Search

Deficits in college degree attainment limit important perspectives and ways of knowing that inspire creativity and innovation. Disproportional outcomes for racially minoritized groups that are historically underrepresented in science, technology, engineering, and mathematics exacerbate this problem and promote societal inequities, structural racism, professional segregation, and racial wealth gaps. Culturally responsive programming that incorporates empathy and equity for non-majority populations can empower students from diverse backgrounds to achieve their educational goals. This paper describes the outcomes of a first-year place-based learning community in which students studied the science, culture, values, and social justice concerns of the Indigenous people of the Klamath River Basin by completing a water quality experiment alongside faculty, Indigenous scientists, and cultural experts. A combination of survey data and thematic analysis was used to evaluate the impact of the program on intellectual growth, gains in psychosocial factors associated with first-year student success, and academic achievement. All student participants demonstrated intellectual growth and gains in psychosocial factors associated with STEM retention, but the effects were most pronounced for students who identified parallels between issues faced by Native American communities and their home communities. The most significant gains in STEM retention and academic achievement occurred for URG students (students from underrepresented groups) who learned about Native American culture through the water quality laboratory. The majority of students expressed the importance of understanding the cultural, environmental, and/or social justice issues of Native American people to their future careers. We believe ours is one of the first studies that specifically examines the improved outcomes for first-year URG college STEM students that can result from curriculum that highlights scientific, cultural, and social justice concerns of Indigenous communities.

Decarbonization plans depend on the rapid, large-scale deployment of batteries to sufficiently decarbonize the electricity system and on-road transport. This can take many forms, shaped by technology, materials, and supply chain selection, which will have local and global environmental and social impacts. Current knowledge gaps limit the ability of decision-makers to make choices in facilitating battery deployment that minimizes or avoids unintended environmental and social consequences. These gaps include a lack of harmonized, accessible, and up-to-date data on manufacturing and supply chains and shortcomings within sustainability and social impact assessment methods, resulting in uncertainty that limits incorporation of research into policy making. These gaps can lead to unintended detrimental effects of large-scale battery deployment. To support decarbonization goals while minimizing negative environmental and social impacts, we elucidate current barriers to tracking how decision-making for large-scale battery deployment translates to environmental and social impacts and recommend steps to overcome them.

BACKGROUND: Identifying lipidomic markers of diet quality is needed to inform the development of biomarkers of diet, and to understand the mechanisms driving the diet- coronary heart disease (CHD) association. OBJECTIVES: This study aimed to identify lipidomic markers of diet quality and examine whether these lipids are associated with incident CHD. METHODS: Using liquid chromatography-mass spectrometry, we measured 1542 lipid species from 1694 American Indian adults (aged 18-75 years, 62% female) in the Strong Heart Family Study. Participants were followed up for development of CHD through 2020. Information on the past year diet was collected using the Block Food Frequency Questionnaire, and diet quality was assessed using the Alternative Healthy Eating Index-2010 (AHEI). Mixed-effects linear regression was used to identify individual lipids cross-sectionally associated with AHEI. In prospective analysis, Cox frailty model was used to estimate the hazard ratio (HR) of each AHEI-related lipid for incident CHD. All models were adjusted for age, sex, center, education, body mass index, smoking, alcohol drinking, level of physical activity, energy intake, diabetes, hypertension, and use of lipid-lowering drugs. Multiple testing was controlled at a false discovery rate of

Multilevel service delivery frameworks are approaches to structuring and organizing a spectrum of evidence-based services and supports, focused on assessment, prevention, and intervention designed for the local context. Exemplar frameworks in child mental health include positive behavioral interventions and supports in education, collaborative care in primary care, and systems of care in community mental health settings. Yet, their high-quality implementation has lagged. This work proposes a conceptual foundation for multilevel service delivery frameworks spanning diverse mental health service settings that can inform development of strategic implementation supports. We draw upon the existing literature for three exemplar multilevel service delivery frameworks in different child mental health service settings to (1) identify core components common to each framework, and (2) to highlight prominent implementation determinants that interface with each core component. Six interrelated components of multilevel service delivery frameworks were identified, including, (1) a systems-level approach, (2) data-driven problem solving and decision-making, (3) multiple levels of service intensity using evidence-based practices, (4) cross-linking service sectors, (5) multiple providers working together, including in teams, and (6) built-in implementation strategies that facilitate delivery of the overall model. Implementation determinants that interface with core components were identified at each contextual level. The conceptual foundation provided in this paper has the potential to facilitate cross-sector knowledge sharing, promote generalization across service settings, and provide direction for researchers, system leaders, and implementation intermediaries/practitioners working to strategically support the high-quality implementation of these frameworks.

