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Allosteric control of reaction thermodynamics is well understood, but the mechanisms by which changes in local geometries of receptor sites lower activation reaction barriers in electronically uncoupled, remote reaction moieties remain relatively unexplored. Here we report a molecular scaffold in which the rate of thermal E-to-Z isomerization of an alkene increases by a factor of as much as 10⁴in response to fast binding of a metal ion to a remote receptor site. A mechanochemical model of the olefin coupled to a compressive harmonic spring reproduces the observed acceleration quantitatively, adding the studied isomerization to the very few reactions demonstrated to be sensitive to extrinsic compressive force. The work validates experimentally the generalization of mechanochemical kinetics to compressive loads and demonstrates that the formalism of force-coupled reactivity offers a productive framework for the quantitative analysis of the molecular basis of allosteric control of reaction kinetics. Important differences in the effects of compressive vs. tensile force on the kinetic stabilities of molecules are discussed.

 

We present a measurement of the Hubble ConstantH₀using the gravitational wave event GW190412, an asymmetric binary black hole merger detected by LIGO/Virgo, as a dark standard siren. This event does not have an electromagnetic counterpart, so we use the statistical standard siren method and marginalize over potential host galaxies from the Dark Energy Spectroscopic Instrument (DESI) survey. GW190412 is well-localized to 12 deg²(90% credible interval), so it is promising for a dark siren analysis. The dark siren value for$H_0={85.4}_{-33.9}^{+29.1}$km s⁻¹ Mpc⁻¹, with a posterior shape that is consistent with redshift overdensities. When combined with the bright standard siren measurement from GW170817 we recover$H_0={77.96}_{-5.03}^{+23.0}$km s⁻¹ Mpc⁻¹, consistent with both early and late-time Universe measurements ofH₀. This work represents the first standard siren analysis performed with DESI data, and includes the most complete spectroscopic sample used in a dark siren analysis to date.

 

Mesenchymal stromal cells (MSCs) have shown promise in regenerative medicine applications due in part to their ability to modulate immune cells. However, MSCs demonstrate significant functional heterogeneity in terms of their immunomodulatory function because of differences in MSC donor/tissue source, as well as non-standardized manufacturing approaches. As MSC metabolism plays a critical role in their ability to expand to therapeutic numbers ex vivo, we comprehensively profiled intracellular and extracellular metabolites throughout the expansion process to identify predictors of immunomodulatory function (T-cell modulation and indoleamine-2,3-dehydrogenase (IDO) activity). Here, we profiled media metabolites in a non-destructive manner through daily sampling and nuclear magnetic resonance (NMR), as well as MSC intracellular metabolites at the end of expansion using mass spectrometry (MS). Using a robust consensus machine learning approach, we were able to identify panels of metabolites predictive of MSC immunomodulatory function for 10 independent MSC lines. This approach consisted of identifying metabolites in 2 or more machine learning models and then building consensus models based on these consensus metabolite panels. Consensus intracellular metabolites with high predictive value included multiple lipid classes (such as phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins) while consensus media metabolites included proline, phenylalanine, and pyruvate. Pathway enrichment identified metabolic pathways significantly associated with MSC function such as sphingolipid signaling and metabolism, arginine and proline metabolism, and autophagy. Overall, this work establishes a generalizable framework for identifying consensus predictive metabolites that predict MSC function, as well as guiding future MSC manufacturing efforts through identification of high-potency MSC lines and metabolic engineering.

 

This full research paper documents assessment definitions from engineering faculty members, mainly from Research 1 universities. Assessments are essential components of the engineering learning environment, and how engineering faculty make decisions about assessments in their classroom is a relatively understudied topic in engineering education research. Exploring how engineering faculty think and implement assessments through the mental model framework can help address this research gap. The research documented in this paper focuses on analyzing data from an informational questionnaire that is part of a larger study to understand how the participants define assessments through methods inspired by mixed method strategies. These strategies include descriptive statistics on demographic findings and Natural Language Processing (NLP) and coding on the open-ended response question asking the participants to define assessments, which yielded cluster themes that characterize the definitions. Findings show that while many participants defined assessments in relation to measuring student learning, other substantial aspects include benchmarking, assessing student ability and competence, and formal evaluation for quality. These findings serve as foundational knowledge toward deeper exploration and understanding of assessment mental models of engineering faculty that can begin to address the aforementioned research gap on faculty assessment decisions in classrooms. 

The Dark Energy Spectroscopic Instrument, consisting of 5020 robotic fiber positioners and associated systems on the Mayall telescope at Kitt Peak, Arizona, is carrying out a survey to measure the spectra of 40 million galaxies and quasars and produce the largest 3D map of the universe to date. The primary science goal is to use baryon acoustic oscillations to measure the expansion history of the universe and the time evolution of dark energy. A key function of the online control system is to position each fiber on a particular target in the focal plane with an accuracy of 11μm rms 2D. This paper describes the set of software programs used to perform this function along with the methods used to validate their performance.

 

Abstract Each year, hundreds of international researchers enter Greenland to conduct scientific fieldwork. Historically, they have had little interaction with local communities and scientists at Greenland research institutes. Recognising that collaboration between Greenland and the United States can yield better research, consider more diverse perspectives, articulate the benefits of research to Greenland society, and train the next generation in a collaborative framework, representatives from both countries have been engaged in a series of events to cultivate bilateral relationships. Here, we describe the process of these events (workshops, conference sessions, and public dialogues), the findings, and the outcomes that have followed. Prior to this focused engagement, United States and Greenland scientists typically pursued their research independently. Since the engagement, more researchers from both countries have successfully partnered to obtain funding for collaborative research. Furthermore, development of a bilateral collaboration network is underway. The focused approach on bilateral engagement also proved essential for maintaining research and other activities during the global pandemic. When United States researchers were prevented from entering Greenland, their Greenland partners were able to continue the fieldwork, ensuring that progress was not lost. Future international projects can build on these successes to expand collaborative and interdisciplinary research in Greenland. 

Abstract. Since the 1960s, a deep groundwater system in Wright Valley, Antarctica, has been the hypothesized source of brines to hypersaline Don Juan Pond and Lake Vanda, both of which are rich in calcium and chloride. Modeling studies do not support other possible mechanisms, such as evaporative processes, that could have led to the current suite of ions present in both waterbodies. In 2011 and 2018, an airborne electromagnetic survey was flown over Wright Valley to map subsurface resistivity (down to 600 m) in exploration of liquid water. The surveys revealed widespread unfrozen brine in the subsurface near Lake Vanda, Don Juan Pond, and the North Fork of Wright Valley. While our geophysical survey can neither confirm nor deny deep groundwater connectivity between Lake Vanda and Don Juan Pond, it does point to the potential for deep valley-wide brine, likely within the Ferrar Dolerite formation.