bluuebunny/crossref_metadata_2025 huggingface dataset:
Microfracture development and chemical damage analysis of limestone based on fractal theory
Authors: Chen Luwang , Li Ruirui , Wang Lanting , Zhang Jie , Ou Qinghua , Ren Xingxing , Zhou Kandong
Published: October 2020

To explore the influence of microfracture development caused by chemical dissolution on the mechanical properties of limestone, this paper presents a new numerical simulation and quantitative analysis method. First, the dissolution rate was determined by the theory of chemical kinetics, and a differential equation that can be solved for results of the fracture evolution process by COMSOL Multiphysics was established to describe the microfracture's expansion. The fractal dimensions of the microfractures were found to have a linear relationship with the damage variables at different time periods through analysis of the simulation results with the fractal geometry method using fracture width as the index, which proves that the evolution of damage has a fractal nature. After that, a damage evolution equation was fitted to predict the deterioration in rock mechanical properties under hydrochemical actions and the predictive uniaxial compressive strength of limestone is seen to be in agreement with experimental test results. The application of the fractal geometry method has important engineering significance as it relates the development of microscopic fractures to changes in the macroscopic mechanical properties and predicts the mechanical properties of the rock under chemical damage.
Mitochondrial Quality Control and Restraining Innate Immunity
Authors: Moehlman Andrew T. , Youle Richard J.
Published: October 2020

Maintaining mitochondrial health is essential for the survival and function of eukaryotic organisms. Misfunctioning mitochondria activate stress-responsive pathways to restore mitochondrial network homeostasis, remove damaged or toxic proteins, and eliminate damaged organelles via selective autophagy of mitochondria, a process termed mitophagy. Failure of these quality control pathways is implicated in the pathogenesis of Parkinson's disease and other neurodegenerative diseases. Impairment of mitochondrial quality control has been demonstrated to activate innate immune pathways, including inflammasome-mediated signaling and the antiviral cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING)–regulated interferon response. Immune system malfunction is a common hallmark in many neurodegenerative diseases; however, whether inflammation suppresses or exacerbates disease pathology is still unclear. The goal of this review is to provide a historical overview of the field, describe mechanisms of mitochondrial quality control, and highlight recent advances on the emerging role of mitochondria in innate immunity and inflammation.
Human Embryogenesis: A Comparative Perspective
Authors: Gerri Claudia , Menchero Sergio , Mahadevaiah Shantha K. , Turner James M.A. , Niakan Kathy K.
Published: October 2020

Understanding human embryology has historically relied on comparative approaches using mammalian model organisms. With the advent of low-input methods to investigate genetic and epigenetic mechanisms and efficient techniques to assess gene function, we can now study the human embryo directly. These advances have transformed the investigation of early embryogenesis in nonrodent species, thereby providing a broader understanding of conserved and divergent mechanisms. Here, we present an overview of the major events in human preimplantation development and place them in the context of mammalian evolution by comparing these events in other eutherian and metatherian species. We describe the advances of studies on postimplantation development and discuss stem cell models that mimic postimplantation embryos. A comparative perspective highlights the importance of analyzing different organisms with molecular characterization and functional studies to reveal the principles of early development. This growing field has a fundamental impact in regenerative medicine and raises important ethical considerations.
Developing Therapies for Neurodegenerative Disorders: Insights from Protein Aggregation and Cellular Stress Responses
Authors: Mallucci Giovanna R. , Klenerman David , Rubinsztein David C.
Published: October 2020

As the world's population ages, neurodegenerative disorders are poised to become the commonest cause of death. Despite this, they remain essentially untreatable. Characterized pathologically both by the aggregation of disease-specific misfolded proteins and by changes in cellular stress responses, to date, therapeutic approaches have focused almost exclusively on reducing misfolded protein load—notably amyloid beta (Aβ) in Alzheimer's disease. The repeated failure of clinical trials has led to despondency over the possibility that these disorders will ever be treated. We argue that this is in fact a time for optimism: Targeting various generic stress responses is emerging as an increasingly promising means of modifying disease progression across these disorders. New treatments are approaching clinical trials, while novel means of targeting aggregates could eventually act preventively in early disease.
Preventing and Treating Anthracycline Cardiotoxicity: New Insights
Authors: Sawicki Konrad Teodor , Sala Valentina , Prever Lorenzo , Hirsch Emilio , Ardehali Hossein , Ghigo Alessandra
Published: October 2020

Anthracyclines are the cornerstone of many chemotherapy regimens for a variety of cancers. Unfortunately, their use is limited by a cumulative dose-dependent cardiotoxicity. Despite more than five decades of research, the biological mechanisms underlying anthracycline cardiotoxicity are not completely understood. In this review, we discuss the incidence, risk factors, types, and pathophysiology of anthracycline cardiotoxicity, as well as methods to prevent and treat this condition. We also summarize and discuss advances made in the last decade in the comprehension of the molecular mechanisms underlying the pathology.
Synergetic Effect of 5-Methyl-1H-Benzotriazole and Sodium Dodecyl Benzene Sulfonate on CMP Performance of Ruthenium Barrier Layer in KIO4-Based Slurry
Authors: Xu Yi , Tan Baimei , Hu Lianjun , Liu Yuling
Published: October 2020

