bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Sports Training Data Monitoring System Based on Wireless Internet of Things
Authors: Yao Wang , Zhihai Zhang
Published: September 2022

With the development of the times and the continuous improvement of science and technology, people’s living standards are getting better and better, living conditions are getting more and more abundant, the infrastructure of cities is becoming more and more perfect, the comprehensive strength of the country is constantly increasing, and the speed of development is also increasing fast. However, under conditions of continuous development, the physical health of adolescents and children has not improved, the physical fitness of adolescents has declined, and many problems have appeared. This survey will combine embedded software and Internet technology, focusing on testing the safety of the sports training system and collecting data. It is very necessary for us to investigate the safety of the sports training system. The system also has potential for development. Only when the safety of the sports training system is determined can we understand the most suitable exercise methods for contemporary youths and ensure that they are not right in order to make the relevant sports training methods more confidently when a second injury occurs to the body. The sports training system to be studied this time consists of three basic technologies, namely, data collection terminals, database stations, and web servers. We will install the relevant equipment of the data collection system in the campus, such as teaching buildings or campus buildings and roads on the open space next to it, and a chip with a wireless transmission system will be placed in the student’s campus card. This chip is small in size, high in transmission efficiency, and easy to carry by students. Therefore, when each student holds the campus card, the related equipment in the campus card will be signal linked with the equipment installed in the school. This mode is wireless, which is very convenient and fast. In this way, we can collect the identity information and money storage status of the campus card through the web server. When the student ID is displayed on the computer screen, it proves that the student has swiped the card successfully.
Presentation of Machine Learning Approaches for Predicting the Severity of Accidents to Propose the Safety Solutions on Rural Roads
Authors: Habibzadeh Mohammad , Ameri Mahmoud , Ziari Hassan , Kamboozia Neda , Sadat Haghighi Seyede Mojde
Published: September 2022

The aim of the current research was to develop models to predict the severity of accidents on rural roads in Tehran province, Iran. In this regard, using accident data from 2017 to 2020, the machine learning algorithms, including multiple logistic regression, multilayer perceptron neural network (MLPNN), and radial basis function neural network (RBFNN) models, as well as statistical methods, including Kolmogorov–Smirnov test, Friedman test, and factor analysis, were implemented to determine the contributory factors in the severity of accidents. Thus, nine variables affecting the severity of accidents were considered in modeling, and then the effect of each variable was calculated. By comparing the results of artificial neural network (ANN) models and the Friedman test, it was indicated that the human factor had a remarkable effect on accident severity. In addition, both machine learning and statistical methods can be served as guidance for safety authorities to provide safety solutions, thereby leading to reducing accidents. Finally, the performances of ANN models were analyzed by other mathematical models built by MATLAB programming.
Construction of Online Shopping Legal Protection Mechanism Based on Artificial Intelligence Technology
Authors: Yan Pingyan , Zhang Shimei
Published: September 2022

With the rapid development of the Internet and social economy, in the process of online shopping, a series of problems frequently occur, the most serious of which is tort and rights protection, but laws and regulations often lag behind the development of e-commerce transactions. Artificial intelligence technology embodies the exchange and use of digital information, which is an inevitable trend in the development of modern society. The research object of this research is students. Based on the connotation and significance of artificial intelligence technology, it aims to put forward effective solutions and suggestions to the law problems that arise in the online shopping process of students through some data analysis obtained by artificial intelligence technology, so as to provide reference for guiding student groups to form correct consumption concepts and promoting relevant institutions to maintain a safe and reasonable online shopping mechanism and platform environment. According to the above goals, this research combines the Agent technology in the field of artificial intelligence, proposes and builds a legal protection system framework that meets the requirements of online shoppers, discusses how to use the law to regulate infringement and rights protection in the process of online shopping, and has implications for improving the legal system in the process of online shopping.
Application of Internet of Things Audio Technology Based on Parallel Storage System in Music Classroom
Authors: Kai Hong
Published: September 2022

In order to improve the effect of music classroom teaching, this paper combines the parallel storage system and the Internet of Things audio technology to construct a music education system to improve the effect of music education in colleges and universities. Moreover, this paper expounds a grid-free method for sparsity and parameter estimation from the model and mathematical principles and proposes a grid-free DOA method based on fast reconstruction of the T-matrix. This method is guaranteed to produce sparse parameter estimates. At the same time, the numerical simulation shows that the method has stable estimation performance as sparse and parameter estimation methods. In addition, this paper constructs a music classroom teaching system based on parallel storage system and Internet of Things audio technology. Through the experimental research, it can be seen that the parallel storage system and the Internet of Things audio technology has obvious application effect in the music classroom, which can effectively improve the teaching effect of the music classroom.
A Local Alternative to Global Wholesale Online Schooling during COVID-19: A Phenomenological Single-Case Study of a Standalone School in Bangladesh
Authors: Alam Md. Saiful , Asmawi Adelina , Fatema Sayeda , Ullah Md. Mohib , Azad Md. Abul Kalam
Published: September 2022

