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Abstract Evidence from preclinical animal models suggests that the stress-buffering function of the endocannabinoid (eCB) system may help protect against stress-related reductions in hippocampal volume, as is documented in major depressive disorder (MDD). However, stress exposure may also lead to dysregulation of this system. Thus, pathways from marked stress histories, such as childhood maltreatment (CM), to smaller hippocampal volumes and MDD in humans may depend on dysregulated versus intact eCB functioning. We examined whether the relation between MDD and peripheral eCB concentrations would vary as a function of CM history. Further, we examined whether eCBs moderate the relation of CM/MDD and hippocampal volume. Ninety-one adults with MDD and 62 healthy comparison participants (HCs) were recruited for a study from the Canadian Biomarker Integration Network in Depression program (CAN-BIND-04). The eCBs, anandamide (AEA) and 2-arachidonylglycerol (2-AG), were assessed from blood plasma. Severe CM history was assessed retrospectively via contextual interview. MDD was associated with eCBs, though not all associations were moderated by CM or in the direction expected. Specifically, MDD was associated with higher AEA compared to HCs regardless of CM history, a difference that could be attributed to psychotropic medications. MDD was also associated with higher 2-AG, but only for participants with CM. Consistent with hypotheses, we found lower left hippocampal volume in participants with versus without CM, but only for those with lower AEA, and not moderate or high AEA. Our study presents the first evidence in humans implicating eCBs in stress-related mechanisms involving reduced hippocampal volume in MDD.

Neural network-level changes underlying symptom remission in major depressive disorder (MDD) are often studied from a single perspective. Multimodal approaches to assess neuropsychiatric disorders are evolving, as they offer richer information about brain networks. A FATCAT-awFC pipeline was developed to integrate a computationally intense data fusion method with a toolbox, to produce a faster and more intuitive pipeline for combining functional connectivity with structural connectivity (denoted as anatomically weighted functional connectivity (awFC)). Ninety-three participants from the Canadian Biomarker Integration Network for Depression study (CAN-BIND-1) were included. Patients with MDD were treated with 8 weeks of escitalopram and adjunctive aripiprazole for another 8 weeks. Between-group connectivity (SC, FC, awFC) comparisons contrasted remitters (REM) with non-remitters (NREM) at baseline and 8 weeks. Additionally, a longitudinal study analysis was performed to compare connectivity changes across time for REM, from baseline to week-8. Association between cognitive variables and connectivity were also assessed. REM were distinguished from NREM by lower awFC within the default mode, frontoparietal, and ventral attention networks. Compared to REM at baseline, REM at week-8 revealed increased awFC within the dorsal attention network and decreased awFC within the frontoparietal network. A medium effect size was observed for most results. AwFC in the frontoparietal network was associated with neurocognitive index and cognitive flexibility for the NREM group at week-8. In conclusion, the FATCAT-awFC pipeline has the benefit of providing insight on the ‘full picture’ of connectivity changes for REMs and NREMs while making for an easy intuitive approach.

Background Cerebral small vessel disease is associated with higher ratios of soluble-epoxide hydrolase derived linoleic acid diols (12,13-dihydroxyoctadecenoic acid [DiHOME] and 9,10-DiHOME) to their parent epoxides (12(13)-epoxyoctadecenoic acid [EpOME] and 9(10)-EpOME); however, the relationship has not yet been examined in stroke. Methods and Results Participants with mild to moderate small vessel stroke or large vessel stroke were selected based on clinical and imaging criteria. Metabolites were quantified by ultra-high-performance liquid chromatography-mass spectrometry. Volumes of stroke, lacunes, white matter hyperintensities, magnetic resonance imaging visible perivascular spaces, and free water diffusion were quantified from structural and diffusion magnetic resonance imaging (3 Tesla). Adjusted linear regression models were used for analysis. Compared with participants with large vessel stroke (n=30), participants with small vessel stroke (n=50) had a higher 12,13-DiHOME/12(13)-EpOME ratio (β=0.251, P=0.023). The 12,13-DiHOME/12(13)-EpOME ratio was associated with more lacunes (β=0.266, P=0.028) but not with large vessel stroke volumes. Ratios of 12,13-DiHOME/12(13)-EpOME and 9,10-DiHOME/9(10)-EpOME were associated with greater volumes of white matter hyperintensities (β=0.364, P

