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Background Bispecific T cell engaging antibodies (TEAs) with one arm targeting a cancer antigen and another arm binding to CD3 have demonstrated impressive efficacy in multiple clinical studies. However, establishing a safety/efficacy balance remains challenging. For instance, some TEAs have severe safety issues. Additionally, not all patients or all cancer cells of one patient respond equally to TEAs. Methods Here, we developed a next-generation bispecific TEA with better safety/efficacy balance and expanded mechanisms of action. Using the computer-aided antibody design strategy, we replaced heavy chain complementarity-determining regions (HCDRs) in one Rituximab arm with HCDRs from a CD3 antibody and generated a novel CD20/CD3 bispecific antibody. Results After series of computer-aided sequence optimization, the lead molecule, GB261, showed great safety/efficacy balance both in vitro and in animal studies. GB261 exhibited high affinity to CD20 and ultra-low affinity to CD3. It showed comparable T cell activation and reduced cytokine secretion compared with a benchmark antibody (BM). ADCC and CDC caused by GB261 only killed CD20+ cells but not CD3+ cells. It exhibited better RRCL cell killing than the BM in a PBMC-engrafted, therapeutic treatment mouse model and good safety in cynomolgus monkeys. Conclusions Thus, GB261 is a promising novel TEA against CD20+ cancers.

Introduction This study aimed to systemically summarize the present literature about circulating cystatin C (Cys C) levels in type 2 diabetes mellitus (T2DM) and provide a more precise evaluation of Cys C levels in T2DM. Material and methods Relevant studies about Cys C concentrations in T2DM were searched in PubMed, EMBASE and the Cochrane Library database (up to Oct 31 2018). We computed the pooled standard mean difference (SMD) with its 95% confidence interval (CI) of Cys C levels through a random-effect model. The Q test and the I2 statistic were used to assess and quantify between-study heterogeneity; publication bias was evaluated through a funnel plot and Egger’s linear regression test. Results After the literature search and screening process, 14 studies with 723 T2DM patients and 473 healthy controls were finally included in the meta-analysis. The results showed that T2DM patients had significantly higher Cys C levels compared to healthy controls (SMD = 1.39, 95% CI: 0.92–1.86, p < 0.001). Publication bias was not detected based on the symmetrical shape of the funnel plot and the results of Egger’s test (p = 0.452). Subgroup analyses suggested that variables of human race, age, gender, study sample size and disease duration have a relationship with Cys C level in T2DM patients. Conclusions Overall, our study suggests that patients with T2DM have an elevated circulating Cys C level compared to healthy controls, and it is associated with race, age, gender, study sample size and disease duration. Further investigations are still needed to explore the causal relationship of aberrant Cys C concentrations in T2DM.

The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (COVID-19) have not been adequately studied. AI-assisted chest high-resolution computed tomography (HRCT) was used to investigate the proportion of COVID-19 patients with pulmonary fibrosis, the relationship between the degree of fibrosis and the clinical classification of COVID-19, the characteristics of and risk factors for pulmonary fibrosis, and the evolution of pulmonary fibrosis after discharge. The incidence of pulmonary fibrosis in patients with severe or critical COVID-19 was significantly higher than that in patients with moderate COVID-19. There were significant differences in the degree of pulmonary inflammation and the extent of the affected area among patients with mild, moderate and severe pulmonary fibrosis. The IL-6 level in the acute stage and albumin level were independent risk factors for pulmonary fibrosis. Ground-glass opacities, linear opacities, interlobular septal thickening, reticulation, honeycombing, bronchiectasis and the extent of the affected area were significantly improved 30, 60 and 90 days after discharge compared with at discharge. The more severe the clinical classification of COVID-19, the more severe the residual pulmonary fibrosis was; however, in most patients, pulmonary fibrosis was improved or even resolved within 90 days after discharge.

Digital acousto-optic holography uses sound wave field interacted with interested object to modulate laser beam to generate an optical digital hologram. A numerical reconstruction of the digital hologram is carried out to reproduce the object information. This technology is able to image the interior structure of non-transparent object with high precision.

The viewing angle of liquid crystal display in manned spacecraft is analyzed with its properties and type. Three modes to improve the viewing angle for liquid crystal display in manned spacecraft are presented, including, IPS, MVA and compensated film mode. The principles of these modes are analyzed to improving the viewing angle of liquid crystal display in manned spacecraft. Various solutions are compared and concluded for different phases of spacecraft manufacture. In conclusion, liquid crystalline with compensation film is the best choice to solve the viewing angle problem on liquid crystal display in manned spacecraft when LCDs have been equipped.

To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019 (COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-ML). 136 moderate and 83 severe patients were selected from the patients with COVID-19 pneumonia. The clinical and laboratory data were collected for statistical analysis. The texture features of the Non-focus area of the first chest CT of patients with COVID-19 pneumonia were extracted, and then the classification model of the first chest CT of COVID-19 pneumonia was constructed by using these texture features based on the Auto-ML method of radiomics, The area under curve(AUC), true positive rate(TPR), true negative rate (TNR), positive predictive value(PPV) and negative predictive value (NPV) of the operating characteristic curve (ROC) were used to evaluate the accuracy of the first chest CT image classification model in patients with COVID-19 pneumonia. The TPR, TNR, PPV, NPV and AUC of the training cohort and test cohort of the moderate group and the control group, the severe group and the control group, the moderate group and the severe group were all greater than 95% and 0.95 respectively. The non-focus area of the first CT image of COVID-19 pneumonia has obvious difference in different clinical types. The AUTO-ML classification model of Radiomics based on this difference can be used to predict the clinical types of COVID-19 pneumonia.

