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Along with the evolution of deep neural networks (DNNs) in many real-world applications, the complexity of model building has also dramatically increased. Therefore, it is vital to protect the intellectual property (IP) of the model builder and ensure the trustworthiness of the deployed models. Meanwhile, adversarial attacks on DNNs (e.g., backdoor and poisoning attacks) that seek to inject malicious behaviors have been investigated recently, demanding a means for verifying the integrity of the deployed model to protect the users. This paper presents a novel DNN authentication framework DeepAuth that embeds a unique and fragile signature to each protected DNN model. Our approach exploits sensitive key samples that are well crafted from the input space to latent space and then to logit space for producing signatures. After embedding, each model will respond distinctively to these key samples, which creates a model-unique signature as a strong tool for authentication and user identity. The signature embedding process is also designed to ensure the fragility of the signature, which can be used to detect malicious modifications such that an illegitimate user or an altered model should not have the intact signature. Extensive evaluations on various models over a wide range of datasets demonstrate the effectiveness and efficiency of the proposed DeepAuth.

BackgroundSeveral reports in recent years have found an association between gut microbiota and upper urinary urolithiasis. However, the causal relationship between them remains to be clarified.MethodsGenetic variation is used as a tool in Mendelian randomization for inference of whether exposure factors have a causal effect on disease outcomes. We selected summary statistics from a large genome-wide association study of the gut microbiome published by the MiBioGen consortium with a sample size of 18,340 as an exposure factor and upper urinary urolithiasis data from FinnGen GWAS with 4,969 calculi cases and 213,445 controls as a disease outcome. Then, a two-sample Mendelian randomization analysis was performed by applying inverse variance-weighted, MR-Egger, maximum likelihood, and weighted median. In addition, heterogeneity and horizontal pleiotropy were excluded by sensitivity analysis.ResultsIVW results confirmed that class Deltaproteobacteria (OR = 0.814, 95% CI: 0.666–0.995, P = 0.045), order NB1n (OR = 0.833, 95% CI: 0.737–0.940, P = 3.15 × 10−3), family Clostridiaceae1 (OR = 0.729, 95% CI: 0.581–0.916, P = 6.61 × 10−3), genus Barnesiella (OR = 0.695, 95% CI: 0.551–0.877, P = 2.20 × 10−3), genus Clostridium sensu_stricto_1 (OR = 0.777, 95% CI: 0.612–0.986, P = 0.0380), genus Flavonifractor (OR = 0.711, 95% CI: 0.536–0.944, P = 0.0181), genus Hungatella (OR = 0.829, 95% CI: 0.690–0.995, P = 0.0444), and genus Oscillospira (OR = 0.758, 95% CI: 0.577–0.996, P = 0.0464) had a protective effect on upper urinary urolithiasis, while Eubacterium xylanophilum (OR =1.26, 95% CI: 1.010–1.566, P = 0.0423) had the opposite effect. Sensitivity analysis did not find outlier SNPs.ConclusionIn summary, a causal relationship was found between several genera and upper urinary urolithiasis. However, we still need further randomized controlled trials to validate.

Decidualization is the process of conversion of endometrial stromal cells (ESCs) into decidual stromal cells (DSCs), which is caused by progesterone production that begins during the luteal phase of the menstrual cycle and then increases throughout pregnancy dedicated to support embryonic development. Decidualization deficiency is closely associated with various pregnancy complications, such as recurrent miscarriage (RM). Here, we reported that Src-homology-2-containing phospho-tyrosine phosphatase (SHP2), a key regulator in the signal transduction process downstream of various receptors, plays an indispensable role in decidualization. SHP2 expression was upregulated during decidualization. SHP2 inhibitor RMC-4550 and shRNA mediated SHP2 reduction resulted in a decreased level of phosphorylation of ERK and aberrant cytoplasmic localization of progesterone receptor (PR), coinciding with reduced expression of IGFBP1 and various other target genes of decidualization. Solely inhibiting ERK activity recapitulated these observations. Administration of RMC-4550 led to decidualization deficiency and embryo absorption in mouse. Moreover, reduced expression of SHP2 was detected in decidua of RM patients. Our results revealed that SHP2 is key to PR's nuclear localization, thereby indispensable for decidualization and that reduced expression of SHP2 might be engaged in the pathogenesis of RM.

