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At least 433 records · Page 24

Regional differences in tobacco smoking and lung cancer in Portugal in 2018: a population-based analysis using nationwide incidence and mortality data

Objectives: This study aims to estimate the proportion of lung cancer cases and deaths attributable to tobacco smoking in Portugal in 2018, complemented by trends in incidence and mortality, by sex and region. Design: Cancer cases for 1998–2011 and cancer deaths for 1991–2018 were obtained from population-based registries and Statistics Portugal, respectively. We projected cases for 2018 and used reported deaths for the same year to estimate, using Peto’s method, the number and proportion of lung cancer cases and deaths caused by tobacco smoking in 2018. We calculated the age-adjusted incidence and mortality rates in each year of diagnosis and death. We fitted a joinpoint regression to the observed data to estimate the annual percentage change (APC) in the rates. Setting: Portugal. Results: In 2018, an estimated 3859 cases and 3192 deaths from lung cancer were attributable to tobacco smoking in Portugal, with men presenting a population attributable fraction (PAF) of 82.6% (n=3064) for incidence and 84.1% (n=2749) for mortality, while in women those values were 51.0% (n=795) and 42.7% (n=443), respectively. In both sexes and metrics, the Azores were the region with the highest PAF and the Centre with the lowest. During 1998–2011, the APC for incidence ranged from 0.6% to 3.0% in men and 3.6% to 7.9% in women, depending on region, with mortality presenting a similar pattern between sexes. Conclusion: Exposure to tobacco smoking has accounted for most of the lung cancer cases and deaths estimated in Portugal in 2018. Differential patterns of tobacco consumption across the country, varying implementation of primary prevention programmes and differences in personal cancer awareness may have contributed to the disparities observed. Primary prevention of lung cancer remains a public health priority, particularly among women.

60 APPLIED LIFE SCIENCES↗

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19: a study protocol

The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model's predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states.

59 BASIC BIOLOGICAL SCIENCES↗

DEMOS (Demographic Microsimulator Tool for Longitudinal Synthetic Population) [SWR-25-135] related to NLR SWR-26-076

The Demographic Microsimulator (DEMOS) is an agent-based simulation framework used to model the evolution of population demographic characteristics and lifecycle events, such as education attainment, marital status, and other key transitions. DEMOS modules are designed to capture the interdependencies between short-term and long-term lifecycle events, which are often influential in downstream transportation and land-use modeling. A key feature of DEMOS is its ability to track changes in an agent’s demographic status from year t to year t + 1. This structure allows the model to evolve populations over any user-defined time horizon. As a result, DEMOS is well suited for analyzing medium- and long-term transportation-related decisions, including household vehicle transactions (e.g., purchasing, selling, or replacing vehicles) and work location choices. Core features of DEMOS include the modeling of more than ten lifecycle events, behaviorally realistic patterns informed by long-running panel data, explicit representation of interdependencies among lifecycle processes, and a flexible, modular simulation architecture. A technical memorandum describing DEMOS is available here. The memorandum provides an overview of the framework’s functionality, model structure, input and output data, and its applications in transportation planning and broader policy analysis contexts. Interested readers are also encouraged to consult the paper listed below for additional details on the DEMOS methodology. Sun, Bingrong, Shivam Sharda, Venu M. Garikapati, Mohamed Amine Bouzaghrane, Juan Caicedo, Srinath Ravulaparthy, Isabel Viegas de Lima, Ling Jin, C. Anna Spurlock, and Paul Waddell. "Demographic Microsimulator for Integrated Urban Systems: Adapting Panel Survey of Income Dynamics to Capture the Continuum of Life." Transportation Research Record (2025): 03611981251333339.

