52 research outputs found
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
Pterostilbene Suppresses Ovarian Cancer Growth via Induction of Apoptosis and Blockade of Cell Cycle Progression Involving Inhibition of the STAT3 Pathway
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
Resveratrol Induces Differentiation Markers Expression in Anaplastic Thyroid Carcinoma via Activation of Notch1 Signaling and Suppresses Cell Growth
Comparative Evaluation of Solubility, Cytotoxicity and Photostability Studies of Resveratrol and Oxyresveratrol Loaded Nanosponges
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