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Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.

Background and aimsRecently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies.Design and settingCross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years).CasesCases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected.MeasurementsGraph theory metrics of segregation and integration were used to summarize SCN.FindingsMirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar.ConclusionStructural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

Abstract High-aspect-ratio mechanical resonators are pivotal in precision sensing, from macroscopic gravitational wave detectors to nanoscale acoustics. However, fabrication challenges and high computational costs have limited the length-to-thickness ratio of these devices, leaving a largely unexplored regime in nano-engineering. We present nanomechanical resonators that extend centimeters in length yet retain nanometer thickness. We explore this expanded design space using an optimization approach which judiciously employs fast millimeter-scale simulations to steer the more computationally intensive centimeter-scale design optimization. By employing delicate nanofabrication techniques, our approach ensures high-yield realization, experimentally confirming room-temperature quality factors close to theoretical predictions. The synergy between nanofabrication, design optimization guided by machine learning, and precision engineering opens a solid-state path to room-temperature quality factors approaching 10 billion at kilohertz mechanical frequencies – comparable to the performance of leading cryogenic resonators and levitated nanospheres, even under significantly less stringent temperature and vacuum conditions.

Several GWAS reported Myocyte Enhancer Factor 2 C (MEF2C) gene associations with white matter microstructure and psychiatric disorders, and MEF2C involvement in pathways related to neuronal development suggests a common biological factor underlying these phenotypes. We aim to refine the MEF2C effects in the brain relying on an integrated analysis of white matter and psychiatric phenotypes in an extensively characterized sample. This study included 870 Brazilian adults (47% from an attention-deficit/hyperactivity disorder outpatient clinic) assessed through standardized psychiatric interviews, 139 of which underwent a magnetic resonance imaging scan. We evaluated variants in the MEF2C region using two approaches: 1) a gene-wide analysis, which uses the sum of polymorphism effects, and 2) SNP analyses, restricted to the independent variants within the gene. The outcomes included psychiatric phenotypes and fractional anisotropy for brain images. Results: The gene-wide analyses pointed to a nominal association between MEF2C and the Temporal Portion of the Superior Longitudinal Fasciculus (SLFTEMP). The SNP analysis identified four independent variants significantly associated with SLFTEMP and one (rs4218438) with Substance Use Disorder. Our findings showing specific associations of MEF2C variants with temporal-frontal circuitry components may help to elucidate how the MEF2C gene underlies a broad range of psychiatric phenotypes since these regions are relevant to executive and cognitive functions.

Nowadays, the high penetration of inverter-interfaced distributed energy resources (DERs) has raised a well-founded concern regarding the interaction of these devices with the upstream grid. The harmonic interaction phenomenon between these players can be described by time-domain simulations, using high computational effort switched and/or average models often impractical for large power systems. This paper proposes an innovative low-computational-burden model named passive impedance network (PIN), capable of accurately representing DERs in electric power systems (EPSs). Through passive RLC components, the PIN model can describe DER dynamic behavior at a certain frequency of interest, making it able to represent harmonic flow within the EPS nodes. The proposed model is compared with the switched model, average model, and an experimental setup under different grid distortions and injected current profiles. A comparison of the total demand distortion (TDD) between the proposed PIN model and the experimental results is carried out. The effect of DER parameter deviations on PIN model accuracy is addressed, in which the absolute error of the PIN model TDD values are 0.65% and 0.06% for the experimental and switched model, respectively. Besides, the PIN model presents an improved computational performance compared to the time-domain-based switching model, requiring 99% less computational burden.

