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This multi-methods investigation was conducted to examine the experiences of preservice and in-service elementary teachers (n=11) from rural and American Indian Reservation communities who participated in an NSF-funded Research Experience for Teachers (RET), a summer residential research-focused professional development experience. The primary intent of the professional development was to build elementary teachers' self-efficacy in the design and implementation of community-centered and culturally responsive engineering education curricula. Over six weeks, teachers participated in energy-related research experiences in campus engineering laboratories while simultaneously developing engineering curricula for their elementary classrooms that focused on energy, a cross-cutting elementary topic. Results indicate that teachers showed significant gains in personal teaching efficacy beliefs in science and engineering. Findings also suggest that participating teachers felt significantly more comfortable teaching engineering post-program compared to pre-program. Quantitative results from this study align with the qualitative findings and indicate that the experience positively impacted teachers' capacities to teach engineering and integrate culturally responsive practices. Results also help identify specific attributes of the experience that contributed to their professional learning. Findings from this study contribute to the refinement of theories on teacher self-efficacy in engineering education and help guide future professional development efforts that foster inclusive student engineering identity formation within their classrooms.

This large-scale survey study examined how teachers select and integrate global and culturally diverse children's and young adult literature for their classrooms. Results from the survey captured self-reports of the selection process, suggesting if and how teachers were selecting and integrating this literature and reflecting possible influence from children's and young adult literature courses taken in teacher preparation programs. Taking general children's and young adult literature courses, and specific courses on diverse literature and global literature was found to be related to teachers' responses to questions centered on selecting, evaluating, and integrating global and culturally diverse literature. These courses may be pivotal to increase the needed integration of global and culturally diverse children's and young adult literature into secondary and elementary classroom instruction.

This study presents data from a large-scale Before After Control Impact (BACI) design field experiment that measured the sediment reduction achieved by remediating large alluvial gullies. The study was carried out on Bonnie Doon Creek on the lower Burdekin River, in Queensland Australia. Prior to remediation, the four large alluvial gully complexes (active area of ∼17ha) were conservatively estimated to be delivering 5800 ± 1500 t of fine sediment (

Abstract Background To validate the clinical utility of a previously identified circulating tumor DNA methylation marker (meth-ctDNA) panel for disease detection and survival outcomes, meth-ctDNA markers were compared to PSA levels and PSMA PET/CT findings in men with different stages of prostate cancer (PCa). Methods 122 PCa patients who underwent [⁶⁸Ga]Ga-PSMA-11 PET/CT and plasma sampling (03/2019–08/2021) were analyzed. cfDNA was extracted, and a panel of 8 individual meth-ctDNA markers was queried. PET scans were qualitatively and quantitatively assessed. PSA and meth-ctDNA markers were compared to PET findings, and their relative prognostic value was evaluated. Results PSA discriminated best between negative and tumor-indicative PET scans in all (AUC 0.77) and hormone-sensitive (hsPC) patients (0.737). In castration-resistant PCa (CRPC), the meth-ctDNA marker KLF8 performed best (AUC 0.824). CHST11 differentiated best between non- and metastatic scans (AUC 0.705) overall, KLF8 best in hsPC and CRPC (AUC 0.662, 0.85). Several meth-ctDNA markers correlated low to moderate with the tumor volume in all (5/8) and CRPC patients (6/8), while PSA levels correlated moderately to strongly with the tumor volume in all groups (all p

The Marysvale volcanic field in southwestern Utah hosts three large-volume gravity slides: the Sevier (SGS), the Markagunt (MGS), and the Black Mountains (BGS). The gravity slides are composed of lahar deposits, lava flows, and ash-flow tuffs erupted from former stratovolcanoes and other vents during the Oligocene and Miocene. The ash-flow tuffs are prime targets for dating to constrain the age of the gravity slides because some ash-flow tuffs are deformed within the slides, whereas others are undeformed and cap the slides. Furthermore, the gravity slides produced pseudotachylyte during slide motion, a direct indicator for the timing of each slide. This work provides new 40Ar/39Ar dates for several ash-flow tuffs and pseudotachylyte for the SGS, along with U/Pb zircon dates for one deformed tuff and alluvium near the slide plane. Results show that the slide was emplaced at 25.25 ± 0.05 Ma and was immediately followed by the eruption of the Antimony Tuff at 25.19 ± 0.02 Ma. The model presented here suggests that the intrusion of magma related to the Antimony Tuff acted as a triggering mechanism for the slide and that slide movement itself led to decompression melting and eruption of the Antimony Tuff. This sequence of events occurred on a geologically rapid timescale and may have been virtually instantaneous.

