, strengths and limitations. But being evidence‐based and theoretically informed is no guarantee that a framework will be used. A single, one‐size‐fits‐all framework may be less useful than a range of resources that can be adapted and combined in a locally generated co‐design activity.We suggest that those who seek to develop or strengthen the patient or lay involvement in their own research use a three‐step process. First, explore the published examples described in this paper and the Appendix None declared.This study is part of the “Partnerships for Health, Wealth and Innovation” research stream of the Oxford Biomedical Research Centre which received ethics clearance through the University of Oxford Central University Research Ethics Committee (R51801/RE001). Written consent was obtained from patient participants.TG (the manuscript's guarantor) affirms that the manuscript is an honest, accurate and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned  have been explained. Click here for additional data file. Click here for additional data file. Click here for additional data file.


CTO). We aimed to investigate this association in a large cohort of implantable cardioverter defibrillator patients with long‐term follow‐up.Previous studies report conflicting results about a higher incidence of ventricular arrhythmias in patients with a chronic total coronary occlusion . At baseline, 240 patients (33%) had a CTO, and the CTOs were present for at least 44 (2–127) months. The median follow‐up duration was 4 (2–6) years. On long‐term follow‐up, CTO patients had a higher crude appropriate device therapy rate  and a lower crude survival rate  compared with patients without a CTO. Corrected for baseline characteristics including left ventricular ejection fraction, the presence of a CTO was an independent predictor for appropriate device therapy.All consecutive patients from 1992 onwards who underwent implantable cardioverter defibrillator implantation for ischemic cardiomyopathy at the Leiden University Medical Center were evaluated. Coronary angiograms were reviewed for the presence of a CTO in implantable cardioverter defibrillator patients was associated with more appropriate device therapy and worse prognosis at long‐term follow‐up. Further investigation is warranted regarding a potential beneficial effect of CTO revascularization on the incidence of ventricular arrhythmias.The presence of a  In a large cohort of patients with an implantable cardioverter defibrillator for ischemic cardiomyopathy, the presence of a chronic total coronary occlusion is associated with higher mortality and more appropriate device therapy rates, and chronic total coronary occlusion revascularization may influence this association positively.When clinicians encounter a patient with a chronic total coronary occlusion, with or without an implantable cardioverter defibrillator, they should be aware of a potentially higher ventricular arrhythmia occurrence in these patients, and chronic total coronary occlusion revascularization and/or implantable cardioverter defibrillator therapy should be considered carefully for improving survival and patient burden.The presence of a chronic total coronary occlusion (CTO) has been associated with a worse prognosis compared with patients with multivessel disease (MVD) without a CTO or single‐vessel disease (SVD).One of the hypotheses is that a CTO has a malicious influence on cardiac electrical stability, which makes patients with a CTO more prone to ventricular arrhythmias (VA),The data, analytic methods, and study materials will not be made available to other researchers for purposes of reproducing the results or replicating the procedure.®; Leiden University Medical Center, Leiden, The Netherlands). Indications for the ICD implantations were at the treating physician's discretion according to international guidelines.All consecutive patients from the year 1992 onward who underwent ICD implantation for primary or secondary prevention at the Leiden University Medical Center and had known ischemic heart disease were evaluated. Patient baseline characteristics, ICD‐related and clinical follow‐up were prospectively collected in the departmental Cardiology Information System  0 flow and an assumed duration of ≥3 months . In case of the presence of a CTO, the location of the CTO was recorded in a database following a 16‐segment subdivision of the coronary artery tree.Additionally, the quality of collaterals to the CTO was assessed using the Rentrop grade system.All devices that were used were manufactured by Biotronik , Boston Scientific , Medtronic , or St. Jude Medical . A single‐chamber ICD, or a dual‐chamber ICD, or a Cardiac Resynchronization Therapy Defibrillator (CRT‐D) was implanted.Periodic follow‐up visits were performed every 3 to 6 months. During follow‐up visits, patients were clinically assessed, and devices were interrogated. During this device interrogation, stored episodes were analyzed and defibrillator interventions were registered. Device therapy was classified on the basis of intracardiac electrograms and was considered appropriate only when occurring in response to VT or ventricular fibrillation (VF). All other triggers for therapy were considered inappropriate.In the case of emigration or transmigration resulting in