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.

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.

Timely reperfusion of ischemic tissues and hemodynamic reconstruction are key to the treatment of acute ischemic stroke. The low temporal resolution of current imaging methods commonly used in clinical practice have the risk of diagnostic delay. In this study, a noninvasive cerebral blood flow (CBF) monitoring device was established based on inductive sensing technology, aiming at rapid and real-time assessment of ischemic tissue blood flow reperfusion to improve the treatment conditions and assess the prognostic outcome of acute ischemic stroke. The noninvasive CBF monitoring device was constructed using an inductive sensor and the LDC1612 evaluation module. Based on a homemade physical model of CBF pulsation and a healthy volunteer test, the depth and range of the sensor were evaluated by the time-domain amplitude and frequency-domain variation characteristics of resonant frequency. The monitoring results were processed using wavelet transform, high and low pass filtering, and cubic spline interpolation to remove the baseline and extract the CBF signal components. Based on the cardiogenic CBF pulsation mechanism, the periodic amplitude and area of CBF signals in resting and carbon dioxide inhalation states were extracted from healthy volunteers, and the feasibility of noninvasive monitoring of CBF by inductive sensing technology was evaluated. The experimental results showed that the method can evaluate the periodic pulsation of CBF and the changes of CBF in real-time with high accuracy. Thus, the present study verifies that the noninvasive CBF monitoring device based on inductive sensing technology can effectively detect the cardiac pulsations of CBF, which is expected to break the time window effect caused by the imaging examination and provide a new technology for noninvasive real-time monitoring of CBF perfusion changes.

In this study, a MOF-199/Ag@Au SERS sensing structure was successfully synthesized by combining metal–organic frameworks (MOFs) with surface-enhanced Raman scattering (SERS) technology for the efficient detection of dopamine (DA), a biomarker for neurological diseases, in serum. Using electrochemical methods, a copper-based MOF (MOF-199) was synthesized in situ on copper substrates and further deposited with silver nanoparticles (AgNPs). Subsequently, gold nanoshells were encapsulated around these silver cores by in situ chemical deposition. This preparation process is simple, controllable, and inexpensive. Furthermore, a novel Azo reaction-based DA SERS method was proposed to detect 1 pM DA, which represents an improvement in sensitivity by two orders of magnitude compared to previous unlabeled SERS detection methods and by four orders of magnitude compared to another SERS approach proposed in this work. There was an excellent linear relationship (R² = 0.976) between the SERS signal at 1140 cm⁻¹ and the DA concentration (0.001 M~1 pM). The results indicate that the MOF-199/Ag@Au sensor structure can successfully achieve both the qualitative and quantitative detection of DA in serum, thus providing a robust technical basis for the application of SERS technology in the field of clinical neurological disease screening.

Assessment of cerebral blood flow (CBF) is essential for the prevention and management of strokes. In this study, the electromagnetic coupling sensor with a dual-layer planar spiral structure was designed to enhance electrical coupling and reduce detection frequency. Based on this sensor, a wearable device for dynamic monitoring of CBF was established, which reflected changes in brain conductivity and permittivity by measured resonant frequency (RF). The brine concentration and volume detection sensitivity of this sensor were evaluated in the basic performance test experiments. Its detection depth and range were tested on a model of simulated vascular pulsation. We further studied the feasibility of the wearable device to obtain different CBF responses corresponding to various internal pressure excitations. In addition, we recruited 24 healthy volunteers to simultaneously monitor cerebral oxygen (CO) and RF, and we examined the pattern of RF change throughout the caffeine-induced CBF disturbance. Based on the main frequency change characteristics of the RF signal after taking caffeine, the effectiveness of the wearable monitoring device to distinguish between normal and abnormal CBF states was analyzed. The results show that the measured RF has a significant linear relationship with brine concentration and volume, with sensitivities of 0.0751 KHz/(g/ml) and 2.2359e-5 KHz/ml respectively. The frequencies of periodic changes in RF correspond to that of simulated vascular pulsation, and the sensor has a detection depth of 9 cm and a detection range of 4 cm. In CBF detection under various simulated intravascular pressures, the average RF exhibits the same trend of variation as the simulated intravascular pressure. These results indicate that the wearable gadget can detect CBF that has been triggered by various simulated vascular pulsation frequencies and internal pressures. During the process of increased cerebrovascular stiffness and decreased CO produced by caffeine consumption in healthy volunteers, the characteristics of RF pulsation exhibit a nonlinear downward trend. The abnormal state of CBF selected based on the turning point of the main frequency change under the short-time Fourier transform is significantly different from the normal state (p<0.05). The results illustrate that the ECS-based wearable device can assess immediate responses to abnormal intracranial blood supply and distinguish different intracranial overall CBF levels effectively.

Acute cerebral ischemia is an important clinical disease that is usually detected by magnetic resonance imaging or computed tomography. The magnetic inductive phase shift (MIPS) is a new method for detecting cerebral diseases, which is non-invasive, miniaturized, and low-cost. A total of 25 rabbits were studied using a two-coil sensor with a 0.3-200 MHz frequency range, and all the subjects were measured for 1 hour. Based on the rabbit acute cerebral ischemia model, the rabbits were divided into unilateral ligation, bilateral ligation, and non-ligation groups. The results showed that the average MIPS values of the non-ligation, unilateral ligation, and bilateral ligation group were -0.195 ± 0.079°, -4.873 ± 1.042°, and -9.165 ± 2.862° respectively. MIPS distinguished different severities of cerebral ischemia in rabbits with statistical significance (p <; 0.05). Laser Doppler flowmetry (LDF) was used as the gold standard for collecting cerebral blood flow data. The strong correlation between the LDF measurements and the phase shift suggested that the phase shift reflects blood flow changes in the brain. Overall, these results suggest that the MIPS detection method has the potential to provide early detection of global cerebral ischemia. Furthermore, this method effectively distinguished different severities of cerebral ischemia.