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In recent years, researchers have shifted from pathologizing Black youths, when investigating the Black-White achievement gap, to focusing on factors contributing to their resilience and success. A critical review was conducted of three widely cited asset-based theoretical frameworks that are used to examine African American students' academic achievement. The review delineates the contributions and limitations of each model when studying African American students. In doing so, a new framework, linking the strengths of all three existing models, is presented as a tool to challenge existing educational practices and foster new theoretical and methodological contributions to this area of research.

The devaluation of women of Color (WoC) by way of gender discrimination and systemic racism is well documented. For WoC in engineering a chief cause is the observable wage gap. Women who identify as Asian, Black/African American, Latina/Chicana, Indigenous/Native American, Native Hawaiian, Pacific Islander, Native Alaskan, and/or multiracial have reported stark wage disparities. In this paper, we offer a phenomenological study of how WoC engineering faculty across U.S. academic institutions describe the challenges and practices associated with wage disparities and how they navigate these disparities. This study, which is based on participant interviews, is guided by three research questions: (1) What do WoC engineering tenure-track faculty perceive about wage disparities based on their race and gender? (2) How do WoC faculty understand the institutional practices that contribute to wage disparities? and (3) How do WoC engineering faculty respond to and address wage disparities? Using structural racism and intersectionality as our guiding conceptual framework, we interviewed 32 self-identified WoC who identified structures and systems of institutional racism related to the maintenance of wage disparities. In terms of findings, we note that WoC have two primary strategies to respond to wage disparity: advocacy and agency. The experiences of WoC engineering faculty in our study highlight unsatisfying institutional responses, and thus WoC often rely on their own agency to advocate for themselves and to advocate for and mentor other WoC faculty. We found a few notable cases where men advocated for women to help close the wage gap. Our work reveals that pay inequity for WoC is often coupled with other forms of exclusion and marginalization. Reducing wage disparities in academia is critical to advancing diversity efforts and ensuring equitable support for WoC faculty. Our findings suggest that institutions can work diligently to rectify wage inequality, including making sustainable structural and salary modifications and sharing the burden of combatting wage inequities. Finally, our findings also highlight the importance of making policy changes to reduce pay inequalities, such as providing transparent pay information and more opportunities to earn merit raises.

Extant literature has demonstrated that children's diurnal stress physiology often looks different on childcare versus home days. Specifically, children experience a rise in cortisol, rather than a decline, over the day while in full-time care. Additionally, temperamental fit within classroom environment may influence both child and teacher cortisol and outcomes. The current study investigated whether teachers' cortisol levels (n = 11) were associated with child cortisol levels (n = 71, mean age = 4.18 ± 0.81, 51% female) in the classroom while taking into account temperament, child sex assigned at birth, and classroom quality. Cortisol samples were collected on consecutive days at home and childcare for children, and at childcare for teachers. We hypothesized that (1) teacher cortisol will predict child afternoon cortisol, (2) that a portion of the variance in this relationship will be accounted for by classroom quality. Using a cross-sectional design, children in this sample had higher cortisol values in the afternoon while at childcare than at similar times of day at home. Teachers demonstrated a typical diurnal decline across the day but variation in total cortisol output at childcare. Two distinct predictors of afternoon cortisol levels were identified in children attending childcare: child age and mean teacher cortisol levels across the day, while negative affect and classroom quality were not significant. Younger children and children whose teachers had higher mean cortisol levels were more likely to have high afternoon cortisol at childcare. Higher diurnal cortisol values for teachers may indicate a higher stress environment for both teachers and children. These preliminary findings suggest that teacher stress may not only have implications for children in terms of teacher burnout, high staff turnover, and learning, but possibly also for children's health and well-being. Implications for research and policy, as well as limitations and strengths, are discussed.

The goal of this qualitative research is to understand equitable teaching practices of computer science classrooms in the Chicago Public Schools through the video analysis specifically for the Latinx students. Data was collected through video recording from 10 different CPS classrooms. The videos were analyzed qualitative to determine the inquiry driven equitable practices. Though the equitable practices were identified based on the classroom video analysis, literature review on equitable practices and core ECS philosophy informed us to recognize and group the themes and their indicators of equity. This research plays a crucial role in terms of informing the current equitable teaching practices based on the videos in ECS classrooms in Chicago, also the research identifies a need to study further cultural references in terms of teaching computer science curriculum. This research has significance for designing professional development for marginalized population in computer science and possibly for other STEM areas.

