Three-dimensional (3D), submillimeter-scale constructs of neural cells, known as cortical spheroids, are of rapidly growing importance in biological research because these systems reproduce complex features of the brain in vitro. Despite their great potential for studies of neurodevelopment and neurological disease modeling, 3D living objects cannot be studied easily using conventional approaches to neuromodulation, sensing, and manipulation. Here, we introduce classes of microfabricated 3D frameworks as compliant, multifunctional neural interfaces to spheroids and to assembloids. Electrical, optical, chemical, and thermal interfaces to cortical spheroids demonstrate some of the capabilities. Complex architectures and high-resolution features highlight the design versatility. Detailed studies of the spreading of coordinated bursting events across the surface of an isolated cortical spheroid and of the cascade of processes associated with formation and regrowth of bridging tissues across a pair of such spheroids represent two of the many opportunities in basic neuroscience research enabled by these platforms.
Advances in Large Language Models (LLMs) have inspired a surge of research exploring their expansion into the visual domain. While recent models exhibit promise in generating abstract captions for images and conducting natural conversations, their performance on textrich images leaves room for improvement. In this paper, we propose the Contrastive Reading Model (Cream), a novel neural architecture designed to enhance the language-image understanding capability of LLMs by capturing intricate details typically overlooked by existing methods. Cream integrates vision and auxiliary encoders, complemented by a contrastive feature alignment technique, resulting in a more effective understanding of textual information within document images. Our approach, thus, seeks to bridge the gap between vision and language understanding, paving the way for more sophisticated Document Intelligence Assistants. Rigorous evaluations across diverse tasks, such as visual question answering on document images, demonstrate the efficacy of Cream as a state-of-the-art model in the field of visual document understanding. We provide our codebase and newly-generated datasets at https://github.com/naver-ai/cream.
Advances
in materials chemistry and engineering serve as the basis
for multifunctional neural interfaces that span length scales from
individual neurons to neural networks, neural tissues, and complete
neural systems. Such technologies exploit electrical, electrochemical,
optical, and/or pharmacological modalities in sensing and neuromodulation
for fundamental studies in neuroscience research, with additional
potential to serve as routes for monitoring and treating neurodegenerative
diseases and for rehabilitating patients. This review summarizes the
essential role of chemistry in this field of research, with an emphasis
on recently published results and developing trends. The focus is
on enabling materials in diverse device constructs, including their
latest utilization in 3D bioelectronic frameworks formed by 3D printing,
self-folding, and mechanically guided assembly. A concluding section
highlights key challenges and future directions.
Therapeutic compression garments (TCGs) are key tools for the management of a wide range of vascular lower extremity conditions. Proper use of TCGs involves application of a minimum and consistent pressure across the lower extremities for extended periods of time. Slight changes in the characteristics of the fabric and the mechanical properties of the tissues lead to requirements for frequent measurements and corresponding adjustments of the applied pressure. Existing sensors are not sufficiently small, thin, or flexible for practical use in this context, and they also demand cumbersome, hard-wired interfaces for data acquisition. Here, we introduce a flexible, wireless monitoring system for tracking both temperature and pressure at the interface between the skin and the TCGs. Detailed studies of the materials and engineering aspects of these devices, together with clinical pilot trials on a range of patients with different pathologies, establish the technical foundations and measurement capabilities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.