Colorimetric sensors have been widely used to detect numerous analytes due to their cost-effectiveness, high sensitivity and specificity, and clear visibility, even with the naked eye. In recent years, the emergence of advanced nanomaterials has greatly improved the development of colorimetric sensors. This review focuses on the recent (from the years 2015 to 2022) advances in the design, fabrication, and applications of colorimetric sensors. First, the classification and sensing mechanisms of colorimetric sensors are briefly described, and the design of colorimetric sensors based on several typical nanomaterials, including graphene and its derivatives, metal and metal oxide nanoparticles, DNA nanomaterials, quantum dots, and some other materials are discussed. Then the applications, especially for the detection of metallic and non-metallic ions, proteins, small molecules, gas, virus and bacteria, and DNA/RNA are summarized. Finally, the remaining challenges and future trends in the development of colorimetric sensors are also discussed.

Three-dimensional (3D) surface-enhanced Raman scattering (SERS) substrates have demonstrated remarkable abilities of ultrasensitive and reproducible molecular detection. The combination of both electromagnetic and chemical enhancement processes, light trapping, and multiple scattering effects of 3D structures are what enhance their performance. The principles of underlying enhancements are summarized systematically, and the main types of 3D substrates—vertically aligned nanowires, dendritic and fractal nanostructures, porous frameworks and aerogels, core–shell and hollow nanospheres, and hierarchical hybrid structures—are categorized in this review. Advances in fabrication techniques, such as template-assisted growth, electrochemical and galvanic deposition, dealloying and freeze-drying, self-assembly, and hybrid integration, are critically evaluated in terms of structural tunability and scalability. Novel developments in the field of biosensing are also highlighted, including non-enzymatic glucose sensing, tumor biomarker sensing, and drug delivery. The remaining limitations, such as low reproducibility, mechanical stability, and substrate standardization, are also noted, and future directions, such as stimuli-responsive designs, multifunctional hybrid platforms, and data-driven optimization strategies of SERS technologies, are also included.

The current study proposes a green synthesis method for silver nanoparticles (Ag NPs) using various concentrations of Flos Sophorae Immaturus extract as reducing and capping agents. The UV-Visible (UV-Vis) spectroscopy, X-ray Diffraction (XRD), Fourier Transform Infrared spectroscopy (FTIR), X-ray Photoelectron Spectroscopy (XPS), Dynamic Light Scattering (DLS) and Transmission Electron Microscopy (TEM) were used to characterize resulting brown nanopowder. The as-prepared Ag NPs had a high negative zeta potential value of ∼ -38 mv, indicating the existence of electrostatic stabilization. The average sizes of ∼27.8 nm, 28.5 nm, 34.3 nm and 36.5 nm were measured by TEM. Moreover, FTIR and XPS analyses validated the production and chemical composition of Ag NPs from silver nitrate. The antibacterial activity of Ag NPs was examined against E. coli, P. aeruginosa, and S. aureus using agar well diffusion and the minimum inhibitory concentration (MIC) method. The antibacterial activity of the as-prepared Ag NPs from 4 mL extract was excellent against E. coli, P. aeruginosa, and S. aureus and the MIC values were 31.250, 15.625, and 31.250 mg/L, respectively. Based on these results, this study proposes a practical approach for the synthesis of Ag NPs in the industry and medical fields.

Neurovascular coupling (NVC) refers to the dynamic regulation of cerebral blood flow via neuronal activity, a mechanism crucial for maintaining normal brain function. This review elucidates the intricate physiological mechanisms underlying NVC, emphasizing the coordinated roles of neurons, glial cells, and vascular cells in mediating activity-induced changes in blood flow. We examine how NVC is impaired in neurological disorders such as Alzheimer’s disease and stroke, where the dysfunction of this coupling contributes to neurodegeneration and neurological deficits. A broad range of techniques for assessing NVC is discussed—encompassing the established modalities like transcranial Doppler, near-infrared spectroscopy, and functional magnetic resonance imaging (fMRI), as well as emerging technologies such as functional ultrasound imaging and miniaturized endoscopy that enable high-resolution monitoring in deep brain regions. We also highlight the computational modeling approaches for simulating NVC dynamics and identify the novel biomarkers of NVC dysfunction with potential utility in early diagnosis. Finally, emerging translational applications—including neuromodulation techniques and targeted pharmacological interventions—are explored as means to restore normal neurovascular function. These advancements underscore the clinical significance of NVC research, paving the way for improved diagnostic tools and therapeutic strategies in neurological disorders.

Background: Cerebral edema is an extremely common secondary disease in post-stroke. Point-of-care testing for cerebral edema types has important clinical significance for the precise management to prevent poor prognosis. Nevertheless, there has not been a fully accepted bedside testing method for that. Methods: A symmetric cancellation near-field coupling phase shift (NFCPS) monitoring system is established based on the symmetry of the left and right hemispheres and the fact that unilateral lesions do not affect healthy hemispheres. For exploring the feasibility of this system to reflect the occurrence and development of cerebral edema, 13 rabbits divided into experimental group (n = 8) and control group (n = 5) were performed 24-h NFCPS continuous monitoring experiments. After time difference offset and feature band averaging processing, the changing trend of NFCPS at the stages dominated by cytotoxic edema (CE) and vasogenic edema (VE), respectively, was analyzed. Furthermore, the features under the different time windows were extracted. Then, a discriminative model of cerebral edema types based on support vector machines (SVM) was established and performance of multiple feature combinations was compared. Results: The NFCPS monitoring outcomes of experimental group endured focal ischemia modeling by thrombin injection show a trend of first decreasing and then increasing, reaching the lowest value of − 35.05° at the 6th hour. Those of control group do not display obvious upward or downward trend and only fluctuate around the initial value with an average change of − 0.12°. Furthermore, four features under the 1-h and 2-h time windows were extracted. Based on the discriminative model of cerebral edema types, the classification accuracy of 1-h window is higher than 90% and the specificity is close to 1, which is almost the same as the performance of the 2-h window. Conclusion: This study proves the feasibility of NFCPS technology combined with SVM to distinguish cerebral edema types in a short time, which is promised to become a new solution for immediate and precise management of dehydration therapy after ischemic stroke.