BACKGROUND: Dyslipidemia is an independent risk factor for coronary heart disease (CHD). Standard lipid panel cannot capture the complexity of the blood lipidome (ie, all molecular lipids in the blood). To date, very few large-scale epidemiological studies have assessed the full spectrum of the blood lipidome on risk of CHD, especially in a longitudinal setting. METHODS AND RESULTS: Using an untargeted liquid chromatography-mass spectrometry, we repeatedly measured 1542 lipid species from 1835 unique American Indian participants who attended 2 clinical visits (≈5.5 years apart) and followed up to 17.8 years in the Strong Heart Family Study (SHFS). We first identified baseline lipid species associated with risk of CHD, followed by replication in a European population. The model adjusted for age, sex, body mass index, smoking, hypertension, diabetes, low-density lipoprotein cholesterol, estimated glomerular filtration rate, education, and physical activity at baseline. We then examined the longitudinal association between changes in lipid species and changes in cardiovascular risk factors during follow-up. Multiple testing was controlled by the false discovery rate. We found that baseline levels of multiple lipid species (eg, phosphatidylcholines, phosphatidylethanolamines, and ceramides) were associated with the risk of CHD and improved the prediction accuracy over conventional risk factors in American Indian people. Some identified lipids in American Indian people were replicated in European people. Longitudinal changes in multiple lipid species (eg, acylcarnitines, phosphatidylcholines, and triacylglycerols) were associated with changes in cardiovascular risk factors. CONCLUSIONS: Baseline plasma lipids and their longitudinal changes over time are associated with risk of CHD. These findings provide novel insights into the role of dyslipidemia in CHD.

Beavers are semi-aquatic rodents that are considered to be pests by humans due to their habit of building dams and the damage they cause to their surrounding ecosystems. Using a program known as NaxEnt, which is a statistical package that can determine the probabilities of species distributions based on surrounding environmental information, we analyzed both nusiance reports of beavers as well as crowdsourced information to create a habitat suitability model. It appears that beavers were most strongly associated with the land cover types of Powerlines/Utility, Non-Forested Wetland, Water-based Recreation, Cropland, and Open Land. Nuisance beavers are negatively correlated with human population density, while iNaturalist beavers were positively correlated. It appears that these models and the workflow for creating them has developed into a suitable base for future research, while also showing the effect that public participation can have on data.

Multilevel service delivery frameworks are approaches to structuring and organizing a spectrum of evidence-based services and supports, focused on assessment, prevention, and intervention designed for the local context. Exemplar frameworks in child mental health include positive behavioral interventions and supports in education, collaborative care in primary care, and systems of care in community mental health settings. Yet, their high-quality implementation has lagged. This work proposes a conceptual foundation for multilevel service delivery frameworks spanning diverse mental health service settings that can inform development of strategic implementation supports. We draw upon the existing literature for three exemplar multilevel service delivery frameworks in different child mental health service settings to (1) identify core components common to each framework, and (2) to highlight prominent implementation determinants that interface with each core component. Six interrelated components of multilevel service delivery frameworks were identified, including, (1) a systems-level approach, (2) data-driven problem solving and decision-making, (3) multiple levels of service intensity using evidence-based practices, (4) cross-linking service sectors, (5) multiple providers working together, including in teams, and (6) built-in implementation strategies that facilitate delivery of the overall model. Implementation determinants that interface with core components were identified at each contextual level. The conceptual foundation provided in this paper has the potential to facilitate cross-sector knowledge sharing, promote generalization across service settings, and provide direction for researchers, system leaders, and implementation intermediaries/practitioners working to strategically support the high-quality implementation of these frameworks.

BackgroundAfrican American smokers have 2.5 times higher risk for stroke compared with nonsmokers (higher than other races). About 50% of the African American population carry 1 or 2 genetic variants (G1 and G2; rare in other races) of the apolipoprotein L1 gene (APOL1). Studies showed these variants may be associated with stroke. However, the role of the APOL1 risk variants in tobacco-related stroke is unknown.Methods and resultsIn a cross-sectional study, we examined whether APOL1 risk variants modified the relationship between tobacco smoking and stroke prevalence in 513 African American adults recruited at University of California, San Francisco. Using DNA, plasma, and questionnaires we determined APOL1 variants, smoking status, and stroke prevalence. Using logistic regression models, we examined the association between smoking (ever versus never smokers) and stroke overall, and among carriers of APOL1 risk variants (1 or 2 risk alleles), and noncarriers, separately. Among participants, 41% were ever (current and past) smokers, 54% were carriers of the APOL1 risk variants, and 41 had a history of stroke. The association between smoking and stroke differed by APOL1 genotype (Pinteraction term=0.014). Among carriers, ever versus never smokers had odds ratio (OR) 2.46 (95% CI, 1.08-5.59) for stroke (P=0.034); OR 2.00 (95% CI, 0.81-4.96) among carriers of 1 risk allele, and OR 4.72 (95% CI, 0.62-36.02) for 2 risk alleles. Among noncarriers, smoking was not associated with a stroke.ConclusionsCurrent and past smokers who carry APOL1 G1 and/or G2 risk variants may be more susceptible to stroke among the African American population.

