Ducks Unlimited

Data visualization tools are important tools for making health decisions based on large amounts of data. However, very few comparisons of data visualization tools have been done in the context of health-related research. This paper compares commonly available visualization tools from the perspective of a dashboard developer in the context of scientific health research using real-world data and to provide general suggestions for dashboard developers’ future visualization efforts in health-related scientific discoveries. We evaluated four commonly available visualization tools (Tableau, Spotfire, PowerBI, and R Shiny). Each tool was evaluated on visualization outcomes (comparing the generated outputs of tables, scatterplots, correlation plots, treemaps, heatmaps, and geographic maps), usability, Cloud compatibility, analytic integration, and a few other factors. All tools generated comparable visualization outcomes in our tests and were equally usable with the exception of R Shiny which is not recommended for users with limited coding experience. Every tool except R Shiny supports connections to PostgreSQL, gSheets, and Athena without additional configurations. All tools support integration with R and Python; however, PowerBI requires some additional configuration. Every tool is capable of data pre-processing and supports data transformation, null detection and outlier detection. Each tool has its own unique advantages and limitations.

Abstract Large datasets, combined with modeling techniques, provide a quantitative way to estimate when known archaeological sites will be impacted by climatological changes. With over 4,000 archaeological sites recorded on the coast of Georgia, USA, the state provides an ideal opportunity to compare methods. Here, we compare the popular passive “bathtub” modeling with the dynamic Sea Level Affecting Marshes Model (SLAMM) combined with the Marshes Equilibrium Model (MEM). The goal of this effort is to evaluate prior modeling and test the benefits of more detailed ecological modeling in assessing site loss. Our findings indicate that although rough counts of archaeological sites destroyed by sea-level rise (SLR) are similar in all approaches, using the latter two methods provides critical information needed in prioritizing site studies and documentation before irrevocable damages occur. Our results indicate that within the next 80 years, approximately 40% of Georgia's coastal sites will undergo a loss of archaeological context due to wetlands shifting from dry ecological zones to transitional marshlands or submerged estuaries and swamps.

Objective: Sphingolipids (SPL) in circulation have been associated with pathological outcomes of metabolic and cardiovascular diseases that are known to be influenced by aging. We sought to determine the age association of plasma SPL species in people with no diabetes. Methods: We determined plasma levels (pmole/mL) of 58 SPL species, including ceramides (Cer), monohexosylceramides (MHC), sphingomyelins (SM), sphingosine (So), and sphingosine 1-phosphate (S1P) in 239 normoglycemic participants using LC-MS/MS after dividing them into five age groups, 19-29y (n=46), 30-39y (n=47), 40-49y (n=64), 50-59y (n=67), and ≥60y (n=15). Correlation analysis identified SPL species that differ significantly among the age groups and that significantly correlate with aging. Results: We identified the ratio of C18:0/C18:1 in Cer, MHC, and SM differed significantly in different age groups along with some very-long-chain (VLC) species of MHC and SM, SM C14:0, total SM, and SM% of SPL, which remained significant after adjusting for gender, race, BMI, waist circumference, FPG, and 2hPG. Interestingly, Cer C18:1 (r=0.20, p<0.01) positively correlated with aging, and the ratio of Cer C18:0/C18:1 (r= -0.27, p<0.0001) and MHC (r= -0.23, p<0.001) correlated negatively. While levels of So (r= -0.29, p<0.0001) and MHC C26:0 (r= -0.20, p<0.01), MHC C28:0 (r= -0.25, p<0.0001), MHC C34:0 (r= -0.23, p<0.001) and MHC ratio of C26:0/C26:1 (r= -0.27, p<0.0001) and MHC% of SPL (r= -0.20, p<0.01) correlated negatively, SM% of SPL (r=0.21, p<0.001) correlated positively. Conclusions: Our results show that the plasma concentration of certain SPL species and ratios differ with age and correlate differentially with age. Thus, alterations in SPL metabolism may be linked to aging and age-related disorders. Disclosure N. Feto: None. P. Asuzu: None. F.B. Stentz: None. J.Y. Wan: None. S. Dagogo-Jack: Consultant; Merck Sharp & Dohme Corp., Medtronic, Bayer Inc. Stock/Shareholder; Aerami. N. Mandal: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK128129, R01 DK067269, and DK 48411)

