PartCom: Part Composition Learning for 3D Open-Set Recognition

3D recognition is the foundation of 3D deep learning in many emerging fields, such as autonomous driving and robotics.Existing 3D methods mainly focus on the recognition of a fixed set of known classes and neglect possible unknown classes during testing. These unknown classes may cause serious accidents in safety-critical applications, i.e. autonomous driving. In this work, we make a first attempt to address 3D open-set recognition (OSR) so that a classifier can recognize known classes as well as be aware of unknown classes. We analyze open-set risks in the 3D domain and point out the overconfidence and under-representation problems that make existing methods perform poorly on the 3D OSR task. To resolve above problems, we propose a novel part prototype-based OSR method named PartCom. We use part prototypes to represent a 3D shape as a part composition, since a part composition can represent the overall structure of a shape and can help distinguish different known classes and unknown ones. Then we formulate two constraints on part prototypes to ensure their effectiveness. To reduce open-set risks further, we devise a PUFS module to synthesize unknown features as representatives of unknown samples by mixing up part composite features of different classes. We conduct experiments on three kinds of 3D OSR tasks based on both CAD shape dataset and scan shape dataset. Extensive experiments show that our method is powerful in classifying known classes and unknown ones and can attain much better results than SOTA baselines on all 3D OSR tasks. The project will be released

Comparative Proteomic Analysis of Liver Tissues and Serum in db/db Mice

Background and Aims: Non-alcoholic fatty liver disease (NAFLD) affects one-quarter of individuals worldwide. Liver biopsy, as the current reliable method for NAFLD evaluation, causes low patient acceptance because of the nature of invasive sampling. Therefore, sensitive non-invasive serum biomarkers are urgently needed. Results: The serum gene ontology (GO) classification and Kyoto encyclopedia of genes and genomes (KEGG) analysis revealed the DEPs enriched in pathways including JAK-STAT and FoxO. GO analysis indicated that serum DEPs were mainly involved in the cellular process, metabolic process, response to stimulus, and biological regulation. Hepatic proteomic KEGG analysis revealed the DEPs were mainly enriched in the PPAR signaling pathway, retinol metabolism, glycine, serine, and threonine metabolism, fatty acid elongation, biosynthesis of unsaturated fatty acids, glutathione metabolism, and steroid hormone biosynthesis. GO analysis revealed that DEPs predominantly participated in cellular, biological regulation, multicellular organismal, localization, signaling, multi-organism, and immune system processes. Protein-protein interaction (PPI) implied diverse clusters of the DEPs. Besides, the paralleled changes of the common upregulated and downregulated DEPs existed in both the liver and serum were validated in the mRNA expression of NRP1, MUP3, SERPINA1E, ALPL, and ALDOB as observed in our proteomic screening. Methods: We conducted hepatic and serum proteomic analysis based on the leptin-receptor-deficient mouse (db/db), a well-established diabetic mouse model with overt obesity and NAFLD. The results show differentially expressed proteins (DEPs) in hepatic and serum proteomic analysis. A parallel reaction monitor (PRM) confirmed the authenticity of the selected DEPs. Conclusion: These results are supposed to offer sensitive non-invasive serum biomarkers for diabetes and NAFLD

Bromodomain-containing protein 4 activates androgen receptor transcription and promotes ovarian fibrosis in PCOS

Summary: Polycystic ovary syndrome (PCOS) is an endocrine disorder and the main cause of anovulatory infertility, in which persistent activation of androgen receptor (AR) due to aberrant acetylation modifications of transcription is a potential trigger; however, the precise mechanisms of AR activation are poorly understood. In this study, AR activation in dehydroepiandrosterone- and letrozole-induced rat PCOS ovaries coincided with a marked increase of a chromatin acetylation “reader” BRD4. Further bioinformatic analysis showed that the AR promoter contained highly conserved binding motifs of BRD4 and HIF-1α. BRD4 and HIF-1α inducibly bound to the histone 3/4 acetylation-modified AR promoter, while administration of a BRD4-selective inhibitor JQ1 reduced the binding and AR transcription and improved the adverse expression of the core fibrotic mediators in PCOS ovaries and DHT-treated granulosa cells. Our data indicate that BRD4 upregulation and the resultant AR transcriptional activation constitute an important regulatory pathway that promotes ovarian fibrosis in PCOS

Comparative study on CO_2 sources in soil developed on carbonate rock and non-carbonate rock in Central Guizhou

In this paper, by using concentration and carbon stable isotope the CO2 sources of soil profiles developed on limestone, dolostone and claystone basements in Central Guizhou, China are comparatively studied. The results show that CO2 concentration of soil profiles developed on different basements is different, having the following sequence: limestone ; dolostone;claystone. Below the soil depth of 20 cm from the surface the δ13 value of CO2 in soil profile developed on limestone ranges from -12.811%. - -13.492%.(PDB), that in soil profile developed on dolostone varys from -13.212%. - -14.271%.(PDB) and that in soil profile developed on claystone is about-20.234%. - -21.485%.(PDB). Taking the carbon isotope of soil organic matter and carbonate rock as two isotopic endmembers, the proportion of soil CO2 generated by dissolution of carbonate rock is calculated, about 21%–25% for soil profile developed on limestone basement, 19%–21% for soil profile developed on dolostone basement. There is almost no influx of CO2 generated by the dissolution of carbonate rock in soil profile developed on claystone basement