The chemical mechanical polishing (CMP) of ruthenium barrier layer of copper interconnection for 14 nm and below technology node has been connected with more challenges, among which the corrosion of copper and ruthenium and the selectivity of removal rate between ruthenium and copper has attracted more attention. This paper mainly focus on the influence of 5-methyl-1H-benzotriazole(MBTA) and sodium dodecyl benzene sulfonate (SDBS) on the polishing properties of copper and ruthenium during ruthenium barrier CMP in the KIO4-based solutions. The results show that the removal rate and corrosion current density of ruthenium decrease with the increase of MBTA concentration. Subsequently, it is demonstrated that the formation of passivating film on ruthenium surface is due to the physisorption of MBTA, which occupies the reaction sites between ruthenium and KIO4 and inhibits the corrosion of ruthenium. SDBS was introduced to KIO4-based solution to compensate for the deficiency of MBTA in inhibiting copper corrosion. It has been proved that the coordinated use of MBTA and SDBS can reduce the copper removal rate to about 326 Å min−1 and obtain acceptable surface morphology. The synergistic inhibition mechanism of MBTA and SDBS on copper corrosion can be elucidated as: under the action of KIO4 and mixed inhibitors, a dense and integrated passivating film is generated on the copper surface to inhibit the excessive corrosion of copper. The passivating film is comprised of Cu–MBTA complex, adsorbed SDBS, copper oxides, Cu(IO4)2 and Cu(IO3)2. The results of CMP and ZRA experiments represent that the combination of MBTA and SDBS can adjust the removal rate selectivity of copper, ruthenium and low-κ dielectrics to 1.56:1:1.01 and evidently alleviate the galvanic corrosion of copper.
Feng‐Liao‐Chang‐Wei‐Kang Combined with 5‐Fluorouracil Synergistically Suppresses Colitis‐Associated Colorectal Cancer via the IL‐6/STAT3 Signalling Pathway
Authors: Zhong Lifan , Yang Fan , Gan Lianfang , Yang Zhaoxin , Tian Shuhong , Huang Mianqing , Lv Chuanzhu , Huang Ling
Published: October 2020

Background. Colitis‐associated colorectal cancer (CAC) develops from active colonic inflammation, which is characterized by the production of proinflammatory cytokines that can induce mutations. IL‐6 is produced by multiple cell types located within the tumor microenvironment including tumor‐infiltrating immune cells, stromal cells, and the tumor cells themselves. The aim of our study was to explore the mechanism of Feng‐Liao‐Chang‐Wei‐Kang (FLCWK) and 5‐fluorouracil (5‐FU) in treating CAC. Method. HCT116 cells were treated with 5‐FU in the absence or presence of FLCWK. Cell proliferation was assayed by MTT assays. Apoptosis and the cell cycle phases were detected by flow cytometry. Western blotting and Q‐PCR assays were used to detect the expression levels of proteins and genes related to the IL‐6/STAT3 signalling pathway. A mouse model for CAC was established by treating animals with 12.5 mg/kg azoxymethane (AOM) followed by 3 cycles of 2.5% dextran sodium sulphate (DSS). The associated pathological changes were determined after haematoxylin and eosin (H&E) staining. The expression of related proteins and genes in various tissues was examined using immunofluorescence techniques. Results. FLCWK enhanced the ability of 5‐FU to promote apoptosis by inhibiting the proliferation of HCT116 cells and blocking the IL‐6/STAT3 pathway. FLCWK combined with 5‐FU reduced the number and size of colon tumors in mice with CAC and significantly increased their survival rate. In the CAC model, FLCWK synergized with 5‐FU to inhibit the phosphorylation of STAT3, preventing IL‐6/STAT3 signal transduction and thus further inducing apoptosis and inhibition of colon cancer cell proliferation. Conclusion. FLCWK can inhibit the activation of STAT3 by reducing the production of IL‐6, thereby increasing the occurrence of colitis‐related colorectal cancer with 5‐FU.
Turing Instability of Brusselator in the Reaction-Diffusion Network
Authors: Ji Yansu , Shen Jianwei
Published: October 2020

Turing instability constitutes a universal paradigm for the spontaneous generation of spatially organized patterns, especially in a chemical reaction. In this paper, we investigated the pattern dynamics of Brusselator from the view of complex networks and considered the interaction between diffusion and reaction in the random network. After a detailed theoretical analysis, we obtained the approximate instability region about the diffusion coefficient and the connection probability of the random network. In the meantime, we also obtained the critical condition of Turing instability in the network-organized system and found that how the network connection probability and diffusion coefficient affect the reaction-diffusion system of the Brusselator model. In the end, the reason for arising of Turing instability in the Brusselator with the random network was explained. Numerical simulation verified the theoretical results.
Comparative Analysis of 95 Patients with Different Severity in the Early Outbreak of COVID-19 in Wuhan, China
Authors: He Fang , Ding Xue-feng , Cao Meng , Gong Hai-ying , Fu Xiang-zhen , Luo Jie , Liu Kui , Tian Zhou-zhou , Luo Lin , Fan Yu-yuan , Li Ting , Yao Qian-Jing , Chen Xiao-ju , Duan Xiang-lin , Chen Li , Jiang Li
Published: October 2020