referral to centers far from the primary center, or when follow‐up visits were not performed for ≥12 months, follow‐up was considered incomplete. These patients were censored in the analysis at last known date of contact. In the case of heart transplantation or premature termination of ICD treatment, follow‐up was ended at the time of intervention. Patients who did not reach any end point remained at risk until the end of the study. Survival status was retrieved from regularly updated municipal civil registries. In all deceased patients, the cause of death was retrieved from hospital letters or follow‐up reports if present, and otherwise from the general practitioner.The end points of interest for this study were the occurrence of appropriate device therapy (as a substitute for VA occurrence) and all‐cause mortality, hypothesizing that in the CTO group these end points would occur more often. Appropriate device therapy was defined as shock or antitachycardia pacing for VF/VT. Therapy delivered for anything other than VT or VF was defined as inappropriate. Additionally, (patient and coronary) variables associated with the occurrence of appropriate device therapy and all‐cause mortality were identified. Furthermore, we investigated the impact of a CTO on end points in patients with an ICD for primary as compared with secondary prevention, the role of collateral vessels to the CTO, and the influence of SVD and MVD with or without a CTO on outcomes. At baseline, we calculated an adjusted MADITII  risk score for all patients. The previously published MADITII risk scoret test or nonparametric tests, respectively. Categorical variables are depicted as frequencies , and comparisons between groups were made with the Fisher exact test or χ2 test when applicable. All‐cause mortality event rates within groups are depicted with Kaplan–Meier curves, and were compared using the log‐rank test. Kaplan–Meier estimates for 10‐year follow‐up were derived from the analyses, and depicted as the estimate rates with SE. Cox proportional hazards regression was used to assess the predictive value of variables on outcomes, after visual verification of the proportionality assumption. Appropriate variables were included after backward stepwise selection, excluding variables with a P>0.10. For appropriate device therapy, the left ventricular ejection fraction (LVEF) was forced into the multivariate model since it is a known strong predictor for device therapy. Overall, a P value of <0.05 was considered statistically significant. All analyses were performed using SPSS .Continuous variables are depicted as mean (±SD) or median (interquartile range), and comparisons between groups were made using independent In total, the cohort consisted of 722 patients with an ICD for ischemic cardiomyopathy (ICM) for whom an angiography was available   years, the overall crude cumulative event rates in this ICD population were 30% for appropriate device therapy and 39% for all‐cause mortality. Both appropriate device therapy and all‐cause mortality occurred more frequently in the CTO group, compared with the non‐CTO group   and there was a trend for higher all‐cause mortality , mainly because of myocardial viability, inducible arrhythmias in the CTO territory, or severe CAD for which CABG was indicated. Patients with a revascularized CTO had similar appropriate device therapy rates compared with patients without a CTO n=447)  received more appropriate device therapy and (2) had a higher all‐cause mortality, compared with ICD patients with ICM but without a CTO; (3) corrected for several baseline characteristics . The presence of a CTO was an independent predictor for more appropriate device therapy in this specific patient population.Previous published studiesIn the COMMIT‐HF  substudy with patients with ischemic systolic heart failure n=675), the presence of a CTO (n=278) was associated with an increased 2‐year all‐cause mortality compared with patients without a CTO (n=397). Also, 1‐year cardiovascular mortality and 1‐year major adverse cardiovascular event rates were significantly higher in the group of patients with a CTO,75, the pThe cause of the high death rate in CTO patients, despite the presence of an ICD, remains unclear. In our cohort this does not appear to be driven by a higher occurrence of, for example, untreatable VAs in the patients with a CTO. It could be postulated that an ICD does decrease mortality from VAs, but that CTO patients have a higher mortality because of the presence of other comorbidities, such as diabetes mellitus. In addition, when looking at the MADITII risk score  in our population,The pathophysiology of VAs is important and accordingly, the cause of the CTO could be just as important. Di Marco et al have shown that the presence of a CTO in a previous infarcted area (infarct‐related artery [IRA]‐CTO) is associated with the occurrence of more VA  and more ICD therapy.Most CTOs are infarct‐related artery–CTOs,The influence of collateral vessels to a CTO has been investigated sparsely. One registry showed that the presence of well‐developed collaterals to a concomitant CTO in ST‐segment elevation myocardial infarction patients was associated with better long‐term survival.The presence of a CTO results in higher all‐cause mortality rates in patients with an ICD