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Objective and Importance: The objective of this study was to describe long-term outcomes after cochlear implantation in keratitis-ichthyosis-deafness (KID) syndrome, often caused by GJB2 mutations, in the context of other reported cases. Clinical presentation and intervention: The authors conducted correlative clinical and molecular genetic analysis on two implanted patients with KID syndrome, and tabulated their clinical outcomes. Both children had initially successful surgery. In one case, due to skin-related problems, despite extensive salvage surgery cochlear explantation was required. This patient now communicates with sign language and lip-reading. This contrasts with the outcome for the other patient whereby at post-operative year 10 he is able to easily converse by telephone. Both patients each carry a de novo 148G > A GJB2 mutation.Conclusion: Patients with KID syndrome appear to be good candidates for cochlear implantation but may face significant skin-related problems which could disrupt successful post-operative habilitation. Consultation with dermatological colleagues regarding any new therapies may be warranted. [ABSTRACT FROM AUTHOR]

Age-related macular degeneration (AMD) is an inflammatory disease, which causes visual impairment and blindness in older people. The proteins of the complement system are central to the development of this disease. Local and systemic inflammation in AMD are mediated by the deregulated action of the alternative pathway of the complement system. Variants in complement system genes alter an individual's risk of developing AMD. Recent studies have shown how some risk-associated genetic variants alter the function of the complement system. In this review, we describe the evolution of the complement system and bring together recent research to form a picture of how changes in complement system genes and proteins affect the function of the complement cascade, and how this affects the development of AMD. We discuss the application of this knowledge to prevention and possible future treatments of AMD. [ABSTRACT FROM AUTHOR]

Background: Environmental toxicants may impact survival in children with cancer, but the literature investigating these associations remains limited. Because oil and gas developments emit several hazardous air pollutants, the authors evaluated the relationship between residential proximity to oil or gas development and survival across 21 different pediatric cancers., Methods: The Texas Cancer Registry had 29,730 children (≤19 years old) diagnosed with a primary cancer between 1995 to 2017. Geocoded data were available for 285,266 active oil or gas wells and 109,965 horizontal wells. The authors calculated whether each case lived within 1000 m (yes/no) from each type of oil or gas development. Survival analyses were conducted using Cox regression, adjusting for potential confounders., Results: A total of 14.2% of cases lived within 1000 m of an oil or gas well or horizontal well. Living within 1000 m of an oil or gas well was associated with risk of mortality in cases with acute myeloid leukemia (AML) (adjusted hazard ratio [aHR], 1.36; 95% confidence interval [CI], 1.01-1.84) and hepatoblastoma (aHR, 2.13; 95% CI, 1.03-4.39). An inverse association was observed with Ewing sarcoma (aHR, 0.35; 95% CI, 0.13-0.95). No associations were observed with horizontal well. There was evidence of a dose-response effect in children with AML or hepatoblastoma and residential proximity to oil or gas wells. In general, the magnitude of association increased with decreasing distance and with higher number of wells across the three distances., Conclusions: Residential proximity to oil or gas wells at diagnosis is associated with the risk of mortality in children with AML or hepatoblastoma., (© 2024 American Cancer Society.)

According to the uncertain geographic context problem, a lack of temporal information can hinder measures of bias in mortgage lending. This study extends previous methods to: (1) measure the persistence of racial bias in mortgage lending for Black Americans by adding temporal trends and credit scores, and (2) evaluate the continuity of bias in discriminatory areas from 1990 to 2020. These additions create an indicator of persistent structural housing discrimination. We studied the Boston-Cambridge-Newton and Dallas-Fort Worth metropolitan statistical areas to examine distinct historical trajectories and urban development. We estimated the odds of mortgage denial for census tracts. Overall, all tracts in Boston-Cambridge-Newton (N = 1003) and Dallas-Fort Worth (N = 1312) displayed significant change, with greater odds of bias over time in Dallas-Fort Worth and lower odds in Boston-Cambridge-Newton. Historically redlined areas displayed the strongest persistence of bias. Results suggest that temporal data can identify persistence and improve sensitivity in measuring neighborhood bias. Understanding the temporality of residential exposure can increase research rigor and inform policy to reduce the health effects of racial bias., (© 2024. The New York Academy of Medicine.)