Abstract Flooding is a pervasive natural hazard with wide-ranging impacts on society. Using a high-resolution global flood model considering coastal, fluvial, and pluvial hazards, we clarify the role of climate effects versus population growth effects in changing flood exposure. Between 2020 and 2100, the population likely exposed to 1% annual risk (100-year) flood hazard will increase from 1.6 to 1.9 billion people. Of this change from the 2020 exposure, we attribute 21.1% to climate change, 76.8% to population change, and 2.1% to both climate and population change. The largest driver of uncertainty in exposure is population change, while climate change remains a smaller but still important driver. The global increase in exposure between 2020 and 2100 is primarily driven by low-GDP regions, and by 2100 the lowest GDP areas will make up 63% of the exposure both overall and in urban areas. Urban areas are especially vulnerable in nearly all global regions, and urban areas sensitive to extreme events are expected to see a 33% increase in population exposure. This study highlights the vast inequities in flood exposure, and future work should direct resources and strategies toward sustainable risk mitigation in these areas.

Abstract Aim The combination of positron emission tomography (PET) and magnetic resonance imaging (MRI) provides an innovation leap in the use of fertilized chicken eggs (in ovo model) in preclinical imaging as PET/MRI enables the investigation of the chick embryonal organ-specific distribution of PET-tracers. However, hybrid PET/MRI inheres technical challenges in quantitative in ovo PET such as attenuation correction (AC) for the object as well as for additional hardware parts present in the PET field-of-view, which potentially contribute to quantification biases in the PET images if not accounted for. This study aimed to investigate the influence of the different sources of attenuation on in ovo PET/MRI and assess the accuracy of MR-based AC for in ovo experiments. Method An in-house made chicken egg phantom was used to investigate the magnitude of self-attenuation and the influence of the MRI hardware on the PET signal. The phantom was placed in a preclinical PET/MRI system and PET acquisitions were performed without, and after subsequently adding the different hardware parts to the setup. Reconstructions were performed without any AC for the different setups and with subsequently incorporating the hardware parts into the AC. In addition, in ovo imaging was performed using [18F]FDG and [68Ga]Ga-Pentixafor, and PET data was reconstructed with the different AC combinations. Quantitative accuracy was assessed for the phantom and the in ovo measurements. Results In general, not accounting for the self-attenuation of the egg and the hardware parts caused an underestimation of the PET signal of around 49% within the egg. Accounting for all sources of attenuation allowed a proper quantification with global offsets of 2% from the true activity. Quantification based on % injected dose per cc (%ID/cc) was similar for the in ovo measurements, regardless of whether hardware parts were included in AC or not, when the injected activity was extracted from the PET images. However, substantial quantification biases were found when the self-attenuation of the egg was not taken into account. Conclusion Self-attenuation of the egg and PET signal attenuation within the hardware parts of the MRI substantially influence quantitative accuracy in in ovo measurements. However, when compensating for the self-attenuation of the egg by a respective AC, a reliable quantification using %ID/cc can be performed even if not accounting for the attenuation of the hardware parts.

Abstract Gut microbiota affect transplantation outcomes; however, the influence of immunosuppression and cell therapy on the gut microbiota in cardiovascular care remains unexplored. We investigated gut microbiota dynamics in a nonhuman primate (NHP) cardiac ischemia/reperfusion model while under immunosuppression and receiving cell therapy with human induced pluripotent stem cell (hiPSC)-derived endothelial cells (EC) and cardiomyocytes (CM). Both immunosuppression and EC/CM co-treatment increased gut microbiota alpha diversity. Immunosuppression promoted anaerobes, such as Faecalibacterium, Streptococcus, Anaerovibrio and Dialister, and altered amino acid metabolism and nucleosides/nucleotides biosynthesis in host plasma. EC + CM cotreatment favors Phascolarctobacterium, Fusicatenibacter, Erysipelotrichaceae UCG-006, Veillonella and Mailhella. Remarkably, gut microbiota of the EC/CM co-treatment group resembled that of the pre-injury group, and the NHPs exhibited a metabolic shift towards amino acid and fatty acid/lipid biosynthesis in plasma following cell therapy. The interplay between shift in microbial community and host homeostasis during treatment suggests gut microbiome modulation could improve cell therapy outcomes.

