Adversarial attacks on graph classification via Bayesian optimisation

Graph neural networks, a popular class of models effective in a wide range of graph-based learning tasks, have been shown to be vulnerable to adversarial attacks. While the majority of the literature focuses on such vulnerability in node-level classification tasks, little effort has been dedicated to analysing adversarial attacks on graph-level classification, an important problem with numerous real-life applications such as biochemistry and social network analysis. The few existing methods often require unrealistic setups, such as access to internal information of the victim models, or an impractically-large number of queries. We present a novel Bayesian optimisation-based attack method for graph classification models. Our method is black-box, query-efficient and parsimonious with respect to the perturbation applied. We empirically validate the effectiveness and flexibility of the proposed method on a wide range of graph classification tasks involving varying graph properties, constraints and modes of attack. Finally, we analyse common interpretable patterns behind the adversarial samples produced, which may shed further light on the adversarial robustness of graph classification models. An open-source implementation is available at https://github.com/xingchenwan/grabnel

Analysis of the clinicopathological characteristics and prognosis of triple-positive breast cancer and HER2-positive breast cancer—A retrospective study

BackgroundAdjuvant chemotherapy and targeted therapy have become standard postoperative therapeutic modalities for human epidermal growth factor receptor 2 (HER2)-positive breast cancer(HER2-positive,HR-negative), including triple-positive breast cancer(HER2-positive,HR-positive). However, these two types of breast cancer differ in terms of pathogenesis. This article analyzes these two types of breast cancer by comparing their prognoses.MethodsThe clinicopathological characteristics of 135 patients, including 60 patients with triple-positive breast cancer and 75 patients with HER2-positive breast cancer, were analyzed to compare the disease-free survival (DFS) and overall survival (OS) of the two groups over a 5-year period. A multifactorial Cox risk model was constructed by grouping age, menstrual status, maximum tumor diameter, number of lymph node metastases, pathological staging, and Ki-67 staining results. All statistical data were analyzed in detail using SPSS25.0 statistical software.ResultsThe 5-year OS rates of patients with breast cancer in the triple-positive and HER2-positive groups were 96.7% and 82.7%, respectively, and the 5-year DFS rates were 90% and 73.3%, respectively. The Cox results revealed that molecular staging was an independent factor affecting recurrent metastasis and survival of breast cancer patients (hazard ratio [HR] =2.199, 95% confidence interval [CI], 1.296-8.266; HR = 9.994, 95% CI, 2.019-49.465).ConclusionThe 5-year DFS and OS rates were significantly better in the triple-positive group than in the HER2-positive group. Subgroups received different prognosis for different chemotherapy regimens. Breast cancer patients should be treated according to the risk of recurrence with symptomatic treatment and precise regulation

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

Epigenetic regulation of gene expression by BRD4 in cancer and innate immune response