Given the shutdown of the schools worldwide thanks to COVID-19 pandemic hit early in 2020, there had been, for a while, a mounting global concern over continuing education and averting children’s learning loss. Paying heed to that concern, many nations across the world transitioned to online education as a wholesale alternative approach to emergency schooling. However, online schooling was no single panacea specially for those developing countries which are hardly able to meet the success conditions of online teaching and learning. This phenomenological case study describes a novel pandemic-time rural schooling activity as an alternative to the wholesale online education commonly adopted globally during the pandemic. We have theoretically based the study on the Activity Theories postulated by Vygotsky and Cole and extended by Engeström. We collected qualitative data by semistructured interviews and by gathering school documents. Following Williams and Moser’s coding method and Miles et al.’s two-cycle coding process, we analyzed the collected data. The novel schooling activity that this study found is “clustered (sub-)schools” made up of the split-ups of the regular school. The findings in detail are discussed and recommendations are made.
Optimal Bidding Strategy of a Pumped Hydro Energy Storage Integrated Nuclear Power Plant considering Possible Outage
Authors: Uğuz Fatih , Turan Abdulkerim , Gökçek Tayfur , Ateş Yavuz , Erdinç Ozan
Published: September 2022

Recently, harmful gases emitted into the atmosphere disrupt the balance of nature and cause climate changes. The tendency towards renewable energy is increasing in order to prevent climate change. The importance of the conventional power plants in the power system is maintained due to the intermittent nature of renewable energy sources. In this regard, nuclear power which is one of the conventional power plants takes attention. In this study, a new approach for optimal scheduling of a Pumped Hydro Energy Storage (PHES) integrated Nuclear Power Plant (NPP) system is proposed. It is expected that PHES provides significant economic contribution to the grid operator especially by ensuring energy supply security of the NPP. Two different market types named Day Ahead Market (DAM) and Balancing Market (BM) in Turkey are implemented in the trades by using real electricity prices obtained from Energy Exchange Istanbul (EXIST), which is Energy Market Operator in Turkey. In order to evaluate the effectiveness of the proposed model, seasonal impacts of four different months are also examined in several case studies. Furthermore, sustainability analyzes are conducted considering probability of interruption of the NPP during 8 hours. According to the results, it is observed that promising solutions can be obtained thanks to the integration of the PHES in the presence of the different market types even if outages are planned.
A Natural Language Processing (NLP) Evaluation on COVID-19 Rumour Dataset Using Deep Learning Techniques
Authors: Fatima Rubia , Samad Shaikh Naila , Riaz Adnan , Ahmad Sadique , El-Affendi Mohammed A. , Alyamani Khaled A. Z. , Nabeel Muhammad , Ali Khan Javed , Yasin Affan , Latif Rana M. Amir
Published: September 2022

Context and Background: Since December 2019, the coronavirus (COVID-19) epidemic has sparked considerable alarm among the general community and significantly affected societal attitudes and perceptions. Apart from the disease itself, many people suffer from anxiety and depression due to the disease and the present threat of an outbreak. Due to the fast propagation of the virus and misleading/fake information, the issues of public discourse alter, resulting in significant confusion in certain places. Rumours are unproven facts or stories that propagate and promote sentiments of prejudice, hatred, and fear. Objective. The study’s objective is to propose a novel solution to detect fake news using state-of-the-art machines and deep learning models. Furthermore, to analyse which models outperformed in detecting the fake news. Method. In the research study, we adapted a COVID-19 rumours dataset, which incorporates rumours from news websites and tweets, together with information about the rumours. It is important to analyse data utilizing Natural Language Processing (NLP) and Deep Learning (DL) approaches. Based on the accuracy, precision, recall, and the f1 score, we can assess the effectiveness of the ML and DL algorithms. Results. The data adopted from the source (mentioned in the paper) have collected 9200 comments from Google and 34,779 Twitter postings filtered for phrases connected with COVID-19-related fake news. Experiment 1. The dataset was assessed using the following three criteria: veracity, stance, and sentiment. In these terms, we have different labels, and we have applied the DL algorithms separately to each term. We have used different models in the experiment such as (i) LSTM and (ii) Temporal Convolution Networks (TCN). The TCN model has more performance on each measurement parameter in the evaluated results. So, we have used the TCN model for the practical implication for better findings. Experiment 2. In the second experiment, we have used different state-of-the-art deep learning models and algorithms such as (i) Simple RNN; (ii) LSTM + Word Embedding; (iii) Bidirectional + Word Embedding; (iv) LSTM + CNN-1D; and (v) BERT. Furthermore, we have evaluated the performance of these models on all three datasets, e.g., veracity, stance, and sentiment. Based on our second experimental evaluation, the BERT has a superior performance over the other models compared.
Parametric Marcinkiewicz Integral and Its Higher-Order Commutators on Variable Exponents Morrey-Herz Spaces
Authors: Omer Omer Abdalrhman , Saibi Khedoudj , Abidin Muhammad Zainul , Osman Mawia
Published: September 2022

