Amyotrophic lateral sclerosis (ALS) is a multi-system disease featured by movement disorder. Studies on ALS using static neuroimaging indexes demonstrated inconsistent results. However, recent work indicated that the intrinsic brain activity was time-varying, and the abnormal temporal dynamics of brain activity in ALS remains unknown. Resting-state functional magnetic resonance imaging data were first obtained from 54 patients with ALS and 54 healthy controls (HCs). Then the dynamic regional homogeneity (d-ReHo) was calculated and compared between the two groups. Correlation analyses between altered d-ReHo and clinical scores were further performed. Compared with HCs, ALS patients showed higher d-ReHo in the left lingual gyrus while lower d-ReHo in the left rectus gyrus and left parahippocampal gyrus. Moreover, the d-ReHo in the left lingual gyrus exhibited correlation with disease progression rate in ALS at a trend level. Our findings suggested that altered dynamics in intrinsic brain activity might be a potential biomarker for diagnosing of ALS.
Breast tumor segmentation is an important step in the diagnostic procedure of physicians and computer-aided diagnosis systems. We propose a two-step deep learning framework for breast tumor segmentation in breast ultrasound (BUS) images which requires only a few manual labels. The first step is breast anatomy decomposition handled by a semi-supervised semantic segmentation technique. The input BUS image is decomposed into four breast anatomical structures, namely fat, mammary gland, muscle and thorax layers. Fat and mammary gland layers are used as constrained region to reduce the search space for breast tumor segmentation. The second step is breast tumor segmentation performed in a weakly-supervised learning scenario where only image-level labels are available. Breast tumors are first recognized by a classification network and then segmented by the proposed class activation mapping and deep level set (CAM-DLS) method. For breast anatomy decomposition, the proposed framework achieves Dice similarity coefficient (DSC) of 83.0 ± 11.8%, 84.3 ± 10.0%, 80.7 ± 15.4% and 91.0 ± 11.4% for fat, mammary gland, muscle and thorax layers, respectively. For breast tumor recognition, the proposed framework achieves sensitivity of 95.8%, precision of 92.4%, specificity of 93.9%, accuracy of 94.8% and F1-score of 0.941. For breast tumor segmentation, the proposed framework achieves DSC of 77.3% and intersection-over-union (IoU) of 66.0%. In conclusion, the proposed framework could efficiently perform breast tumor recognition and segmentation simultaneously in a weakly-supervised setting with anatomical constraints. 相似文献
Brain Imaging and Behavior - Despite the fast growing interest in the impact of microbiome–gut–brain interaction on regulating emotional behavior in animals, the underlying mechanisms... 相似文献
To overcome the limiting antigenic repertoire of protein sub-units and the side effects of adjuvants applied in second generation vaccines, the present work combined in vitro and in vivo manipulations to develop biomaterials allowing natural antigen-loading and presentation in vitro and further activation of the immune response in vivo. 3-dimensional laser micro-textured implantable Si-scaffolds supported mouse macrophage adherence, allowed natural seeding with human serum albumin (antigen) and specific antibody and inflammatory cytokine production in vitro. Implantation of Si-scaffolds loaded with antigen-activated macrophages induced an inflammatory reaction along with antigen-specific antibody production in vivo, which could be detected even 30 days post implantation. Analysis of implant histology using scanning electron microscopy showed that Si-scaffolds could be stable for a 6-month period. Such technology leads to personalized implantable vaccines, opening novel areas of research and treatment. 相似文献
In this study, the response of Pu2Zr2O7 and La2Zr2O7 to electronic radiation is simulated, employing an ab initio molecular dynamics method. It is shown that Pu2Zr2O7 undergoes a crystalline-to-amorphous structural transition with 0.3% electronic excitation, while for La2Zr2O7, the structural amorphization occurs with 1.2% electronic excitation. During the microstructural evolution, the anion disorder further drives cation disorder and eventually results in the structural amorphization of Pu2Zr2O7 and La2Zr2O7. The difference in responses to electron radiation between Pu2Zr2O7 and La2Zr2O7 mainly results from the strong correlation effects between Pu 5f electrons and the smaller band gap of Pu2Zr2O7. These results suggest that Pu2Zr2O7 is less resistant to amorphization under local ionization rates that produce a low level of electronic excitation, since the level of the concentration of excited electrons is relatively low in Pu2Zr2O7. The presented results will advance the understanding of the radiation damage effects of zirconate pyrochlores. 相似文献