bluuebunny/crossref_metadata_2025 huggingface dataset:
Metric Dimension Threshold of Graphs
Authors: Korivand Meysam , Khashyarmanesh Kazem , Tavakoli Mostafa
Published: September 2022

Let G be a connected graph. A subset S of vertices of G is said to be a resolving set of G, if for any two vertices u and v of G there is at least a member w of S such that d(u, w) ≠ d(v, w). The minimum number t that any subset S of vertices G with |S| = t is a resolving set for G, is called the metric dimension threshold, and is denoted by dimth(G). In this paper, the concept of metric dimension threshold is introduced according to its application in some real‐word problems. Also, the metric dimension threshold of some families of graphs and a characterization of graphs G of order n for which the metric dimension threshold equals 2, n − 2, and n − 1 are given. Moreover, some graphs with equal the metric dimension threshold and the standard metric dimension of graphs are presented.
Classification of Imbalanced Data Set in Financial Field Based on Combined Algorithm
Authors: Yu Tingting , Huo Yunxiang
Published: September 2022

In view of the imbalance of data categories in financial data mining, a two-stage classification algorithm was proposed based on SVM and KNN to classify imbalanced data. In the first stage, two one-class SVM classifiers are constructed, and the samples are divided into four types: majority class (MC), minority class (mC), boundary, and outlier while the KNN algorithm is introduced to classify boundary and outlier samples in the second stage. In addition, the effectiveness of the algorithm is verified by several imbalanced data sets in the financial field. The results show that the proposed algorithm has predominant execution in financial precision marketing analysis, and compared with other algorithms, the proposed algorithm achieves better performance in G-mean and AUC and F1 indexes. This research provides an effective way for the classification of imbalanced data in the financial field.
Diffuse-Type Tenosynovial Giant Cell Tumour Involving Bone Masquerading as Langerhans Cell Histiocytosis
Authors: Cheung Florence M. F. , So Timothy Y. C. , Sung Tony H. T. , Lam Ying-Lee
Published: September 2022

We presented a case of diffuse-type tenosynovial giant cell tumour (DTSGCT) of foot masquerading as Langerhans cell histiocytosis. Preliminary diagnosis by needle biopsy was difficult due to the major involvement of bones and the overshadowing effect of the accompanying Langerhans cells. The complete curettage specimen with relevant immunohistochemistry and molecular tests made the final diagnosis of DTSGCT possible. The biomolecular mechanism for the masquerading phenomenon was explained by CSF1 overexpression in the neoplastic cells attracting migration and proliferation of CSF1R-positive Langerhans cells.
The Establishment of Hypertrophic Cardiomyopathy Diagnosis Model via Artificial Neural Network and Random Decision Forest Method
Authors: Li Shuanglei , Feng Zekun , Xiao Cangsong , Wu Yang , Ye Weihua
Published: September 2022

Hypertrophic cardiomyopathy is a hereditary disease characterized by asymmetric ventricular hypertrophy as the key anatomical feature. Currently, there exists no effective method for the early diagnosis of hypertrophic cardiomyopathy. In this analysis, we incorporated multiple GEO datasets containing RNA profiles of hypertrophic cardiomyopathic patient tissues, identified 642 differentially expressed genes, and performed GO and KEGG analyses. Furthermore, we narrowed down 46 characteristic genes from these differentially expressed genes using random decision forests and conducted transcription factor regulation analysis on them. Using 40 genes that showed overlap between the training set and the verification set, the artificial neural network was trained, and the final MPS scoring model was constructed, and a receiver-operating characteristic (ROC) curve was drawn. We used the MPS model to predict the verification dataset and drew the ROC curve, which demonstrated the good prediction performance of the model. In conclusion, this study combines a random decision forest and artificial neural network to build a diagnostic model for hypertrophic cardiomyopathy to predict the disease, aiming at early detection and treatment, prolonging the survival time, and improving the quality of life of patients.
Network Pharmacology and Molecular Docking-Based Investigation of Potential Targets of Astragalus membranaceus and Angelica sinensis Compound Acting on Spinal Cord Injury
Authors: Cao Shengnan , Hou Guangjian , Meng Ya , Chen Yuanzhen , Xie Liangyu , Shi Bin
Published: September 2022