Sun, Bingrong [National Laboratory of the Rockies ↗

Enhanced thermoelectric performance of SnSe by controlled vacancy population

Abstract The thermoelectric performance of SnSe strongly depends on its low-energy electron band structure that provides high density of states in a narrow energy window due to the multi-valley valence band maximum (VBM). Angle-resolved photoemission spectroscopy measurements, in conjunction with first-principles calculations, reveal that the binding energy of the VBM of SnSe is tuned by the population of Sn vacancy, which is determined by the cooling rate during the sample growth. The VBM shift follows precisely the behavior of the thermoelectric power factor, while the effective mass is barely modified upon changing the population of Sn vacancies. These findings indicate that the low-energy electron band structure is closely correlated with the high thermoelectric performance of hole-doped SnSe, providing a viable route toward engineering the intrinsic defect-induced thermoelectric performance via the sample growth condition without an additional ex-situ process. Graphical Abstract

77 NANOSCIENCE AND NANOTECHNOLOGY↗

The ancestral environment of teosinte populations shapes their root microbiome

Summary Background The composition of the root microbiome affects the host’s growth, with variation in the host genome associated with microbiome variation. However, it is not known whether this intra-specific variation of root microbiomes is a consequence of plants performing targeted manipulations of them to adapt to their local environment or varying passively with other traits. To explore the relationship between the genome, environment and microbiome, we sampled seeds from teosinte populations across its native range in Mexico. We then grew teosinte accessions alongside two modern maize lines in a common garden experiment. Metabarcoding was performed using universal bacterial and fungal primers to profile their root microbiomes. Results The root microbiome varied between the two modern maize lines and the teosinte accessions. We further found that variation of the teosinte genome, the ancestral environment (temperature/elevation) and root microbiome were all correlated. Multiple microbial groups significantly varied in relative abundance with temperature/elevation, with an increased abundance of bacteria associated with cold tolerance found in teosinte accessions taken from high elevations. Conclusions Our results suggest that variation in the root microbiome is pre-conditioned by the genome for the local environment (i.e. non-random). Ultimately, these claims would be strengthened by confirming that these differences in the root microbiome impact host phenotype, for example, by confirming that the root microbiomes of high-elevation teosinte populations enhance cold tolerance.

Genetics & Heredity↗

Integration of Biorelevant Pediatric Dissolution Methodology into PBPK Modeling to Predict In Vivo Performance and Bioequivalence of Generic Drugs in Pediatric Populations: a Carbamazepine Case Study

This study investigated the impact of gastro-intestinal fluid volume and bile salt (BS) concentration on the dissolution of carbamazepine (CBZ) immediate release (IR) 100 mg tablets and to integrate these in vitro biorelevant dissolution profiles into physiologically based pharmacokinetic modelling (PBPK) in pediatric and adult populations to determine the biopredictive dissolution profile. Dissolution profiles of CBZ IR tablets (100 mg) were generated in 50–900 mL biorelevant adult fasted state simulated gastric and intestinal fluid (Ad-FaSSGF and Ad-FaSSIF), also in three alternative compositions of biorelevant pediatric FaSSGF and FaSSIF medias at 200 mL. This study found that CBZ dissolution was poorly sensitive to changes in the composition of the biorelevant media, where dissimilar dissolution (F2 = 46.2) was only observed when the BS concentration was changed from 3000 to 89 μM (Ad-FaSSIF vs Ped-FaSSIF 50% 14 BS). PBPK modeling demonstrated the most predictive dissolution volume and media composition to forecast the PK was 500 mL of Ad-FaSSGF/Ad-FaSSIF media for adults and 200 mL Ped-FaSSGF/FaSSIF media for pediatrics. A virtual bioequivalence simulation was conducted by using Ad-FaSSGF and/or Ad-FaSSIF 500 mL or Ped-FaSSGF and/or Ped-FaSSIF 200 mL dissolution data for CBZ 100 mg (reference and generic test) IR product. The CBZ PBPK models showed bioequivalence of the product. This study demonstrates that the integration of biorelevant dissolution data can predict the PK profile of a poorly soluble drug in both populations. Further work using more pediatric drug products is needed to verify biorelevant dissolution data to predict the in vivo performance in pediatrics.