We have investigated the internal structure of materials by use of a digital acousto-optic holographic technique. The innovative technique is effective in detecting the internal structure information of functional gradient materials. The present visible-light-source-based digital holographic techniques are not able to detect the internal structure information of non-transparent objects and that motivates us to seek the ultrasound-based digital optical holography alternative. The characteristic model of functional gradient materials is modeled through finite element modeling software. The effects of material composition, shape and density on the ultrasound field distribution are simulated, which reveal the propagation pattern of the ultrasound in functional gradient materials as the shape, density and elastic modulus of the medium affect the acoustic properties. The dynamic changes of quantitative mapping relationship between the internal structural information and the sound field is also analyzed. Results indicate that the change is correlated with the internal structural information of the object. The simulation results provide useful quantifiable information for the subsequent research of digital acousto-optic holography to detect the internal structure of materials. Our research is applicable to various industrial problems where traditional digital holographic techniques alone fail to deliver solutions.

This paper presents the competition on Offline Recognition and Spotting of Handwritten Mathematical Expressions (OffRaSHME) held at the 17th International Conference on Frontiers in Handwriting Recognition (ICFHR 2020). Handwritten Mathematical Expression Recognition (HMER) has wide potential applications and is capturing increasing attention in recent years. Previous HMER competitions mainly focused on online datasets or offline datasets that are converted from online data. In this competition, we have collected a dataset of offline handwritten mathematical expressions by scanning papers that contain expressions. Moreover, we labeled the offline dataset at symbol level, i.e., the bounding boxes of each symbol are also provided, to facilitate the research of HMER. At last, 19,749 offline handwritten mathematical expressions are collected for training, and 2,000 ones are provided for evaluating the participating systems. In the competition, 7 teams submitted 8 systems for the task of offline HMER, among which 5 systems only use the provided datasets without any extra data while 3 systems use extra data. The winner team achieved a recognition accuracy of 79.85% (without extra data) and 81.85% (with extra data) on the offline formula recognition task.

Objective: To explore the possibility of predicting the clinical types of Corona-Virus-Disease-2019(COVID-19) pneumonia by analyzing the non-focus area of the lung in the first chest CT image of patients with COVID-19 by using automatic machine learning (Auto-ML).Methods: 136 moderate and 83 severe patients were selected from the patients with COVID-19 pneumonia. The clinical and laboratory data were collected for statistical analysis. The texture features of the Non-focus area of the first chest CT of patients with COVID-19 pneumonia were extracted, and then the classification model of the first chest CT of COVID-19 pneumonia was constructed by using these texture features based on the Auto-ML method of radiomics, The area under curve(AUC), true positive rate(TPR), true negative rate(TNR), positive predictive value(PPV) and negative predictive value(NPV) of the operating characteristic curve (ROC) were used to evaluate the accuracy of the first chest CT image classification model in patients with COVID-19 pneumonia.Result: The TPR, TNR, PPV, NPV and AUC of the training cohort and test cohort of the moderate group and the control group, the severe group and the control group, the moderate group and the severe group were all greater than 95% and 0.95 respectively. Conclusion: The non-focus area of the first CT image of COVID-19 pneumonia has obvious difference in different clinical types. The AUTO-ML classification model of Radiomics based on this difference can be used to predict the clinical types of COVID-19 pneumonia.

This work deals with the reliability-based design and optimization of ship structural components subjected to stochastic loads and accounting for the local fatigue damage and buckling and ultimate global strength of the ship hull. The multi-objective structural optimization is performed in minimizing the component net-section area, lateral deflection, and fatigue damage, avoiding local buckling. The probability of compressive collapse and fatigue damage of the ship hull and associated cost is used as a base to define the best design solution. The Pareto frontier solutions, calculated by the non-dominated sorting genetic algorithm (NSGA-II), are employed in defining the feasible solutions of the design variables. The first-order reliability method (FORM) is employed to estimate the Beta reliability index based on the topology of the structural component as a part of the Pareto frontier solutions. Comparing with the original design solution, the optimized section of the identified best design solution area decreased by 9%.

Precision or personalized cancer medicine is a clinical approach that strives to customize therapies based upon the genomic profiles of individual patient tumors. Machine learning (ML) is a computational method particularly suited to the establishment of predictive models of drug response based on genomic profiles of targeted cells. We report here on the application of our previously established open-source support vector machine (SVM)-based algorithm to predict the responses of 175 individual cancer patients to a variety of standard-of-care chemotherapeutic drugs from the gene-expression profiles (RNA-seq or microarray) of individual patient tumors. The models were found to predict patient responses with >80% accuracy. The high PPV of our algorithms across multiple drugs suggests a potential clinical utility of our approach, particularly with respect to the identification of promising second-line treatments for patients failing standard-of-care first-line therapies.