Abstract Background Poly (ADP-ribose) polymerase (PARP) enzymes are crucial for the repair of DNA single-strand breaks and have become key therapeutic targets in homologous recombination-deficient cancers, including prostate cancer. To enable non-invasive monitoring of PARP-1 expression, several PARP-1-targeting positron emission tomography (PET) tracers have been developed. Here, we aimed to preclinically investigate [carbonyl-11C]DPQ as an alternative PARP-1 PET tracer as it features a strongly distinct chemotype compared to the frontrunners [18F]FluorThanatrace and [18F]PARPi. Results [carbonyl-11C]DPQ was synthesised in a GE TracerLab FXC2 module, yielding sufficient activity (940 ± 410 MBq), molar activity (53 ± 16 GBq/µmol) and radiochemical purity (> 97%) for subsequent preclinical evaluation. [carbonyl-11C]DPQ showed high stability in formulation, in human plasma, and when incubated with human liver microsomes. In vitro, similar specific uptake was observed in both PC3 prostate cancer cells and CHO-K1 Chinese hamster ovary cells. However, in vivo studies using fertilised chicken eggs (in ovo model) revealed poor and non-displaceable tumour accumulation in PC3-derived xenografts, despite confirmed vascularisation and PARP-1 expression. Rapid uptake was observed in the liver (10 min), with less than 30% of the intact compound remaining in the liver 70 min post-injection. Conclusions Although [carbonyl-11C]DPQ demonstrated metabolic stability and specific binding in vitro, suboptimal tumour-targeting properties and pronounced liver metabolism were observed in ovo. Therefore, further animal experiments with mammalian models were not indicated.

Abstract As camera trapping grows in popularity and application, some analytical limitations persist including processing time and accuracy of data annotation. Typically images are recorded by camera traps although videos are becoming increasingly collected even though they require much more time for annotation. To overcome limitations with image annotation, camera trap studies are increasingly linked to community science (CS) platforms. Here, we extend previous work on CS image annotations to camera trap videos from a challenging environment; a dense tropical forest with low visibility and high occlusion due to thick canopy cover and bushy undergrowth at the camera level. Using the CS platform Chimp&See, established for classification of 599 956 video clips from tropical Africa, we assess annotation precision and accuracy by comparing classification of 13 531 1‐min video clips by a professional ecologist (PE) with output from 1744 registered, as well as unregistered, Chimp&See community scientists. We considered 29 classification categories, including 17 species and 12 higher‐level categories, in which phenotypically similar species were grouped. Overall, annotation precision was 95.4%, which increased to 98.2% when aggregating similar species groups together. Our findings demonstrate the competence of community scientists working with camera trap videos from even challenging environments and hold great promise for future studies on animal behaviour, species interaction dynamics and population monitoring.

Abstract Objectives Radical prostatectomy (RP) is a common intervention in patients with localized prostate cancer (PCa), with nerve-sparing RP recommended to reduce adverse effects on patient quality of life. Accurate pre-operative detection of extraprostatic extension (EPE) remains challenging, often leading to the application of suboptimal treatment. The aim of this study was to enhance pre-operative EPE detection through multimodal data integration using explainable machine learning (ML). Methods Patients with newly diagnosed PCa who underwent [68Ga]Ga-PSMA-11 PET/MRI and subsequent RP were recruited retrospectively from two time ranges for training, cross-validation, and independent validation. The presence of EPE was measured from post-surgical histopathology and predicted using ML and pre-operative parameters, including PET/MRI-derived features, blood-based markers, histology-derived parameters, and demographic parameters. ML models were subsequently compared with conventional PET/MRI-based image readings. Results The study involved 107 patients, 59 (55%) of whom were affected by EPE according to postoperative findings for the initial training and cross-validation. The ML models demonstrated superior diagnostic performance over conventional PET/MRI image readings, with the explainable boosting machine model achieving an AUC of 0.88 (95% CI 0.87–0.89) during cross-validation and an AUC of 0.88 (95% CI 0.75–0.97) during independent validation. The ML approach integrating invasive features demonstrated better predictive capabilities for EPE compared to visual clinical read-outs (Cross-validation AUC 0.88 versus 0.71, p = 0.02). Conclusion ML based on routinely acquired clinical data can significantly improve the pre-operative detection of EPE in PCa patients, potentially enabling more accurate clinical staging and decision-making, thereby improving patient outcomes. Critical relevance statement This study demonstrates that integrating multimodal data with machine learning significantly improves the pre-operative detection of extraprostatic extension in prostate cancer patients, outperforming conventional imaging methods and potentially leading to more accurate clinical staging and better treatment decisions. Key Points Extraprostatic extension is an important indicator guiding treatment approaches. Current assessment of extraprostatic extension is difficult and lacks accuracy. Machine learning improves detection of extraprostatic extension using PSMA-PET/MRI and histopathology. Graphical Abstract