60 APPLIED LIFE SCIENCES↗

Survival and Age at Maturity in Head-Started Wood Turtles ( Glyptemys insculpta ) with Implications for Population Recovery

A small relict population of Glyptemys insculpta (Wood Turtle) was discovered on a protected area in New Jersey in 2006. Marking and radio-tracking of the old founder individuals helped to determine movement patterns and habitat use. Monitoring of nesting females revealed that nesting habitat and nest success was limited due to invasive plants, human landscape alteration, and Procyon lotor (Raccoon) depredation. We initiated habitat restoration including creation of protected nesting areas, mowing in winter, invasive plant removal, and adjacent landowner education. Here, we direct-released hatchlings from protected nests from 2006 to 2015, yet only a few were detected in subsequent years. Between 2011 and 2023, some or all of each hatchling cohort were head-started indoors at a high school for 9 months. We have continuously radio-tracked all head-starts from the 2011 cohort and portions of the 2012–2014 cohorts. Head-started turtles found their own food, established home ranges, and hibernated communally with founder adults. Subsidized Raccoons, mowers, automobiles, and flooding events—all human-instigated—were the causes of mortality. The first males and first females from the 2011 head-start cohort reached maturity in 2017 and 2019, respectively, at ages 6–8, younger than expected by 4–5 years. Successful reproduction by head-starts was confirmed by viable hatchlings produced in 2019, 2020, and 2023. Head-starting can pull a relict population out of the nose-dive to extirpation when used in conjunction with habitat-restoration practices, but it must be conducted with persistence and continuity over at least the number of years it takes for the earliest cohorts to reach maturity and begin producing offspring of their own.

59 BASIC BIOLOGICAL SCIENCES↗

COVID-19 Impact on Prison Population and Flow Dynamics

The goal of this project was to develop a unique, high-level, concept model that will (1) help examine the consequences COVID-19 has had on prison population and flow dynamics in Illinois and (2) explore (to the extent possible) how that will unfold in the short- and mid-term future. Argonne has unique expertise in dynamic systems modeling and highly specialized simulation capabilities, which will be helpful in developing such a model. The ultimate objective of this CRADA is to develop with the Illinois Public Sentencing Policy Advisory Council (SPAC) the capability to identify and understand factors and interactions associated with prison population and flow dynamics in Illinois. This understanding will then potentially lead to improvements in the allocation of various resources and services. This approach would also be useful to all other states.

59 BASIC BIOLOGICAL SCIENCES↗

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial insights into cosmology, but traditional Monte Carlo methods for cosmological inference are computationally prohibitive and inadequate for processing the thousands of lenses anticipated from future cosmic surveys. New tools for inference, such as SBI using Neural Ratio Estimation (NRE), address this challenge effectively. By training a machine learning model on simulated data of strong lenses, we can learn the likelihood-to-evidence ratio for robust inference. Our scalable approach enables more constrained population-level inference of $w$ compared to individual lens analysis, constraining $w$ to within $1\sigma$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Total Effective Dose from Radiologic Emissions from INL Facilities for Calculation of Population Dose for the INL 2024 Annual Site Environmental Report

Total effective radiation dose from airborne releases was calculated using air dispersion modeling performed by the National Oceanic and Atmospheric Administration (NOAA) Idaho Falls Office using their HYSPLIT computer model (Stein et al. 2015; Draxler et al. 2013), and the Dose Multi-Media (DOSEMM) dose assessment model (Rood 2019) . The objective of these calculations was to provide a grid of total effective dose across a model domain that encompasses a 50-mile (80-km) radius from any Idaho National Laboratory (INL) Site source. In addition to INL Site sources, releases from the Radiological and Environmental Sciences Laboratory (RESL) (IF-683) and IF-603 located at the INL Research Center (IRC) within the Idaho Falls city limits were also included. Due to tracking limitations, radionuclides released from IF-611 and IF-603 are modeled as released from IF-603. The dose results will be combined with GIS software to compute a total population dose for the calendar year (CY) 2024 and will be reported in the INL Annual Site Environmental Report (ASER). This report does not cover the population dose calculation and only documents generation of the gridded dose file.