Objective. To explore the clinical characteristics of patients with different severity in the early outbreak of COVID-19, hoping to provide reference for clinical diagnosis and treatment. Methods. We retrospectively analyzed the clinical data of 95 COVID-19 patients in Wuhan Red Cross Hospital of China from January 17 to February 13, 2020. All patients were investigated with epidemiological questionnaires. Outcomes were followed up until April 1, 2020. Results. There were 53 males and 42 females, aged 22–84 years (mean 57.3 years). Clinical classification included 54 cases of common type, 27 cases of severe type, and 14 cases of critical type. Six patients had been exposed to the local Huanan seafood market. There were 38 clusters of COVID-19, including 27 family clusters and 11 work unit clusters. Common symptoms included fever (86 (90.5%) of 95), cough (73 (76.8%)), and fatigue (50 (52.6%)). Laboratory findings showed that the most common abnormalities were lymphopenia (75 (78.9%)), elevated D-dimer (60 (63.2%)), and elevated C-reactive protein (56 (58.9%)) on admission. All patients had abnormal chest computed tomography, showing patchy shadows or ground-glass opacities. Severe and critical cases were older, more likely to have shortness of breath, more likely to have underlying comorbidities, and more likely to have abnormal laboratory findings than common cases. The prognosis of patients with different degrees of severity was significantly different. All common and severe patients (100%) were cured and discharged from the hospital, while 10 (71.4%) of 14 critical patients died. Conclusions. COVID-19 has fast transmission speed and high pathogenicity. We must assess the severity of the disease and take corresponding treatment measures as early as possible.
[Retracted] Effect of Dexmedetomidine on Postoperative Lung Injury during One‐Lung Ventilation in Thoracoscopic Surgery
Authors: Meng Jun , Lv Qin , Yao Jiaxiang , Wang Siyu , Yang Kun
Published: October 2020

Objective. To investigate the effect of dexmedetomidine on postoperative lung injury in patients undergoing thoracoscopic surgery. Methods. From March 2019 to October 2019, 40 patients were randomly divided into two groups: dexmedetomidine group (group D) and control group (group C). Except recording the general condition of the patients in both groups preoperatively and intraoperatively, the oxygenation index (OI) and alveolar‐arterial oxygen partial pressure difference (A‐aDO2) were monitored at admission (T0), immediately after one‐lung ventilation (T1), 0.5 h after one‐lung ventilation (T2), and 15 minutes after inhaling air before leaving the room (T3). The content of IL‐8 in arterial blood was measured by enzyme‐linked immunosorbent assay (ELISA) at T0 and T2, and the expression of AQP1 protein in isolated lung tissue was measured by immunohistochemistry and Western blot. The incidence of postoperative pulmonary complications (atelectasis, pneumonia, and acute respiratory distress syndrome) was used as the index of lung injury. Results. There was no significant difference in the general condition before and during operation between the two groups. There was no significant difference in arterial blood IL‐8 content between the two groups at the T0 time point, but the arterial blood IL‐8 content at the T2 time point was significantly higher than that at the T0 time point, especially in group C. The results of immunohistochemistry and Western blot showed that the expression level of AQP1 protein in the isolated lung tissue of group D was significantly higher than that of group C (P < 0 05). At T3, the OI of group D was significantly higher than that of group C, and the A‐aDO2 of group D was significantly lower than that of group C (P < 0.05). There was no significant difference in the incidence of postoperative PPCs between the two groups. Conclusion. Dexmedetomidine can reduce the level of plasma IL‐8 and upregulate the expression of AQP1 in the lung tissue of patients undergoing thoracoscopic surgery under one‐lung ventilation, but it has no significant effect on the incidence of postoperative PPCs. Dexmedetomidine can be safely used in thoracoscopic surgery and has a certain protective effect on lung injury.
Personal Credit Default Prediction Model Based on Convolution Neural Network
Authors: Zhou Xiang , Zhang Wenyu , Jiang Yefeng
Published: October 2020

It has great significance for the healthy development of credit industry to control the credit default risk by using the information technology. For some traditional research about the credit default prediction model, more attention is paid to the model accuracy, while the business characteristics of the credit risk prevention are easy to be ignored. Meanwhile, to reduce the complicity of the model, the data features need be extracted manually, which will decrease the high-dimensional correlation among the analyzing data and then result in the low prediction performance of the model. So, in the paper, the CNN (convolutional neural network) is used to establish a personal credit default prediction model, and both ACC (accuracy) and AUC (the area under the ROC curve) are taken as the performance evaluation index of the model. Experimental results show the model ACC (accuracy) is above 95% and AUC (the area under the ROC curve) is above 99%, and the model performance is much better than the classical algorithm including the SVM (support vector machine), Bayes, and RF (random forest).
The Inertial Integrated Navigation Algorithms in the Polar Region
Authors: Song Li-Jun , Yang Guang-Qiao , Zhao Wang-Liang , Ding You-Jun , Wu Feng , He Xing
Published: October 2020