INTRODUCTION: Compared to stably housed peers, people experiencing homelessness (PEH) have lower rates of ideal glycemic control, and experience premature morbidity and mortality. High rates of behavioral health comorbidities and trauma add to access barriers driving poor outcomes. Limited evidence guides behavioral approaches to support the needs of PEH with diabetes. Lay coaching models can improve care for low-resource populations with diabetes, yet we found no evidence of programs specifically tailored to the needs of PEH. METHODS: We used a multistep, iterative process following the ORBIT model to develop the Diabetes Homeless Medication Support (D-HOMES) program, a new lifestyle intervention for PEH with type 2 diabetes. We built a community-engaged research team who participated in all of the following steps of treatment development: (1) initial treatment conceptualization drawing from evidence-based programs, (2) qualitative interviews with affected people and multi-disciplinary housing and healthcare providers, and (3) an open trial of D-HOMES to evaluate acceptability (Client Satisfaction Questionnaire, exit interview) and treatment engagement (completion rate of up to 10 offered coaching sessions). RESULTS: In step (1), the D-HOMES treatment manual drew from existing behavioral activation and lay health coach programs for diabetes as well as clinical resources from Health Care for the Homeless. Step (2) qualitative interviews (n = 26 patients, n = 21 providers) shaped counseling approaches, language and choices regarding interventionists, tools, and resources. PTSD symptoms were reported in 69% of patients. Step (3) trial participants (N = 10) overall found the program acceptable, however, we saw better program satisfaction and treatment engagement among more stably housed people. We developed adapted treatment materials for the target population and refined recruitment/retention strategies and trial procedures sensitive to prevalent discrimination and racism to better retain people of color and those with less stable housing. DISCUSSION: The research team has used these findings to inform an NIH-funded randomized control pilot trial. We found synergy between community-engaged research and the ORBIT model of behavioral treatment development to develop a new intervention designed for PEH with type 2 diabetes and address health equity gaps in people who have experienced trauma. We conclude that more work and different approaches are needed to address the needs of participants with the least stable housing.

BackgroundEfforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states.MethodsWe describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants.ResultsWe are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites.ConclusionWe describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.

Purpose: To describe what researchers are investigating and how they are measuring the constructs of their investigations within the speech-language pathology (SLP) clinical education literature. Method: A scoping review methodology (Arksey & O'Malley, 2005) was employed to develop a picture of clinical education articles which reported a measured outcome. Articles that met criteria were categorized by the purpose of the investigation and the outcome measures reported. Result: 124 articles met inclusion criteria. Analysis of study purposes revealed a wide breadth of foci that were grouped into four broad clusters: Outcome Measures, Student Perspectives, Educational Contexts, and Teaching Methods. Most of the studies in the corpus relied only on student self-report measures. In addition, any specific outcome measure was typically used only once and not found in subsequent studies. Trends indicate a variety of constructs are being studied at an exploratory level with limited in-depth investigation. Conclusion: Given the inconsistency of outcome measures and reliance on self-report measures, more research is needed to validate recommendations of best practices in clinical education. Areas of need include developing and implementing validated outcomes, more frequent investigation of clinical education using measures other than student self-reports, and testing theories found in other fields.

PurposeTo determine whether SD-101, a Toll-like receptor 9 agonist, potentiates the antitumor activity of anti-PD-1 antibodies in patients with anti-PD-1/PD-L1 naïve, recurrent/metastatic head and neck squamous cell carcinoma (HNSCC).Patients and methodsPatients with PD-1 Ab-naïve HNSCC received either 2 mg SD-101 injected in one to four lesions or 8 mg SD-101 injected into a single lesion weekly × 4 doses then every 3 weeks × 7 doses. Pembrolizumab was administered at 200 mg every 3 weeks.ResultsA total of 28 patients received 2 mg and 23 received 8 mg per injection, respectively. A total of 76% of patients had received prior systemic therapy. Combined positive score was ≥1 to < 20 in 35 patients (70%) and ≥ 20 in 15 patients (30%) of 50 patients with available data. There were 12 patients with grade ≥3 treatment-related adverse events (24%), and no treatment-related deaths. The objective response rate was 24% including 2 complete and 10 partial responses. The median duration of response was 7.0 [95% confidence interval (CI): 2.1-11.1] months. The response rate was higher in human papillomavirus-positive (HPV+) patients (44%, N = 16). Responses were not associated with PD-L1 expression levels or IFNγ-related gene expression at baseline. Responses were observed both in injected (32%) and in noninjected lesions (29%). Progression-free and overall survival at 9 months were 19.0% (95% CI: 9.1-31.7) and 64.7% (95% CI: 45.3-78.7), respectively.ConclusionsSD-101 combined with pembrolizumab induced objective responses, especially in HPV+ tumors, which were frequently associated with increased intratumoral inflammation and effector immune cell activity.

