bluuebunny/crossref_metadata_2025 huggingface dataset:
3D Lagrangian Particle Tracking in Fluid Mechanics
Authors: Schröder Andreas , Schanz Daniel
Published: October 2022

In the past few decades various particle image–based volumetric flow measurement techniques have been developed that have demonstrated their potential in accessing unsteady flow properties quantitatively in various experimental applications in fluid mechanics. In this review, we focus on physical properties and circumstances of 3D particle–based measurements and what knowledge can be used for advancing reconstruction accuracy and spatial and temporal resolution, as well as completeness. The natural candidate for our focus is 3D Lagrangian particle tracking (LPT), which allows for position, velocity, and acceleration to be determined alongside a large number of individual particle tracks in the investigated volume. The advent of the dense 3D LPT technique Shake-The-Box in the past decade has opened further possibilities for characterizing unsteady flows by delivering input data for powerful data assimilation techniques that use Navier–Stokes constraints. As a result, high-resolution Lagrangian and Eulerian data can be obtained, including long particle trajectories embedded in time-resolved 3D velocity and pressure fields.
Study on the Level of Integration of Equipment Manufacturing Industry and Producer Service Industry in the Region Transforming Provinces and Its Influencing Factors: Taking Shanxi Province as an Example
Authors: Ding Tao , Bai Guoxin , Xu Han
Published: October 2022

At present, China’s equipment manufacturing industry and producer service industry are gradually ushered in the leapfrog high-quality development of the rising period. It is particularly important how Shanxi, as the vanguard of the transformation and development, positively responds to the national call to break the shackles of the current integrated development of equipment manufacturing and producer services, for Shanxi Province and even the country’s future industrial integration, transformation, and upgrading to accumulate “Shanxi Experience.” Therefore, this paper measures and analyzes the integration level of equipment manufacturing and production services between 2012 and 2017 using the input-output method. Then, by constructingthe model of the factors influencing the integration of Shanxi’s equipment manufacturing industry and producer service industry, selecting the relevant indicators and bringing in the relevant data from 2009 to 2019, by using the principal component regression analysis method, and thus clarifies the main factors that influence the convergence of the equipment manufacturing industry and production service industry in Shanxi. Finally, this paper has provided targeted countermeasures and suggestions to further promote the integration of the two industries in Shanxi Province.
Clinical Observation of Modified Implantation of ASD Closure Device to Treat BPFs
Authors: Lu Yangfei , Zhang Jisong , Chen Enguo , Ying Kejing
Published: October 2022

Objectives. The aim of the paper is to explore the clinical efficacy and prognosis of the modified implantation of atrial septal defect (ASD) closure device to treat bronchopleural fistulas (BPFs). Methods. This paper has reviewed the results of 13 BPF patients implanted with a modified ASD closure device in Shaw Hospital Affiliated with the Medical College of Zhejiang University from October 2018 to November 2021. Anesthesia was selected based on the patient’s condition. Different sizes of ASD closures were selected based on the characteristics of fistulas. The modified implantation of the ASD closure device was applied to treat BPFs. The closure effects, closure time, and Borg score were observed at 4 weeks, 8 weeks, and 12 weeks after the surgery. Results. All 13 BPF patients were successfully implanted with the ASD closure device, and the immediate clinical remission rate was 100%. Follow-up at 4 weeks after the surgery showed that 2 cases were automatically discharged within a few days and 4 cases had closed fistula at 1 day after the surgery; follow-up at 8 weeks after the surgery showed that 1 case with fistula closure was observed at 55 days after the surgery; follow-up at 12 weeks after the surgery showed that 1 case with fistula closure was observed at 82 days after the surgery. T/P values (T = 7.90, 5.99, 7.44,