Background: Hispanic or Latino populations (hereafter, "Latinos") are a rapidly expanding U.S. demographic and have documented inequities in preventable diseases and conditions. Many Latinos reside in ethnic enclaves, and understanding the context and healthcare accessibility within these places is critical., Objective: This study described the neighborhood social and built environment attributes of Latino enclaves and evaluated associations between enclaves and geographic healthcare accessibility., Design: Cross-sectional ecologic analysis., Subjects: Our unit of analysis was all neighborhoods (n ~ 20,000 census tracts) in California, Florida, New Jersey, New York, and Texas in years 2000 and 2010., Main Measures: The primary exposure of interest, "Latino enclaves," was defined using neighborhood-level data on the percentage of Latino residents, foreign-born Latinos, Spanish speakers with limited English proficiency, and linguistically isolated Spanish-speaking households. The primary outcome was a neighborhood-level measure of geographic healthcare accessibility of primary care physicians, which accounted for both the supply of physicians and population demand for healthcare (i.e., population size within driving distance)., Results: Approximately 30% of neighborhoods were classified as Latino enclaves, 87% of which were enclaves in both 2000 and 2010. Compared with non-enclaves, Latino enclaves had more markers of structural disadvantage including having higher proportions of poverty, uninsured individuals, crowded housing, and higher crime scores. Results from multivariable models suggest that more culturally distinct neighborhoods (i.e., higher enclave score) had lower healthcare accessibility, though when stratified, this association persisted only in high (≥ 20%) poverty neighborhoods., Conclusion: This study highlights several neighborhood structural disadvantages within Latino enclaves, including higher poverty, uninsured individuals, and crime compared to non-enclave neighborhoods. Moreover, our findings point to the need for interventions aimed at improving healthcare accessibility particularly within socioeconomically disadvantaged Latino enclaves. Addressing these inequities demands multifaceted approaches that consider both social and structural factors to ensure equitable healthcare access for Latino populations., (© 2024. The Author(s), under exclusive licence to Society of General Internal Medicine.)

The field of software engineering is advancing at astonishing speed, with packages now available to support many stages of data science pipelines. These packages can support infectious disease modelling to be more robust, efficient and transparent, which has been particularly important during the COVID-19 pandemic. We developed a package for the construction of infectious disease models, integrated it with several open-source libraries and applied this composite pipeline to multiple data sources that provided insights into Australia's 2022 COVID-19 epidemic. We aimed to identify the key processes relevant to COVID-19 transmission dynamics and thereby develop a model that could quantify relevant epidemiological parameters. The pipeline's advantages include markedly increased speed, an expressive application programming interface, the transparency of open-source development, easy access to a broad range of calibration and optimisation tools and consideration of the full workflow from input manipulation through to algorithmic generation of the publication materials. Extending the base model to include mobility effects slightly improved model fit to data, with this approach selected as the model configuration for further epidemiological inference. Under our assumption of widespread immunity against severe outcomes from recent vaccination, incorporating an additional effect of the main vaccination programs rolled out during 2022 on transmission did not further improve model fit. Our simulations suggested that one in every two to six COVID-19 episodes were detected, subsequently emerging Omicron subvariants escaped 30-60% of recently acquired natural immunity and that natural immunity lasted only one to eight months on average. We documented our analyses algorithmically and present our methods in conjunction with interactive online code notebooks and plots. We demonstrate the feasibility of integrating a flexible domain-specific syntax library with state-of-the-art packages in high performance computing, calibration, optimisation and visualisation to create an end-to-end pipeline for infectious disease modelling. We used the resulting platform to demonstrate key epidemiological characteristics of the transition from the emergency to the endemic phase of the COVID-19 pandemic., Competing Interests: The authors declare no competing interests., (© 2024 The Authors.)

Background: Recent modifications to low-dose CT (LDCT)-based lung cancer screening guidelines increase the number of eligible individuals, particularly among racial and ethnic minorities. Because these populations disproportionately live in metropolitan areas, we analyzed the association between travel time and initial LDCT completion within an integrated, urban safety-net health care system., Methods: Using Esri's StreetMap Premium, OpenStreetMap, and the r5r package in R, we determined projected private vehicle and public transportation travel times between patient residence and the screening facility for LDCT ordered in March 2017 through December 2022 at Parkland Memorial Hospital in Dallas, Texas. We characterized associations between travel time and LDCT completion in univariable and multivariable analyses. We tested these associations in a simulation of 10,000 permutations of private vehicle and public transportation distribution., Results: A total of 2,287 patients were included in the analysis, of whom 1,553 (68%) completed the initial ordered LDCT. Mean age was 63 years, and 73% were underrepresented minorities. Median travel time from patient residence to the LDCT screening facility was 17 minutes by private vehicle and 67 minutes by public transportation. There was a small difference in travel time to the LDCT screening facility by public transportation for patients who completed LDCT versus those who did not (67 vs 66 min, respectively; P=.04) but no difference in travel time by private vehicle for these patients (17 min for both; P=.67). In multivariable analysis, LDCT completion was not associated with projected travel time to the LDCT facility by private vehicle (odds ratio, 1.01; 95% CI, 0.82-1.25) or public transportation (odds ratio, 1.14; 95% CI, 0.89-1.44). Similar results were noted across travel-type permutations. Black individuals were 29% less likely to complete LDCT screening compared with White individuals., Conclusions: In an urban population comprising predominantly underrepresented minorities, projected travel time is not associated with initial LDCT completion in an integrated health care system. Other reasons for differences in LDCT completion warrant investigation.

