Pathway Possibilities: The Lilly Endowment's Pathways for Tomorrow Initiative

Looking to the future for what supervision and mentoring will look like and be utilized

Comparison of Experimental vs Theoretical Abundances of ¹³CH₃D and ¹²CH₂D₂ for Isotopically Equilibrated Systems from 1 to 500 °C

Methane is produced and consumed via numerous microbial and chemical reactions in atmospheric, hydrothermal, and magmatic reactions. The stable isotopic composition of methane has been used extensively for decades to constrain the source of methane in the environment. A recently introduced isotopic parameter used to study the formation temperature and formational conditions of methane is the measurement of molecules of methane with multiple rare, heavy isotopes (‘clumped’) such as ¹³CH₃D and ¹²CH₂D₂. In order to place methane clumped-isotope measurements into a thermodynamic reference frame that allows calculations of clumped-isotope based temperatures (geothermometry) and comparison between laboratories, all past studies have calibrated their measurements using a combination of experiment and theory based on the temperature dependence of clumped isotopologue distributions for isotopically equilibrated systems. These have previously been performed at relatively high temperatures (>150˚C). Given that many natural occurrences of methane form below these temperatures, previous calibrations require extrapolation when calculating clumped-isotope based temperatures outside of this calibration range. We provide a new experimental calibration of the relative equilibrium abundances of ¹³CH₃D and ¹²CH₂D₂ from 1–500˚C using a combination of γ-Al₂O₃ and Ni-based catalysts and compare them to new theoretical computations using Path Integral Monte Carlo (PIMC) methods and find 1:1 agreement (within ± 1 standard error) for the observed temperature dependence of clumping between experiment and theory over this range. This demonstrates that measurements, experiments, and theory agree from 1–500°C providing confidence in the overall approaches. Polynomial fits to PIMC computations, which are considered the most rigorous theoretical approach available, are given as follows (valid T ≥ 270 K): ∆¹³CH₃D≅1000×ln(K¹³CH₃D)= 1.47348×10¹⁹/T⁷ - 2.08648×10¹⁷/T⁶ + 1.19810×10¹⁵/T⁵ - 3.54757×10¹²/T⁴ +5.54476×10⁹/T³ – 3.49294×10⁶/T² + 8.89370×10₂/T ∆¹²CH₂D₂≅1000×ln(8/3×K¹²CH₂D₂)= -9.67634×10¹⁵/T⁶ + 1.71917×10¹⁴/T⁵ - 1.24819×10¹²/T⁴ + 4.30283×10⁹/T3 -4.48660×10⁶/T² + 1.86258×10³/T. We additionally compare PIMC computations to those performed utilizing traditional approaches that are the basis of most previous calibrations (Bigeleisen, Mayer, and Urey model, BMU) and discuss the potential sources of error in the BMU model relative to PIMC computations

<i>Trypanosoma evansi</i>: Genetic variability detected using amplified restriction fragment length polymorphism (AFLP) and random amplified polymorphic DNA (RAPD) analysis of Kenyan isolates

We compared two methods to generate polymorphic markers to investigate the population genetics of Trypanosoma evansi; random amplified polymorphic DNA (RAPD) and amplified restriction fragment length polymorphism (AFLP) analyses. AFLP accessed many more polymorphisms than RAPD. Cluster analysis of the AFLP data showed that 12 T.evansi isolates were very similar (‘type A’) whereas 2 isolates differed substantially (‘type B’). Type A isolates have been generally regarded as genetically identical but AFLP analysis was able to identify multiple differences between them and split the type A T. evansi isolates into two distinct clades

The future of evolutionary medicine: sparking innovation in biomedicine and public health

Evolutionary medicine - i.e. the application of insights from evolution and ecology to biomedicine - has tremendous untapped potential to spark transformational innovation in biomedical research, clinical care and public health. Fundamentally, a systematic mapping across the full diversity of life is required to identify animal model systems for disease vulnerability, resistance, and counter-resistance that could lead to novel clinical treatments. Evolutionary dynamics should guide novel therapeutic approaches that target the development of treatment resistance in cancers (e.g., via adaptive or extinction therapy) and antimicrobial resistance (e.g., via innovations in chemistry, antimicrobial usage, and phage therapy). With respect to public health, the insight that many modern human pathologies (e.g., obesity) result from mismatches between the ecologies in which we evolved and our modern environments has important implications for disease prevention. Life-history evolution can also shed important light on patterns of disease burden, for example in reproductive health. Experience during the COVID-19 (SARS-CoV-2) pandemic has underlined the critical role of evolutionary dynamics (e.g., with respect to virulence and transmissibility) in predicting and managing this and future pandemics, and in using evolutionary principles to understand and address aspects of human behavior that impede biomedical innovation and public health (e.g., unhealthy behaviors and vaccine hesitancy). In conclusion, greater interdisciplinary collaboration is vital to systematically leverage the insight-generating power of evolutionary medicine to better understand, prevent, and treat existing and emerging threats to human, animal, and planetary health

