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Abstract Bottlenecks inherent in batch and column adsorption configurations have impeded the implementation of the adsorption technique in large-scale wastewater treatment systems. This study mainly aimed to develop an innovative wastewater treatment prototype that integrates inclined plate settlers (IPS) and composite adsorbent coating (CAC). The objective is to enable the removal of Cd2+ from aqueous solutions in a continuous setup, thereby enhancing its practicality for large-scale applications. The combined IPS-CAC system was optimized at various angle of inclination (θ), influent flow rate (Q) and adsorbate initial concentration (C o) using the Box–Behnken Design (BBD) of the Response Surface Methodology (RSM). At optimized operating parameters (θ = 45°, Q = 5 ml/min and C i = 1.87 mg/L) the IPS-CAC Cd2+ predicted (R 2 = 0.9926) and experimental removal efficiencies were 75.8% and 69.7 ± 4.67%, respectively. The IPS-CAC breakthrough adsorption capacity was 9.6 mg/g. Comparing IPS-CAC performance with a tank without plates and IPS with plain plates, the Cd2+ removal efficiencies were 2.4 ± 0.1% and 4.6 ± 1.1%, respectively, confirming the synergistic effect of IPS and CAC. Additionally, breakthrough curves were acquired for various flow rates, cadmium influent concentrations, and plate inclination angles. Only a 10% decline in the removal effectiveness (from 69.7 to 59.7%) of the CAC after three adsorption–regeneration cycles was observed, indicating its stability for heavy metal removal. The results underpin the potential of using IPS-CAC for industrial wastewater treatment and enhancing the use of adsorption on a larger scale.

BackgroundDiscrimination is a recognized psychosocial stressor that has been linked to various negative health outcomes. This study explored the impact of discrimination on gut health, specifically focusing on microbiome changes, predicted metagenomic differences, transcriptomic profiles, and the potential for using a multi-omic approach to predict discrimination to identify discrimination status for an individual. Methods: We conducted a comprehensive investigation involving male and premenopausal female participants, using the Everyday Discrimination Scale to classify them into either high or low discrimination. Multiple questionnaires were administered to evaluate participants’ physiological, psychological, and perceived stressors. Two diet questionnaires were also administered. Stool samples were collected for microbiome analysis and RNA sequencing. Microbial composition changes were analyzed using the Shannon index and Chao1 richness estimator for alpha diversity and the Aitchison distance metric for beta diversity. Differential abundance was evaluated using MaAsLin2, followed by metatranscriptomics sequencing and annotation. A multi-omic approach utilizing random forest was used to assess the predictability of discrimination.ResultsThe study results showed that high discrimination was linked to higher gut microbiome species richness (Chao1, p = 0.02) and significant beta diversity differences (p = 0.04). Prevotella and Ruminococcaceae were both less abundant in the high discrimination group. High discrimination participants also reported higher levels of depression, anxiety, perceived stress, early life adversity, visceral sensitivity, and neuroticism than those in the low discrimination group. Gene expression analysis revealed distinctive patterns, with significant changes in genes associated with environmental sensing (two-component system) and metabolic pathways. In a plot comparing gene transcription to DNA content, certain genes showed higher expression levels in participants who experienced both high and low levels of discrimination. Our random forest classifier demonstrated the capability to accurately differentiate individuals with high and low discrimination in our training cohort (AUC = 0.91).ConclusionThese findings illuminate the substantial impact of discrimination on gut health, encompassing microbiome composition, gene expression, and functional pathways. These findings suggest that discrimination is associated with internal biological changes that can be associated with negative health outcomes, opening research to examine novel pathways that can be used to mitigate the negative health effects of discrimination.

