Adhesive L1CAM-Robo Signaling Aligns Growth Cone F-Actin Dynamics to Promote Axon-Dendrite Fasciculation in C. elegans

Neurite fasciculation through contact-dependent signaling is important for the wiring and function of the neuronal circuits. Here, we describe a type of axon-dendrite fasciculation in C. elegans, where proximal dendrites of the nociceptor PVD adhere to the axon of the ALA interneuron. This axon-dendrite fasciculation is mediated by a previously uncharacterized adhesive signaling by the ALA membrane signal SAX-7/L1CAM and the PVD receptor SAX-3/Robo but independent of Slit. L1CAM physically interacts with Robo and instructs dendrite adhesion in a Robo-dependent manner. Fasciculation mediated by L1CAM-Robo signaling aligns F-actin dynamics in the dendrite growth cone and facilitates dynamic growth cone behaviors for efficient dendrite guidance. Disruption of PVD dendrite fasciculation impairs nociceptive mechanosensation and rhythmicity in body curvature, suggesting that dendrite fasciculation governs the functions of mechanosensory circuits. Our work elucidates the molecular mechanisms by which adhesive axon-dendrite signaling shapes the construction and function of sensory neuronal circuits

The polarity protein VANG-1 antagonizes Wnt signaling by facilitating Frizzled endocytosis

Signaling that instructs the migration of neurons needs to be tightly regulated to ensure precise positioning of neurons and subsequent wiring of the neuronal circuits. Wnt-Frizzled signaling controls neuronal migration in metazoans, in addition to many other aspects of neural development. We show that Caenorhabditis elegans VANG-1, a membrane protein that acts in the planar cell polarity (PCP) pathway, antagonizes Wnt signaling by facilitating endocytosis of the Frizzled receptors. Mutations of vang-1 suppress migration defects of multiple classes of neurons in the Frizzled mutants, and overexpression of vang-1 causes neuronal migration defects similar to those of the Frizzled mutants. Our genetic experiments suggest that VANG-1 facilitates Frizzled endocytosis through β-arrestin2. Co-immunoprecipitation experiments indicate that Frizzled proteins and VANG-1 form a complex, and this physical interaction requires the Frizzled cysteine-rich domain. Our work reveals a novel mechanism mediated by the PCP protein VANG-1 that downregulates Wnt signaling through Frizzled endocytosis

Adhesive L1CAM-Robo Signaling Aligns Growth Cone F-Actin Dynamics to Promote Axon-Dendrite Fasciculation in C. elegans

Neurite fasciculation through contact-dependent signaling is important for the wiring and function of the neuronal circuits. Here, we describe a type of axon-dendrite fasciculation in C. elegans, where proximal dendrites of the nociceptor PVD adhere to the axon of the ALA interneuron. This axon-dendrite fasciculation is mediated by a previously uncharacterized adhesive signaling by the ALA membrane signal SAX-7/L1CAM and the PVD receptor SAX-3/Robo but independent of Slit. L1CAM physically interacts with Robo and instructs dendrite adhesion in a Robo-dependent manner. Fasciculation mediated by L1CAM-Robo signaling aligns F-actin dynamics in the dendrite growth cone and facilitates dynamic growth cone behaviors for efficient dendrite guidance. Disruption of PVD dendrite fasciculation impairs nociceptive mechanosensation and rhythmicity in body curvature, suggesting that dendrite fasciculation governs the functions of mechanosensory circuits. Our work elucidates the molecular mechanisms by which adhesive axon-dendrite signaling shapes the construction and function of sensory neuronal circuits

Centella asiatica extract protects against amyloid β1–40-induced neurotoxicity in neuronal cells by activating the antioxidative defence system