for ICM for both primary and secondary prevention. The presence of a CTO has, however, a less abundant effect on appropriate device therapy in secondary prevention patients in the long term. However, the relatively lower number of secondary prevention patients in our cohort n=191) could have played a role in this observed difference. On the Kaplan–Meier curve, at 2‐year follow‐up a clear divergence of the appropriate therapy rates in the secondary prevention patients with a CTO can be observed. This coincides with the observations made in the VACTO secondary study. In their population (n=425) of secondary prevention patients, the presence of a CTO was associated with, and was an independent predictor for, both decreased survival and more appropriate therapy.1 could hSince it has been established that patients with a CTO experience more VAs and have a lower life expectancy, one of the most significant questions is whether CTO revascularization can improve outcomes. In general registry populations of patients with a CTO, CTO revascularization seems to improve outcomes.In a systematic review and meta‐analysis of studies investigating the effect of CTO revascularization on ECG parameters, we found that directly after successful revascularization, several ECG parameters improved compared with before CTO revascularization.This study has several limitations that should be taken into account when interpreting the data. First, this study is a registry study, with all associated limitations. Importantly, because of the retrospective nature of this study, there is a lack of insight into reasons whether or not to revascularize the diagnosed CTOs. Also, in some of the patients the exact cause of death could no longer be determined, and since in The Netherlands it is not customary to read out the ICD postmortem, no information on arrhythmias premortem was available. Second, for some subanalyses the numbers are low, so these analyses should be considered purely as hypothesis generating.The current study shows that in a large cohort of patients with an ICD for ICM, the presence of a CTO is associated with more appropriate device therapy and worse survival at long‐term follow‐up, compared with patients without a CTO. Moreover, the presence of a CTO in patients with an ICD is an independent predictor for the occurrence of VAs leading to more appropriate device therapy. CTO revascularization might ameliorate this negative effect of a CTO on the myocardium.None.


The difficulty in studying nonbreeding birds means that little is known about them or their resource requirements, despite forming a large and significant component of a population. One way to assess food requirements is to examine changes in body mass, because it indicates the amount of food acquired. In terms of body mass changes, our expectation is that nonbreeders will either (a) be in poorer condition than the breeders which potentially explains why they do not breed or (b) remain at a stable higher mass as they are unconstrained by the physiological costs associated with rearing chicks. Here, we interrogate body mass datasets of breeding and nonbreeding birds of two penguin species to assess these predictions and determine whether differences in mass exist between these two groups throughout the breeding season. The first dataset is from a wild Adélie penguin population, where bird mass was recorded automatically and breeding status determined from a resighting program. A second population of captive gentoo penguins were weighed regularly each breeding season. We demonstrate that although there were times in each year when breeders were heavier than their nonbreeding counterparts for both populations, the mass changes showed qualitatively similar patterns throughout the breeding season irrespective of breeding status. Heavier breeders at times during the breeding season are not unexpected but the overall similar pattern of mass change irrespective of breeding status is in contrast to expectations. It appears that breeding status per se and the constraints that breeding places on birds are not the only driver of changes in mass throughout the breeding season and, although not explicitly studied here, the role of hormones in driving changes in appetite could be key to explain these results. These results present a significant step toward understanding food requirements of nonbreeders in avian populations. For many species of birds, nonbreeders include the younger members of the population which may take several years to return to their breeding colonies  to protect and provision their eggs or chicks . We do this for a wild population of Adélie penguins 2This study examines the change in penguin mass across multiple breeding seasons for marked individuals from a wild population of Adélie penguins at Béchervaise Island  off the Mac.Robertson Land coast of East Antarctica and a captive population of the closely related gentoo penguin living in an aquarium in Australia. Data used in this analysis for the Béchervaise Island population include breeding seasons between 1998/99 and 2002/03 and for the gentoo penguins between 2009/10 through until 2014/15. All procedures involving Adélie penguins were approved by the Australian Antarctic Division Animal Ethics Committee, while work on gentoo penguins was with