Pittsburgh Supercomputing Center

Abstract Description Regulatory CD8 T cells (8Tregs) were first described two decades ago, as a counterpart to regulatory CD4 T cells. Since then, multiple groups have published on 8Tregs that can suppress an overexuberant immune response and ultimately prevent autoimmunity during inflammation. The consensus is that 8Tregs have a memory phenotype (“MP”, CD44hi CD122+) in unimmunized mice and express one or both markers: Ly49, an NK receptor, and Helios, a transcription factor. However, important questions remain unanswered regarding the definitive markers, specificity, and functional mechanism of these 8Tregs. To address these questions, we performed single-cell RNA sequencing on Ly49+ or Helios+ cells, revealing multiple subsets, and indicating that true 8Tregs may be within the Ly49+/Helios+ subpopulation. We also conducted TCR repertoire analysis on cells from mice with a fixed TCRβ chain. These studies showed that Helios+ and Ly49+Helios+ populations have an overlapping repertoire which is distinct from the “conventional” MP population. Interestingly, TCRs enriched in Helios+ MP CD8 T cells were previously defined as being prominent among prostate tumor-infiltrating lymphocytes (TRAMP TILs) in the same fixed TCRβ transgenic model. These results lead us to speculate that the TCR specificity drives the phenotype of these cells and raise the possibility that TCRs from 8Tregs recognize self-antigens expressed in tumors. Funding Sources Supported by NIH AI38903 Topic Categories Lymphocyte Differentiation and Peripheral Maintenance (LYM)

Abstract Description KLRG1+ long-lived effector cells (LLECs), are CD8 T cells that persist in the blood and spleen for months and contribute robust protective immunity against systemic infection. We asked whether LLEC (or their progeny) ever leave the blood stream to combat tissue-restricted infections like influenza, and whether they could generate resident memory T cells (TRM). We found that effector cells derived from LLECs rapidly enter nonlymphoid tissues and reduce pathogen burden but show dependence on antigen presentation by vascular endothelial cells. Flow cytometry and single-cell RNA sequencing revealed that secondary memory cells arising from any memory precursor develop a similar resident memory phenotype and transcriptional signature. These data lead us to conclude that despite other limits on their differentiation, LLECs retain the ability to enter non-lymphoid tissues and establish residency. In specific pathogen free mice exposed to a single acute infection, LLECs tend to fade over time. However, in mice which are first exposed to natural commensals and pathogens through cohousing with pet store mice, LLECs dominate the memory CD8 T cell pool. We find that increased production of short-lived effector cells followed by a diminished contraction phase improves formation of LLEC. Current work tests whether noncanonical cytokines or conversion from other memory subsets supports LLEC in cohoused mice, potentially revealing new strategies for memory T cell persistence. Funding Sources This work was supported by NIH/NIAID: R01AI155468 and F32AI178962 Topic Categories Lymphocyte Differentiation and Peripheral Maintenance (LYM)

We present the first characterization of the statistical relationship between a large sample of novae in M31 and their progenitor stellar populations in the form of a delay time distribution. To this end, we leverage the spatially resolved stellar age distribution of the M31 disk derived from deep Hubble Space Telescope photometry by the Panchromatic Hubble Andromeda Treasury survey and a large catalog of novae in M31. Our delay time distribution has two statistically significant detections: one population of nova progenitors with ages between 2 and 3.2 Gyr and an unnormalized rate of ( events M ⊙ -1, and another of ages between 7.9 Gyr and the age of the Universe with ( events M ⊙ -1 (uncertainties are statistical and systematic, respectively). Together with the upper limits we derive at other time bins, these detections are consistent with either a constant production efficiency or a higher production efficiency of novae at earlier delay times.

Earthquakes pose a significant threat worldwide, requiring rapid and accurate damage assessments to guide emergency response efforts. While empirical ground motion models are commonly used for their speed and simplicity, they often fail to account for critical factors such as site effects and the spatial variability of ground shaking. Physics-based ground shaking simulations can provide a more accurate alternative by modelling fault rupture, wave propagation and local site effects. However, their application in the near real-time has been limited due to computational complexity and long processing times. To overcome these limitations, we have developed UrgentShake, an HPC-based system designed to generate physics-based ground shaking scenarios under strict time constraints. A key focus of UrgentShake is the implementation of efficient strategies to reduce the computational time required to produce reliable solutions without compromising accuracy. Preliminary evaluations on two reference seismic events demonstrate UrgentShake's capability to significantly reduce time-to-solution, ensuring its potential to meet the critical timing demands of seismic emergency responses.

