MetaViewer: Towards A Unified Multi-View Representation

Existing multi-view representation learning methods typically follow a specific-to-uniform pipeline, extracting latent features from each view and then fusing or aligning them to obtain the unified object representation. However, the manually pre-specify fusion functions and view-private redundant information mixed in features potentially degrade the quality of the derived representation. To overcome them, we propose a novel bi-level-optimization-based multi-view learning framework, where the representation is learned in a uniform-to-specific manner. Specifically, we train a meta-learner, namely MetaViewer, to learn fusion and model the view-shared meta representation in outer-level optimization. Start with this meta representation, view-specific base-learners are then required to rapidly reconstruct the corresponding view in inner-level. MetaViewer eventually updates by observing reconstruction processes from uniform to specific over all views, and learns an optimal fusion scheme that separates and filters out view-private information. Extensive experimental results in downstream tasks such as classification and clustering demonstrate the effectiveness of our method.Comment: 8 pages, 5 figures, conferenc

A Dynamic Feature Interaction Framework for Multi-task Visual Perception

Multi-task visual perception has a wide range of applications in scene understanding such as autonomous driving. In this work, we devise an efficient unified framework to solve multiple common perception tasks, including instance segmentation, semantic segmentation, monocular 3D detection, and depth estimation. Simply sharing the same visual feature representations for these tasks impairs the performance of tasks, while independent task-specific feature extractors lead to parameter redundancy and latency. Thus, we design two feature-merge branches to learn feature basis, which can be useful to, and thus shared by, multiple perception tasks. Then, each task takes the corresponding feature basis as the input of the prediction task head to fulfill a specific task. In particular, one feature merge branch is designed for instance-level recognition the other for dense predictions. To enhance inter-branch communication, the instance branch passes pixel-wise spatial information of each instance to the dense branch using efficient dynamic convolution weighting. Moreover, a simple but effective dynamic routing mechanism is proposed to isolate task-specific features and leverage common properties among tasks. Our proposed framework, termed D2BNet, demonstrates a unique approach to parameter-efficient predictions for multi-task perception. In addition, as tasks benefit from co-training with each other, our solution achieves on par results on partially labeled settings on nuScenes and outperforms previous works for 3D detection and depth estimation on the Cityscapes dataset with full supervision.Comment: Accepted by International Journal of Computer Vision. arXiv admin note: text overlap with arXiv:2011.0979

HDL Subclass Proteomic Analysis and Functional Implication of Protein Dynamic Change During HDL Maturation

Recent clinical trials reported that increasing high-density lipoprotein-cholesterol (HDL-C) levels does not improve cardiovascular outcomes. We hypothesize that HDL proteome dynamics determine HDL cardioprotective functions. In this study, we characterized proteome profiles in HDL subclasses and established their functional connection. Mouse plasma was fractionized by fast protein liquid chromatography, examined for protein, cholesterial, phospholipid and trigliceride content. Small, medium and large (S/M/L)-HDL subclasseses were collected for proteomic analysis by mass spectrometry. Fifty-one HDL proteins (39 in S-HDL, 27 in M-HDL and 29 in L-HDL) were identified and grouped into 4 functional categories (lipid metabolism, immune response, coagulation, and others). Eleven HDL common proteins were identified in all HDL subclasses. Sixteen, 3 and 7 proteins were found only in S-HDL, M-HDL and L-HDL, respectively. We established HDL protein dynamic distribution in S/M/L-HDL and developed a model of protein composition change during HDL maturation. We found that cholesterol efflux and immune response are essential functions for all HDL particles, and amino acid metabolism is a special function of S-HDL, whereas anti-coagulation is special for M-HDL. Pon1 is recruited into M/L-HDL to provide its antioxidative function. ApoE is incorporated into L-HDL to optimize its cholesterial clearance function. Next, we acquired HDL proteome data from Pubmed and identified 12 replicated proteins in human and mouse HDL particle. Finally, we extracted 3 shared top moleccular pathways (LXR/RXR, FXR/RXR and acute phase response) for all HDL particles and 5 top disease/bio-functions differentially related to S/M/L-HDL subclasses, and presented one top net works for each HDL subclass. We conclude that beside their essencial functions of cholesterol efflux and immune response, HDL aquired antioxidative and cholesterol clearance functions by recruiting Pon1 and ApoE during HDL maturation

MRI of neurosyphilis presenting as brain tumor: A case report

Syphilis has a broad spectrum of clinical manifestations, among which cerebral gumma is a kind of neurosyphilis. However, it is rare and can be cured by penicillin. We report a case of syphilitic gumma of which the patient was first suspected of brain tumor, but confirmed by surgery to be cerebral gumma due to neurosyphilis. Magnetic resonance imaging, which is thought to be one of the potential and specific diagnostic methods for neurosyphilis, is discussed

The efficacy and safety of anti-CD19/CD20 chimeric antigen receptor- T cells immunotherapy in relapsed or refractory B-cell malignancies:a meta-analysis

Abstract Background Chimeric antigen receptor T (CAR T) cells immunotherapy is rapidly developed in treating cancers, especially relapsed or refractory B-cell malignancies. Methods To assess the efficacy and safety of CAR T therapy, we analyzed clinical trials from PUBMED and EMBASE. Results Results showed that the pooled response rate, 6-months and 1-year progression-free survival (PFS) rate were 67%, 65.62% and 44.18%, respectively. We observed that received lymphodepletion (72% vs 44%, P = 0.0405) and high peak serum IL-2 level (85% vs 31%, P = 0.04) were positively associated with patients’ response to CAR T cells. Similarly, costimulatory domains (CD28 vs CD137) in second generation CAR T was positively associated with PFS (52.69% vs 33.39%, P = 0.0489). The pooled risks of all grade adverse effects (AEs) and grade ≥ 3 AEs were 71% and 43%. Most common grade ≥ 3 AEs were fatigue (18%), night sweats (14%), hypotension (12%), injection site reaction (12%), leukopenia (10%), anemia (9%). Conclusions In conclusion, CAR T therapy has promising outcomes with tolerable AEs in relapsed or refractory B-cell malignancies. Further modifications of CAR structure and optimal therapy strategy in continued clinical trials are needed to obtain significant improvements

The Complex of Phycobiliproteins, Fucoxanthin, and Krill Oil Ameliorates Obesity through Modulation of Lipid Metabolism and Antioxidants in Obese Rats

Phycobiliproteins, fucoxanthin, and krill oil are natural marine products with excellent activities. In the study, we prepared the complex of phycobiliproteins, fucoxanthin, and krill oil (PFK) and assessed the anti-obesity, lipid-lowering, and antioxidant activities in high-fat diet rats. The results showed that the rats significantly and safely reduced body weight gain and regulated serum biochemical parameters at 50 mg/kg phycobiliproteins, 10 mg/kg fucoxanthin, and 100 mg/kg krill oil. Furthermore, the molecular mechanism study suggested that the complex of PFK confined the enzyme activities of lipid synthesis and enhanced antioxidant activity to improve obesity indirectly. The conclusions demonstrated that the complex of PFK has potent anti-obesity and hypolipidemic effects which have potential use as a natural and healthy food and medicine for anti-obesity and lowering blood lipids in the future