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For the past decade, the College of Chemistry at UC Berkeley has iteratively redesigned general chemistry laboratory courses to introduce students to green chemistry concepts, while simultaneously using green chemistry as a relevant context to learn chemistry. To investigate the effectiveness of this curriculum we developed approaches to investigate student understanding of green chemistry. We adapted a constructivist educational framework to iteratively design fixed and free response items appropriate for large enrollment courses that probe student knowledge of green chemistry concepts and practices. Two free response items were designed to probe students' ability to define green chemistry and make green chemistry decisions in the context of a case study. A set of fixed response items were designed to probe particular aspects of green chemistry knowledge that were included in the course. Together, we used these items to characterize (1) changes in student understanding of green chemistry and (2) how prior ''green'' knowledge impacts student learning of new green chemistry principles in the general chemistry laboratory course. Analysis of student responses indicated that, on average, students demonstrated increased green chemistry understanding after completing this green chemistry aligned laboratory course. Students were able to integrate more normative green chemistry principles in their answers and began to indicate awareness of complex interconnected systems. Because the items focused on assessing student knowledge of green chemistry, rather than their self-assessment of knowledge, they provided valuable insight regarding students' prior green chemistry knowledge that will be used to develop future versions of the curriculum.

A student-led mathematics bootcamp has been designed and implemented to help foster community building, improve confidence in mathematical skills, and provide mathematical resources for incoming physical chemistry doctoral students. The bootcamp is held immediately before the start of the first semester of graduate school and uses an active learning approach to review and practice undergraduate-level mathematics problems over 5 days in small student groups. This work includes the development and presentation of a new, publicly available mathematics curriculum for the bootcamp on select mathematics topics, including calculus, linear algebra, functions, differential equations, statistics, and coding in Python, aiming at improving students' confidence and learning experiences in graduate quantum mechanics and statistical physics courses. Surveys before and after the bootcamp showed an increase in students' confidence in problem-solving in key mathematical areas and social aspects of peer-led group learning. Qualitative and quantitative analyses demonstrate that the bootcamp reduced prior inequities in students' confidence metrics based on gender and mathematical background.

Abstract Congenital diaphragmatic hernia (CDH) is a birth defect characterized by incomplete closure of the diaphragm, herniation of abdominal organs into the chest, and compression of the lungs and the heart. Besides complications related to pulmonary hypoplasia, 1 in 4 survivors develop neurodevelopmental impairment, whose etiology remains unclear. Using a fetal rat model of CDH, we demonstrated that the compression exerted by herniated organs on the mediastinal structures results in decreased brain perfusion on ultrafast ultrasound, cerebral hypoxia with compensatory angiogenesis, mature neuron and oligodendrocyte loss, and activated microglia. In CDH fetuses, apoptosis was prominent in the subventricular and subgranular zones, areas that are key for neurogenesis. We validated these findings in the autopsy samples of four human fetuses with CDH compared to age- and sex-matched controls. This study reveals the molecular mechanisms and cellular changes that occur in the brain of fetuses with CDH and creates opportunities for therapeutic targets.

Genetic liability to substance use disorders can be parsed into loci that confer general or substance-specific addiction risk. We report a multivariate genome-wide association meta-analysis that disaggregates general and substance-specific loci for published summary statistics of problematic alcohol use, problematic tobacco use, cannabis use disorder, and opioid use disorder in a sample of 1,025,550 individuals of European descent and 92,630 individuals of African descent. Nineteen independent SNPs were genome-wide significant (P < 5e-8) for the general addiction risk factor (addiction-rf), which showed high polygenicity. Across ancestries, PDE4B was significant (among other genes), suggesting dopamine regulation as a cross-substance vulnerability. An addiction-rf polygenic risk score was associated with substance use disorders, psychopathologies, somatic conditions, and environments associated with the onset of addictions. Substance-specific loci (9 for alcohol, 32 for tobacco, 5 for cannabis, 1 for opioids) included metabolic and receptor genes. These findings provide insight into genetic risk loci for substance use disorders that could be leveraged as treatment targets.

