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Following Donald Trump’s surprising victory in the 2016 US presidential election, some popular and scholarly sources suggested that Trump’s candidacy may have been bolstered, in part, by the mobilization of “politically alienated” voters. This argument is puzzling, however, as certain forms of political alienation are often negatively related to political participation, making it unclear whether or how alienation may have been related to turnout and to support for Trump at the ballot box. I shed light on this puzzle using data from the American National Election Studies, which contain measures of two dimensions of political alienation: inefficacy and cynicism. With these data I examine how either dimension relates to turnout and to vote choice in 2016 and in 2020. Cynicism emerges as a positive predictor of both turnout and the Trump vote in 2016, but not in 2020. Inefficacy, however, does not positively predict turnout or the Trump vote in either election. I offer a potential explanation for the diminished relationship between cynicism and mobilization in the 2020 elections by applying a Structural Topic Model to open-ended survey responses about Trump, which reveals a substantial decrease in the salience of Trump’s “political outsider” qualities during his reelection bid.

Every animal secretes mucus, placing them among the most diverse biological materials. Mucus hydrogels are complex mixtures of water, ions, carbohydrates, and proteins. Uncertainty surrounding their composition and how interactions between components contribute to mucus function complicates efforts to exploit their properties. There is substantial interest in commercializing mucus from the garden snail,Cornu aspersum, for skincare, drug delivery, tissue engineering, and composite materials.C. aspersumsecretes three mucus—one shielding the animal from environmental threats, one adhesive mucus from the pedal surface of the foot, and another pedal mucus that is lubricating. It remains a mystery how compositional differences account for their substantially different properties. Here, we characterize mucus proteins, glycosylation, ion content, and mechanical properties that could be used to provide insight into structure-function relationships through an integrative “mucomics” approach. We identify macromolecular components of these hydrogels, including a previously unreported protein class termed Conserved Anterior Mollusk Proteins (CAMPs). Revealing differences betweenC. aspersummucus shows how considering structure at all levels can inform the design of mucus-inspired materials.

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.

Abstract. We present the Fire Inventory from National Center for Atmospheric Research (NCAR) version 2.5 (FINNv2.5), a fire emissions inventory that provides publicly available emissions of trace gases and aerosols for various applications, including use in global and regional atmospheric chemistry modeling. FINNv2.5 includes numerous updates to the FINN version 1 framework to better represent burned area, vegetation burned, and chemicals emitted. Major changes include the use of active fire detections from the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375 m spatial resolution, which allows smaller fires to be included in the emissions processing. The calculation of burned area has been updated such that a more rigorous approach is used to aggregate fire detections, which better accounts for larger fires and enables using multiple satellite products simultaneously for emissions estimates. Fuel characterization and emissions factors have also been updated in FINNv2.5. Daily fire emissions for many trace gases and aerosols are determined for 2002–2019 (Moderate Resolution Imaging Spectroradiometer (MODIS)-only fire detections) and 2012–2019 (MODIS + VIIRS fire detections). The non-methane organic gas emissions are allocated to the species of several commonly used chemical mechanisms. We compare FINNv2.5 emissions against other widely used fire emissions inventories. The performance of FINNv2.5 emissions as inputs to a chemical transport model is assessed with satellite observations. Uncertainties in the emissions estimates remain, particularly in Africa and South America during August–October and in southeast and equatorial Asia in March and April. Recommendations for future evaluation and use are given.

The mechanism of action of deep brain stimulation (DBS) to the basal ganglia for Parkinson’s disease remains unclear. Studies have shown that DBS decreases pathological beta hypersynchrony between the basal ganglia and motor cortex. However, little is known about DBS’s effects on long range corticocortical synchronization. Here, we use machine learning combined with graph theory to compare resting-state cortical connectivity between the off and on-stimulation states and to healthy controls. We found that turning DBS on increased high beta and gamma band synchrony (26 to 50 Hz) in a cortical circuit spanning the motor, occipitoparietal, middle temporal, and prefrontal cortices. The synchrony in this network was greater in DBS on relative to both DBS off and controls, with no significant difference between DBS off and controls. Turning DBS on also increased network efficiency and strength and subnetwork modularity relative to both DBS off and controls in the beta and gamma band. Thus, unlike DBS’s subcortical normalization of pathological basal ganglia activity, it introduces greater synchrony relative to healthy controls in cortical circuitry that includes both motor and non-motor systems. This increased high beta/gamma synchronization may reflect compensatory mechanisms related to DBS’s clinical benefits, as well as undesirable non-motor side effects.

Mono- and bi-allelic variants in ALDH18A1 cause a spectrum of human disorders associated with cutaneous and neurological findings that overlap with both cutis laxa and spastic paraplegia. ALDH18A1 encodes the bifunctional enzyme pyrroline-5-carboxylate synthetase (P5CS) that plays a role in the de novo biosynthesis of proline and ornithine. Here we characterize a previously unreported homozygous ALDH18A1 variant (p.Thr331Pro) in four affected probands from two unrelated families, and demonstrate broad-based alterations in amino acid and antioxidant metabolism. These four patients exhibit variable developmental delay, neurological deficits and loose skin. Functional characterization of the p.Thr331Pro variant demonstrated a lack of any impact on the steady-state level of the P5CS monomer or mitochondrial localization of the enzyme, but reduced incorporation of the monomer into P5CS oligomers. Using an unlabeled NMR-based metabolomics approach in patient fibroblasts and ALDH18A1-null human embryonic kidney cells expressing the variant P5CS, we identified reduced abundance of glutamate and several metabolites derived from glutamate, including proline and glutathione. Biosynthesis of the polyamine putrescine, derived from ornithine, was also decreased in patient fibroblasts, highlighting the functional consequence on another metabolic pathway involved in antioxidant responses in the cell. RNA sequencing of patient fibroblasts revealed transcript abundance changes in several metabolic and extracellular matrix-related genes, adding further insight into pathogenic processes associated with impaired P5CS function. Together these findings shed new light on amino acid and antioxidant pathways associated with ALDH18A1-related disorders, and underscore the value of metabolomic and transcriptomic profiling to discover new pathways that impact disease pathogenesis.