A polyamide 12(PA12) reinforced with glass beads (GBs) solid rocket motor (SRM) produced by 3D Printing is proposed in the paper. The ablation research of the combustion chamber is studied by simulating the motor’s operating environment through ablation experiments. The results show that the maximum ablation rate for the motor was 0.22 mm/s, which occurred at the location where the combustion chamber meets the baffle. The closer to the nozzle, the greater its ablation rate. Through the microscopic appearance analysis of the composite material from the inner wall surface to the outer wall surface in several directions before and after the ablation experiments, it was found that the GBs with weak or no interfacial adhesion to PA12 may make the mechanical properties of the material degrade. The ablated motor had a large number of holes and some deposits on the inner wall surface. Also by evaluating the surface chemistry of the material, it was found that the composite material underwent thermal decomposition. Moreover, it underwent a complex chemical reaction with the propellant.

Monolayer transition-metal dichalcogenide (TMD) materials have attracted a great attention because of their unique properties and promising applications in integrated optoelectronic devices. Being layered materials, they can be stacked vertically to fabricate artificial van der Waals lattices, which offer unique opportunities to tailor the electronic and optical properties. The integration of TMD heterostructures in planar microcavities working in strong coupling regime is particularly important to control the light-matter interactions and form robust polaritons, highly sought for room temperature applications. Here, we demonstrate the systematic control of the coupling-strength by embedding multiple WS2 monolayers in a planar microcavity. The vacuum Rabi splitting is enhanced from 36 meV for one monolayer up to 72 meV for the four-monolayer microcavity. In addition, carrying out time-resolved pump-probe experiments at room temperature we demonstrate the nature of polariton interactions which are dominated by phase space filling effects. Furthermore, we also observe the presence of long-living dark excitations in the multiple monolayer superlattices. Our results pave the way for the realization of polaritonic devices based on planar microcavities embedding multiple monolayers and could potentially lead the way for future devices towards the exploitation of interaction-driven phenomena at room temperature.

Primary tumor resection for metastatic breast cancer (MBC) has demonstrated a survival advantage, however, not all patients with MBC benefit from surgery. The purpose of this study was to develop a predictive model to select patients with MBC who are most likely to benefit from surgery at the primary site. Data from patients with MBC were obtained from the Surveillance, Epidemiology and End Results (SEER) cohort and patients treated at the Yunnan Cancer Hospital. The patients from the SEER database were divided into surgery and non-surgery groups and a 1:1 propensity score matching (PSM) was used to balance baseline characteristics. We hypothesized that patients who underwent local resection of primary tumors had improved overall survival (OS) compared to those who did not undergo surgery. Based on the median OS time of the non-surgery group, patients from the surgery group were further categorized into beneficial and non-beneficial groups. Logistic regression analysis was performed to identify independent factors associated with improved survival in the surgery group and a nomogram was established using the most significant predictive factors. Finally, internal and external validation of the prognostic nomogram was also evaluated by concordance index (C-index) and using a calibration curve. A total of 7759 eligible patients with MBC were identified in the SEER cohort and 92 with MBC patients who underwent surgery at the Yunnan Cancer Hospital. Amongst the SEER cohort, 3199 (41.23%) patients received surgery of the primary tumor. After PSM, the OS between the surgery and non-surgery group was significantly different based on Kaplan–Meier survival analysis (46 vs. 31 months, P

With the development of the market economy and changes in the demand for talents in the market, the cultivation of innovation and entrepreneurship (IAE) among university students has been emphasized, and how to improve the quality of IAE education and promote the overall development of university students has become a key concern of university teachers. Therefore, the design and implementation of the IAE project management system should be explored in the study, starting from the IAE education of university students. The thesis addresses the current situation and characteristics of IAE development of university students and develops a WEB system applicable to the project management of IAE for university students at this stage. Cluster analysis is a mathematical statistical method for grouping and categorising similar data. The design of a classification system based on university innovation and entrepreneurship data proposes a new definition of outlier index for outliers detected in real time, combined with the concept of CBLOF(t). On this basis, the system also implements the monitoring function for abnormal data, thus serving as system optimisation and fault warning. The system implements the main functions such as login, registration, project release, project declaration, and management.

