Toward chip-scale integration: microcomb-enabled ultra-broadband spectroscopy
Peer-Reviewed Publication
Updates every hour. Last Updated: 5-Nov-2025 13:11 ET (5-Nov-2025 18:11 GMT/UTC)
This work presents a miniaturized spectrometer spanning 5.2 THz across the full C-band by pairing a GHz-tunable laser with a stabilized Si3N4 soliton microcomb. The system achieves kHz-level frequency resolution and retrieves both amplitude and phase—resolving molecular absorption lines in a gas cell and extracting dispersion from integrated photonic devices. The demonstrated stability and precision, along with a simplified architecture, point toward fully integrated, chip-scale ultrabroadband spectroscopy in future implementations.
This study reveals unique insights into improving biliary cold preservation by exploring the natural cold tolerance mechanisms of hibernating mammals. Researchers established Syrian hamster intrahepatic cholangiocyte organoids (shICOs), which demonstrated superior resistance to cooling-rewarming stress compared to mouse-derived organoids (mICOs). Enhanced iron homeostasis and anti-ferroptosis capacity in shICOs suggest a novel strategy to reduce bile duct injury during liver transplantation.
This study constructs a spatiotemporal single-nucleus transcriptomic atlas of neurons in the entorhinal cortex–hippocampal (EC-HPC) circuit during Alzheimer’s disease (AD) progression. By performing Smart-seq2-based single-nucleus RNA sequencing on neurons from APP/PS1 transgenic mice and wild-type controls across different brain regions and disease stages, the study reveals two distinct neuronal populations associated with AD pathology: progressively lost EC-stellate neurons and expanding GFAP⁺ neurons with glia-like features. These findings highlight neuronal identity changes and energy metabolism dysfunction in AD, offering new insights into early diagnosis and intervention.
This study uncovers a novel role of RNA G-quadruplex (rG4) structures in regulating translation and cellular senescence. By integrating ribosome profiling and rG4-RIP sequencing, the researchers reveal that rG4 structures within coding regions cause ribosome pausing, disrupt protein homeostasis, and accelerate senescence. The RNA helicase DHX9 is identified as a key factor that unwinds rG4 structures and maintains translational balance. These findings highlight rG4 stabilization as a potential driver of aging and age-related diseases, offering new therapeutic opportunities by targeting rG4 dynamics.
This review article delves into the potential of secreted proteins as therapeutic targets for treating MASLD, a global epidemic with limited pharmacological interventions. The authors highlight the diverse roles of secreted proteins in regulating glucose and lipid metabolism and discuss their dysregulation in MASLD. The review summarizes recent findings on various secreted protein families, including orosomucoid (ORM), SPARC, neuregulin (Nrg), growth differentiation factor (GDF), interleukin (IL), fibroblast growth factor (FGF), bone morphogenic protein (BMP), Isthmin-1 (Ism1), and mesencephalic astrocyte-derived neurotrophic factor (MANF).
High-entropy materials (HEMs) have attracted considerable research attention in battery applications due to exceptional properties such as remarkable structural stability, enhanced ionic conductivity, superior mechanical strength, and outstanding catalytic activity. These distinctive characteristics render HEMs highly suitable for various battery components, such as electrodes, electrolytes, and catalysts. This review systematically examines recent advances in the application of HEMs for energy storage, beginning with fundamental concepts, historical development, and key definitions. Three principal categories of HEMs, namely high-entropy alloys, high-entropy oxides, and high-entropy MXenes, are analyzed with a focus on electrochemical performance metrics such as specific capacity, energy density, cycling stability, and rate capability. The underlying mechanisms by which these materials enhance battery performance are elucidated in the discussion. Furthermore, the pivotal role of machine learning in accelerating the discovery and optimization of novel high-entropy battery materials is highlighted. The review concludes by outlining future research directions and potential breakthroughs in HEM-based battery technologies.