Geometric Deep Learning for Autonomous Driving: Unlocking the Power of Graph Neural Networks With CommonRoad-Geometric

Heterogeneous graphs offer powerful data representations for traffic, given their ability to model the complex interaction effects among a varying number of traffic participants and the underlying road infrastructure. With the recent advent of graph neural networks (GNNs) as the accompanying deep learning framework, the graph structure can be efficiently leveraged for various machine learning applications such as trajectory prediction. As a first of its kind, our proposed Python framework offers an easy-to-use and fully customizable data processing pipeline to extract standardized graph datasets from traffic scenarios. Providing a platform for GNN-based autonomous driving research, it improves comparability between approaches and allows researchers to focus on model implementation instead of dataset curation.Comment: Presented at IV 202

DAMPs and radiation injury

The heightened risk of ionizing radiation exposure, stemming from radiation accidents and potential acts of terrorism, has spurred growing interests in devising effective countermeasures against radiation injury. High-dose ionizing radiation exposure triggers acute radiation syndrome (ARS), manifesting as hematopoietic, gastrointestinal, and neurovascular ARS. Hematopoietic ARS typically presents with neutropenia and thrombocytopenia, while gastrointestinal ARS results in intestinal mucosal injury, often culminating in lethal sepsis and gastrointestinal bleeding. This deleterious impact can be attributed to radiation-induced DNA damage and oxidative stress, leading to various forms of cell death, such as apoptosis, necrosis and ferroptosis. Damage-associated molecular patterns (DAMPs) are intrinsic molecules released by cells undergoing injury or in the process of dying, either through passive or active pathways. These molecules then interact with pattern recognition receptors, triggering inflammatory responses. Such a cascade of events ultimately results in further tissue and organ damage, contributing to the elevated mortality rate. Notably, infection and sepsis often develop in ARS cases, further increasing the release of DAMPs. Given that lethal sepsis stands as a major contributor to the mortality in ARS, DAMPs hold the potential to function as mediators, exacerbating radiation-induced organ injury and consequently worsening overall survival. This review describes the intricate mechanisms underlying radiation-induced release of DAMPs. Furthermore, it discusses the detrimental effects of DAMPs on the immune system and explores potential DAMP-targeting therapeutic strategies to alleviate radiation-induced injury

Radiation upregulates macrophage TREM-1 expression to exacerbate injury in mice

IntroductionExposure to high-dose ionizing radiation causes tissue injury, infections and even death due to immune dysfunction. The triggering receptor expressed on myeloid cells-1 (TREM-1) has been demonstrated to critically amplify and dysregulate immune responses. However, the role of TREM-1 in radiation injury remains unknown. Extracellular cold-inducible RNA-binding protein (eCIRP), a new damage-associated molecular pattern, is released from activated or stressed cells during inflammation. We hypothesized that ionizing radiation upregulates TREM-1 expression via eCIRP release to worsen survivalMethodsRAW264.7 cells and peritoneal macrophages collected from C57BL/6 wild-type (WT) mice were exposed to 5- and 10-Gray (Gy) radiation. C57BL/6 WT and CIRP-/- mice underwent 10-Gy total body irradiation (TBI). TREM-1 expression on RAW264.7 cells and peritoneal macrophages in vitro and in vivo were evaluated by flow cytometry. eCIRP levels in cell culture supernatants and in peritoneal lavage isolated from irradiated mice were evaluated by Western blotting. We also evaluated 30-day survival in C57BL/6 WT, CIRP-/- and TREM-1-/- mice after 6.5-Gy TBI.ResultsThe surface protein and mRNA levels of TREM-1 in RAW264.7 cells were significantly increased at 24 h after 5- and 10-Gy radiation exposure. TREM-1 expression on peritoneal macrophages was significantly increased after radiation exposure in vitro and in vivo. eCIRP levels were significantly increased after radiation exposure in cell culture supernatants of peritoneal macrophages in vitro and in peritoneal lavage in vivo. Moreover, CIRP-/- mice exhibited increased survival after 6.5-Gy TBI compared to WT mice. Interestingly, TREM-1 expression on peritoneal macrophages in CIRP-/- mice was significantly decreased compared to that in WT mice at 24 h after 10-Gy TBI. Furthermore, 30-day survival in TREM-1-/- mice was significantly increased to 64% compared to 20% in WT mice after 6.5-Gy TBI.ConclusionOur data indicate that ionizing radiation increases TREM-1 expression in macrophages via the release of eCIRP, and TREM-1 contributes to worse survival after total body irradiation. Thus, targeting TREM-1 could have the potential to be developed as a novel medical countermeasure for radiation injury

Five-year follow up of genotypic resistance patterns in HIV-1 subtype C infected patients in Botswana after failure of thymidine analogue-based regimens