Student wellbeing is regarded as a salient priority across higher education. Given the growing participation of higher education students in work-integrated learning, it is important to explore how student wellbeing is being supported in this critical learning environment. While student wellbeing must be considered across all educational contexts, wellbeing may be most challenged when working and learning online. The purpose of this research, therefore, was to explore ways in which student wellbeing is supported by program coordinators when students are engaging in online work-integrated learning (eWIL). Seventeen program coordinators across Canada were interviewed and data were analyzed thematically. Thematic analysis generated three main themes: program coordinators' perspectives on their role in supporting student wellbeing, wellbeing supports offered to students engaged in WIL, and intersectional considerations for supporting student wellbeing. These findings advance the discussion of innovative and tailored approaches needed to support student wellbeing in online work-integrated learning environments.

This national study included a quantitative inquiry regarding the impact of COVID-19 on service-learning from 207 participants representing community partner organizations (n = 145) and higher education institutions (n = 62). Community partners reported a decreased number of students engaged in service-learning after the outbreak of COVID-19. Response patterns emerged between community partners and higher education participant groups. The perceived helpfulness of service-learning for student success and fostering relationships differed statistically among the partner types--higher education participants rated these higher than community partners. Reasons for participating varied among partner types, and community partners identified volunteer procurement among the most helpful support higher education offers beyond service-learning. Changing policies, wearing masks, and virtual communication were cited as main adaptations to COVID-19 but prioritized differently among partners. This study uncovered the emerging and varied perspectives of higher education and community partners regarding service-learning at this significant time in history.

Abstract Background In radiotherapy, 2D orthogonally projected kV images are used for patient alignment when 3D-on-board imaging (OBI) is unavailable. However, tumor visibility is constrained due to the projection of patient’s anatomy onto a 2D plane, potentially leading to substantial setup errors. In treatment room with 3D-OBI such as cone beam CT (CBCT), the field of view (FOV) of CBCT is limited with unnecessarily high imaging dose. A solution to this dilemma is to reconstruct 3D CT from kV images obtained at the treatment position. Methods We propose a dual-models framework built with hierarchical ViT blocks. Unlike a proof-of-concept approach, our framework considers kV images acquired by 2D imaging devices in the treatment room as the solo input and can synthesize accurate, full-size 3D CT within milliseconds. Results We demonstrate the feasibility of the proposed approach on 10 patients with head and neck (H&N) cancer using image quality (MAE: 97%) and patient position uncertainty (shift error:

Abstract Oxygen isotopes (δ 18O) are the most commonly utilized speleothem proxy and have provided many foundational records of paleoclimate. Thus, understanding processes affecting speleothem δ 18O is crucial. Yet, prior calcite precipitation (PCP), a process driven by local hydrology, is a widely ignored control of speleothem δ 18O. Here we investigate the effects of PCP on a stalagmite δ 18O record from central Vietnam, spanning 45 – 4 ka. We employ a geochemical model that utilizes speleothem Mg/Ca and cave monitoring data to correct the δ 18O record for PCP effects. The resulting record exhibits improved agreement with regional speleothem δ 18O records and climate model simulations, suggesting that the corrected record more accurately reflects precipitation δ 18O (δ 18Op). Without considering PCP, our interpretations of the δ 18O record would have been misleading. To avoid misinterpretations of speleothem δ 18O, our results emphasize the necessity of considering PCP as a significant driver of speleothem δ 18O.

Abstract Periodontitis is a highly prevalent inflammatory illness that leads to the destruction of tooth supporting tissue structures and has been associated with an increased risk of cardiovascular disease (CVD). Precision medicine, an emerging branch of medical treatment, aims can further improve current traditional treatment by personalizing care based on one’s environment, genetic makeup, and lifestyle. Genomic databases have paved the way for precision medicine by elucidating the pathophysiology of complex, heritable diseases. Therefore, the investigation of novel periodontitis-linked genes associated with CVD will enhance our understanding of their linkage and related biochemical pathways for targeted therapies. In this article, we highlight possible mechanisms of actions connecting PD and CVD. Furthermore, we delve deeper into certain heritable inflammatory-associated pathways linking the two. The goal is to gather, compare, and assess high-quality scientific literature alongside genomic datasets that seek to establish a link between periodontitis and CVD. The scope is focused on the most up to date and authentic literature published within the last 10 years, indexed and available from PubMed Central, that analyzes periodontitis-associated genes linked to CVD. Based on the comparative analysis criteria, fifty-one genes associated with both periodontitis and CVD were identified and reported. The prevalence of genes associated with both CVD and periodontitis warrants investigation to assess the validity of a potential linkage between the pathophysiology of both diseases.