Problem solving is a key component of authentic scientific research and practice in organic chemistry. One factor that has been shown to have a major role in successful problem solving in a variety of disciplines is metacognitive regulation, defined as the control of one's thought processes through the use of planning, monitoring, and evaluation strategies. Despite the growing interest in assessing and promoting metacognition in the field of chemical education, few studies have investigated this topic in the context of organic chemistry students. To gain a deeper understanding of how and why students make use of strategies related to metacognitive regulation in their approaches to solving problems, we conducted interviews with Organic Chemistry I, Organic Chemistry II, and graduate organic chemistry students and used multiple measures to examine students' metacognition. As a part of these interviews, students verbalized their thoughts as they worked on complex predict-the-product problems and completed a self-report instrument indicating which planning, monitoring, and evaluation strategies they had used while completing each problem. Think-aloud protocols were analyzed for the presence of each of the behaviors included on the self-report instrument, and students' use of metacognitive strategies was compared to identify differences between students with different levels of experience and between students who generated more and less successful solutions to the problems. Students who generated more successful solutions to the problems tended to report using a greater number of metacognitive strategies. When asked why they did or did not use certain metacognitive strategies, students indicated a number of factors, such as not feeling able to use these strategies effectively or believing that using these strategies was unnecessary. The results of this study support the importance of teaching metacognitive problem-solving strategies in organic chemistry courses and suggest several methods for the assessment and instruction of metacognition.

Abstract Background Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in patients with Type 1 Diabetes (T1D). Early markers of CVD include increased carotid intima-media thickness (CIMT) and pulse wave velocity (PWV), but these existing ultrasound technologies show limited spatial and temporal resolution in young adults. The purpose of this study is to evaluate the utility of high-resolution ultrasound modalities, including high frequency ultrasound CIMT (hfCIMT) and ultrafast ultrasound PWV (ufPWV), in young adults with Type 1 Diabetes. Methods This is a prospective single-center observational cohort study including 39 participants with T1D and 25 age and sex matched controls. All participants underwent hfCIMT and ufPWV measurements. hfCIMT and ufPWV measures of T1D were compared with controls and associations with age, sex, BMI, A1c, blood pressure, and lipids were studied. Results Mean age was 24.1 years old in both groups. T1D had a greater body mass index (27.7 [5.7] vs 23.1 [3.2] kg/m2), LDL Cholesterol, and estimated GFR, and had a mean A1c of 7.4 [1.0] % (57 mmol/mol) and diabetes duration of 16.1 [3.7] years with 56% using insulin pumps. In T1D, hfCIMT was significantly increased as compared to controls (0.435 ± 0.06 mm vs 0.379 ± 0.06 mm respectively, p

Ultrafast laser pump-probe spectroscopy is an important and growing field of physical chemistry that allows the measurement of chemical dynamics on their natural time scales, but undergraduate laboratory courses lack examples of such spectroscopy and the interpretation of the dynamics that occur. Here we develop and implement an ultrafast pump-probe spectroscopy experiment for the undergraduate physical chemistry laboratory course at the University of California Berkeley. The goal of the experiment is to expose students to concepts in solid-state chemistry and ultrafast spectroscopy via classic coherent phonon dynamics principles developed by researchers over multiple decades. The experiment utilizes a modern high-repetition-rate 800 nm femtosecond Ti:sapphire laser, split pulses with a variable time delay, and sensitive detection of transient reflectivity signals using the lock-in technique. The experiment involves minimal intervention from students and is therefore easy and safe to implement in the laboratory. Students first perform an intensity autocorrelation measurement on the femtosecond laser pulses to obtain their temporal duration. Then, students measure the pump-probe reflectivity of a single-crystal antimony sample to determine the period of coherent phonon oscillations initiated by an ultrafast pulse excitation, which is analyzed by fitting to a sine wave. Students who completed the experiment in-person obtained good experimental results, and students who took the course remotely due to the COVID-19 pandemic were provided with the data they would have obtained during the experiment to analyze. Evaluation of student written and oral reports reveals that the learning goals were met, and that students gained an appreciation for the field of ultrafast laser-induced chemistry.

