MET is a receptor tyrosine kinase (RTK) responsible for initiating signaling pathways involved in development and wound repair. MET activation relies on ligand binding to the extracellular receptor, which prompts dimerization, intracellular phosphorylation, and recruitment of associated signaling proteins. Mutations, which are predominantly observed clinically in the intracellular juxtamembrane and kinase domains, can disrupt typical MET regulatory mechanisms. Understanding how juxtamembrane variants, such as exon 14 skipping (METΔEx14), and rare kinase domain mutations can increase signaling, often leading to cancer, remains a challenge. Here, we perform a parallel deep mutational scan (DMS) of the MET intracellular kinase domain in two fusion protein backgrounds: wild type and METΔEx14. Our comparative approach has revealed a critical hydrophobic interaction between a juxtamembrane segment and the kinase ⍺C-helix, pointing to potential differences in regulatory mechanisms between MET and other RTKs. Additionally, we have uncovered a β5 motif that acts as a structural pivot for the kinase domain in MET and other TAM family of kinases. We also describe a number of previously unknown activating mutations, aiding the effort to annotate driver, passenger, and drug resistance mutations in the MET kinase domain.

Anthropogenic activities emit ~2000 Mg yr-1 of the toxic pollutant mercury (Hg) into the atmosphere, leading to long-range transport and deposition to remote ecosystems. Global anthropogenic emissions inventories report increases in Northern Hemispheric (NH) Hg emissions during the last three decades, in contradiction with the observed decline in atmospheric Hg concentrations at NH measurement stations. Many factors can obscure the link between anthropogenic emissions and atmospheric Hg concentrations, including trends in the re-emissions of previously released anthropogenic (“legacy”) Hg, atmospheric sink variability, and spatial heterogeneity of monitoring data. Here we assess the observed trends in gaseous elemental mercury (Hg0) in the NH and apply biogeochemical box modeling and chemical transport modeling to understand the trend drivers. Using linear mixed effects modeling of observational data from 51 stations, we find negative Hg0 trends in most NH regions, with an overall trend for 2005–2020 of ‑0.011 ± 0.006 ng m-3 yr-1 (±2 SD). In contrast to existing emission inventories, our modelling analysis suggests that NH anthropogenic emissions must have declined by at least 140 Mg yr-1 between the years 2005 and 2020 to be consistent with observed trends. Faster declines in 95th percentile Hg0 values than median values in Europe, North America, and East Asian measurement stations corroborate that the likely cause is a decline in nearby anthropogenic emissions rather than background legacy re-emissions. Our results are relevant for evaluating the effectiveness of the Minamata Convention on Mercury, demonstrating that existing emissions inventories are incompatible with the observed Hg0 declines. 

While most electricity systems are designed to handle peak demand during summer months, pathways to deep decarbonization generally electrify building heating, thus increasing electricity demand during winter. A key question is how climate variability and change will affect peak heating and cooling demand in an electrified future. We conduct a spatially explicit analysis of trends in temperature-based proxies of electricity demand over the past 70 years. Average annual demand for heating (cooling) decreases (increases) over most of the contiguous US. However, while climate change drives robust increases in peak cooling demand, trends in peak heating demand are generally smaller and less robust. Because the distribution of temperature exhibits a long left tail, severe cold snaps dominate the extremes of thermal demand. As building heating electrifies, system operators must account for these events to ensure reliability.

Aquaporin-0 (AQP0) tetramers form square arrays in lens membranes through a yet unknown mechanism, but lens membranes are enriched in sphingomyelin and cholesterol. Here, we determined electron crystallographic structures of AQP0 in sphingomyelin/cholesterol membranes and performed molecular dynamics (MD) simulations to establish that the observed cholesterol positions represent those seen around an isolated AQP0 tetramer and that the AQP0 tetramer largely defines the location and orientation of most of its associated cholesterol molecules. At a high concentration, cholesterol increases the hydrophobic thickness of the annular lipid shell around AQP0 tetramers, which may thus cluster to mitigate the resulting hydrophobic mismatch. Moreover, neighboring AQP0 tetramers sandwich a cholesterol deep in the center of the membrane. MD simulations show that the association of two AQP0 tetramers is necessary to maintain the deep cholesterol in its position and that the deep cholesterol increases the force required to laterally detach two AQP0 tetramers, not only due to protein–protein contacts but also due to increased lipid–protein complementarity. Since each tetramer interacts with four such ‘glue’ cholesterols, avidity effects may stabilize larger arrays. The principles proposed to drive AQP0 array formation could also underlie protein clustering in lipid rafts.