Because the accuracy of the existing airborne navigation is lacking in the polar region, it is difficult to ensure the safety and reliability of the aircraft when it is flying over the polar region. The integrated navigation system based on the inertial navigation technology uses multi-information fusion to assist collaborative navigation and obtain an indirect grid navigation algorithm that combines the azimuth navigation algorithm and the grid navigation algorithm to solve the existing problems. This paper analyzes the principle of the inertial navigation system in the polar region, the semiphysical simulation experiments are carried out by using the navigation theory and the background engineering, and the accuracies of the integrated navigation system of the indirect grid frame in the polar region and the integrated navigation system in the middle and low latitudes are consistent, which verifies the feasibility and effectiveness of the SINS/CNS/GPS integrated navigation system in the polar region. In addition, the paper provides the theoretical basis and the application of engineering to achieve the SINS/CNS/GPS integrated navigation system in the polar region.
Peptide Extracts from Native Lactic Acid Bacteria Generate Ghost Cells and Spheroplasts upon Interaction with Salmonella enterica, as Promising Food Antimicrobials
Authors: Tenea Gabriela N.
Published: October 2020

Protecting foods from contamination applying peptides produced by lactic acid bacteria is a promising strategy to increase the food quality and safety. Interacting with the pathogen membranes might produce visible changes in shape or cell wall damage. Previously, we showed that the peptides produced by Lactobacillus plantarum UTNGt2, Lactobacillus plantarum UTNCys5‐4, and Lactococcus lactis subsp. lactis UTNGt28 exhibit a broad spectrum of antibacterial activity against several foodborne pathogens in vitro. In this study, their possible mode of action against the commensal microorganism Salmonella enterica subsp. enterica ATCC51741 was investigated. The target membrane permeability was determined by detection of beta‐galactosidase release from ONPG (o‐nitro‐phenyl‐L‐D‐galactoside) substrate and changes in the whole protein profile indicating that the peptide extracts destroy the membrane integrity and may induce breaks in membrane proteins to some extent. The release of aromatic molecules such as DNA/RNA was detected after the interaction of Salmonella with the peptide extract. Transmission electronic microscopy (TEM) micrographs depicted at least four simultaneous secondary events after the peptide extract treatment underlying their antimicrobial actions, including morphological alterations of the membrane. Spheroplast and filament formation, vacuolation, and DNA relaxation were identified as the principal events from the Gt2 and Cys5‐4 peptide extracts, while Gt28 induced the formation of ghost cells by release of cytoplasmic content, filaments, and separation of cell envelope layers. Gel retarding assays indicate that the Gt2 and Gt28 peptide extracts are clearly binding the Salmonella DNA, while Cys5‐4 partially interacted with Salmonella genomic DNA. These results increased our knowledge about the inhibitory mechanism employed by several peptide extracts from native lactic acid bacteria against Salmonella. Further, we shall develop peptide‐based formulation and evaluate their biocontrol effect in the food chains.
The Possibility of China’s Industrial Park Management Committee to Promote Interenterprise Cooperative Innovation in the Park: A Trilateral Evolutionary Game Perspective
Authors: Guo Zhuopin , Zhen Jie , Qu Yiying , Ren Hao
Published: October 2020

Under China’s distinct policy-driven agglomeration approach, the Chinese industrial park displays a low degree of industrial relevance and weak cooperation among enterprises in the park. The key to solving this problem lies in the guiding role of the park management committee. Accordingly, this study constructs a trilateral evolutionary game model of interenterprise cooperative innovation inside the industrial park under the supervision of the park management committee, leadership of the core enterprises, and with the participation of the small- and medium-sized enterprises. Through simulation analysis, this study explores the influencing factors behind the trilateral cooperative innovation strategy choices. Results show that (1) the park management committee, core enterprises, and small- and medium-sized enterprises have different degrees of influence on each other’s willingness to participate in cooperative innovation; (2) small- and medium-sized enterprises are sensitive to the management committee’s policy support, and core enterprises are sensitive to the management committee’s financial support; (3) core enterprises are more sensitive to penalties and income distribution than small- and medium-sized enterprises; (4) the degree of resource complementarity and trust among enterprises has a profound effect on core enterprises and small- and medium-sized enterprises’ willingness to participate in cooperative innovation.
A Big Data Analytics Approach for Dynamic Feedback Warning for Complex Systems
Authors: Li Wenrui , Li Menggang , Mei Yiduo , Li Ting , Wang Fang
Published: October 2020

With the development of science and technology, the application of big data is becoming more and more widespread, and it has gradually expanded to various fields such as economy and commerce. Since the 2008 international financial crisis, the mainstream economics has shown deficiencies to a certain extent. On the one hand, the expressions pursued by mainstream economic theories are too strict, restricting its processing capabilities. On the other hand, the linearization method ignores the diversity, complexity, and variability of changes in the economic system, which may ignore the emergence of some serious crises. Due to the increasing distance between theoretical models and practice, theoretical models cannot guide the practice and sometimes even mislead the latter. In this paper, we propose a method of dynamic feedback early warning based on big data, which uses the LPPL model to fit parameters. Finally, we used this method to analyze the case of the A-share disaster. The research results show that the method makes the early warning coefficients of dynamic and complex systems more scientific and accurate.
Establishment of a Financial Crisis Early Warning System for Domestic Listed Companies Based on Three Decision Tree Models
Authors: Wang Gang , Wang Keming , Zhou Yingying , Mo Xiaoyan , Xiao Weilin
Published: October 2020