approval of the Melbourne Aquarium Curator and Management.2.1Adélie and gentoo penguins are closely related species. Adélie penguins have a circumpolar breeding distribution around Antarctica on ice‐free areas on the continent and offshore islands and gentoo penguins breed on sub‐Antarctic islands and the Antarctic Peninsula. Both species breed during the austral summer and build nests made of small pebbles, and moss and tussocks in the case of gentoos.The Adélie penguin breeding season commences in October of one year and finishes in late March of the following calendar year Ainley, . The malGentoos exhibit considerable variability in the timing of breeding, and some birds remain at or visit colonies throughout the winter months  individual penguins recently bred  and 50 (nonbreeders) in any 5‐day period  23–29 November, when predominantly breeding males are present at nests and (b) 11–18 December, when predominantly breeding females are present  for feeding and swimming , and premolt Emmerson et al., t tests on yearly means and standard deviations. Significance values were adjusted to account for multiple comparisons. Holm–Sidak multiple t tests were conducted with GraphPad Prism version 6 for Windows, GraphPad Software, La Jolla California USA (www.graphpad.com).At each key mass point, we tested for differences between breeders and nonbreeders for both the date of, and the mass for each sex and species using Holm–Sidak multiple 2.2.2To determine whether mass differed according to breeding status within each year, we examined whether there was a difference between the mass of breeders and nonbreeders during each 5‐day period throughout the breeding season for each sex and species combination. We used linear mixed‐effects models with mass as the response variable, and year , breeding status (breeder or nonbreeder), and 5‐day period  as explanatory variables, and with bird ID as a random factor. Mass data for each sex were analyzed separately for Adélie and gentoo penguins.lme4 library , the nonbreeders had a lower mass at times than the breeders  suggest that large fat reserves during incubation are beneficial as insurance against being forced to abandon the egg, but after brooding, fat reserves are no longer adaptive and adults may shed surplus fat  are reported to gain body mass during the winter months as a way of increasing their chance of survival during a period with less predictable food availability and potentially in response to increased energy demands during the colder winter months (Anker‐Nilssen et al., In light of these results, it is important to consider why seabird mass fluctuates dramatically during the breeding season and what possible mechanisms underlie the similar qualitative pattern reported here for the breeders and nonbreeders for both species and the failed breeders in the case of Adélie penguins. Results from Little Auks ( Taylor, . PuffinsOne important consideration for interpreting the results from this study is that the nonbreeder Adélie penguins at Béchervaise Island reported here are those birds that visited the colony at least once during the breeding season. While these birds were classified as nonbreeders if they were not tied to a nest or laid an egg, their presence at the breeding colony, particularly at the start of the breeding season, may indicate that they were intending to breed and may have gone some way toward attaining suitable breeding condition, and so it is perhaps not surprising that some of these birds follow the same cycle as the breeders. In addition, it is also possible that some of the birds classified as nonbreeders may have been very early failed breeders, and while any misclassification of their breeding status is likely to be very low, it is important to keep this in mind. Based on our estimation of the size of the entire nonbreeding population (Southwell et al., The results from our long‐term mark‐resight and monitoring program, and an automated weighing platform have allowed us to understand mass change patterns of Adélie penguins in relation to breeding status and hints strongly at the role that hormones play in regulating their appetite to sustain such mass changes. Data from the weighing platform fill a substantial data gap on the annual cycle of mass changes in Adélie penguins. Adélie penguins are central‐place foragers during the breeding season and can have substantial distances to traverse across the ice to reach their foraging grounds (Emmerson & Southwell, In conclusion, the results from this study on sex‐ and species‐specific changes in body mass in relation to breeding status during a breeding season present a significant step toward estimating the annual cycle of resource and food requirements for the important nonbreeder component of a seabird population. In future studies, it would be worthwhile confirming the role that hormones play in relation to body condition and appetite for both wild populations as well as their captive counterparts (Spée et al., None declared.LE and CS conceived the ideas, designed the methodology, and collated the Adélie penguin data. LE analyzed the data. SW collected and collated the gentoo penguin data. All authors contributed critically to the writing of the manuscript and gave final approval for publication. Click here for additional data file.