Entre las lenguas indígenas sudamericanas y dentro de la misma familia lingüística tupí-guaraní, el guaraní paraguayo es una de las lenguas más estudiadas y descriptas. Desde los primeros trabajos de los religiosos Ruiz de Montoya ([1639] 1876 y 1640) y Restivo ([1722] 1893 y [1724] 1892), destinados a la descripción del guaraní hablado en las misiones jesuíticas, de la entonces llamada Provincia del Paraguay, la lengua ha sido objeto de numerosas gramáticas (Guasch, 1996; Canese, 1983; ALG, 2020, entre otros) y diccionarios (Guasch, 1961; Canese y Alcaraz, 1997; Sanabria, 2007, entre otros) hasta la fecha. La lengua guaraní incluso cuenta con un organismo en Paraguay, la Academia de la Lengua Guaraní (ALG, de aquí en más), que se ha abocado tanto a su descripción como a su estandarización desde su creación en el año 2012. No obstante, si bien valiosos para la implementación de políticas lingüísticas y educativas, los trabajos anteriormente citados, de corte más prescriptivista y normativo, suelen centrarse en una única variedad del guaraní: el guaranieté (también llamado "guaraní académico" o "guaraní culto"), asociado con la lengua escrita, y rara vez reflejan el uso real de la lengua por parte de los hablantes. Lino Trinidad Sanabria, quien se encuentra entre los miembros fundadores de la ALG, incluye, por ejemplo, en su diccionario (Sanabria, 2007) un apéndice sobre el jopará, la variedad del guaraní más influenciada por el español, donde advierte que debe evitarse en tanto "atenta con la autenticidad y el brillo de la lengua guaraní" (Sanabria, 2007: 5). Asimismo, en términos analíticos, la tradición generalmente se vale de categorías que, si bien resultan útiles para describir las lenguas europeas, encuentran limitaciones al aplicarse a una lengua tipológicamente disímil, como es el caso del guaraní.

Understanding the impact of undergraduate research experiences (UREs) and course-based undergraduate research experiences (CUREs) is crucial as universities debate the value of allocating scarce resources to these activities. We report on the Berkeley Undergraduate Research Evaluation Tools (BURET), designed to assess the learning outcomes of UREs and CUREs in chemistry and other sciences. To validate the tools, we administered BURET to 70 undergraduate students in the College of Chemistry and 19 students from other STEM fields, comparing the performance of students who had less than one year of undergraduate research to those with more than one year of research experience. Students wrote reflections and responded to interviews during poster presentations of their research project. BURET asks students to communicate the significance of their project, analyze their experimental design, interpret their data, and propose future research. Scoring rubrics reward students for integrating disciplinary evidence into their narratives. We found that the instruments yielded reliable scores, and the results clarified the impacts of undergraduate research, specifically characterizing the strengths and weaknesses of undergraduate researchers in chemistry at our institution. Students with at least a year of research experience were able to use disciplinary evidence more effectively than those with less than one year of experience. First-year students excelled at explaining the societal relevance of their work, but they incorporated only minimal discussion of prior research into their reflections and presentations. Students at all levels struggled to critique their own experimental design. These results have important implications for undergraduate learning, suggesting areas for faculty members, graduate student research mentors, and CURE or URE programs to improve undergraduate research experiences.

A central practice in the discipline of organic chemistry is the ability to solve certain fundamental problems, including predicting reactivity, proposing mechanisms, and designing syntheses. These problems are encountered frequently by both students and practitioners, who need to utilize vast amounts of content knowledge in specific ways to generate reasonable solutions. To gain insight into how one of these major problem types can be solved, we have investigated student approaches to complex predict-the-product problems through the detailed analysis of think-aloud interviews. This work led to the creation of a general workflow model that describes the reasoning pathways of students with varying levels of expertise when attempting to predict organic reactivity. The problems used in this study were designed to be non-trivial and potentially ambiguous to elicit ''true'' problem solving and discourage a purely memorization-based approach, even from more experienced organic chemists. Rich descriptions of undergraduate and graduate student interviews are provided, and student thought processes are characterized in terms of common problem-solving actions. These actions were developed into the workflow model using an iterative method that combined results from our analysis with the experiences of instructors and feedback from both undergraduate focus groups and graduate students. The workflow serves as both a potential instructional tool and a model for student thinking. This model is general enough to be applied to both successful and unsuccessful solution pathways by both novice undergraduates and more expert-like graduate students. Characteristics of more successful and more experienced problem solvers are investigated, and concrete strategies that can be recommended to students are discussed. The results of this study complement existing work on other fundamental problem types in organic chemistry and suggest a variety of teaching interventions to develop students into more successful organic problem solvers.