In this article, we prove the boundedness of the parametric Marcinkiewicz integral and its higher-order commutators generated by BMO spaces on the variable Morrey-Herz space. All the results are new even when

α

·

is a constant.
An Image Segmentation Method Based on the Law of Universal Gravitation and Adaptive Affinity Propagation Spectrum Clustering
Authors: Lu Hua , Zhu Jianrong
Published: September 2022

There are many problems of division in natural and social sciences, and with the development of science and technology, the requirement for division is also increasing. It is difficult to divide accurately by experience and expertise alone, and the most important research branch of the division problem is the clustering algorithm. It is to group similar samples into one class and divide the elements with large differences into different classes. Due to the simplicity and efficiency of the clustering algorithm, it is widely used in image segmentation. The conventional Spectral Clustering (SC) algorithm cannot recognize nonconvex data and has the disadvantage of strong dependence on biased parameter values. To address this problem, the Gravity-based Adaptive Spectral Clustering (GASC) algorithm is proposed in this study. Based on the conventional SC algorithm, the algorithm uses gravity to calculate the similarity (gravity) between data, and uses information entropy and adaptive enhancement (AdaBoost) algorithms to obtain the weights of correct cluster sampling points and wrong cluster sampling points in each cluster, so as to reduce the dependence of the algorithm on bias parameters and reduce the number of wrongly divided sample points. Meanwhile, the GASC algorithm is applied to image segmentation. The implementation process includes three stages: image preprocessing, feature extraction, and clustering. The comparison experiments show that the mean values of normalization and accuracy of the GASC algorithm are improved compared with other clustering algorithms, and the segmentation accuracy for images is higher.
Screening Potential Diagnostic Biomarkers for Age‐Related Sarcopenia in the Elderly Population by WGCNA and LASSO
Authors: Lin Shangjin , Ling Ming , Chen Cong , Cai Xiaoxi , Yang Fengjian , Fan Yongqian
Published: September 2022

Background. Sarcopenia is a common chronic disease characterized by age‐related decline in skeletal muscle mass and function, and the lack of diagnostic biomarkers makes community‐based screening problematic. Methods. Three gene expression profiles related with sarcopenia were downloaded and merged by searching the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and eigengenes of a module in the merged dataset were identified by differential expression analysis and weighted gene coexpression network analysis (WGCNA), and common genes (CGs) were defined as the intersection of DEGs and eigengenes of a module. CGs were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Subsequently, the least absolute shrinkage and selection operator (LASSO) analysis was performed to screen the CGs for identifying the diagnostic biomarkers of sarcopenia. Based on the diagnostic biomarkers, we established a novel nomogram model of sarcopenia. At last, we validated the diagnostic biomarkers and evaluated the diagnostic performance of the nomogram model by the area under curve (AUC) value. Results. We screened out 107 DEGs and 788 eigengenes in the turquoise module, and 72 genes were selected as CGs of sarcopenia by intersection. GO analysis showed that CGs were mainly involved in metal ion detoxification and mitochondrial structure, and KEGG analysis revealed that CGs were mainly enriched in the mineral absorption, glucagon signaling pathway, FoxO signaling pathway, insulin signaling pathway, AMPK signaling pathway, and estrogen signaling pathway. Then, six diagnostic biomarkers (ARHGAP36, FAM171A1, GPCPD1, MT1X, ZNF415, and RXRG) were identified by LASSO analysis. Finally, the validation AUC values indicated that the six diagnostic biomarkers had high diagnostic accuracy for sarcopenia. Conclusion. We identified six diagnostic biomarkers with high diagnostic performance, providing new insights into the incidence and progression of sarcopenia in future research.
Microbial Diversity Reduction in Soil by Long-Term Climate Warming
Authors: Dave Mayank , Panwar Kartika , Dadhich Itika , Sharma Yagya , Malodia Anupriya , Shaik Nagaraju
Published: September 2022

Global environmental changes are altering where species dwell and how they interact with one another. Organisms exist in intricate communities with thousands of different species, some of which are beneficial, some of which are destructive, and others of which have no influence at all. Because natural communities are made up of organisms with widely disparate life histories and modes of change, it is improbable that they will all react in the same manner to changes in the environment. The consequences of global change on interactions between plants and herbivores and plants and pollinators have been extensively reported. Less attention has been made to the interactions of soil bacteria and plants, as well as soil microorganisms. Because soil microorganisms govern how nutrients vary, feed nutrients to plants, allow neighbours to cohabit, and manage plant populations, changes in how soil microorganisms and plants interact may have a significant impact on the sorts of plants in an ecosystem and how it operates. This study investigates how soil interactions impact soil bacteria and how they interact with one another, both directly and indirectly. It also covers novel and fascinating areas of inquiry, as well as the implications that changes in these relationships have on the makeup and operation of ecosystems.
Study of the Use of Antinematode Drugs, Mebendazole and Pyrantel, in Galicia (Spain) from 2016 to 2020
Authors: Vázquez- Prieto S. , Vaamonde A. , Paniagua E.
Published: September 2022

