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Post-operative transesophageal echocardiography (TEE) is standard of care to evaluate for residual disease and quality of surgical repair. The residual lesion score (RLS) as defined by the pediatric heart network explored the impact of residual lesions on outcomes using discharge transthoracic echocardiogram (TTE). In tetralogy of fallot with pulmonary stenosis (TOF/PS), the residual right ventricular outflow tract (RVOT) gradient is one marker of quality of repair. Given peri-operative differences in hemodynamics, this study aims to define the correlation between TEE and discharge TTE RVOT gradient. This single center retrospective study included patients with TOF/PS undergoing primary repair with accompanying perioperative TEE and discharge TTE. TEE and TTE measurements were compared. An RLS based on the type of repair was assigned to the post-operative TEE based on the RVOT doppler velocity. TEE RVOT peak velocity and VTI correlated with TTE RVOT peak velocity (Spearman rank correlation coefficient = 0.62 (p < 0.001)) and VTI (Spearman rank correlation coefficient = 0.66 (p < 0.001)) at time of discharge. Application of RLS at the time of the TEE does not accurately reflect RLS at the time of discharge based on current criteria (p-value based on McNemar's Chi-squared test = 0.24). The ability of post-op TEE measurement to predict need for re-intervention is just as effective as TTE. On ROC analysis, the TEE RVOT peak velocity had similar AUC (0.672) compared to discharge TTE RVOT peak velocity (0.721) on predicting need for re-intervention. After surgical repair of TOF/PS, there is a strong correlation between post-op TEE and discharge RVOT peak velocity. TEE offers a chance to guide immediate re-intervention if needed and may be applied to severe residual post-op RVOT peak velocity. Further studies are needed to identify RLS based on TEE and its relationship to outcomes and intraoperative management. [ABSTRACT FROM AUTHOR]

Context Treatment for transmasculine youth (TMY) can involve testosterone treatment and is sometimes preceded by gonadotropin-releasing hormone agonist (GnRHa) treatment for puberty blockade. GnRHas can increase final height in birth-assigned females with central precocious puberty. Maximizing final adult height (FAH) is an important outcome for many TMY. Objective Our objective was to determine how GnRHa treatment before testosterone impacts FAH. Methods Retrospective cohort study at 5 US transgender health clinics. Participants were 32 TMY treated with GnRHas in early to midpuberty before testosterone (GnRHa + T group) and 62 late/postpubertal TMY treated with testosterone only (T-only group). Results The difference between FAH minus midparental target height (MPTH) was +2.3 ± 5.7 cm and −2.2 ± 5.6 cm in the GnRHa + T and T-only groups, respectively (P <.01). In the GnRHa + T group, FAH was 1.8 ± 3.4 cm greater than predicted adult height (PAH) (P <.05) and FAH vs initial height (IH) z-score was 0.5 ± 1.2 vs 0.16 ± 1.0 (P <.05). After adjusting for patient characteristics, each additional month of GnRHa monotherapy increased FAH by 0.59 cm (95% CI 0.31, 0.9 cm), stage 3 breast development at start of GnRHa was associated with 6.5 cm lower FAH compared with stage 2 (95% CI −10.43, −2.55), and FAH was 7.95 cm greater in the GnRHa + T group than in T-only group (95% CI −10.85, −5.06). Conclusion Treatment with GnRHa in TMY in early puberty before testosterone increases FAH compared with MPTH, PAH, IH, and TMY who only received testosterone in late/postpuberty. TMY considering GnRHas should be counseled that GnRHas may mildly increase their FAH if started early. [ABSTRACT FROM AUTHOR]

Background: Congenital heart disease (CHD) is the most common birth defect, influenced by maternal health, environmental conditions, and genetics. Maternal health and nutrition, particularly maternal diabetes, is a modifiable risk factor for development of CHD in the fetus. However, the importance of food access during pregnancy on the development of CHD remains unknown. The objective of this study was to investigate the association between maternal neighborhood characteristics, particularly food access, and occurrence of prenatally diagnosed CHD. Methods: A retrospective case series studied maternal-fetal dyads with prenatally diagnosed CHD between 2019 and 2021 in Washington, DC. Moran's I of maternal addresses evaluated geographic clustering of disease. Negative binomial regression assessed association between census tract demographics and population-adjusted CHD rate. Results: A total of 307 dyads were analyzed. Global Moran's I showed significant CHD clustering (p-value = .004). However, degree of clustering was not clinically meaningful. After adjusting for neighborhood socioeconomic status, residing in food deserts was not a predictor for CHD. However, neighborhoods with a higher percentage of households receiving Supplemental Nutrition Assistance Program (SNAP) benefits were associated with higher rates of conotruncal heart defects (Incident Rate Ratio [IRR] = 1.04, CI = 1.01-1.08) and aggregate CHD (IRR = 1.03, CI = 1.01-1.05). Conclusions: Neighborhood location and food access were not associated with CHD. However, increased enrollment in SNAP was associated with higher rates of CHD. The association between CHD and SNAP benefits warrants further exploration. Understanding food access and maternal nutrition may illuminate disparities in the burden of CHD. [ABSTRACT FROM AUTHOR]