Background. Astragalus membranaceus (Huang-qi, AM) and Angelica sinensis (Dang-gui, AS) are common Chinese herbal medicines and have historically been used in spinal cord injury (SCI) therapies. However, the underlying molecular mechanisms of AM&AS remain little understood. The purpose of this research was to explore the bioactive components and the mechanisms of AM&AS in treating SCI according to network pharmacology and the molecular docking approach. Methods. AM&AS active ingredients were first searched from Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Traditional Chinese Medicine Information Database (TCM-ID). Meanwhile, we collected relevant target genes of SCI through the GeneCards database, OMIM database, PharmGkb database, DurgBank database, and TDD database. By utilizing the STRING database, we constructed a network of protein-protein interactions (PPIs). In addition, we used R and STRING to perform GO and KEGG function enrichment analyses. Subsequently, AutoDock Vina was employed for a molecular docking study on the most active ingredients and most targeted molecules to validate the results of the network pharmacology analysis mentioned above. Result. The overall number of AM&AS active compounds identified was 22, while the number of SCI-related targets identified was 159. Then, the 4 key active ingredients were MOL000098 quercetin, MOL000422 kaempferol, MOL000354 isorhamnetin, and MOL000392 formononetin. A total of fourteen core targets were TP53, ESR1, MAPK1, MTC, HIF1A, HSP90AA1, FOS, MAPK14, STAT1, AKT1, EGFR, RELA, CCND1, and RB1. The KEGG enrichment analysis results indicated that lipid and atherosclerosis, PI3K-Akt signaling pathway, human cytomegalovirus infection, fluid shear stress, and atherosclerosis, etc., were enhanced with SCI development. Based on the analyses of docked molecules, four main active compounds had high affinity for the key targets. Conclusions. Altogether, it identified the mechanisms by which AM&AS was used for SCI treatment, namely, active ingredients, targets and signaling pathways. Consequently, further research into AM&AS treating SCI can be conducted on this scientific basis.
Study on the Application Value of Concurrent Chemoradiotherapy and Clinical Nursing Pathway for Postoperative Patients with Esophageal Cancer
Authors: Yang Jinglei , Zhang Xianzhong , Yang Guangrong , Mi Xiufang , Zhang Yang , Sui Yingzhong
Published: September 2022

Backgrounds. To observe the value of concurrent chemoradiotherapy and clinical nursing pathway for postoperative patients with esophageal cancer (EC). Methods. A total of 88 postoperative EC patients were divided into the radiotherapy group (RG group, 44 cases) and the chemoradiotherapy group (CRG group, 44 cases). The RG group received single three-dimensional conformal radiotherapy+clinical nursing pathway, and the CRG group was combined with chemotherapy on this basis. The 5-year overall survival rate, progression-free survival rate, pathological remission and survival rate, lymph node metastasis and survival rate, quality of life analysis, tumor-related factor level, and incidence of adverse reactions were compared between the two groups. Results. The overall survival rates at 1, 3, and 5 years were 93.18%, 56.82%, and 50.0% in the CRG group and 86.36%, 52.27%, and 43.18% in the RG group, respectively. The 5-year progression-free survival rate of the CRG group was 60.87%, which was clearly higher than that of the RG group (33.33%). The 1-, 3-, and 5-year overall survival rates of pCR and NpCR patients were 90.48%, 80.95%, and 61.90% and 89.55%, 44.78%, and 38.81%, respectively. The overall 1-year, 3-year, and 5-year survival rates were 81.08%, 37.84, and 24.32% and 96.08%, 66.67%, and 62.75% in patients with lymph node metastasis and nonlymph node metastasis, respectively, with statistical significant differences. The emotional function, physical function, cough, pain, and eating difficulty in the CRG group were better than those in the RG group. After treatment, serum CEA, SCC, CYFRA21-1, and CA199 levels in the CRG group were obviously downregulated compared with those in the RG group. There was no obvious difference in the incidence of adverse reactions between the CRG group and the RG group. Conclusion. Single radiotherapy and concurrent chemoradiotherapy can be used as effective means in the treatment of EC. Moreover, the quality of life and survival time of the concurrent chemoradiotherapy group were dramatically better than those of the single radiotherapy group, and the antitumor ability of the concurrent chemoradiotherapy group was stronger.
TAOK1 Promotes Proliferation and Invasion of Non-Small-Cell Lung Cancer Cells by Inhibition of WWC1
Authors: Chen Lian
Published: September 2022

Background. For patients with advanced non-small-cell lung cancer (NSCLC), targeted therapy significantly improves the therapeutic effect of NSCLC patients. With the development of molecular targeted therapy, more and more NSCLC-related genes have been found. Thousand and one amino-acid kinase 1 (TAOK1) has been identified as a potential target for drug research in various cancers. The main objective of this study was to explore the expression and function of TAOK1 in NSCLC. Methods. Western blotting was employed to assess TAOK1 expression in NSCLC cell lines. The effects of TAOK1 on biological behaviors, including proliferation, invasion, and apoptosis of NSCLC cells, were assessed. The relationship between TAOK1 and WW and C2 domain containing 1 (WWC1) was assessed by Co-IP assay. The subcutaneous injection of tumor cells in nude mice was used to verify it in vivo. Results. As expected, TAOK1 was increased in NSCLC cell lines. Following TAOK1 knockdown, NSCLC cells exhibited a significant decrease in the invasion and increased apoptosis in vitro. Instead, the TAOK1 elevation showed the opposite results. The Co-IP assay identified that TAOK1 specifically interacted with WWC1. Knockdown of WWC1 overturned TAOK1 silencing-mediated malignant phenotype of NSCLC cells. Additionally, subcutaneous tumorigenesis assays in nude mice confirmed that TAOK1 knockdown markedly restrained the proliferation capacity of NSCLC cells in vivo. Conclusion. Surprisingly, TAOK1 overexpression in NSCLC promotes tumor cell growth and invasion, which is associated with downregulation of its downstream protein WWC1, and this result might provide a robust research basis to inquire about the precise therapeutic targets for NSCLC.
Decreased GZMB, NRP1, ITPR1, and SERPINB9 Transcripts Lead to Reduced Regulatory T Cells Suppressive Capacity in Generalized Vitiligo Patients
Authors: Giri Prashant S. , Bharti Ankit H. , Dwivedi Mitesh
Published: September 2022