ZnX (X = S, Se) can perform photocatalytic hydrogen generation from water splitting. However, the reaction cannot be driven by solar energy because of the wide band gaps of ZnX. To tune their photocatalytic activity for the hydrogen generation driven by solar energy, we investigate the geometrical structures, the electronic, optical and photocatalytic properties of Hg-doped ZnX by using the first-principles density functional theory calculation with the meta-GGA + MBJ potential. Four concentrations of Hg dopants are considered. The carrier mobility and the recombination of the hole and electron are calculated and used to evaluate the photocatalytic activity of the structures. The results demonstrate that the formation energies of the doped structures are small, which implies that the synthesis of these materials is not difficult in energy. The energy band gaps of ZnX decrease along with the increase of the doping concentration, and the smallest one still satisfies the requirement of photocatalytic water splitting. Additionally, the optical absorption of the Hg-doped ZnSe in the near ultraviolet and visible light range increases significantly. The obvious charge difference and the relative ratio of electron and hole are observed. Therefore, Hg-doped ZnSe is a potential candidate for hydrogen generation from water splitting driven by solar energy.

Although the pristine ZnS can perform photocatalytic hydrogen production from water splitting, the reaction can not be driven by the visible light because of its wide energy band gap. Therefore, ZnS doped with carbon group elements (C, Si, Ge, Sn, Pb) has been investigated by using first-principles density functional theory calculations to understand the feasibility of the reaction driven by solar energy. All the geometrical structures are fully optimized. The electronic and optical properties of these structures have been calculated with the meta-GGA + MBJ method and with projector augmented wave potential. The results show that all the doped structures have low formation energies, implying that the synthesis of the doped structures is not difficult in energy. Moreover, the absorptions of the doped structures in the visible light range are significantly enhanced, but their energy levels are still suitable for water splitting to generate hydrogen, which means that carbon group elements doped ZnS structures are promising candidate materials for water splitting driven by visible light.

Band gap engineering can efficiently improve the photocatalytic activity of semiconductors for hydrogen generation from water splitting. Herein, we present a comprehensive investigation on the geometrical structures, electronic, optical, and potential photocatalytic properties and charge carrier mobility of pristine and group-IVA element-doped SrIn2O4 using first-principles density functional theory with the meta-GGA+MBJ potential. The calculated formation energies are moderate, indicating that the synthesis of the doped structures is experimentally feasible. In addition, the energy band gaps of the group-IVA element-doped SrIn2O4 range from 1.67 to 3.07 eV, which satisfy the requirements for photocatalytic water splitting, except for that of the Si mono-doped structure. Based on the deformation potential theory, a high charge carrier mobility of 2093 cm2 V−1 s−1 is obtained for the pristine SrIn2O4 and those of the doped-structures are also large, although a decrease in the values of some are observed. The optical absorption coefficient of the doped structures in the near ultraviolet (UV) and visible light range significantly increases. Therefore, group-IVA element-doped SrIn2O4 are potential candidates as photocatalysts for hydrogen generation from water splitting driven by visible light.

The enhanced photocatalytic performance of Se-/In-doped TlAsS 2 to generate hydrogen from water splitting is investigated based on the first-principle density functional theory calculation with meta-GGA + TPSS. Three structures, namely, pristine TlAsS 2 and substitutions of S with Se and Tl with In, are considered. Their geometrical lattices are fully optimized and their electronic and optical properties are calculated to evaluate the photocatalytic efficiency for hydrogen generation. Results show that the three structures can be used for solar energy photocatalysis to generate hydrogen from water splitting. Moreover, the Se- and In-doped atoms can strengthen the absorption coefficient within the visible light range. Therefore, these structures are promising catalysts for generating hydrogen from water splitting through solar energy photocatalysis.

Part 2: Poster Papers; International audience; It is generally very difficult to optimize the routing policies in optical networks with dynamic traffic. Most widely-used routing policies, e.g., shortest path routing and least congested path (LCP) routing, are heuristic policies. Although the LCP is often regarded as the best-performing adaptive routing policy, we are often eager to know whether there exist better routing policies that surpass these heuristics in performance. In this paper, we propose a framework of reinforcement learning (RL) based routing scheme, that learns routing decisions during the interactions with the environment. With a proposed self-learning method, the RL agent can improve its routing policy continuously. Simulations on a ring-topology metro optical network demonstrate that, the proposed scheme outperforms the LCP routing policy.

Introduction: COVID-19 showed certain characteristic features of multiple signs in bilateral lungs COVID-19 with a solitary pulmonary nodule (SPN) also occurs

The task of multi-label classification is to predict multiple possible labels for the unseen instance. Currently the prevalence of multi-label data in daily life has stirred up a spree of research activities. But most of those established multi-label classification methods mainly focus on such issues as class imbalance, label relations and dimension compression. These methods usually have an untenable hypothesis that each instance is of equal importance for all labels, based on which an identical set of instances is used to establish the learning model for all labels. In this paper we introduce the concept of labeling-importance and work out each instance’s labeling-important degrees that are in line with the polynomial distribution. Afterwards, a relatively important set of instances is selected for each label before establishing its classification model. The superior performance of this proposed method is validated by comprehensive experiments.