Understanding convective aggregation is very important for understanding tropical climate and climate sensitivity. However, we still lack a full understanding of how aggregation evolves in the real world or what phenomena and scales are analogous to the self-aggregation observed in idealized models. In this study, we apply the moist static energy (MSE) variance budget framework to ERA5 reanalysis data to study the evolution of large-scale aggregation over tropical oceans at basin wide scales. Our novel phase space diagnostics focuses on the variability of observed aggregation compared to most previous self-aggregation studies, which focus more on the aggregated mean state. We visualize observed aggregation to evolve anomalously around a mean state in a cyclical fashion forming aggregation - disaggregation cycles. We find horizontal advection of MSE to play the primary role in determining when the domain aggregates or disaggregates. In contrast, all advective, radiative and surface flux feedbacks are found important for determining the magnitude of the aggregation anomalies. Surface fluxes and horizontal advection tend to dampen aggregation anomalies, while radiative fluxes and vertical advection tend to amplify aggregation anomalies. Looking deeper into the advection terms, we find that changes in vertical advection are dominated by an enhanced low level subsidence over the dry regions during the more aggregated states. This creates an anomalous drying tendency over the dry regions, which maintains aggregation anomalies. In contrast, horizontal advection changes are found to be dominated by increased moisture advection out of the moist columns with stronger aggregation.

Geothermal heat flux beneath the Greenland and Antarctic ice sheets is an important boundary condition for ice sheet dynamics. Subglacial heat flux is rarely measured directly, so it has been inferred indirectly from proxies (e.g. seismic structure, magnetic Curie depth, surface topography). We seek to improve understanding of the relationship between heat flux and one such proxy---seismic structure---and determine how well heat flux data can be predicted from the structure (the \emph{characterization} problem). We also seek to quantify the extent to which this relationship can be transported from one continent to another (the \emph{transportability} problem). To address these problems, we use direct heat flux observations and new seismic structural information in the contiguous US and Europe, and construct three Machine Learning models of the relationship across a hierarchy of model complexity (Linear Regression, Decision Tree, Random Forest). The more complex models fit smaller scale variations in heat flux. We compare the models in terms of model interpretability, accuracy to predict heat flux, and transportability from one continent to another. To evaluate model accuracy, we divide data on the same continent into training and validation datasets, and then validate the model (trained from the training data) with validation data. We measure model transportability by cross-validating the US-trained models against European heat flux, and vice versa. We find that the Random Forest and Decision Tree models are the most accurate, while the Linear Regression and Decision Tree models are the most transportable. The Decision Tree model can uniquely illuminate the regional variations of the relationship between heat flux and seismic structure. From the Decision Tree model, uppermost mantle shear wavespeed, crustal shear wavespeed and Moho depth together explain about half of the observed heat flux variations in both the US ($r^2 \approx 0.6$ (coefficient of determination), $\mathrm{RMSE} \approx \hfu{8}$ (Root Mean Squared Error)) and Europe ($r^2 \approx 0.5, \mathrm{RMSE} \approx \hfu{13}$). Uppermost mantle wavespeed is a much stronger predictor than the other two variables combined. Transporting the US-trained models to Europe reveals that the geographical distribution of heat flux can be reasonably predicted ($\rho = 0.48$ (correlation coefficient)), but the absolute amplitude of the variations cannot ($r^2 = 0.17$), similarly from Europe to the US ($\rho = 0.66, r^2 = 0.24$). We attribute the transportability deterioration to differences between the continents in seismic structural imaging data and parameterization, and crustal radiogenic heat production. Despite these issues, our method has the potential to improve the reliability and resolution of heat flux inferences across Antarctica. Furthermore, our validation and cross-validation methods can be applied to heat flux proxies other than seismic structure, which may help resolve inconsistencies between existing subglacial heat flux inferences using different proxies.

Vascular smooth muscle cells (VSMCs) envelop vertebrate brain arteries, playing a crucial role in regulating cerebral blood flow and neurovascular coupling. The dedifferentiation of VSMCs is implicated in cerebrovascular diseases and neurodegeneration. Despite its importance, the process of VSMC differentiation on brain arteries during development remains inadequately characterized. Understanding this process could aid in reprogramming and regenerating differentiated VSMCs in cerebrovascular diseases. In this study, we investigated VSMC differentiation on the zebrafish circle of Willis (CoW), comprising major arteries that supply blood to the vertebrate brain. We observed that the arterial expression of CoW endothelial cells (ECs) occurs after their migration from the cranial venous plexus to form CoW arteries. Subsequently, acta2+ VSMCs differentiate from pdgfrb+ mural cell progenitors upon recruitment to CoW arteries. The progression of VSMC differentiation exhibits a spatiotemporal pattern, advancing from anterior to posterior CoW arteries. Analysis of blood flow suggests that earlier VSMC differentiation in anterior CoW arteries correlates with higher red blood cell velocity wall shear stress. Furthermore, pulsatile blood flow is required for differentiation of human brain pdgfrb+ mural cells into VSMCs as well as VSMC differentiation on zebrafish CoW arteries. Consistently, the flow-responsive transcription factor klf2a is activated in ECs of CoW arteries prior to VSMC differentiation, and klf2a knockdown delays VSMC differentiation on anterior CoW arteries. In summary, our findings highlight the role of blood flow activation of endothelial klf2a as a mechanism regulating the initial VSMC differentiation on vertebrate brain arteries.