Generalized vitiligo (GV) is an autoimmune skin disease characterized by bilateral white patches over the entire body. Regulatory T cells (Tregs) maintain peripheral tolerance; however, they are found to be reduced in numbers and function in vitiligo patients. The exact mechanism for reduced Treg suppressive capacity is unknown. Therefore, we aimed to assess transcript levels of Tregs-associated immunosuppressive genes (GZMB, NRP1, PDCD1, FASLG, and TNFRS18), regulatory molecules of Tregs suppressive function (SERPINB9, ITPR1, and UBASH3A), and Treg-associated transcription factors (GATA2, GATA3, RUNX1, STAT3, and STAT5) in 52 GV patients and 48 controls by real-time PCR (qPCR). We found significantly reduced GZMB, NRP1, SERPINB9, and ITPR1 transcripts in GV Tregs compared to controls (

p
=
0.03

,

p
=
0.023

,

p
=
0.0045

, and

p
<
0.0001

, respectively). There were 0.44-, 0.45-, 0.32-, and 0.54-fold decrease in GZMB, NRP1, SERPINB9, and ITPR1 transcripts in GV Tregs. Additionally, disease activity and severity-based analyses revealed significantly decreased GZMB (

p
=
0.019

and 0.034), SERPINB9 (

p
=
0.031

and

p
=
0.035

), and ITPR1 (

p
=
0.0003

and

p
=
0.034

) transcripts in active vitiligo and severe GV patients’ Tregs. Interestingly, we found a positive correlation for ITPR1 with GZMB (

r
=
0.45

,

p
=
0.0009

) and SERPINB9 (

r
=
0.52

,

p
=
0.001

) transcripts in GV Tregs. Moreover, we found positive correlation for percentage Treg mediated suppression of CD4+ and CD8+T cells with ITPR1 (

r
=
0.54

;

r
=
0.49

), GZMB (

r
=
0.61

;

r
=
0.58

), NRP1 (

r
=
0.55

;

r
=
0.52

), and SERPINB9 (

r
=
0.56

;

r
=
0.48

) in GV Tregs. Further, calcium treatment of Tregs resulted into significantly increased ITPR1, SERPINB9, and GZMB transcripts in GV Tregs (

p
=
0.023

,

p
=
0.0345

,

p
=
0.02

). Overall, our results for the first time revealed the crucial role of GZMB, NRP1, SERPINB9, and ITPR1 transcripts in decreased Treg suppressive capacity leading to GV pathogenesis, progression, and severity. In addition, our study highlighted that ITPR1 might be linked with decreased GZMB and NRP1 expression in GV Tregs. Moreover, our study for the first time suggest that increased SERPINB9 transcripts may lead to endogenous granzyme B-mediated Tregs apoptosis, and calcium treatment of Tregs may improve the Treg suppressive capacity. These findings may further aid in development of Treg-based therapeutics for GV.
Dual-Hop Transmission and Multiple Relays for Performance Analysis of Designing Physical Layer Security for IoT Networks
Authors: Nguyen Nhan Duc , Le Anh-Tu , Do Dinh-Thuan , Munochiveyi Munyaradzi
Published: September 2022

This article presents a secure performance metric of a downlink nonorthogonal multiple access (NOMA) in the presence of interference from the traditional user. In the context of NOMA, we deploy two-hop transmission to improve the performance of destinations. Further, multiple relays are implemented to aid robust signal-to-interference-plus-noise ratio (SINR) at destinations. We derive a closed-form expression of secure outage probability (SOP) to characterize security concerns in the case an eavesdropper exists in the overage of second hop transmission. We verify all expressions by employing Monte Carlo simulations.
Deep Learning Model for Stock Excess Return Prediction Based on Nonlinear Random Matrix and Esg Factor
Authors: Meng Tiantian , Yahya M. H. , Chai Jingmin
Published: September 2022

Aiming at the problem that the traditional model has low accuracy in describing stock excess return, in order to further analyze the change law of stock excess, based on the nonlinear random matrix and esg factor theory, the traditional learning model is analyzed, and the corresponding optimized deep learning model is obtained by introducing the single ring theorem and statistical data. Through the analysis and research of related indexes, the change rules of different indexes are obtained, and the optimization model is used to calculate and forecast the excess return of stocks. The results show that the statistics and spectral radius show typical local linear variation with the increase of eigenvalue. The corresponding statistics show a trend of gradual increase. The corresponding spectral radius has a decreasing variation law, and the two curves have obvious symmetry at some eigenvalues. It can be seen from the change curves under different factors that the change trend of the yield curve is mainly affected by the investment factor, while the change rule of the specific value of the yield curve is controlled by the profit factor. This shows that the two factors have the same influence on the stock excess return. The influence of optimized deep learning model on stock excess index has typical linear characteristics, which can be divided into linear increase and linear decline according to different change rules. The basic type has the greatest influence, while the corresponding pattern analysis type has the least influence. Finally, the method of experimental verification is used to verify the stock excess data, and the results show that the optimized deep learning model can better characterize the experimental results. Therefore, the optimized deep learning model based on nonlinear random matrix and esg factor can carry out targeted analysis of different types of stock returns, thus improving research ideas and calculation methods for the application of deep learning model in different fields.
Calbindin S100A16 Promotes Renal Cell Carcinoma Progression and Angiogenesis via the VEGF/VEGFR2 Signaling Pathway
Authors: Wang Ning , Wang Rongjiang , Tang Jianer , Gao Jianguo , Fang Zhihai , Zhang Meng , Shen Xufeng , Lu Lingqun , Chen Yu
Published: September 2022