Background: Tyrosine kinase inhibitors (TKIs) have been developed against EGFR. However, in NSCLC (Non-small Cell Lung Cancer) and some other cancers, the occurrence of activating mutations in EGFR leads to acquired resistance. Anomalous cMET signaling additionally contributes to developing resistance to targeted therapies, including ones directed at EGFR. A number of bispecific antibodies targeting EGFR and cMET are in clinical trials and JNJ-61186372 (Amivantamab) from Janssen labs, has been given fast track approval by the FDA. In this study we created bispecific and trispecific antibody formats which target both cMET and EGFR. Trispecific (TsAb), unlike the bispecific (BsAb), binds to two different epitopes on cMET and one on EGFR resulting in enhanced internalization of the receptors. This study demonstrates that our antibodies exhibit enhanced capabilities than the benchmark at clinical stage in cell and non-cell based in vitro assays. Methods: The two cMET binding arms of TsAb were designed to block the cMET-HGF (ligand) interaction and enhance the internalization of the receptors. Cell based assays were performed using a NSCLC cell line NCI-H1975 (ATCC CRL-5908) and HGF-expressing NCI-H1975. Receptor binding and receptor/ligand blocking (cMET/HGF and EGFR/EGF) assays were performed using both ELISA and flow cytometry. Phosphorylation assays were performed using ELISA and Western blotting. Receptor internalization studies were executed using the pHrodo labelling kit and were further assessed through fluorescence microscopy and quantified through flow cytometry. ADCC assays (Antibody dependent cellular cytotoxicity) were performed through the Crystal violet method. Results: BsAb was more effective than benchmark in terms of its binding capabilities to cMET and EGFR receptors and also in blocking the interaction of cMET and EGFR with their ligands. Moreover, functional assays revealed that the new BsAb is in most cases better than benchmark in successfully inhibiting the phosphorylation of not only the cMET and EGFR receptors but also the downstream signaling pathways which are involved in cancer cell proliferation, survival and obstructing the apoptotic pathways. Furthermore, the new TsAb was found to be more effective than BsAb and benchmark in cMET/EGFR receptor internalization which may lead to additional extenuation of the downstream pathways for these receptors. Cancer cell killing assays for ABT BsAb show ADCC comparable to the benchmark. Conclusion: Comparing to BsAbs, TsAb induces enhanced internalization of the cMET/EGFR receptors leading to further extenuation of the downstream oncogenic signaling pathways. These data suggest the development of ABT BsAb and specifically TsAb as a new drug target for patients with lung cancer and NSCLC in particular. Citation Format: Mohd Zaman, Cai Huang, Sachith Gallolu Kankanamalage, Amit K. Chaudhary, Jianbo Dong, Yue Liu. Development of cMET/cMET/EGFR Trispecific antibody as therapeutic modality for Non-small Cell Lung Cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB069.

Background Bispecific T cell engaging antibodies (TEAs) with one arm targeting a cancer antigen and another arm binding to CD3 have demonstrated impressive efficacy in multiple clinical studies. However, establishing a balance of safety versus efficacy remains challenging. For instance, some TEAs have severe safety issues such as causing cytokine release symptom. Additionally, due to the heterogeneity of cancer cells, not all patients or all cancer cells of one patient respond equally to TEA treatments. It has been shown that cancer cells with PD-L1 overexpression respond to TEA therapy worse than other cancer cells. To develop next generation bispecific TEAs with a better balance of safety, efficacy and expanded mechanism of actions, we replaced heavy chain complementarity-determining regions (HCDRs) in one arm of Rituximab with HCDRs from a CD3 antibody to make a novel CD20/CD3 bispecific antibody, Rituximab/CD3 (GB261). After several rounds of computer aided sequence optimization, the final lead molecule demonstrated a superior balance of safety and efficacy in both in vitro and animal studies. Methods The affinities of antibodies to antigens were determined using FACS and SPR. T cell activation was determined by measuring CD69+/CD2+ cell percentage using FACS and cytokine release. Cancer cell killing assays were performed by measuring target cell depletion after incubating with PBMCs, ADCC assays were performed by measuring target cell depletion after incubating with NK92-CD16 cells and CDC was performed by measuring target cell depletion after incubating with complements-enriched human serum. In vivo cancer cell killing was performed using human PBMC engrafted NDG mouse models. Pre-tox and PK study were performed with cynomolgus monkey.Results GB261 exhibited high affinity to CD20 and an extremely low affinity to CD3. It showed similar T cell activation and cancer cell killing in Rituximab resistant Raji cells (RRCL) while reducing cytokine secretion compared to a benchmark CD20/CD3 (BM). GB261-induced ADCC and CDC only killed CD20+ cells but not CD3+ cells. When RRCL and PBMC cells (1:1) were co-injected with antibodies, it exhibited cancer killing effect comparable to the BM in a PBMC engrafted mouse model. However, if RRCL cells were injected first, then PBMC cells and antibodies were co-injected 4 days later, it showed superior cancer cell killing. Moreover, it delayed cancer relapse more effectively than Rutuximab in mice. Pre-tox and PK data in a cyno model also suggested that GB261 has good safety and PK. Finally, GB261 also demonstrated excellent manufacturability based on expression level and bio-analytic data.Conclusions GB261 exhibits enhanced efficacy and safety, and great manufacturability, presenting several advantages over the BM antibody. Thus, GB261 is a promising bispecific therapeutic antibody against CD20+ cancers. Citation Format: Wenyan Cai, Jianbo Dong, Sachith Gallolu Kankanamalage, Allison Titong, Jiadong Shi, Zhejun Jia, Bo Wang, Cai Huang, Jing Zhang, Jun Lin, Steven Z. Kan, Joe Zhou, Yue Liu. A novel CD20/CD3 T cell engager designed from Rituximab targeting CD20+ cancer with multiple mechanisms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB068.