Supramolecular host–guest systems are generally at thermodynamic equilibrium states or in kinetically trapped states. Herein, we demonstrate the concept of a chemical fuel-driven competitive host–g...

Organic-inorganic halide perovskites are promising materials for high-performance photovoltaics. The doping strategy is considered to be an effective method for regulating the performance of perovskite solar cells, yet its efficiency is still far below what has been anticipated. Here, we systematically investigate the regulatory mechanisms of the performance of perovskites by exploiting potassium iodide (KI) doping. We find that the surface states are passivated apart from the modified lattice structure. Most importantly, carrier recombination and transport are regulated by varying two different trap states when doping KI. The corresponding defect penalty can be effectively restrained at an optimal concentration of added KI (5%). A significant increase in the conductivity and radiative efficiency is achieved under such conditions. Our results provide fundamental insights into defect engineering through doping and a promising route toward highly efficient perovskite solar cells.

Photodynamic therapy (PDT) has garnered immense research interest. PDT can directly kill the cells via a combination of photosensitizer, light, and molecular oxygen. It has emerged as a promising therapeutic option for cancer treatment owing to its advantages such as minimized systemic toxicity, minimal invasiveness, high therapeutic efficacy, and potential for developing antitumor immunity. The novel photosensitizer 32-(4-methoxyphenyl)-152-aspartyl-chlorin e6 (DYSP-C34) was synthesized by introducing a 32-aryl substitution and amino acid substituent of the Chenghai chlorin (CHC). Briefly, 32-(4-methoxyphenyl) substitution was achieved via olefin metathesis reactions. The aspartic acid side chain was introduced regioselectively at C-152, followed by hydrolysis to yield the target DYSP-C34. CHC with the same chemical structure as chlorin e6 was prepared from chlorophyll a, which was extracted from Spirulina powders derived from Chenghai Lake in the Yunnan province of China. This strategy successfully endowed the resultant photosensitizer with better cellular permeability and increased water solubility. In addition, the photodynamic antitumor effects of PDT largely depend on the dose of photosensitizer used, time between photosensitizer administration and light exposure, and possibly other still poorly known variables. Determination of optimal conditions for PDT requires a coordinated interdisciplinary effort. Therefore, the pharmacokinetics and tissue distribution of DYSP-C34 in vivo are critical for the efficacy and safety of PDT. Herein, a high performance liquid chromatography-ultraviolet (HPLC-UV) detection method was established for the determination of the new photosensitizer DYSP-C34 in rat plasma. The sample preparation involved a protein-precipitation and liquid-liquid extraction method. Methanol was used to precipitate proteins and chloroform was used to extract chlorins. Then, DYSP-C34 was separated on a Unitary C18 column (250 mm×4.6 mm, 5 μm) with a mobile phase comprising methanol and 5 mmol/L tetrabutylammonium phosphate buffer solution (70∶30, v/v). The flow rate was 1.0 mL/min with UV detection using a wavelength of 400 nm at 40 ℃. Results showed that DYSP-C34 and chlorin e6 trimethyl ester (IS) were well separated under these conditions. The method was sensitive and sufficiently precise with a good linear relationship (determination coefficient (r2)=0.9941) over the range of 1-200 μg/mL in rat plasma. At three spiked levels (8, 40, and 120 μg/mL), the average recoveries were 74.39%, 69.71%, and 65.89%, respectively. The intra-day and inter-day relative standard deviations (RSDs) were lower than 5%. The precision met the requirements of biological sample determination. Furthermore, DYSP-C34 was stable in rat plasma under various storage conditions at room temperature, three freeze-thaw cycles, and long-term cryopreservation. The validated method was successfully applied to the pharmacokinetic study of DYSP-C34 after intravenous injection of a single dose in rat plasma. The pharmacokinetic parameters after intravenous injection of DYSP-C34 (16 mg/kg) were calculated. The plasma half-life (t1/2z) was 6.98 h, the area under the plasma concentration-time curve AUC(0-∞) was 1025.01 h·mg/L and the mean retention time MRT(0-∞) was 9.19 h. In addition, the results of DYSP-C34 distribution in tumor-bearing mice showed that DYSP-C34 could accumulate in tumor tissues, with higher concentrations in liver and kidney tissues, and lower concentrations in heart, spleen, and lung tissues. In summary, a specific, simple, and accurate HPLC-UV method was developed and validated for the determination of DYSP-C34 in rat plasma and tumor-bearing mouse tissues. The pharmacokinetics of DYSP-C34 after intravenous administration in rats and the tissue distribution characteristics of tumor-bearing mice were clarified for the first time. It is significant for clinical rational drug use and pharmacodynamic research. Therefore, choosing an appropriate time for light treatment time can achieve the best photodynamic effect. The results of pharmacokinetics and tissue distribution of DYSP-C34 provide vital guidance for subsequent pharmacodynamic research and further clinical trials in terms of dosage, light time, light toxicity and side effects.