BackgroundChildhood psychotic-like experiences (PLEs) often precede the development of later severe psychopathology. This study examined whether childhood PLEs are associated with several psychopathology-related polygenic scores (PGSs) and additionally examined possible neural and behavioral mechanisms.MethodsAdolescent Brain Cognitive Development Study baseline data from children with European ancestry (n = 4650, ages 9-10 years, 46.8% female) were used to estimate associations between PLEs (i.e., both total and presence of significantly distressing) and PGSs for psychopathology (i.e., schizophrenia, psychiatric cross-disorder risk, PLEs) and related phenotypes (i.e., educational attainment [EDU], birth weight, inflammation). We also assessed whether variability in brain structure indices (i.e., volume, cortical thickness, surface area) and behaviors proximal to PGSs (e.g., cognition for EDU) indirectly linked PGSs to PLEs using mediational models.ResultsTotal and significantly distressing PLEs were associated with EDU and cross-disorder PGSs (all %ΔR2s = 0.202%-0.660%; false discovery rate-corrected ps < .006). Significantly distressing PLEs were also associated with higher schizophrenia and PLE PGSs (both %ΔR2 = 0.120%-0.216%; false discovery rate-corrected ps < .03). There was evidence that global brain volume metrics and cognitive performance indirectly linked EDU PGS to PLEs (estimated proportion mediated = 3.33%-32.22%).ConclusionsTotal and significantly distressing PLEs were associated with genomic risk indices of broad-spectrum psychopathology risk (i.e., EDU and cross-disorder PGSs). Significantly distressing PLEs were also associated with genomic risk for psychosis (i.e., schizophrenia, PLEs). Global brain volume metrics and PGS-proximal behaviors represent promising putative intermediary phenotypes that may indirectly link genomic risk to psychopathology. Broadly, polygenic scores derived from genome-wide association studies of adult samples generalize to indices of psychopathology risk among children.

Historically, efforts to improve academic climate have been siloed-many efforts involve the collection of data to understand issues affecting diversity at an institutional level, while others prioritize recruitment and retention of historically marginalized groups. Few initiatives, however, effectively combine the two in order to create concrete action plans to eliminate structural barriers that hinder the retention of minorities in STEM. In this Editorial, we present the history and details of a collaborative effort to improve the academic climate of the Department of Chemistry at University of California, Berkeley. This initiative began in 2016 as a graduate student-led, grassroots movement to develop a method to assess the department's academic climate. Over the past several years-and with support from stakeholders at all levels-it has grown into a department-wide effort to systematically collect data, exchange ideas, and implement goal-oriented interventions to make our academic community more inclusive. With the recent development of a five-year strategic plan and funding increase to provide financial support for student-led programs, we have institutionalized a method to maintain the initiative's momentum. Here, we share our approaches, insights, and perspectives from community members who have shaped this movement. We also provide advice to help other academic communities determine a practical path toward affecting positive cultural change.

Ongoing efforts to improve diversity in science, technology, engineering, and mathematics (STEM) primarily manifest as attempts to recruit more women and individuals from historically marginalized groups. Yet, these efforts fail to repair the specific, systemic issues within academic communities that hinder diverse individuals from persisting and thriving in STEM. Here, we present the results of a quantitative, multiyear effort to make the academic climate of an R1 STEM department more inclusive. We use a student-led, department-specific, faculty-supported initiative to assess and improve the climate of the Department of Chemistry at the University of California, Berkeley, as a case study. Our results provide quantitative evidence that community discussions grounded in our own data, alongside cooperative community efforts to address the issues present in those data, are effective methods for driving positive change. Longitudinal assessment of our academic climate from 2018 to 2020 via annual department-wide surveys indicates that these interventions have succeeded in shifting the perception of our academic climate. This study confirms the positive outcomes of having a practical, sustainable, and data-driven framework for affecting change within a graduate community.

Paul Kahn has offered a fascinating account of the role of political theology in the field of law, through an exploration of some core concepts of the discipline. This article explores the nature of Kahn’s undertaking through a comparison with Carl Schmitt. The conclusion is that, rather than actual theology, Kahn’s “political theology” is a valuable form of legal anthropology anchored in an exploration of our legal culture.

Increasing access to undergraduate research is critical in efforts to retain students pursuing careers in STEM. Alternatives to traditional research positions, such as course based undergraduate research experiences (CUREs), have played important roles in engaging more undergraduates in research. However, these opportunities are only a subset of possible nontraditional research experiences which can enrich the undergraduate experience. In this study, we critically examined and improved the research-group-led undergraduate research program (GURP) to better meet the needs of undergraduates seeking research. Specifically, we investigated if the program was successful with a greater diversity of data sets, if assessments of learning were consistent across different data sets and teaching environments, and if the program promoted student engagement in research. We have found that this model is scalable, robust, and adaptable to different implementations while producing consistent and positive learning outcomes for students. Especially remarkable are students' increased self-identification as scientists and statistically significant gains in self-perceived competency across multiple domains of knowledge. This program model has shown promising results as a partially and fully online research experience for undergraduates and has benefited program alumni in their research careers. To assist research groups starting similar programs, we have created public data sets and instructional resources. We believe that GURP programs can work in a variety of situations and hope that they can become a tool to increase interest and build communities for young researchers.