Land degradation and biodiversity decline are two of the main threats currently faced by humankind. For this reason, ecosystem restoration has become a priority in recent decades. Restoration actions in riparian forests may offer particularly high benefit/effort ratios since riparian zones provide multiple ecosystem services beyond the areas they occupy. As riparian restoration becomes increasingly widespread, it becomes ever more necessary to identify reliable indicators that can efficiently aid in evaluating restoration outcomes. In this study, we review various riparian restoration projects across different contexts. Our specific objectives were to i) review the monitoring methodologies used, ii) identify the most frequently used vegetation indicators applied, and iii) assess the use of such indicators and related sampling methods at different temporal and spatial scales. We systematically reviewed 103 studies published from 1990 to 2022 that monitored riparian vegetation restoration. We found that most of the reviewed studies evaluated restoration outcomes using field sampling (72%). In studies that used remote sensing (RS) data, medium-resolution satellite imagery and aerial RGB imagery were the most frequently used. River reach was the most frequent monitoring extent (53% of studies), while the number of studies decreased as the monitoring scale increased. Most studies monitored short-term changes using field sampling, while remote sensing data was more frequently applied in long-term monitoring. The analysis of studies that applied remote sensing and field data monitoring highlighted that there is no consensus about the best design to combine both methods. Ground cover, species abundance and richness, and regeneration were the most frequently used indicators. In smaller-scale and shorter-term monitoring studies, vegetation composition indicators (e.g., abundance and richness) were more frequently used, while in larger-scale and longer-term monitoring studies, vegetation structure indicators (e.g., ground cover) were more common. A mismatch exists between restoration goals and the indicators applied, suggesting that the development of monitoring routines that can be applied across different contexts is essential for the evaluation and adaptive management of riparian restoration actions. The potential of remote sensing has not yet been fully exploited in riparian restoration evaluation, and studies that incorporate field and remote sensing data in the multiscale evaluation of restoration practices are urgently required.

Stingless bees (Hymenoptera: Meliponini) are pollinators of both cultivated and wild crop plants in the Neotropical region. However, they are susceptible to pesticide exposure during foraging activities. The fungicide fluazinam is commonly applied in bean and sunflower cultivation during the flowering period, posing a potential risk to the stingless bee Partamona helleri, which serves as a pollinator for these crops. In this study, we investigated the impact of acute oral exposure (24 h) fluazinam on the survival, morphology and cell death signaling pathways in the midgut, oxidative stress and behavior of P. helleri worker bees. Worker bees were exposed for 24 h to fluazinam (field concentrations 0.5, 1.5 and 2.5 mg a.i. mL−1), diluted in 50 % honey aqueous solution. After oral exposure, fluazinam did not harm the survival of worker bees. However, sublethal effects were revealed using the highest concentration of fluazinam (2.5 mg a.i. mL−1), particularly a reduction in food consumption, damage in the midgut epithelium, characterized by degeneration of the brush border, an increase in the number and size of cytoplasm vacuoles, condensation of nuclear chromatin, and an increase in the release of cell fragments into the gut lumen. Bees exposed to fluazinam exhibited an increase in cells undergoing autophagy and apoptosis, indicating cell death in the midgut epithelium. Furthermore, the fungicide induced oxidative stress as evidenced by an increase in total antioxidant and catalase enzyme activities, along with a decrease in glutathione S-transferase activity. And finally, fluazinam altered the walking behavior of bees, which could potentially impede their foraging activities. In conclusion, our findings indicate that fluazinam at field concentrations is not lethal for workers P. helleri. Nevertheless, it has side effects on midgut integrity, oxidative stress and worker bee behavior, pointing to potential risks for this pollinator.

BackgroundChinese immigrants experience significant disparities in tobacco use. Culturally adapted tobacco treatments targeting this population are sparse and the use is low. The low use of these treatment programs is attributed to their exclusive focus on individuals who are ready to quit and the wide range of barriers that Chinese immigrants face to access these programs. To support Chinese immigrant smokers at all levels of readiness to quit and address their access barriers, we developed the WeChat Quit Coach, a culturally and linguistically appropriate WeChat (Tencent Holdings Limited)–based peer group mobile messaging smoking cessation intervention. ObjectiveThis study aims to assess the feasibility, acceptability, and preliminary effects of WeChat Quit Coach. MethodsWe enrolled a total of 60 Chinese immigrant smokers in 2022 in New York City for a pilot randomized controlled trial (RCT) and a single-arm pilot test. The first 40 participants were randomized to either the intervention arm (WeChat Quit Coach) or the control arm (self-help print material) using 1:1 block randomization stratified by sex. WeChat Quit Coach lasted 6 weeks, featuring small peer groups moderated by a coach, daily text messages with text questions, and chat-based instant messaging support from the coach in response to peer questions. The next 20 participants were enrolled in the single-arm pilot test to further assess intervention feasibility and acceptability. All 60 participants were offered a 4-week supply of complimentary nicotine replacement therapy. Surveys were administered at baseline and 6 weeks, with participants in the pilot RCT completing an additional survey at 6 months and biochemical verification of abstinence at both follow-ups. ResultsOf 74 individuals screened, 68 (92%) were eligible and 60 (88%) were enrolled. The majority of participants, with a mean age of 42.5 (SD 13.8) years, were male (49/60, 82%) and not ready to quit, with 70% (42/60) in the precontemplation or contemplation stage at the time of enrollment. The pilot RCT had follow-up rates of 98% (39/40) at 6 weeks and 93% (37/40) at 6 months, while the single-arm test achieved 100% follow-up at 6 weeks. On average, participants responded to daily text questions for 25.1 days over the 42-day intervention period and 23% (9/40) used the chat-based instant messaging support. Most participants were satisfied with WeChat Quit Coach (36/39, 92%) and would recommend it to others (32/39, 82%). At 6 months, self-reported 7-day point prevalence abstinence rates were 25% (5/20) in the intervention arm and 15% (3/20) in the control arm, with biochemically verified abstinence rates of 25% (5/20) and 5% (1/20), respectively. ConclusionsWeChat Quit Coach was feasible and well-received by Chinese immigrants who smoke and produced promising effects on abstinence. Large trials are warranted to assess its efficacy in promoting abstinence in this underserved population. Trial RegistrationClinicalTrials.gov NCT05130788; https://clinicaltrials.gov/study/NCT05130788