Background: Despite profound financial challenges during the COVID‐19 pandemic, there is a gap in estimating their effects on mental health and well‐being among older adults. Methods: The National Health and Aging Trends Study is an ongoing nationally representative cohort study of US older adults. Outcomes included mental health related to COVID‐19 (scores averaged across eight items ranging from one to four), sleep quality during COVID‐19, loneliness during COVID‐19, having time to yourself during COVID‐19, and hopefulness during COVID‐19. Exposures included income decline during COVID‐19 and financial difficulty due to COVID‐19. Propensity score weighting produced covariate balance for demographic, socioeconomic, household, health, and well‐being characteristics that preceded the pandemic to estimate the average treatment effect. Sampling weights accounted for study design and non‐response. Results: In weighted and adjusted analyses (n = 3257), both income decline during COVID‐19 and financial difficulty due to COVID‐19 were associated with poorer mental health related to COVID‐19 (b = −0.159, p < 0.001 and b = −0.381, p < 0.001, respectively), poorer quality sleep (OR = 0.63, 95% CI: 0.46, 0.86 and OR = 0.42, 95% CI: 0.30, 0.58, respectively), more loneliness (OR = 1.53, 95% CI: 1.16, 2.02 and OR = 2.72, 95% CI: 1.96, 3.77, respectively), and less time to yourself (OR = 0.54, 95% CI: 0.40, 0.72 and OR = 0.37, 95% CI: 0.27, 0.51, respectively) during COVID‐19. Conclusions: Pandemic‐related financial challenges are associated with worse mental health and well‐being regardless of pre‐pandemic characteristics, suggesting that they are distinct social determinants of health for older adults. Timely intervention is needed to support older adults experiencing pandemic‐related financial challenges. [ABSTRACT FROM AUTHOR]

Collecting neighborhood data can both be time- and resource-intensive, especially across broad geographies. In this study, we leveraged 1.4 million publicly available Google Street View (GSV) images from Utah to construct indicators of the neighborhood built environment and evaluate their associations with 2017–2019 health outcomes of approximately one-third of the population living in Utah. The use of electronic medical records allows for the assessment of associations between neighborhood characteristics and individual-level health outcomes while controlling for predisposing factors, which distinguishes this study from previous GSV studies that were ecological in nature. Among 938,085 adult patients, we found that individuals living in communities in the highest tertiles of green streets and non-single-family homes have 10–27% lower diabetes, uncontrolled diabetes, hypertension, and obesity, but higher substance use disorders—controlling for age, White race, Hispanic ethnicity, religion, marital status, health insurance, and area deprivation index. Conversely, the presence of visible utility wires overhead was associated with 5–10% more diabetes, uncontrolled diabetes, hypertension, obesity, and substance use disorders. Our study found that non-single-family and green streets were related to a lower prevalence of chronic conditions, while visible utility wires and single-lane roads were connected with a higher burden of chronic conditions. These contextual characteristics can better help healthcare organizations understand the drivers of their patients' health by further considering patients' residential environments, which present both risks and resources. [ABSTRACT FROM AUTHOR]

Objectives: Built environments can affect health, but data in many geographic areas are limited. We used a big data source to create national indicators of neighborhood quality and assess their associations with health. Methods: We leveraged computer vision and Google Street View images accessed from December 15, 2017, through July 17, 2018, to detect features of the built environment (presence of a crosswalk, non–single-family home, single-lane roads, and visible utility wires) for 2916 US counties. We used multivariate linear regression models to determine associations between features of the built environment and county-level health outcomes (prevalence of adult obesity, prevalence of diabetes, physical inactivity, frequent physical and mental distress, poor or fair self-rated health, and premature death [in years of potential life lost]). Results: Compared with counties with the least number of crosswalks, counties with the most crosswalks were associated with decreases of 1.3%, 2.7%, and 1.3% of adult obesity, physical inactivity, and fair or poor self-rated health, respectively, and 477 fewer years of potential life lost before age 75 (per 100 000 population). The presence of non–single-family homes was associated with lower levels of all health outcomes except for premature death. The presence of single-lane roads was associated with an increase in physical inactivity, frequent physical distress, and fair or poor self-rated health. Visible utility wires were associated with increases in adult obesity, diabetes, physical and mental distress, and fair or poor self-rated health. Conclusions: The use of computer vision and big data image sources makes possible national studies of the built environment's effects on health, producing data and results that may inform national and local decision-making. [ABSTRACT FROM AUTHOR]