The study focuses on the preparation of activated carbon from Prosopis juliflora (PJAC) wood by pyrolysis and chemical activation. The objective is to assess its effectiveness as an adsorbent for synthesizing a composite adsorbent coating (CAC) for Cadmium (Cd2+) removal from aqueous solution. The effect of preparation factors related to Cd2+ removal efficiency was assessed. The Design of Experiments (DoE) for the adsorption of Cd2+ on the PJAC were done using the Box-Behnken Design (BBD) of the Response Surface Methodology (RSM) (Design Expert software version 11). The influence of impregnation ratio (IR), carbonization time (t), and carbonization temperature (T) on the Cd (II) percent (%) removal was evaluated. The response surface graphs in 3D were also generated for the response variable, and the higher R2 coefficient values were fitted into the polynomial quadric model. The results indicated that all the variable preparation factors were significant in the Cd2+ removal by PJAC with carbonization temperature being the most significant. At the optimum conditions i.e. impregnation ratio (1.8), carbonization temperature (595 °C) and carbonization time (174 min), the model predicted a 99.9 % Cd2+ removal efficiency while the adsorption experiment obtained a 96.7 % removal efficiency, respectively. Later, the morphological and chemical properties of the PJAC prepared with optimal parameters were analyzed using different characterization techniques including SBET, SEM-EDX, pHPZC, FTIR and XRD. The SEM images revealed a rough and porous morphological surface with an SBET of 600.4 m2/g and a near neutral pHPZC of 6.92. The XRD pattern indicated the crystalline nature of the prepared adsorbent. The pre and post adsorption FTIR spectrum of the PJAC demonstrated a distinct difference with the latter showing a reduction in peak intensity and height. These results underpin the potential of utilizing invasive plants like Prosopis Juliflora as adsorbents for heavy metal removal.

Abstract Background Living in a disadvantaged neighborhood is associated with worse health outcomes, including brain health, yet the underlying biological mechanisms are incompletely understood. We investigated the relationship between neighborhood disadvantage and cortical microstructure, assessed as the T1-weighted/T2-weighted ratio (T1w/T2w) on magnetic resonance imaging, and the potential mediating roles of body mass index (BMI) and stress, as well as the relationship between trans-fatty acid intake and cortical microstructure. Methods Participants comprised 92 adults (27 men; 65 women) who underwent neuroimaging and provided residential address information. Neighborhood disadvantage was assessed as the 2020 California State area deprivation index (ADI). The T1w/T2w ratio was calculated at four cortical ribbon levels (deep, lower-middle, upper-middle, and superficial). Perceived stress and BMI were assessed as potential mediating factors. Dietary data was collected in 81 participants. Results Here, we show that worse ADI is positively correlated with BMI (r = 0.27, p = .01) and perceived stress (r = 0.22, p = .04); decreased T1w/T2w ratio in middle/deep cortex in supramarginal, temporal, and primary motor regions (p

BackgroundOn March 16, 2021, a white man shot and killed eight victims, six of whom were Asian women at Atlanta-area spa and massage parlors. The aims of the study were to: (1) qualitatively summarize themes of tweets related to race, ethnicity, and racism immediately following the Atlanta spa shootings, and (2) examine temporal trends in expressions hate speech and solidarity before and after the Atlanta spa shootings using a new methodology for hate speech analysis.MethodsA random 1% sample of publicly available tweets was collected from January to April 2021. The analytic sample included 708,933 tweets using race-related keywords. This sample was analyzed for hate speech using a newly developed method for combining faceted item response theory with deep learning to measure a continuum of hate speech, from solidarity race-related speech to use of violent, racist language. A qualitative content analysis was conducted on random samples of 1,000 tweets referencing Asians before the Atlanta spa shootings from January to March 15, 2021 and 2,000 tweets referencing Asians after the shooting from March 17 to 28 to capture the immediate reactions and discussions following the shootings.ResultsQualitative themes that emerged included solidarity (4% before the shootings vs. 17% after), condemnation of the shootings (9% after), racism (10% before vs. 18% after), role of racist language during the pandemic (2 vs. 6%), intersectional vulnerabilities (4 vs. 6%), relationship between Asian and Black struggles against racism (5 vs. 7%), and discussions not related (74 vs. 37%). The quantitative hate speech model showed a decrease in the proportion of tweets referencing Asians that expressed racism (from 1.4% 7 days prior to the event from to 1.0% in the 3 days after). The percent of tweets referencing Asians that expressed solidarity speech increased by 20% (from 22.7 to 27.2% during the same time period) (p < 0.001) and returned to its earlier rate within about 2 weeks.DiscussionOur analysis highlights some complexities of discrimination and the importance of nuanced evaluation of online speech. Findings suggest the importance of tracking hate and solidarity speech. By understanding the conversations emerging from social media, we may learn about possible ways to produce solidarity promoting messages and dampen hate messages.

