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BackgroundMaternal solvent exposure has been suspected to increase offspring cancer risk. The study aimed to evaluate the associations between maternal residential exposure to solvents from industrial pollution during pregnancy and childhood cancer.MethodsThe present study included 15,744 cancer cases (aged 0-19 years at diagnosis) identified from California Cancer Registry and 283,141 controls randomly selected from California Birth Registry (20:1 frequency-matched by birth year: 1998-2016). We examined industrial releases of tetrachloroethylene and 1,1,1-trichloroethane within 3 km of the birth address, while we used a 5 km buffer for carbon disulfide. We calculated the total exposure from all linked Toxic Release Inventory sites during each index pregnancy and assigned "ever/never" and "high/low exposed/unexposed" exposure, using median values. We performed quadratic decay models to estimate cancer risks associated with maternal solvent exposure in pregnancy.Results1,1,1-Trichloroethane was associated with rhabdomyosarcoma (adjusted Odds Ratio (aOR): 1.96; 95% Confidence Interval (CI): 1.16, 3.32) in the "ever exposed" group. Ever exposure to carbon disulfide was associated with increased risks of medulloblastoma (OR = 1.85, 95% CI 1.01, 3.40) and ependymoma (OR = 1.63, 95% CI 0.97, 2.74).ConclusionsOverall, our findings suggested maternal residential exposure to solvents from industrial sources might be associated with elevated childhood cancer risks.

BackgroundOrganophosphorus pesticides (OP) have been associated with various human health conditions. Animal experiments and in-vitro models suggested that OP may also affect the gut microbiota. We examined associations between ambient chronic exposure to OP and gut microbial changes in humans.MethodsWe recruited 190 participants from a community-based epidemiologic study of Parkinson's disease living in a region known for heavy agricultural pesticide use in California. Of these, 61% of participants had Parkinson's disease and their mean age was 72 years. Microbiome and predicted metagenome data were generated by 16S rRNA gene sequencing of fecal samples. Ambient long-term OP exposures were assessed using pesticide application records combined with residential addresses in a geographic information system. We examined gut microbiome differences due to OP exposures, specifically differences in microbial diversity based on the Shannon index and Bray-Curtis dissimilarities, and differential taxa abundance and predicted Metacyc pathway expression relying on regression models and adjusting for potential confounders.ResultsOP exposure was not associated with alpha or beta diversity of the gut microbiome. However, the predicted metagenome was sparser and less evenly expressed among those highly exposed to OP (p = 0.04). Additionally, we found that the abundance of two bacterial families, 22 genera, and the predicted expression of 34 Metacyc pathways were associated with long-term OP exposure. These pathways included perturbed processes related to cellular respiration, increased biosynthesis and degradation of compounds related to bacterial wall structure, increased biosynthesis of RNA/DNA precursors, and decreased synthesis of Vitamin B1 and B6.ConclusionIn support of previous animal studies and in-vitro findings, our results suggest that ambient chronic OP pesticide exposure alters gut microbiome composition and its predicted metabolism in humans.

This article outlines a novel approach for career readiness which embeds a global engagement trip within a social entrepreneurship course. Utilizing an empathy driven approach, the instructional innovation exposes students to social impact and innovation in an entrepreneurial setting, provides an opportunity for rich engagements with social and micro-entrepreneurs, and facilitates connection with self and others. Reflexive assignments and dialogues are integrated throughout the instructional innovation allowing students to identify and reflect on their aspirations and intentions for creating societal impact in their career journeys. Participation in this experience has resulted in outcomes related to career goals, including new plans for building social impact into work and renewed social entrepreneurial intentions. Instructions, exercises, and evidence of their effectiveness are provided.

This paper describes the use of mural-making as part of the knowledge mobilization activities of an international research partnership project. The mural depicts the technical and academic activities of people with disabilities in a university setting as meaningful action in inclusive research processes. The main objective of this 30-meter mural painting on a wall in the University of Bamenda was to demonstrate that inclusive research could encourage the inclusion and participation of people with disabilities in all areas of academic and professional activities of the university. A mural-making protocol was developed by the faculty and implemented by the team. It included the collection, analysis, and understanding of data on inclusion; design of drawings and the mural; wall preparation; plotting; and execution of the actual mural. The brightly colored mural now draws attention to inclusion, provides a vision of hopefulness, and complements the narrative character of inclusive education and research on campus.