To the best of our knowledge, there is no study on the use of drugs focused on the consumption of antinematode drugs in any region of the world. In the present study, we analyzed and evaluated the use of mebendazole and pyrantel in the provinces of Galicia (Spain), as well as described the variability of the consumption of both drugs between these provinces from 2016 to 2020. A descriptive, cross-sectional, and retrospective study of the consumption of these drugs, expressed in defined daily dose per 1000 inhabitants per day (DHD), was carried out. The DHD values for both drugs were small, although clearly higher, both on average and in variability, in the case of mebendazole. The difference in the mean DHD between both drugs and the geographical differences observed was statistically significant. The seasonal differences were statistically significant for both active principles, with lower values in summer. The active principle most consumed in all the provinces and years was mebendazole. The main consequence of the excessive use of this drug compared to pyrantel may be the increased risk of the development of resistance and of therapeutic failure, as well as the consequent limitation of pharmacological options in the future.
Research on the Dilemma and Path of Rural Industry Integration and Internet Revitalization Driven by e-Commerce
Authors: Xu Feng
Published: September 2022

Because e-commerce is based on the Internet, it has the advantages of fast response speed and strong promotion ability, which potentially mitigates the problems of low popularity and unreasonable industrial structure in the development of rural industries. This paper integrates Internet technology, studies in detail the functional process of rural industries integrating the Internet, and establishes the corresponding platform. Then, it analyzes the problems of rural industrial integration of the Internet to achieve rural revitalization and applies this rural industrial integration of the Internet revitalization platform to the rural development of different cities. By studying the difficulties in rural industry among cities, this paper compares and analyzes the optimization measures of this path and puts forward the corresponding solutions. In short, this paper integrates rural industry with Internet technology, which greatly improves the popularity of rural industry, optimizes the rural industrial structure, and provides ideas and experimental support for the realization of rural revitalization.
Numerical and Experimental Assessment of Mechanical Properties of Biobased Epoxy Reinforced by Flax Fibres and Seashell Nanoparticles for Prosthetic Socket
Authors: Hadi Ahmed Namah , Mohammed Mohammed Razzaq , Al-Bakri Amir F.
Published: September 2022

Chronic diseases such as peripheral vascular and arteriosclerosis, wars, terrorist attacks, natural disasters, and traffic collisions are the major causes of the high demand for prostheses. The inadequacy of the typically used materials at reasonable prices and the high stiffness of these materials, which can negatively influence socket-limb load transfer, imply an urgent need to find alternatives to the existing prosthetic sockets. This work aims to use renewable, low-hazard, and low-cost natural flax fibres and seashell nanoparticles as substitutes for conventional reinforcement materials for prosthetic sockets. Seashell nanoparticles of 1, 3, and 5 weight fractions and 3 layers of flax fibres were integrated into biobased epoxy. Tensile and flexural properties of modified and unmodified specimens were assessed, and the finite element technique (ANSYS-20) was utilised to analyse and evaluate the mechanical characteristics of the specimens by observing the stress and total deformation. Here, all fabricated nanocomposites provided tensile and flexural strength higher than that of additive-free biobased epoxy. In addition, hybrid nanocomposites fabricated from 3 layers of flax fibres and 3 wt% of seashell nanoparticles were revealed to have the highest mechanical properties compared with unmodified resin and biobased epoxy filled with other percentages of the reinforcement. These findings were further validated numerically in which the total deformation was shown to decrease after the addition of 3 wt% of these nanoparticles within the nanocomposites. Moreover, the antibacterial activity proved its superb antimicrobial performance against various pathogenic microorganisms, namely, Staphylococcus aureus and E. coli. Accordingly, the fabricated composite systems are suggested to be an appropriate candidate for forming prosthetic sockets. These composites have promising mechanical and antibacterial properties, and they are made of affordable and available materials, which can be a suitable option, particularly in poor countries due to the fact that advanced technologies may require a substantial amount of money for equipment, surgery fees, and medical care.
Analysis of Farmer Relocation Selection Behavior Based on Bayesian Network
Authors: Li Song , Guo Yanbo
Published: September 2022

The study of farmers’ migration choice behavior can reflect people’s needs for the future living environment from the side and has practical and important guiding significance for adjusting and improving the focus of future development. In order to make a detailed analysis of the prediction of migrant workers’ behavior in cities, this paper studies the internal mechanism of the change of commuters’ commuting patterns under the background of urban suburbanization. Using Bayesian network, this paper establishes a model of commuting mode transfer of urban immigrants, taking personal and family attributes as control variables. The influence of factors such as migration attributes and changes in building environment perception before and after migration is analyzed. Based on the survey data, a Bayesian network of farmers’ land use behavior is established by using Bayesian network method to investigate the choice of farmers’ migration direction. In the research process of migration direction, the research structure shows that 60.1% of farmers want to stay in the countryside, rather than migrate through Bayesian network algorithm. The results of regression analysis by establishing a multivariate logistic model show that there is a strong willingness to choose small towns and large cities. However, the willingness to choose not to relocate to local villages is relatively weak.
Design and Communication of City Brand Image Based on Big Data and Personalized Recommendation System
Authors: Lin Yan , Hu Guofeng
Published: September 2022

