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The ability to decompose complex multi-object scenes into meaningful abstractions like objects is fundamental to achieve higher-level cognition. Previous approaches for unsupervised object-oriented scene representation learning are either based on spatial-attention or scene-mixture approaches and limited in scalability which is a main obstacle towards modeling real-world scenes. In this paper, we propose a generative latent variable model, called SPACE, that provides a unified probabilistic modeling framework that combines the best of spatial-attention and scene-mixture approaches. SPACE can explicitly provide factorized object representations for foreground objects while also decomposing background segments of complex morphology. Previous models are good at either of these, but not both. SPACE also resolves the scalability problems of previous methods by incorporating parallel spatial-attention and thus is applicable to scenes with a large number of objects without performance degradations. We show through experiments on Atari and 3D-Rooms that SPACE achieves the above properties consistently in comparison to SPAIR, IODINE, and GENESIS. Results of our experiments can be found on our project website: https://sites.google.com/view/space-project-page

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BackgroundAntibody drug conjugate (ADC) showed potent therapeutic efficacy in several types of cancers. The role of autophagy in antitumor effects of ADC remains unclear.MethodsIn this study, the ADC, Rituximab-monomethyl auristatin E (MMAE) with a Valine–Citrulline cleavable linker, was designed to investigate its therapeutic efficacy against non-Hodgkin lymphoma (NHL) as well as the underlying mechanisms. Methylthiazolyldiphenyl-tetrazolium bromide (MTT) was used to detect growth inhibition in B-cell lymphoma cell lines, Ramos and Daudi cells, which were treated by Rituximab-MMAE alone or combined with autophagy conditioner. Apoptosis was detected by flow cytometry and immunohistochemistry, and apoptosis inhibitor was employed to discover the relationship between autophagy and apoptosis during the Rituximab-MMAE treatment. Autophagy was determined by three standard techniques which included confocal microscope, transmission electron microscope, and western blots. Ramos xenograft tumors in BALB/c nude mice were established to investigate the antitumor effect of combination use of Rituximab-MMAE and autophagy conditioner in B-NHL therapy.ResultsOur results showed that Rituximab-MMAE elicited caspase-3-dependent apoptosis in NHL cells and exhibited potent therapeutic efficacy in vivo. Autophagy, which was characterized by upregulated light chain 3-II expression, and accumulation of autophagosomes, was triggered during the Rituximab-MMAE treatment. Meanwhile, inactivation of Akt/mTOR pathway was shown to be involved in the autophagy triggered by Rituximab-MMAE, indicating a probable mechanism of the ADC-initiated autophagy. Importantly, inhibition of autophagy by chloroquine suppressed the Rituximab-MMAE-induced apoptosis, while activating autophagy by rapamycin significantly enhanced the therapeutic effect of Rituximab-MMAE both in vitro and in vivo.ConclusionOur data elucidated the critical relationship between autophagy and apoptosis in Rituximab-MMAE-based therapy and highlighted the potential approach for NHL therapy by combined administration of the ADC and autophagy activator.