Epigenetic regulation of gene expression plays essential roles in controlling normal cellular functions as well as abnormal cellular activities in human diseases like inflammatory diseases and cancers. The bromodomain-containing protein 4 (BRD4), one of the BET (bromodomain and extra terminal) family proteins, represents a class of epigenetic readers that regulate gene transcription by binding to acetylated lysine of histone and non-histone proteins via their bromodomains (BDs). This interaction either changes the availabilities of cis-regulatory elements by altering chromatin compacity or activates specific transcription factors, both of which contribute to transcriptional activation of BRD4’s target genes. BRD4 has been implicated in the dysregulated transcription of oncogenes and inflammatory genes during disease progression; thus, the small molecule inhibitors that target the bromodomains of BRD4, as well as other BET family proteins, are under clinical investigations. Gastric cancer has become one of the leading malignancies that cause death with a 5-year survival rate of 10%. Although BET inhibitors (BETis) have shown potential therapeutic effects against gastric cancer, the detailed mechanism by which BRD4 facilities gastric cancer cell proliferation remains elusive. In an effort to understand the contribution of BET to gastric cancer development, we confirmed that BRD4 was overexpressed in gastric cancer patient tissues compared to normal tissue. Meanwhile, BET inhibitor JQ1 inhibited multiple gastric cancer cell proliferation by inducing BRD4-dependent cellular senescence. Depletion of BRD4, but not other BET proteins, recapitulated JQ1-induced cellular senescence with increased cellular SA--Galactose activity and elevated p21 levels. BRD4 inhibited p21 expression at the post-transcriptional level through activating the transcription of miR-106b-5p, which targets the 3’-UTR of p21 mRNA. Overexpression of miR-106b-5p prevented JQ1-induced p21 expression and BRD4 inhibition-associated cellular senescence, whereas miR-106b-5p inhibitor upregulated p21 and induced cellular senescence. Finally, we demonstrated that inhibition of E2F suppressed the binding of BRD4 to the promoter of miR-106b-5p and inhibited its transcription, leading to the increased p21 levels and cellular senescence in gastric cancer cells. Our results reveal a novel mechanism by which BRD4 regulates cancer cell proliferation by modulating the cellular senescence through the E2F/miR-106b-5p/p21 axis and provide new insights into using BET inhibitors as potential anti-cancer drugs. Other than its critical role in facilitating tumor cell proliferation, BRD4 has also been investigated in the dysregulated cytokine production at the transcriptional level during inflammatory disease progression. BRD4 has been shown to activate NF-B-dependent inflammatory gene expression by binding to acetylated RelA subunit of NF-B through its bromodomains, highlighting its essential role in transcriptional regulation of cytokine production. Although the production of inflammatory cytokines is heavily regulated at the transcriptional level, a group of functional cytokines, such as interleukin-1 (IL-1) and IL-18, require post-translational maturation mediated by the activation of the inflammasome complex. In order to study the comprehensive role of BRD4 in cytokine production, we seek to investigate if BRD4 plays a role in regulating inflammasome activation and cytokine maturation. Using Salmonella enterica serovar Typhimurium (S. Typhimurium) as a NLRC4 inflammasome activator, we found that Brd4-deficient bone marrow-derived macrophages (BMDMs) displayed blunted NLRC4 inflammasome activation with decreased caspase-1 activation, Asc oligomerization, IL-1 maturation, gasdermin-D (Gsdmd) cleavage, and pyroptosis upon bacterial infection. RNA-seq results unveiled that the ablation of Brd4 in BMDMs suppressed the transcription of Naips and Nlrc4. Mechanistically, ChIP-seq analysis revealed that Brd4 co-localized with Irf8 and Pu.1 at the promoter regions of Naips, activating their transcriptions. Moreover, myeloid lineage-specific Brd4 conditional-knockout (Brd4-CKO) mice were more sensitive to S. Typhimurium infection with the significantly enhanced bacterial burden and tissue damages. Altogether, our findings emphasize the unexpected role of Brd4 in NLRC4 inflammasome activation through modulating the transcription of Naips and Nlrc4. ¬¬ In summary, BRD4, as an epigenetic reader, activates the transcription of diverse sets of genes through engaging distinct transcription factors in the cell context- and disease-dependent manner. In the gastric cancer cells, BRD4 controls cancer cell proliferation by modulating the cellular senescence through the E2F/miR-106b-5p/p21 axis. Meanwhile, in the innate immune response, Brd4 engages Irf8 and Pu.1 in maintaining the transcription of Naips and Nlrc4, which confers a prompt inflammasome activation against invading pathogens. Of note, mechanistically, BRD4’s transcriptional activities highly, but not exclusively, depend on the interaction between its bromodomains and acetylated lysine on histone or transcription factors, which supports the clinical investigations using BETis as anti-cancer and -inflammatory disease drugs.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste

Gas Sensitivity and Sensing Mechanism Studies on Au-Doped TiO2 Nanotube Arrays for Detecting SF6 Decomposed Components

The analysis to SF6 decomposed component gases is an efficient diagnostic approach to detect the partial discharge in gas-insulated switchgear (GIS) for the purpose of accessing the operating state of power equipment. This paper applied the Au-doped TiO2 nanotube array sensor (Au-TiO2 NTAs) to detect SF6 decomposed components. The electrochemical constant potential method was adopted in the Au-TiO2 NTAs’ fabrication, and a series of experiments were conducted to test the characteristic SF6 decomposed gases for a thorough investigation of sensing performances. The sensing characteristic curves of intrinsic and Au-doped TiO2 NTAs were compared to study the mechanism of the gas sensing response. The results indicated that the doped Au could change the TiO2 nanotube arrays’ performances of gas sensing selectivity in SF6 decomposed components, as well as reducing the working temperature of TiO2 NTAs

A DFT Calculation of Fluoride-Doped TiO2 Nanotubes for Detecting SF6 Decomposition Components

Gas insulated switchgear (GIS) plays an important role in the transmission and distribution of electric energy. Detecting and analyzing the decomposed components of SF6 is one of the important methods to realize the on-line monitoring of GIS equipment. In this paper, considering the performance limits of intrinsic TiO2 nanotube gas sensor, the adsorption process of H2S, SO2, SOF2 and SO2F2 on fluoride-doped TiO2 crystal plane was simulated by the first-principle method. The adsorption mechanism of these SF6 decomposition components on fluorine-doped TiO2 crystal plane was analyzed from a micro perspective. Calculation results indicate that the order of adsorption effect of four SF6 decomposition components on fluoride-doped TiO2 crystal plane is H2S > SO2 > SOF2 > SO2F2. Compared with the adsorption results of intrinsic anatase TiO2 (101) perfect crystal plane, fluorine doping can obviously enhance the adsorption ability of TiO2 (101) crystal plane. Fluorine-doped TiO2 can effectively distinguish and detect the SF6 decomposition components based on theoretical analysis