OBJECTIVES During the coronavirus disease 2019 (COVID-19) pandemic, a growing prevalence of racial and ethnic discrimination occurred when many Americans struggled to maintain healthy lifestyles. This study investigated the associations of racial and ethnic discrimination with changes in exercise and screen time during the pandemic in the United States. METHODS We included 2,613 adults who self-identified as non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, or Hispanic from the Health, Ethnicity, and Pandemic study, a cross-sectional survey conducted among a nationally representative sample of United States adults between October and November 2020. We assessed self-reported racial and ethnic discrimination by measuring COVID-19-related racial and ethnic bias and examined its associations with changes in exercise and screen time using multivariable logistic regression models. We analyzed data between September 2021 and March 2022. RESULTS COVID-19-related racial and ethnic bias was associated with decreased exercise time among non-Hispanic Asian (odds ratio [OR], 1.46; 95% confidence interval [CI], 1.13 to 1.89) and Hispanic people (OR, 1.91; 95% CI, 1.32 to 2.77), and with increased screen time among non-Hispanic Black people (OR, 1.94; 95% CI, 1.33 to 2.85), adjusting for age, sex, education, marital status, annual household income, insurance, and employment status. CONCLUSIONS Racial and ethnic discrimination may have adversely influenced exercise and screen time changes among racial and ethnic minorities during the COVID-19 pandemic in the United States. Further studies are needed to investigate the mechanisms through which racial and ethnic discrimination can impact lifestyles and to develop potential strategies to address racial and ethnic discrimination as a barrier to healthy lifestyles.

Migrants have been theorized to be healthier than their non-migrant counterparts; however, there is limited examination of health selection using binational data and how selection occurs, particularly for mental health outcomes. This study examines the role of visa status and financial strain as critical factors for mental health selection among Filipino migrants to the U.S. and non-migrants who remain in the Philippines. We used the baseline data from the Health of Philippine Emigrants Study (HoPES; n = 1631) to compare depressive symptoms between non-migrants and migrants who were both surveyed prior to their departure to the U.S. We assessed depressive symptoms using linear regression by migration status, financial strain, and by visa categories including fiancée/marriage, unlimited family reunification, limited family reunification, and employment. Overall, all migrants reported lower depressive symptoms than non-migrants; however, depressive symptoms varied by visa type. Fiancée/marriage migrants had lower depressive symptoms than compared to limited family reunification migrants. Additionally, those who reported financial strain had higher depressive symptoms than those without any financial strain. We find that migrants were positively selected for mental health using a unique sample of Filipino migrants before they left for the U.S.

Integrin α11β1 is a collagen-binding integrin that is needed to induce and maintain the myofibroblast phenotype in fibrotic tissues and during wound healing. The expression of the α11 is upregulated in cancer-associated fibroblasts (CAFs) in various human neoplasms. We investigated α11 expression in human cutaneous squamous cell carcinoma (cSCC) and in benign and premalignant human skin lesions and monitored its effects on cSCC development by subjecting α11-knockout (Itga11−/−) mice to the DMBA/TPA skin carcinogenesis protocol. α11-deficient mice showed significantly decreased tumor cell proliferation, leading to delayed tumor development and reduced tumor burden. Integrin α11 expression was significantly upregulated in the desmoplastic tumor stroma of human and mouse cSCCs, and the highest α11 expression was detected in high-grade tumors. Our results point to a reduced ability of α11-deficient stromal cells to differentiate into matrix-producing and tumor-promoting CAFs and suggest that this is one causative mechanism underlying the observed decreased tumor growth. An unexpected finding in our study was that, despite reduced CAF activation, the α11-deficient skin tumors were characterized by the presence of thick and regularly aligned collagen bundles. This finding was attributed to a higher expression of TGFβ1 and collagen crosslinking lysyl oxidases in the Itga11-/- tumor stroma. In summary, our data suggest that α11β1 operates in a complex interactive tumor environment to regulate ECM synthesis and collagen organization and thus foster cSCC growth. Further studies with advanced experimental models are still needed to define the exact roles and molecular mechanisms of stromal α11β1 in skin tumorigenesis.

