Latest ArticlesSuper-resolution imaging technology is an important technical means for demonstrating related physiological and pathological molecular phenomena, change processes and functional regulation in the field of neuroscience research. It breaks through the diffraction limit of traditional optical microscopes, enabling scientists to study biological structures and material details at the nanoscale. Various super-resolution technologies assist researchers in better exploring neuroscience from different aspects such as spatiotemporal resolution, three-dimensional tomography capabilities, and in vivo imaging capabilities, thereby analyzing the nanoscale distribution and dynamic changes of synaptic structures and neurotransmitter receptors, and providing key details for further research on neurodegenerative diseases. This article summarizes the phased development of super-resolution imaging technology in recent years, as well as the advantages and limitations of different technologies. It particularly introduces the application of super-resolution imaging technology in ultra-microstructure imaging of the nervous system, imaging of living animals, deep imaging of the brain, and related research on neurodegenerative diseases and drug development. It aims to provide references for their efficient and reasonable application in neuroscience research.
Optical coherence tomography (OCT) is a key technology for high-resolution biomedical imaging. Intraoperative handheld endoscopic OCT combines optical fiber communication with endoscopic technology. Based on the principle of low coherence interference, it uses a submillimeter miniaturized handheld probe (diameter≤1 mm) and flexible scanning mechanisms such as MEMS actuation and fiber vibration. Overcoming the penetration depth limitation of traditional OCT, it can obtain micron-level high-resolution structural images such as retinal stratification and vascular intima in turbid media such as blood and tissue fluid. Its clinical application widely covers ophthalmology (real-time navigation of vitreoretinal surgery), cardiology (vascular anastomosis evaluation), neurosurgery (deep brain tissue imaging) and breast tumor resection (microscopic margin assessment), etc. Through the integrated surgical instruments such as lateral or forward scanning probes and OCT surgical forceps, the operation and imaging can be synchronized and the blind area of the visual field can be eliminated. The current technology has challenges in narrow lumen adaptability and multimodal information fusion. The future development will focus on the development of submillimeter flexible probes, artificial intelligence-assisted lesion recognition, robot collaborative navigation, and the popularization of low-cost disposable devices, so as to promote its evolution to an intelligent surgical navigation system. This article briefly describes the current development status of intraoperative handheld endoscopic OCT, reviews its representative works in terms of system structure optimization and clinical application, and presents an outlook for its future development.
In vivo small animal imaging technology serves as a powerful tool for investigating tumor biology and evaluating anti-tumor therapeutic efficacy. This non-invasive modality enables real-time, dynamic observation of tumor initiation, progression, metastasis, and treatment response in living organisms, offering distinct advantages including visualizability, high spatiotemporal resolution, and exceptional sensitivity. Widely adopted in oncology research, this technology encompasses multimodal imaging approaches such as optical, nuclear medicine, and magnetic resonance imaging, each demonstrating unique characteristics and application scenarios. This article systematically summarizes three predominant in vivo small animal imaging techniques—optical 3D imaging, near-infrared fluorescence imaging, and 3D tomographic scanning, highlighting their respective technical advantages and application domains. Through presenting cutting-edge case studies in tumor mechanism research, metastasis monitoring, and therapeutic response assessment, this review aims to provide substantive references for advancing the application of in vivo small animal imaging in oncology research and anti-tumor treatment development.
Intravital two-photon imaging technology has the advantage of deep imaging, enabling the direct monitoring of the dynamic processes within living organisms. It has become an important research tool in the field of life sciences. We briefly explain the basic principles of two-photon microscopy and its applications in life science research in recent years. We mainly focuse on analyzing the development trends of intravital two-photon imaging technology and discuss the current challenges and future optimization directions. We look forward to the continuous optimization of intravital two-photon imaging technology, which can promote its wider application.