Abstract Background Cancer‐associated cachexia (CAC) is a metabolic syndrome contributing to therapy resistance and mortality in lung cancer patients (LCP). CAC is typically defined using clinical non‐imaging criteria. Given the metabolic underpinnings of CAC and the ability of [18F]fluoro‐2‐deoxy‐D‐glucose (FDG)‐positron emission tomography (PET)/computer tomography (CT) to provide quantitative information on glucose turnover, we evaluate the usefulness of whole‐body (WB) PET/CT imaging, as part of the standard diagnostic workup of LCP, to provide additional information on the onset or presence of CAC. Methods This multi‐centre study included 345 LCP who underwent WB [18F]FDG‐PET/CT imaging for initial clinical staging. A weight loss grading system (WLGS) adjusted to body mass index was used to classify LCP into ‘No CAC’ (WLGS‐0/1 at baseline prior treatment and at first follow‐up: N = 158, 51F/107M), ‘Dev CAC’ (WLGS‐0/1 at baseline and WLGS‐3/4 at follow‐up: N = 90, 34F/56M), and ‘CAC’ (WLGS‐3/4 at baseline: N = 97, 31F/66M). For each CAC category, mean standardized uptake values (SUV) normalized to aorta uptake () and CT‐defined volumes were extracted for abdominal and visceral organs, muscles, and adipose‐tissue using automated image segmentation of baseline [18F]FDG‐PET/CT images. Imaging and non‐imaging parameters from laboratory tests were compared statistically. A machine‐learning (ML) model was then trained to classify LCP as ‘No CAC’, ‘Dev CAC’, and ‘CAC’ based on their imaging parameters. SHapley Additive exPlanations (SHAP) analysis was employed to identify the key factors contributing to CAC development for each patient. Results The three CAC categories displayed multi‐organ differences in . In all target organs, was higher in the ‘CAC’ cohort compared with ‘No CAC’ (P in ‘CAC’ was reduced by 5%. The ‘Dev CAC’ cohort displayed a small but significant increase in of pancreas (+4%), skeletal‐muscle (+7%), subcutaneous adipose‐tissue (+11%), and visceral adipose‐tissue (+15%). In ‘CAC’ patients, a strong negative Spearman correlation (ρ = −0.8) was identified between and volumes of adipose‐tissue. The machine‐learning model identified ‘CAC’ at baseline with 81% of accuracy, highlighting of spleen, pancreas, liver, and adipose‐tissue as most relevant features. The model performance was suboptimal (54%) when classifying ‘Dev CAC’ versus ‘No CAC’. Conclusions WB [18F]FDG‐PET/CT imaging reveals groupwise differences in the multi‐organ metabolism of LCP with and without CAC, thus highlighting systemic metabolic aberrations symptomatic of cachectic patients. Based on a retrospective cohort, our ML model identified patients with CAC with good accuracy. However, its performance in patients developing CAC was suboptimal. A prospective, multi‐centre study has been initiated to address the limitations of the present retrospective analysis.

Introduction Global outbreaks involving mpox clade IIb began in mid-2022. Today, clade IIb and clade I outbreaks continue. Reliable mpox vaccines can prevent serious mpox disease and death.Areas covered Globally, two vaccines hold mpox indications, regardless of mpox viral clade: MVA-BN (Bavarian Nordic) and LC16m8 (KM Biologics). This review summarizes the human and pivotal animal data establishing safety and efficacy for MVA-BN and LC16m8, including real-world evidence gathered during mpox outbreaks from 2022 through 2024.Expert opinion Some regulatory decisions for MVA-BN and LC16m8 followed pathways based on surrogate outcomes, including lethal-challenge studies in nonhuman primates, among other atypical aspects. Nonetheless, MVA-BN and LC16m8 hold unencumbered registration in multiple countries. Effectiveness of MVA-BN as primary preventive vaccination (PPV) in humans against clade IIb mpox is clear from real-world studies; effectiveness of LC16m8 against clade IIb is likely from surrogate endpoints. Effectiveness of MVA-BN and LC16m8 as PPV against more-lethal clade I is likely, based on animal-challenge studies with multiple orthopoxvirus species and other studies. Both vaccines have solid safety records. MVA-BN’s replication incompetence favors adoption, whereas LC16m8 has more pediatric data. Additional real-world evidence, in additional geographic settings and special populations (e.g. pregnancy, immune suppression, atopic dermatitis), is needed.

