Imaging tumors in their early stages is crucial to increase the surviving rate of cancer patients. Currently most fluorescence probes visualize the neoplasia by targeting the tumor‐associated receptor over‐expressed on the cancer cell membrane. However, the expression level of these receptors in vivo is hard to predict, which limits their clinical translation. Furthermore, the signal output of these receptor‐targeting probes usually stays at a high level, which leads to a strong background signal in normal tissue due to non‐specific binding. In contrast to receptors, characteristics of the tumor microenvironment – such as acidosis – are pervasive in almost all solid tumors and can be easily accessed. In this work, a novel biodegradable nanoprobe InNP1 that demonstrates pH‐activated near‐infrared (NIR) fluorescence in both human glioblastoma U87MG cancer cells in vitro and the subcutaneous U87MG tumor xenografts in vivo is developed. Bio‐distribution, in vivo optical imaging, and autoradiography studies demonstrate that the pH‐activated NIR fluorescence is the dominant factor responsible for the high tumor/normal tissue (T/N) ratio of InNP1 in vivo. Overall, the work provides a nanoprobe prototype to visualize the solid tumor in vivo with high sensitivity and minimal systemic toxicity by sensing the tumor acidic microenvironment. 相似文献
This study reveals the mechanism of the dual‐emission properties for asymmetrical diphenylsulfone and diphenylketone derivatives. A series of asymmetrical diphenylketone and diphenylsulfone derivatives with dual‐emission properties are designed and synthesized. By single crystal structure analyses, various photophysical studies, and 2D 1H–1H NOSEY NMR studies, the lower energy emission bands in the dual‐emission spectra are successfully assigned to hydrogen‐bonding‐assisted intermolecular charge transfer emission. The emission properties of these compounds can easily be tuned in both solid state and solution state by destroying or strengthening the intermolecular hydrogen bonding. In addition, thermally activated delayed fluorescence characteristics for the intermolecular charge transfer emissions are also observed. The control of the intermolecular and intramolecular charge transfers serves as the basis for the generation of the white‐light emission. For compound CPzPO, nearly pure white‐light emission with CIE coordinates of (0.31, 0.32) is easily achieved by precipitation from dichloromethane and hexane mixed solvent system. These results clearly give an insight into the dual‐emission properties and provide a rational strategy for the design and synthesis of single‐component white‐light‐emitting materials and mechanoresponsive light‐emitting materials. 相似文献
Sensor-based activity recognition (AR) depends on effective feature representation and classification. However, many recent studies focus on recognition methods, but largely ignore feature representation. Benefitting from the success of Convolutional Neural Networks (CNN) in feature extraction, we propose to improve the feature representation of activities. Specifically, we use a reversed CNN to generate the significant data based on the original features and combine the raw training data with significant data to obtain to enhanced training data. The proposed method can not only train better feature extractors but also help better understand the abstract features of sensor-based activity data. To demonstrate the effectiveness of our proposed method, we conduct comparative experiments with CNN Classifier and CNN-LSTM Classifier on five public datasets, namely the UCIHAR, UniMiB SHAR, OPPORTUNITY, WISDM, and PAMAP2. In addition, we evaluate our proposed method in comparison with traditional methods such as Decision Tree, Multi-layer Perceptron, Extremely randomized trees, Random Forest, and k-Nearest Neighbour on a specific dataset, WISDM. The results show our proposed method consistently outperforms the state-of-the-art methods.