Carbon dots (CDs) are a new type of carbon nanomaterial that have unique physical and chemical properties, good biocompatibility, low toxicity, easy surface functionalization, making them widely used in biological...

Airway segmentation on CT scans is critical for pulmonary disease diagnosis and endobronchial navigation. Manual extraction of airway requires strenuous efforts due to the complicated structure and various appearance of airway. For automatic airway extraction, convolutional neural networks (CNNs) based methods have recently become the stateof-the-art approach. However, there still remains a challenge for CNNs to perceive the tree-like pattern and comprehend the connectivity of airway. To address this, we propose a voxel-connectivity aware approach named AirwayNet for accurate airway segmentation. By connectivity modeling, conventional binary segmentation task is transformed into 26 tasks of connectivity prediction. Thus, our AirwayNet learns both airway structure and relationship between neighboring voxels. To take advantage of context knowledge, lung distance map and voxel coordinates are fed into AirwayNet as additional semantic information. Compared to existing approaches, AirwayNet achieved superior performance, demonstrating the effectiveness of the network's awareness of voxel connectivity.Pulmonary diseases, including chronic obstructive pulmonary diseases (COPD) and lung cancer, pose high risks to human health. The standard computed tomography (CT) helps radiologists detect pathological changes. For tracheal and bronchial surgery, airway tree modeling on CT scans is often considered a prerequisite. Meticulous efforts are required to manually segment airway due to its tree-like structure and variety in size, shape, and intensity. ⋆ Corresponding author: Jie Yang.

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Many techniques and strategies, such as positron emission tomography, magnetic resonance imaging, and immunohistochemistry, have been explored to diagnose tumors efficiently. [3][4][5] Among them, due to the advantages of high sensitivity, simplicity, and noninvasiveness, fluorescence molecular imaging has become a promising approach that enables detecting and visualizing the tumorrelated biomarkers in vivo. [6][7][8][9] However, tumor microenvironment (TME), as a complex system that consist of tumor cells, nearby interstitial tissues, capillaries, and various cytokines, always exhibits aberrant physiologic conditions such as low concentration of oxygen (hypoxia), acidic pH and increased interstitial fluid pressure, was still an obstacle for accurate fluorescence molecular imaging of tumor cells. [10][11][12][13][14] Accurate imaging of the dynamic changes in TME allows for the early detection of tumor and noninvasive assessment during tumor development and proliferation, and thus facilitates employing personalized therapies to improve patient survival. [15,16] To this goal, great achievements have been made to characterize dynamic changes of molecular signatures in TME. [17][18][19][20] Stimulus-responsive fluorescence imaging modality shows great promise for detection of tumor due to the advantages of high sensitivity, simplicity and noninvasiveness. However, some non-cancer regions including nodules and inflammation may also exhibit a stimulus-related characteristic, which cause the problem of nonspecific responsiveness and then cause "false positive" results for tumor recognition. Herein, hypoxia and acidic pH, two typical features strongly associated with tumor invasion, progression and metastasis in tumor microenvironment (TME), are chosen as dual stimuli to fabricate "dual lock-and-key" fluorescent nanoprobe for highly specific and precise imaging of tumor cells. Mesoporous silica coated gold nanorods (AuNR@ mSiO 2 ) are employed as nanocarrier and nanoquencher to load the pH-sensitive fluorescent reporter (Rho-TP). Azobenzene (azo) which can be reduced to amines by the highly expressed azoreductase under hypoxic conditions, is elected as the effective gatekeeper for AuNR@mSiO 2 by forming complex with β-cyclodextrin polymer via host-guest interaction (azo/β-CDP). By elaborately combining the hypoxia-responsive gatekeeper and pH-responsive fluorescent signal reporter into one nanoprobe, sensitive and specific imaging of tumor cells can be realized. The fabricated dual lock-and-key fluorescent nanoprobe successfully further apply in tumor-bearing mice model, which indicate potential of early diagnosis and assessment of cancer treatment.

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