There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.

Categorical perception (CP) facilitates the discrimination of stimuli belonging to different categories relative to those from the same category. Effects of CP on the discrimination of color and shape have been attributed to the top-down modulation of visual perception by the left-lateralized language processes. We used a divided visual field (DVF) search paradigm to investigate the prospective effects of CP for face identity and gender processing. Consistent with visual processing of face identity in the right hemisphere, we found CP facilitated perception only in the left visual field (LVF). In contrast, and consistent with language-induced CP, we observed a between-category advantage for processing face gender only in the right visual field (RVF). Taken together, our results suggest that language-induced CP plays a role in the category-based visual processing of faces by the left hemisphere, but face familiarity processing might be dependent on different, identity-specialized networks in the right hemisphere.

Because their resistant, sporopolleninous walls preserve a record of morphogenetic change during spore formation, fossil cryptospores provide a direct physical record of the evolution of sporogenesis during the algal–plant transition. That transition itself is a story of the evolution of development—it is not about phylogeny. Here, we review the fossil record of terrestrially derived spore/cryptospore assemblages and attempt to place these microfossils in their evolutionary context with respect to the origin of complex multicellularity in plants. Cambrian cryptospores show features related to karyokinesis seen in extant charophytes, but they also possess ultrastructure similar to that seen in liverworts today. Dyadospora, a cryptospore dyad recovered from sporangia of Devonian embryophytes, first occurs in the earliest Ordovician. Tetrahedraletes, a likely precursor to the trilete spore, first occurs in the Middle Ordovician. These fossils correspond to evolutionary novelties that were acquired during a period of genome assembly prior to the existence of upright, axial sporophytes. The cryptospore/spore fossil record provides a temporal scaffold for the acquisition of novel characters relating to the evolution of plant sporogenesis during the Cambrian–Silurian interval.

Using a cluster randomized trial, we investigated the effects of mathematics professional development on student achievement in elementary schools. Pairs of schools were matched on prior mathematics; percentage of students receiving free or reduced-price lunch and percentage of limited English proficient students were randomly assigned to two groups. One received professional development on mathematics that focuses on diagnosing student thinking and the other received professional development on formative assessment. Student-level achievement data (pretest and posttest performance on a standardized test of mathematics) were nested within grades and schools and analyzed using mixed-effects multi-level linear modeling. The results indicate students in schools that were provided the mathematics professional development had greater mathematics achievement than students in schools in a control condition. The effect held across grade levels.

Courtney R Carlson Strother,1 Lauren E Dittman,1 Marco Rizzo,1 Steven L Moran,2 Peter C Rhee1 1Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA; 2Department of Plastic Surgery, Mayo Clinic, Rochester, MN, USACorrespondence: Peter C Rhee, Department of Orthopedic Surgery, Mayo Clinic, 200 1st Street SW, Rochester, MN, USA, 55905, Tel +1 507-284-3422, Fax +1 507-266-2533, Email rhee.peter@mayo.eduPurpose: The aim of this study was to evaluate the occurrence of early (< 6 weeks) post-operative complications following ulnar nerve decompressions at the cubital tunnel performed under regional anesthesia compared to those performed under general anesthesia.Methods: In situ ulnar nerve decompressions at the cubital tunnel performed at a single institution from 2012 through 2019 were retrospectively reviewed. Post-operative complications were compared between subjects who underwent the procedure with regional versus general anesthesia.Results: Ninety-one ulnar nerve in situ decompressions were included in the study, which were performed under regional anesthesia in 55 and general anesthesia in 36 cases. The occurrence of post-operative complications was not significantly different between patients who received regional (n = 7) anesthesia and general (n = 8) anesthesia. None of the complications were directly attributed to the type of anesthesia administered. The change in pre- and post-operative McGowan scores were not significantly different between anesthesia groups (p = 0.81).Conclusion: In situ ulnar nerve decompression at the cubital tunnel under regional anesthesia does not result in increased post-operative complications compared to those surgeries performed under general anesthesia. In situ ulnar nerve decompression performed under regional anesthesia is a safe and reliable option for patients who wish to avoid general anesthesia.Level of Evidence: III.Keywords: cubital tunnel, regional anesthesia, ulnar neuropathy