Background and Aims: The two most common interventions used to treat painless jaundice from pancreatic cancer are endoscopic retrograde cholangiopancreatography (ERCP) and percutaneous transhepatic biliary drainage (PTBD). Our study aimed to characterize the geographic distribution of ERCP-performing hospitals among patients with pancreatic cancer in the United States and the association between geographic accessibility to ERCP-performing hospitals and biliary interventions patients receive., Methods: This is a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database for pancreatic cancer from 2005 to 2013. Multilevel models were used to examine the association between accessibility to ERCP hospitals within a 30- and 45-min drive from the patient's residential ZIP Code and the receipt of ERCP treatment. A two-step floating catchment area model was used to calculate the measure of accessibility based on the distribution across SEER regions., Results: 7464 and 782 patients underwent ERCP and PTBD, respectively, over the study period. There were 808 hospitals in which 8246 patients diagnosed with pancreatic cancer in SEER regions from 2005 to 2013 received a procedure. Patients with high accessibility within both 30- and 45-min drive to an ERCP-performing hospital were more likely to receive an ERCP (30-min adjusted odds ratio [aOR]: 1.53, 95% confidence interval [CI]: 1.17-2.01; 45-min aOR: 1.31, 95% CI: 1.01-1.70). Furthermore, in the adjusted model, Black patients (vs. White) and patients with stage IV disease were less likely to receive ERCP than PTBD., Conclusions: Patients with pancreatic cancer and high accessibility to an ERCP-performing hospital were more likely to receive ERCP. Disparities in the receipt of ERCP persisted for Black patients regardless of their access to ERCP-performing hospitals., (© 2024 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.)

Performance in visual search tasks is frequently summarised by "search slopes" - the additional cost in reaction time for each additional distractor. While search tasks with a shallow search slopes are termed efficient (pop-out, parallel, feature), there is no clear dichotomy between efficient and inefficient (serial, conjunction) search. Indeed, a range of search slopes are observed in empirical data. The Target Contrast Signal (TCS) Theory is a rare example of quantitative model that attempts to predict search slopes for efficient visual search. One study using the TCS framework has shown that the search slope in a double-feature search (where the target differs in both colour and shape from the distractors) can be estimated from the slopes of the associated single-feature searches. This estimation is done using a contrast combination model, and a collinear contrast integration model was shown to outperform other options. In our work, we extend TCS to a Bayesian multi-level framework. We investigate modelling using normal and shifted-lognormal distributions, and show that the latter allows for a better fit to previously published data. We run a new fully within-subjects experiment to attempt to replicate the key original findings, and show that overall, TCS does a good job of predicting the data. However, we do not replicate the finding that the collinear combination model outperforms the other contrast combination models, instead finding that it may be difficult to conclusively distinguish between them., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The objective of this systematic review is to identify prognostic factors among women and their offspring affected by gestational diabetes mellitus (GDM), focusing on endpoints of cardiovascular disease (CVD) and type 2 diabetes (T2D) for women, and cardiometabolic profile for offspring., Methods: This review included studies published in English language from January 1st, 1990, through September 30th, 2021, that focused on the above outcomes of interest with respect to sociodemographic factors, lifestyle and behavioral characteristics, traditional clinical traits, and 'omics biomarkers in the mothers and offspring during the perinatal/postpartum periods and across the lifecourse. Studies that did not report associations of prognostic factors with outcomes of interest among GDM-exposed women or children were excluded., Results: Here, we identified 109 publications comprising 98 observational studies and 11 randomized-controlled trials. Findings indicate that GDM severity, maternal obesity, race/ethnicity, and unhealthy diet and physical activity levels predict T2D and CVD in women, and greater cardiometabolic risk in offspring. However, using the Diabetes Canada 2018 Clinical Practice Guidelines for studies, the level of evidence was low due to potential for confounding, reverse causation, and selection biases., Conclusions: GDM pregnancies with greater severity, as well as those accompanied by maternal obesity, unhealthy diet, and low physical activity, as well as cases that occur among women who identify as racial/ethnic minorities are associated with worse cardiometabolic prognosis in mothers and offspring. However, given the low quality of evidence, prospective studies with detailed covariate data collection and high fidelity of follow-up are warranted., (© 2024. The Author(s).)