42 - ENGINEERING↗

Inhibition of ethylene involved in resistance to E. turcicum in an exotic-derived double haploid maize population

Northern corn leaf blight (NCLB) is an economically important disease of maize. While the genetic architecture of NCLB has been well characterized, the pathogen is known to overcome currently deployed resistance genes, and the role of hormones in resistance to NCLB is an area of active research. The objectives of the study were (i) to identify significant markers associated with resistance to NCLB, (ii) to identify metabolic pathways associated with NCLB resistance, and (iii) to examine role of ethylene in resistance to NCLB. We screened 252 lines from the exotic-derived double haploid BGEM maize population for resistance to NCLB in both field and greenhouse environments. We used a genome wide association study (GWAS) and stepwise regression to identify four markers associated with resistance, followed by a pathway association study tool (PAST) to identify important metabolic pathways associated with disease severity and incubation period. The ethylene synthesis pathway was significant for disease severity and incubation period. We conducted a greenhouse assay in which we inhibited ethylene to examine the role of ethylene in resistance to NCLB. We observed a significant increase in incubation period and a significant decrease in disease severity between plants treated with the ethylene inhibitor and mock-treated plants. Our study confirms the potential of the BGEM population as a source of novel alleles for resistance. We also confirm the role of ethylene in resistance to NCLB and contribute to the growing body of literature on ethylene and disease resistance in monocots.

59 BASIC BIOLOGICAL SCIENCES↗

Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗

Potential Themis-family Asteroid Contribution to the Jupiter-family Comet Population

Recent dynamical analyses suggest that some Jupiter family comets (JFCs) may originate in the main asteroid belt instead of the outer solar system. This possibility is particularly interesting given evidence that icy main-belt objects are known to be present in the Themis asteroid family. We report results from dynamical analyses specifically investigating the possibility that icy Themis family members could contribute to the observed population of JFCs. Numerical integrations show that such dynamical evolution is indeed possible via a combination of eccentricity excitation apparently driven by the nearby 2:1 mean-motion resonance with Jupiter, gravitational interactions with planets other than Jupiter, and the Yarkovsky effect. We estimate that, at any given time, there may be tens of objects from the Themis family on JFC-like orbits with the potential to mimic active JFCs from the outer solar system, although not all, or even any, may necessarily be observably active. We find that dynamically evolved Themis family objects on JFC-like orbits have semimajor axes between 3.15 and 3.40 au for the vast majority of their time on such orbits, consistent with the strong role that the 2:1 mean-motion resonance with Jupiter likely plays in their dynamical evolution. We conclude that a contribution from the Themis family to the active JFC population is plausible, although further work is needed to better characterize this contribution.

79 ASTRONOMY AND ASTROPHYSICS↗

Spectroscopic Studies of 30 Short-period Cataclysmic Variable Stars and Remarks on the Evolution and Population of Similar Objects

We present spectroscopy and orbital periods P {sub orb} for 30 apparently nonmagnetic cataclysmic binaries with periods below ∼3 hr, nearly all of which are dwarf novae, mostly of the SU Ursae Majoris subclass. We then turn to the evidence supporting the prediction that short-period dwarf novae evolve toward longer periods after passing through a minimum period—the “period bounce” phenomenon. Plotting data from the literature reveals that for superhump period excess ϵ = (P {sub sh} − P {sub orb})/P {sub orb} below ∼0.015, the period appears to increase with decreasing ϵ, agreeing at least qualitatively with the predicted behavior. Next, motivated by the long (decadal) outburst intervals of the WZ Sagittae subclass of short-period dwarf novae, we ask whether there could be a sizable population of “lurkers”—systems that resemble dwarf novae at minimum light, but which do not outburst over accessible timescales (or at all) and therefore do not draw attention to themselves. By examining the outburst history of the Sloan Digital Sky Survey sample of CVs, which were selected by color and not by outburst, we find that a large majority of the color-selected dwarf-nova-like objects have been observed to outburst, and we conclude that “lurkers,” if they exist, are a relatively minor part of the CV population.