Abstract Background Neuropsychiatric symptoms (NPS) are a core feature of most neurodegenerative and cerebrovascular diseases. White matter hyperintensities and brain atrophy have been implicated in NPS. We aimed to investigate the relative contribution of white matter hyperintensities and cortical thickness to NPS in participants across neurodegenerative and cerebrovascular diseases. Methods Five hundred thirteen participants with one of these conditions, i.e. Alzheimer’s Disease/Mild Cognitive Impairment, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Parkinson’s Disease, or Cerebrovascular Disease, were included in the study. NPS were assessed using the Neuropsychiatric Inventory – Questionnaire and grouped into hyperactivity, psychotic, affective, and apathy subsyndromes. White matter hyperintensities were quantified using a semi-automatic segmentation technique and FreeSurfer cortical thickness was used to measure regional grey matter loss. Results Although NPS were frequent across the five disease groups, participants with frontotemporal dementia had the highest frequency of hyperactivity, apathy, and affective subsyndromes compared to other groups, whilst psychotic subsyndrome was high in both frontotemporal dementia and Parkinson’s disease. Results from univariate and multivariate results showed that various predictors were associated with neuropsychiatric subsyndromes, especially cortical thickness in the inferior frontal, cingulate, and insula regions, sex(female), global cognition, and basal ganglia-thalamus white matter hyperintensities. Conclusions In participants with neurodegenerative and cerebrovascular diseases, our results suggest that smaller cortical thickness and white matter hyperintensity burden in several cortical-subcortical structures may contribute to the development of NPS. Further studies investigating the mechanisms that determine the progression of NPS in various neurodegenerative and cerebrovascular diseases are needed.

Molecular phylogenetic studies of land plant (embryophyte) origins have begun to tease apart those evolutionary contributions derived from prior algal genes and those de novo genes that evolved during a charophyteâembryophyte transition. Applying the concept of genomic assembly in plant evolution to the fossil record leads to a paradigm shift in the interpretation of the Ordovician record of land plants. Traditional phylogenetic thinking requires fossil species taxa to occupy nodes on a phylogeny. An evo-devo approach can view character evolution separately from species taxa, freeing up fossil spores and tissue fragments to become clues to underlying developmental pathways or gene regulatory networks. This results in a re-assessment of what is meant by the presence of land plants in the Ordovician landscape. The new model helps to reconcile discrepancies between molecular time-trees and the âmissingâ record of fossil plants during the Ordovician Period.

IntroductionPeople living with type 2 diabetes who experience homelessness face a myriad of barriers to engaging in diabetes self-care behaviors that lead to premature complications and death. This is exacerbated by high rates of comorbid mental illness, substance use disorder, and other physical health problems. Despite strong evidence to support lay health coach and behavioral activation, little research has effectively engaged people living with type 2 diabetes who had experienced homelessness (DH).MethodsWe used community engaged research and incremental behavioral treatment development to design the Diabetes HOmeless MEdication Support (D-HOMES) program, a one-on-one, 3 month, coaching intervention to improve medication adherence and psychological wellness for DH. We present results of our pilot randomized trial (with baseline, 3 mo., 6 mo. assessments) comparing D-HOMES to enhanced usual care (EUC; brief diabetes education session and routine care; NCT05258630). Participants were English-speaking adults with type 2 diabetes, current/recent (