Introduction: Access to primary care has been a long-standing priority for improving population health. Asian Americans, who often settle in ethnic enclaves, have been found to underutilize health care. Understanding geographic primary care accessibility within Asian American enclaves can help to ensure the long-term health of this fast-growing population., Methods: U.S. Census data from five states (California, Florida, New Jersey, New York, and Texas) were used to develop and describe census-tract level measures of Asian American enclaves and social and built environment characteristics for years 2000 and 2010. The 2-step floating catchment area method was applied to National Provider Identifier data to develop a tract-level measure of geographic primary care accessibility. Analyses were conducted in 2022-2023, and associations between enclaves (versus nonenclaves) and geographic primary care accessibility were evaluated using multivariable Poisson regression with robust variance estimation, adjusting for potential area-level confounders., Results: Of 24,482 census tracts, 26.1% were classified as Asian American enclaves. Asian American enclaves were more likely to be metropolitan and have less poverty, lower crime, and lower proportions of uninsured individuals than nonenclaves. Asian American enclaves had higher primary care accessibility than nonenclaves (adjusted prevalence ratio=1.23, 95% CI=1.17, 1.29)., Conclusions: Asian American enclaves in five of the most diverse and populous states in the U.S. had fewer markers of disadvantage and greater geographic primary care accessibility. This study contributes to the growing body of research elucidating the constellation of social and built environment features within Asian American enclaves and provides evidence of health-promoting characteristics of these neighborhoods., (Copyright © 2023 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Population models of cancer reflect the overall US population by drawing on numerous existing data resources for parameter inputs and calibration targets. Models require data inputs that are appropriately representative, collected in a harmonized manner, have minimal missing or inaccurate values, and reflect adequate sample sizes. Data resource priorities for population modeling to support cancer health equity include increasing the availability of data that 1) arise from uninsured and underinsured individuals and those traditionally not included in health-care delivery studies, 2) reflect relevant exposures for groups historically and intentionally excluded across the full cancer control continuum, 3) disaggregate categories (race, ethnicity, socioeconomic status, gender, sexual orientation, etc.) and their intersections that conceal important variation in health outcomes, 4) identify specific populations of interest in clinical databases whose health outcomes have been understudied, 5) enhance health records through expanded data elements and linkage with other data types (eg, patient surveys, provider and/or facility level information, neighborhood data), 6) decrease missing and misclassified data from historically underrecognized populations, and 7) capture potential measures or effects of systemic racism and corresponding intervenable targets for change., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Aims/hypothesis: In pregnancies where the mother has glucokinase-MODY (GCK-MODY), fetal growth is determined by fetal genotype. When the fetus inherits a maternal pathogenic GCK variant, normal fetal growth is anticipated, and insulin treatment of maternal hyperglycaemia is not recommended. At present, fetal genotype is estimated from measurement of fetal abdominal circumference on ultrasound. Non-invasive prenatal testing of fetal GCK genotype (NIPT-GCK) using cell-free DNA in maternal blood has recently been developed. We aimed to compare the diagnostic accuracy of NIPT-GCK with that of ultrasound, and determine the feasibility of using NIPT-GCK to guide pregnancy management., Methods: We studied an international cohort of pregnant women with hyperglycaemia due to GCK-MODY. We compared the diagnostic accuracy of NIPT-GCK with that of measurement of fetal abdominal circumference at 28 weeks' gestation (n=38) using a directly genotyped offspring sample as the reference standard. In a feasibility study, we assessed the time to result given to clinicians in 43 consecutive pregnancies affected by GCK-MODY between July 2019 and September 2021., Results: In terms of diagnostic accuracy, NIPT-GCK was more sensitive and specific than ultrasound in predicting fetal genotype (sensitivity 100% and specificity 96% for NIPT-GCK vs sensitivity 53% and specificity 61% for fetal abdominal circumference 75th percentile). In terms of feasibility, a valid NIPT-GCK fetal genotype (≥95% probability) was reported in all 38 pregnancies with an amenable variant and repeated samples when needed. The median time to report was 5 weeks (IQR 3-8 weeks). For the 25 samples received before 20 weeks' gestation, results were reported at a median gestational age of 20 weeks (IQR 18-24), with 23/25 (92%) reported before 28 weeks., Conclusions/interpretation: Non-invasive prenatal testing of fetal genotype in GCK-MODY pregnancies is highly accurate and is capable of providing a result before the last trimester for most patients. This means that non-invasive prenatal testing of fetal genotype is the optimal approach to management of GCK-MODY pregnancies., (© 2023. The Author(s).)

Background: Informal learning experiences in science, technology, engineering, and math (STEM) can enhance STEM learning that occurs in formal educational settings and curricula as well as generate enthusiasm for considering STEM careers. The aim of this systematic review is to focus on the experiences of neurodiverse students in informal STEM learning. Neurodiversity is a subgroup of neurodevelopmental conditions, such as autism, attention deficit disorder, dyslexia, dyspraxia, and other neurological conditions. The neurodiversity movement regards these conditions as natural forms of human variation, as opposed to dysfunction, and recognizes that neurodiverse individuals possess many strengths relevant to STEM fields., Methods: The authors will systematically search electronic databases for relevant research and evaluation articles addressing informal STEM learning for K-12 children and youth with neurodiverse conditions. Seven databases and content-relevant websites (e.g., informalscience.org) will be searched using a predetermined search strategy and retrieved articles will be screened by two members of the research team. Data synthesis will include meta-synthesis techniques, depending on the designs of the studies., Discussion: The synthesis of the findings resulting from various research and evaluation designs, across the K-12 age span, and across various informal STEM learning contexts, will lead to depth and breadth of understanding of ways to improve informal STEM learning programs for neurodiverse children and youth. The identification of informal STEM learning program components and contexts shown to yield positive results will provide specific recommendations for improving inclusiveness, accessibility, and STEM learning for neurodiverse children and youth., Trial Registration: The current study has been registered in PROSPERO., Registration Number: CRD42021278618., (© 2023. The Author(s).)