P
<
0.05

) of paired t-tests before surgery and 4 weeks, 8 weeks, and 12 weeks after the surgery were rated by the Borg scale. The data were statistically different, and the clinical symptoms improved significantly. As of publication, the follow-up at 12 weeks after the surgery showed that the clinical remission rate was 9/11, namely, 81.8%, 3 of 11 cases had relieved clinical symptoms but still needed continuous drainage, and 2 cases had fistula closure. The median time of thoracic extubation was 63 (3,120) days. No patients died from surgical complications or BPF recurrence during the prognosis and the follow-up period. Conclusions. The modified implantation method has a high success rate and clinical remission rate, quick and early fistula closure, and simple and noninvasive operation, without the need for a dedicated delivery sheath and rigid endoscopy. Moreover, it has accurate positioning, reliable closure efficiency, and prognosis, and can be completed under local anesthesia. This reduces the operation time, difficulty, and risks of anesthesia.
Graph-Theory-Based Degree Centrality Combined with Machine Learning Algorithms Can Predict Response to Treatment with Antipsychotic Medications in Patients with First-Episode Schizophrenia
Authors: Liu Wenming , Fang Peng , Guo Fan , Qiao Yuting , Zhu Yuanqiang , Wang Huaning
Published: October 2022

Objectives. Schizophrenia (SCZ) is associated with disrupted functional brain connectivity, and antipsychotic medications are the primary and most commonly used treatment for schizophrenia. However, not all patients respond to antipsychotic medications. Methods. The study is aimed at investigating whether the graph-theory-based degree centrality (DC), derived from resting-state functional MRI (rs-fMRI), can predict the treatment outcomes. rs-fMRI data from 38 SCZ patients were collected and compared with findings from 38 age- and gender-matched healthy controls (HCs). The patients were treated with antipsychotic medications for 16 weeks before undergoing a second rs-fMRI scan. DC data were processed using DPABI and SPM12 software. Results. SCZ patients at baseline showed increased DC in the frontal and temporal gyrus, anterior cingulate cortex, and precuneus and reduced DC in bilateral subcortical gray matter structures. However, those abnormalities showed a clear renormalization after antipsychotic medication treatments. Support vector machine analysis using leave-one-out cross-validation achieved a correct classification rate of 84.2% (sensitivity 78.9%, specificity 89.5%, and area under the receiver operating characteristic curve (AUC) 0.925) for differentiating effective subjects from ineffective subjects. Brain areas that contributed most to the classification model were mainly located within the bilateral putamen, left inferior frontal gyrus, left middle occipital cortex, bilateral middle frontal gyrus, left cerebellum, left medial frontal gyrus, left inferior temporal gyrus, and left angular. Furthermore, the DC change within the bilateral putamen is negatively correlated with the symptom improvements after treatment. Conclusions. Our study confirmed that graph-theory-based measures, combined with machine-learning algorithms, can provide crucial insights into pathophysiological mechanisms and the effectiveness of antipsychotic medications.
[Retracted] Artificial Intelligence Technology Driven Environmental Factors Extraction and Analysis Method in Traditional Clothing Handicraft
Authors: Tao Ran , Guo Qi
Published: October 2022

The application of artificial intelligence (AI) technology in the field of clothes can provide a good development mode and system under the social context of AI technology development. AI provides help for the development of intelligent clothing. Intelligent clothing is a high‐tech product that integrates intelligent technology and clothing. It combines cutting‐edge technologies in electronic information technology, sensor technology, textile science, and material science. In the extraction and analysis of environmental factors in clothing handicraft, AI technology has a considerable application prospect and a certain development potential. In order to improve the accuracy of environmental factors extraction in clothing handicraft, this paper uses convolutional neural network (CNN) to extract and analyze environmental factors in traditional clothing handicraft. We carried out experiments on the extraction of environmental factors in clothing handicrafts with pure color, few patterns, patterns, and complex background. The experimental results show that the CNN has a good effect on the extraction of environmental factors in clothing handicraft under different backgrounds. In addition, the model in this paper has good stability, accuracy, and feature extraction speed, which has high practical value and research significance.
Evolutionary Game Analysis of Green Building Development Dynamic System under Government Regulation: From the Perspective of the Contractor
Authors: Li Xiangjun
Published: October 2022