In order to define the positioning of the urban brand image, design the urban brand image, integrate and optimize the communication channels, improve the public participation awareness, and enhance the core competitiveness of the city. In this paper, a personalized recommendation search engine based on big data identifies keywords input by urban users. And give more accurate results based on some relevant information that can be extracted. This paper analyzes how to make better use of big data for tourism destination brand image management, and the existing shortcomings, and puts forward relevant suggestions. The industries related to cultural creative design and tourism elements constitute an intertwined cultural and tourism industry chain, and data technology plays an important role in the cultural and tourism industry chain. Through the development of tourism, tourists will produce comprehensive and diversified consumption in the city. Based on the analysis of big data, it can provide strong decision support for the government and industry managers, and realize the image design and communication of the urban brand identification system. Through the big data platform, establish the brand management strategy, improve the communication content of the city’s brand image, and timely feedback the opinions and suggestions of tourists on the tourism destination, so as to adjust the communication strategy of the tourism image according to the feedback information of tourists. The results show that the big data personalized recommendation system can achieve ideal results in urban brand value and urban tourism related factors.
EIF3C Promotes Lung Cancer Tumorigenesis by Regulating the APP/HSPA1A/LMNB1 Axis
Authors: Ding Xiaoli , Hou Lanlan , Zhang Huijuan , Chen Zhiping , Liu Zhanyu , Gong Junjie , Tang Zhixian , Hu Rong
Published: September 2022

Objective. This study was designed to explore the role and mechanism of eukaryotic initiation factor 3C (EIF3C) in the proliferation and apoptosis of lung cancer cells. Methods. EIF3C expression in clinic lung cancer tissues was detected by immunohistochemistry assay. Cell transfection with lentivirus EIF3C short hairpin RNA (shRNA) was performed with Lipofectamine 2000. Cell proliferation was evaluated by Celigo and MTT assays. Caspase-3/7 activity was assessed using caspase-3/7 assay kit for cell apoptosis detection. The apoptosis rate of lung cancer cells was assessed by flow cytometry. A transplanted tumor nude-mouse model was established to clarify the role of EIF3C in lung cancer. The potential mechanism of EIF3C was explored by mRNA microarray analysis. Among the top 30 up- and downregulated mRNAs selected for RT-qPCR, 5 were chosen for western blot analysis. Results. EIF3C was abnormally overexpressed in lung cancer cell lines and tissues. Silencing EIF3C suppressed the proliferation and promoted the apoptosis of lung cancer cells. In vivo experiments using transplanted tumor nude-mouse model suggested that EIF3C promoted lung cancer tumorigenesis. Further, mRNA microarray analyses identified 189 upregulated and 83 downregulated differentially expressed mRNA between the KD and negative control groups. After validation by RT-qPCR and western blot, three downstream genes (APP, HSPA1A, and LMNB1) were confirmed. Conclusion. EIF3C overexpression may facilitate the proliferation and hamper the apoptosis of lung cancer cells by regulating the APP/HSPA1A/LMNB1 axis.
METTL1-Mediated m7G tRNA Modification Promotes Lenvatinib Resistance in Hepatocellular Carcinoma
Authors: Huang Manling , Long Jianting , Yao Zhijia , Zhao Yi , Zhao Yutong , Liao Junbin , Lei Kai , Xiao Han , Dai Zihao , Peng Sui , Lin Shuibin , Xu Lixia , Kuang Ming
Published: September 2022

The tyrosine kinase inhibitor lenvatinib is a first-line drug for treating patients with advanced hepatocellular carcinoma (HCC). However, its efficacy is severely hampered by drug resistance. Insights into the molecular mechanisms underlying lenvatinib resistance could provide new strategies to improve and prolong responses. Here, we performed unbiased proteomic screening of parental and lenvatinib-resistant HCC cells and discovered that methyltransferase-like protein-1 (METTL1) and WD repeat domain 4 protein (WDR4), the two key components of the tRNA N7-methylguanosine (m7G) methyltransferase complex, were dramatically upregulated in lenvatinib-resistant cells. METTL1 knockdown overrode resistance by impairing the proliferation capacity of HCC cells and promoting apoptosis under lenvatinib treatment. In addition, overexpression of wild-type METTL1 but not its catalytic dead mutant induced lenvatinib resistance. Animal experiments including hydrodynamic injection, subcutaneous implantation, and orthotopic xenograft mouse models further demonstrated the critical function of METTL1/WDR4-mediated m7G tRNA modification in promoting lenvatinib resistance in vivo. Mechanistically, METTL1 promoted translation of EGFR pathway genes to trigger drug resistance. This work reveals the important role of METTL1-mediated m7G tRNA modification in promoting lenvatinib resistance and provides a promising prediction marker and intervention target for resistance.

