The Adversarial Attack and Detection under the Fisher Information Metric

Many deep learning models are vulnerable to the adversarial attack, i.e., imperceptible but intentionally-designed perturbations to the input can cause incorrect output of the networks. In this paper, using information geometry, we provide a reasonable explanation for the vulnerability of deep learning models. By considering the data space as a non-linear space with the Fisher information metric induced from a neural network, we first propose an adversarial attack algorithm termed one-step spectral attack (OSSA). The method is described by a constrained quadratic form of the Fisher information matrix, where the optimal adversarial perturbation is given by the first eigenvector, and the model vulnerability is reflected by the eigenvalues. The larger an eigenvalue is, the more vulnerable the model is to be attacked by the corresponding eigenvector. Taking advantage of the property, we also propose an adversarial detection method with the eigenvalues serving as characteristics. Both our attack and detection algorithms are numerically optimized to work efficiently on large datasets. Our evaluations show superior performance compared with other methods, implying that the Fisher information is a promising approach to investigate the adversarial attacks and defenses.Comment: Accepted as an AAAI-2019 oral pape

Bile dynamics within the biliary tract and microfluidic-based bile component detection: A review

Bilestones are solid masses found in the gallbladder or biliary tract, which block the normal bile flow and eventually result in severe life-threatening complications. Studies have shown that bilestone formation may be related to bile flow dynamics and the concentration level of bile components. The bile flow dynamics in the biliary tract play a critical role in disclosing the mechanism of bile stasis and transportation. The concentration of bile composition is closely associated with processes such as nucleation and crystallization. Recently, microfluidic-based biosensors have been favored for multiple advantages over traditional bench-top detection assays for their less sample consumption, portability, low cost, and high sensitivity for real-time detection. Here, we reviewed the developments in bile dynamics study and microfluidics-based bile component detection methods. These studies may provide valuable insights into the bilestone formation mechanisms and better treatment, alongside our opinions on the future development of in vitro lithotriptic drug screening of bilestones and bile characterization tests

Conserved roles of C. elegans and human MANFs in sulfatide binding and cytoprotection.

Mesencephalic astrocyte-derived neurotrophic factor (MANF) is an endoplasmic reticulum (ER) protein that can be secreted and protects dopamine neurons and cardiomyocytes from ER stress and apoptosis. The mechanism of action of extracellular MANF has long been elusive. From a genetic screen for mutants with abnormal ER stress response, we identified the gene Y54G2A.23 as the evolutionarily conserved C. elegans MANF orthologue. We find that MANF binds to the lipid sulfatide, also known as 3-O-sulfogalactosylceramide present in serum and outer-cell membrane leaflets, directly in isolated forms and in reconstituted lipid micelles. Sulfatide binding promotes cellular MANF uptake and cytoprotection from hypoxia-induced cell death. Heightened ER stress responses of MANF-null C. elegans mutants and mammalian cells are alleviated by human MANF in a sulfatide-dependent manner. Our results demonstrate conserved roles of MANF in sulfatide binding and ER stress response, supporting sulfatide as a long-sought lipid mediator of MANF's cytoprotection

CD8(+) T Cells Involved in Metabolic Inflammation in Visceral Adipose Tissue and Liver of Transgenic Pigs

Anti-inflammatory therapies have the potential to become an effective treatment for obesity-related diseases. However, the huge gap of immune system between human and rodent leads to limitations of drug discovery. This work aims at constructing a transgenic pig model with higher risk of metabolic diseases and outlining the immune responses at the early stage of metaflammation by transcriptomic strategy. We used CRISPR/Cas9 techniques to targeted knock-in three humanized disease risk genes, GIPR(dn) , hIAPP and PNPLA3(I148M) . Transgenic effect increased the risk of metabolic disorders. Triple-transgenic pigs with short-term diet intervention showed early symptoms of type 2 diabetes, including glucose intolerance, pancreatic lipid infiltration, islet hypertrophy, hepatic lobular inflammation and adipose tissue inflammation. Molecular pathways related to CD8(+) T cell function were significantly activated in the liver and visceral adipose samples from triple-transgenic pigs, including antigen processing and presentation, T-cell receptor signaling, co-stimulation, cytotoxicity, and cytokine and chemokine secretion. The similar pro-inflammatory signaling in liver and visceral adipose tissue indicated that there might be a potential immune crosstalk between the two tissues. Moreover, genes that functionally related to liver antioxidant activity, mitochondrial function and extracellular matrix showed distinct expression between the two groups, indicating metabolic stress in transgenic pigs' liver samples. We confirmed that triple-transgenic pigs had high coincidence with human metabolic diseases, especially in the scope of inflammatory signaling at early stage metaflammation. Taken together, this study provides a valuable large animal model for the clinical study of metaflammation and metabolic diseases.Peer reviewe

PM2.5 induced liver lipid metabolic disorders in C57BL/6J mice

PM2.5 can cause adverse health effects via several pathways, such as inducing pulmonary and systemic inflammation, penetration into circulation, and activation of the autonomic nervous system. In particular, the impact of PM2.5 exposure on the liver, which plays an important role in metabolism and detoxification to maintain internal environment homeostasis, is getting more attention in recent years. In the present study, C57BL/6J mice were randomly assigned and treated with PM2.5 suspension and PBS solution for 8 weeks. Then, hepatic tissue was prepared and identified by metabolomics analysis and transcriptomics analysis. PM2.5 exposure can cause extensive metabolic disturbances, particularly in lipid and amino acids metabolic dysregulation.128 differential expression metabolites (DEMs) and 502 differently expressed genes (DEGs) between the PM2.5 exposure group and control group were detected. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DEGs were significantly enriched in two disease pathways, non-alcoholic fatty liver disease (NAFLD) and type II diabetes mellitus (T2DM), and three signaling pathways, which are TGF-beta signaling, AMPK signaling, and mTOR signaling. Besides, further detection of acylcarnitine levels revealed accumulation in liver tissue, which caused restricted lipid consumption. Furthermore, lipid droplet accumulation in the liver was confirmed by Oil Red O staining, suggesting hepatic steatosis. Moreover, the aberrant expression of three key transcription factors revealed the potential regulatory effects in lipid metabolic disorders, the peroxisomal proliferative agent-activated receptors (PPARs) including PPARα and PPARγ is inhibited, and the activated sterol regulator-binding protein 1 (SREBP1) is overexpressed. Our results provide a novel molecular and genetic basis for a better understanding of the mechanisms of PM2.5 exposure-induced hepatic metabolic diseases, especially in lipid metabolism