Background: Social connectedness decreases human mortality, improves cancer survival, cardiovascular health, and body mass, results in better-controlled glucose levels, and strengthens mental health. However, few public health studies have leveraged large social media data sets to classify user network structure and geographic reach rather than the sole use of social media platforms., Objective: The objective of this study was to determine the association between population-level digital social connectedness and reach and depression in the population across geographies of the United States., Methods: Our study used an ecological assessment of aggregated, cross-sectional population measures of social connectedness, and self-reported depression across all counties in the United States. This study included all 3142 counties in the contiguous United States. We used measures obtained between 2018 and 2020 for adult residents in the study area. The study's main exposure of interest is the Social Connectedness Index (SCI), a pair-wise composite index describing the "strength of connectedness between 2 geographic areas as represented by Facebook friendship ties." This measure describes the density and geographical reach of average county residents' social network using Facebook friendships and can differentiate between local and long-distance Facebook connections. The study's outcome of interest is self-reported depressive disorder as published by the Centers for Disease Control and Prevention., Results: On average, 21% (21/100) of all adult residents in the United States reported a depressive disorder. Depression frequency was the lowest for counties in the Northeast (18.6%) and was highest for southern counties (22.4%). Social networks in northeastern counties involved moderately local connections (SCI 5-10 the 20th percentile for n=70, 36% of counties), whereas social networks in Midwest, southern, and western counties contained mostly local connections (SCI 1-2 the 20th percentile for n=598, 56.7%, n=401, 28.2%, and n=159, 38.4%, respectively). As the quantity and distance that social connections span (ie, SCI) increased, the prevalence of depressive disorders decreased by 0.3% (SE 0.1%) per rank., Conclusions: Social connectedness and depression showed, after adjusting for confounding factors such as income, education, cohabitation, natural resources, employment categories, accessibility, and urbanicity, that a greater social connectedness score is associated with a decreased prevalence of depression., (©Alaina M Beauchamp, Christoph U Lehmann, Richard J Medford, Amy E Hughes. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 27.03.2023.)

Background-matching camouflage is a well-established strategy to reduce detection, but implementing this on heterogeneous backgrounds is challenging. For prey with fixed color patterns, solutions include specializing on a particular visual microhabitat, or adopting a compromise or generalist appearance, matching multiple backgrounds less well. Existing studies suggest both approaches can succeed, but most consider relatively simple scenarios, where artificial prey appear against two backgrounds differing in a single visual characteristic. Here, we used computer-based search tasks with human participants to test the relative benefits of specializing and generalizing for complex targets, displayed on either two or four types of naturalistic backgrounds. Across two background types, specialization was beneficial on average. However, the success of this strategy varied with search duration, such that generalist targets could outperform specialists over short search durations due to the presence of poorly matched specialists. Over longer searches, the remaining well-matched specialists had greater success than generalists, leading to an overall benefit of specialization at longer search durations. Against four different backgrounds, the initial cost to specialization was greater, so specialists and generalists ultimately experienced similar survival. Generalists performed better when their patterning was a compromise between backgrounds that were more similar to each other than when backgrounds were more different, with similarity in luminance more relevant than pattern differences. Time dependence in the relative success of these strategies suggests that predator search behavior may affect optimal camouflage in real-world situations., Competing Interests: We declare we have no conflicts of interest., (© The Author(s) 2023. Published by Oxford University Press on behalf of the International Society for Behavioral Ecology.)

In situ X-ray computed tomography (X-ray CT) is used to investigate the effects of characteristic microstructural features on the pitting initiation and propagation in austenitic stainless steel specimens prepared with laser powder bed fusion (LPBF) additive manufacturing. In situ X-ray CT in probing the mechanism and kinetics of localized corrosion is demonstrated by immersing two LPBF specimens with different porosities in an aggressive ferric chloride solution for the evaluation of corrosion. X-ray CT images are acquired from the specimens after every 8 hours of immersion over an extended period of time (216 hours). Corrosion pit growth is then quantitatively analyzed with a data-constrained modeling method. The pitting growth mechanism of LPBF stainless steel is found to be different from that of conventional stainless steels. More specifically, the mechanism of corrosion pit initiation is closely correlated with the original lack of fusion porosity (LOF) distribution on the surface of the specimens and preferential pit propagation through the LOF pores inside the specimens. Pit growth kinetics are derived from pit volume changes determined through 3D data analysis. The pit growth kinetics in LPBF specimens are found to vary in the initial pit formation, competitive pit propagation, and the dominant pit growth stages., (© 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Foraging refers to search involving multiple targets or multiple types of targets, and as a model task has a long history in animal behaviour and human cognition research. Foraging behaviour is usually operationalized using summary statistics, such as average distance covered during target collection (the path length) and the frequency of switching between target types. We recently introduced an alternative approach, which is to model each instance of target selection as random selection without replacement. Our model produces estimates of a set of foraging biases, such as a bias to select closer targets or targets of a particular category. Here we apply this model to predict individual target selection events. We add a new start position bias to the model, and generate foraging paths using the parameters estimated from individual participants' pre-existing data. The model predicts which target the participant will select next with a range of accuracy from 43% to 69% across participants (chance is 11%). The model therefore explains a substantial proportion of foraging behaviour in this paradigm. The situations where the model makes errors reveal useful information to guide future research on those aspects of foraging that we have not yet explained.