Abstract Background Ethnicity is known to be an important correlate of health outcomes, particularly during the COVID-19 pandemic, where some ethnic groups were shown to be at higher risk of infection and adverse outcomes. The recording of patients’ ethnic groups in primary care can support research and efforts to achieve equity in service provision and outcomes; however, the coding of ethnicity is known to present complex challenges. We therefore set out to describe ethnicity coding in detail with a view to supporting the use of this data in a wide range of settings, as part of wider efforts to robustly describe and define methods of using administrative data. Methods We describe the completeness and consistency of primary care ethnicity recording in the OpenSAFELY-TPP database, containing linked primary care and hospital records in > 25 million patients in England. We also compared the ethnic breakdown in OpenSAFELY-TPP with that of the 2021 UK census. Results 78.2% of patients registered in OpenSAFELY-TPP on 1 January 2022 had their ethnicity recorded in primary care records, rising to 92.5% when supplemented with hospital data. The completeness of ethnicity recording was higher for women than for men. The rate of primary care ethnicity recording ranged from 77% in the South East of England to 82.2% in the West Midlands. Ethnicity recording rates were higher in patients with chronic or other serious health conditions. For each of the five broad ethnicity groups, primary care recorded ethnicity was within 2.9 percentage points of the population rate as recorded in the 2021 Census for England as a whole. For patients with multiple ethnicity records, 98.7% of the latest recorded ethnicities matched the most frequently coded ethnicity. Patients whose latest recorded ethnicity was categorised as Other were most likely to have a discordant ethnicity recording (32.2%). Conclusions Primary care ethnicity data in OpenSAFELY is present for over three quarters of all patients, and combined with data from other sources can achieve a high level of completeness. The overall distribution of ethnicities across all English OpenSAFELY-TPP practices was similar to the 2021 Census, with some regional variation. This report identifies the best available codelist for use in OpenSAFELY and similar electronic health record data.

Abstract Motivation Data is increasingly used for improvement and research in public health, especially administrative data such as that collected in electronic health records. Patients enter and exit these typically open-cohort datasets non-uniformly; this can render simple questions about incidence and prevalence time-consuming and with unnecessary variation between analyses. We therefore developed methods to automate analysis of incidence and prevalence in open cohort datasets, to improve transparency, productivity and reproducibility of analyses. Implementation We provide both a code-free set of rules for incidence and prevalence that can be applied to any open cohort, and a python Command Line Interface implementation of these rules requiring python 3.9 or later. General features The Command Line Interface is used to calculate incidence and point prevalence time series from open cohort data. The ruleset can be used in developing other implementations or can be rearranged to form other analytical questions such as period prevalence. Availability The command line interface is freely available from https://github.com/THINKINGGroup/analogy_publication .

Abstract To navigate our complex social world, it is crucial to deploy multiple learning strategies, such as learning from directly experiencing action outcomes or from observing other people’s behavior. Despite the prevalence of experiential and observational learning in humans and other social animals, it remains unclear how people favor one strategy over the other depending on the environment, and how individuals vary in their strategy use. Here, we describe an arbitration mechanism in which the prediction errors associated with each learning strategy influence their weight over behavior. We designed an online behavioral task to test our computational model, and found that while a substantial proportion of participants relied on the proposed arbitration mechanism, there was some meaningful heterogeneity in how people solved this task. Four other groups were identified: those who used a fixed mixture between the two strategies, those who relied on a single strategy and non-learners with irrelevant strategies. Furthermore, groups were found to differ on key behavioral signatures, and on transdiagnostic symptom dimensions, in particular autism traits and anxiety. Together, these results demonstrate how large heterogeneous datasets and computational methods can be leveraged to better characterize individual differences.