To speed up the development of green buildings (GB) and meet the requirements of low energy consumption, low carbon dioxide emissions, and green sustainable development, the key is to build a high-efficient green building dynamic system (GBDS). The government, the developer, and the contractor are the main power of GB promotion, and they are the main participants of GBDS. This paper aims to study how to improve the motivation of contractors’ investment and participation in GB under the government regulation measures, to make up for the gap of research on the contractor’s dynamic mechanism in the GBDS. In the research, evolutionary game theory was applied to build a dynamic model of the evolutionary game among the government, the developer, and the contractor, and the evolutionary laws and stability strategies of their game behaviors were analyzed. The research results show that the contractor’s motivation of building GBs depends on the sum of receipts after the mix of income from construction and government rewards and penalties. The higher the sum of receipts is, the more stable the contractor’s decision to participate in GBs is. When the government gives better incentive measures to the contractor, it is easier for the government, the developer, and the contractor to form an unanimous decision on the GB strategy, so the development dynamic system of GB is more stable.
Predictive Value Analysis of Serum Ig A, Ig G, and TNF-α in Recurrence of Multiple Myeloma
Authors: Jia Xinyan , Liu Xiangxin , Yang Wenzhong
Published: October 2022

Objective. The study is aimed at analyzing the predictive value of serum Ig A, Ig G, and TNF-α in the recurrence of multiple myeloma (MM). Methods. 136 patients with MM treated in our hospital from January 2010 to January 2017 were followed up for 5 years. Finally, 100 patients who met the inclusion and exclusion criteria and had the complete follow-up visit were selected as the study subjects, with the recurrence of MM as endpoint event, and the observation was taken until the occurrence of endpoint event in patients or the termination of this study. They were divided into the recurrence group (RG) and the nonrecurrence group (NRG) according to whether the endpoint event occurred. The venous blood of patients was collected at the first diagnosis and subsequent visit (at the time of recurrence or termination of the study) to measure the Ig A and Ig G using a full automatic special protein analyzer and the TNF-α level by enzyme-linked immunosorbent assay. The data obtained in this study were analyzed by univariate analysis to choose the factors with difference in statistical significance to draw the ROC curve, and the areas under the curve (AUC) were recorded to analyze the potential mechanism of Ig A, Ig G, and TNF-α in predicting the recurrence of MM. Results. After follow-up visit, there were 62 patients with recurrence (62.0%) and 38 patients without recurrence (38.0%), with no obvious difference in gender, age, body weight, and immune classification between the two groups (

P
>
0.05

). Compared with the NRG, the levels of soluble interleukin-2 receptor (sIL-2R) and β2-microglobulin (β2-MG) in the RG at the first diagnosis were distinctly higher (

P
<
0.001

); the levels of Ig A, Ig G, and TNF-α in the RG at the first diagnosis were visibly higher (

P
<
0.05

); and the levels of Ig A, Ig G, and TNF-α in the RG at the subsequent visit were clearly higher (

P
<
0.05

). There was a correlation between Ig G, Ig A, and TNF-α and β2-MG at the first diagnosis and the subsequent visit (

P
<
0.05

); there was a correlation between Ig G and TNF-α, and sIL-2R at the first diagnosis and the subsequent visit (

P
<
0.05

); and there was a correlation between Ig A and sIL-2R at the subsequent visit (

P
<
0.05

). The AUC of Ig G, Ig A, and TNF-α in predicting the MM at the first diagnosis were 0.772, 0.776, and 0.778, respectively. Conclusion. The serum Ig A, Ig G, and TNF-α had a predictive value in the recurrence of MM, and TNF-α was correlated with sIL-2R and β2-MG, with the highest AUC and the best predictive value.
Investigation of Proton Beam-Driven Fusion Reactions Generated by an
Ultra-Short Petawatt-Scale Laser Pulse
Authors: Schollmeier Marius S. , Shirvanyan Vahe , Capper Christie , Steinke Sven , Higginson Adam , Hollinger Reed , Morrison John T. , Nedbailo Ryan , Song Huanyu , Wang Shoujun , Rocca Jorge J. , Korn Georg , Batani Dimitri
Published: October 2022