AbstractCentella asiatica (雷公根 léi gōng gēn) is a traditional medicinal herb with high antioxidant activity, which decreases amyloid-β (Aβ) deposition in the brain. At the same time, aggregated Aβ-induced oxidative stress is the trigger in the pathogenesis of Alzheimer's disease (AD). Here, we investigated the ability of C. asiatica ethanol extract (CAE) to protect PC12 and IMR32 cells from Aβ1–40-induced production of reactive oxygen species (ROS) and concomitant neurotoxicity. Aggregated Aβ1–40 treatment resulted in reduced cell viability, which can be reversed by cotreatment with 25, 50, and 100 μg/mL CAE. Moreover, CAE eliminated the Aβ1–40-mediated increase in ROS production. Thus, CAE-mediated protection against aggregated Aβ1–40-induced neurotoxicity is attributable to modulation of the antioxidative defense system in cells, including the activities of superoxide dismutase, catalase, glutathione peroxidase, glutathione reductase, and levels of glutathione and glutathione disulfide by CAE. This emphasizes the potential therapeutic and preventive value of CAE in the treatment of AD

The polarity protein VANG-1 antagonizes Wnt signaling by facilitating Frizzled endocytosis

Signaling that instructs the migration of neurons needs to be tightly regulated to ensure precise positioning of neurons and subsequent wiring of the neuronal circuits. Wnt-Frizzled signaling controls neuronal migration in metazoans, in addition to many other aspects of neural development. We show that Caenorhabditis elegans VANG-1, a membrane protein that acts in the planar cell polarity (PCP) pathway, antagonizes Wnt signaling by facilitating endocytosis of the Frizzled receptors. Mutations of vang-1 suppress migration defects of multiple classes of neurons in the Frizzled mutants, and overexpression of vang-1 causes neuronal migration defects similar to those of the Frizzled mutants. Our genetic experiments suggest that VANG-1 facilitates Frizzled endocytosis through β-arrestin2. Co-immunoprecipitation experiments indicate that Frizzled proteins and VANG-1 form a complex, and this physical interaction requires the Frizzled cysteine-rich domain. Our work reveals a novel mechanism mediated by the PCP protein VANG-1 that downregulates Wnt signaling through Frizzled endocytosis

ActAnywhere: Subject-Aware Video Background Generation

Generating video background that tailors to foreground subject motion is an important problem for the movie industry and visual effects community. This task involves synthesizing background that aligns with the motion and appearance of the foreground subject, while also complies with the artist's creative intention. We introduce ActAnywhere, a generative model that automates this process which traditionally requires tedious manual efforts. Our model leverages the power of large-scale video diffusion models, and is specifically tailored for this task. ActAnywhere takes a sequence of foreground subject segmentation as input and an image that describes the desired scene as condition, to produce a coherent video with realistic foreground-background interactions while adhering to the condition frame. We train our model on a large-scale dataset of human-scene interaction videos. Extensive evaluations demonstrate the superior performance of our model, significantly outperforming baselines. Moreover, we show that ActAnywhere generalizes to diverse out-of-distribution samples, including non-human subjects. Please visit our project webpage at https://actanywhere.github.io

Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models

Large language models (LLMs) have achieved remarkable progress in various natural language processing tasks with emergent abilities. However, they face inherent limitations, such as an inability to access up-to-date information, utilize external tools, or perform precise mathematical reasoning. In this paper, we introduce Chameleon, a plug-and-play compositional reasoning framework that augments LLMs to help address these challenges. Chameleon synthesizes programs to compose various tools, including LLM models, off-the-shelf vision models, web search engines, Python functions, and rule-based modules tailored to user interests. Built on top of an LLM as a natural language planner, Chameleon infers the appropriate sequence of tools to compose and execute in order to generate a final response. We showcase the adaptability and effectiveness of Chameleon on two tasks: ScienceQA and TabMWP. Notably, Chameleon with GPT-4 achieves an 86.54% accuracy on ScienceQA, significantly improving upon the best published few-shot model by 11.37%; using GPT-4 as the underlying LLM, Chameleon achieves a 17.8% increase over the state-of-the-art model, leading to a 98.78% overall accuracy on TabMWP. Further studies suggest that using GPT-4 as a planner exhibits more consistent and rational tool selection and is able to infer potential constraints given the instructions, compared to other LLMs like ChatGPT.Comment: 25 pages, 10 figures. Project page: https://chameleon-llm.github.i