Racial and ethnic inequities in survival persist for children with acute lymphoblastic leukemia (ALL). In the US, there are strong associations between SES, race/ethnicity, and place of residence. This is evidenced by ethnic enclaves: neighborhoods with high concentrations of ethnic residents, immigrants, and language isolation. The Latinx enclave index (LEI) can be used to investigate how residence in a Latinx enclave is associated with health outcomes. We studied the association between LEI score and minimal residual disease (MRD) in 142 pediatric ALL patients treated at Texas Children's Hospital. LEI score was associated with end-induction MRD positivity (OR per unit increase 1.63, CI 1.12-2.46). There was also a significant trend toward increased odds of MRD positivity among children living in areas with the highest enclave index scores. MRD positivity at end of induction is associated with higher incidence of relapse and lower overall survival among children with ALL; future studies are needed to elucidate the exact causes of these findings and to improve ALL outcomes among children residing within Latinx enclaves.Supplemental data for this article is available online at https://doi.org/10.1080/08880018.2022.2047850.

Introduction: Texas Health Resources (THR), a large, nonprofit health care system based in the Dallas-Fort Worth area, has collaborated with the University of Texas Southwestern Medical Center (UTSW) to develop and operate a unique, integrated approach for Learning Health System (LHS) workforce development. This training model centers on academic health system faculty members conducting later-stage translational research within a partnering regional care delivery organization., Methods: The THR Clinical Scholars Program engages early career UTSW faculty members to conduct studies that are likely to have an impact on care delivery at the health system level. Interested candidates submit formal applications to the program. A joint committee comprised of senior research faculty from UTSW and THR clinical leadership reviews proposals with a focus on the shared LHS needs of both institutions-developing high quality research output that can be applied to enhance care delivery. A key prioritization criterion for funding is the degree to which the research addresses a question relevant to THR as a high-volume network with multiple channels for consumers to access care. The program emphasis is on supporting embedded research initiatives using health system data to generate knowledge that will improve the quality and efficiency of care for the patient populations served by the participant organizations., Results: We discuss specific strategic and tactical components of the THR Clinical Scholars Program including an overview of the academic affiliation agreement between the collaborating organizations, criteria for successful program applications, data sharing, and funding. We also share project summaries from selected clinical scholars as examples of the LHS research done in the program to date., Conclusion: This experience report provides an implementation framework for other academic health systems interested in adopting similar LHS workforce training models with community partners., Competing Interests: Drs. Medford, Hughes, and Pandey have had institutional salary and research services support through the Texas Health Clinical Scholars Program. Drs. Peterson and Lehman oversee UTSW programs partially funded through the Texas Health Resources‐UTSW academic affiliation agreement. The other authors have no conflicts of interest to declare., (© 2022 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.)

Background: Incidence rates of gastric cancer are increasing in young adults (age <50 years), particularly among Hispanic persons. We estimated incidence rates of early-onset gastric cancer (EOGC) among Hispanic and non-Hispanic White persons by census tract poverty level and county-level metro/nonmetro residence., Methods: We used population-based data from the California and Texas Cancer Registries from 1995 to 2016 to estimate age-adjusted incidence rates of EOGC among Hispanic and non-Hispanic White persons by year, sex, tumor stage, census tract poverty level, metro versus nonmetro county, and state. We used logistic regression models to identify factors associated with distant stage diagnosis., Results: Of 3,047 persons diagnosed with EOGC, 73.2% were Hispanic White. Incidence rates were 1.29 [95% confidence interval (CI), 1.24-1.35] and 0.31 (95% CI, 0.29-0.33) per 100,000 Hispanic White and non-Hispanic White persons, respectively, with consistently higher incidence rates among Hispanic persons at all levels of poverty. There were no statistically significant associations between ethnicity and distant stage diagnosis in adjusted analysis., Conclusions: There are ethnic disparities in EOGC incidence rates that persist across poverty levels., Impact: EOGC incidence rates vary by ethnicity and poverty; these factors should be considered when assessing disease risk and targeting prevention efforts., (©2022 American Association for Cancer Research.)

Background: Human birthweight is a complex, multifactorial trait. Maternal characteristics contribute to birthweight variation by influencing the intrauterine environment. Variation explained by genetic effects is also important, but their contributions have not been assessed alongside other key determinants. We aimed to investigate variance in birthweight explained by genetic scores in addition to easily-measurable clinical and anthropometric variables., Methods: We analysed 549 European-ancestry parent-offspring trios from a UK community-based birth cohort. We investigated variance explained in birthweight (adjusted for sex and gestational age) in multivariable linear regression models including genetic scores, routinely-measured maternal characteristics, and parental anthropometric variables. We used R-Squared (R 2 ) to estimate variance explained, adjusted R-squared (Adj-R 2 ) to assess improvement in model fit from added predictors, and F-tests to compare nested models., Results: Maternal and fetal genetic scores together explained 6.0% variance in birthweight. A model containing maternal age, weight, smoking, parity and 28-week fasting glucose explained 21.7% variance. Maternal genetic score explained additional variance when added to maternal characteristics (Adj-R 2  = 0.233 vs Adj-R 2  = 0.210, p < 0.001). Fetal genetic score improved variance explained (Adj-R 2  = 0.264 vs 0.248, p < 0.001) when added to maternal characteristics and parental heights., Conclusions: Genetic scores account for variance explained in birthweight in addition to easily measurable clinical variables. Parental heights partially capture fetal genotype and its contribution to birthweight, but genetic scores explain additional variance. While the genetic contribution is modest, it is comparable to that of individual clinical characteristics such as parity, which suggests that genetics could be included in tools aiming to predict risk of high or low birthweights., (© 2022. The Author(s).)

