3D Point Capsule Networks

In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence of our novel unified 3D auto-encoder formulation. Their dynamic routing scheme and the peculiar 2D latent space deployed by our approach bring in improvements for several common point cloud-related tasks, such as object classification, object reconstruction and part segmentation as substantiated by our extensive evaluations. Moreover, it enables new applications such as part interpolation and replacement.Comment: As published in CVPR 2019 (camera ready version), with supplementary materia

3D Point Capsule Networks

In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence of our novel unified 3D auto-encoder formulation. Their dynamic routing scheme and the peculiar 2D latent space deployed by our approach bring in improvements for several common point cloud-related tasks, such as object classification, object reconstruction and part segmentation as substantiated by our extensive evaluations. Moreover, it enables new applications such as part interpolation and replacement

Net volatilization of PAHs from the North Pacific to the Arctic Ocean observed by passive sampling

The North Pacific-Arctic Oceans are important compartments for semi-volatile organic compounds’ (SVOCs) global marine inventory, but whether they act as a “source or sink” remains controversial. To study the air-sea exchange and fate of SVOCs during their poleward long-range transport, low-altitude atmosphere and surface seawater were measured for polycyclic aromatic hydrocarbons (PAHs) by passive sampling from July to September in 2014. Gaseous PAH concentrations (0.67–13 ng m−3) were dominated by phenanthrene (Phe) and fluorene (Flu), which displayed an inverse correlation with latitude, as well as a significant linear relationship with partial pressure and inverse temperature. Concentrations of PAHs in seawater (1.8–16 ng L−1) showed regional characteristics, with higher levels near the East Asia and lower values in the Bering Strait. The potential impact from the East Asian monsoon was suggested for gaseous PAHs, which – similar to PAHs in surface seawater - were derived from combustion sources. In addition, the data implied net volatilization of PAHs from seawater into the air along the entire cruise; fluxes displayed a similar pattern to regional and monthly distribution of PAHs in seawater. Our results further emphasized that air-sea exchange is an important process for PAHs in the open marine environments

Prognostic and Predictive Value of Three DNA Methylation Signatures in Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the leading cause of cancer-related mortality worldwide. Molecular characterization-based methods hold great promise for improving the diagnostic accuracy and for predicting treatment response. The DNA methylation patterns of LUAD display a great potential as a specific biomarker that will complement invasive biopsy, thus improving early detection.Method: In this study, based on the whole-genome methylation datasets from The Cancer Genome Atlas (TCGA) and several machine learning methods, we evaluated the possibility of DNA methylation signatures for identifying lymph node metastasis of LUAD, differentiating between tumor tissue and normal tissue, and predicting the overall survival (OS) of LUAD patients. Using the regularized logistic regression, we built a classifier based on the 3616 CpG sites to identify the lymph node metastasis of LUAD. Furthermore, a classifier based on 14 CpG sites was established to differentiate between tumor and normal tissues. Using the Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we built a 16-CpG-based model to predict the OS of LUAD patients.Results: With the aid of 3616-CpG-based classifier, we were able to identify the lymph node metastatic status of patients directly by the methylation signature from the primary tumor tissues. The 14-CpG-based classifier could differentiate between tumor and normal tissues. The area under the receiver operating characteristic (ROC) curve (AUC) for both classifiers achieved values close to 1, demonstrating the robust classifier effect. The 16-CpG-based model showed independent prognostic value in LUAD patients.Interpretation: These findings will not only facilitate future treatment decisions based on the DNA methylation signatures but also enable additional investigations into the utilization of LUAD DNA methylation pattern by different machine learning methods

Stiffness of Substrate Influences the Distribution but not the Synthesis of Autophagosomes in Human Liver (LO2) Cells

Extracellular matrix (ECM) often becomes stiffer during tumor development, which not only gives the tumor's hardness feel but also actively contributes to the tumor formation. A good example is hepatocellular carcinoma (HCC) that usually develops within chronically stiffened liver tissues due to fibrosis and cirrhosis. On the other hand, HCC cells exhibit reduced autophagy in a malignancy dependent manner, suggesting autophagy is suppressed during tumor development. However, it is not known whether ECM stiffness would influence autophagy during tumor development. To investigate this issue, We cultured the human liver (LO2) cells that stably expressed autophagosome indicator LC3 on polydimethylsiloxane (PDMS) gels with stiffness varying from 11 to 1220 kPa. and on plastic cell culture dish as controls for up to 48h. We found that the total protein level of LC3-II in LO2 cells was not affected by the substrate stiffness. However the autophagosomes in LO2 cells cultured on the soft substrate (11 kPa PDMS gel) were localized and accumulated around the nucleus, while those on the stiff substrate (1220 kPa PDMS gel or plastic dish surface) were dispersed throughout the cytoplasmic space. Therefore, our data suggest that ECM stiffness may not directly synthesize nascent autophagosomes, but instead influence the location/translocation and ultimately distribution of autophagosomes in the cells

Inhibition of RhoA-Subfamily GTPases Suppresses Schwann Cell Proliferation Through Regulating AKT Pathway Rather Than ROCK Pathway

Inhibiting RhoA-subfamily GTPases by C3 transferase is widely recognized as a prospective strategy to enhance axonal regeneration. When C3 transferase is administered for treating the injured peripheral nerves, Schwann cells (SCs, important glial cells in peripheral nerve) are inevitably impacted and therefore SC bioeffects on nerve regeneration might be influenced. However, the potential role of C3 transferase on SCs remains elusive. Assessed by cell counting, EdU and water-soluble tetrazolium salt-1 (WST-1) assays as well as western blotting with PCNA antibody, herein we first found that CT04 (a cell permeable C3 transferase) treatment could significantly suppress SC proliferation. Unexpectedly, using Y27632 to inhibit ROCK (the well-accepted downstream signal molecule of RhoA subfamily) did not impact SC proliferation. Further studies indicated that CT04 could inactivate AKT pathway by altering the expression levels of phosphorylated AKT (p-AKT), PI3K and PTEN, while activating AKT pathway by IGF-1 or SC79 could reverse the inhibitory effect of CT04 on SC proliferation. Based on present data, we concluded that inhibition of RhoA-subfamily GTPases could suppress SC proliferation, and this effect is independent of conventional ROCK pathway but involves inactivation of AKT pathway