Background: The built environment is a structural determinant of health and has been shown to influence health expenditures, behaviors, and outcomes. Traditional methods of assessing built environment characteristics are time-consuming and difficult to combine or compare. Google Street View (GSV) images represent a large, publicly available data source that can be used to create indicators of characteristics of the physical environment with machine learning techniques. The aim of this study is to use GSV images to measure the association of built environment features with health-related behaviors and outcomes at the census tract level.Methods: We used computer vision techniques to derive built environment indicators from approximately 31 million GSV images at 7.8 million intersections. Associations between derived indicators and health-related behaviors and outcomes on the census-tract level were assessed using multivariate regression models, controlling for demographic factors and socioeconomic position. Statistical significance was assessed at the α = 0.05 level.Results: Single lane roads were associated with increased diabetes and obesity, while non-single-family home buildings were associated with decreased obesity, diabetes and inactivity. Street greenness was associated with decreased prevalence of physical and mental distress, as well as decreased binge drinking, but with increased obesity. Socioeconomic disadvantage was negatively associated with binge drinking prevalence and positively associated with all other health-related behaviors and outcomes.Conclusions: Structural determinants of health such as the built environment can influence population health. Our study suggests that higher levels of urban development have mixed effects on health and adds further evidence that socioeconomic distress has adverse impacts on multiple physical and mental health outcomes. [ABSTRACT FROM AUTHOR]

The activation of heterodimeric (α/β) integrin transmembrane receptors by cytosolic protein talin is crucial for regulating diverse cell-adhesion-dependent processes, including blood coagulation, tissue remodeling, and cancer metastasis. This process is triggered by the coincident binding of N-terminal FERM (four-point-one-protein/ezrin/radixin/moesin) domain of talin (talin-FERM) to the inner membrane surface and integrin β cytoplasmic tail, but how these binding events are spatiotemporally regulated remains obscure. Here we report the crystal structure of a dormant talin, revealing how a C-terminal talin rod segment (talin-RS) self-masks a key integrin-binding site on talin-FERM via a large interface. Unexpectedly, the structure also reveals a distinct negatively charged surface on talin-RS that electrostatically hinders the talin-FERM binding to the membrane. Such a dual inhibitory topology for talin is consistent with the biochemical and functional data, but differs significantly from a previous model. We show that upon enrichment with phosphotidylinositol-4,5-bisphosphate (PIP2) - a known talin activator, membrane strongly attracts a positively charged surface on talin-FERM and simultaneously repels the negatively charged surface on talin-RS. Such an electrostatic 'pull-push' process promotes the relief of the dual inhibition of talin-FERM, which differs from the classic 'steric clash' model for conventional PIP2-induced FERM domain activation. These data therefore unravel a new type of membrane-dependent FERM domain regulation and illustrate how it mediates the talin on/off switches to regulate integrin transmembrane signaling and cell adhesion. [ABSTRACT FROM AUTHOR]

In solid-state fermentation, among various solid supports evaluated, banana peel was found to be an ideal support and resulted into higher levels of laccase (6281.4 ± 63.60 U l) along with notable levels of manganese peroxidase production (1339.0 ± 131.23 U l) by Aspergillus fumigatus VkJ2.4.5. Maximum levels of laccase was achieved under derived conditions consisting of 80% of moisture level, 6 days of incubation period, 6% inoculum level, and an aeration level of 2.5 l min. A column-tray bioreactor was designed to scale up and economize the enzyme production in three successive cycles of fermentation using the same fungal biomass. Thermal and pH stability profiles revealed that enzyme was stable up to 50°C and at varying pH range from 5-9 for up to 2 h. The apparent molecular weight of laccase was found to be 34 ± 1 kDa. MALDI-TOF/TOF analysis of the protein showed significant homology with maximum identity of 67% to other laccases reported in database. [ABSTRACT FROM AUTHOR]

Obesity is a global epidemic affecting millions. Implementation of interventions to curb obesity rates requires timely surveillance. In this study, we estimated sex-specific obesity prevalence using social media, search queries, demographics and built environment variables. We collected 3,817,125 and 1,382,284 geolocated tweets on food and exercise respectively, from Twitter's streaming API from April 2015 to March 2016. We also obtained searches related to physical activity and diet from Google Search Trends for the same time period. Next, we inferred the gender of Twitter users using machine learning methods and applied mixed-effects state-level linear regression models to estimate obesity prevalence. We observed differences in discussions of physical activity and foods, with males reporting higher intensity physical activities and lower caloric foods across 40 and 48 states, respectively. In addition, counties with the highest percentage of exercise and food tweets had lower male and female obesity prevalence. Lastly, our models separately captured overall male and female spatial trends in obesity prevalence. The average correlation between actual and estimated obesity prevalence was 0.797(95% CI, 0.796, 0.798) and 0.830 (95% CI, 0.830, 0.831) for males and females, respectively. Social media can provide timely community-level data on health information seeking and changes in behaviors, sentiments and norms. Social media data can also be combined with other data types such as, demographics, built environment variables, diet and physical activity indicators from other digital sources (e.g., mobile applications and wearables) to monitor health behaviors at different geographic scales, and to supplement delayed estimates from traditional surveillance systems. [ABSTRACT FROM AUTHOR]