We present results from a pitcher-catcher experiment utilizing a proton
beam generated with nanostructured targets at a petawatt-class, short-pulse
laser facility to induce proton-boron fusion reactions in a secondary
target. A 45-fs laser pulse with either 400 nm wavelength and 7 J energy, or
800 nm and 14 J, and an intensity of up to 5 × 1021
W/cm2 was used to irradiate either thin foil
targets or near-solid density, nanostructured targets made of boron nitride
(BN) nanotubes. In particular, for 800 nm wavelength irradiation, a BN
nanotube target created a proton beam with about five times higher maximum
energy and about ten times more protons than a foil target. This proton beam
was used to irradiate a thick plate made of boron nitride placed in close
proximity to trigger 11B
(p, α)
2α fusion reactions. A suite of diagnostics
consisting of Thomson parabola ion spectrometers, postshot nuclear
activation measurements, neutron time-of-flight detectors, and
differentially filtered solid-state nuclear track detectors were used to
measure both the primary proton spectrum and the fusion products. From the
primary proton spectrum, we calculated (p, n) and
(α,n) reactions in the catcher and compare
with our measurements. The nuclear activation results agree quantitatively
and neutron signals agree qualitatively with the calculations, giving
confidence that primary particle distributions can be obtained from such
measurements. These results provide new insights for measuring the ion
distributions inside of proton-boron fusion targets.
YTHDF2 Regulates Macrophage Polarization through NF-κB and MAPK Signaling Pathway Inhibition or p53 Degradation
Authors: Cai Luhui , Li Di , Feng Zhihui , Gu Xiaofei , Xu Qiong , Li Qimeng
Published: October 2022

Macrophages are heterogeneous cells that can be polarized into M1 or M2 phenotype. m6A “reader” YTH domain family protein 2 (YTHDF2) has been the m6A binding protein with the highest activity, which can recognize and disturb m6A-containing mRNA in processing bodies to reduce mRNA stability. YTHDF2 is recently identified as an effective RNA binding protein that modulates inflammatory gene levels within inflammatory responses. However, the role of YTHDF2 in M1/M2 macrophage polarization has not been reported. We established a M1/M2 macrophage polarization model using bone-marrow-derived macrophages and found that the expression levels of YTHDF2 in M1/M2 macrophages were both elevated. YTHDF2-knockdown macrophage polarization model was then established, and through qPCR, ELISA, and FACS, we discovered that suppressing YTHDF2 encouraged M1 polarization but restrained M2 polarization. In M1 macrophages, YTHDF2 silencing had no significant effect on p53 expression; however, in YTHDF2 knockdown, M2 macrophage p53 expression was remarkably upregulated. p53 inhibitor PFT-α was then applied and revealed that suppressing p53 simultaneously promoted YTHDF2-silenced M1 polarization and facilitated M2 macrophage polarization. Actinomycin D assays were further utilized to examine the mRNA degradation level of different cytokines, and p53 mRNA degradation in YTHDF2-depleted M2 cells was discovered impeded. Western Blot analysis also implied that a deficit in YTHDF2 expression may activate MAPK and NF-κB pathways. In this study, YTHDF2 induces M2 macrophage polarization by promoting the degradation of p53 mRNA. YTHDF2 suppresses M1 macrophage polarization by inhibiting NF-κB, p38, and JNK signaling pathways, yet p53 remains unaffected in YTHDF2-silenced M1 macrophages.
Video Visualization Technology and Its Application in Health Statistics Teaching for College Students
Authors: Li Chengfei , Xie Yuan , Li Shuanbao
Published: October 2022