ABSTRACT: Detecting and classifying animal species is the first step in determining their long-term viability and the influence we may be having on them. Second, it aids people in recognizing predators and non-predatory animals, both of which pose a significant threat to humans and the environment. Third, it lowers the rate of traffic accidents in various regions since it has been a regular sighting on roadways, resulting in several collisions with automobiles. However, animal species' detection and Classification of animal species face many challenges such as the size and inconsistent behaviors various among the species. This paper proposes using a novel two-stage network with a modified multi-scale attention mechanism to create a more integrated recognition and classification system to attend to the challenges. At the regional proposal stage, a deeply characterized pyramid design with lateral connections was adopted, making the semantic characteristic of a small item more sensitive. Secondly, by reason of a densely connected convolutional network, the functional transmission is enhanced and multiplexed throughout the classification stage, resulting in a more precise Classification with fewer parameters. The Proposed model was evaluated using the AP and mAP evaluation metrics on the Animal wildlife and the challenging Animal-80 dataset. An mAP of +0.1% and an AP of 5% to 20% increase in each class was achieved by the attention-based proposed model compared to the non-attention-based model. Further comparison with other related works shows the proposed techniques' effectiveness for detecting and classifying animal species.

With the continual development of artificial intelligence and smart computing in recent years, quantitative approaches have become increasingly popular as an efficient modeling tool as they do not necessitate complicated mathematical models. Many nations have taken steps, such as transitioning to online schooling, to decrease the harm caused by coronaviruses. Inspired by the demand for technology in early education, the present research uses a radial basis function (RBF) neural network (NN) modeling technique to predict preschool instructors’ technology usage in classes based on recognized determinant characteristics of technology acceptance. In this regard, this study utilized the RBFNN approach to predict preschool teachers’ technology acceptance behavior, based on the theory of planned behavior, which states that behavioral achievement, in our case the actual technology use in class, depends on motivation, intention and ability, and behavioral control. Thus, this research design is based on an adapted version of the technology acceptance model (TAM) with eight dimensions: D1. Perceived usefulness, D2. Perceived ease of use, D3. Perceived enjoyment, D4. Intention to use, D5. Actual use, D6. Compatibility, D7. Attitude, and D8. Self-efficacy. According to the TAM, actual usage is significantly predicted by the other seven dimensions used in this research. Instead of using the classical multiple linear regression statistical processing of data, we opted for a NN based on the RBF approach to predict the actual usage behavior. This study included 182 preschool teachers who were randomly chosen from a project-based national preschool teacher training program and who responded to our online questionnaire. After designing the RBF function with the actual usage as an output variable and the other seven dimensions as input variables, in the model summary, we obtained in the training sample a sum of squares error of 37.5 and a percent of incorrect predictions of 43.3%. In the testing sample, we obtained a sum of squares error of 14.88 and a percent of incorrect predictions of 37%. Thus, we can conclude that 63% of the classified data are correctly assigned to the models’ dependent variable, i.e., actual technology use, which is a significant rate of correct predictions in the testing sample. This high significant percentage of correct classification represents an important result, mainly because this is the first study to apply RBFNN’s prediction on psychological data, opening up a new interdisciplinary field of research.

Abstract Background It is well established that racism is a fundamental contributor to poor health and inequities. There is consistent evidence of high exposure to discrimination among Aboriginal and Torres Strait Islander (Indigenous Australian) peoples, but impacts have not been fully quantified, in part due to limited measurement tools. We aim to validate instruments developed to measure interpersonal discrimination. Methods Instruments were discussed at five focus groups and with experts, and field tested in developing Mayi Kuwayu: The National Study of Aboriginal and Torres Strait Islander Wellbeing. Data from 7501 baseline survey participants were analysed. Acceptability was assessed according to extent of missingness, construct validity using exploratory and confirmatory factor analysis, and reliability using Cronbach’s alpha. Associations between each instrument and outcomes conceptually understood to be closely (community-level racism) or less closely (family wellbeing) related were quantified to test convergent and discriminant validity. Results An 8-item instrument captures experiences of discrimination in everyday life and a 4-item instrument experiences in healthcare, each followed by a global attribution item. Item missingness was 2.2–3.7%. Half (55.4%) of participants reported experiencing any everyday discrimination, with 65.7% attributing the discrimination to Indigeneity; healthcare discrimination figures were 34.1% and 51.1%. Items were consistent with two distinct instruments, differentiating respondents with varying experiences of discrimination. Scales demonstrated very good reliability and convergent and divergent validity. Conclusion These brief instruments demonstrate face validity and robust psychometric properties in measuring Aboriginal and Torres Strait Islander adults’ experiences of interpersonal discrimination in everyday life and in healthcare. They can be used to quantify population-level experiences of discrimination, and associated wellbeing consequences, and monitor change.