Introduction: Polycystic ovary syndrome (PCOS) is a widespread endocrine disorder that affects millions of women globally. The conventional approach to managing PCOS involves dietary adjustments, lifestyle modifications, pharmacological interventions, and in some cases, surgical procedures. This comprehensive review is dedicated to exploring novel treatment options for PCOS, with a specific focus on physical modalities, herbal approaches, holistic therapies, medical procedures, bacteriotherapeutics, and supplements. Method: To conduct this review, a systematic literature search was carried out up to 2023, utilizing reputable databases such as PubMed, Embase, Google Scholar, and the Cochrane Library. The search identified 33 key articles meeting the inclusion criteria, which encompassed both animal and human studies concentrating on PCOS and innovative interventions. The primary emphasis during the evaluation was on efficacy and safety. The articles were organized into six distinct groups: holistic therapies, herbal and natural approaches, physical modalities, medical procedures, bacteriotherapeutics, and supplements. Quality assessment involved the use of the Cochrane risk-of-bias tool and Assessment of Multiple Systematic Reviews (AMSTAR) 2. Results: The review unveiled a spectrum of interventions, ranging from acupuncture, yoga, and herbal remedies to high-intensity ultrasound, ultrasound cavitation, probiotics, fecal microbiota transplantation, and supplements. While some interventions exhibited promising results, conflicting reports and uncertainties persisted. Notably, positive effects on insulin resistance and androgen levels were observed with supplements. The intricate nature of PCOS treatments underscores the need for evidence-based strategies. Conclusion: While noninvasive and natural treatments show promise in the management of PCOS, rigorous research is indispensable to evaluate their long-term safety and optimal clinical utilization. The integration of lifestyle changes, conventional therapies and novel treatments, presents a potential avenue for a comprehensive and effective approach to treating PCOS, offering hope to millions of affected women worldwide. Caution is advised in the emerging realm of alternative treatments, and consulting health care professionals for informed decision-making in PCOS management continues to be strongly recommended.

Background: Breast cancer (BC) is frequently diagnosed among Canadian women. While targeted therapies are available for most BC patients; treatment resistance is common and novel therapeutic targets are of interest. Thyroid hormones (TH) bound to thyroid hormone receptors (THR) influence cell proliferation and differentiation; they are also involved in the growth and development of normal breast tissue. Evidence suggests that THRβ is a tumor suppressor in various solid tumors. Purpose: This narrative review discusses retrospective studies regarding the clinical relevance of THRβ as a potential prognostic biomarker and therapeutic target in BC. Methods: We consulted with an information specialist to develop a search strategy to find all literature related to THRα expression as a potential prognostic and therapeutic biomarker in breast cancer. The primary search was developed for Medline and translated to Embase. The searches were conducted on the Ovid platform on 18 August 2023. Results: Across seven retrospective studies identified, several have shown an association between higher THRβ1 expression with a lower risk of BC recurrence and with longer overall survival. Conclusions: Some evidence suggests that THRβ expression is associated with a lower risk of BC recurrence and death. Validation of THRβ as an independent prognostic biomarker and possible predictive biomarker of response to endocrine therapy and/or chemotherapy is of interest. Given that THRβ is upstream of the AKT/PI3K pathway, its potential as a predictive biomarker of response to AKT inhibitors and/or PI3K inhibitors may also be of value. Finally, the potential re-purposing of THRβ agonists as anti-cancer agents warrants investigation.

Abstract Background Organophosphorus pesticides (OP) have been associated with various human health conditions. Animal experiments and in-vitro models suggested that OP may also affect the gut microbiota. We examined associations between ambient chronic exposure to OP and gut microbial changes in humans. Methods We recruited 190 participants from a community-based epidemiologic study of Parkinson’s disease living in a region known for heavy agricultural pesticide use in California. Of these, 61% of participants had Parkinson’s disease and their mean age was 72 years. Microbiome and predicted metagenome data were generated by 16S rRNA gene sequencing of fecal samples. Ambient long-term OP exposures were assessed using pesticide application records combined with residential addresses in a geographic information system. We examined gut microbiome differences due to OP exposures, specifically differences in microbial diversity based on the Shannon index and Bray–Curtis dissimilarities, and differential taxa abundance and predicted Metacyc pathway expression relying on regression models and adjusting for potential confounders. Results OP exposure was not associated with alpha or beta diversity of the gut microbiome. However, the predicted metagenome was sparser and less evenly expressed among those highly exposed to OP (p = 0.04). Additionally, we found that the abundance of two bacterial families, 22 genera, and the predicted expression of 34 Metacyc pathways were associated with long-term OP exposure. These pathways included perturbed processes related to cellular respiration, increased biosynthesis and degradation of compounds related to bacterial wall structure, increased biosynthesis of RNA/DNA precursors, and decreased synthesis of Vitamin B1 and B6. Conclusion In support of previous animal studies and in-vitro findings, our results suggest that ambient chronic OP pesticide exposure alters gut microbiome composition and its predicted metabolism in humans.