The financial crisis is a realistic problem that the general enterprise must encounter in the process of financial management. Due to the impact of the COVID-19 and the Sino-US trade war, domestic companies with unsound financial conditions are at risk of shutdowns and bankruptcies. Therefore, it is urgently needed to study the financial warning of enterprises. In this study, three decision tree models are used to establish the financial crisis early warning system. These three decision tree models include C50, CART, and random forest decision trees. In addition, the ROC curve was used for comprehensive evaluation of the accuracy analysis of the model to confirm the predictive ability of each model. This result can provide reference for domestic financial departments and provide financial management basis for the investing public.
Enhancing Satellite Clock Bias Prediction Accuracy in the Case of Jumps with an Improved Grey Model
Authors: Yu Ye , Huang Mo , Duan Tao , Wang Changyuan , Hu Rui
Published: October 2020

High accuracy and reliable predictions of the bias of in-orbit atomic clocks are crucial to the application of satellites, while their clocks cannot transfer time information with the earth stations. It brings forward a new short-term, mid-long-term, and long-term prediction approach with the grey predicting model (GM(1, 1)) improved by the least absolute deviations (GM(1, 1)-LAD) when there are abnormal cases (larger fluctuations, jumps, and/or singular points) in SCBs. Firstly, it introduces the basic GM(1, 1) models. As the parameters of the conventional GM(1, 1) model determined by the least squares method (LSM) is not the best in these cases, leading to magnify the fitting errors at the abnormal points, the least absolute deviations (LAD) is used to optimize the conventional GM(1, 1) model. Since the objective function is a nondifferentiable characteristic, some function transformation is inducted. Then, the linear programming and the simplex method are used to solve it. Moreover, to validate the prediction performances of the improved model, six prediction experiments are performed. Compared with those of the conventional GM(1, 1) model and autoregressive moving average (ARMA) model, results indicate that (1) the improved model is more adaptable to SCBs predictions of the abnormal cases; (2) the root mean square (RMS) improvement for the improved model are 5.7%∼81.7% and 6.6%∼88.3%, respectively; (3) the maximum improvement of the pseudorange errors (PE) and mean absolute errors (MAE) for the improved model could reach up to 88.30%, 89.70%, and 87.20%, 85.30%, respectively. These results suggest that our improved method can enhance the prediction accuracy and PE for these abnormal cases in SCBs significantly and effectively and deliver a valuable insight for satellite navigation.
Synthesis and Characterization of Hierarchical Mesoporous-Macroporous TiO2-ZrO2 Nanocomposite Scaffolds for Cancellous Bone Tissue Engineering Applications
Authors: Mahtabian Shima , Yahay Zahra , Mirhadi Seyed Mehdi , Tavangarian Fariborz
Published: October 2020

Bone tissue engineering has been introduced several decades ago as a substitute for traditional grafting techniques to treat bone defects using engineered materials. The main goal in bone tissue engineering is to introduce materials and structures which can mimic the function of bone to restore the damaged tissue and promote cell restoration and proliferation. Titania and zirconia are well-known bioceramics which have been widely used in tissue engineering applications due to their unsurpassed characteristics. In this study, hierarchical meso/macroporous titania-zirconia (TiO2-ZrO2) nanocomposite scaffolds have been synthesized and evaluated for bone tissue engineering applications. The scaffolds were produced using the evaporation-induced self-assembly (EISA) technique along with the foamy method. To characterize the samples, X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), simultaneous thermal analysis (STA), and Brunauer-Emmett-Teller (BET) analysis were performed. The results showed that TiO2-ZrO2 scaffolds can be produced after sintering the samples at 550°C for 2 h. Among samples with different weight percentages of zirconia and titania, the sample containing 13 wt.% zirconia was considered as the optimum sample due to its structural integrity. This scaffold had pore size, pore wall size, and mesopores in the range of 185±66 μm, 15±4 μm, and 7-13 nm, respectively. The specific surface area obtained from the BET theory, total volume, and mean diameter of pores of this sample was 13.627 m2g1-, 0.03788 cm3g-1, and 11 nm, respectively. The results showed that the produced scaffolds can be considered as the promising candidates for cancellous bone regeneration.
R-CNN-Based Satellite Components Detection in Optical Images
Authors: Chen Yulang , Gao Jingmin , Zhang Kebei
Published: October 2020

The accurate detection of satellite components based on optical images can provide data support for aerospace missions such as pointing and tracking between satellites. However, the traditional target detection method is inefficient when performing calculations and has a low detection precision, especially when the attitude of the satellite and illumination conditions change considerably. To enable the precise detection of satellite components, we analyse the imaging characteristics of a satellite in space and propose a method to detect the satellite components. This approach is based on a regional-based convolutional neural network (R-CNN), and it can enable the accurate detection of various satellite components by using optical images. First, on the basis of the Mask R-CNN, we combine the DenseNet, ResNet, and FPN to construct a new feature extraction structure and obtain the R-CNN based satellite-component-detection model (RSD). The feature maps are extracted and concatenated at a deeper multiscale level, and the feature propagation between each layer is enhanced by providing a dense connection. Next, an information-rich satellite dataset is constructed, which is composed of images of various kinds of satellites from various perspectives and orbital positions. The detection model is trained and optimized on the constructed dataset to obtain the satellite component detection model. Finally, the proposed RSD model and original Mask R-CNN are tested on the same established test set. The experimental results show that the proposed detection model has higher precision, recall rate, and F1 score. Therefore, the proposed approach can effectively detect satellite components, based on optical images.
Short Bowel Syndrome and Kidney Transplantation: Challenges, Outcomes, and the Use of Teduglutide
Authors: Abou Diwan Elizabeth , Patel Ankit B. , Cuenca Alex G. , Elias Nahel , Gilligan Hannah M. , Heher Eliot , Leaf David E. , Wojciechowski David , Safa Kassem
Published: October 2020