To find the covert patterns of abnormality in patients with unilateral temporal lobe epilepsy (TLE) and visually normal brain magnetic resonance images (MRI‐negative), comparing them to those with visible abnormalities (MRI‐positive).We used multimodal brain MRI from patients with unilateral TLE and employed contemporary machine learning methods to predict the known laterality of seizure onset in 104 subjects . A visualization approach entitled "Importance Maps" was developed to highlight image features predictive of seizure laterality in both the MRI‐positive and MRI‐negative cases.Seizure laterality could be predicted with an area under the receiver operating characteristic curve of 0.981  in MRI‐positive and 0.842 (95% CI = 0.736‐0.949) in MRI‐negative cases. The known image features arising from the hippocampus were the leading predictors of seizure laterality in the MRI‐positive cases, whereas widespread temporal lobe abnormalities were revealed in the MRI‐negative cases.Covert abnormalities not discerned on visual reading were detected in MRI‐negative TLE, with a spatial pattern involving the whole temporal lobe, rather than just the hippocampus. This suggests that MRI‐negative TLE may be associated with subtle but widespread temporal lobe abnormalities. These abnormalities merit close inspection and postacquisition processing if there is no overt lesion. This study was conducted to determine the covert patterns of abnormality in patients with unilateral TLE and visually normal brain MR imagesMultimodal brain MRI and contemporary machine learning methods were used, and a visualization approach entitled "Importance Maps" was developedCovert abnormalities in MRI‐negative TLE had a spatial pattern involving the whole temporal lobe, rather than just the hippocampus, and assisted lateralization1Epilepsy is a common and serious neurological disease that can have a devastating effect on a person's life if not adequately treated. However, one‐third of patients continue to have frequent seizures despite optimal medical therapy.The identification of an underlying abnormality on magnetic resonance imaging (MRI) is a key goal of the surgical workup, but such abnormalities are only demonstrated on conventional MRI in about two‐thirds of cases .Detection of brain abnormalities on magnetic resonance (MR) images using contemporary methods such as machine learning is an emerging and promising area of research.Keihaninejad et al reported a distribution of brain abnormalities using an SVM classifier trained to lateralize TLE, and also included MRI‐negative cases.Several different approaches have shown promise in lateralizing seizure origin in TLE, although mostly in MRI‐positive cases. In the case of MRI‐negative TLE, if a trained classifier is demonstrating reasonable predictive capability, then these apparently normal images must contain abnormalities, albeit subtle or poorly understood ones. Determining these abnormalities would provide valuable insight into why visual inspection might fail in the MRI‐negative cases and may guide more principled and accurate visual image interpretation in the future.In this study, we trained a random forest classifier (RFC) on image features from multimodal MRI  and carried out feature importance measurements, demonstrating the patterns of abnormality across the temporal lobe in both MRI‐positive and MRI‐negative cases. We created visualizations of these results, which we call "Importance Maps," that show the spatial pattern of abnormalities across the temporal lobes in these two patient groups.2Previous neurosurgical excision of brain tissue (13 excluded)Brain images with one or more visually apparent space‐occupying lesion The study cohort included patients diagnosed with TLE by a consultant epileptologist. The patients underwent routine clinical scans including T1, T2, and FLAIR volumes on a 3T Signa HDx scanner  at the Epilepsy Society MRI Unit, Chalfont St Peter between 2009 and 2013. Patients were included if they had provided written, informed consent and clinical consensus at the multidisciplinary epilepsy surgery meeting or careful review of notes and investigations  demonstrated findings consistent with unilateral TLE. The study was approved by the National Hospital for Neurology and Neurosurgery and the Queen Square Institute of Neurology Joint Research Ethics Committee. Starting from a dataset of 135 cases, image volumes were visually inspected and reports from a consultant neuroradiologist were reviewed to exclude cases that met any of the following criteria:This left 104 cases for use in the analysis: 82 MRI‐positive and 22 MRI‐negative. In all cases, the seizure laterality was established through the combination of all relevant information, including clinical semiology, radiological findings on MRI, positron emission tomography, and/or ictal single photon emission computed tomography, scalp video EEG, and where available intracranial EEG and/or magnetoencephalography, neuropsychology, and postoperative histology of resected tissues. The proportion of left‐ and right‐lateralized cases was approximately equal for the MRI‐positive and the MRI‐negative patient groups .Patient demographics and a clinical summary are shown in Table For the MRI‐positive group, 68 of 82 patients had imaging findings consistent with hippocampal sclerosis, whereas 5 of 82 patients had findings consistent with focal cortical dysplasia. The remaining 9 of 82 patients had a visually recognizable abnormality within the temporal lobe that allowed lateralization of the