INTRODUCTION: There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance. METHODS: We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method. RESULTS: The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohens d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = -0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. DISCUSSION: Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.

The appropriate use of forest biomass can support the transition to a society with clean and renewable energy. In this context, the research aimed to evaluate the waste biomass from Tectona grandis L.f. for energy purposes. Seven teak wood waste types were used, accessible from the harvesting stage to wood processing. Physical attributes (moisture and basic density) and proximate analysis (volatile materials, ashes, and fixed carbon content) were evaluated, which were used to estimate the energy attributes (higher, lower, and net heating value and energy density). It was found that most waste components had moisture content averages below 30% and did not differentiate statistically. For the basic density, values varied between 366 and 519 kg.m-3. Proximate analysis and energetic attributes of the teak wastes support its feasibility for bioenergy use, focused on trimmings and thin logs. It was concluded that teak waste has the potential for energy purposes if its specific characteristics are considered and appropriate ways of use and conversion are chosen.

The grid-forming converter that supplies voltage magnitude and frequency is a key element for isolated remote communities, and then wear-out analysis is an essential figure of merit. Therefore, this paper proposes the two-phase three-wire (2$\Phi$3 W) grid forming converter applied in a case study of isolated riverside communities in the Brazilian Amazon region. The proposed xyn-converter displaces the voltage line angle in 180$^{\circ }$, differing from $\alpha \beta$n-converter and abn-converter that displace voltage line angle in 90$^{\circ }$ and 120$^{\circ }$ respectively. First, the authors have also proposed a semiconductor current stress evaluation for 2$\Phi$3 W converters comparing the RMS current. Then, the lifetime evaluation of the three evaluated grid-forming converters is conducted. The results show that the converter operating in the xyn-converter presents the highest reliability among the three converters. Finally, the thermal stress analysis is validated by means of a 2$\Phi$3 W converter prototype with an open semiconductor module. For the evaluated converters, the xyn-converter has the least thermal stress for balanced and unbalanced load conditions and therefore the longest lifespan. The experimental validation shows that the average temperature of the xyn-converter is 19.4% and 23.3% lower than both the abn-converter and the $\alpha \beta$n-converter under balanced load conditions.

Objective:. This study, examining literature up to December 2023, aims to comprehensively assess surgical care for incarcerated individuals, identifying crucial knowledge gaps for informing future health services research and interventions. Background:. The US prison system detains around 2 million individuals, mainly young, indigent males from ethnic and racial minorities. The constitutional right to healthcare does not protect this population from unique health challenges and disparities. The scarcity of literature on surgical care necessitates a systematic review to stimulate research, improve care quality, and address health issues within this marginalized community. Methods:. A systematic review, pre-registered with the International Prospective Register of Systematic Reviews (CRD42023454782), involved searches in PubMed, Embase, and Web of Science. Original research on surgical care for incarcerated individuals was included, excluding case reports/series (

Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.