To meet the demand for portability and low cost to facilitate the widespread application of spectrometers, this paper presents the comparative analysis of different spectrometer types. Taking the crossed Czerny-Turner (C-T) optical path as a reference, we designed and implemented a portable fiber-optic spectrometer based on a crossed C-T structure. An orthogonal crossed dual spherical mirror configuration was adopted to compress the optical path dimensions, and a prototype system was constructed for experimental validation. Through optimized component selection, a low-cost spectrometer with high portability and strong functionality was developed. The prototype system underwent wavelength calibration, and its aberrations were briefly analyzed. Ultimately, the system achieves a spectral resolution of 1 nm within the 381～716 nm wavelength range. This design resolves the traditional trade-off between size and performance in fiber-optic spectrometers, demonstrating significant application value for rapid detection and real-time spectral analysis.
Intravital two-photon imaging technology has become an essential tool in life science research due to its ability to intuitively monitor the in vivo dynamic processes of living organisms. However, sample preparation has always been a major challenge in the application of this technology, and it directly determines the stability and quality of imaging. There is currently no systematic introduction to sample preparation for intravital two-photon imaging. Based on the rich practical experience accumulated in the laboratory over the years in the preparation of samples for intravital imaging, we mainly introduce the sample preparation procedures and key points of operation for tissues such as the lung, intestine, brain, liver, and skin. The aim is to provide a reference for sample preparation and operation before intravital two-photon imaging, assist researchers in mastering the operation of intravital two-photon imaging, and promote the broader application of this technology.
To develop a spatiotemporal hybrid perception deep learning (DL) model using contrast-enhanced ultrasound (CEUS) videos for diagnosis of hepatocellular carcinoma (HCC) in liver imaging reporting and data system (LI-RADS) category LR-M liver nodules.
This study conducted a retrospective analysis of patients diagnosed with LR-M nodules by CEUS from the First Affiliated Hospital of Sun Yat-sen University and the First Affiliated Hospital of Guangxi Medical University. Using pathological and comprehensive diagnostic results as the gold standard, the patients were categorized into HCC and non-HCC. A multi-scale spatiotemporal split-phase parallel feature extraction of CEUS video using R(2+1)D-18 convolutional neural network is used to construct a diagnostic model for HCC, and the information integrity and computational efficiency are balanced by a frame sampling strategy (15/30/45 frames), supplemented by gradient-weighted class activation mapping (Grad-CAM) visualisation to explain the decision basis. The diagnostic efficacy of the model is evaluated using accuracy, sensitivity, specificity, positive predictive value, negative predictive value and receiver operating characteristic (ROC) curve.
A total of 176 LR-M patients from the First Affiliated Hospital of Sun Yat-sen University were divided into training and validation sets in a 7:3 ratio, while 46 LR-M patients from the First Affiliated Hospital of Guangxi Medical University served as the test set. When using 45-frame videos as input, with sensitivities of 91.67% and 84.21%, specificities of 96.43% and 81.48%, and area under curves (AUCs) of 0.940 and 0.828 in the validation and test sets. The model had a higher detection rate of HCC compared with the alpha-fetoprotein (AFP) index (validation set: 50.00%, test set: 31.58%; both P value < 0.05), and the combined use of the DL model with AFP could optimize the overall diagnostic efficacy.
The DL model with CEUS spatiotemporal perception enables accurate diagnosis of HCC in LR-M category liver lesions, demonstrating significantly superior performance over AFP. Moreover, the combined diagnosis of the both can reduce unnecessary liver biopsy.
Exploring the challenges of artifact detection in endoscopic videos through the perspective of long-tailed learning.
Through analysis of artifact distribution characteristics in endoscopic videos from the public EAD2020 dataset, we develop a long-tailed endoscopic artifact detection algorithm via a decoupled framework. The proposed multi-expert system strategically partitions head and tail classes into two distinct subsets, with domain-specific experts processing each group separately. We innovatively design a hierarchical expert aggregation mechanism and further integrate visual prompts to enhance cross-group discrimination capabilities, ultimately achieving a significant improvement in artifact detection performance as measured by the comprehensive mean Average Precision (mAP) metric.