In view of the present situation of “learning difficulty” in health statistics, this paper proposes a video visualization technology based on the convolutional neural network, which updates parameters by calculating the gradient of loss function to obtain accurate or nearly accurate loss function. Taking the students from 2014 to 2017 in a university in Henan as the research object, this paper analyzes the video visualization technology and its application effect on the teaching of college students’ health statistics from the aspects of students’ course awareness, learning behavior, communication between teachers and students, knowledge mastery, and course satisfaction. The results show that the external model load difference between each explicit variable and latent variable is statistically significant. Learning behavior and communication between teachers and students have a direct impact on the mastery of knowledge, and the degree of influence from high to low is as follows: learning behavior and communication between teachers and students. The teaching effect model of health statistics based on video visualization technology of the convolutional neural network has certain practicability.
Bioinformatics Identification of Ferroptosis-Associated Biomarkers and Therapeutic Compounds in Psoriasis
Authors: Mao Jingyi , Ma Xin
Published: October 2022

Purpose. Psoriasis is closely linked to ferroptosis. This study aimed to identify potential ferroptosis-associated genes in psoriasis using bioinformatics. Methods. Data from the GSE30999 dataset was downloaded from the Gene Expression Omnibus (GEO), and the ferroptosis-associated genes were retrieved from FerrDb. The differentially expressed ferroptosis-associated genes were identified using Venn diagrams. Subsequently, a network of protein-protein interactions (PPIs) between psoriasis targets and ferroptosis-associated genes was constructed based on the STRING database and analyzed by Cytoscape software. The Metascape portal conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Moreover, the expression of ferroptosis-related genes was verified in the GSE13355 dataset. Finally, the verified genes were used to predict the therapeutic drugs for psoriasis using the DGIdb/CMap database. SwissDock was used to examine ligand docking, and UCSF Chimera displayed the results visually. Results. Among 85 pairs of psoriasis lesion (LS) and no-lesion (NL) samples from patients, 19 ferroptosis-associated genes were found to be differentially expressed (3 upregulated genes and 16 downregulated genes). Based on the PPI results, these ferroptosis-associated genes interact with each other. The GO and KEGG enrichment analysis of differentially expressed ferroptosis-related genes indicated several enriched terms related to the oxidative stress response. The GSE13355 dataset verified the results of the bioinformatics analysis obtained from the GSE30999 dataset regarding SLC7A5, SLC7A11, and CHAC1. Psoriasis-related compounds corresponding to SLC7A5 and SLC7A11 were also identified, including Melphalan, Quisqualate, Riluzole, and Sulfasalazine. Conclusion. We identified 3 differentially expressed ferroptosis-related genes through bioinformatics analysis. SLC7A5, SLC7A11, and CHAC1 may affect the development of psoriasis by regulating ferroptosis. These results open new avenues in understanding the treatment of psoriasis.
Impact of Labour Productivity Differences on Urban‐Rural Integration Development and Its Spatial Effect: Evidence from a Spatial Durbin Model
Authors: Wang Wei , Zhu Yulin
Published: October 2022

Lewis’ dual economic structure theory holds that differences in labour productivity affect urban‐rural integration development. Based on this theory, this paper analyses the spatial mechanism of labour productivity affecting the development of urban‐rural integration. A multidimensional index system is constructed to estimate the degree of urban‐rural integration development, and a spatial Durbin model is used to quantitatively analyse the spatial effect between the difference in labour productivity and the development of urban‐rural integration. The results show that there is a significant positive spatial agglomeration phenomenon in urban‐rural integration in the Yangtze River Economic Belt. The convergence of labour productivity will not only promote local urban‐rural integration but also inhibit the urban‐rural integration development of other administrative divisions, but it can still play a positive role in promoting the urban–rural integration development of the whole region. Finally, based on the above research conclusions, this paper puts forward three policy suggestions: optimizing the human capital structure, promoting rural industrial integration, and exploring the land reform system.
Facial Line Angles: A Key to Tooth-like Rehabilitation
Authors: Kallala Rim , Gassara Yosra , Azouzi Ines , Adli Amani , Hadyaoui Dalenda , Nouira Zohra , Baccouche Chiraz , Touzi Soumaya , Harzallah Belhassen , Cherif Mounir
Published: October 2022