Studies of migration and health focus on a "healthy migrant effect" whereby migrants are healthier than individuals not migrating. Health selection remains the popular explanation of this phenomenon. However, studies are mixed on whether selection occurs and typically examine migrants post-departure. This study used a novel pre-migration dataset to identify which health and social domains differ between migrants and their non-migrant counterparts and their contribution to explaining variance in self-rated health by migrant status at pre-migration and 1-year later. Data were used from the baseline and 1-year follow-up of the Health of Philippine Emigrants Study (HoPES). We used multivariable ordinary least squares regression to examine differences in self-rated health between migrants to the U.S. and a comparable group of non-migrants at baseline (premigration) and one year later, accounting for seven domains: physical health, mental health, health behavior, demographics, socioeconomic factors and healthcare utilization, psychosocial factors, and social desirability. A migrant advantage was present for self-rated health at baseline and 1-year. Accounting for all domains, migrants reported better self-rated health compared to non-migrants both at baseline (β = 0.32; 95% CI = 0.22, 0.43) and at 1-year (β = 0.28; 95% CI = 0.10, 0.46). Migrant status, health behavior, and mental health accounted for most of the variance in self-rated health both at baseline and 1-year follow-up. This analysis provides evidence of migrant health selection and nuanced understanding to what is being captured by self-rated health in studies of migrant health that should be considered in future research.

This study examined whether killings of George Floyd, Ahmaud Arbery, and Breonna Taylor by current or former law enforcement officers in 2020 were followed by shifts in public sentiment toward Black people. Methods: Google searches for the names “Ahmaud Arbery,” “Breonna Taylor,” and “George Floyd” were obtained from the Google Health Application Programming Interface (API). Using the Twitter API, we collected a 1% random sample of publicly available U.S. race-related tweets from November 2019–September 2020 (N = 3,380,616). Sentiment analysis was performed using Support Vector Machines, a supervised machine learning model. A qualitative content analysis was conducted on a random sample of 3,000 tweets to understand themes in discussions of race and racism and inform interpretation of the quantitative trends. Results: The highest rate of Google searches for any of the three names was for George Floyd during the week of May 31 to June 6, the week after his murder. The percent of tweets referencing Black people that were negative decreased by 32% (from 49.33% in November 4–9 to 33.66% in June 1–7) (p

Abstract Background Previously sharpin has been identified as an endogenous inhibitor of β1-integrin activation by directly binding to a conserved region in the cytoplasmic tails (CTs) of the integrin β1-associated α subunits. Methods Here we employed biochemical approaches and cellular analyses to evaluate the function and molecular mechanism of the sharpin-kindlin-1 complex in regulating β1-integrin activation. Results In this study, we found that although the inhibition of sharpin on β1-integrin activation could be confirmed, sharpin had no apparent effect on integrin αIIbβ3 activation in CHO cell system. Notably, a direct interaction between sharpin and the integrin β1 CT was detected, while the interaction of sharpin with the integrin αIIb and the β3 CTs were substantially weaker. Importantly, sharpin was able to inhibit the talin head domain binding to the integrin β1 CT, which can mechanistically contribute to inhibiting β1-integrin activation. Interestingly, we also found that sharpin interacted with kindlin-1, and the interaction between sharpin and the integrin β1 CT was significantly enhanced when kindlin-1 was present. Consistently, we observed that instead of acting as an activator, kindlin-1 actually suppressed the talin head domain mediated β1-integrin activation, indicating that kindlin-1 may facilitate recruitment of sharpin to the integrin β1 CT. Conclusion Taken together, our findings suggest that sharpin may complex with both kindlin-1 and the integrin β1 CT to restrict the talin head domain binding, thus inhibiting β1-integrin activation.

