GigaGen (United States)

Closed-loop simulation is essential for advancing end-to-end autonomous driving systems. Contemporary sensor simulation methods, such as NeRF and 3DGS, rely predominantly on conditions closely aligned with training data distributions, which are largely confined to forward-driving scenarios. Consequently, these methods face limitations when rendering complex maneuvers (e.g., lane change, acceleration, deceleration). Recent advancements in autonomous-driving world models have demonstrated the potential to generate diverse driving videos. However, these approaches remain constrained to 2D video generation, inherently lacking the spatiotemporal coherence required to capture intricacies of dynamic driving environments. In this paper, we introduce DriveDreamer4D, which enhances 4D driving scene representation leveraging world model priors. Specifically, we utilize the world model as a data machine to synthesize novel trajectory videos, where structured conditions are explicitly leveraged to control the spatial-temporal consistency of traffic elements. Besides, the cousin data training strategy is proposed to facilitate merging real and synthetic data for optimizing 4DGS. To our knowledge, DriveDreamer4D is the first to utilize video generation models for improving 4D reconstruction in driving scenarios. Experimental results reveal that DriveDreamer4D significantly enhances generation quality under novel trajectory views, achieving a relative improvement in FID by 32.1%, 46.4%, and 16.3% compared to PVG, S<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup>Gaussian, and Deformable-GS. Moreover, DriveDreamer4D markedly enhances the spatiotemporal coherence of driving agents, which is verified by a comprehensive user study and the relative increases of 22.6%, 43.5%, and 15.6% in the NTA-IoU metric.

Evaluating the effectiveness of Chagas disease treatment poses challenges due to the lack of biomarkers for disease progression and therapeutic response. In this study, we aimed to assess the clearance of Trypanosoma cruzi (T. cruzi) parasites in a group of benznidazole (BNZ)-treated chronic Chagas disease patients using high-sensitivity quantitative PCR (qPCR) and track T. cruzi antibody levels through a semiquantitative chemiluminescent assay. A total of 102 T. cruzi seropositive patients with previous PCR-positive results were enrolled in the study. We collected samples 30 days before treatment (T-30d), on the day before initiating BNZ treatment (T0d), and at follow-up visits 60 days (T60d), 6 months (T6M), 12 months (T12M), and 36 months (T36M) after treatment initiation. Treatment efficacy was assessed by testing of serial samples using a target-capture qPCR assay specific to satellite T. cruzi DNA and the ORTHO T. cruzi ELISA Test System for antibody quantitation. Of the enrolled individuals, 87 completed at least 50% of the treatment course, and 86 had PCR results at follow-up visits T6M, T12M, and T36M. PCR results exhibited fluctuations before and after treatment, but levels were significantly lower post-treatment. Only 15 cases consistently tested PCR-negative across all post-treatment visits. Notably, nearly all participants demonstrated a declining antibody trajectory, with patients who tested PCR-negative at T36M exhibiting an earlier and more pronounced decline compared to PCR-positive cases at the same visit. Our study suggests that serial PCR results pose challenges in interpretation. In contrast, serial antibody levels may serve as an ancillary, or even a more reliable indicator of parasite decline following BNZ treatment. Monitoring antibody levels can provide valuable insights into the efficacy of treatment and the persistence of parasites in Chagas disease patients.

ABSTRACTPlasma-derived polyclonal antibodies are polyvalent drugs used for many important clinical indications that require modulation of multiple drug targets simultaneously, including emerging infectious disease and transplantation. However, plasma-derived drugs suffer many problems, including low potency, impurities, constraints on supply, and batch-to-batch variation. In this study, we demonstrated proofs-of-concept for a technology that uses microfluidics and molecular genomics to capture diverse mammalian antibody repertoires as multivalent recombinant drugs. These “recombinant hyperimmune” drugs comprised thousands to tens of thousands of antibodies and were derived from convalescent human donors, or vaccinated human donors or immunized mice. Here we used our technology to build a highly potent recombinant hyperimmune for Severe Acute Respiratory Syndrome Coronavirus-2 (SARS CoV-2) in less than three months. We also validated a recombinant hyperimmune for Zika virus disease that abrogates antibody-dependent enhancement (ADE) through Fc engineering. For patients with primary immune deficiency (PID), we built high potency polyvalent recombinant hyperimmunes against pathogens that commonly cause serious lung infections. Finally, to address the limitations of rabbit-derived anti-thymocyte globulin (ATG), we generated a recombinant human version and demonstrated in vivo function against graft-versus-host disease (GVHD). Recombinant hyperimmunes are a novel class of drugs that could be used to target a wide variety of other clinical applications, including cancer and autoimmunity.