A temática educação especial apresenta relevância crescente pelos desafios e dilemas que coloca em termos das práticas educativas cotidianas. Objetivou-se analisar o papel da família e das instituições no processo educativo especial. Foi feita revisão sistemática seguindo as diretrizes PRISMA, buscando por artigos originais publicados entre 2011 e 2021 nas bases de dados Science Direct e Web of Sciense com os descritores “Education, Special AND Family”; “Education, Special AND Mainstreaming”. Nos 18 artigos selecionados verificou-se que as instituições de ensino têm o papel de disponibilizar professores especializados/capacitados, acompanhamento e avaliação dos alunos, manejo pedagógico da diversidade, estrutura física e equipamentos/tecnologia; além de amparo à família. Já as famílias necessitam aceitar o diagnóstico, buscar amparo psicológico, social e econômico dos órgãos competentes, além de auxiliar nas atividades da escola. Apesar de existir a possibilidade de educação inclusiva, as instituições exclusivas de educação especial continuarão sendo um importante alicerce aos educandos que demandam apoios múltiplos e contínuos. Conclui-se que é muito importante fortalecer os laços sociais, ou seja, construir um suporte mútuo entre família e escola, com políticas públicas que forneçam subsídio às instituições e às famílias, garantindo assim educação de qualidade ao aluno especial, seja no ensino exclusivo ou inclusivo.

Abstract This study validated the content of an instrument designed to assess the knowledge, involvement (attitudes) and management (practice) of dentists relative to sickle-cell disease (KAPD-SCD). The instrument consisted of five domains composed of a total of thirteen items: I. Dentist’s self-assessment relative to sickle-cell disease; II. Dentist’s knowledge of the repercussions of sickle-cell disease on the stomatognathic system; III. Dentist’s knowledge of the complications of sickle-cell disease in the stomatognathic system; IV. Dentist’s knowledge concerning the dental management of sickle-cell disease patients; and V. Dentist’s involvement in an approach to sickle-cell disease. Twelve experts assigned scores to each item of the instrument. The criteria were clarity, understanding and appropriateness, leaving open fields for comments. Descriptive and content analyses of the data were made. Each expert analyzed 39 assessment units. The percentages considered for agreement were high (>80%), medium (70%-80%), or low (

Objective: To evaluate the prevalence of dental caries in children from 18 months to 5 years of age in eastern (near urban centers) and western (far from urban centers) Parakanã, verify the influence of proximity to non-indigenous cultures, and compare with other ethnicities and non-indigenous. Material and Methods: The universe of children was examined by one researcher in a cross-sectional study. Descriptive analysis and the Mann-Whitney test (p

BackgroundMorphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life.MethodsInterregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed.ResultsAcross the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth.ConclusionsOur findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

El objetivo de esta investigación fue analizar el impacto de la participación en la toma de decisiones en la satisfacción laboral de profesoras universitarias de tiempo completo de Ensenada, Baja California, México. Adicionalmente, la investigación distingue por ser cuantitativa, no experimental y por tener un diseño exploratorio con una dimensión temporal transversal. De esta manera, se aplicaron 90 encuestas a profesoras universitarias de tiempo completo en Ensenada, Baja California, México. De ahí, los datos recabados se analizaron por medio de una modelización de ecuaciones estructurales basada en la técnica de mínimos cuadrados parciales. Los hallazgos indican empíricamente que la participación en la toma de decisiones impacta de manera positiva y estadísticamente significativa a la satisfacción laboral.

IntroductionRates of lung cancer screening among Latinos remain low. The purpose of the study was to understand the perceived benefits, barriers, and cues to action for lung cancer screening among Latinos.MethodsParticipants (N=20) were recruited using community-based recruitment strategies. Eligibility criteria included: 1) self-identified as Hispanic/Latino, 2) spoke English and/or Spanish, and 3) met the USA Preventive Services Task Force eligibility criteria for lung cancer screening. Interviews were conducted in Spanish and English, audio recorded, and transcribed verbatim. Using the health belief model, a qualitative theoretical analysis was used to analyze the interviews.ResultsParticipants’ mean age was 58.3 years old (SD=5.8), half of the participants were female, 55% had completed high school or lower educational level, and 55% reported speaking more Spanish than English. All participants were currently smoking. Fourteen participants (70%) were unaware of lung cancer screening, and eighteen (90%) did not know they were eligible for lung cancer screening. Regarding lung cancer screening, participants reported multiple perceived benefits (e.g., smoking cessation, early detection of lung cancer, increased survivorship) and barriers (e.g., fear of outcomes, cost, lung cancer screening not being recommended by their clinician). Lastly, multiple cues to actions for lung cancer screening were identified (e.g., family as a cue to action for getting screened).ConclusionsMost Latinos who were eligible for lung cancer screening were unaware of it and, when informed, they reported multiple perceived benefits, barriers, and cues to action. These factors provide concrete operational strategies to address lung cancer screening among Latinos.