115, 6-9-year-olds (M age = 7.47 years) participated in a scripted event during which the child's mother or a stranger broke a forbidden puppet and requested secrecy. Then, children were either (1) primed for the goal of honesty (prime), (2) asked to promise to tell the truth (oath), or (3) given no instructions (control) before responding to open-ended, direct, and suggestive questions about their own and the transgressor's behavior. Children who had greater trust in their parents were more protective of the transgressor, disclosing later in the interview and providing fewer honest responses to direct and suggestive questions. Children were more honest in response to the suggestive than direct questions, especially when their mother had transgressed. Neither the prime nor the oath significantly promoted children's honesty. Results advance our understanding of interview and child factors that influence children's disclosures of transgressions committed by parents versus unfamiliar adults.

Communication Accommodation Theory (CAT) predicts that people adjust their language to match that of the other to promote comprehension, coordinate action, and facilitate harmonious relationships. CAT predicts that mothers will adjust their sentence length and complexity to match those of children. Prior tests of CAT confounded trait-like language use with accommodation; we refine the concept of accommodation using the theoretical logic of the Social Relations Model (SRM). We argue that (a) trait effects should be partitioned from unique relationship effects, (b) relationship effects are the appropriate estimate of accommodation, and (c) relationship (dyadic) reciprocity is the mechanism of accommodation. We tested our proposal in 152 mother-child dyads who interacted in play sessions. Mother and child language was recorded, transcribed, and coded. SRM revealed stable, trait-like individual differences in language used by each; however, this stability was much stronger among children than mothers. Both made unique reciprocal linguistic adjustments when interacting with specific adults or children. These results support a new theoretical perspective on communication accommodation and adult child-directed language.

Dyslipidemia is an independent and modifiable risk factor for aging and age-related disorders. Routine lipid panel cannot capture all individual lipid species in blood (i.e., blood lipidome). To date, a comprehensive assessment of the blood lipidome associated with mortality is lacking in large-scale community-dwelling individuals, especially in a longitudinal setting. Using liquid chromatograph-mass spectrometry, we repeatedly measured individual lipid species in 3,821 plasma samples collected at two visits (~ 5.5 years apart) from 1,930 unique American Indians in the Strong Heart Family Study. We first identified baseline lipids associated with risks for all-cause mortality and CVD mortality (mean follow-up period: 17.8 years) in American Indians, followed by replication of top hits in European Caucasians in the Malmö Diet and Cancer-Cardiovascular Cohort (n = 3,943, mean follow-up period: 23.7 years). The model adjusted age, sex, BMI, smoking, hypertension, diabetes, and LDL-c at baseline. We then examined the associations between changes in lipid species and risk of mortality. Multiple testing was controlled by false discovery rate (FDR). We found that baseline levels and longitudinal changes of multiple lipid species, e.g., cholesterol esters, glycerophospholipids, sphingomyelins, and triacylglycerols, were significantly associated with risks of all-cause or CVD mortality. Many lipids identified in American Indians could be replicated in European Caucasians. Network analysis identified differential lipid networks associated with risk of mortality. Our findings provide novel insight into the role of dyslipidemia in disease mortality and offer potential biomarkers for early prediction and risk reduction in American Indians and other ethnic groups.

Oil supply-side policies—setbacks, excise taxes and carbon taxes—are increasingly considered for decarbonizing the transportation sector. Understanding not only how such policies reduce oil extraction and greenhouse gas (GHG) emissions but also which communities receive the resulting health benefits and labour-market impacts is crucial for designing effective and equitable decarbonization pathways. Here we combine an empirical field-level oil-production model, an air pollution model and an employment model to characterize spatially explicit 2020–2045 decarbonization scenarios from various policies applied to California, a major oil producer with ambitious decarbonization goals. We find setbacks generate the largest avoided mortality benefits from reduced air pollution and the largest lost worker compensation, followed by excise and carbon taxes. Setbacks also yield the highest share of health benefits and the lowest share of lost worker compensation borne by disadvantaged communities. However, currently proposed setbacks may fail to meet California’s GHG targets, requiring either longer setbacks or additional supply-side policies.

OBJECTIVES: In an evolving era of immunotherapeutic options for persistent or recurrent laryngeal squamous cell carcinoma (LSCC), there is a need for improved biomarkers of treatment response and survival to inform optimal treatment selection and prognostication. Herein, our primary objective was to explore correlations between tumor infiltrating lymphocytes (TILs) and PD-L1 Combined Positive Score (CPS). Secondarily, we sought to explore their combined association with survival outcomes in patients with persistent or recurrent LSCC treated with salvage surgery. MATERIALS AND METHODS: This was a retrospective cohort study at a single academic medical center. Immunohistochemistry staining for TILs and PD-L1 was performed on a tissue microarray of persistent or recurrent LSCC pathologic specimens. Correlations between TIL subsets and PD-L1 CPS were examined using Pearsons correlation coefficient and survival outcomes were analyzed with the Kaplan-Meier method and log-rank tests. RESULTS: Only CD103+ TILs showed a statistically significant, weakly-positive correlation with PD-L1 CPS (r2 = 0.264, p