Feature-aided pose estimation approach based on variational auto-encoder structure for spacecrafts

Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yielded impressive achievements for spacecraft pose estimation.To improve the robustness and interpretability of CNNs,this paper proposes a Pose Estimation approach based on Variational Auto-Encoder structure(PE-VAE)and a Feature-Aided pose estimation approach based on Variational Auto-Encoder structure(FA-VAE),which aim to accurately estimate the 6 DoF pose of a target spacecraft.Both methods treat the pose vector as latent variables,employing an encoder-decoder network with a Variational Auto-Encoder(VAE)structure.To enhance the precision of pose estimation,PE-VAE uses the VAE structure to introduce reconstruction mechanism with the whole image.Furthermore,FA-VAE enforces feature shape constraints by exclusively reconstructing the segment of the target spacecraft with the desired shape.Comparative evaluation against leading methods on public datasets reveals similar accuracy with a threefold improvement in processing speed,showcasing the significant contribution of VAE structures to accuracy enhancement,and the additional benefit of incorporating global shape prior features.

Leptin-mediated suppression of lipoprotein lipase cleavage enhances lipid uptake and facilitates lymph node metastasis in gastric cancer

Background:Lymph node metastasis(LNM)is the primary mode of metastasis in gastric cancer(GC).However,the precise mechanisms underlying this process remain elusive.Tumor cells necessitate lipid metabolic reprogramming to facilitate metastasis,yet the role of lipoprotein lipase(LPL),a pivotal enzyme involved in exogenous lipid uptake,remains uncertain in tumor metastasis.Therefore,the aim of this study was to investigate the presence of lipid metabolic reprogramming during LNM of GC as well as the role of LPL in this process.Methods:Intracellular lipid levels were quantified using oil red O staining,BODIPY 493/503 staining,and flow cytometry.Lipidomics analysis was employed to identify alterations in intracellular lipid composition following LPL knockdown.Protein expression levels were assessed through immunohistochemistry,Western blotting,and enzyme-linked immunosorbent assays.The mouse popliteal LNM model was utilized to investigate differences in LNM.Immunoprecipitation and mass spectrometry were employed to examine protein associations.In vitro phosphorylation assays and Phos-tag sodium dodecyl-sulfate polyacrylamide gel electrophoresis assays were conducted to detect angiopoietin-like protein 4(ANGPTL4)phosphorylation.Results:We identified that an elevated intracellular lipid level represents a crucial characteristic of node-positive(N+)GC and further demonstrated that a high-fat diet can expedite LNM.LPL was found to be significantly overexpressed in N+GC tissues and shown to facilitate LNM by mediating dietary lipid uptake within GC cells.Leptin,an obesity-related hormone,intercepted the effect exerted by ANGPTL4/Furin on LPL cleavage.Circulating leptin binding to the leptin receptor could induce the activation of inositol-requiring enzyme-1(IRE1)kinase,leading to the phosphorylation of ANGPTL4 at the serine 30 residue and subsequently reducing its binding affinity with LPL.Moreover,our research revealed that LPL disrupted lipid homeostasis by elevating intracellular levels of arachidonic acid,which then triggered the cyclooxygenase-2/prostaglandin E2(PGE2)pathway,thereby promoting tumor lymphangiogenesis.Conclusions:Leptin-induced phosphorylation of ANGPTL4 facilitates LPLmediated lipid uptake and consequently stimulates the production of PGE2,ultimately facilitating LNM in GC.