Significance:

Upregulation of tRNA m7G methyltransferase complex components METTL1 and WDR4 promotes lenvatinib resistance in HCC and confers a sensitivity to METTL1 targeting, providing a promising strategy to override resistance.
Quantitative Spatial Profiling of TILs as the Next Step beyond PD-L1 Testing for Immune Checkpoint Blockade
Authors: Anagnostou Valsamo , Luke Jason J.
Published: September 2022

Analysis of tumor-infiltrating lymphocyte (TIL) functional states, particularly tumor-reactive PD-1T TILs, within specific spatial context, can serve as a biologically informed predictive marker of immunotherapy that may be superior to standard clinical biomarkers. High-plex quantitative immune cell phenotyping within their spatial context has tremendous potential in immuno-oncology.

See related article by Hummelink et al., p. 4893
Abstract A014: The novel anti-inflammatory agent GML (GM1-targeted linoleate-containing TLR2 ligand) inhibits sarcoma metastasis to the lung
Authors: Babes Liane , Wierenga Lauren A. , Dan Ngoc-Ha , Lun Xueqing , Goring Kimberly-Ann R. , Robbins Stephen M. , Senger Donna L.
Published: September 2022

Sarcomas are a heterogeneous group of cancers occurring in tissues derived from the mesenchyme. Despite improved treatment strategies that include surgery and broad-based chemotherapeutics, survival of patients with sarcoma remains unchanged in the last 40 years with 5-year overall survival less than 25%. In part, this high rate of mortality can be attributed to the development of pulmonary metastases, a process that occurs in up to 50% of patients. We propose that preventing the occurrence or growth of lung metastases can improve the outcome for many of these patients. Our growing understanding of the dynamic relationship between inflammation and cancer has led to the investigation of anti-inflammatory approaches to treat cancer, including metastasis. Specifically, recent studies suggest a role for neutrophils in cancer metastasis, identifying a promising target for therapeutic intervention. The aim of the present study is to investigate the role of myeloid cells in the metastatic process, and their potential to act as therapeutic targets during the development of lung metastases. Herein we used human and syngeneic osteosarcoma lung metastatic models together with in vitro assays to assess the role of neutrophils in this process. Our results demonstrate that neutrophils are essential to facilitate the development of osteosarcoma pulmonary metastases and that treatment with the novel anti-inflammatory agent GM1-targeted linoleate-containing TLR2 ligand (GML), known to inhibit neutrophil recruitment, diminishes their occurrence. Overall, our results suggest that neutrophils play a role in mediating osteosarcoma lung metastasis and reveal GML as a potential anti-metastatic drug therapy.

Citation Format: Liane Babes, Lauren A. Wierenga, Ngoc-Ha Dan, Xueqing Lun, Kimberly-Ann R. Goring, Stephen M. Robbins, Donna L. Senger. The novel anti-inflammatory agent GML (GM1-targeted linoleate-containing TLR2 ligand) inhibits sarcoma metastasis to the lung [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A014.
Abstract A018: YAP signaling promotes resistance to MEK and AKT inhibition in NF1-related MPNSTs
Authors: McGee Lauren , Essenburg Curt , Turner Lisa , Hirbe Angela , Dey Anwesha , Zbieg Jason , Graveel Carrie , Steensma Matt
Published: September 2022

Malignant peripheral nerve sheath tumors (MPNSTs) are a rare and deadly sarcoma with few therapeutic options that are the leading cause of death for patients with Neurofibromatosis Type 1 (NF1). MPNSTs are characterized by a large burden of genomic alterations, chemoresistance, and a 5-year survival rate of 25-50%. NF1 is the major negative regulator of RAS, therefore a hallmark of MPNSTs is deregulated RAS/MAPK signaling. To date, no targeted therapies have been approved for MPNST treatment, highlighting the need for an understanding of adaptive signaling mechanisms that drive resistance. The HIPPO pathway is a key regulator of organ growth and cellular differentiation and is a central driver of resistance to RAS pathway inhibition in other cancers. The key HIPPO effector, YAP1, interacts with RAS and AKT signaling pathways, creating alternate routes for resistance in multiple cancers. In our studies, we identified strong YAP activation in response to MEK and AKT inhibition in MPNST cell lines. Since YAP acts as a transcriptional co-activator through interaction with TEAD transcription factors, we proposed that targeting the Hippo pathway in MPNST will abrogate MAPK inhibitor resistance. To investigate tumor signaling responses and efficacy in vivo, we utilized 3 genomically distinct MPNST patient-derived xenograft (PDX) models. To assess drivers of MPNST resistance, we have developed a preclinical model of drug resistance that simulates clinical treatment schedules. Using a cross-over and a drug holiday design, we are able to evaluate patterns of response and resistance to resumed treatment. We observed distinctive responses to MEK and AKT inhibitors in each PDX line; however, the impact on MPNST growth was minimal with single agent treatment. Comparison of pathway activation between the “drug holiday” biopsies and the treatment endpoint, demonstrated distinct YAP and RAS (pERK) activation levels in resistant tumors. For example, strong YAP activation is observed in correlation with decreased pERK in resistant tumors. YAP activation was strongest at the invasive edge of viable tumor regions. Currently, we are evaluating the efficacy and signaling adaptations to investigate the underlying molecular mechanisms in these MPNST models. Overall, we have demonstrated the development of a clinically relevant model of MPNST resistance and a potential switch between RAS and YAP signaling that promotes resistance to MEK or AKT inhibition.