Context. Massive stars rotate faster, on average, than lower mass stars. Stellar rotation triggers hydrodynamical instabilities which transport angular momentum and chemical species from the core to the surface. Models of high-mass stars that include these processes predict that chemical mixing is stronger at lower metallicity. Aims. We aim to test this prediction by comparing the surface abundances of massive stars at different metallicities. Methods. We performed a spectroscopic analysis of single O stars in the Magellanic Clouds (MCs) based on the ULLYSES and XShootU surveys. We determined the fundamental parameters and helium, carbon, nitrogen, and oxygen surface abundances of 17 LMC and 17 SMC non-supergiant O6–9.5 stars. We complemented these determinations by literature results for additional MCs and also Galactic stars to increase the sample size and metallicity coverage. We investigated the differences in the surface chemical enrichment at different metallicities and compared them with predictions of three sets of evolutionary models. Results. Surface abundances are consistent with CNO-cycle nucleosynthesis. The maximum surface nitrogen enrichment is stronger in MC stars than in Galactic stars. Nitrogen enrichment is also observed in stars with higher surface gravities in the SMC than in the Galaxy. This trend is predicted by models that incorporate chemical transport caused by stellar rotation. The distributions of projected rotational velocities in our samples are likely biased towards slow rotators. Conclusions. A metallicity dependence of surface abundances is demonstrated. The analysis of larger samples with an unbiased distribution of projected rotational velocities is required to better constrain the treatment of chemical mixing and angular momentum transport in massive single and binary stars.

Predicting the properties of molecular crystals is imperative to the field of materials design. In lieu of alternative methods, advances in machine learning have made it possible to predict the properties of materials before synthesis. This is especially important for organic semiconductors (OSCs) that are prone to exhibit polymorphism, as this phenomenom can impact the properties of a system, including the bandgap in OSCs. While graph neural networks (GNNs) have shown promise in predicting the bandgap in OSCs, few studies have considered the impact of polymorphism on their performance. Using the MatDeepLearn framework, we examine five different graph convolution layers of ALIGNN, GATGNN, CGCNN, MEGNet, and SchNet, which all have graph convolutions implemented in torch geometric. A dataset of functional organic molecular crystals is extracted from the OCELOT database, which has calculated density functional theory (DFT) values for the bandgap as well as several sets of polymorphs. The trained models are then evaluated on several test cases including the polymorphs of ROY. In future work we plan to examine the impact of graph representations on the performance of these models in the case of predicting properties of polymorphic OSCs.

Many smaller and under-resourced institutions, including MSIs, HSIs, HBCUs, and EPSCoR institutions, are engaged in significant science research and education and recognize the value of enhanced access to advanced computing resources. Collaborations, shared resources, and expertise from local, regional, and national levels can substantially support their internal efforts. The Ecosystem for Research Networking (ERN) Broadening the Reach (BTR) working group is actively learning from these institutions on how to better support their needs. The group’s findings and recommendations, derived from community engagement, will be shared, as part of the NSF-sponsored CC*CRIA grant OAC-2018927.

Allosteric cooperativity between ATP and substrates is a prominent characteristic of the cAMP-dependent catalytic subunit of protein kinase A (PKA). Not only this long-range synergistic action is involved in substrate recognition and fidelity, but it is also likely to regulate PKA association with regulatory subunits and other binding partners. To date, a complete understanding of the molecular determinants for this intramolecular mechanism is still lacking.Here, we integrated NMR-restrained molecular dynamics simulations and a Markov State Model to characterize the free energy landscape and conformational transitions of the catalytic subunit of protein kinase A (PKA-C). We found that the apoenzyme populates a broad free energy basin featuring a conformational ensemble of the active state of PKA-C (ground state) and other basins with lower populations (excited states). The first excited state corresponds to a previously characterized inactive state of PKA-C with the αC helix swinging outward. The second excited state displays a disrupted hydrophobic packing around the regulatory (R) spine, with a flipped configuration of the F100 and F102 residues at the αC-β4 loop. To experimentally validate the second excited state, we mutated F100 into alanine (F100A) and used NMR spectroscopy to characterize the structural response of the kinase to ATP and substrate binding. While the catalytic efficiency of PKA-CF100A with a canonical peptide substrate remains unaltered, this mutation rearranges the αC-β4 loop conformation, interrupting the structural coupling of the two lobes and abolishing the allosteric binding cooperativity of the enzyme. The highly conserved αC-β4 loop emerges as a pivotal element able to control the synergistic binding between nucleotide and substrate. These results may explain how mutations or insertions near or within this motif affect the function and drug sensitivity in other homologous kinases.