Benefiting from a more powerful backbone network and advanced classifier design, the proposed method achieves significant improvements in endoscopic video analysis: mAP for sequential video frame detection increases from 0.440 to 0.491, while mAP for individual video frame detection rises from 0.339 to 0.384. Notably, our approach comprehensively outperforms existing ensemble methods across all artifact categories.
The proposed multi-expert framework for long-tailed endoscopic video artifact detection achieves balanced performance across artifact categories through grouping and multi-expert methods. This architecture significantly enhances detection performance for tail classes while maintaining head class accuracy, effectively mitigating the inherent class imbalance problem. This study provides a novel direction for medical image detection tasks, particularly in data-imbalanced scenarios.
To develop a highly sensitive and selective electrochemical probe based on molecular imprinting polymers (MIPs) technology for the precise detection of 25-hydroxyvitamin D3 [25-(OH)D3], aiming to meet the diagnostic needs of vitamin D metabolism-related diseases.
The Co3O4@reduced graphene oxide (rGO)@Pt@Au composite substrate was constructed by layer-by-layer modification of screen-printed electrode (SPE) to enhance conductivity. Molecularly imprinted cavities were successfully formed through electropolymerization of polypyrrole and template molecule elution, imparting specific recognition capabilities. By optimizing the scan rate, deposition cycles, incubation time, and temperature, the balance between membrane structure, electron transfer efficiency, and specific binding ability was achieved. The sensor's response performance was evaluated using square wave voltammetry (SWV), and its sensitivity, selectivity, and reproducibility were analyzed.
Scanning electron microscopy (SEM) characterization revealed that after template elution, clear imprinted cavities were formed on the electrode surface, which could detect the target in the range of 100 nmol/L to 1 mmol/L, with a detection limit of 26.76 nmol/L. This detection strategy showed no specific response to interference at 10 times the concentration, and the reproducibility of the electrodes across three batches, with a relative standard deviation of 3.2%, indicated the reliability of the method. The spiked experiments also show its good practical application ability.
This study successfully established a new method with high sensitivity, strong anti-interference ability, and excellent reproducibility, providing a novel approach for the clinical detection of 25-(OH)D3.
To investigate the mechanism and effect of porous hollow iron oxide nanoparticles (HION) nanosensitizers (HION/VER) loaded with VER-155008 prepared to enhance the radiofrequency ablation on hepatocellular carcinoma tumors.
The construction of porous hollow iron oxide nanosensitizers and drug loading were investigated by transmission electron microscopy and zeta potential experiments. The in vitro anti-tumor ability of the sensitizers was examined by cell viability and cell live/dead staining experiments. The in vitro anti-tumor mechanism of the sensitizers was investigated by measuring the intracellular levels of reactive oxygen species (ROS), glutathione (GSH) and heat shock protein 70 (HSP70).
Through material characterization analysis, porous hollow iron oxide nanosensitizers have been successfully constructed with a particle size of about 100 nm. HION/VER reduced tumor cell survival to 50% at 56.89 μg/mL and 45℃. Live/dead staining assay further confirmed that a large number of tumor cells died, indicating that HION/VER has good anti-tumor ability in vitro. Analysis by reactive oxygen fluorescence probe and glutathione level showed that reactive oxygen fluorescence was significantly enhanced and GSH levels decreased, indicating that HION/VER nano-sensitizer could promote iron death through the mechanism of disrupting redox balance. Analyzed by HSP70 immunofluorescence assay, the cellular HSP70 expression was significantly reduced after HION/VER treatment, indicating that the nano-sensitizer increased the sensitivity of tumor cells to mild radiofrequency ablation by inhibiting HSP70.
After HION/VER was endocytosed by the tumor cells, the drug uptake in the cells was increased, and the inhibition of HSP70 increased the sensitivity of the tumor cells to mild radiofrequency ablation by disrupting the redox balance to enhance the iron death, and the effect of radiofrequency ablation was achieved by effectively increasing the sensitivity of the tumor cells to mild radiofrequency ablation.
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