Background Identifying neuroimaging biomarkers of antidepressant response may help guide treatment decisions and advance precision medicine. Aims To examine the relationship between anhedonia and functional neurocircuitry in key reward processing brain regions in people with major depressive disorder receiving aripiprazole adjunct therapy with escitalopram. Method Data were collected as part of the CAN-BIND-1 study. Participants experiencing a current major depressive episode received escitalopram for 8 weeks; escitalopram non-responders received adjunct aripiprazole for an additional 8 weeks. Functional magnetic resonance imaging (on weeks 0 and 8) and clinical assessment of anhedonia (on weeks 0, 8 and 16) were completed. Seed-based correlational analysis was employed to examine the relationship between baseline resting-state functional connectivity (rsFC), using the nucleus accumbens (NAc) and anterior cingulate cortex (ACC) as key regions of interest, and change in anhedonia severity after adjunct aripiprazole. Results Anhedonia severity significantly improved after treatment with adjunct aripiprazole. There was a positive correlation between anhedonia improvement and rsFC between the ACC and posterior cingulate cortex, ACC and posterior praecuneus, and NAc and posterior praecuneus. There was a negative correlation between anhedonia improvement and rsFC between the ACC and anterior praecuneus and NAc and anterior praecuneus. Conclusions Eight weeks of aripiprazole, adjunct to escitalopram, was associated with improved anhedonia symptoms. Changes in functional connectivity between key reward regions were associated with anhedonia improvement, suggesting aripiprazole may be an effective treatment for individuals experiencing reward-related deficits. Future studies are required to replicate our findings and explore their generalisability, using other agents with partial dopamine (D2) agonism and/or serotonin (5-HT2A) antagonism.

Abstract Accurate prediction of new baseline GFR (NBGFR) after radical nephrectomy (RN) can inform clinical management and patient counseling whenever RN is a strong consideration. Preoperative global GFR, split renal function (SRF), and renal functional compensation (RFC) are fundamentally important for the accurate prediction of NBGFR post-RN. While SRF has traditionally been obtained from nuclear renal scans (NRS), differential parenchymal volume analysis (PVA) via software analysis may be more accurate. A simplified approach to estimate parenchymal volumes and SRF based on length/width/height measurements (LWH) has also been proposed. We compare the accuracies of these three methods for determining SRF, and, by extension, predicting NBGFR after RN. All 235 renal cancer patients managed with RN (2006–2021) with available preoperative CT/MRI and NRS, and relevant functional data were analyzed. PVA was performed on CT/MRI using semi-automated software, and LWH measurements were obtained from CT/MRI images. RFC was presumed to be 25%, and thus: Predicted NBGFR = 1.25 × Global GFRPre-RN × SRFContralateral. Predictive accuracies were assessed by mean squared error (MSE) and correlation coefficients (r). The r values for the LWH/NRS/software-derived PVA approaches were 0.72/0.71/0.86, respectively (p

BackgroundEndometriosis is complex, but identifying the novel biomarkers, inflammatory molecules, and genetic links holds the key to the enhanced detection, prediction and treatment of both endometriosis and endometriosis related malignant neoplasia. Here we review the literature relating to the specific molecular mechanism(s) mediating tumorigenesis arising within endometriosis.MethodsGuidance (e.g. Cochrane) and published studies were identified. The Published studies were identified through PubMed using the systematic review methods filter, and the authors' topic knowledge. These data were reviewed to identify key and relevant articles to create a comprehensive review article to explore the molecular fingerprint associated with in endometriosis-driven tumorigenesis.ResultsAn important focus is the link between C3aR1, PGR, ER1, SOX-17 and other relevant gene expression profiles and endometriosis-driven tumorigenesis. Further studies should also focus on the combined use of CA-125 with HE-4, and the role for OVA1/MIA as clinically relevant diagnostic biomarkers in the prediction of endometriosis-driven tumorigenesis.ConclusionsElucidating endometriosis' molecular fingerprint is to understand the molecular mechanisms that drive the endometriosis-associated malignant phenotype. A better understanding of the predictive roles of these genes and the value of the biomarker proteins will allow for the derivation of unique molecular treatment algorithms to better serve our patients.

