Raman microspectroscopy fingerprinting of organoid differentiation state

Organoid intelligence: Integration of organoid technology and artificial intelligence in the new era of in vitro models

Organoid Intelligence ushers in a new era by seamlessly integrating cutting-edge organoid technology with the power of artificial intelligence. Organoids, three-dimensional miniature organ-like structures cultivated from stem cells, offer an unparalleled opportunity to simulate complex human organ systems in vitro. Through the convergence of organoid technology and AI, researchers gain the means to accelerate discoveries and insights across various disciplines. Artificial intelligence algorithms enable the comprehensive analysis of intricate organoid behaviors, intricate cellular interactions, and dynamic responses to stimuli. This synergy empowers the development of predictive models, precise disease simulations, and personalized medicine approaches, revolutionizing our understanding of human development, disease mechanisms, and therapeutic interventions. Organoid Intelligence holds the promise of reshaping how we perceive in vitro modeling, propelling us toward a future where these advanced systems play a pivotal role in biomedical research and drug development.

Salivary Gland Bioengineering

Salivary gland dysfunction affects millions globally, and tissue engineering may provide a promising therapeutic avenue. This review delves into the current state of salivary gland tissue engineering research, starting with a study of normal salivary gland development and function. It discusses the impact of fibrosis and cellular senescence on salivary gland pathologies. A diverse range of cells suitable for tissue engineering including cell lines, primary salivary gland cells, and stem cells are examined. Moreover, the paper explores various supportive biomaterials and scaffold fabrication methodologies that enhance salivary gland cell survival, differentiation, and engraftment. Innovative engineering strategies for the improvement of vascularization, innervation, and engraftment of engineered salivary gland tissue, including bioprinting, microfluidic hydrogels, mesh electronics, and nanoparticles, are also evaluated. This review underscores the promising potential of this research field for the treatment of salivary gland dysfunction and suggests directions for future exploration.

Spectroscopic techniques for monitoring stem cell and organoid proliferation in 3D environments for therapeutic development

Spectroscopic techniques for monitoring stem cell and organoid proliferation have gained significant attention in therapeutic development. Spectroscopic techniques such as fluorescence, Raman spectroscopy, and infrared spectroscopy offer noninvasive and real-time monitoring of biochemical and biophysical changes that occur during stem cell and organoid proliferation. These techniques provide valuable insight into the underlying mechanisms of action of potential therapeutic agents, allowing for improved drug discovery and screening. This review highlights the importance of spectroscopic monitoring of stem cell and organoid proliferation and its potential impact on therapeutic development. Furthermore, this review discusses recent advances in spectroscopic techniques and their applications in stem cell and organoid research. Overall, this review emphasizes the importance of spectroscopic techniques as valuable tools for studying stem cell and organoid proliferation and their potential to revolutionize therapeutic development in the future.

Recent Advances in Raman Spectral Imaging in Cell Diagnosis and Gene Expression Prediction

Normal and tumor regions within cancer tissue can be distinguished using various methods, such as histological analysis, tumor marker testing, X-ray imaging, or magnetic resonance imaging. Recently, new discrimination methods utilizing the Raman spectra of tissues have been developed and put into practical use. Because Raman spectral microscopy is a non-destructive and non-labeling method, it is potentially compatible for use in the operating room. In this review, we focus on the basics of Raman spectroscopy and Raman imaging in live cells and cell type discrimination, as these form the bases for current Raman scattering-based cancer diagnosis. We also review recent attempts to estimate the gene expression profile from the Raman spectrum of living cells using simple machine learning. Considering recent advances in machine learning techniques, we speculate that cancer type discrimination using Raman spectroscopy will be possible in the near future.