Parkinson's disease (PD) is a complex neurodegenerative disease with etiology rooted in genetic vulnerability and environmental factors. Here we combine quantitative epidemiologic study of pesticide exposures and PD with toxicity screening in dopaminergic neurons derived from PD patient induced pluripotent stem cells (iPSCs) to identify Parkinson's-relevant pesticides. Agricultural records enable investigation of 288 specific pesticides and PD risk in a comprehensive, pesticide-wide association study. We associate long-term exposure to 53 pesticides with PD and identify co-exposure profiles. We then employ a live-cell imaging screening paradigm exposing dopaminergic neurons to 39 PD-associated pesticides. We find that 10 pesticides are directly toxic to these neurons. Further, we analyze pesticides typically used in combinations in cotton farming, demonstrating that co-exposures result in greater toxicity than any single pesticide. We find trifluralin is a driver of toxicity to dopaminergic neurons and leads to mitochondrial dysfunction. Our paradigm may prove useful to mechanistically dissect pesticide exposures implicated in PD risk and guide agricultural policy.

Background The COVID-19 pandemic disrupted cardiovascular disease management in primary care in England.Objective To describe the impact of the pandemic on blood pressure screening and hypertension management based on a national quality of care scheme (Quality and Outcomes Framework, QOF) across key demographic, regional and clinical subgroups.Methods With NHS England approval, a population-based cohort study was conducted using OpenSAFELY-TPP on 25.2 million NHS patients registered at general practices (March 2019 to March 2023). We examined monthly changes in recorded blood pressure screening in the preceding 5 years in patients aged ≥45 years and recorded the hypertension prevalence and the percentage of patients treated to target (≤140/90 mmHg for patients aged ≤79 years and ≤150/90 mmHg for patients aged ≥80 years) in the preceding 12 months.Results The percentage of patients aged ≥45 years who had blood pressure screening recorded in the preceding 5 years decreased from 90% (March 2019) to 85% (March 2023). Recorded hypertension prevalence was relatively stable at 15% throughout the study period. The percentage of patients with a record of hypertension treated to target in the preceding 12 months reduced from a maximum of 71% (March 2020) to a minimum of 47% (February 2021) in patients aged ≤79 years and from 85% (March 2020) to a minimum of 58% (February 2021) in patients aged ≥80 years before recovery. Blood pressure screening rates in the preceding 5 years remained stable in older people, patients with recorded learning disability or care home status.Conclusions The pandemic substantially disrupted hypertension management QOF indicators, which is likely attributable to general reductions of blood pressure measurement including screening. OpenSAFELY can be used to continuously monitor changes in national quality-of-care schemes to identify changes in key clinical subgroups early and support prioritisation of recovery from care disrupted by COVID-19.

Objective To investigate the effect of the covid-19 pandemic on the number of patients with group A streptococcal infections and related antibiotic prescriptions.Design Retrospective cohort study in England using OpenSAFELY-TPP.Setting Primary care practices in England that used TPP SystmOne software, 1 January 2018 to 31 March 2023, with the approval of NHS England.Participants Patients registered at a TPP practice at the start of each month of the study period. Patients with missing data for sex or age were excluded, resulting in a population of 23 816 470 in January 2018, increasing to 25 541 940 by March 2023.Main outcome measures Monthly counts and crude rates of patients with group A streptococcal infections (sore throat or tonsillitis, scarlet fever, and invasive group A streptococcal infections), and recommended firstline, alternative, and reserved antibiotic prescriptions linked with a group A streptococcal infection before (pre-April 2020), during, and after (post-April 2021) covid-19 restrictions. Maximum and minimum count and rate for each infectious season (time from September to August), as well as the rate ratio of the 2022-23 season compared with the last comparably high season (2017-18).Results The number of patients with group A streptococcal infections, and antibiotic prescriptions linked to an indication of group A streptococcal infection, peaked in December 2022, higher than the peak in 2017-18. The rate ratios for monthly sore throat or tonsillitis (possible group A streptococcal throat infection), scarlet fever, and invasive group A streptococcal infection in 2022-23 relative to 2017-18 were 1.39 (95% confidence interval (CI) 1.38 to 1.40), 2.68 (2.59 to 2.77), and 4.37 (2.94 to 6.48), respectively. The rate ratio for prescriptions of first line, alternative, and reserved antibiotics to patients with group A streptococcal infections in 2022-23 relative to 2017-18 were 1.37 (95% CI 1.35 to 1.38), 2.30 (2.26 to 2.34), and 2.42 (2.24 to 2.61), respectively. For individual antibiotic prescriptions in 2022-23, azithromycin showed the greatest relative increase versus 2017-18, with a rate ratio of 7.37 (6.22 to 8.74). This finding followed a marked decrease in the recording of patients with group A streptococcal infections and associated prescriptions during the period of covid-19 restrictions where the maximum count and rates were lower than any minimum rates before the covid-19 pandemic.Conclusions Recording of rates of scarlet fever, sore throat or tonsillitis, and invasive group A streptococcal infections, and associated antibiotic prescribing, peaked in December 2022. Primary care data can supplement existing infectious disease surveillance through linkages with relevant prescribing data and detailed analysis of clinical and demographic subgroups.