Purpose. Recent research has indicated that the calcium‐binding protein S100A16 promotes carcinogenesis and tumor growth in several forms of cancer. The objective of this study was to examine the relationship between S100A16 and renal cell cancer. Methods. By using The Cancer Genome Atlas (TCGA) database, the differentially expressed gene S100A16 was identified, and its appearance and link to the prognosis of persons with renal cancer were confirmed. Cox regression was used in multivariate analysis, and a nomogram was developed for internal validation. The correlation between S100A16 and immune cells was analyzed in the TIMER database. Moreover, the potential mechanism of action was investigated utilizing GO and KEGG enrichment analyses. Proliferation, migration, and angiogenesis were investigated in vitro, and the involvement of S100A16 in the undesirable biological events of renal cell carcinoma (RCC) was further explored. Results. S100A16 was the differentially expressed molecule identified through database screening. Malignant tissues showed higher S100A16 expression than noncancerous tissues, and S100A16 expression was mostly localized in the cytoplasm. According to the TCGA and KM‐plotter datasets, patients with RCC and low S100A16 expression had superior OS, PFI, and DSS. The C‐index of the nomogram was 0.754 (0.726–0.782), and the accuracy of the prediction model was high. The TIMER database shows that the expression of S100A16 is associated with immune infiltration and may play an important role in promoting tumor cell immune escape in the RCC tumor microenvironment. S100A16 may influence the biological processes of RCC via the VEGF/VEGFR2 signaling route and PI3K‐Akt signaling pathway and through P53 alteration and cell cycle according to the gene enrichment technique. In vitro cytological experiments demonstrated that S100A16 knockdown can inhibit the proliferation and migration of renal cancer cells and the expression levels of VEGF, VEGFR2, and phosphorylated AKT within renal cancer cells, thereby inhibiting angiogenesis in renal cancer cells and resulting in a poor prognosis of RCC. Conclusion. A decrease in S100A16 expression may dramatically increase the OS, PFI, and DSS of patients with RCC and may thus be used as a biomarker for predicting RCC. It may be associated with the immune infiltration of RCC and play a crucial role in the immune evasion of tumor cells within the RCC microenvironment. Intervention of s100a16 can promote the progression and angiogenesis of renal cell carcinoma through the VEGF/VEGFR2 signal transduction pathway and lead to poor prognosis of renal cell carcinoma. These findings suggest a potential target for the development of anticancer strategies for renal cancer.
Artificial Intelligence Algorithm-Based Feature Extraction of Computed Tomography Images and Analysis of Benign and Malignant Pulmonary Nodules
Authors: Gao Yuantong , Chen Yuyang , Jiang Yuegui , Li Yongchou , Zhang Xia , Luo Min , Wang Xiaoyang , Li Yang
Published: September 2022

This study was aimed to explore the effect of CT image feature extraction of pulmonary nodules based on an artificial intelligence algorithm and the image performance of benign and malignant pulmonary nodules. In this study, the CT images of pulmonary nodules were collected as the research object, and the lung nodule feature extraction model based on expectation maximization (EM) was used to extract the image features. The Dice similarity coefficient, accuracy, benign and malignant nodule edges, internal signs, and adjacent structures were compared and analyzed to obtain the extraction effect of this feature extraction model and the image performance of benign and malignant pulmonary nodules. The results showed that the detection sensitivity of pulmonary nodules in this model was 0.955, and the pulmonary nodules and blood vessels were well preserved in the image. The probability of burr sign detection in the malignant group was 73.09% and that in the benign group was 8.41%. The difference was statistically significant (

P
<
0.05

). The probability of malignant component leaf sign (69.96%) was higher than that of a benign component leaf sign (0), and the difference was statistically significant (

P
<
0.05

). The probability of cavitation signs in the malignant group (59.19%) was higher than that in the benign group (3.74%), and the probability of blood vessel collection signs in the malignant group (74.89%) was higher than that in the benign group (11.21%), with statistical significance (

P
<
0.05

). The probability of the pleural traction sign in the malignant group was 17.49% higher than that in the benign group (4.67%), and the difference was statistically significant (

P
<
0.05

). In summary, the feature extraction effect of CT images based on the EM algorithm was ideal. Imaging findings, such as the burr sign, lobulation sign, vacuole sign, vascular bundle sign, and pleural traction sign, can be used as indicators to distinguish benign and malignant nodules.
Diversity, Structural, and Regeneration Analysis of Woody Species in the Afromontane Dry Forest of Harego, Northeastern Ethiopia
Authors: Bogale Worku Belachew , Birhane Hizkias Emiru , Muhie Dawud Seid
Published: September 2022

The study was conducted in the Harego dry Afromontane forest, Northeastern Ethiopia, to analyze woody species composition, diversity, structure, and regeneration status. To collect the vegetation data, a total of 67 sample plots measuring