Chloramphenicol is an old antibiotic that also inhibits mammalian mitochondrial protein synthesis. Our studies demonstrated that chloramphenicol is highly cytotoxic to myeloma cells, acting in a dose- and time-dependent manner. Chloramphenicol sharply suppressed ATP levels in myeloma cells at concentrations ≥ 25 μg/mL. Colorimetric and clonogenic assays indicate that chloramphenicol inhibits growth of myeloma cell lines at concentrations ≥ 50 μg/mL, and inhibits primary myeloma cell growth at concentrations ≥ 25 μg/mL. Flow cytometry and Western blotting showed that chloramphenicol induces myeloma cell apoptosis at concentrations ≥ 50 μg/mL. Chloramphenicol increased levels of cytochrome c, cleaved caspase-9 and cleaved caspase-3, suggesting that myeloma cell apoptosis occurs through the mitochondria-mediated apoptosis pathway. It thus appears chloramphenicol is not only an old antibiotic, it is also a potential cytotoxic agent effective against myeloma cells. This suggests chloramphenicol may be an effective "new" drug for the treatment of myeloma.

New luminescent oxynitridosilicates doped with Eu2+ and Ce3+ have been synthesized by solid state reaction method at 1450oC. The host has the general formula La1-ySr1-xSiO3N: (yCe3+, xEu2+), which presents greenish-yellow or orange photoluminescence under UV/blue excitation. Remarkable long wavelength emissions centered above 565 nm were observed for the Ce3+ activated oxynitridosilicates, with compositions LaSrSiO3N:0.02Ce3+, and LaSrSiO3N:(0.02Ce3+, 0.02Eu2+) for 598 nm due to a significant amount of energy transfer from Ce3+ ions to Eu2+ ions. By combining the title LaSrSiO3N:(Ce3+, Eu2+) phosphors with the 450 nm InGaN chip, a broad range of white light with correlated color temperatures of ~3500 K and color-rendering index of 92 can be generated, demonstrating their promising practical applicability to the warm-white light-emitting diodes.

Aims: To evaluate the role of free fatty acid receptor 2 (FFAR2)/G-protein coupled receptor 43 in mediating the effects of the short chain fatty acids (SCFAs) sodium acetate (SA) and sodium propionate (SP) on islet function in vitro, and to identify the intracellular signalling pathways used in SCFA-induced potentiation of glucose-induced insulin secretion. Materials and methods: Islets of Langerhans were isolated from wild-type and FFAR2−/− mice and from human donors without diabetes. The effects of SA and SP on dynamic insulin secretion from perifused islets were quantified by radioimmunoassay, signalling downstream of SCFAs was profiled by single-cell calcium microfluorimetry, and measurement of cAMP was performed using a fluorescence assay. Islet apoptosis was induced by exposure to cytokines or sodium palmitate, and the effects of SA and SP in regulating islet apoptosis were assessed by quantification of caspase 3/7 activities. Results: Deletion of FFAR2 did not affect islet morphology or insulin content. SA and SP reversibly potentiated insulin secretion from mouse islets in a FFAR2-dependent manner. SCFA-induced potentiation of insulin secretion was coupled to Gq activation of phospholipase C and protein kinase C, with no evidence of Gi-mediated signalling. SA and SP protected human and mouse islets from apoptosis, and these pro-survival properties were dependent on islet expression of FFAR2. Conclusion: Our results indicate that FFAR2 directly mediates both the stimulatory effects of SA and SP on insulin secretion and their protection against islet apoptosis. We have also shown that SCFA coupling in islets occurs via Gq-coupled intracellular signalling.

Due to the massive items and users limited scope, many existing recommendation systems suffer a more and more serious sparse problem on rating matrix. Most of the recommendation systems employ the content-based method or the collaborative filter model to abbreviate the sparse problem. While in our paper, based on the assumption that users who have rated similar sets of items are likely to have similar preference information, we present a constrained user exposure matrix factorization collaborative filter model and apply it to deal with the matrix sparsity problem, which it makes a better recommendation to users who have very few ratings. In detail, for the sake of capturing the effect of user having rated a particular item, we introduce a constrained matrix to user latent vector space. This effect will have an impact on the prior mean of user latent feature vector. After that, using the user feature vector and item feature vector to estimate the values of unrated items. The experimental results show that the proposed model gets higher prediction precision than the state-of-the-art models in providing recommendation for user having very few ratings.