Neural network based ranking has been widely adopted owing to its powerful capacity in modeling complex relationships (e.g., users and items, questions and answers). Online neural network ranking, i.e., the so called fast neural ranking, is considered a challenging task because neural network measures are in general non-convex and asymmetric. Traditional approximate near neighbor (ANN) search which typically focuses on metric ranking measures, is not applicable to these complex measures. To tackle this challenge, in this paper, we propose to construct BipartitE Graph INdices (BEGIN) for fast neural ranking. BEGIN contains two types of nodes: base/searching objects and sampled queries. The edges connecting these types of nodes are constructed via the neural network ranking measure. The proposed algorithm is a natural extension from traditional search on graph methods and is more suitable for fast neural ranking. Experiments demonstrate the effectiveness and efficiency of the proposed method.

A coordinated crosstalk between the maternal body and embryo is indispensable in a successful pregnancy. However, reliable models to study the potential cellular and molecular mechanisms of maternal-fetal interaction have not been established. The widely used research models including animal models and cell lines have significant limitations. Recently, the emergence and advancement of organoids have aroused attention. Endometrial organoids and trophoblast organoids which recapitulate human decidua and trophoblasts in three-dimensional cultures provide new opportunities to study the physiological or pathological processes of decidualization and implantation. Furthermore, to recapitulate precise cell-cell communication in the decidual microenvironment in vivo, the co-culture of multicellular organoids will be a potential optimal model for future investigations of crosstalk at the maternal-fetal interface. Here, we focus on the latest development and advancement of endometrial organoids and trophoblast organoids.

Chemistry is a basis for almost all science and engineering disciplines, and needs to be well mastered by both researchers and students. But in the eyes of many Chinese students and their parents, chemistry is not an initial choice because first, it seems to be less important than mathematics and physics, and second, chemistry-majored students usually cannot get high salaries after graduation, and may encounter safety risks when conducting chemical experiments. How can we encourage students in learning chemistry? How can we improve higher chemistry education so that students can truly grasp the basic chemical principles, increase their chemical skills and apply the learnt knowledge in their future careers? Here in this panel discussion, six experts in higher chemistry education try to give their observations and opinions on these issues. Yadong Li President at Anhui Normal University; inorganic chemist. Yan Li Professor at College of Chemistry and Molecular Engineering, Peking University. Jian Pei Professor at College of Chemistry and Molecular Engineering, Peking University. Zhenfeng Xi Professor at College of Chemistry and Molecular Engineering, Peking University. Song Gao (Chair) President at Sun Yat-sen University; inorganic chemist. Lan-Sun Zheng (Chair) Professor at College of Chemistry and Chemical Engineering, Xiamen University.