Objective: Our objective was to establish genotypic resistance profiles among the 4% of Batswana patients who experienced virologic failure while being followed within Botswana's National Antiretroviral Treatment Program between 2002 and 2007. Methods: At the beginning of the national program in 2002, almost all patients received stavudine (d4T), together with didanosine (ddI), as part of their first nucleoside reverse transcriptase inhibitor (NRTI)-based regimen (Group 1). In contrast, the standard of care for all patients subsequently enrolled (2002-2007) included zidovudine/lamivudine (ZDV/3TC) (Group 2). Genotypes were analyzed in 26 patients from Group 1 and 37 patients from Group 2. Associations between mutations were determined using Pearson's correlation coefficient and Jaccard's coefficient of similarity. Results: Seventy-eight percent of genotyped patients possessed mutations associated with protease inhibitor (PI) resistance while 87% and 90%, respectively, exhibited mutations associated with NRTIs and non-nucleoside reverse transcriptase inhibitors (NNRTIs). The most frequent PI mutations involving resistance to NFV were L90M (25.2%) and D30N (16.2%), but mutations at positions K45Q and D30N were often observed in tandem (P = 60.5, J = 50; p = 0.002; Group 2) alongside Q61E in 42.8% of patients who received ZDV/3TC. Both major patterns of thymidine analogue mutations, TAM 1 (48%) and TAM 2 (59%), were represented in patients from Group 1 and 2, although M184V was higher among individuals who had initially received ddI (61% versus 40.5%). In contrast, L74V was more frequent among individuals from Group 2 (16.2% versus 7.7%). Differences in regard to NNRTI mutations were also observed between Group 1 and Group 2 patients. Conclusion: Despite a low rate of therapeutic failure (4%) among these patients, those who failed possessed high numbers of resistance mutations as well as novel resistance mutations and/or polymorphisms at sites within reverse transcriptase and protease

The JWST Resolved Stellar Populations Early Release Science Program I.: NIRCam Flux Calibration

We use globular cluster data from the Resolved Stellar Populations Early Release Science (ERS) program to validate the flux calibration for the Near Infrared Camera (NIRCam) on the James Webb Space Telescope (JWST). We find a significant flux offset between the eight short wavelength detectors, ranging from 1-23% (about 0.01-0.2 mag) that affects all NIRCam imaging observations. We deliver improved zeropoints for the ERS filters and show that alternate zeropoints derived by the community also improve the calibration significantly. We also find that the detector offsets appear to be time variable by up to at least 0.1 mag.Comment: Accepted for publication in RNAA

Magnetoluminescence

Pulsar Wind Nebulae, Blazars, Gamma Ray Bursts and Magnetars all contain regions where the electromagnetic energy density greatly exceeds the plasma energy density. These sources exhibit dramatic flaring activity where the electromagnetic energy distributed over large volumes, appears to be converted efficiently into high energy particles and gamma-rays. We call this general process magnetoluminescence. Global requirements on the underlying, extreme particle acceleration processes are described and the likely importance of relativistic beaming in enhancing the observed radiation from a flare is emphasized. Recent research on fluid descriptions of unstable electromagnetic configurations are summarized and progress on the associated kinetic simulations that are needed to account for the acceleration and radiation is discussed. Future observational, simulation and experimental opportunities are briefly summarized.Comment: To appear in "Jets and Winds in Pulsar Wind Nebulae, Gamma-ray Bursts and Blazars: Physics of Extreme Energy Release" of the Space Science Reviews serie

Beyond tissueInfo: functional prediction using tissue expression profile similarity searches

We present and validate tissue expression profile similarity searches (TEPSS), a computational approach to identify transcripts that share similar tissue expression profiles to one or more transcripts in a group of interest. We evaluated TEPSS for its ability to discriminate between pairs of transcripts coding for interacting proteins and non-interacting pairs. We found that ordering protein–protein pairs by TEPSS score produces sets significantly enriched in reported pairs of interacting proteins [interacting versus non-interacting pairs, Odds-ratio (OR) = 157.57, 95% confidence interval (CI) (36.81–375.51) at 1% coverage, employing a large dataset of about 50 000 human protein interactions]. When used with multiple transcripts as input, we find that TEPSS can predict non-obvious members of the cytosolic ribosome. We used TEPSS to predict S-nitrosylation (SNO) protein targets from a set of brain proteins that undergo SNO upon exposure to physiological levels of S-nitrosoglutathione in vitro. While some of the top TEPSS predictions have been validated independently, several of the strongest SNO TEPSS predictions await experimental validation. Our data indicate that TEPSS is an effective and flexible approach to functional prediction. Since the approach does not use sequence similarity, we expect that TEPSS will be useful for various gene discovery applications. TEPSS programs and data are distributed at http://icb.med.cornell.edu/crt/tepss/index.xml