Objectives Long-term sickness absence from employment has negative consequences for the economy and can lead to widened health inequalities. Sick notes (also called ‘fit notes’) are issued by general practitioners when a person cannot work for health reasons for more than 7 days. We quantified the sick note rate in people with evidence of COVID-19 in 2020, 2021 and 2022, as an indication of the burden for people recovering from COVID-19.Design Cohort study.Setting With National Health Service (NHS) England approval, we used routine clinical data (primary care, hospital and COVID-19 testing records) within the OpenSAFELY-TPP database.Participants People 18–64 years with a recorded positive test or diagnosis of COVID-19 in 2020 (n=365 421), 2021 (n=1 206 555) or 2022 (n=1 321 313); general population matched in age, sex and region in 2019 (n=3 140 326), 2020 (n=3 439 534), 2021 (n=4 571 469) and 2022 (n=4 818 870); people hospitalised with pneumonia in 2019 (n=29 673).Primary outcome measure Receipt of a sick note in primary care.Results Among people with a positive SARS-CoV-2 test or COVID-19 diagnosis, the sick note rate was 4.88 per 100 person-months (95% CI 4.83 to 4.93) in 2020, 2.66 (95% CI 2.64 to 2.67) in 2021 and 1.73 (95% CI 1.72 to 1.73) in 2022. Compared with the age, sex and region-matched general population, the adjusted HR for receipt of a sick note over the entire follow-up period (up to 10 months) was 4.07 (95% CI 4.02 to 4.12) in 2020 decreasing to 1.57 (95% CI 1.56 to 1.58) in 2022. The HR was highest in the first 30 days postdiagnosis in all years. Among people hospitalised with COVID-19, after adjustment, the sick note rate was lower than in people hospitalised with pneumonia.Conclusions Given the under-recording of postacute COVID-19-related symptoms, these findings contribute a valuable perspective on the long-term effects of COVID-19. Despite likely underestimation of the sick note rate, sick notes were issued more frequently to people with COVID-19 compared with those without, even in an era when most people are vaccinated. Most sick notes occurred in the first 30 days postdiagnosis, but the increased risk several months postdiagnosis may provide further evidence of the long-term impact.

BACKGROUND: Pesticide exposure has consistently been associated with Parkinsons disease (PD) onset. Yet, fewer epidemiologic studies have examined whether pesticides influence PD motor and non-motor symptom progression. OBJECTIVES: Using a geographic information system tool that integrates agricultural pesticide use reports and land use records to derive ambient exposures at residences and workplaces, we assessed associations between specific pesticides previously related to PD onset with PD symptom progression in two PD patient cohorts living in agricultural regions of California. METHODS: We calculated the pounds of pesticide applied agriculturally near each participants residential or occupational addresses from 1974 to the year of PD diagnosis, using a geographic information system tool that links the California Pesticide Use Reports database to land use data. We examined 53 pesticides selected a priori as they have previously been associated with PD onset. We longitudinally followed two PD patient cohorts (PEG1 N = 242, PEG2 N = 259) for an average of 5.0 years (SD ± 3.5) and 2.7 years (SD ± 1.6) respectively and assessed PD symptoms using the movement disorder specialist-administered Unified Parkinsons disease Rating Scale part III (UPDRS), Mini-Mental State Examination (MMSE), and Geriatric Depression Scale (GDS). Weighted time-to-event regression models were implemented to estimate effects. RESULTS: Ten agricultural pesticides, including copper sulfate (pentahydrate), 2-methyl-4-chlorophenoxyacetic acid (MCPA) dimethylamine salt, tribufos, sodium cacodylate, methamidophos, ethephon, propargite, bromoxynil octanoate, monosodium methanearsonate (MSMA), and dicamba, were associated with faster symptom progression. Among these pesticides, residential or workplace proximity to higher amounts of copper sulfate (pentahydrate) and MCPA (dimethylamine salt) was associated with all three progression endpoints (copper sulfate: HRs = 1.22-1.36, 95 % CIs = 1.03-1.73; MCPA: HRs = 1.27-1.35, 95 % CIs = 1.02-1.70). CONCLUSIONS: Our findings suggest that pesticide exposure may not only be relevant for PD onset but also PD progression phenotypes. We have implicated ten specific pesticide active ingredients in faster PD motor and non-motor decline.

