Cellular metabolism plays a critical role in various physiological and pathological processes. High resolution imaging of intracellular metabolic activities is crucial for understanding many biological pathways, and for facilitating disease prognosis and treatment assessment. Raman scattering (RS) spectroscopy/microscopy, in particular stimulated Raman scattering (SRS), has emerged as a powerful imaging technology for cellular imaging with high specificity, high sensitivity, and subcellular resolution. Since its invention, SRS microscopy imaging has been extensively applied in life science for studying composition, structure, metabolism, development, and disease in biological systems. This review focuses on the latest applications of SRS imaging, particularly with heavy water probing, for studying metabolic dynamics of biomolecules in organisms during aging and diseases. Furthermore, future applications and development of SRS imaging in both life science and medicine are considered.

New research reveals how the neurovascular architecture of the murine calvarium, the skull's upper part, changes with age.

Organoids have gained significant interest due to their ability to recapitulate the structural, molecular, and functional complexity of corresponding organs. While methods have been developed to characterize and benchmark organoid structural and molecular properties, capturing the functional development and maturation of organoids remains challenging. To address this, the development of multifunctional bioelectronics for interfacing with organoids has been actively pursued. However, conventional electronics face limitations in achieving multifunctional recording and control across the entire three-dimensional (3D) volume of organoids in a long-term stable manner due to the large morphological and cellular composition changes during development. In this review, we first discuss the application of conventional electronics for organoid interfacing. We then focus on the development of flexible and stretchable electronics designed to create organoid/electronics hybrids for chronically stable interfaces. We also review recent advancements in flexible multifunctional electronics for charting multimodal cell activities throughout development. Furthermore, we explore the integration of flexible bioelectronics with other characterization modalities for comprehensive multimodal charting of cells within 3D tissues. Finally, we discuss the potential of integrating artificial intelligence into the organoid system through embedded electronics, harnessing organoid intelligence for biosymbiotic computational systems. These advancements could provide valuable tools for characterizing organoid functional development and maturation, establishing patient-specific models, developing therapeutic opportunities, and exploring novel computational strategies.

As global temperatures rise, the ability to understand how plants respond to heat has never been more critical. 

A cutting-edge humidity sensing system has been unveiled, capable of monitoring human behaviors in real-time through the detection of respiratory patterns. 

Long-term and precise intracellular signal detection is critical for advancing our understanding of brain diseases and developing effective diagnostic tools. 

A new fully automated in vivo screening system (AISS) has been developed to transform drug evaluation by enabling rapid, precise, and non-invasive multi-organ imaging in zebrafish. Integrating cutting-edge microfluidic technology with computer-vision-based control, this innovative system automates every aspect of zebrafish larvae handling— from loading and encapsulation to immobilization and drug exposure. 

A recent study reveals how the expansion and functional divergence of terpene synthase genes (TPSs) in flowering plants (angiosperms) have driven the astonishing diversity of terpenes—critical compounds involved in plant defense, floral scents, and fruit flavors. 

As climate change and population growth increase pressure on global food production, regional-scale crop growth and associated process (CROP-AP) models have become essential tools for understanding and predicting agricultural productivity. A new review, published in Science China Earth Sciences, categorizes these models into four types—statistical models, crop growth models, hydrology-crop coupling models, and ecosystem models. The study explores their main functions from five aspects: crop yield prediction, crop water consumption, agricultural non-point source pollution, greenhouse gas emissions, and climate change impact and responses, and identifies key future research directions, including model validation and calibration, the ability to simulate the coupling of crop physiology and human activities, enhancing model scalability, multi-model ensembles, data and code sharing, and the integration of artificial intelligence.

Researchers used in situ pH measurements and in situ UV-Vis spectroscopy to investigate the kinetically controlled growth of Co(OH)₂. They discovered that Co polyhedra with unconventional coordination play a crucial role in the formation process of Co(OH)₂, reshaping our understanding of the formation process.