IntroductionCompared to stably housed peers, people experiencing homelessness (PEH) have lower rates of ideal glycemic control, and experience premature morbidity and mortality. High rates of behavioral health comorbidities and trauma add to access barriers driving poor outcomes. Limited evidence guides behavioral approaches to support the needs of PEH with diabetes. Lay coaching models can improve care for low-resource populations with diabetes, yet we found no evidence of programs specifically tailored to the needs of PEH.MethodsWe used a multistep, iterative process following the ORBIT model to develop the Diabetes Homeless Medication Support (D-HOMES) program, a new lifestyle intervention for PEH with type 2 diabetes. We built a community-engaged research team who participated in all of the following steps of treatment development: (1) initial treatment conceptualization drawing from evidence-based programs, (2) qualitative interviews with affected people and multi-disciplinary housing and healthcare providers, and (3) an open trial of D-HOMES to evaluate acceptability (Client Satisfaction Questionnaire, exit interview) and treatment engagement (completion rate of up to 10 offered coaching sessions).ResultsIn step (1), the D-HOMES treatment manual drew from existing behavioral activation and lay health coach programs for diabetes as well as clinical resources from Health Care for the Homeless. Step (2) qualitative interviews (n = 26 patients, n = 21 providers) shaped counseling approaches, language and choices regarding interventionists, tools, and resources. PTSD symptoms were reported in 69% of patients. Step (3) trial participants (N = 10) overall found the program acceptable, however, we saw better program satisfaction and treatment engagement among more stably housed people. We developed adapted treatment materials for the target population and refined recruitment/retention strategies and trial procedures sensitive to prevalent discrimination and racism to better retain people of color and those with less stable housing.DiscussionThe research team has used these findings to inform an NIH-funded randomized control pilot trial. We found synergy between community-engaged research and the ORBIT model of behavioral treatment development to develop a new intervention designed for PEH with type 2 diabetes and address health equity gaps in people who have experienced trauma. We conclude that more work and different approaches are needed to address the needs of participants with the least stable housing.

Deep artificial neural networks (DNNs) have moved to the forefront of medical image analysis due to their success in classification, segmentation, and detection challenges. A principal challenge in large-scale deployment of DNNs in neuroimage analysis is the potential for shifts in signal-to-noise ratio, contrast, resolution, and presence of artifacts from site to site due to variances in scanners and acquisition protocols. DNNs are famously susceptible to these distribution shifts in computer vision. Currently, there are no benchmarking platforms or frameworks to assess the robustness of new and existing models to specific distribution shifts in MRI, and accessible multi-site benchmarking datasets are still scarce or task-specific. To address these limitations, we propose ROOD-MRI: a novel platform for benchmarking the Robustness of DNNs to Out-Of-Distribution (OOD) data, corruptions, and artifacts in MRI. This flexible platform provides modules for generating benchmarking datasets using transforms that model distribution shifts in MRI, implementations of newly derived benchmarking metrics for image segmentation, and examples for using the methodology with new models and tasks. We apply our methodology to hippocampus, ventricle, and white matter hyperintensity segmentation in several large studies, providing the hippocampus dataset as a publicly available benchmark. By evaluating modern DNNs on these datasets, we demonstrate that they are highly susceptible to distribution shifts and corruptions in MRI. We show that while data augmentation strategies can substantially improve robustness to OOD data for anatomical segmentation tasks, modern DNNs using augmentation still lack robustness in more challenging lesion-based segmentation tasks. We finally benchmark U-Nets and vision transformers, finding robustness susceptibility to particular classes of transforms across architectures. The presented open-source platform enables generating new benchmarking datasets and comparing across models to study model design that results in improved robustness to OOD data and corruptions in MRI.