Background: Monitoring disease incidence rates over time with population surveillance data is fundamental to public health research and practice. Bayesian disease monitoring methods provide advantages over conventional methods including greater flexibility in model specification and the ability to conduct formal inference on model-derived quantities of interest. However, software platforms for Bayesian inference are often inaccessible to nonspecialists., Objective: To increase the accessibility of Bayesian methods among health surveillance researchers, we introduce a Bayesian methodology and open source software package, surveil, for time-series modeling of disease incidence and mortality. Given case count and population-at-risk data, the software enables health researchers to draw inferences about underlying risk and derivative quantities including age-standardized rates, annual and cumulative percent change, and measures of inequality., Methods: We specify a Poisson likelihood for case counts and model trends in log-risk using the first-difference (random-walk) prior. Models in the surveil R package were built using the Stan modeling language. We demonstrate the methodology and software by analyzing age-standardized colorectal cancer (CRC) incidence rates by race and ethnicity for non-Latino Black (Black), non-Latino White (White), and Hispanic/Latino (of any race) adults aged 50-79 years in Texas's 4 largest metropolitan statistical areas between 1999 and 2018., Results: Our analysis revealed a cumulative decline of 31% (95% CI -37% to -25%) in CRC risk among Black adults, 17% (95% CI -23% to -11%) for Latino adults, and 35% (95% CI -38% to -31%) for White adults from 1999 to 2018. None of the 3 observed groups experienced significant incidence reduction in the final 4 years of the study (2015-2018). The Black-White rate difference (per 100,000) was 44 (95% CI 30-57) in 1999 and 35 (95% CI 28-43) in 2018. Cumulatively, the Black-White gap accounts for 3983 CRC cases (95% CI 3746-4219) or 31% (95% CI 29%-32%) of total CRC incidence among Black adults in this period., Conclusions: Stalled progress on CRC prevention and excess CRC risk among Black residents warrant special attention as cancer prevention and control priorities in urban Texas. Our methodology and software can help the public and health agencies monitor health inequalities and evaluate progress toward disease prevention goals. Advantages of the methodology over current common practice include the following: (1) the absence of piecewise linearity constraints on the model space, and (2) formal inference can be undertaken on any model-derived quantities of interest using Bayesian methods., (©Connor Donegan, Amy E Hughes, Simon J Craddock Lee. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 16.08.2022.)

Egg rejection is a crucial defence strategy against brood parasitism that requires the host to correctly recognise the foreign egg. Rejection behaviour has, thus, evolved in many hosts, facilitated by the visual differences between the parasitic and host eggs, and driving hosts to rely on colour and pattern cues. On the other hand, the need to recognise non-egg-shaped objects to carry out nest sanitation led birds to evolve the ability to discriminate and eject objects using mainly shape cues. However, little is known regarding the evolutionary significance of rejection behaviour in general and the cognitive processes underlying it. Here, we investigated the response of the barn swallow (Hirundo rustica) during pre-laying and laying stages to four objects types that differed in shape (eggs vs stars) and colour/pattern (mimetic vs non-mimetic) to investigate (1) what cognitive mechanisms are involved in object discrimination and (2) whether egg rejection is a direct defence against brood parasitism, or simply a product of nest sanitation. We found that swallows ejected stars more often than eggs in both stages, indicating that swallows possess a template for the shape of their eggs. Since the effect of colour/pattern on ejection decisions was minor, we suggest that barn swallows have not evolved a direct defence against brood parasitism but instead, egg ejection might be a product of their well-developed nest sanitation behaviour. Nonetheless, the fact that mimetic eggs were ejected especially in the pre-laying stage shows that nest sanitation could be an effective defence against poorly timed brood parasitism., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: Obesity is associated with kidney stone disease, but it is unknown whether this association differs by SES. This study assessed the extent to which obesity and neighborhood characteristics jointly contribute to urinary risk factors for kidney stone disease., Methods: This was a retrospective analysis of adult patients with kidney stone disease evaluated with 24-hour urine collection (2001-2020). Neighborhood-level socioeconomic data were obtained for a principal component analysis, which identified 3 linearly independent factors. Associations between these factors and 24-hour urine measurements were assessed using linear regression as well as groupings of 24-hour urine results using multivariable logistic regression. Finally, multiplicative interactions were assessed testing effect modification by obesity, and analyses stratified by obesity were performed. Analyses were performed in 2021., Results: In total, 1,264 patients met the study criteria. Factors retained on principal component analysis represented SES, family structure, and housing characteristics. On linear regression, there was a significant inverse correlation between SES and 24-hour urine sodium (p=0.0002). On multivariable logistic regression, obesity was associated with increased odds of multiple stone risk factors (OR=1.61; 95% CI=1.15, 2.26) and multiple dietary factors (OR=1.33; 95% CI=1.06, 1.67). No significant and consistent multiplicative interactions were observed between obesity and quartiles of neighborhood SES, family structure, or housing characteristics., Conclusions: Obesity was associated with the presence of multiple stone risk factors and multiple dietary factors; however, the strength and magnitude of these associations did not vary significantly by neighborhood SES, family structure, and housing characteristics., (Copyright © 2022 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Background: We explore the ivermectin discourse and sentiment in the United States with a special focus on political leaning through the social media blogging site Twitter., Methods: We used sentiment analysis and topic modeling to geospatially explore ivermectin Twitter discourse in the United States and compared it to the political leaning of a state based on the 2020 presidential election., Results: All modeled topics were associated with a negative sentiment. Tweets originating from democratic leaning states were more likely to be negative., Conclusions: Real-time analysis of social media content can identify public health concerns and guide timely public health interventions tackling disinformation., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Texas discontinued state-sponsored business restrictions and mask mandates on March 10, 2021, and mandated that no government officials, including public school officials, may implement mask requirements even in areas where COVID-19 hospitalizations comprised more than 15% of hospitalizations. Nonetheless, some public school districts began the 2021-2022 school year with mask mandates in place. We used quasi-experimental methods to analyze the impact of school mask mandates, which appear to have resulted in approximately 40 fewer student cases per week in the first eight weeks of school. ( Am J Public Health . 2022;112(6):871-875. https://doi.org/10.2105/AJPH.2022.306769).