400

m

2

20
m
×
20
m

were laid systematically. Species identity, abundance, height, and diameter at breast height (DBH) were recorded for each sample plot. Diversity, structural, and regeneration status were analyzed for the forest. A total of 50 woody species representing 35 families and 44 genera were identified and recorded. According to the IUCN Red List Category, Rhus glutinosa A. Rich and Prunus africana (Hook.f.) Kalkm. are vulnerable species. Fabaceae was the dominant family, and of the total species, 27 were shrubs, 19 were trees, and 4 were climbers. The species accumulation curve indicates that the majority of plant species in the study area were captured by our sampling efforts. The values of true Shannon (N1 = 17) and true Simpson (N2 = 11) indicate that species in the Harego forest are more or less evenly distributed. The abundance-frequency ratio of all woody species (WI = >0.05) indicates the heterogeneity of species composition. The total density and basal area were 4400 stems ha−1 and 9.66 m2 ha−1, respectively. The majority of the species fallen into the lower IVI classes. The diameter and height class distribution revealed an inverted J-shape. The increase in population demand and disturbance shows a high variation in stand structure and hampered natural regeneration, which needs immediate conservation actions.
Parameter Testing and System of Skiing Aerial Skills under the Background of Artificial Intelligence
Authors: Wang Dan
Published: September 2022

Skiing aerial skills are a perfect combination of gymnastics tossing technology and skiing technology. It pursues technology and aesthetics in the process of completing the action, and is a sporting event with strong skills and high viewing. However, the training of ski aerial skills is more difficult, and there is no qualified training mode, which may be detrimental to the long-term development of the overall strength of ski aerial skills. Therefore, based on the shortcomings of the current stage, this paper proposed a ski aerial skill movement detection system. The system mainly assists the MTi sensor to obtain the sports shape parameters of the skier’s sports information and then analyzes the obtained data to find out the approximate data of each parameter when the skiing succeeds and fails, as well as the relationship between acceleration and speed. The experimental results showed that the maximum resultant acceleration and resultant velocity are obtained at the lowest point of the landslide. At a certain stage of the air, the resultant acceleration is always around 10 m/s2 due to gravity. The shoulder joint angle of the skier at the moment of introduction is about 163.2° for success and about 167.6° for failure. The inclination of the trunk is about 30.4° when the action is successful at the moment of landing, while the inclination of the trunk is about 38.4° when the action fails, and the angle of the hip joint in the successful and failed actions is about 138.5° and 153.8°, respectively.
Research on Modern Book Packaging Design Based on Aesthetic Evaluation Based on a Deep Learning Model
Authors: Wen Wen
Published: September 2022

Through the analysis of the application and development of deep learning in the field of book design and publishing, the article expounds on the positive impact of deep learning on book design and publishing, discusses the shortcomings of deep learning in creative ability, aesthetic ability, emotion, etc., and then discusses the design and publishing of books. The future development direction of intelligent aided design and intelligent personalized design is proposed to provide a reference for researchers in deep learning and book design and publication.
A SYN Flood Attack Detection Method Based on Hierarchical Multihead Self-Attention Mechanism
Authors: Guo Xiaojun , Gao Xuan
Published: September 2022

Existing SYN flood attack detection methods have obvious problems such as poor feature selectivity, weak generalization ability, easy overfitting, and low accuracy during training. In the paper, we present a SYN flood attack detection method based on the Hierarchical Multihad Self-Attention (HMHSA) mechanism. First, we use one-hot encoding and normalization to preprocess traffic data. Then the preprocessed traffic data is transmitted to the Feature-based Multihead Self-Attention (FBMHA) layer for feature selection. Finally, we use data slices to determine the features of the preprocessed traffic data under time series by passing the preprocessed traffic data into the Slice-based Multihead Self-Attention (SBMHA) layer. We tested the proposed method on different datasets. The experimental results show that compared with other works, our method presents better in feature selection and higher detection accuracy (even up to 99.97%).
Identification of Novel Immunologic Checkpoint Gene Prognostic Markers for Ovarian Cancer
Authors: Huo Xiao , Zhang Xi , Li Shuhong , Wang Shuzhen , Sun Hengzi , Yang Mo
Published: September 2022

Ovarian cancer has a higher resistance to chemotherapy, displaying the highest mortality rate among gynecological cancers. Recently, immune checkpoint inhibitor therapy is an effective treatment for selected patients. However, a low response rate for immune checkpoint treatment was observed for ovarian cancer patients. Therefore, it is necessary to identify ovarian cancer patients who might gain benefits from immune checkpoint treatment. Datasets containing ovarian cancer samples with mRNA-seq and clinical follow-up data were downloaded from different databases like The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The researchers applied the univariate analysis for selecting the immune checkpoint genes (ICGs) at a significance level of