Recently, improvement of appearance and a quest for beauty have become a primary concern for patients. It is a challenging task for a clinician to achieve esthetic integration of prosthetic pieces for anterior teeth, particularly for highly demanding patients who give attention to particular details. The challenge is harder when only one tooth has to be restored. The objective is to achieve a fully and perfectly integrated rehabilitation with natural dentition. Poorly described, facial line angles are key to the success of achieving the desired tooth shape, especially for the maxillary central incisor. They influence both the shape and color of the tooth through optical illusion. Their misplacement could certainly spoil the esthetic outcome. Thus, it is mandatory to respect and recreate them. The objective of the present study was to define and then to highlight their importance. It also aimed to give some tips on how to perfect the shape of prosthetic teeth through a clinical case of central incisor esthetic rehabilitation.
How to Write a Contemporary Scientific Article?
Authors: Krasnov Vladimir M.
Published: October 2022

Today, scientists are drowned in information and have no time to read all publications, even in a specific area. Information is sifted and only a small fraction of articles is read. Under these circumstances, scientific articles have to be properly adjusted to pass through the superficial sifting. Here, I present instructions for PhD students with almost serious advice on how to write (and how not to write) a contemporary scientific article. I argue that it should “tell a story” and should answer on the three main questions: Why, What, and So what?
Learning Behavior Based on Data Mining Technology
Authors: Wang Jing , Zhang Qiuhong , Guan Meijing
Published: October 2022

With the release of the Education Informatization 2.0 Action Plan and the rapid development of learning analysis technology, educational data mining becomes a new research direction. Data mining can improve teachers’ teaching methods and students’ learning skills by acquiring information hidden in the educational data. Based on the learning behavior data of college students, this paper uses BP neural network, a data mining method, to predict their comprehensive evaluation results. The results show that there is a close relationship between students’ learning behavior and their comprehensive scores. In addition, models of naive Bayes, logistic regression, and decision tree are established for verification and comparison. Compared with other models, BP neural network model has higher prediction accuracy and better performance. It can serve as an important basis to improve students’ learning methods and teachers’ teaching methods.
Experimental and Thermodynamic Investigation on CO2 Absorption in Aqueous MEA Solutions
Authors: Zhu Kai , Yue Changhai , Wei Zhenhao , Huang Jingjing , Hu Meng , Ji Yufan , Liu Hanfei , Zhu Hao , Guo Wanxiao , Zhou Feng , Yao Chaoqun , Huang Yiping
Published: October 2022

The vapor-liquid equilibrium (VLE) of CO2 in a reactive solvent is essential for the proper simulation and design of CO2 absorption processes. This work presents a systematic investigation on CO2 absorption in various aqueous monoethanolamine (MEA) solutions. CO2 solubility in MEA was measured at 298, 313, 333, and 353 K with CO2 partial pressure ranging from 34.5 to 78.0 kPa. A modified Kent-Eisenberg model was developed based on the measured solubility data, showing good predictions over the liquid phase speciation for the CO2-H2O-MEA system. We presented a new analysis based on the first-order difference curve of distribution profiles of the species. Based on the main reactions that occurred, the CO2 absorption process was demonstrated to be divided into four regions with increasing CO2 loading from 0 to 1. Accordingly, kinetic study was proposed to be conducted in the first region, whereas measuring of mass transfer in the first three regions. The findings in this work extend the existing knowledge of CO2 absorption process in terms of speciation and can provide important guidance for further study of the process characteristics using aqueous amine absorbents.
Effect of Microscopic Pore Throat Structure on Displacement Characteristics of Lacustrine Low Permeability Sandstone: A Case Study of Chang 6 Reservoir in Wuqi Oilfield, Ordos Basin
Authors: Qiang Ren , Hu Wei , Guofa Lei , Weigang Zhang , Bingyu Ge , Junxiang Nan
Published: October 2022