A large number of Chinese scientists are working overseas, especially in the USA and Europe, where scientific communities are highly internationalized and diverse. In contrast, international scientists working in China are fewer, naturally generating some curiosity about them—why do they come to China, and how are their experiences in China? In this article, we introduce five such scientists and their stories.

Prof. Pinxian Wang (汪品先) of Tongji University, born in 1936, is one of the leading deep-sea scientists in China. As the first co-chief scientist of Chinese nationality in the international Ocean Drilling Program (ODP), he co-led ODP Leg 184 in 1999; and in 2018, at 82 years old, he dived to a depth of 1400 meters in the South China Sea (SCS) in China's manned submersible ‘Deep Sea Warrior’. In recent years, he has also become a star of science popularization in China—he has more than 1.7 million followers on China's video-sharing platform bilibili, and his popular science book Deep Sea in Simple Words is a best seller. In September 2022, Prof. Wang was interviewed by NSR’s Associate Editor-in-Chief, Zhonghe Zhou. In this interview, Prof. Wang summarized his six-decade-long scientific career, talked about the past and future of China's deep-sea research efforts, and explained his opinion on how to promote scientific culture in China.

Oxaliplatin-based chemotherapy is a standard treatment for advanced colorectal cancer (CRC) patients. However, chemoresistance-induced resistance is an essential cause for mortality. Therefore, it is necessary to study the mechanism of drug resistance in CRC.Here, we established two strains of patient-derived organoids (PDOs) selected from oxaliplatin-resistant and treatment-naïve CRC patients. To dissect the drug-resistant mechanisms, these CRC-PDOs were subjected to single-cell RNA sequencing (scRNA-Seq).We found that the drug sensitivity test outcome from these organoids subjected to oxaliplatin and 5-FU exposure was consistent with the clinic readout. CRC-PDOs well recapitulated the morphology and histology of their parental biopsies based on HE and IHC staining of pathological biomarkers. The scRNA-Seq data filtered drug-resistant cell populations and related signaling pathways (e.g. oxidative phosphorylation and ATP metabolic process). The data also revealed several putative drug resistant-driven genes (STMN1, VEGFA and NDRG1) and transcription factors (E2F1, BRCA1, MYBL2, CDX2 and CDX1).We generated an oxaliplatin-resistant CRC organoid model that was employed to provide potential therapeutic targets for treating CRC patients exhibiting oxaliplatin-resistance.

The pollution of natural water bodies by pharmaceutical compounds has led to serious concerns regarding ecological and public health safety. In this study, novel recyclable phenylalanine (Phe)-modified magnetic ferroferric oxide nanoparticles (Fe

Background The natural resistance of rapidly growing mycobacteria (RGM) to multiple antibiotics renders the treatment of the infections caused less successful. The objective of this study was to evaluate the in vitro susceptibilities of four oxazolidinones against different RGM species. Methods The microplate alamarBlue assay was performed to identify the minimum inhibitory concentrations (MICs) of four oxazolidinones – delpazolid, sutezolid, tedizolid, and linezolid – for 32 reference strains and 115 clinical strains of different RGM species. The MIC breakpoint concentration was defined as 16 μg/ml for linezolid. Next, the gene fragments associated with oxazolidinone resistance were amplified and sequenced, and mutations were defined in contrast with the sequences of the reference strains. Results Tedizolid showed the strongest inhibitory activity against the Mycobacterium abscessus isolates. Delpazolid exhibited better antimicrobial activity against the Mycobacterium fortuitum isolates when compared to linezolid, with 4-fold lower MIC values. The protein alignment and structure-based analysis showed that there might be no correlation between oxazolidinone resistance and mutations in the rplC, rplD, and 23S rRNA genes in the tested RGM. Conclusions Tedizolid had the strongest inhibitory activity against M. abscessus in vitro, while delpazolid presented the best inhibitory activity against M. fortuitum. This provides important insights into the potential clinical application of oxazolidinones to treat RGM infections.