P
<
0.05

as the candidate ICGs. The Spearman correlation coefficients were calculated to compare the correlation between tumor mutation burden and candidate ICGs, and the Kaplan-Meier plots were generated. They also assessed the external validation datasets and the results of immunohistochemical staining. 46 and 35 ICGs were extracted from the TCGA and GEO datasets, respectively, and we categorized the ICGs into 3 expression patterns. Nine (TCGA) and three (GEO) ICGs were significantly related to the prognosis. Univariate survival analysis indicated a significant prognostic relationship between the expression levels of ICOS, TIGIT, and TNFRSF8 and overall survival (OS). Moreover, the expression of ICOS and TIGIT also presented a significantly positive relationship with the CD8A expression. Importantly, patients with a higher CD8A and ICOS expression level (ICOS-H/CD8A-H) showed a better survival rate compared to other patients. Stratified analysis using TIGIT, TNFRSF8, and CD8A expression also showed an improved prognosis for the high TIGIT/high CD8A expression subgroup and the low TNFRSF8/low CD8A expression subgroup compared to the other subgroups. This study identified different immune subtypes that can predict the OS of ovarian cancer patients. This data could prove to be beneficial for making important clinical decisions and designing individual immunotherapeutic strategies.
Swimming Movement Guidance Training System Based on OpenCL Technology
Authors: Tian Xiaopeng
Published: September 2022

In order to improve the physical quality and even ability of swimmers, this study built OpenCL technology for the swimming movement design system of swimmers, so as to design a series of movements. Combined with the capture system, this paper captures and processes the athletes’ movements, obtains the key position information, and calculates the accurate data. It can provide effective guidance for accurately positioning athletes’ swimming movements, enable users to have a clearer understanding of their own movements, improve users’ movements, and enhance the system operation effect. According to the technology and application requirements of virtual swimming training simulator, the overall design scheme of the device is determined. From the point of view of ensuring the comfort and safety of simulated virtual swimming, the design, installation, and strength verification of the supporting structure are carried out. Hardware design and selection shall be carried out according to the requirements of head position detection and virtual environment presentation, including the design of positioning ball set, camera selection, and VR head display selection. The software functions of head position detection program and virtual scene program are designed according to the requirements of natural human-computer interaction. The designed swimming guidance training system has complete functions and stable operation and can be used as an auxiliary tool for swimming training.
Fyn Signaling in Ischemia-Reperfusion Injury: Potential and Therapeutic Implications
Authors: Du Fang , Tang Tao , Li Qingzhu , Liu Jiaxin
Published: September 2022

Ischemic stroke caused by arterial occlusion is the most common type of stroke and is one of the leading causes of disability and death, with the incidence increasing each year. Fyn is a nonreceptor tyrosine kinase belonging to the Src family of kinases (SFKs), which is related to many normal and pathological processes of the nervous system, including neurodevelopment and disease progression. In recent years, more and more evidence suggests that Fyn may be closely related to cerebral ischemia-reperfusion, including energy metabolism disorders, excitatory neurotoxicity, intracellular calcium homeostasis, free radical production, and the activation of apoptotic genes. This paper reviews the role of Fyn in the pathological process of cerebral ischemia-reperfusion, including neuroexcitotoxicity and neuroinflammation, to explore how Fyn affects specific signal cascades and leads to cerebral ischemia-reperfusion injury. In addition, Fyn also promotes the production of superoxide and endogenous NO, so as to quickly react to produce peroxynitrite, which may also mediate cerebral ischemia-reperfusion injury, which is discussed in this paper. Finally, we revealed the treatment methods related to Fyn inhibitors and discussed its potential as a clinical treatment for ischemic stroke.
Multi-Dimensional Post Competency Evaluation Model in Human Resource Management under the Background of Artificial Intelligence
Authors: Zhang JunXia , Yuan Ying
Published: September 2022

In order to evaluate the competence of candidates in human resource management and select the most suitable talents, the behavior time interview method is used to build a personnel competency model, and various competency indicators are determined. According to the existing mature traditional analysis methods, we calculate the weight of each index and give the competency score. Based on the traditional competency model, the parameters of the training content of BP neural network are obtained. After the training results are tested, a new competency evaluation model based on artificial intelligence is proposed. The results show that the relative error between the model training results and the expected output is very small, the maximum value is −0.12%, and the maximum relative error between the output value obtained by BP neural network and the expected value is 3.8%. Therefore, the personnel competency model based on BP neural network constructed in this paper has accurate calculation results, and its application in the company’s human resource management is feasible and has strong applicability.
Abstract A002: Dynamic single cell imaging of cancer stem cells and clonality in fusion-negative rhabdomyosarcoma
Authors: Eng Tiffany , Wei Yun , Qin Qian , Yan Chuan , Yang Qiqi , Veloso Alexandra , McCarthy Karin , Langenau David
Published: September 2022

Rhabdomyosarcoma (RMS) accounts for 50% of all soft-tissue childhood sarcomas and is characterized by tumor cells that molecularly and morphologically resemble undifferentiated skeletal muscle. Treatment involves an aggressive regimen of chemotherapy followed by surgical resection and/or radiation therapy. Although survival rates can be as high as 70-90% in low-risk or localized disease, patients with oligoclonal or relapsed disease have extremely poor prognoses. Thus, there is a clinical imperative to identify novel therapeutic targets, particularly ones that could reduce clonality and suppress cancer stem cell self-renewal. Our lab has recently shown that fusion-negative (FN-)RMS contain four dominant tumor cell states: proliferative, ground, mesenchymal cancer stem cells (mCSCs) and differentiated muscle. Importantly, the mCSCs are largely quiescent under normal growth conditions but re-enter the cell cycle to promote tumor growth following stress. This suggests that mCSCs are likely responsible for driving therapy resistance and relapse. Building on our previous successes in live imaging cancer stem cells using transgenic zebrafish models that express fluorophores under control of developmentally restricted muscle promoters, we are now developing similar approaches to drive fluorescent protein expression in human FN-RMS cell lines to trace lineage fate and to witness the division history of mCSCs in real time. Using a combination of CRISPR/Cas9 gene inactivation and these newly developed tools, we are poised to identify new self-renewal pathways by the direct, live-cell imaging of FN-RMS engrafted into optically clear, immune-deficient zebrafish. In addition, we are also using tumor clonality as a surrogate of increased tumor aggression and cancer stem cell potential in the zebrafish RAS-induced RMS model. We have adapted the transgenic zebrafish model of kRASG12D-induced RMS to analyze tumor clonality using multispectral Zebrabow and GESTALT, a CRISPR barcoding technique that tracks cell fate. Using RMS-specific gene expression datasets that are associated with cancer stem cells, we are now screening for genes that elevate tumor clonality, increase tumor penetrance and accelerate tumor growth. Ultimately, by developing these lineage tracing tools in both human RMS cell lines and our transgenic Zebrafish RMS model, we will identify new modulators of the mCSC transcriptional cell states and possible therapeutic targets.

