Here, we report a novel polymeric nanoparticle prepared by the self-assembly of amphiphilic copolymers containing a fluorescent naphthalimide (NAPH) and a photochromic spiropyran (SP), which possesses reversibly photoswitchable dual-color fluorescence and controlled release properties. The amphiphilic copolymers were synthesized by incorporating NAPH and SP into methyl ether poly­(ethylene glycol)-poly­(β-amino esters) (MPEG-PAE) via quaternization. The nanoparticles would change between yellow and purple reversibly upon UV and visible light irradiation because of the photoisomerization between SP and merocyanine (MC). The corresponding fluorescence would be switched between green and orange-red reversibly upon blue light excitation through the fluorescence resonance energy transfer from the excited NAPH to the photoisomerized MC. Meanwhile, the prepared spherical nanoparticles could be swollen under UV irradiation as the hydrophobic SP isomerized to hydrophilic MC; the nanoparticles could also be swollen under acidic conditions because of the protonation of the amino groups of PAE. Upon UV light irradiation and acidic stimulation, the cargoes, hydrophobic Coumarin 102, encapsulated in the nanoparticles would be released. The prepared nanoparticles, which exhibit not only excellent reversible dual-color fluorescence properties but also prominent controlled release performance, will open up new possibilities for the combined application of fluorescence imaging and controlled release.

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Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal diseases. However, it is very time-consuming and fatiguing for a physician to review a large number of WCE images. Some methods to address this problem have recently been presented. However, these methods generally employ classification algorithms to discriminate abnormal from normal images, which do not localize, recognize, or detect abnormal patterns in abnormal images. We sought to identify a better method for the WCE abnormal pattern detection. In this paper, convolutional neural networks (CNNs) are used to implement detection function, and several methods are also adopted to boost the performance of WCE abnormality detection from aspects of the CNN architecture, region proposal, and transfer learning. First, we present a deep cascade network, namely, CascadeProposal, trained end-to-end to generate a small number of region proposals with high-recall by a region proposal rejection module and to simultaneously detect abnormal patterns using a detection module. Second, we use a multiregional combination (MRC) method to obtain good coverage of the regions of interest and employ the salient region segmentation (SRS) method to capture accurate region locations. Third, we use the dense region fusion (DRF) method for object boundary refinement. Fourth, we introduce negative category (Neg) and transfer learning (TL) strategies into our CNNs to obtain a better model performance. The extensive experiments are performed on our WCE image dataset of more than 7k annotated images. A final mean average precision (mAP) of 70.3% and a better mAP of 72.3% can be achieved via CascadeProposal with ZF and Fast R-CNN with VGG-16 networks, respectively, using MRC+Neg+TL method in the training stage and MRC+DRF+SRS method in the testing stage. The comprehensive results demonstrate that our method is efficient and effective for WCE abnormality detection with high-localization accuracy. INDEX TERMS Convolutional neural networks, medical image analysis, region proposal, transfer learning, wireless capsule endoscopy, WCE abnormality detection.

The antifungal agent voriconazole (VRC) exhibits extreme inter-individual and intra-individual variation in terms of its clinical efficacy and toxicity. Inflammation, as reflected by C-reactive protein (CRP) concentrations, significantly affects the metabolic ratio and trough concentrations of voriconazole. Bacteroides fragilis (B. fragilis) is an important component of the human intestinal microbiota. Clinical data have shown that B. fragilis abundance is comparatively higher in patients not presenting with adverse drug reactions, and inflammatory cytokine (IL-1β) levels are negatively correlated with B. fragilis abundance. B. fragilis natural product capsular polysaccharide A (PSA) prevents various inflammatory disorders. We tested the hypothesis that PSA ameliorates abnormal voriconazole metabolism by inhibiting inflammation. Germ-free animals were administered PSA intragastrically for 5 days after lipopolysaccharide (LPS) stimulation. Their blood and liver tissues were collected to measure VRC concentrations. PSA administration dramatically improved the resolution phase of LPS-induced hepatic VRC metabolism and inflammatory factor secretion. It reversed inflammatory lesions and alleviated hepatic pro-inflammatory factor secretion. Both in vitro and in vivo data demonstrate that PSA reversed LPS-induced IL-1β secretion, downregulated the TLR4/NF-κB signaling pathway and upregulated CYP2C19 and P-gp. To the best of our knowledge, this study is the first to show that PSA from the probiotic B. fragilis ameliorates abnormal voriconazole metabolism by inhibiting TLR4-mediated NF-κB transcription and regulating drug metabolizing enzyme and transporter expression. Thus, PSA could serve as a clinical adjunct therapy.