Quantification of diesel injector dribble using 3D reconstruction from x-ray and DBI imaging

[EN] Post-injection dribble is known to lead to incomplete atomisation and combustion due to the release of slow moving, and often surface-bound, liquid fuel after the end of the injection event. This can have a negative effect on engine emissions, performance, and injector durability. To better quantify this phenomenon we present a new image processing approach to quantify the volume and surface area of ligaments produced during the end of injection, for an ECN ‘Spray B’ 3-hole injector. Circular approximation for cross-sections was used to estimate three-dimensional parameters of droplets and ligaments. The image processing consisted in three stages: edge detection, morphological reconstruction, and 3D reconstruction. For the last stage of 3D reconstruction, smooth surfaces were obtained by computation of the alpha shape which represents a bounding volume enveloping a set of 3D points. The object model was verified by calculation of surface area and volume from 2D images of figures with well-known shapes. We show that the object model fits non-spherical droplets and pseudo-cylindrical ligaments reasonably well. We applied our processing approach to datasets generated by different research groups to decouple the effect of gas temperature and pressure on the fuel dribble process. High-speed X-ray phase-contrast images obtained at room temperature conditions (297 K) at the 7-ID beamline of the Advanced Photon Source at Argonne National Laboratory, together with diffused back-illumination (DBI) images captured at a wide range of temperature conditions (293-900 K) by CMT Motores Térmicos, were analysed and compared quantitatively.This work was supported by the UK’s Engineering and Physical Science Research Council [grants EP/K020528/1 and EP/M009424/1], and BP Formulated Products Technology. The authors acknowledge the support of this work from CMT Motores Térmicos (Universitat Politècnica de València, Spain). Parts of this research were performed at the 7-ID beam line of the Advanced Photon Source at Argonne National Laboratory. Use of the APS is supported by the U.S. Department of Energy (DOE) under Contract No. DEAC02-06CH11357. This research was partially funded by DOE's Vehicle Technologies Program, Office of Energy Efficiency and Renewable Energy. The authors would like to thank Team Leaders Gurpreet Singh and Leo Breton for their support of this workSechenyh, V.; Turner, J.; Sykes, D.; Duke, D.; Swantek, A.; Matusik, K.; Kastengren, A.... (2017). Quantification of diesel injector dribble using 3D reconstruction from x-ray and DBI imaging. En Ilass Europe. 28th european conference on Liquid Atomization and Spray Systems. Editorial Universitat Politècnica de València. 216-223. https://doi.org/10.4995/ILASS2017.2017.4742OCS21622

University makes me angry: Investigating stimulus-response (S-R) and cognitive-mediation (C-M) emotion beliefs in undergraduate students

Emotion regulation through cognitive reappraisal is well-studied, but less so are the predispositional and superordinate beliefs that influence reappraisal. Recently, researchers developed the cognitive mediation beliefs questionnaire (CMBQ), which measures two emotion beliefs, namely stimulus-response (S-R) generation beliefs and cognitive mediation (C-M) change beliefs. In working populations S-R generation beliefs are inversely related to cognitive reappraisal tendencies and positive mental health, and positively related to emotion reactivity. C-M change beliefs are positively related to cognitive reappraisal tendencies, and inversely related to emotion reactivity and positive mental health. As yet, there is no evidence for the validity of the CMBQ within student samples, or for the associations between its subscales and cognitive reappraisal, emotion reactivity, and positive mental health. Therefore, in the present study the CMBQ is tested for factorial, convergent (associations with cognitive reappraisal), and concurrent (associations with emotion reactivity and positive mental health) validity in a cohort of 621 undergraduate students in the United Kingdom (U.K.). Results indicate support for the factorial and convergent validity of the CMBQ, with mixed evidence for the concurrent validity of the CMBQ. A CM-SR discrepancy score appeared to provide a promising variable when associated with emotion reactivity and positive mental health. The findings are discussed in terms of practical and research implications of the findings