79 ASTRONOMY AND ASTROPHYSICS↗

SPISEA: A Python-based Simple Stellar Population Synthesis Code for Star Clusters

We present Stellar Population Interface for Stellar Evolution and Atmospheres (SPISEA), an open-source Python package that simulates simple stellar populations. The strength of SPISEA is its modular interface which offers the user control of 13 input properties including (but not limited to) the initial mass function, stellar multiplicity, extinction law, and the metallicity-dependent stellar evolution and atmosphere model grids used. The user also has control over the initial–final mass relation in order to produce compact stellar remnants (black holes, neutron stars, and white dwarfs). We demonstrate several outputs produced by the code, including color–magnitude diagrams, HR-diagrams, luminosity functions, and mass functions. SPISEA is object-oriented and extensible, and we welcome contributions from the community. The code and documentation are available on GitHub (https://github.com/astropy/SPISEA) and ReadtheDocs (https://spisea.readthedocs.io/en/latest/), respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

The Blue Straggler Population of the Open Clusters Trumpler 5, Trumpler 20, and NGC 2477

We present a study based on Gaia DR2 of the population of blue straggler stars in the open clusters Trumpler 5, Trumpler 20, and NGC 2477. All candidates were selected according to their position in the color–magnitude diagram, their proper motion components, and their parallax. We also looked for yellow stragglers, i.e., possible evolved blue stragglers. We found that Trumpler 5 hosts a large blue straggler star population, which allowed us to analyze their radial distribution as a probe of the cluster’s dynamical status. The blue straggler star distribution was compared with that of red giant branch stars to evaluate mass segregation. Our results indicate that blue straggler stars are not more centrally concentrated than red giant branch stars stars in any of the clusters. The radial distribution of blue straggler stars in Trumpler 5 is flat. Additionally, using a multi-epoch radial velocity survey conducted with the high-resolution spectrograph FLAMES/GIRAFFE at the Very Large Telescope, we measured the radial velocities of a sample of stragglers to compare with the mean radial velocity and velocity dispersion of the clusters. Based on the radial velocity variations for different epochs, we roughly classified these stars as possible close or long-period binaries.

47 OTHER INSTRUMENTATION↗

Anomalous Stellar Populations in Low-surface-brightness Galaxies

We present new Hubble Space Telescope WFC3 near-IR observations of the color–magnitude diagrams (CMDs) in two low-surface-brightness galaxies, F575-3 and F615-1, notable for having no current star formation based on a lack of Hα emission. Key features of the near-IR CMDs are resolved, such as the red giant branch (RGB), the asymptotic giant branch (AGB) region, and the top of the blue main sequence. F575-3 has the bluest RGB of any CMD in the literature, indicating an extremely low mean metallicity. F615-1 has unusually wide RGB and AGB sequences, suggesting multiple episodes of star formation from metal-poor gas, and possibly infalling material. Both galaxies have an unusual population of stars to the red of the RGB and lower in luminosity than typical AGB stars. These stars have normal optical colors but abnormal near-IR colors. We suggest that this population of stars might be analogous to local peculiar stars like Be stars with strong near-IR excesses owing to a surrounding disk of hot gas.

47 OTHER INSTRUMENTATION↗

The APOGEE Library of Infrared SSP Templates (A-LIST): High-resolution Simple Stellar Population Spectral Models in the H Band

Integrated light spectroscopy from galaxies can be used to study the stellar populations that cannot be resolved into individual stars. This analysis relies on stellar population synthesis (SPS) techniques to study the formation history and structure of galaxies. However, the spectral templates available for SPS are limited, especially in the near-infrared (near-IR). We present A-LIST (APOGEE Library of Infrared SSP Templates), a new set of high-resolution, near-IR SSP spectral templates spanning a wide range of ages (2–12 Gyr), metallicities ( − 2.2 < [M/H] < + 0.4) and α abundances ( − 0.2 < [α/M] < + 0.4). This set of SSP templates is the highest resolution (R ∼ 22, 500) available in the near-IR, and the first such based on an empirical stellar library. Our models are generated using spectra of ∼300,000 stars spread across the Milky Way, with a wide range of metallicities and abundances, from the APOGEE survey. We show that our model spectra provide accurate fits to M31 globular cluster spectra taken with APOGEE, with best-fit metallicities agreeing with those of previous estimates to within ∼0.1 dex. We also compare these model spectra to lower-resolution E-MILES models and demonstrate that we recover the ages of these models to within ∼1.5 Gyr. This library is available in https://github.com/aishashok/ALIST-library.

47 OTHER INSTRUMENTATION↗