We hereby propose the use of stable, biocompatible, and uniformly sized polymeric micelles as high-radiotracer-payload carriers at region-of-interest with negligible background activity due to no or low offsite radiolysis. We modified glycol chitosan (GC) polymer with varying levels of palmitoylation (P) and quaternization (Q). Quaternary ammonium palmitoyl glycol chitosan (GCPQ) with a Q:P ratio of 9:35 (Q9P35GC) offers >99% biocompatibility at 10 mg mL−1. Q9P35GC micelles exhibit >99% 99mTechnetium (99mTc) radiolabeling via the stannous chloride reduction method without heat. The 99mTc-Q9P35GC micelles (65 ± 3 nm) exhibit >98% 6 h serum stability at 37 °C and 7 day of radiochemical stability at 25 °C. HepG2 cells show a higher uptake of FITC-Q9P35GC than Q13P15GC and Q20P15GC. The in vivo 24 h organ cumulated activity (MBq h) order follows: liver (234.4) > kidneys (60.95) > GIT (0.73) > spleen (88.84). The liver to organ ratio remains higher than 2.4, rendering a better contrast in the liver. The radiotracer uptake decreases significantly in fibrotic vs. normal liver, whereas a blocking study with excess Q9P35GC significantly decreases the radiotracer uptake in a healthy vs. fibrotic liver. FITC-Q9P35GC shows in vivo hepato-specific uptake. Radiotracer liver uptake profile follows reversible binding kinetics with data fitting to two-tissue compartmental (2T), and graphical Ichise multilinear analysis (MA2) with lower AIC and higher R2 values, respectively. The study concludes that 99mTc-Q9P35GC can be a robust radiotracer for noninvasive hepatocyte function assessment and diagnosis of liver fibrosis. Furthermore, its multifunctional properties enable it to be a promising platform for nanotheranostic applications.

Objectives: Studies of older U.S. adults have consistently found that African Americans perform worse on cognitive measures than whites, but there are inconsistencies as to whether these findings hold over time. Moreover, studies have focused on adults 51 and older, without considering younger ages; thus it is unclear the age at which these disparities surface. The present study examines black-white disparities in mental status trajectories among adults as young as 25 years over a 25-year period. Method: Data come from the Americans’ Changing Lives Study (ACL) (n = 3,617). Participants, ranging from ages 25–100 years old at baseline, were followed from 1986 to 2011 over 5 waves. Mental status was assessed at each wave using a 5-item Short Portable Mental Status Questionnaire. Growth models were used to estimate the associations between age, race, baseline status, and longitudinal changes in mental status, controlling for sociodemographic (e.g., education, income) and other health risk factors (diabetes, stroke, tobacco use, depression). Results: Racial disparities were seen beginning in midlife and this relationship was curvilinear. Specifically, blacks had a steeper rate of mental status decline than whites and these disparities persisted after accounting for social and health risk factors (b = 0.0090, p

ObjectivesTo examine whether intersections of race with other key sociodemographic categories contribute to variations in multiple dimensions of race- and non-race-related, interpersonal-level discrimination and burden in urban-dwelling African Americans and Whites.MethodsData from 2,958 participants aged 30-64 in the population-based Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study were used to estimate up to four-way interactions of race, age, gender, and poverty status with reports of racial and everyday discrimination, discrimination across multiple social statuses, and related lifetime discrimination burden in multiple regression models.ResultsWe observed that: 1) African Americans experienced all forms of discrimination more frequently than Whites, but this finding was qualified by interactions of race with age, gender, and/or poverty status; 2) older African Americans, particularly African American men, and African American men living in poverty reported the greatest lifetime discrimination burden; 3) older African Americans reported greater racial discrimination and greater frequency of multiple social status-based discrimination than younger African Americans; 4) African American men reported greater racial and everyday discrimination and a greater frequency of social status discrimination than African American women; and, 5) White women reported greater frequency of discrimination than White men. All p's < .05.ConclusionsWithin African Americans, older, male individuals with lower SES experienced greater racial, lifetime, and multiple social status-based discrimination, but this pattern was not observed in Whites. Among Whites, women reported greater frequency of discrimination across multiple social statuses and other factors (i.e., gender, income, appearance, and health status) than men. Efforts to reduce discrimination-related health disparities should concurrently assess dimensions of interpersonal-level discrimination across multiple sociodemographic categories, while simultaneously considering the broader socioecological context shaping these factors.