We show how to reduce the computational time of the practical implementation of the Raviart-Thomas mixed method for second-order elliptic problems. The implementation takes advantage of a recent result which states that certain local subspaces of the vector unknown can be eliminated from the equations by transforming them into stabilization functions; see the paper published online in JJIAM on August 10, 2023. We describe in detail the new implementation (in MATLAB and a laptop with Intel(R) Core (TM) i7-8700 processor which has six cores and hyperthreading) and present numerical results showing 10 to 20% reduction in the computational time for the Raviart-Thomas method of index $ k $, with $ k $ ranging from 1 to 20, applied to a model problem.

Abstract The value and uncertainty associated with choice alternatives constitute critical features relevant for decisions. However, the manner in which reward and risk representations are temporally organized in the brain remains elusive. Here we leverage the spatiotemporal precision of intracranial electroencephalography, along with a simple card game designed to elicit the unfolding computation of a set of reward and risk variables, to uncover this temporal organization. Reward outcome representations across wide-spread regions follow a sequential order along the anteroposterior axis of the brain. In contrast, expected value can be decoded from multiple regions at the same time, and error signals in both reward and risk domains reflect a mixture of sequential and parallel encoding. We further highlight the role of the anterior insula in generalizing between reward prediction error and risk prediction error codes. Together our results emphasize the importance of neural dynamics for understanding value-based decisions under uncertainty.

Background: Examining lung cancer (LC) cases in Virginia (VA) is essential due to its significant public health implications. By studying demographic, environmental, and socioeconomic variables, this paper aims to provide insights into the underlying drivers of LC prevalence in the state adjusted for spatial associations at the zipcode level. Methods: We model the available VA zipcode-level LC counts via (spatial) Poisson and negative binomial regression models, taking into account missing covariate data, zipcode-level spatial association and allow for overdispersion. Under latent Gaussian Markov Random Field (GMRF) assumptions, our Bayesian hierarchical model powered by Integrated Nested Laplace Approximation (INLA) considers simultaneous (spatial) imputation of all missing covariates through elegant prediction. The spatial random effect across zip codes follows a Conditional Autoregressive (CAR) prior. Results: Zip codes with elevated smoking indices demonstrated a corresponding increase in LC counts, underscoring the well-established connection between smoking and LC. Additionally, we observed a notable correlation between higher Social Deprivation Index (SDI) scores and increased LC counts, aligning with the prevalent pattern of heightened LC prevalence in regions characterized by lower income and education levels. On the demographic level, our findings indicated higher LC counts in zip codes with larger White and Black populations (with Whites having higher prevalence than Blacks), lower counts in zip codes with higher Hispanic populations (compared to non-Hispanics), and higher prevalence among women compared to men. Furthermore, zip codes with a larger population of elderly people (age ≥ 65 years) exhibited higher LC prevalence, consistent with established national patterns. Conclusions: This comprehensive analysis contributes to our understanding of the complex interplay of demographic and socioeconomic factors influencing LC disparities in VA at the zip code level, providing valuable information for targeted public health interventions and resource allocation. Implementation code is available at GitHub.

ABSTRACTThe need for more attention to the social and human dimensions in global change sciences and natural resources management requires in-depth understandings of transformative approaches and processes. More inclusive and systemic approaches are needed that embrace complexity and support transformative learning, shifts in power relations, collective and relational agency and structural transformations for adaptive and innovative governance. Scientific understanding of how such change can be brought about is still limited. In this paper, which sets the scene for this Special Issue, we develop a conceptual framework for analyzing transformative processes across a range of diverse cases. Aspects of the conceptual framework are applied, tested and elaborated in three following papers in the Special Issue, deepening understanding of how transformative change in complex social-ecological systems may originate at nexus boundary zones such as that portrayed by the water-food-energy nexus. Specifically, the paper conceptually elaborates four iteratively related dynamics of transformative learning, transforming power relations, transformative agency and transforming structures which intersect in transformation processes. The perspectives offer tools for cross case analysis in the longer term, but also tools for supporting co-engaged, generative research processes.