Abstract Introduction Biology-guided radiotherapy (BgRT) is a novel radiation delivery approach utilizing fluorodeoxyglucose (FDG) activity on positron emission tomography (PET) imaging performed in real-time to track and direct RT. Our institution recently acquired the RefleXion X1 BgRT system and sought to assess the feasibility of targeting metastatic sites in various organs, including the liver. However, in order for BgRT to function appropriate, adequate contrast in FDG activity between the tumor and the background tissue, referred to as the normalized SUV (NSUV), is necessary for optimal functioning of BgRT. Methods We reviewed the charts of 50 lung adenocarcinoma patients with liver metastases. The following variables were collected: SUVmax and SUVmean for each liver metastasis, SUVmean and SUVmax at 5 and 10 mm radially from the lesion, and NSUV at 5 mm and 10 mm (SUVmax of the liver metastasis divided by SUV mean at 5 mm at 10 mm respectively). Results 82 measurable liver metastases were included in the final analysis. The average SUVbackground of liver was 2.26 (95% confidence interval [CI] 2.17–2.35); average SUVmean for liver metastases was 5.31 (95% CI 4.87–5.75), and average SUVmax of liver metastases was 9.19 (95% CI 7.59–10.78). The average SUVmean at 5 mm and 10 mm radially from each lesion were 3.08 (95% CI 3.00-2.16) and 2.60 (95% CI 2.52–2.68), respectively. The mean NSUV at 5 mm and 10 mm were 3.13 (95% CI 2.53–3.73) and 3.69 (95% CI 3.00-4.41) respectively. Furthermore, 90% of lesions had NSUV greater than 1.45 at 5 mm and greater than 1.77 at 10 mm. Conclusions This is the first study to comprehensively characterize FDG contrast between the liver tumor and background, referred to as NSUV. Due to the high background SUV normally found in the liver, this work will be valuable for guiding optimization of BgRT for treating liver metastases in the future using the RefleXion® X1 and potentially other similar BgRT platforms.

Abstract Background Feed costs account for a high proportion of the variable cost of beef production, ultimately impacting overall profitability. Thus, improving feed efficiency of beef cattle, by way of determining the underlying genomic control and selecting for feed efficient cattle provides a method through which feed input costs may be reduced whilst also contributing to the environmental sustainability of beef production. The rumen microbiome dictates the feed degradation capacity and consequent nutrient supply in ruminants, thus potentially impacted by feed efficiency phenotype. Equally, liver tissue has been shown to be responsive to feed efficiency phenotype as well as dietary intake. However, although both the rumen microbiome and liver transcriptome have been shown to be impacted by host feed efficiency phenotype, knowledge of the interaction between the rumen microbiome and other peripheral tissues within the body, including the liver is lacking. Thus, the objective of this study was to compare two contrasting breed types (Charolais and Holstein-Friesian) divergent for residual feed intake (RFI) over contrasting dietary phases (zero-grazed grass and high-concentrate), based on gene co-expression network analysis of liver transcriptome data and microbe co-abundance network of rumen microbiome data. Traits including RFI, dry matter intake (DMI) and growth rate (ADG), as well as rumen concentrations of volatile fatty acids were also included within the network analysis. Results Overall, DMI had the greatest number of connections followed by RFI, with ADG displaying the fewest number of significant connections. Hepatic genes related to lipid metabolism were correlated to both RFI and DMI phenotypes, whilst genes related to immune response were correlated to DMI. Despite the known relationship between RFI and DMI, the same microbes were not directly connected to these phenotypes, the Succiniclasticum genus was however, negatively connected to both RFI and ADG. Additionally, a stepwise regression analysis revealed significant roles for both Succiniclasticum genus and Roseburia.faecis sp. in predicting RFI, DMI and ADG. Conclusions Results from this study highlight the interactive relationships between rumen microbiome and hepatic transcriptome data of cattle divergent for RFI, whilst also increasing our understanding of the underlying biology of both DMI and ADG in beef cattle.

Abstract As an adoptive cellular therapy, Chimeric Antigen Receptor T cell (CAR T cell) therapy has shown remarkable success in hematological malignancies but only limited efficacy against solid tumors. Compared with blood cancers, solid tumors present a series of challenges that ultimately combine to neutralize the function of CAR T cells. These challenges include, but are not limited to, antigen heterogeneity - variability in the expression of the antigen on tumor cells, as well as trafficking and infiltration into the solid tumor tissue. A critical question for solving the heterogeneity problem is whether CAR T therapy induces bystander effects, such as antigen spreading. Antigen spreading occurs when CAR T cells activate other endogenous antitumor CD8 T cells against antigens that were not originally targeted. In this work, we develop a mathematical model of CAR T cell therapy for solid tumors that considers both antigen heterogeneity and bystander effects. Our model is based on in vivo treatment data that includes a mixture of target antigen-positive and target antigen-negative tumor cells. We use our model to simulate large cohorts of virtual patients to better understand the relationship involving bystander killing. We also investigate several strategies for enhancing bystander effects, thus increasing CAR T cell therapy’s overall efficacy for solid tumors.