Among patients with short bowel syndrome who commonly have kidney disease, kidney transplantation remains challenging. We describe the clinicopathologic course of a 59-year old man with short bowel syndrome secondary to Crohn’s disease who underwent a deceased donor kidney transplant that was complicated by recurrent acute kidney allograft injury due to volume depletion from diarrhea, ultimately requiring the placement of permanent intravenous access for daily volume expansion at home resulting in the recovery of allograft function. Teduglutide treatment at 1.8 years post-transplant led to a dramatic decrease in diarrhea. A literature review of similar cases yielded 18 patients who underwent 19 kidney transplants. Despite high rates of complications, at the time of last follow-up (median 2.1 years [0.04-7]), 94% of the patients were still alive and 89% had functioning allografts, with a median eGFR of 37.5 [14-122] ml/min/1.73m2. In conclusion, despite high rates of complications, kidney transplantation in patients with short bowel syndrome is associated with acceptable short- and midterm outcomes. Further, we report for the first time the effects of the glucagon-like peptide-2 analogue teduglutide for short bowel syndrome in a kidney transplant recipient.
Reconstruction of Total Bone Defects following Resection of Malignant Tumors of the Upper Extremity with 3D Printed Prostheses: Presentation of Two Patients with a Follow-Up of Three Years
Authors: Ackmann Thomas , Klingebiel Sebastian , Gosheger Georg , Rachbauer Anna , Theil Christoph , Andreou Dimosthenis
Published: October 2020

Wide tumor resection is the local treatment of choice for patients with primary malignant bone tumors and a prerequisite for long-term survival. We present two patients that underwent total bone resection in the upper limb because of primary malignant bone tumors. The defects were then reconstructed by a 3D printed prosthesis, a procedure that, to our knowledge, has not been reported for bone defects of the upper extremity so far. Complete resection of the affected bone was required in a five-year-old girl with a high-grade osteoblastic osteosarcoma of the humerus and a 53-year-old man with a dedifferentiated leiomyosarcoma of the radius, due to the tumor’s extent. Following neoadjuvant chemotherapy, resection of the entire affected humerus including the axillary nerve took place in the first case and the entire affected radius including parts of the radial nerve in the second case. Approximately three years after surgery, both patients are alive and pain-free. Despite a postoperative drop hand that affected the now 56-year-old man, he is able to carry out everyday activities such as brushing his teeth, writing, and eating. The now eight-year-old girl is also able to engage in normal activities with her left arm such as eating and carrying lightweight objects. Both patients are tumor-free to date.
A Host-Based Anomaly Detection Framework Using XGBoost and LSTM for IoT Devices
Authors: Wang Xiali , Lu Xiang
Published: October 2020

The Internet of Things (IoT) is rapidly spreading in various application scenarios through its salient features in ubiquitous device connections, ranging from agriculture and industry to transportation and other fields. As the increasing spread of IoT applications, IoT security is gradually becoming one of the most significant issues to guard IoT devices against various cybersecurity threats. Usually, IoT devices are the main components responsible for sensing, computing, and transmitting; in this case, how to efficiently protect the IoT device itself away from cyber attacks, like malware, virus, and worm, becomes the vital point in IoT security. This paper presents a brand new architecture of intrusion detection system (IDS) for IoT devices, which is designed to identify device- or host-oriented attacks in a lightweight manner in consideration of limited computation resources on IoT devices. To this end, in this paper, we propose a stacking model to couple the Extreme Gradient Boosting (XGBoost) model and the Long Short-Term Memory (LSTM) model together for the abnormal state analysis on the IoT devices. More specifically, we adopt the system call sequence as the indicators of abnormal behaviors. The collected system call sequences are firstly processed by the famous n-gram model, which is a common method used for host-based intrusion detections. Then, the proposed stacking model is used to identify abnormal behaviors hidden in the system call sequences. To evaluate the performance of the proposed model, we establish a real-setting IP camera system and place several typical IoT attacks on the victim IP camera. Extensive experimental evaluations show that the stacking model has outperformed other existing anomaly detection solutions, and we are able to achieve a 0.983 AUC score in real-world data. Numerical testing demonstrates that the XGBoost-LSTM stacking model has excellent performance, stability, and the ability of generalization.
Bilateral Pseudoarthrosis of the Medial End of the Clavicles: A Rare Case Report with a Two-Year Follow-Up
Authors: Braga Júnior Manuel Bomfim , de Souza Argos Queiroz Alves , Bitencourt Júnior Carlos Augusto Belchior , de Alencar Fernando Henrique Uchôa , Lôbo Renan Teixeira , de Alencar Neto Jonatas Brito , Lira Réjelos Charles Aguiar
Published: October 2020

