In 2016, the National Center for Advancing Translational Science launched the Trial Innovation Network (TIN) to address barriers to efficient and informative multicenter trials. The TIN provides a national platform, working in partnership with 60+ Clinical and Translational Science Award (CTSA) hubs across the country to support the design and conduct of successful multicenter trials. A dedicated Hub Liaison Team (HLT) was established within each CTSA to facilitate connection between the hubs and the newly launched Trial and Recruitment Innovation Centers. Each HLT serves as an expert intermediary, connecting CTSA Hub investigators with TIN support, and connecting TIN research teams with potential multicenter trial site investigators. The cross-consortium Liaison Team network was developed during the first TIN funding cycle, and it is now a mature national network at the cutting edge of team science in clinical and translational research. The CTSA-based HLT structures and the external network structure have been developed in collaborative and iterative ways, with methods for shared learning and continuous process improvement. In this paper, we review the structure, function, and development of the Liaison Team network, discuss lessons learned during the first TIN funding cycle, and outline a path toward further network maturity.

OBJECTIVES/GOALS: The rates of computational phenotyping algorithm reuse across health systems are low, leading to a proliferation of algorithms for the same trait. We propose a framework for reusing computational phenotyping algorithms and describe the real-world deployment of this framework for the development of the Colorado Diabetes EHR Research Repository. METHODS/STUDY POPULATION: The novel phenotype reuse framework consists of 4 steps: select algorithms that are appropriate for reuse by assessing whether they are fit for purpose; extend the algorithm to account for changes in data and care practice standards; localize the algorithm to use local database standards and terminologies; optimize the algorithm by applying a data driven approach to achieve the desired local performance. To identify individuals with type 1 diabetes (T1D) or type 2 diabetes (T2D), we selected and implemented T2D algorithms in a cohort of adults with any diabetes or pre-diabetes related diagnosis code, medication, or abnormal glucose-related laboratory test in the clinical data warehouse for UCHealth and the University of Colorado. RESULTS/ANTICIPATED RESULTS: We included a total of 926,290 patients who were identified by initial filters. Patients were more likely to be female (53%), identify as non-Hispanic white (69%) and had a median age of 58 years (IQR: 41, 70). Implementation, extension, localization, & optimization through iterative chart review prioritized high sensitivity for all-cause diabetes and high specificity for T1D and T2D. Of the original cohort, 252,946 (27%) were identified by the all-cause diabetes algorithm. Of these 11,688 were identified as T1D and 135,588 as T2D. After optimization the all-cause diabetes algorithm had 88% sensitivity, 90% specificity, 74% positive predictive value (PPV), and 96% negative predictive value (NPV). Our algorithms for T1D and T2D had high specificity (100% and 99%, respectively) and PPV (100 and 96% respectively). DISCUSSION/SIGNIFICANCE: Developing computational phenotyping algorithms is expensive and time consuming, yet algorithm reuse is low due to a lack of practical approaches for reusing algorithms. We demonstrate application of a novel framework for algorithm reuse, yielding good alignment of algorithm performance with study goals for identifying individuals with diabetes.

Two introduced carnivores, the European red fox Vulpes vulpes and domestic cat Felis catus, have had extensive impacts on Australian biodiversity. In this study, we collate information on consumption of Australian birds by the fox, paralleling a recent study reporting on birds consumed by cats. We found records of consumption by foxes on 128 native bird species (18% of the non-vagrant bird fauna and 25% of those species within the fox’s range), a smaller tally than for cats (343 species, including 297 within the fox’s Australian range, a subset of that of the cat). Most (81%) bird species eaten by foxes are also eaten by cats, suggesting that predation impacts are compounded. As with consumption by cats, birds that nest or forage on the ground are most likely to be consumed by foxes. However, there is also some partitioning, with records of consumption by foxes but not cats for 25 bird species, indicating that impacts of the two predators may also be complementary. Bird species ≥3.4 kg were more likely to be eaten by foxes, and those <3.4 kg by cats. Our compilation provides an inventory and describes characteristics of Australian bird species known to be consumed by foxes, but we acknowledge that records of predation do not imply population-level impacts. Nonetheless, there is sufficient information from other studies to demonstrate that fox predation has significant impacts on the population viability of some Australian birds, especially larger birds, and those that nest or forage on the ground.

Field studies were conducted to assess two sulfur-containing additives for use with glyphosate applied postemergence to glyphosate-resistant cotton for the control of sicklepod and yellow nutsedge. Neither diammonium sulfate (AMS) nor ammonium thiosulfate (ATS), both applied at 2.24 kg/ha, increased control of either species. Effective control of both species was dependent on glyphosate (isopropylamine salt) rate alone, with optimum control at 1.26 kg ae/ha. Plant-mapping data further indicated that sulfur-containing additives generally had no effect on either cotton fruiting patterns or yield. However, applying glyphosate at any rate did increase seed cotton yield in 2 of 3 yr vs. no glyphosate. In addition, applying glyphosate at any rate resulted in an increase in the number of bolls vs. no glyphosate in the following plant-mapping responses: total number of bolls per plant, number of abcised bolls per plant, bolls at the top five sympodial nodes, and bolls at positions 1 and 2 on the sympodia. Glyphosate absorption and subsequent translocation, as influenced by the addition of the sulfur-containing additives, was evaluated using radiotracer techniques. Glyphosate absorption after 48 h was 86, 63, and 37% of amount applied in cotton, sicklepod, and yellow nutsedge, respectively. Absorption by sicklepod and yellow nutsedge was not affected by the addition of either of the additives. Absorption by cotton was reduced by ATS but was not affected by AMS. In yellow nutsedge and cotton, glyphosate concentration in the treated area and adjacent tissue was not affected by either additive. A greater portion of glyphosate was translocated away from the treated area in sicklepod with glyphosate plus AMS (32%) than with glyphosate plus ATS (21%). AMS and ATS may be used in glyphosate-resistant cotton without the risk of either crop injury or yield reduction. However, their use for increased control of annual weed species, such as sicklepod and yellow nutsedge, may not be warranted.