seizure focus but without a confident underlying diagnosis of the lesion from the radiologist.The numbers of patients in the MRI‐positive and MRI‐negative groups who had surgery and histology were 55 of 82 and 10 of 22, respectively. International League Against Epilepsy outcomes at 12 months after surgery are shown in Table 2.1Our analysis used T1‐weighted, T2‐weighted, and FLAIR MR image volumes. The T2‐weighted and FLAIR volumes were rigidly registered to the T1, and each T1‐weighted image volume was parcellated into its constituent anatomical regions using the Geodesic Information Flows (GIF) method.Right/left ratios between the volumes of each of the regions within the temporal lobes .Right/left ratios between the means of the image intensities within each temporal lobe region for the T1, T2, FLAIR, and JM image volumes .Right/left ratios between the standard deviations of the image intensities within each temporal lobe region for the T1, T2, FLAIR, and JM image volumes .The following measurements were then made for regions of the temporal lobe parcellated by GIF:This provided a set of 117 features per patient.These features were used to train an RFCTo ensure the validity of the feature importances determined above, we evaluated the predictive capability of these features using SVMs. The type of kernel used for the MRI‐positive cases was linear, whereas for the MRI‐negative cases the radial basis function was chosen due to laterality detection in MRI‐negative cases being a significantly more difficult problem. We used a different type of classifier (SVM) from that used for determining the feature importances (RFC) to ensure the generalizability of the results. Hyperparameters of the SVM classifier were optimized using the grid‐search method, and its capability to lateralize the seizure origin was assessed using bolstering,3The performance of the SVM classifier at lateralizing the seizure origin was as follows: a maximum area under the receiver operating characteristic (ROC) curve of 0.981 (95% CI = 0.974‐0.989) was achieved in the MRI‐positive and 0.842 (95% CI = 0.736‐0.949) in the MRI‐negative cases  and 0.842 (95% CI = 0.736‐0.949) obtained in determining seizure laterality in MRI‐positive and MRI‐negative cases, respectively, are similar to those reported in other studies addressing TLE lateralization.Maximum areas under the ROC curve for lateralization in the MRI‐positive and MRI‐negative cases were obtained using the top three and 52 imaging features, respectively (Figure The abnormality patterns demonstrated in the Importance Maps are the most significant results in our study. A comparison between them suggests that there is a fundamental difference in the pattern of imaging abnormalities within the MRI‐negative cases compared to the visually recognizable patterns in the MRI‐positive cases. In other words, the MRI‐negative abnormalities are not simply a more subtle version of those seen in MRI‐positive patients.This observed difference is in accord with other investigations. For example, MRI‐negative TLE subjects have been demonstrated to exhibit significantly different connectivity patterns from those of MRI‐positive TLE subjects,A prominent difference in our study was the contrasting significance of the hippocampus and the other temporal lobe regions in the MRI‐positive and MRI‐negative cases, respectively. The hippocampus is conventionally focused on by radiologists reporting MRI scans in patients with TLE, as hippocampal sclerosis is a common cause of TLE.Our results provide a novel insight into why human readers may not visually identify the patterns of abnormality in certain images. The results suggest that, in cases that are difficult to lateralize using the conventional approach, it would be useful to carefully examine images for possible abnormalities and asymmetry within the amygdala, the temporal white matter, and inferior cortical regions of the temporal lobe. Postacquisition processing of these regions in such cases may also prove useful and help to unveil the subtle changes that elude visual inspection.There are limitations to our approach. First, it is not possible to compare the pattern of detected image abnormalities with the histological ground truth in every case, because surgery is not always performed. Second, the use of simple imaging features such as regional volumes and signal variations remain fairly basic when compared to the myriad of more sophisticated image features that are available in the field of medical image computing.A radiological re‐review of the MRI‐negative cases in our study already revealed subtle signal abnormalities aiding lateralization in 8 of the 22 cases. We expect further work in this area, particularly appropriate postprocessing methods enabled by machine learning, could help highlight signal abnormalities, and enable higher rates of successful radiological assessment.5This study has demonstrated that covert abnormalities exist in multimodal MR scans in MRI‐negative TLE, and that these abnormalities follow a different pattern from those in MRI‐positive TLE. These findings could aid clinical reading of MRI‐negative images in the future. The study also introduced the concept of Importance Maps, which may provide an elegant and principled way to characterize patterns of image abnormality that have previously eluded visual detection. They could be used by radiologists to help guide image evaluation in these more challenging cases.None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines. Click here for additional data file.