The mechanisms whereby alkali feldspar megacrysts form have been debated for several decades; yet, we do not understand well the processes that lead to their formation. We take advantage of glacially polished outcrop surfaces from the Cathedral Peak Granodiorite in the Tuolumne Intrusive Complex, CA to quantitatively characterize alkali feldspar textures, to provide better insight into their origin. On the glacially polished surfaces, we trace alkali feldspar crystals >10 mm in the field. From the same localities, we also collect large slabs and stain them to reveal feldspar textures for crystals <20 mm in size. We scan the resulting field tracings and rock slabs to quantify CSDs using image processing techniques with the software ImageJ. The CSDs from glacially polished outcrop surfaces and complementary polished and stained rock slabs reveal two stages of crystallization. Crystals >20 mm show log-linear CSDs with shallow slopes, suggesting magmatic nucleation and growth on timescales of thousands of years. Crystals <20 mm define a second stage of crystallization, with much steeper slopes, suggesting a period of enhanced nucleation leading to formation of a groundmass during the final stages of solidification on timescales of decades to centuries. We do not find any evidence for CSDs affected by textural coarsening, or any effects of subsolidus processes. Our data suggest that these megacrysts form in large, slowly cooling magma, where low nucleation rates dominate. These crystals are not special in their magmatic formation – only in their size. A change in solidification conditions led to the formation of a groundmass, which warrants further study to better understand this crystallization stage in a plutonic environment.

Central noradrenergic (NA) neurons are key constituents of the respiratory homeostatic network. NA dysfunction is implicated in several developmental respiratory disorders including Congenital Central Hyperventilation Syndrome (CCHS), Sudden Infant Death Syndrome (SIDS) and Rett Syndrome. The current unchallenged paradigm in the field, supported by multiple studies, is that glutamate co-transmission in subsets of central NA neurons plays a role in breathing control. If true, NA-glutamate co-transmission may also be mechanistically important in respiratory disorders. However, the requirement of NA-derived glutamate in breathing has not been directly tested and the extent of glutamate co-transmission in the central NA system remains uncharacterized. Therefore, we fully characterized the cumulative fate maps and acute adult expression patterns of all three Vesicular Glutamate Transporters ( Slc17a7 (Vglut1), Slc17a6 (Vglut2), and Slc17a8 (Vglut3)) in NA neurons, identifying a novel, dynamic expression pattern for Vglut2 and an undescribed co-expression domain for Vglut3 in the NA system. In contrast to our initial hypothesis that NA derived glutamate is required to breathing, our functional studies showed that loss of Vglut2 throughout the NA system failed to alter breathing or metabolism under room air, hypercapnia, or hypoxia in unrestrained and unanesthetized mice. These data demonstrate that Vglut2-based glutamatergic signaling within the central NA system is not required for normal baseline breathing and hypercapnic, hypoxic chemosensory reflexes. These outcomes challenge the current understanding of central NA neurons in the control of breathing and suggests that glutamate may not be a critical target to understand NA neuron dysfunction in respiratory diseases.

Chronic high-fat feeding triggers chronic metabolic dysfunction including obesity, insulin resistance, and diabetes. How high-fat intake first triggers these pathophysiological states remains unknown. Here, we identify an acute microglial metabolic response that rapidly translates intake of high-fat diet (HFD) to a surprisingly beneficial effect on metabolism and spatial / learning memory. High-fat intake rapidly increases palmitate levels in cerebrospinal fluid and triggers a wave of microglial metabolic activation characterized by mitochondrial membrane activation and fission as well as metabolic skewing towards aerobic glycolysis. These effects are detectable throughout the brain and can be detected within as little as 12 hours of HFD exposure. In vivo, microglial ablation and conditional DRP1 deletion show that the microglial metabolic response is necessary for the acute effects of HFD. 13 C-tracing experiments reveal that in addition to processing via β-oxidation, microglia shunt a substantial fraction of palmitate towards anaplerosis and re-release of bioenergetic carbons into the extracellular milieu in the form of lactate, glutamate, succinate, and intriguingly, the neuro-protective metabolite itaconate. Together, these data identify microglia as a critical nutrient regulatory node in the brain, metabolizing away harmful fatty acids and releasing the same carbons as alternate bioenergetic and protective substrates for surrounding cells. The data identify a surprisingly beneficial effect of short-term HFD on learning and memory.