‘We aim to have CO2 emissions peak before 2030 and achieve carbon neutrality before 2060,’ President Xi Jinping so declared at the General Debate of the 75th United Nations General Assembly on 22 September 2020. More than 130 countries globally have proposed their own carbon neutrality goals by 2050 or 2060. Thus, carbon neutrality is a collective effort of human societies to cope with the climate crisis. If all countries could follow their own plans and reach carbon neutrality in a few decades, we may have a chance to control global warming within 1.5 or 2oC, confining climate change to a relatively safe zone. As a developing country with a large population, high coal consumption and large manufacturing industries, can China achieve the huge task of societal transformation that will enable carbon peaking and carbon neutrality within the next four decades? How will China transform traditional power generation and manufacturing industries, as well as create new technologies for carbon capture and storage? In this panel discussion chaired by Prof. Xinhe Bao, a scientist of energy and chemistry, top experts gathered to discuss the challenges and potential solutions, outlining the coming ‘green industrial revolution’. Huiming Cheng Professor, Institute of Metal Research, Chinese Academy of Sciences; Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Zhengtang Guo Professor, Institute of Geology and Geophysics, Chinese Academy of Sciences Yaling He Professor, School of Energy and Power Engineering, Xi’an Jiaotong University Zheng Li Professor, Institute of Climate Change and Sustainable Development, Tsinghua University Minggao Ouyang Professor, School of Vehicle and Mobility, Tsinghua University Zhengrong Shi Professor, College of Energy and Mechanical Engineering, Shanghai University of Electric Power Zaiku Xie Professor, China Petroleum and Chemical Corporation (SINOPEC) Xinhe Bao (Chair) Professor, University of Science and Technology of China, and Dalian Institute of Chemical Physics, Chinese Academy of Sciences

A reasonable and effective control of chemotherapy-induced nausea and vomiting (CINV) plays an important role in the comprehensive treatment of cancer. Megestrol belongs to the 17α-hydroxyprogesterone derivative and is a highly effective synthetic progesterone. Recorded in the instructions may improve appetite and cachexia in patients with advanced tumors. In recent years, clinical practice and small sample studies have shown that megestrol combined with chemotherapy can improve CINV. This randomized controlled trial aimed to evaluate the clinical efficacy and safety of megestrol acetate combined with a 5-Hydroxytryptamine (5-HT3) receptor antagonist and dexamethasone in patients with CINV.Patients with malignant tumors who were treated with cisplatin-containing chemotherapy in our hospital from September 2018 to December 2019 were enrolled. A total of 120 patients were selected and randomly assigned to receive either megestrol acetate dispersible tablets with a 5-HT3 receptor antagonist and dexamethasone (megestrol group) or a 5-HT3 receptor antagonist plus dexamethasone (control group). Megestrol acetate dispersible tablets: 160 mg orally every morning from the day of chemotherapy until it lasts for ten days. Abstract IV of the quality-of-life scale for cancer patients in China was used to assess the quality of life (QOL) of the participants. All adverse reactions during chemotherapy were assessed according to the CTCAE 4.03 evaluation standard issued by the National Cancer Institute and divided into five grades according to severity.For the control of nausea, the rates of complete prevention were significantly higher in the megestrol group than in the control patients during the delayed [53.3% (31/60)The triple antiemetic protocol using megestrol acetate with a 5-HT3 receptor antagonist plus dexamethasone can improve CINV symptoms caused by highly emetogenic chemotherapy (HEC) with cisplatin, with an excellent control effect and few adverse reactions, especially for delayed CINV.Chinese Clinical Trial Registry ChiCTR1800017953.