The worldwide refugee crisis has given rise to 16.2 million refugees in 2017 alone, 52% of which were children (via the CBCL and symptoms reported by teachers via the CTRF was positively associated with maternal psychopathology (Buchmüller et al.  did not athology . Buchmülathology  found meathology –9.The CBCL and CTRF consist of 100 questions assessing child behavior on eight scales; these scales are organized into three categories: internalizing problems, externalizing problems, and total problems  use of bThe sample of parents used by Buchmüller et al.  had a meBuchmüller et al.’s  study reAll authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.The authors declare that this manuscript was written in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Safeguarding ecosystem services and biodiversity is critical to achieving sustainable development. To date, ecosystem services quantification has focused on the biophysical supply of services with less emphasis on human beneficiaries . Only when both occur do ecosystems benefit people, but demand may shift ecosystem service priorities toward human‐dominated landscapes that support less biodiversity. We quantified how accounting for demand affects the efficiency of conservation in capturing both human benefits and biodiversity by comparing conservation priorities identified with and without accounting for demand. We mapped supply and benefit for 3 ecosystem services  by adapting existing ecosystem service models to include and exclude factors representing human demand. We then identified conservation priorities for each with the conservation planning program Marxan. Particularly for flood mitigation and crop pollination, supply served as a poor proxy for benefit because demand changed the spatial distribution of ecosystem service provision. Including demand when jointly targeting biodiversity and ecosystem service increased the efficiency of conservation efforts targeting ecosystem services without reducing biodiversity outcomes. Our results highlight the importance of incorporating demand when quantifying ecosystem services for conservation planning. Article impact statement: Efforts to conserve ecosystem services are more efficient when they account for demand. Demand does not reduce biodiversity outcomes. Ecosystem services (ESs) are the direct and indirect contributions of ecosystems to human well‐being. Environmental degradation has decreased the capacity of ecosystems to support biodiversity and to provide nonmarket ESs  and demand  . We simulated optimal conservation networks for each of supply, benefit, and biodiversity with the optimization program Marxan   with the InVEST model for monthly water yield . All calculations were performed at a 30‐m resolution.We mapped the supply and benefit of nature‐based recreation with a model previously developed for Vermont . The spline term significantly improved the model  (Supporting Information). We used the predicted log‐transformed land cost as an index of relative costs of conservation to minimize the effect of high‐value developed areas on the mean value at a hexagon scale—these areas are not characteristic of protected areas.We used land value to approximate the relative costs of conservation. For roughly 50% of our study area, public tax records of property values could be associated with digitized parcel maps. We estimated unknown land values with a generalized additive model with socioeconomic predictors and a spline smoother for spatial location Bivand  because To determine how demand affects ESs, we compared the density and spatial distributions of supply and benefit. We measured density distributions as kernel density with the geom_density function of the “ggplot2” package in R. We compared density distributions of supply and benefit with a 2‐sided Kolmogorov–Smirnov test. We tested cross‐autocorrelation of supply and benefit in space with the centered Mantel statistic as implemented in R's ncf package , supply and biodiversity, and benefit and biodiversity (both multifactor optimization). We also performed an optimization for biodiversity alone as a control. Identifying joint spatial priorities for biodiversity and ESs better illustrates opportunities to achieve both targets than assessing their spatial correlation. Correlations reflect similarities between places with both low and high value, but only high‐value areas are relevant in the context of spatial planning. Even if correlation overall is low, there may still be locations that efficiently conserve biodiversity and ESs.i is the targeted conservation features ; protection target is the target amount of a conservation feature that the optimization seeks to achieve; protection achieved is the amount of a conservation feature held within the selected priority areas; λ is the species penalty factor for missing a conservation feature's protection target ; and cost constraint is a penalty for exceeding a user‐defined cost constraint. We set equal weights for biodiversity and ESs and set the cost constraint penalty high enough such that the solution never exceeded our constraint.We used Marxan . Optimal solutions never exceeded the cost threshold and maximized the protection of conservation features within that constraint (a maximum coverage problem).We performed 500 runs for each simulation and used the best solutions as our priority areas  of each hexagon in terms of biodiversity, supply, and benefit, as the amount of each per unit cost. We then standardized ROI as a percentile rank.rs = −0.08, flood mitigation rs = 0.26, nature‐based recreation rs = 0.95, p < 2.2 × 10−16 e−16 in all cases)   and when doing so will achieve smaller efficiency gains .Efforts that target ES without considering biodiversity are unlikely to provide high levels of biodiversity regardless of the