PurposeAtypical teratoid/rhabdoid tumor (AT/RT) is an aggressive, early-childhood brain tumor without standard effective treatment. To our knowledge, we conducted the first AT/RT-specific cooperative group trial, ACNS0333, to examine the efficacy and safety of intensive postoperative chemotherapy and focal radiation to treat AT/RT.Patients and methodsPatients from birth to 22 years of age with AT/RT were eligible. After surgery, they received 2 courses of multiagent chemotherapy, followed by 3 courses of high-dose chemotherapy with peripheral blood stem cell rescue and involved-field radiation therapy. Timing of radiation was based on patient age and disease location and extent. Central testing of tumor and blood for SMARCB1 status was mandated. Tumor molecular subclassification was performed retrospectively. The primary analysis was event-free survival (EFS) for patients < 36 months of age compared with a cooperative groups' historical cohort. Although accrual was based on the therapeutic question, potential prognostic factors, including age, tumor location, M stage, surgical resection, order of therapy, germline status, and molecular subtype, were explored.ResultsOf 65 evaluable patients, 54 were < 36 months of age. ACNS0333 therapy significantly reduced the risk of EFS events in patients < 36 months of age compared with the historical cohort (P < .0005; hazard rate, 0.43; 95% CI, 0.28 to 0.66). Four-year EFS and overall survival for the entire cohort were 37% (95% CI, 25% to 49%) and 43% (95% CI, 31% to 55%), respectively. Timing of radiation did not affect survival, and 91% of relapses occurred by 2 years from enrollment. Treatment-related deaths occurred in 4 patients.ConclusionThe ACNS0333 regimen dramatically improved survival compared with historical therapies for patients with AT/RT. Clinical characteristics and molecular subgrouping suggest prognostic differences. ACNS0333 results lay a foundation on which to build future studies and incorporate testing of new therapeutic agents.

As youth increasingly access the public sphere and contribute to civic life through digital tools, scholars and educators are rethinking how civically engaged writing is taught, nurtured, and assessed. This article presents the conceptual underpinnings of the National Writing Project's Civically Engaged Writing Analysis Continuum (CEWAC), a new tool for assessing youth's civically engaged writing. It defines four attributes of civically engaged writing using qualitative analysis of expert interviews and literature: employs a public voice, advocates civic engagement or action, argues a position based on reasoning and evidence, and employs a structure to support a position. The article also presents reliability and validity evidence for CEWAC. The study finds that CEWAC has a moderate to high level of exact agreement and a high level of exact or adjacent agreement. Covariation analyses showed that, even with similar scoring patterns, CEWAC's attributes hold at least a moderate level of independence. This evidence, coupled with robust qualitative evidence around reliability and validity, establish CEWAC's strong technical properties. The findings suggest that CEWAC can be used both in research and in the classroom to make visible attributes of civically engaged writing often overlooked in traditional assessment frameworks. Keywords: public writing, civic engagement, writing assessment, rubric, reliability

Abstract Background Efforts to develop neuroimaging-based biomarkers in major depressive disorder (MDD), at the individual level, have been limited to date. As diagnostic criteria are currently symptom-based, MDD is conceptualized as a disorder rather than a disease with a known etiology; further, neural measures are often confounded by medication status and heterogeneous symptom states. Methods We describe a consortium to quantify neuroanatomical and neurofunctional heterogeneity via the dimensions of novel multivariate coordinate system (COORDINATE-MDD). Utilizing imaging harmonization and machine learning methods in a large cohort of medication-free, deeply phenotyped MDD participants, patterns of brain alteration are defined in replicable and neurobiologically-based dimensions and offer the potential to predict treatment response at the individual level. International datasets are being shared from multi-ethnic community populations, first episode and recurrent MDD, which are medication-free, in a current depressive episode with prospective longitudinal treatment outcomes and in remission. Neuroimaging data consist of de-identified, individual, structural MRI and resting-state functional MRI with additional positron emission tomography (PET) data at specific sites. State-of-the-art analytic methods include automated image processing for extraction of anatomical and functional imaging variables, statistical harmonization of imaging variables to account for site and scanner variations, and semi-supervised machine learning methods that identify dominant patterns associated with MDD from neural structure and function in healthy participants. Results We are applying an iterative process by defining the neural dimensions that characterise deeply phenotyped samples and then testing the dimensions in novel samples to assess specificity and reliability. Crucially, we aim to use machine learning methods to identify novel predictors of treatment response based on prospective longitudinal treatment outcome data, and we can externally validate the dimensions in fully independent sites. Conclusion We describe the consortium, imaging protocols and analytics using preliminary results. Our findings thus far demonstrate how datasets across many sites can be harmonized and constructively pooled to enable execution of this large-scale project.