In optical packet switching (OPS)-based data center networks (DCNs), it is preferred to set up temporal optical circuit switching (OCS) paths for large-data transmission that requires high reliability. However, inappropriate OCS path selection could severely affect the original OPS traffic. This is because an OCS path may break the network topology and cause OPS packet circulations. We propose to maintain bypassing routes for every link of the OCS path when it is established. Then, the OPS packets can bypass the OCS links by being deflected to the bypassing routes. Therefore, this method facilitates the coexistence of OCS in OPS-based DCNs. Numerical simulations demonstrate the benefit achieved by our proposal compared with non-bypassing-route scenarios.

In this paper, we consider an integrated service system, providing multirate guaranteed services and homogeneous best-effort services. The total system capacity is shared by both service types, while the guaranteed service customers are treated as high priority and are allocated fixed data rate bandwidth units. The best-effort service customers are supported by the remaining capacity leftover by the guaranteed services, in a processor-sharing manner. Admission control on the best-effort service customers is adopted to provide a certain level of quality of service (not guaranteed) to avoid the effect of repeated attempts. The best-effort customer blocking probability is an important metric for network dimensioning. In this integrated service system, we observe that the blocking probability of the best-effort customers is not insensitive to the shapes of their flow-size distributions and the guaranteed customers’ holding-time distributions. We obtain here by light computation, for the best-effort customers, blocking probability bounds, and approximations, which possess the insensitivity property. Considering that the distributions for customers’ holding times and flow sizes may be unknown, the proposed insensitive bounds and approximations will facilitate system design and network dimensioning with predictable and acceptable performance.

We review our work on an intra-data center (DC) network based on co-deployment of optical packet switching (OPS) and optical circuit switching (OCS), conducted within the framework of a five-year-long national R&D program in Japan (∼March 2016). For the starter, preceding works relevant to optical switching technologies in intra-DC networks are briefly reviewed. Next, we present the architecture of our torus-topology OPS and agile OCS intra-DC network, together with a new flow management concept, where instantaneous optical path on-demand, so-called Express Path is established. Then, our hybrid optoelectronic packet router (HOPR), which handles 100 Gbps (25 Gbps × 4-wavelength) optical packets and its enabling device and sub-system technologies are presented. The HOPR aims at a high energy-efficiency of 0.09 [W/Gbps] and low-latency of 100 ns regime. Next, we provide the contention resolution strategies in the OPS and agile OCS network and present the performance analysis with the simulation results. It is followed by the discussions on the power consumption of intra-DC networks. We compare the power consumption and the throughput of a conventional fat-tree topology with the N -dimensional torus topology. Finally, for further power saving, we propose a new scheme, which shuts off HOPR buffers according to the server operation status.

AimsTo examine the effects of Abn‐CBD (GPR55 agonist) and LH‐21 (CB1 antagonist) on human and mouse islet function, and to determine signalling via GPR55 using islets from GPR55−/− mice.Materials and methodsIslets isolated from human organ donors and mice were incubated in the absence or presence of Abn‐CBD or LH‐21, and insulin secretion, [Ca2+]i, cAMP, apoptosis, β‐cell proliferation and CREB and AKT phosphorylation were examined using standard techniques.ResultsAbn‐CBD potentiated glucose‐stimulated insulin secretion and elevated [Ca2+]i in human islets and islets from both GPR55+/+ and GPR55−/− mice. LH‐21 also increased insulin secretion and [Ca2+]i in human islets and GPR55+/+ mouse islets, but concentrations of LH‐21 up to 0.1 μM were ineffective in islets from GPR55−/− mice. Neither ligand affected basal insulin secretion or islet cAMP levels. Abn‐CBD and LH‐21 reduced cytokine‐induced apoptosis in human islets and GPR55+/+ mouse islets, and these effects were suppressed after GPR55 deletion. They also increased β‐cell proliferation: the effects of Abn‐CBD were preserved in islets from GPR55−/− mice, while those of LH‐21 were abolished. Abn‐CBD and LH‐21 increased AKT phosphorylation in mouse and human islets.ConclusionsThis study showed that Abn‐CBD and LH‐21 improve human and mouse islet β‐cell function and viability. Use of islets from GPR55−/− mice suggests that designation of Abn‐CBD and LH‐21 as a GPR55 agonist and a CB1 antagonist, should be revised.

The cooperative output regulation problem for a class of nonlinear uncertain multi-agent systems is considered. Based on the distributed internal model, the problem is firstly transformed into a global stabilization problem of the augmented system. Then, using the backstepping design method, a distributed control law with its stability analysis is proposed to solve the global stabilization problem of the augmented system. Finally, a numerical simulation is made to show the efficacy of the analytic results.

Rhynchophylline (Rhy) is an alkaloid isolated from Uncaria which has long been recommended for the treatment of central nervous diseases. In our study, the neuroprotective effect of Rhy was investigated in a stroke model, namely permanent middle cerebral artery occlusion (pMCAO). Rats were injected intraperitoneally once daily for four consecutive days before surgery and then received one more injection after surgery. The protein and mRNA levels of p-Akt, p-mTOR, apoptosis-related proteins (p-BAD and cleaved caspase-3), TLR2/4/9, NF-κB, MyD88, BDNF and claudin-5 were examined. Following pMCAO, Rhy treatment not only ameliorated neurological deficits, infarct volume and brain edema, but also increased claudin-5 and BDNF expressions (p < 0.05). Moreover, Rhy could activate PI3K/Akt/mTOR signaling while inhibiting TLRs/NF-κB pathway. Wortmannin, a selective PI3K inhibitor, could abolish the neuroprotective effect of Rhy and reverse the increment in p-Akt, p-mTOR and p-BAD levels. In conclusion, we hypothesize that Rhy protected against ischemic damage, probably via regulating the Akt/mTOR pathway.