Bilateral clavicle fractures are considered rare. Most of the cases are caused by high energy traumas, such as automobile accidents. Such fracture is related to a higher frequency and severity of associated lesions. In this report, the authors present a twenty-two-year-old male patient’s case who, after a motorcycle collision, suffered a bilateral medial end clavicle closed fracture, developing asymptomatic bilateral pseudoarthrosis after the patient refuses surgical treatment. The presented case is quite rare. Aspect related to the patient’s evolution during treatment will be discussed, plus the fracture mechanism, associated injuries, the bilateral clavicular fractures treatment, and management in cases of pseudoarthrosis will be analyzed.
The Impact of Length-Scale Variation When Diagnosing the Standard Deviations of Background Error in a 4D-Var System and Filtering Method Investigation
Authors: Xing Xiang , Liu Bainian , Zhang Weimin , Cao Xiaoqun , Leng Hongze
Published: October 2020

The four-dimensional variational data assimilation (4D-Var) method has been widely employed as an operational scheme in mainstream numerical weather prediction (NWP) centers. In addition to the ensemble data assimilation method, the randomization technique is still used to diagnose the standard deviations of background error in variational data assimilation (VAR) systems; however, such randomization techniques induce sampling noise, which may contaminate the quality of the standard deviations. First, this paper studies the properties of the sampling noise induced by the randomization technique. The results show that the sampling noise is on a small scale displaying high-frequency oscillations around the estimate compared with the estimate and this difference motivates the use of filtering techniques to eliminate the sampling noise effects. The characteristics of the standard deviation field of the control variables are also investigated, and the standard deviation fields of different model parameters have different scales and vary with the vertical model levels. To eliminate such sampling noise, the spectral filtering method used widely in the operational system and a modified spatial averaging approach are investigated. Although both methods have splendid performance in eliminating sampling noise, the spatial averaging approach is more efficient and easier to implement in operational systems. In addition, the optimal filtered results from the spatial averaging approach are dependent on model parameters and vertical levels, which is consistent with the variation in the standard deviation field. Finally, the spatial averaging approach is tested on the operational system at the global scale based on the YH4DVAR and the global NWP system, and the results indicate that the spatial averaging approach has positive effects on both analysis and forecast quality.
Chlamydia trachomatis Infection, when Treated during Pregnancy, Is Not Associated with Preterm Birth in an Urban Safety-Net Hospital
Authors: Vercruysse Jessica , Mekasha Samrawit , Stropp Lisa Movilla , Moroney James , He Xianbao , Liang Yanmei , Vragovic Olivera , Valle Eduardo , Ballard Jennifer , Pudney Jeffrey , Kuohung Wendy , Ingalls Robin R.
Published: October 2020

Preterm birth is a major public health problem, occurring in more than half a million births per year in the United States. A number of maternal conditions have been recognized as risk factors for preterm birth, but for the majority of cases, the etiology is not completely understood. Chlamydia trachomatis is one of the most prevalent sexually transmitted infections in the world. However, its role in adverse pregnancy outcome in women is still debated. In order to determine if genitourinary tract infection with C. trachomatis during pregnancy was associated with preterm birth, we conducted a case-control study on women who delivered at Boston Medical Center, an urban “safety-net” hospital that serves a socioeconomically disadvantaged and racially diverse population. Women with known risk factors for preterm birth or immune suppression were excluded. Variables collected on enrolled subjects included demographics; diagnosis of C. trachomatis during or prior to pregnancy; tobacco, alcohol, and illicit substance use; gestational age; and birthweight and gender of the newborn. We also collected urine for chlamydia testing at the time of delivery and placental biopsies for nucleic acid amplification and histological studies. A total of 305 subjects were enrolled: 100 who delivered preterm and 205 who delivered full term. Among those subjects, we identified 19 cases of pregnancy-associated C. trachomatis infection: 6/100 preterm and 13/205 full term, a difference which was not statistically significant. Only two cases of untreated chlamydia infection were identified postpartum, and both occurred in women who delivered at term. We conclude that genitourinary tract infection with C. trachomatis during pregnancy, when appropriately treated, is not associated with preterm birth.
A Novel Inhibitor of HSP70 Induces Mitochondrial Toxicity and Immune Cell Recruitment in Tumors
Authors: Barnoud Thibaut , Leung Jessica C. , Leu Julia I-Ju , Basu Subhasree , Poli Adi Narayana Reddy , Parris Joshua L.D. , Indeglia Alexandra , Martynyuk Tetyana , Good Madeline , Gnanapradeepan Keerthana , Sanseviero Emilio , Moeller Rebecca , Tang Hsin-Yao , Cassel Joel , Kossenkov Andrew V. , Liu Qin , Speicher David W. , Gabrilovich Dmitry I. , Salvino Joseph M. , George Donna L. , Murphy Maureen E.
Published: October 2020

The protein chaperone HSP70 is overexpressed in many cancers including colorectal cancer, where overexpression is associated with poor survival. We report here the creation of a uniquely acting HSP70 inhibitor (HSP70i) that targets multiple compartments in the cancer cell, including mitochondria. This inhibitor was mitochondria toxic and cytotoxic to colorectal cancer cells, but not to normal colon epithelial cells. Inhibition of HSP70 was efficacious as a single agent in primary and metastatic models of colorectal cancer and enabled identification of novel mitochondrial client proteins for HSP70. In a syngeneic colorectal cancer model, the inhibitor increased immune cell recruitment into tumors. Cells treated with the inhibitor secreted danger-associated molecular patterns (DAMP), including ATP and HMGB1, and functioned effectively as a tumor vaccine. Interestingly, the unique properties of this HSP70i in the disruption of mitochondrial function and the inhibition of proteostasis both contributed to DAMP release. This HSP70i constitutes a promising therapeutic opportunity in colorectal cancer and may exhibit antitumor activity against other tumor types.