Citation Format: Tiffany Eng, Yun Wei, Qian Qin, Chuan Yan, Qiqi Yang, Alexandra Veloso, Karin McCarthy, David Langenau. Dynamic single cell imaging of cancer stem cells and clonality in fusion-negative 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 A002.
Abstract A006: Defining the microenvironment of alveolar soft part sarcoma & it’s role in therapeutic outcomes
Authors: Philippot Alexis M. , Dang Ngoc Ha , Menon Shyam V. , Bourdage Jennifer , Lun Xueqing , Ahn Bo Young , Robbins Stephen M. , Senger Donna L.
Published: September 2022

Alveolar soft part sarcoma (ASPS) is a rare pediatric malignancy which has characteristically poor clinical outcomes due to a propensity to metastasize along with a complete lack of chemotherapeutic options. One additional difficulty of this rare tumor is an absence of established in vivo models. Here, we describe the establishment of a patient derived xenograft model (PDX), and corresponding cell line, from the lung metastases of a 14-year-old female diagnosed with ASPS. Using this model, we performed a drug screen, from which the proteasome inhibitor carfilzomib inhibited tumor cell viability and growth in vitro and in vivo. To further elucidate factors implicated in tumor progression and chemotherapy resistance, we characterized the microenvironment and secretome of the ASPS PDX. In keeping with recent literature showing large numbers of tumor associated macrophage (TAMs) in ASPS, we found that 96% of the myeloid cells present in the PDX were TAMS, with 35% taking on a pro-tumor phenotype. Further, factors secreted by the tumor microenvironment largely support immune cell recruitment and pro-tumor phenotypes. Interestingly, in vivo assessment demonstrates that Iba1+ macrophage populations decrease by 60% with carfilzomib treatment. This prompted investigation into the potential impact of TAMs on ASPS growth and progression, and if they are implicated in the therapeutic response to carfilzomib. Based on preliminary findings that carfilzomib targets the pro-tumor phenotypic states of bone marrow derived macrophage in vitro, we hypothesize that carfilzomib alters the recruitment and phenotype of TAMs, decreasing tumor cell viability in vitro, and thus tumor burden in vivo.

Citation Format: Alexis M. Philippot, Ngoc Ha Dang, Shyam V. Menon, Jennifer Bourdage, Xueqing Lun, Bo Young Ahn, Stephen M. Robbins, Donna L. Senger. Defining the microenvironment of alveolar soft part sarcoma & it’s role in therapeutic outcomes [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 A006.
Abstract A007: Resident memory T cells express PD-1 in high grade liposarcoma
Authors: Angeles Christina V. , Han Jichang , Wilkoswki Jodi , Bresler Scott
Published: September 2022

Objective: Memory T cells play crucial roles in anti-tumor immunity. Tumor-associated resident memory T cells (TRM) have been associated with durable immune response and improved patient survival across multiple tumor types. SARC028, a phase II, multicenter trial of pembrolizumab, a programmed death 1 (PD-1) checkpoint inhibitor immunotherapy, showed promising activity in select histologic subtypes of advanced soft tissue sarcoma (STS), including dedifferentiated liposarcoma (DDLPS). However, there was only a 20% overall response rate. Notably, the patients who did respond to immunotherapy had durable responses, supporting our enthusiasm to understand the potential role for TRM in liposarcoma anti-tumor immunity. The characterization of memory T cells in liposarcoma, and whether TRM are present has not been explored. Design: Fresh retroperitoneal liposarcoma specimens from 8 patients: 3 well-differentiated liposarcoma (WDLPS) and 5 DDLPS were collected. Lymphocytes were analyzed by flow cytometry using T-cell (CD45, CD3, CD4, CD8) and phenotypic markers (CD69, CD62L, CD103, CD49a, PD-1, TIM-3). Results: DDLPS had a 4-fold higher overall T-cell infiltration and a 2.5-fold higher CD8+/CD4+ T-cell ratio than WDLPS. DDLPS contained CD8+ T cells with a CD45RA− CCR7− CD69hi CD62Llo phenotype, characteristic of a TRM response, and well as CD69lo effector memory T (TEM) cells. DDLPS had 3-fold more TRM than WDLPS. DDLPS had a much higher level of activated PD-1+ CD69+ CD8+ resident memory T-cell population compared to WDLPS. Additionally, the population of TRM had higher PD-1 expression compared to TEM in both DDLPS and WDLPS. Conclusions: These data suggest that TRM subsets may contribute to the responsiveness to anti-PD1 therapy in patients with DDLPS. Further investigations may lead to the discovery of TRM-targeted T-cell therapies in DDLPS, which currently has limited treatment options.

