The urotensin II receptor triggers an early meningeal response and a delayed macrophage-dependent vasospasm after subarachnoid hemorrhage in male mice.

Subarachnoid hemorrhage (SAH) can be associated with neurological deficits and has profound consequences for mortality and morbidity. Cerebral vasospasm (CVS) and delayed cerebral ischemia affect neurological outcomes in SAH patients, but their mechanisms are not fully understood, and effective treatments are limited. Here, we report that urotensin II receptor UT plays a pivotal role in both early events and delayed mechanisms following SAH in male mice.

Micro-macro SERS strategy for highly sensitive paper cartridge with trace-level molecular detection.

Surface-enhanced Raman Scattering (SERS) has become a powerful spectroscopic technology for highly sensitive detection. However, SERS is still limited in the lab because it either requires complicated preparation or is limited to specific compounds, causing poor applicability for practical applications. Herein, a micro-macro SERS strategy, synergizing polymer-assisted printed process with paper-tip enrichment process, is proposed to fabricate highly sensitive paper cartridges for sensitive practical applications.

Fragment-Fusion Transformer: Deep Learning-Based Discretization Method for Continuous Single-Cell Raman Spectral Analysis.

Raman spectroscopy has become an important single-cell analysis tool for monitoring biochemical changes at the cellular level. However, Raman spectral data, typically presented as continuous data with high-dimensional characteristics, is distinct from discrete sequences, which limits the application of deep learning-based algorithms in data analysis due to the lack of discretization. Herein, a model called fragment-fusion transformer is proposed, which integrates the discrete fragmentation of continuous spectra based on their intrinsic characteristics with the extraction of intrafragment features and the fusion of interfragment features.

Honeycomb-Inspired Surface-Enhanced Raman Scattering Microarray for Large-Area Automated Testing of Urease in Saliva Samples.

Surface-enhanced Raman scattering (SERS) technology, as an important analytical tool, has been widely applied in the field of chemical and biomedical sensing. Automated testing is often combined with biochemical analysis technologies to shorten the detection time and minimize human error. The present SERS substrates for sample detection are time-consuming and subject to high human error, which are not conducive to the combination of SERS and automated testing.