Air defense process of large surface warship formation is a very important part in the combat. In current research, however, less attention has been paid to the whole process of air defense of surface warship formation in macro perspective. This paper applies the PEPA method to model the air defense process of surface warship formation. The cooperation among elements has been taken into account in the established model and the basic process of the air defense has been described as well. By analysis it shows the performance of air defense of warship formation increases with the increase of elements’ quantity, and finally reaches a stable value. Then the composition of the basic formation elements that the interception capacity of air defense operation attains the maximum can be obtained from the test results. Therefore, it provides a new quantitative method to deal with the air defense problem of warship formation.

Permanent magnet linear synchronous motors (PMLSM) is a multi-variable, strong coupling, nonlinear complex system. As a result, the design of an appropriate controller on dynamic performance of PMLSM is very important. In this paper, a feedforward controller based on pole-placement design strategy is proposed to improve the dynamic performance by increasing the speed response while reducing steady state errors. The parameters which influence the dynamic characteristic of the system were discussed. The dynamic response and disturbance rejection ability for linear feed system were verified by the experiments. Finally the control performance of pole-placement and PID was compared.

Developing low-carbon economy is an important task for sustainable social development, college students are new force to spread the low carbon concept and practice low carbon development. Therefore, the strengthening of the college students, low carbon concept of culture is of great significance. Low-carbon life is not just a fashion we pursue should fulfill the social obligations. Learn from foreign low-carbon lifestyle based on, Raised this responsibility requires schools, the teachers and students tripartite fulfill in order to jointly build a harmonious campus.

Goutengsan, a Chinese herbal formula, potential protection on Alzheimer’s disease (AD) has been less reported. In current study, we investigated the protection of Goutengsan on Aβ1–42-induced pheochromocytoma-derived cells (PC12). Furthermore, the components from Goutengsan in rat plasma were identified by microdialysis (MD) forin vivosampling. Meanwhile, the protection of components identified was also verified. At last, we found that Goutengsan has a potential protective effect on Aβ1–42-induced PC12 cells via reducing cells damage and increasing cells vitality as well as six components (pachymic acid, liquiritin, rhynchophylline, isorhynchophylline, corynoxeine, and isocorynoxeine) which may be effective components. This study helps to understand the treatment of Goutengsan for AD and would facilitate the clinical and further studies for this formula.

With the rapid development of ground mobile communication, it has obtained rich frequency resources, and the corresponding technology is mature and reliable. Considering the future development of the International Space Station (ISS), the demand of wireless communication would increase, while the frequency resources are rare. This paper proposes the ISS space-to-space communication system by multiplexing ground mobile communication frequency resources, which extend the ISS space-to-space communication frequency resources.

In recent years, the proportion of traditional Chinese medicine in scientific research and its clinical use increased gradually. The research result also becomes more and more valuable, but in the process of using traditional Chinese medicine, it also needs to pay more attention. With the gradual deepening of the toxicity of traditional Chinese medicine, some traditional Chinese medicines have also been found to have the potential toxicity, with the exception of some traditional toxicity Chinese medicine. Traditional Chinese medicine in the growth, processing, processing, transportation and other aspects of pollution or deterioration will also cause the side effects to the body. Clinical practice should be based on the theory of traditional Chinese medicine to guide rational drug use and follow the symptomatic medication, the principle of proper compatibility. The constitution of the patients are different, except for a few varieties of traditional Chinese medicines are natural herbs with hepatotoxicity, liver toxicity of most of the traditional Chinese medicine has idiosyncratic features. The liver plays an important role in drug metabolism. It is easy to be damaged by drugs. Therefore, the study of traditional Chinese medicine potential liver toxicity and its toxic components has become one of the basic areas of traditional Chinese medicine research. Based on the review of the literatures, this paper summarizes the clinical classification of liver toxicity, the pathogenesis of target cell injury, and systematically summarizes the mechanism of liver toxicity and toxic mechanism of traditional Chinese medicine. This paper provided ideas for the study of potential liver toxicity of traditional Chinese medicine and protection for clinical safety of traditional Chinese medicine.

A series of Na5La(WO4)4:M3+ (M = Eu, Sm, Bi) phosphors have been synthesized successfully by the solid-state reactions. The corresponding crystal structure and lattice parameters were refined by the Rietveld method, and the impact of doped metal ions upon the structure were also studied. The photoluminescent properties were investigated at room temperature. All the samples were observed a strong red emission under 395nm or 465 nm excitation, and the CIE chromaticity coordinates (x = 0.67, y = 0.33) was found to be close to the National Television Standard Committee (NTSC) standard red, implying high color purity. This kind of tungstate phosphor is a promising candidate as the red phosphor for white light-emitting diodes (WLED).