Citation Format: Lauren McGee, Curt Essenburg, Lisa Turner, Angela Hirbe, Anwesha Dey, Jason Zbieg, Carrie Graveel, Matt Steensma. YAP signaling promotes resistance to MEK and AKT inhibition in NF1-related MPNSTs [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr A018.
Abstract IA008: Altering the T cell receptor repertoire in the sarcoma tumor immune microenvironment
Authors: Pollack Seth M. , Seo Y. Dave
Published: September 2022

Our lab has been interested in characterizing the T cell receptor (TCR) repertoire of sarcoma subtypes as well as characterizing their immune infiltrates and studying the changes that occur on experimental immunotherapies. In this trial, 15 patients with metastatic soft tissue sarcoma STS patients with a superficial injectable lesion were treated weekly with an intratumoral (IT) toll like receptor 4 (TLR4) agonist Glucopyranosyl Lipid Adjuvant (GLA) for 8-12 weeks plus concurrent radiotherapy. Core biopsies and blood were collected pre and post treatment, and immune analysis was performed by T cell receptor (TCR) sequencing and multiplex IHC. RECIST v1.1 and CTCAE guidelines were used to monitor clinical outcomes. No grade 3 or higher treatment-related toxicity was observed, and local tumor control was achieved in 93% (14/15). 6 (40%) had overall stable disease after IT GLA, and one had complete regression of injected tumor. 3 other patients had long term control of injected tumor past 250 days, during which the uninjected STS had progression despite radiation. In patients with durable local control after IT GLA, multiplex IHC demonstrated increased CD4 and CD8 T cell infiltration, as well as decrease in regulatory T cells. In patient #5-6, TCR sequencing revealed 5-fold increase in PBMC clonality, with selective clonal expansion of T cells present in pre-treatment biopsy. In patient #10-6 (local control to 370 days), there was clonal expansion of T cells within TME which were also found in post treatment PBMC; matched single cell sequencing revealed these clones to be CD4 T cells with Th1 gene signatures. In this trial we found that GLA with radiation induced effective local control of superficial, metastatic STS lesion, inducing a shift in the TME towards an inflammatory state with strong infiltration of T cells. There was selective expansion of clones present in pre-treatment TME in circulating PBMC post IT GLA, isolated to be Th1 cells in one patient. This suggests induction of adaptive anti-tumor response, which may further be enhanced by combination with other immunomodulators.

Citation Format: Seth M. Pollack, Y. Dave Seo. Altering the T cell receptor repertoire in the sarcoma tumor immune microenvironment [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr IA008.
Abstract IA014: Stem cell and developmental hierarchies in rhabdomyosarcoma
Authors: Langenau David M. , Wei Yun , Qin Qian , Pinello Luca
Published: September 2022

Rhabdomyosarcoma (RMS) is the most common soft-tissue sarcoma of childhood and is comprised of at least two major molecular subtypes. Despite sharing features with skeletal muscle, the conservation of underlying cellular hierarchy with human muscle development and the identification of molecularly-defined tumor-propagating cells have not been reported. Using single-cell RNA sequencing of patient-derived RMS, DNA-barcode cell fate mapping, antibody enrichment and functional stem cell assays, and mouse xenograft modeling, we have uncovered tumor cell hierarchies in Fusion-negative (FN-) RMS that are shared with normal human muscle development. We also identified common developmental stages at which tumor cells become arrested. FN-RMS resemble early muscle found in embryonic and larval development, while fusion-positive (FP-) RMS express a highly specific developmental gene program found in muscle cells transiting from embryonic to fetal development at 7-7.75 weeks of age. FP-RMS also have neural-pathway enriched cell states, suggesting less-rigid adherence to muscle development hierarchies in this disease. Finally, we identify a new molecularly-defined tumor-propagating cell in FN-RMS that shares remarkable similarity to the newly described bi-potent, muscle mesenchyme stem/progenitor cell that makes both muscle and osteogenic cells.

Citation Format: David M. Langenau, Yun Wei, Qian Qin, Luca Pinello. Stem cell and developmental hierarchies in rhabdomyosarcoma [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr IA014.
Abstract IA025: Using genetically engineered mouse models to study sarcoma metastasis
Authors: Kirsch David G. , Patel Rutulkumar , Finkelstein Sophie R. , Ban Joy , Tang Yuning J , Huang Jianguo , Alman Benjamin A. , Mowery Yvonne M.
Published: September 2022