Abstract Elite athletes are high-performance outliers within their specific sports. Even though science seeks to understand the nature of expertise and elite performance, much knowledge remains compartmentalized within subdisciplines. Despite this multidimensionality being acknowledged, an interdisciplinary approach to understanding elite athletes is still rare. This paper synthesizes insights across scientific domains in order to describe the population and individual characteristics of elite athletes. We analyzed diagnostic data from approximately 300 German squad athletes across eight different sports (e.g., gymnastics, volleyball, ice hockey, 3 × 3 basketball etc., agefemale = 18.95 ± 4.84 years, agemale = 19.32 ± 4.19 years) with expertise values ranging from 2 (low expertise) to 16 (high expertise). Data covered muscular strength, lower-body dynamics, muscle-power genetics, blood micronutrients, basic cognitive function, mental health, social support, and training conditions. Results of logistic regressions identified basic cognitive function (B = 0.89) and well-balanced blood micronutrients (B = 1.22) as critical factors distinguishing elite athletes. Additionally, multiple linear regressions suggested that lower-body dynamics (ß = 0.72) is related to increasing expertise values. We examined interactions between determinants of elite performance, and found that social support is positively associated with mental health and training conditions, whereas muscular strength correlates with lower-body dynamics. Focusing on top elite athletes in contrast to semi-elite athletes, we found higher within-group similarities in basic cognitive function and blood micronutrients. Findings indicate the need for a systemic, individualized, and comprehensive model using individual-based profiles.

Abstract Background Accurate pharmacokinetic modelling in PET necessitates measurements of an input function, which ideally is acquired non-invasively from image data. For hepatic pharmacokinetic modelling two input functions need to be considered, to account for the blood supply from the hepatic artery and portal vein. Image-derived measurements at the portal vein are challenging due to its small size and image artifacts caused by respiratory motion. In this work we seek to demonstrate, using phantom experiments, how a dedicated PET/MR protocol can tackle these challenges and potentially provide input function measurements of the portal vein in a clinical setup. Methods A custom 3D printed PET/MR phantom was constructed to mimic the liver and portal vein. PET/MR acquisitions were made with emulated respiratory motion. The PET/MR imaging protocol consisted of high-resolution anatomical MR imaging of the portal vein, followed by a PET acquisition in parallel to a dedicated motion-tracking MR sequence. Motion tracking and deformation information were extracted from PET data and subsequently used in PET reconstruction to produce dynamic series of motion-free PET images. Anatomical MR images were used post PET reconstruction for partial volume correction of the input function measurements. Results Reconstruction of dynamic PET data with motion-compensation provided nearly motion-free series of PET frame data, suitable for image derived input function measurements of the portal vein. After partial volume correction, the individual input function measurements were within a 16.1% error range from the true activity in the portal vein compartment at the time of PET acquisition. Conclusion The proposed protocol demonstrates clinically feasible PET/MR imaging of the liver for pharmacokinetic studies with accurate quantification of the portal vein input function, including correction for respiratory motion and partial volume effects.

It is critical to assess bushfire impact rapidly and accurately because bushfires play a significant role in forest degradation and present a threat to ecosystems and human lives. Over the past decades, several supervised algorithms of burn severity mapping have been proposed, facing the significant drawback of time-consuming labeling. Moreover, there is no robust framework for burn severity mapping through fusing multi-sensor, multi-resolution, and multi-temporal remote sensing imagery from satellite and aerial platforms. Therefore, this paper presents an unsupervised two-step pipeline: processing 2D data followed by 3D data for burn severity mapping, both of which are acquired from either aircraft or satellites. For the 2D data processing, our proposed unsupervised burned area detection (UsBA detection) model enhances burned area mapping accuracy by integrating Ultra-High Resolution (UHR) aerial imagery with bi-temporal medium-resolution PlanetScope imagery, using a Segment Anything Model (SAM)-assisted UNetFormer (pre-trained on the target-style public dataset – LoveDA Rural) for refinement. The model demonstrates superior burned area segmentation, evidenced by improved evaluation metrics calculated from labeled test sites. For the 3D analysis, the burned areas extracted from 2D processing are further assessed using pre- and post-event airborne laser data. We implement a voxel-based workflow, including necessary steps such as ground filtering through Superpoints in RANSAC Planes (SiRP) method and biomass change analysis. The results indicate that the 3D branch provides a reliable lower bound of the actual damage map, because the vegetation growth between two measurements remains, in essence, undetected. The proposed framework offers a more accurate and robust solution for burn severity mapping utilizing combined 2D and 3D data, evaluated on a multi-source dataset from a real bushfire event that occurred in Bushland Park, South Australia.