Abstract Cytochrome P450 drug-metabolizing enzymes may contribute to interindividual differences in antidepressant outcomes. We investigated the effects of CYP2C19 and CYP2D6 gene variants on response, tolerability, and serum concentrations. Patients (N = 178) were treated with escitalopram (ESC) from weeks 0–8 (Phase I), and at week 8, either continued ESC if they were responders or were augmented with aripiprazole (ARI) if they were non-responders (

Genogroup II (GII) noroviruses are a major cause of diarrheal disease burden in children in both high- and low-income countries. GII.17 noroviruses are composed of distinct genetic clusters (I, II, IIIa, and IIIb) and have shown potential for replacing historically more prevalent GII.4 strains, but the serological basis for GII.17 antigenic diversity has not been studied in children. Utilizing samples from a birth cohort, we investigated antibody and B-cell responses to GII.17 cluster variants in confirmed GII.17 infections in young children as well as demonstrated that the distinct genetic clusters co-circulate. Polyclonal serum antibodies bound multiple clusters but showed cluster-specific blockade activity in a surrogate virus neutralization assay. Antibodies secreted by immortalized memory B cells (MBCs) from an infant GII.17 case were highly specific to GII.17 and exhibited blockade activity against this genotype. We isolated an MBC-derived GII.17-specific Immunoglobulin A (IgA) monoclonal antibody called NVA.1 that potently and selectively blocked GII.17 cluster IIIb and recognized an epitope targeted in serum from cluster IIIb–infected children. These data indicate that multiple antigenically distinct GII.17 variants co-circulate in young children, suggesting retention of cluster diversity alongside potential for immune escape given the existence of antibody-defined cluster-specific epitopes elicited during infection.

The Canadian Open Neuroscience Platform (CONP) takes a multifaceted approach to enabling open neuroscience, aiming to make research, data, and tools accessible to everyone, with the ultimate objective of accelerating discovery. Its core infrastructure is the CONP Portal, a repository with a decentralized design, where datasets and analysis tools across disparate platforms can be browsed, searched, accessed, and shared in accordance with FAIR principles. Another key piece of CONP infrastructure is NeuroLibre, a preprint server capable of creating and hosting executable and fully reproducible scientific publications that embed text, figures, and code. As part of its holistic approach, the CONP has also constructed frameworks and guidance for ethics and data governance, provided support and developed resources to help train the next generation of neuroscientists, and has fostered and grown an engaged community through outreach and communications. In this manuscript, we provide a high-level overview of this multipronged platform and its vision of lowering the barriers to the practice of open neuroscience and yielding the associated benefits for both individual researchers and the wider community.

Background: Deep-rooted and widespread gender-based bias and discrimination threaten achievement of the Sustainable Development Goals. Despite evidence that addressing gender inequities contributes to better health and development outcomes, the resources for, and effectiveness of, such efforts in development assistance for health (DAH) have been insufficient. This paper explores systemic challenges in DAH that perpetuate or contribute to gender inequities, with a particular focus on the role of external donors and funders. Methods: We applied a co-creation system design process to map and analyze interactions between donors and recipient countries, and articulate drivers of gender inequities within the landscape of DAH. We conducted qualitative primary data collection and analysis in 2021 via virtual facilitated discussions and visual mapping exercises among a diverse set of 41 stakeholders, including representatives from donor institutions, country governments, academia, and civil society. Results: Six systemic challenges emerged as perpetuating or contributing to gender inequities in DAH: 1) insufficient input and leadership from groups affected by gender bias and discrimination; 2) decision-maker blind spots inhibit capacity to address gender inequities; 3) imbalanced power dynamics contribute to insufficient resources and attention to gender priorities; 4) donor funding structures limit efforts to effectively address gender inequities; 5) fragmented programming impedes coordinated attention to the root causes of gender inequities; and 6) data bias contributes to insufficient understanding of and attention to gender inequities. Conclusions: Many of the drivers impeding progress on gender equity in DAH are embedded in power dynamics that distance and disempower people affected by gender inequities. Overcoming these dynamics will require more than technical solutions. Groups affected by gender inequities must be centered in leadership and decision-making at micro and macro levels, with practices and structures that enable co-creation and mutual accountability in the design, implementation, and evaluation of health programs.