Immigrants to the United States may have an advantage in terms of healthier weight, but tend to gain excessive weight after arrival, and may suffer from obesity and related health conditions. Acculturation theory suggests that this increase in obesity risk is due to adoption of unhealthy western dietary behaviors, and assumes that “eastern/traditional” dietary behaviors prior to migration are healthier. While this assumption is supported by studies conducted several decades ago, the phenomenon of globalization that has risen since the 1990s has increased exposure to western ideas and behaviors in communities worldwide. Hence, today's immigrants are more likely to have already adopted less healthy behaviors that increase obesity risk prior to their arrival in the U.S., a phenomenon we term “pre-acculturation.” The present study investigates the role of pre-acculturation in obesity development among immigrants from the Philippines.Data come from the Health of Philippine Emigrants Study, fielded in 2017 (n = 1632). Pre-acculturation was measured with English proficiency, preparation to migrate, receiving care packages, texting, telephone, or internet contact with friends/family in the U.S. Outcomes included the body mass index (BMI, kg/m2), waist circumference (WC, cm), waist-to-height ratio (WHtR) and waist-to-hip-ratio (WHR). Covariates included age, gender, education, financial strain, physical activity, and diet.Migrants reported greater English proficiency, preparation, and a slightly lower WHtR than non-migrants, but did not differ on BMI, WC, or WHR. Preparation was associated with greater BMI, WC, and WHtR, and the effects of preparation status differed by migration status. Among migrants, more preparation was associated with greater BMI, WC, and WtHR. Further, among non-migrants, texting and telephone communications was related to lower BMI, WC, and WHR.In summary, pre-acculturation may be a risk factor for obesity in the Philippines, suggesting that binary notions of “Western” versus “eastern/traditional” cultures may be too simplistic. Keywords: Immigration, Obesity, International, Theory

Abstract Background Immigrants to the United States are usually healthier than their U.S.-born counterparts, yet the health of immigrants declines with duration of stay in the U.S. This pattern is often seen for numerous health problems such as obesity, and is usually attributed to acculturation (the adoption of “American” behaviors and norms). However, an alternative explanation is secular trends, given that rates of obesity have been rising globally. Few studies of immigrants are designed to distinguish the effects of acculturation versus secular trends, in part because most studies of immigrants are cross-sectional, lack baseline data prior to migration, and do not have a comparison group of non-migrants in the country of origin. This paper describes the Health of Philippine Emigrants Study (HoPES), a study designed to address many of these limitations. Methods HoPES is a dual-cohort, longitudinal, transnational study. The first cohort consisted of Filipinos migrating to the United States (n = 832). The second cohort consisted of non-migrant Filipinos who planned to remain in the Philippines (n = 805). Baseline data were collected from both cohorts in 2017 in the Philippines, with follow-up data collection planned over 3 years in either the U.S. for the migrant cohort or the Philippines for the non-migrant cohort. At baseline, interviewers administered semi-structured questionnaires that assessed demographic characteristics, diet, physical activity, stress, and immigration experiences. Interviewers also measured weight, height, waist and hip circumferences, blood pressure, and collected dried blood spot samples. Discussion Migrants enrolled in the study appear to be representative of recent Filipino migrants to the U.S. Additionally, migrant and non-migrant study participants are comparable on several characteristics that we attempted to balance at baseline, including age, gender, and education. HoPES is a unique study that approximates a natural experiment from which to study the effects of immigration on obesity and other health problems. A number of innovative methodological strategies were pursued to expand the boundaries of current immigrant health research. Key to accomplishing this research was investment in building collaborative relationships with stakeholders across the U.S. and the Philippines with shared interest in the health of migrants.

Even after remediation, mining impacted soils can leave behind a landscape inhospitable to plant growth and containing residual heavy metals. While phytostabilization can be used to restore such sites by limiting heavy metal spread, it is reliant on soil capable of supporting plant growth. Manure-based biochars, coupled with compost, have demonstrated the ability to improve soil growth conditions in mine impacted soils, however there is a paucity of information regarding their influence on resident microbial populations. The objective of this study was to elucidate the impact of these soil amendments on microbial community structure and function in mine impacted soils placed under phytostabilization management with maize. To this aim, a combination of phospholipid fatty acid (PLFA) and enzymatic analyses were performed. Results indicate that microbial biomass is significantly increased upon addition of biochar and compost, with maximal microbial biomass achieved with 5% poultry litter biochar and compost (62.82 nmol g−1 dry soil). Microbial community structure was impacted by biochar type, rate of application, and compost addition, and influenced by pH (r2 = 0.778), EC (r2 = 0.467), and Mg soil concentrations (r2 = 0.453). In three of the four enzymes analyzed, poultry litter biochar treatments were observed with increased activity rates that were often significantly greater than the unamended control. Overall, enzyme activities rates were influenced by biochar type and rate, and addition of compost. These results suggest that using a combination of biochar and compost can be utilized as a management tool to support phytostabilization strategies in mining impacted soils.