Potential competing interests: No potential competing interests to

126 Background: Lung cancer (LC) causes the most cancer deaths in the US, but early detection improves outcomes. Uptake of Low-Dose CT screening (LDCT) has been low, contributing to race-based disparities. Programmatic management of incidentally detected pulmonary nodules (PN) provides a complementary avenue for early detection which could address disparities. In our PN cohort, Detecting Early LC in the Mississippi Delta (DELUGE), we provide broad access to early detection across a region fraught with geographic, socioeconomic, and race-based disparities. However, many detected PN will not result in LC. After successful implementation at the program level, we seek to evaluate individual-level factors important for early-detection. We evaluated how individuals with small PN identified in DELUGE differ between those who were and were not diagnosed with LC. Methods: DELUGE is a prospective cohort study where we systematically manage incidentally detected PN with trained navigators and evidence-based risk stratification. We constructed DELUGE in a community-based healthcare system across the mid-south with some of the highest per-capita LC incidence and mortality rates in the US. We evaluated all PN ≤30mm in DELUGE from 2015-2022. We compared clinical and demographic characteristics between individuals who were or were not diagnosed with LC within 24 months. Primary analysis used logistic regression, reporting odds ratios (OR) with 95% confidence intervals. Results: From 2015-2022, 17,945 individuals with PN ≤30 mm (71% of the total cohort of 25,339) were identified and enrolled in DELUGE. They had median age of 65 years, were 56% female, and 27% Black / 69% White. 853 (4.8%) patients were diagnosed with LC within two years. PN size significantly predicted LC diagnosis. For every 1 mm increase in nodule size the odds of LC increased by 15% (OR: 1.15 [1.14-1.16]); PN in an upper lobe (OR: 2.0 [1.7-2.2]) and those with cavitation also increased the odds of LC (OR: 2.9[1.9-4.2]). Sex, rural/urban residence, and number of PN were not associated with LC. The most predictive individual level characteristics were age, prior cancer history (OR: 1.3 [1.1-1.5], family cancer history (OR: 1.7 [1.5-2.0], COPD (OR: 3.3 [2.9-3.8]), and smoking history (OR: 6.6 [5.3-8.4]). In the multiple variable model, the most significant associations with LC diagnosis included PN size, age, insurance, family cancer history, COPD, and smoking history (all p<0.0001). This model could provide estimated sensitivity 0.81 and specificity 0.81 for predicting LC (AUC= 0.88). Conclusions: Factors measurable at baseline have predictive ability, and predictive modeling may be useful in management of small PN. More focused follow-up could improve programmatic efficiency, targeting the alleviation of geographic, socioeconomic, and race-based health disparities in this high poverty region of the US.

Le Traité du Quirinal, signé à Rome le 26 novembre 2021 et entré en vigueur le 1 er février 2023, souligne la volonté politique d’une coopération renforcée entre la France et l’Italie. Parmi ses onze articles thématiques, le deuxième concerne les aspects de sécurité et de défense. Le renforcement de la coopération politicomilitaire ne peut commencer que par une meilleure compréhension mutuelle. L’objectif de cet article est précisément de comprendre le système politico-militaire italien, en soulignant ses similitudes et ses différences par rapport à son homologue français, afin de renforcer la coopération en tirant parti des atouts communs, et en notant les limites et les contraintes mutuelles, pour parvenir à une approche complémentaire en vue de la réalisation d’objectifs communs.

Abstract The Prairie Pothole Region (PPR) is globally important for breeding waterfowl but has been altered via wetland drainage and grassland conversion to accommodate agricultural land use. Thus, understanding the ecology of waterfowl in these highly modified landscapes is essential for their conservation. Brood occurrence is the cumulative outcome of key life‐history events including pair formation and territory establishment, nest success, and early brood survival. We applied new technological advances in brood surveying methods to understand brood use of wetlands and how land use and wetland‐specific factors influenced brood use of 413 wetlands in crop‐dominated landscapes in the PPR of Iowa, Minnesota, North Dakota, and South Dakota, USA, during summers of 2018–2020. Dynamic occupancy models combining information from 2 visits throughout the year revealed no difference among the 4 states or between private and public lands, resulting in a region‐wide annual wetland occupancy estimate of 0.41 (95% credible interval [CrI] = 0.26, 0.58). We assessed aquatic invertebrate forage availability, wetland and upland vegetation communities, and various water chemistry metrics in a subset (n = 225) of these wetlands to evaluate how landscape and wetland‐specific factors influenced occupancy. The amount of grassland surrounding wetlands was the only variable to influence occupancy at a landscape scale, while wetland size, invertebrates, fish, and vegetation communities influenced occupancy at finer scales. Closer scrutiny of wetland area revealed occupancy was greater in small wetlands after controlling for total wetland area. Our results indicate the greatest constraint on brood occupancy across crop‐dominated landscapes of the PPR in the United States was the occurrence of semipermanent wetlands suitable for brood rearing. Other factors, such as wetland vegetation or surrounding land use, had minor intervening influences on duck brood use and ducks were distributed invariant of wetland ownership or broad spatial processes occurring among states. These results demonstrated wetland conservation and restoration strategies are likely to yield gains in annual duck broods across this vast, altered, and highly modified landscape.

Food resources are assumed to limit waterfowl populations in the Mississippi Alluvial Valley, thus bioenergetic models are used for spatial allocation of food resources to provide adequate energy to support regional waterfowl population objectives. Changes in population abundance and distributions of midcontinent greater white-fronted geese Anser albifrons have implications for region-specific conservation planning of energetic resources for wintering waterfowl. This research aimed to quantify timing of arrival of greater white-fronted geese to wintering areas and quantify foraging behaviors. These data can help refine bioenergetics models and facilitate future waterfowl habitat planning efforts in the region. Bioenergetics models account for energetic demands of wintering geese by assuming they forage in flooded habitats 25% of the time across a 110-day winter planning period. Although this assumption has gone untested, our estimate of time spent foraging in flooded habitats (27.4% ± 5.8%) confirms the current model parameter of 25% of the time. However, we suggest that this is not the best parameter to use in bioenergetics models as greater white-fronted geese in our study foraged in dry habitats (72.6% ± 5.8%) more often than in flooded habitats. In addition, selection for rice fields in heavily weighted toward early winter (November; β = 2.85), and use declined 70% as winter progressed (February; β = 0.89), likely due to depletion of available rice grain, hunting pressure, and the physiological need to switch from a greater carbohydrate diet to a nitrogen-rich diet. In addition, white-fronted geese arrived to wintering areas earlier than current models accounted for with a mean arrival date of 30 October (± 2.5 days) to the Mississippi Alluvial Valley. We suggest early arrival to the wintering area and greater selection for dry rice fields during early winter indicates exploitative competition by white-fronted geese for shared food resources that may not be adequately accounted for in current bioenergetics models. We suggest current models underestimated energetic demands and the competitive nature of early migratory greater white-fronted geese.