Graph-Based Interaction-Aware Multimodal 2D Vehicle Trajectory Prediction using Diffusion Graph Convolutional Networks

Predicting vehicle trajectories is crucial for ensuring automated vehicle operation efficiency and safety, particularly on congested multi-lane highways. In such dynamic environments, a vehicle's motion is determined by its historical behaviors as well as interactions with surrounding vehicles. These intricate interactions arise from unpredictable motion patterns, leading to a wide range of driving behaviors that warrant in-depth investigation. This study presents the Graph-based Interaction-aware Multi-modal Trajectory Prediction (GIMTP) framework, designed to probabilistically predict future vehicle trajectories by effectively capturing these interactions. Within this framework, vehicles' motions are conceptualized as nodes in a time-varying graph, and the traffic interactions are represented by a dynamic adjacency matrix. To holistically capture both spatial and temporal dependencies embedded in this dynamic adjacency matrix, the methodology incorporates the Diffusion Graph Convolutional Network (DGCN), thereby providing a graph embedding of both historical states and future states. Furthermore, we employ a driving intention-specific feature fusion, enabling the adaptive integration of historical and future embeddings for enhanced intention recognition and trajectory prediction. This model gives two-dimensional predictions for each mode of longitudinal and lateral driving behaviors and offers probabilistic future paths with corresponding probabilities, addressing the challenges of complex vehicle interactions and multi-modality of driving behaviors. Validation using real-world trajectory datasets demonstrates the efficiency and potential

Additional file 1 of Chimeric antigen receptor T-cell therapy for relapsed and refractory thyroid cancer

Additional file 1: Detailed methods and result

DataSheet_4_Nasal and cutaneous mucormycosis in two patients with lymphoma after chemotherapy and target therapy: Early detection by metagenomic next-generation sequencing.xlsx

Mucormycosis is a conditionally pathogenic fungal disease with high morbidity that mainly affects patients with decreased immunity. Diagnosis relies on the histopathological examination of microorganisms with the typical structure of mucormycetes in tissues and subsequent confirmation via culture. Early detection of causative microorganisms is critical to rapidly administer appropriately targeted antibiotics. Metagenomic next-generation sequencing (mNGS) is an innovative and sensitive technique used to identify pathogenic strains. Here we used mNGS to timely diagnose an infection with Lichtheimia ramosa and Mucor irregularis in two patients with hematologic malignancies; the infections manifested as nasal and cutaneous infections and developed after chemotherapy and small molecule targeted therapy. Following treatment with amphotericin B cholesteryl sulfate complex, the symptoms were reduced significantly, and both patients obtained successful outcomes. Additionally, we searched and summarized the current medical literature on the successful diagnosis of mucormycosis using mNGS. These cases indicated that mNGS, a novel culture-independent method, is capable of rapid, sensitive, and accurate identification of pathogens. mNGS may be a complementary method for the early identification of mucormycosis, allowing for appropriate and timely antibiotic administration and thus improving patient outcomes.</p

DataSheet_1_Nasal and cutaneous mucormycosis in two patients with lymphoma after chemotherapy and target therapy: Early detection by metagenomic next-generation sequencing.xls

Mucormycosis is a conditionally pathogenic fungal disease with high morbidity that mainly affects patients with decreased immunity. Diagnosis relies on the histopathological examination of microorganisms with the typical structure of mucormycetes in tissues and subsequent confirmation via culture. Early detection of causative microorganisms is critical to rapidly administer appropriately targeted antibiotics. Metagenomic next-generation sequencing (mNGS) is an innovative and sensitive technique used to identify pathogenic strains. Here we used mNGS to timely diagnose an infection with Lichtheimia ramosa and Mucor irregularis in two patients with hematologic malignancies; the infections manifested as nasal and cutaneous infections and developed after chemotherapy and small molecule targeted therapy. Following treatment with amphotericin B cholesteryl sulfate complex, the symptoms were reduced significantly, and both patients obtained successful outcomes. Additionally, we searched and summarized the current medical literature on the successful diagnosis of mucormycosis using mNGS. These cases indicated that mNGS, a novel culture-independent method, is capable of rapid, sensitive, and accurate identification of pathogens. mNGS may be a complementary method for the early identification of mucormycosis, allowing for appropriate and timely antibiotic administration and thus improving patient outcomes.</p

DataSheet_2_Nasal and cutaneous mucormycosis in two patients with lymphoma after chemotherapy and target therapy: Early detection by metagenomic next-generation sequencing.xls

Mucormycosis is a conditionally pathogenic fungal disease with high morbidity that mainly affects patients with decreased immunity. Diagnosis relies on the histopathological examination of microorganisms with the typical structure of mucormycetes in tissues and subsequent confirmation via culture. Early detection of causative microorganisms is critical to rapidly administer appropriately targeted antibiotics. Metagenomic next-generation sequencing (mNGS) is an innovative and sensitive technique used to identify pathogenic strains. Here we used mNGS to timely diagnose an infection with Lichtheimia ramosa and Mucor irregularis in two patients with hematologic malignancies; the infections manifested as nasal and cutaneous infections and developed after chemotherapy and small molecule targeted therapy. Following treatment with amphotericin B cholesteryl sulfate complex, the symptoms were reduced significantly, and both patients obtained successful outcomes. Additionally, we searched and summarized the current medical literature on the successful diagnosis of mucormycosis using mNGS. These cases indicated that mNGS, a novel culture-independent method, is capable of rapid, sensitive, and accurate identification of pathogens. mNGS may be a complementary method for the early identification of mucormycosis, allowing for appropriate and timely antibiotic administration and thus improving patient outcomes.</p

DataSheet_3_Nasal and cutaneous mucormycosis in two patients with lymphoma after chemotherapy and target therapy: Early detection by metagenomic next-generation sequencing.xlsx

Mucormycosis is a conditionally pathogenic fungal disease with high morbidity that mainly affects patients with decreased immunity. Diagnosis relies on the histopathological examination of microorganisms with the typical structure of mucormycetes in tissues and subsequent confirmation via culture. Early detection of causative microorganisms is critical to rapidly administer appropriately targeted antibiotics. Metagenomic next-generation sequencing (mNGS) is an innovative and sensitive technique used to identify pathogenic strains. Here we used mNGS to timely diagnose an infection with Lichtheimia ramosa and Mucor irregularis in two patients with hematologic malignancies; the infections manifested as nasal and cutaneous infections and developed after chemotherapy and small molecule targeted therapy. Following treatment with amphotericin B cholesteryl sulfate complex, the symptoms were reduced significantly, and both patients obtained successful outcomes. Additionally, we searched and summarized the current medical literature on the successful diagnosis of mucormycosis using mNGS. These cases indicated that mNGS, a novel culture-independent method, is capable of rapid, sensitive, and accurate identification of pathogens. mNGS may be a complementary method for the early identification of mucormycosis, allowing for appropriate and timely antibiotic administration and thus improving patient outcomes.</p