Abstract Background P-glycoprotein (P-gp) is an efflux transporter which is abundantly expressed at the blood-brain barrier (BBB) and which has been implicated in the pathophysiology of various brain diseases. The radiolabelled antiemetic drug [11C]metoclopramide is a P-gp substrate for positron emission tomography (PET) imaging of P-gp function at the BBB. To assess whether [11C]metoclopramide can detect increased P-gp function in the human brain, we employed drug-resistant temporal lobe epilepsy (TLE) as a model disease with a well characterised, regional P-gp up-regulation at the BBB. Methods Eight patients with drug-resistant (DRE) TLE, 5 seizure-free patients with drug-sensitive (DSE) focal epilepsy, and 15 healthy subjects underwent brain PET imaging with [11C]metoclopramide on a fully-integrated PET/MRI system. Concurrent with PET, arterial blood sampling was performed to generate a metabolite-corrected arterial plasma input function for kinetic modelling. The choroid plexus was outmasked on the PET images to remove signal contamination from the neighbouring hippocampus. Using a brain atlas, 10 temporal lobe sub-regions were defined and analysed with a 1-tissue-2-rate constant compartmental model to estimate the rate constants for radiotracer transfer from plasma to brain (K 1) and from brain to plasma (k 2), and the total volume of distribution (V T = K 1/k 2). Results DRE patients but not DSE patients showed significantly higher k 2 values and a trend towards lower V T values in several temporal lobe sub-regions located ipsilateral to the epileptic focus as compared to healthy subjects (k 2: hippocampus: +34%, anterior temporal lobe, medial part: +28%, superior temporal gyrus, posterior part: +21%). Conclusions [11C]Metoclopramide PET can detect a seizure-induced P-gp up-regulation in the epileptic brain. The efflux rate constant k 2 seems to be the most sensitive parameter to measure increased P-gp function with [11C]metoclopramide. Our study provides evidence that disease-induced alterations in P-gp expression at the BBB can lead to changes in the distribution of a central nervous system-active drug to the human brain, which could affect the efficacy and/or safety of drugs. [11C]Metoclopramide PET may be used to assess or predict the contribution of increased P-gp function to drug resistance and disease pathophysiology in various brain diseases. Trial registration EudraCT 2019-003137-42. Registered 28 February 2020.

Introduction: Wilson’s disease is a rare autosomal recessive disorder that disrupts copper metabolism. It presents with distinctive ocular manifestations. Oculodermal melanosis, commonly referred to as nevus of Ota, is a painless condition characterized by hyperpigmentation in and around the eye. In this case report, we describe the unique occurrence of both conditions in this pediatric patient. Case Presentation: A 10-year-old girl exhibited classic ocular signs associated with Wilson’s disease, including Kayser-Fleischer rings and sunflower-type cataracts. Additionally, she displayed unilateral confluent gray-blue hyperpigmentation consistent with a nevus of Ota. As of now, the patient remains asymptomatic, with preserved visual acuity. Conclusions: To the best of our knowledge, this case represents the first report of nevus of Ota in a child diagnosed with Wilson’s disease.

Purpose: The authors of this study examined how four leadership teams participating in a year-long deeper learning leadership academy understood and adapted key practices for change leadership, deeper learning and equity in their PK-12 schools. Design/methodology/approach: This multiple-site case study used interviews, observations and documents to investigate how four school leadership teams developed deeper learning initiatives in their schools. Findings: This study highlights how participants recast the leadership academy's three pillars (change leadership, deeper learning and equity) as they engaged in educational reform for ambitious teaching and learning in their own contexts. Three themes emerged: transforming the culture, teaching the whole child and restructuring for collaboration. Overall, the authors found that district leaders must be fully committed to deeper learning for the culture to truly be transformed in schools under their purview. Originality/value: This article contributes to the literature on supporting school leaders to enact equity-centered deeper learning initiatives using robust professional development. It is useful for understanding key deeper learning strategies and designing future training.