ES measure used (supply or benefit). Many conservation organizations target ES in addition to (not instead of) biodiversity . We ignored differences in how groups of beneficiaries may value benefits to illustrate the effect of accounting for or omitting demand altogether. For instance, we could have weighted structures within floodplains according to expected flooding frequency, vulnerability to flooding, or economic value . We faced methodological challenges when integrating supply and demand to determine benefit. For nature‐based recreation, we used regression to determine the relative importance of supply and demand in determining benefit. For flood mitigation, the relative importance of supply and demand in benefit was unknown; we assumed each component contributed equally and calculated benefit as their unweighted product. Finally, we assessed the relationship between biodiversity and individual ESs, whereas biodiversity likely relates to suites of ESs Duffy . OptimizNature underpins human well‐being, and conservation can help advance a broad range of sustainable development goals ICSU . While ihttps://figshare.com/authors/Keri_Watson/6259679. Queries  should be directed to the corresponding author.Details on the InVEST Seasonal Water Yield model (Appendix S1), a sensitivity analyses of flood‐mitigation supply results to including winter months in the model (Appendix S2) and of our flood‐mitigation service results to the assumption that supply and demand are equally important in determining benefit (Appendix S3), an explanation of modeled land value as a proxy for conservation cost (Appendix S4), maps of demand for each ES (Appendix S5), a comparison of BioFinder to species‐based conservation prioritization (Appendix S6), and a comparison of single‐factor optimizations to hotpots selected based on ROI (Appendix S7) are available online. The authors are solely responsible for the content and functionality of these materials. Shapefiles of ecosystem service supply, demand, and benefit, and best conservation networks for each are freely available from K.W.’s FigShare account: Click here for additional data file.


We argue that the human evolutionary heritage with frequent adaptations through geological time to environmental change has affected a trade‐off between offspring variability and cancer resistance, and thus favored cancer‐prone individuals. We turn the attention to a factor setting the highly cancer‐resistant naked mole rat apart from most other mammals: it has remained phenotypically largely unchanged since 30‐50 million years ago. Research focusing on DNA stability mechanisms in ‘living fossil’ animals may help us find tools for cancer prevention and treatment. In the trade‐off between benefit from offspring variability and deleterious effects of most new mutations, the more cancer‐prone individuals are then favored. To the best of our knowledge, this has not been discussed earlier in the medical literature, although the existence of a similar trade‐off has been suggested by for example, Fisher in 1930Heterocephalus glaber naked mole rat (NMR) has been extensively studied because of its long life span and extremely low cancer incidence.The It is often suggested that we can learn from evolution why the modern and affluent lifestyle of humans comes with a high disease burden, and also how a fix for cancer has already been invented by other animals.There has probably been selection of both promutagenic and DNA‐protective genes, in both somatic and germ cells.It should be possible to test our hypothesis by assessing the germ‐line mutation rate in NMR captivity populationsIn conclusion, we argue that the human evolutionary heritage with many relatively recent species radiations and within‐species adaptations has affected a trade‐off between offspring variability and cancer resistance. If our hypothesis can be verified, research focusing on DNA stability may help us learn from cancer‐resistant animals and find tools for cancer prevention and treatment.There is no conflict of interest.


Fentanyls as a class of drug have pharmacological properties that make them more likely to lead to overdose than other opioids. In addition to high potency and rapid onset of respiratory depression, these drugs also induce respiratory muscle stiffness, making it more difficult to breathe, are less sensitive than heroin to naloxone reversal and may show reduced cross‐tolerance to other opioids.Overdose deaths involving fentanyls  have risen dramatically in North America during the last few years 2) and lowered partial pressure of oxygen (pO2), and thus reduce the drive to breathe. Given the high death rate involving fentanyl overdose the question arises of whether the lethality of fentanyls results simply from their high potency or whether other pharmacological properties also contribute.Heroin and other opioids depress respiration by acting on μ opioid receptors (MORs) to reduce the response to raised partial pressure of carbon dioxide  for morphine but only a fourfold increase in the ED50 for fentanyl Tolerance develops to the respiratory depressant effects of opioids. Cross‐tolerance develops between opioid drugs acting at the same receptor, but the degree of cross‐tolerance will depend upon agonist intrinsic efficacy. In a rodent model measuring opioid‐induced locomotor activity, prolonged treatment with morphine produced a 22‐fold increase in the 50% effective dose (EDA combination of factors—potency, rate of onset, bias, muscle rigidity, lower susceptibility to naloxone reversal, lack of cross‐tolerance—may conspire together to make fentanyls such lethal drugs. We would suggest that the dangers of fentanyls will only be fully understood and then mitigated by rigorously applying pharmacological principles to both experimental and clinical data.None.