Citation Format: Christina V. Angeles, Jichang Han, Jodi Wilkoswki, Scott Bresler. Resident memory T cells express PD-1 in high grade liposarcoma [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 A007.
Abstract A021: Chimeric antigen receptor armored natural killer cell immunotherapy for osteosarcoma
Authors: Robbins Gabrielle , Yamomoto Kenta , Lahr Walker , Skeate Joseph
Published: September 2022

Over the last decade, Chimeric Antigen Receptor based T cell (CAR-T) therapy has developed into an effective immunotherapy for several cancers, primarily limited to those of hematological origin. In other cancers, especially solid tumors, CAR-T cell therapies have several shortcomings and clinical success has been underwhelming. Challenges of CAR-T cell therapy include tumor immune evasion through loss of target antigen expression by tumor cells and inhibition of CAR-T cell function by tumor expressed inhibitory molecules. Natural killer (NK) cells present an alternative to T cells that could be more effective due to their ability to perform both antigen dependent and independent killing. NK cells can mediate the direct killing of transformed cells with reduced or absent MHC expression in addition to carrying out antibody dependent cell mediated cytotoxicity (ADCC) of cells bound by antibodies via the NK cell CD16A receptor. Engineering NK cells to express CARs will effectively enable them with additional antigen specific killing. Due to the multiple modalities for cancer cell killing, there is an increased interest in NK cells for cancer immunotherapy. As NK cells are not associated with graft versus host disease, neurotoxicity, long-term autoimmunity, nor cytokine release syndrome, they are more suited for use in allogeneic settings than T cells and have significant clinical potential for use as off-the-shelf products. However, previous publications and clinical trials have demonstrated that the use of unmanipulated NK cells to treat cancer is minimally effective, likely due to limited engraftment, little in vivo expansion or persistence, and suppression by the tumor microenvironment. NK cells activated and expanded with engineered feeder cells expressing membrane bound interleukin-21 (mbIL-21) and 4-1BBL have shown promising results clinically with high-risk myeloid malignancies and preclinically in several solid tumor models. Therefore, we hypothesize that activated/expanded CAR-NK cells that have been genetically edited can be used to successfully treat osteosarcoma, a disease for which patient outcome has not improved in over forty years. Our proposed objective is to evaluate the non-viral KI of several CARs, either alone or in combination, that optimally activate NK cell antigen-specific killing. Genetically engineered CAR-NK cells will be evaluated for enhanced therapeutic efficacy and safety in osteosarcoma models. Our preliminary data strongly supports the hypothesis that CAR-NK cell-based cancer immunotherapy can be fully realized using activated, genome engineered CAR-NK cells.

Citation Format: Gabrielle Robbins, Kenta Yamomoto, Walker Lahr, Joseph Skeate. Chimeric antigen receptor armored natural killer cell immunotherapy for osteosarcoma [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 A021.
Abstract A025: Profiling tumor infiltrating immune cells for better understanding tumor status and better response to therapeutic strategy in soft tissue sarcomas
Authors: Lee Eun-Young , Kang Hyun Guy , Kim June Hyuk , Park Jong Woong , Park Seog Yun , Yun Tak , You Hye Jin
Published: September 2022

The tumor microenvironment is closely associated with tumor development and progression, which is made up of tumor cells, blood vessels, immune cells, fibroblast, and so on. Especially, immune cells within tumor microenvironments have been attracted in clinicians and researchers for unexpected therapeutic responses. Even in sarcoma, which is rare, and heterogenous leading to few options for cure, immune therapy has been tried and shown to be promising. However, the information of immune cells within soft tissue sarcomas were limited, which mostly have been obtained and characterized by omics-based analyses or tissue staining such as immunohistochemistry. Here, we established platform to profile tumor infiltrating immune cells by flow cytometry. About thirty sarcoma tissues were obtained, in which tumor infiltrating immune cells were profiled. The profiled data were confirmed by immunohistochemistry for correlation. It was shown that infiltrated leukocytes and CD3+ T cells were remarkably increased, whereas NKT and CD4+ T cells were decreased in tumor tissues compared to adjacent normal tissues. M1 macrophage was also increased in tumor tissues. High CD3+ T cell population was positively correlated with CD8+ T cells and PD1+ CD8+ T cell population. Especially, PD1+CD8+ T cells are usually expressed exhaustion-related conditions and low levels of cytotoxic immune cells. This study provides resources to understand immune cell population of soft tissue sarcoma, and will gain a fundamental matrix to study immunotherapy. These studies might show the possibility to find potential prognostic and immunotherapeutic targets.

Citation Format: Eun-Young Lee, Hyun Guy Kang, June Hyuk Kim, Jong Woong Park, Seog Yun Park, Tak Yun, Hye Jin You. Profiling tumor infiltrating immune cells for better understanding tumor status and better response to therapeutic strategy in soft tissue sarcomas [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 A025.