At the leaders’ summit of the 15th Meeting of the Conference of the Parties to the Convention on Biological Diversity (COP15) on 12 October 2021, China's President Xi Jinping declared that China has officially designated its first group of national parks—the Three-River-Source National Park, the Giant Panda National Park, the Northeast China Tiger and Leopard National Park, the Hainan Tropical Forests National Park, and the Wuyishan National Park. The five national parks cover a total area of ∼230 000 square kilometers and protect nearly 30% of the key terrestrial wildlife species found in China. Since the establishment of the United States’ Yellowstone National Park in 1872, national parks have been founded in many countries, and some of them have become distinctive ‘national signatures’ and important ecological security shelters. As a large country with rich biodiversity, China now begins to establish its first five national parks, with a total of about 50 planned for the future, and to form a national-park-centric protected-area system. How will national parks change the landscape of China's ecological conservation? Is China well prepared to scientifically establish and administrate national parks? In this panel discussion, six Chinese ecological conservationists introduce the background, plans and challenges of China's national park system, and provide their scientific perspectives. Guangchun Lei Professor, School of Ecology and Nature Conservation, Beijing Forestry University Zhiyun Ouyang Professor, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences Yang Su Research Fellow, Development Research Center of the State Council of China Rui Yang Professor, Institute for National Parks, Tsinghua University Yujun Zhang Professor, School of Landscape Architecture, Beijing Forestry University Keping Ma (Chair) Professor, Institute of Botany, Chinese Academy of Sciences

Hypothesis The self-assembly of amphiphilic molecules onto solid substrates can result both in the formation of monolayers and multilayers. However, on oxidized and non-oxidized copper (Cu), only monolayer formation was reported for phosphonic acids possessing one phosphate head group. Here, the adsorption of octadecylphosphonic acid (ODPA) on Cu substrates through a self-assembly process was investigated with the initial hypothesis of monolayer formation. Experiments The relative amount of ODPA adsorbed on a Cu substrate was determined by infrared reflection/absorption spectroscopy (IRRAS) and by atomic force microscopy (AFM) investigations before and after ODPA deposition. X-ray photoelectron spectroscopy (XPS) with sputtering was used to characterize the nature of the layers. Findings The results show that the thickness of the ODPA layer increased with deposition time, and after 1 h a multilayer film with a thickness of some tens of nm was formed. The film was robust and required long-time sonication for removal. The origin of the film robustness was attributed to the release of Cu ions, resulting in the formation of Cu-ODPA complexes with Cu ions in the form of Cu(I). Preadsorbing a monolayer of octadecylthiol (ODT) onto the Cu resulted in no ODPA adsorption, since the release of Cu(I) ions was abolished.

Tree models are very widely used in practice of machine learning and data mining. In this paper, we study the problem of model integrity authentication in tree models. In general, the task of model integrity authentication is the design \& implementation of mechanisms for checking/detecting whether the model deployed for the end-users has been tampered with or compromised, e.g., malicious modifications on the model. We propose an authentication framework that enables the model builders/distributors to embed a signature to the tree model and authenticate the existence of the signature by only making a small number of black-box queries to the model. To the best of our knowledge, this is the first study of signature embedding on tree models. Our proposed method simply locates a collection of leaves and modifies their prediction values, which does not require any training/testing data nor any re-training. The experiments on a large number of public classification datasets confirm that the proposed signature embedding process has a high success rate while only introducing a minimal prediction accuracy loss.