Field experiments were conducted in Alabama during 1999 and 2000 to test the hypothesis that any glyphosate-induced yield suppression in glyphosate-resistant cotton would be less with irrigation than without irrigation. Yield compensation was monitored by observing alterations in plant growth and fruiting patterns. Glyphosate treatments included a nontreated control, 1.12 kg ai/ha applied POST at the 4-leaf stage, 1.12 kg/ha applied DIR at the prebloom stage, and 1.12 kg/ha applied POST at 4-leaf and postemergence directed (DIR) at the prebloom cotton stages. The second variable, irrigation treatment, was established by irrigating plots individually with overhead sprinklers or maintaining them under dryland, nonirrigated conditions. Cotton yield and all measured parameters including lint quality were positively affected by irrigation. Irrigation increased yield 52% compared to nonirrigated cotton. Yield and fiber quality effects were independent of glyphosate treatments. Neither yield nor any of the measured variables that reflected whole plant response were influenced by glyphosate treatment or by a glyphosate by irrigation interaction.

Objectives: Parkinson’s disease (PD) results in a range of non-motor deficits that can affect mood, cognition, and language, and many of these issues are unresponsive to pharmacological intervention. Aerobic exercise can improve mood and cognition in healthy older adults, although only a few studies have examined exercise effects on these domains in PD. The current study assesses the effects of aerobic exercise on aspects of cognition, mood, and language production in people with PD. Methods: This study compares the effects of aerobic exercise to stretch-balance training and a no-contact control group in participants with idiopathic PD. The aerobic and stretch-balance groups trained three times a week for 16 weeks, while controls continued normal activities. Outcome measures included disease severity, mood, cognition (speed of processing, memory, and executive function), and language production (picture descriptions). Cognition and language were assessed in single and dual task conditions. Results: Depressive symptoms increased only in the control group (p<.02). Executive function improved in the aerobic exercise group only in the single task (p=.007) and declined in controls in the dual task. Completeness of picture descriptions improved significantly more in the aerobic group than in the stretch-balance group (p<.02). Conclusions: Aerobic exercise is a viable intervention for PD that can be protective against increased depressive symptoms, and can improve several non-motor domains, including executive dysfunction and related aspects of language production. (JINS, 2016, 22, 878–889)

Vegetation affects feedbacks in Earth's hydrologic system, but is constrained by physiological adaptations. In extant ecosystems, the mechanisms controlling plant water used can be measured experimentally; for extinct plants in the recent geological past, water use can be inferred from nearest living relatives, assuming minimal evolutionary change. In deep time, where no close living relatives exist, fossil material provides the only information for inferring plant water use. However, mechanistic models for extinct plant water use must be built on first principles and tested on extant plants. Plants serve as a conduit for water movement from the soil to the atmosphere, constrained by tissue-level construction and gross architecture. No single feature, such as stomata or veins, encompasses enough of the complexity underpinning water-use physiology to serve as the basis of a model of functional water use in all (or perhaps any) extinct plants. Rather, a “functional whole plant” model must be used. To understand the interplay between plant and atmosphere, water use in relation to environmental conditions is investigated in an extinct plant, the seed fern Medullosa ((Division Pteridospermatophyta), by reviewing methods for reconstructing physiological variables such as leaf and stem hydraulic capacity, photosynthetic rate, transpiration rate, stomatal conductance, and albedo. Medullosans had the potential for extremely high photosynthetic and assimilation rates, water transport, stomatal conductance, and transpiration—rates comparable to later angiosperms. When these high growth and gas exchange rates of medullosans are combined with the unique atmospheric gas composition of the late Paleozoic atmosphere, complex vegetation-environmental feedbacks are expected despite their basal phylogenetic position relative to post-Paleozoic seed plants.

Hot Jupiters, i.e., Jupiter-mass planets with orbital semi major axes of <10 stellar radii, can interact strongly with their host stars. If the planet is moving supersonically through the stellar wind, a bow shock will form ahead of the planet where the planetary magnetosphere slams into the the stellar wind or where the planetary outflow and stellar wind meet. Here we present high resolution spectra of the hydrogen Balmer lines for a single transit of the hot Jupiter HD 189733 b. Transmission spectra of the Balmer lines show strong absorption ~70 minutes before the predicted optical transit, implying a significant column density of excited hydrogen orbiting ahead of the planet. We show that a simple geometric bow shock model is able to reproduce the important features of the absorption time series while simultaneously matching the line profile morphology. Our model suggests a large planetary magnetic field strength of ~28 G. Follow-up observations are needed to confirm the pre-transit signal and investigate any variability in the measurement.