Clonal neural tube organoids self-organise floorplate through BMP-mediated cluster competition

Posted by klaurent Rockefeller

Kavli Affiliate: Eric D. Siggia | Authors: Teresa Krammer, Hannah Taylor Stuart, Elena Gromberg, Keisuke Ishihara, Manuela Melchionda, Jingkui Wang, Elena Costantini, Stefanie Lehr, Dillon Cislo, Laura Arbanas, Alexandra Hoermann, Ralph Alexander Neumueller, Nicola Elvassore, Eric Siggia, James Briscoe, Anna Kicheva and Elly Margaret Tanaka | Summary: Organoids can undergo pattern formation by spontaneously forming […]


Continue.. Clonal neural tube organoids self-organise floorplate through BMP-mediated cluster competition

A Chicken Tapasin ortholog can chaperone empty HLA molecules independently of other peptide-loading components

Posted by klaurent Rockefeller

Kavli Affiliate: Michael W. Young | Authors: Georgia F Papadaki, Claire H Woodward, Michael C Young, Trenton J Winters, George M Burslem and Nikolaos G Sgourakis | Summary: Human Tapasin (hTapasin) is the main chaperone of MHC-I molecules, enabling peptide loading and antigen repertoire optimization across HLA allotypes. However, it is restricted to the endoplasmic […]


Continue.. A Chicken Tapasin ortholog can chaperone empty HLA molecules independently of other peptide-loading components

HD mutation results in a dominant negative effect on HTT function

Posted by klaurent Rockefeller

Kavli Affiliate: Ali H. Brivanlou | Authors: Tiago L Laundos, Shu Li, Eric Cheang, Riccardo De Santis, Francesco M Piccolo and Ali H. Brivanlou | Summary: Huntington’s disease (HD) remains an incurable and fatal neurodegenerative disease long after CAG-expansion mutation in the huntingtin gene (HTT) was identified as the cause. The underlying pathological mechanism, whether […]


Continue.. HD mutation results in a dominant negative effect on HTT function

Multi-night naturalistic cortico-basal recordings reveal mechanisms of NREM slow wave suppression and spontaneous awakenings in Parkinson’s disease

Posted by klaurent UCSF

Kavli Affiliate: Philip Starr | Authors: Md Fahim Anjum, Clay Smyth, Derk-Jan Dijk, Philip Starr, Timothy Denison and Simon Little | Summary: Background: Sleep disturbance is a prevalent and highly disabling comorbidity in individuals with Parkinson’s disease (PD) that leads to worsening of daytime symptoms, accelerated disease progression and reduced quality of life. Objectives: We […]


Continue.. Multi-night naturalistic cortico-basal recordings reveal mechanisms of NREM slow wave suppression and spontaneous awakenings in Parkinson’s disease

Oxysterol-liver X receptor signaling mediates CYFIP1 regulation of cortical neurogenesis

Posted by klaurent Hopkins

Kavli Affiliate: David Linden | Authors: Daniel C de la Fuente, Claudia Tamburini, Emily Stonelake, William J Griffiths, Jeremy Hall, Michael J Owen, David E. J. Linden, Andrew Pocklington, Yuqin Wang and Meng Li | Summary: Dysregulation in neural progenitor proliferation and neuronal differentiation has been increasingly recognised as a common pathology in neural cells […]


Continue.. Oxysterol-liver X receptor signaling mediates CYFIP1 regulation of cortical neurogenesis

Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks

Posted by klaurent Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Gaotang Li, Marlena Duda, Xiang Zhang, Danai Koutra, Yujun Yan | Summary: Brain graphs, which model the structural and functional relationships between brain regions, are crucial in neuroscientific and clinical applications involving graph classification. However, dense brain graphs pose computational challenges including high runtime and memory usage […]


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GPT-assisted learning of structure-property relationships by graph neural networks: Application to rare-earth doped phosphors

Posted by dbos Berkeley

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Zichun Zhou, Chen Ming, Yi-Yang Sun, | Summary: Applications of machine learning techniques in materials science are often based on two key ingredients, a set of empirical descriptors and a database of a particular material property of interest. The advent of graph neural networks, such […]


Continue.. GPT-assisted learning of structure-property relationships by graph neural networks: Application to rare-earth doped phosphors

Discovering two-dimensional magnetic topological insulators by machine learning

Posted by dbos Peking

Kavli Affiliate: Jing Wang | First 5 Authors: Haosheng Xu, Yadong Jiang, Huan Wang, Jing Wang, | Summary: Topological materials with unconventional electronic properties have been investigated intensively for both fundamental and practical interests. Thousands of topological materials have been identified by symmetry-based analysis and ab initio calculations. However, the predicted magnetic topological insulators with […]


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DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data

Posted by dbos Peking

Kavli Affiliate: Jiansheng Chen | First 5 Authors: Jingyuan Zhu, Huimin Ma, Jiansheng Chen, Jian Yuan, | Summary: Denoising diffusion probabilistic models (DDPMs) have been proven capable of synthesizing high-quality images with remarkable diversity when trained on large amounts of data. Typical diffusion models and modern large-scale conditional generative models like text-to-image generative models are […]


Continue.. DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data

DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data

Posted by dbos Peking

Kavli Affiliate: Jiansheng Chen | First 5 Authors: Jingyuan Zhu, Huimin Ma, Jiansheng Chen, Jian Yuan, | Summary: Denoising diffusion probabilistic models (DDPMs) have been proven capable of synthesizing high-quality images with remarkable diversity when trained on large amounts of data. Typical diffusion models and modern large-scale conditional generative models like text-to-image generative models are […]


Continue.. DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data