Foraging entails finding multiple targets sequentially. In humans and other animals, a key observation has been a tendency to forage in 'runs' of the same target type. This tendency is context-sensitive, and in humans, it is strongest when the targets are difficult to distinguish from the distractors. Many important questions have yet to be addressed about this and other tendencies in human foraging, and a key limitation is a lack of precise measures of foraging behaviour. The standard measures tend to be run statistics, such as the maximum run length and the number of runs. But these measures are not only interdependent, they are also constrained by the number and distribution of targets, making it difficult to make inferences about the effects of these aspects of the environment on foraging. Moreover, run statistics are underspecified about the underlying cognitive processes determining foraging behaviour. We present an alternative approach: modelling foraging as a procedure of generative sampling without replacement, implemented in a Bayesian multilevel model. This allows us to break behaviour down into a number of biases that influence target selection, such as the proximity of targets and a bias for selecting targets in runs, in a way that is not dependent on the number of targets present. Our method thereby facilitates direct comparison of specific foraging tendencies between search environments that differ in theoretically important dimensions. We demonstrate the use of our model with simulation examples and re-analysis of existing data. We believe our model will provide deeper insights into visual foraging and provide a foundation for further modelling work in this area., Competing Interests: The authors have declared that no competing interests exist.

Hispanic children with acute lymphoblastic leukemia (ALL) experience poorer overall survival (OS) than non-Hispanic White children; however, few studies have investigated the social determinants of this disparity. In Texas, many Hispanic individuals reside in ethnic enclaves-areas with high concentrations of immigrants, ethnic-specific businesses, and language isolation, which are often socioeconomically deprived. We determined whether enclave residence was associated with ALL survival, overall and among Hispanic children. We computed Hispanic enclave index scores for Texas census tracts, and classified children ( N = 4083) as residing in enclaves if their residential tracts scored in the highest statewide quintile. We used Cox regression to evaluate the association between enclave residence and OS. Five-year OS was 78.6% for children in enclaves, and 77.8% for Hispanic children in enclaves, both significantly lower ( p < 0.05) than the 85.8% observed among children not in enclaves. Children in enclaves had increased risk of death (hazard ratio (HR) 1.20, 95% confidence interval (CI) 1.01-1.49) after adjustment for sex, age at diagnosis, year of diagnosis, metropolitan residence and neighborhood socioeconomic deprivation and after further adjustment for child race/ethnicity (HR 1.19, 95% CI 0.97-1.45). We observed increased risk of death when analyses were restricted to Hispanic children specifically (HR 1.30, 95% CI 1.03-1.65). Observations suggest that children with ALL residing in Hispanic enclaves experience inferior OS.

Purpose: We reviewed the available evidence regarding health disparities in kidney stone disease to identify knowledge gaps in this area., Materials and Methods: A literature search was conducted using PubMed®, Embase® and Scopus® limited to articles published in English from 1971 to 2020. Articles were selected based on their relevance to disparities in kidney stone disease among adults in the United States., Results: Several large epidemiological studies suggest disproportionate increases in incidence and prevalence of kidney stone disease among women as well as Black and Hispanic individuals in the United States, whereas other studies of comparable size do not report racial and ethnic demographics. Numerous articles describe disparities in imaging utilization, metabolic workup completion, analgesia, surgical intervention, stone burden at presentation, surgical complications, followup, and quality of life based on race, ethnicity, socioeconomic status and place of residence. Differences in urinary parameters based on race, ethnicity and socioeconomic status may be explained by both dietary and physiological factors. All articles assessed had substantial risk of selection bias and confounding., Conclusions: Health disparities are present in many aspects of kidney stone disease. Further research should focus not only on characterization of these disparities but also on interventions to reduce or eliminate them.