ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning

For robots to perform a wide variety of tasks, they require a 3D representation of the world that is semantically rich, yet compact and efficient for task-driven perception and planning. Recent approaches have attempted to leverage features from large vision-language models to encode semantics in 3D representations. However, these approaches tend to produce maps with per-point feature vectors, which do not scale well in larger environments, nor do they contain semantic spatial relationships between entities in the environment, which are useful for downstream planning. In this work, we propose ConceptGraphs, an open-vocabulary graph-structured representation for 3D scenes. ConceptGraphs is built by leveraging 2D foundation models and fusing their output to 3D by multi-view association. The resulting representations generalize to novel semantic classes, without the need to collect large 3D datasets or finetune models. We demonstrate the utility of this representation through a number of downstream planning tasks that are specified through abstract (language) prompts and require complex reasoning over spatial and semantic concepts. (Project page: https://concept-graphs.github.io/ Explainer video: https://youtu.be/mRhNkQwRYnc )Comment: Project page: https://concept-graphs.github.io/ Explainer video: https://youtu.be/mRhNkQwRYn

ConceptFusion: Open-set Multimodal 3D Mapping

Building 3D maps of the environment is central to robot navigation, planning, and interaction with objects in a scene. Most existing approaches that integrate semantic concepts with 3D maps largely remain confined to the closed-set setting: they can only reason about a finite set of concepts, pre-defined at training time. Further, these maps can only be queried using class labels, or in recent work, using text prompts. We address both these issues with ConceptFusion, a scene representation that is (1) fundamentally open-set, enabling reasoning beyond a closed set of concepts and (ii) inherently multimodal, enabling a diverse range of possible queries to the 3D map, from language, to images, to audio, to 3D geometry, all working in concert. ConceptFusion leverages the open-set capabilities of today's foundation models pre-trained on internet-scale data to reason about concepts across modalities such as natural language, images, and audio. We demonstrate that pixel-aligned open-set features can be fused into 3D maps via traditional SLAM and multi-view fusion approaches. This enables effective zero-shot spatial reasoning, not needing any additional training or finetuning, and retains long-tailed concepts better than supervised approaches, outperforming them by more than 40% margin on 3D IoU. We extensively evaluate ConceptFusion on a number of real-world datasets, simulated home environments, a real-world tabletop manipulation task, and an autonomous driving platform. We showcase new avenues for blending foundation models with 3D open-set multimodal mapping. For more information, visit our project page https://concept-fusion.github.io or watch our 5-minute explainer video https://www.youtube.com/watch?v=rkXgws8fiD

Biological Activities of Polyphenols from Grapes

The dietary consumption of grape and its products is associated with a lower incidence of degenerative diseases such as cardiovascular disease and certain types of cancers. Most recent interest has focused on the bioactive phenolic compounds in grape. Anthocyanins, flavanols, flavonols and resveratrol are the most important grape polyphenols because they possess many biological activities, such as antioxidant, cardioprotective, anticancer, anti-inflammation, antiaging and antimicrobial properties. This review summarizes current knowledge on the bioactivities of grape phenolics. The extraction, isolation and identification methods of polyphenols from grape as well as their bioavailability and potential toxicity also are included

Resveratrol inhibits PDGF receptor mitogenic signaling in mesangial cells: role of PTP1B

Mesangioproliferative glomerulonephritis is associated with overactive PDGF receptor signal transduction. We show that the phytoalexin resveratrol dose dependently inhibits PDGF-induced DNA synthesis in mesangial cells with an IC50 of 10 μM without inducing apoptosis. Remarkably, the increased SIRT1 deacetylase activity induced by resveratrol was not necessary for this inhibitory effect. Resveratrol significantly blocked PDGF-stimulated c-Src and Akt kinase activation, resulting in reduced cyclin D1 expression and attenuated pRb phosphorylation and cyclin-dependent kinase-2 (CDK2) activity. Furthermore, resveratrol inhibited PDGFR phosphorylation at the PI 3 kinase and Grb-2 binding sites tyrosine-751 and tyrosine-716, respectively. This deficiency in PDGFR phosphorylation resulted in significant inhibition of PI 3 kinase and Erk1/2 MAPK activity. Interestingly, resveratrol increased the activity of protein tyrosine phosphatase PTP1B, which dephosphorylates PDGF-stimulated phosphorylation at tyrosine-751 and tyrosine-716 on PDGFR with concomitant reduction in Akt and Erk1/2 kinase activity. PTP1B significantly inhibited PDGF-induced DNA synthesis without inducing apoptosis. These results for the first time provide evidence that the stilbene resveratrol targets PTP1B to inhibit PDGFR mitogenic signaling.—Venkatesan, B., Ghosh-Choudhury, N., Das, F., Mahimainathan, L., Kamat, A., Kasinath, B. S., Abboud, H. E., Choudhury, G. G. Resveratrol inhibits PDGF receptor mitogenic signaling in mesangial cells: role of PTP1B