Despite aggressive conventional therapy, many patients with high-risk soft-tissue sarcoma develop metastatic disease. To investigate mechanism(s) of sarcoma metastasis, our lab has utilized genetically engineered mouse models. For example, we injected an adenovirus expressing Cre recombinase (adeno-Cre) into the gastrocnemius muscle of LSL-KrasG12D; p53Flox/Flox (KP) mice to initiate high grade undifferentiated pleomorphic sarcomas, and after amputation approximately 40% of the mice develop lung metastasis. Using a genetic approach, we found that miR-182, NEAT-1, and HIF-1a regulate metastasis to the lung. We also performed lineage tracing with complementary fluorescent proteins and CRISPR-generated bar codes to find that lung metastases from KP sarcomas arise from clones with specific gene expression profiles. Although the KP sarcoma model is useful for studying metastasis, one limitation of this model is that there are few non-synonymous mutations to engage the immune system. Therefore, we generated a high mutational load primary mouse model of soft tissue sarcoma by injecting adeno-Cre into the gastrocnemius muscle of p53Flox/Flox mice to delete p53 and also injected 3-methylcholanthrene (MCA) to generate primary p53/MCA undifferentiated pleomorphic sarcomas. In this p53/MCA model, the overall rate of lung metastasis after amputation was surprisingly low (~12%). We hypothesized that the immune system suppressed lung metastasis in this model. However, when we generated p53/MCA sarcomas in Rag2 −/− mice that lack mature B and T cells, we still observed a low rate of lung metastasis after amputation. These data suggest that mutations caused by MCA may have disabled tumor intrinsic factors needed to drive sarcoma metastasis. We are currently performing genome-wide screens in the p53/MCA model to search for genes required for sarcoma metastasis.

Citation Format: David G. Kirsch, Rutulkumar Patel, Sophie R. Finkelstein, Joy Ban, Yuning J Tang, Jianguo Huang, Benjamin A. Alman, Yvonne M. Mowery. Using genetically engineered mouse models to study sarcoma metastasis [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr IA025.
Abstract PR004: Fusion protein-driven IGF-IR signals deregulate hippo pathway promoting oncogenic cooperation of YAP1 and FUS-DDIT3
Authors: Berthold Ruth , Isfort Ilka , Erkut Cihan , Heinst Lorena , Grünewald Inga , Wardelmann Eva , Kindler Thomas , Åman Pierre , Grünewald Thomas G.P. , Cidre-Aranaz Florencia , Trautmann Marcel , Fröhling Stefan , Scholl Claudia , Hartmann Wolfgang
Published: September 2022

Introduction: Myxoid liposarcoma (MLS) is molecularly characterized by a recurrent chromosomal translocation which generates a chimeric FUS-DDIT3 fusion gene. The FUS-DDIT3 oncoprotein, acting as a transcriptional dysregulator, has been shown to be essential in MLS pathogenesis, among others through deregulation of IGF-IR/PI3K/AKT signaling, but its exact mode of function remains incompletely understood. Recently, a particular reliance on the Hippo pathway effector and transcriptional co-regulator YAP1 was found in MLS; however, the molecular mechanism of FUS-DDIT3-dependent YAP1 activation and its contribution to MLS pathogenesis remain unclear. Experimental Procedures: The expression of IGF-IR and YAP1 was analyzed in a large cohort of MLS specimens by immunohistochemistry. In vitro analyses were performed employing a human mesenchymal stem cell system stably expressing FUS-DDIT3 and human MLS cell lines. RNA interference-based approaches, experiments with small-molecule kinase inhibitors, co-immunoprecipitation, proximity ligation assays, transcriptome sequencing and adipogenic differentiation assays were performed to determine the interplay of FUS-DDIT3, IGF-IR-dependent signals, and YAP1 in MLS cells. Results: Immunohistochemically, a significant subset of MLS samples showed concurrent expression of IGF-IR and nuclear YAP1. In vitro, FUS-DDIT3-driven IGF-IR signaling was found to promote stability and nuclear accumulation of YAP1 via deregulation of the Hippo pathway. Co-immunoprecipitation and proximity ligation assays revealed nuclear co-localization of FUS-DDIT3 and YAP1 in FUS-DDIT3-expressing mesenchymal stem cells and MLS cell lines. Transcriptome sequencing of MLS cells demonstrated that FUS-DDIT3 and YAP1 co-regulate specific oncogenic gene signatures related to proliferation, cell cycle progression, apoptosis, and adipogenesis. In differentiation assays, FUS-DDIT3 and YAP1 were found to cooperate in adipogenic differentiation arrest. Conclusions: Our study provides molecular insights into a complex FUS-DDIT3-driven network involving IGF-IR signals acting on Hippo/YAP1, and uncovers cooperative effects of YAP1 and FUS-DDIT3 in the pathogenesis of MLS.

Citation Format: Ruth Berthold, Ilka Isfort, Cihan Erkut, Lorena Heinst, Inga Grünewald, Eva Wardelmann, Thomas Kindler, Pierre Åman, Thomas G.P. Grünewald, Florencia Cidre-Aranaz, Marcel Trautmann, Stefan Fröhling, Claudia Scholl, Wolfgang Hartmann. Fusion protein-driven IGF-IR signals deregulate hippo pathway promoting oncogenic cooperation of YAP1 and FUS-DDIT3 [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr PR004.