Glucagon-like peptide-1 (GLP-1) is a gut peptide that promotes insulin release from pancreatic β-cells and stimulates β-cell hyperplasia. GLP-1 secretion causing hypoglycemia has been described once from an ovarian neuroendocrine tumor (NET) but has not been reported from a pancreatic NET (pNET).A 56-yr-old male with a previous diagnosis of diabetes presented with fasting hypoglycemia and was found to have a metastatic pNET secreting glucagon. Neither the primary tumor nor metastases stained for insulin, whereas the resected normal pancreas showed histological evidence of islet cell hyperplasia. We provide evidence that GLP-1 secretion from the tumor was the cause of hyperinsulinemic hypoglycemia.GLP-1 levels were determined in the patient, and immunohistochemistry for GLP-1 was performed on the tumor metastases. Ex vivo tissue culture and a bioassay constructed by transplantation of tumor into nude mice were performed to examine the tumor secretory products and their effects on islet cell function.The patient had high levels of glucagon and GLP-1 with an exaggerated GLP-1 response to oral glucose. Immunohistochemistry and primary tissue culture demonstrated secretion of glucagon and GLP-1 from the tumor metastases, whereas insulin secretion was almost undetectable. Ex vivo coculture of the tumor with normal human islets resulted in inhibition of insulin release, and transplanted mice developed impaired glucose tolerance.This is the first description of glucagon and GLP-1 secretion from a metastatic pNET causing sequential diabetes and hypoglycemia. Hypoglycemia was caused by insulin secretion from hyperplastic β-cells stimulated by tumor-derived GLP-1.

OBJECTIVE: To investigate the value of high b value diffusion-weighted (DW) imaging in differentiating between pancreatic carcinoma and mass-forming chronic pancreatitis (MFCP). METHODS: Fifty-one consecutive patients with pathology-proven pancreatic carcinoma (n = 37) or MFCP (n = 14) were evaluated with DW imaging (b value, 0 and 1000 s/mm2) at a 3-T MR system. Overall 20 healthy volunteers were evaluated as the control group. The apparent diffusion coefficient (ADC) values of normal pancreas, pancreatic carcinoma, MFCP, and mass-associated obstructive pancreatitis were measured. RESULTS: On high b value (1000 s/mm2) DW images, both pancreatic carcinoma and MFCP were hyperintense focal lesions; mass-associated obstructive pancreatitis occurred in 17 of 37 (45.9%) pancreatic carcinoma and 8 of 14 (57.1%) MFCP. The ADC (×10−3 mm2/s) of the pancreatic carcinomas (1.06 ± 0.15) was significantly lower than that of normal pancreas (1.47 ± 0.18; P

In ocean science research, it often requires the integrity of the gas content in samples of seawater. The gas-tight deep-sea water sampler (GTWS) based on pressure self-adaptive equalizer (PSAE) can satisfy the requirement very well. The PSAE is required to achieve a reliable dynamic sealing in deep sea. The general O-ring is difficult to meet this requirement. The polytetrafluoroethylene (PTFE)-coated O-ring is chosen as the sealing parts. The finite element analysis (FEA) software ANSYS is used to analyze the contact pressure of the PTFE-coated O-ring in different conditions, that is, analyze the GTWS’s gas tightness theoretically. Combine with the sea trial results, the feasibility and reliability of the PTFE-coated O-ring in deep-sea dynamic sealing in PSAE can be prove both in theory and practice.

A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network dimensioning and planning. This paper investigates the computationally efficient loss performance modeling for multiservice in hierarchical heterogeneous wireless networks. A speed-sensitive call admission control (CAC) scheme is considered in our model to assign overflowed calls to appropriate tiers. This approach avoids unnecessary and frequent handoff between cells and reduces signaling overheads. An approximation model with guaranteed accuracy and low computational complexity is presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated by comparing the results from the approximation with simulations.

To investigate the expression of nerve growth factor (NGF) and glial cell line-derived neurotrophic factor (GDNF) in monkeys of resuscitation after selective cerebral ultraprofound hypothermia and blood flow occlusion. The monkeys were immediately removed brain after death in operation of group A (identical temperature perfusion group) and group B (ultraprofound hypothermia perfusion group). Immunohistochemical technique was used to determine frontal cellular expression of NGF and GDNF. Statistics were analyzed by ANOVA analyses with significance level at P < 0.05. The expressions of NGF and GDNF in the group B were significantly higher than those in the group A (P < 0.05). NGF and GDNF increased significantly in the monkeys of resuscitation after selective cerebral ultraprofound hypothermia and blood flow occlusion. It may be a protective mechanism for neuron survival and neural function recovery.

An electrorheological(ER) actuator with double driving discs rotating at the same speed in the opposite directions was designed for studying the electrorheological torque experiments. The dynamic model of the disc transmission system consists of the linear part between the output angle and the electric torque, and the nonlinear part between the electric torque and the applied field strength dependent on the ER fluids. Using only the output sampled torque signals, an autoregressive model, the auto-spectral density function, the autoregressive(AR) bispectrum and the slices of the bispectra, taken to analyse the torque dynamic response, are obtained when a zero mean and non-Gaussian white noise interferes with the rotary disc system. The method for AR model order selection based on bispectral cross correlation is proposed and employed to determinate the model order. The experimental and theoretical results show that the time series analysis method and the parametric bispectrum might be helpful to establish the dynamic model of an ER actuator and to quantitatively analyse the torque response.