Many cultural and institutional barriers have prevented chemistry from realizing greater calls for diversity in academia. Though recent work has elucidated how the measures of success used in academia can disadvantage students from underrepresented groups at the undergraduate level, thorough understanding of how success metrics are valued by minoritized students at the graduate level is lacking. Here, we use data generated from the UC Berkeley Department of Chemistry's student-led climate survey to investigate both how graduate students prioritize and how faculty employ common metrics for graduate student success. Results revealed that faculty undervalued metrics preferred by students from underrepresented groups (URGs) in STEM such as underrepresented people of color, women, LGBTQ+ students, and first-generation students. Priorities of students that do not identify as underrepresented displayed no statistically significant differences compared to faculty values. Questions regarding publication record, one of the often-used measures of success in STEM academia, suggest that graduate students, particularly those belonging to URGs, challenge the use of publication record as the primary metric of success in graduate school. These findings highlight some of the ways that definitions of academic success can be exclusionary for graduate students from underrepresented backgrounds and encourage re-envisioning graduate school success in ways that reflect the values of diverse student populations.

BackgroundVariation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder.MethodsTo conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations.FindingsWe identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10-9) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10-9). Cannabis use disorder and cannabis use were genetically correlated (rg 0·50, p=1·50 × 10-21), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia.InterpretationThese findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder.FundingNational Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences.

Stress-induced dysregulation of diurnal cortisol is a cornerstone of stress-disease theories; however, observed associations between cortisol, stress, and health have been inconsistent. The reliability of diurnal cortisol features may contribute to these equivocal findings. Our meta-analysis (5 diurnal features from 11 studies; total participant n = 3307) and investigation (15 diurnal cortisol features) in 2 independent studies (St. Louis Personality and Aging Network [SPAN] Study, n = 147, ages 61–73; Minnesota Longitudinal Study of Risk and Adaptation [MLSRA] Study, n = 90, age 37) revealed large variability in the day-to-day test-retest reliability of diurnal features derived from salivary cortisol data (i.e., ICC = 0.00–0.75). Collectively, these data indicate that some commonly used diurnal cortisol features have poor reliability that is insufficient for individual differences research (e.g., cortisol awakening response) while others (e.g., area under the curve with respect to ground) have fair-to-good reliability that could support reliable identification of associations in well-powered studies.

It is well-documented that the representation of women and racial/ethnic minorities diminishes at higher levels of academia, particularly in science, technology, engineering, and math (STEM). Sense of belonging-the extent to which an individual believes they are accepted, valued, and included in a community-is often emphasized as an important predictor of retention throughout academia. While literature addressing undergraduate sense of belonging is abundant, there has been little investigation of sense of belonging in graduate communities. Because graduate training is required to generate new scientific leaders, it is important to understand and address sense of belonging at the graduate level-paying explicit attention to devising strategies that can be used to increase representation at higher levels of academia. Here, a visual narrative survey and item response modeling are used to quantify sense of belonging among graduate students, postdoctoral researchers, and faculty within the Department of Chemistry at the University of California, Berkeley. Results suggest that graduate students, postdoctoral researchers, and faculty all experience impostor phenomenon. Respondents struggle most with maintaining positive self-perceptions of their productivity, capabilities as a scientist, and success-particularly in comparison to their peers. Communicating about science with peers, talking about teaching hurdles, and engaging in mentoring relationships also contribute significantly to sense of belonging. Faculty members have the highest sense of belonging, while senior graduate students and postdoctoral researchers are least likely to feel a sense of belonging. Additionally, graduate students and postdoctoral researchers who identify as underrepresented, as well as those who submit manuscripts for publication less than their peers, are less likely to feel a sense of belonging. This is the first study to generate a quantitative, nuanced understanding of sense of belonging within the entire graduate academic community of an R1 STEM department. We envision that these methods can be implemented within any research-focused academic unit to better understand the challenges facing community members and identify factors to address in promoting positive culture change. Furthermore, these methods and results should provide a foundation for devising interventions that academic stakeholders can use to directly improve graduate education.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.