Abstract Invasive pneumococcal disease (IPD) due to non-vaccine serotypes after the introduction of pneumococcal conjugate vaccines (PCV) remains a global concern. This study used pathogen genomics to evaluate changes in invasive pneumococcal lineages before, during and after vaccine introduction in South Africa. We included genomes (N = 3104) of IPD isolates from individuals aged

Purpose: To characterize the histologic and molecular subtype distribution of, and survival from, breast cancer (BC) among Canadian women overall, and by stage and age at diagnosis. Methods: Invasive BC cases from the Canadian Cancer Registry for women aged 15–99 years between 2012 and 2017 in Canada, excluding Quebec, were examined using pre-existing mortality linkages. Stage at diagnosis, molecular, and histologic subtypes, and 5-year net survival (NS) by age, subtype, and stage were determined. Results: 107,271 women with BC were included. Luminal A was the most common subtype, present in increasing proportions as women aged, up to a maximum of 55% of cases in 70–74. Ductal and luminal A were most likely to be diagnosed at stage I, while HER2+ had the highest proportion of diagnosis at stage III; triple negative (TN) and unknown had the highest proportion of stage IV. For all stages combined, luminal A had a five-year NS of 98%, while TN was 74%. NS for stage I BC was 99–100% for all subtypes, excepting TN, which was 96%. Survival decreased with advancing stage, most markedly for TN, for which stage III was 47% and stage IV 7%. Survival by equivalent stage and subtype was comparable across age groups but declined in older age categories. Conclusions: The varying natural histories of BC subtypes and histologies can inform prognoses, health system economics, and screening practices. The NS of 96% or greater for stage I, regardless of subtype, highlights the importance of early detection for all subtypes of BC, especially in aggressive subtypes.

The Community Multiscale Air Quality Model (CMAQ) is a local- to hemispheric-scale numerical air quality modeling system developed by the U.S. Environmental Protection Agency (USEPA) and supported by the Community Modeling and Analysis System (CMAS) center. CMAQ is used for regulatory purposes by the USEPA program offices and state and local air agencies and is also widely used by the broader global research community to simulate and understand complex air quality processes and for computational environmental fate and transport and climate and health impact studies. Leveraging state-of-the-science cloud computing resources for high-performance computing (HPC) applications, CMAQ is now available as a fully tested, publicly available technology stack (HPC cluster and software stack) for two major cloud service providers (CSPs). Specifically, CMAQ configurations and supporting materials have been developed for use on their HPC clusters, including extensive online documentation, tutorials and guidelines to scale and optimize air quality simulations using their services. These resources allow modelers to rapidly bring together CMAQ, cloud-hosted datasets, and visualization and evaluation tools on ephemeral clusters that can be deployed quickly and reliably worldwide. Described here are considerations in CMAQ version 5.3.3 cloud use and the supported resources for each CSP, presented through a benchmark application suite that was developed as an example of a typical simulation for testing and verifying components of the modeling system. The outcomes of this effort are to provide findings from performing CMAQ simulations on the cloud using popular vendor-provided resources, to enable the user community to adapt this for their own needs, and to identify specific areas of potential optimization with respect to storage and compute architectures.

Purpose: Science, technology, engineering, and mathematics (STEM) fields are not known for producing a high number of racial activists. On the contrary, scientific discourse often traffics in race-neutral language and ideologies, all the while producing racist science and technologies. This research explored the relationship between racial activism and academic career intentions of underrepresented and racially minoritized (URM) STEM doctoral students. Research Methods/Approach: We surveyed 301 Black/African American, Hispanic/Latinx, and Indigenous STEM doctoral students and 96 White and Asian STEM doctoral students. We deploy QuantCrit as a methodological stance to guide our analysis of the racial activism of students and its effect on their interest and intent in pursuing a STEM career. Findings: We found that among URM STEM doctoral students, racial activism positively predicts the likelihood of pursuing careers in academia. After controlling for the other variables in our regression models, racial activism was the strongest predictor based on standardized beta coefficients. Implications: Recent events have reactivated racial activism in academia, highlighting the experiences of URM STEM students and faculty. Yet Latinx faculty have increased minimally, Indigenous faculty numbers are stagnant, and Black faculty numbers in science and engineering are decreasing. Our research suggests that URM STEM doctoral students seek out careers in academia to leverage their commitment to racial activism by producing racially and culturally affirming science and technology for the benefit of society.