Significance:

These findings describe a novel HSP70i that disrupts mitochondrial proteostasis, demonstrating single-agent efficacy that induces immunogenic cell death in treated tumors.
Fructose Promotes Cytoprotection in Melanoma Tumors and Resistance to Immunotherapy
Authors: Kuehm Lindsey M. , Khojandi Niloufar , Piening Alexander , Klevorn Lauryn E. , Geraud Simone C. , McLaughlin Nicole R. , Griffett Kristine , Burris Thomas P. , Pyles Kelly D. , Nelson Afton M. , Preuss Mary L. , Bockerstett Kevin A. , Donlin Maureen J. , McCommis Kyle S. , DiPaolo Richard J. , Teague Ryan M.
Published: October 2020

Checkpoint blockade immunotherapy relies on the empowerment of the immune system to fight cancer. Why some patients fail to achieve durable clinical responses is not well understood, but unique individual factors such as diet, obesity, and related metabolic syndrome could play a role. The link between obesity and patient outcomes remains controversial and has been mired by conflicting reports and limited mechanistic insight. We addressed this in a C57BL/6 mouse model of diet-induced obesity using a Western diet high in both fats and sugars. Obese mice bearing B16 melanoma or MC38 carcinoma tumors had impaired immune responses to immunotherapy and a reduced capacity to control tumor progression. Unexpectedly, these compromised therapeutic outcomes were independent of body mass and, instead, were directly attributed to dietary fructose. Melanoma tumors in mice on the high-fructose diet were resistant to immunotherapy and showed increased expression of the cytoprotective enzyme heme oxygenase-1 (HO-1). This increase in HO-1 protein was recapitulated in human A375 melanoma cells exposed to fructose in culture. Induced expression of HO-1 shielded tumor cells from immune-mediated killing and was critical for resistance to checkpoint blockade immunotherapy, which could be overcome in vivo using a small-molecule inhibitor of HO-1. This study reveals dietary fructose as a driver of tumor immune evasion, identifying HO-1 expression as a mechanism of resistance and a promising molecular target for combination cancer immunotherapy.

See article by Khojandi et al., p. 214
Developing a Machine Learning Algorithm for Identifying Abnormal Urothelial Cells: A Feasibility Study
Authors: Zhang Zhihui , Fu Xinyan , Liu Jiwei , Huang Zhen , Liu Natalia , Fang Fengqi , Rao Jianyu
Published: October 2020

Introduction: Urine cytology plays an important role in diagnosing urothelial carcinoma (UC). However, urine cytology interpretation is subjective and difficult. Morphogo (ALAB, Boston, MA, USA), equipped with automatic acquisition and scanning, optical focusing, and automatic classification with convolutional neural network has been developed for bone marrow aspirate smear analysis of hematopoietic diseases. The goal of this preliminary study was to determine the feasibility of developing a machine learning algorithm on Morphogo for identifying abnormal urothelial cells in urine cytology slides. Methods: Thirty-seven achieved abnormal urine cytology slides from cases with the diagnosis of atypical urothelial cells and above (suspicions or positive for UC) were obtained from 1 hospital. A pathologist (J.R.) reviewed the slides and manually selected and annotated representative cells to feed into Morphogo with following categories: benign (urothelial cells, squamous cells, degenerated cells, and inflammatory cells), atypical cells, and suspicious cells. Initial validation of the algorithm was performed on a subset of the original 37 cases. Urine samples from additional 12 unknown cases with various histological diagnoses (6 cases of high-grade urothelial carcinoma (HGUC), 1 case of low-grade urothelial carcinoma (LGUC), 1 case of prostate adenocarcinoma, 1 case of renal cell carcinoma, and 4 cases of non-neoplastic conditions) were collected from another hospital for initial blind testing. Results: A total of 1,910 benign and 1,978 abnormal (atypical and suspicious) cells from 37 slides were annotated for developing and training of the algorithm. This algorithm was validated on 27 slides that resulted in identification of at least 1 abnormal cell per slide, with a total of 200 abnormal cells, and an average of 7.4 cells per slide. Of the 12 unknown cases tested, the original cytology was positive for tumor cells in 2 HGUC samples. Morphogo was abnormal (atypical or suspicious) for 6 samples from patients with UC, including one with LGUC and one with prostate adenocarcinoma. Conclusion: Morphogo machine learning algorithm is capable of identifying abnormal urothelial cells. Further validation studies with a larger number of urine samples will be needed to determine if it can be used to assist the cytological diagnosis of UC.