Hongmei Chen,1,* Shanshan Li,2,* Weijie Zhao,3,* Jiaheng Deng,4,* Zhuohong Yan,5 Tingting Zhang,2 Shu’ an Wen,2 Haiping Guo,2 Lei Li,6 Jianfeng Yuan,6 Hongtao Zhang,5 Liping Ma,1 Jianhua Zheng,4,* Mengqiu Gao,1 Yu Pang2 1Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People’s Republic of China; 2Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People’s Republic of China; 3Clinical Trial Agency Office, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People’s Republic of China; 4Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China; 5Department of Central Laboratory, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, People’s Republic of China; 6Electral Safety Research & Development Center, Beijing Normal University, Zhuhai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yu Pang, Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/ Beijing Tuberculosis & Thoracic Tumor Research Institute, No. 9, Beiguan Street, Tongzhou District, Beijing, 101149, People’s Republic of China, Tel +86 10 8950 9359, Email pangyupound@163.com Mengqiu Gao, Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/ Beijing Tuberculosis & Thoracic Tumor Research Institute, No. 9, Beiguan Street, Tongzhou District, Beijing, 101149, People’s Republic of China, Tel +86 10 8950 9302, Email gaomqwdm@aliyun.comBackground: Here, we conducted a peptidomic study in murine model to identify novel antigen biomarkers for the diagnosis of tuberculosis (TB) with improved performance.Methods: Four recombinant proteins, including Mycobacterium tuberculosis protein 32 (MPT32), Mycobacterium tuberculosis protein 64 (MPT64), culture filtrate protein 10 (CFP10), and phosphate ABC transporter substrate-binding lipoprotein (PstS1) were expressed and intravenously injected into BALB/c mice. The serum were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The concentrations of candidate peptides in serum of suspected TB patients were determined using competitive enzyme-linked immunosorbent assay.Results: A total of 65 peptides from 4 MTB precursor recombinant proteins were identified in mouse serum by LC-MS/MS, of which 5 peptides were selected as candidates for serological analysis. The concentrations of peptides MPT64-2, CFP10-2 and PstS1-2 in TB patients were significantly higher than those in non-TB patients. MPT64-2 exhibited the most promising sensitivity (81.4%), followed by PstS1-2 and CFP10-2. In addition, PstS1-2 had the highest specificity (93.3%), followed by CFP10-2 and MPT64-2. According to the area under the curve (AUC), MPT64-2 (AUC = 0.863), PstS1-2 (AUC = 0.812) and CFP10-2 (AUC = 0.809) exhibited better diagnostic validity.Conclusion: We develop an effective approach to identify new antigen biomarkers via LC-MS/MS-based peptidomics. Multiple peptides exhibit promising efficacy in diagnosis of active TB patients.Keywords: tuberculosis, peptidomics, enzyme-linked immunosorbent assay, Mycobacterium tuberculosis protein 64, diagnostics

How intelligent is artificial intelligence (AI)? How intelligent will it become in the future? What is the relationship between AI and human intelligence (HI)? These questions have been a hot topic of discussion in recent years, but no consensus has yet been reached. To discuss these issues, we should first understand the concept of intelligence as well as the underlying mechanisms for both HI and AI. In this NSR Forum, experts from both disciplines gathered to discuss these issues; in particular, the similarities and differences between AI and HI, how these two disciplines could benefit from each other, and the emerging social and ethical challenges of AI. Xiaolan Fu Professor at the Institute of Psychology, Chinese Academy of Sciences (CAS) Yong Gu Professor at the Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, CAS Sheng He Professor at the Institute of Biophysics, CAS Zhuojun Liu Professor at the Academy of Mathematics and Systems Science, CAS Tieniu Tan Professor at the Institute of Automation, CAS Zhi-Hua Zhou Professor at National Key Laboratory for Novel Software Technology, Nanjing University Huimin Lin (Chair) Professor at the Institute of Software, CAS

Hyperspectral imaging can obtain considerable flame information, which can improve the prediction accuracy of combustion characteristics. This paper studies the hyperspectral characteristics of methane flames and proposes several prediction models. The experimental results show that the radiation intensity and radiation types of free radicals are related to the equivalent ratio, and the radiation region of free radicals becomes larger with the increase of the Reynolds number. The polynomial regression prediction models include the linear model and quadratic model. It takes C 2 ∗ / C H ∗ as input parameters, and results can be available immediately. The three-dimensional convolutional neural network (3D-CNN) prediction model takes all spectral and spatial information in the flame hyperspectral image as input parameters. By improving the structural parameters of the convolution network, the final prediction errors of the equivalent ratio and Reynolds number are 2.84% and 3.11%, respectively. The method of combining the 3D-CNN model with hyperspectral imaging significantly improves the prediction accuracy, and it can be used to predict other combustion characteristics such as pollutant emissions and combustion efficiency.