Pore throat structure is the key factor affecting displacement efficiency in low permeability reservoirs. In this paper, the pore throat structure and displacement characteristics of Chang 6 low permeability sandstone reservoir in Wuqi area of Ordos Basin were studied by casting thin section analysis, scanning electron microscopy, XRD, high-pressure mercury injection, and microscopic displacement model of real sandstone test. The results show that the size and homogeneity of the pore throat structure deteriorate gradually from type I to type IV reservoir, and the corresponding displacement efficiency also decreases gradually. The type I reservoir is dominated by uniform displacement, and residual oil is dominated by oil film. Type II reservoir is dominated by mesh and finger displacement, while type III reservoir is dominated by finger displacement, and continuous remaining oil distribution is easy to be formed after water flooding. Pore throat size and homogeneity are important factors affecting oil displacement efficiency. The larger the pore throat size, the more homogeneous the structure, and the stronger the seepage capacity, the higher the oil displacement efficiency. With the increase of volume displacement multiple, the displacement efficiency growth rate of the type I reservoir changes little, while the displacement efficiency growth rate of the type II and type III reservoir decreases gradually. In actual production and development, reasonable control of pressure is the key to dependable production.
A Case Report of Immune Checkpoint Inhibitor-Induced Aortitis Treated with Tocilizumab
Authors: Bloomer Chance H. , Annabathula Rahul V. , Aggarwal Vanya , Upadhya Bharathi , Lycan Thomas W.
Published: October 2022

Vasculitic immune checkpoint inhibitor-related adverse events (irAEs) are rare, with limited data to guide their management. Here, we present a case of a 67-year-old female with stage IV cutaneous melanoma who received first-line pembrolizumab. She had completed 21 cycles of pembrolizumab dosed at 200 mg every 21 days over 15 months when she developed fatigue, chills, decreased appetite, night sweats, nausea, diarrhea, dry cough, and chest pain. A routine, staging positron emission tomography (PET) scan revealed aortitis of the transverse aortic arch. An extensive workup was unremarkable for other causes, so her condition was labeled a grade III immune-related vasculitis. Based on this diagnosis, we started high-dose prednisone and discontinued pembrolizumab. After two months of high-dose prednisone, she developed bothersome weight gain and insomnia, leading to a switch from prednisone to tocilizumab as a steroid-sparing agent. The selection of tocilizumab was based on its routine use for giant cell arteritis which can have extracranial symptoms including thoracic aortitis. Her symptoms resolved, and subsequent PET scans showed resolution of the aortitis and no evidence of metastatic melanoma. As the indications for immunotherapy expand, rare complications are becoming more prevalent, and more data will be needed to guide their management. While there is evidence for tocilizumab use as a steroid-sparing treatment for large-vessel vasculitides due to other conditions, this is the first case of its use to treat an aortitis irAE to our knowledge. In this case, it was an effective means of treating the patient while sparing them from prolonged corticosteroids.
Analysis of Damage Constitutive Model for Frozen Red Clay under Uniaxial Compression
Authors: Lin Bin , Zhao Yongjia , Li Guoqiang
Published: October 2022

At present, it is in the peak period of infrastructure construction in western China, and due to the natural climate, the soil has been frozen for a long time, but there is little research on frozen red clay at present. Therefore, it is necessary to further study the mechanical properties of frozen red clay. In this paper, taking the remolded red clay as the test material, the change characteristics of uniaxial compression and uniaxial creep of frozen soil under different test factors are studied by artificial freezing method, and the damage theory is introduced to analyze the test results. The results of uniaxial compression test of frozen soil show that temperature has a great influence on the uniaxial compressive strength, and the compressive strength increases with the decrease of temperature, and the damage theory is introduced. It is found that the initial damage stress increases with the decrease of temperature, while the initial strain changes little with temperature. A damage constitutive equation which can well reflect the whole damage process of frozen red clay is established. The experimental research results of this paper can provide some theoretical reference for the engineering of soil quality for freezing red clay.
Machine Learning-Assisted Competency Modeling for Human Resource Management Jobs
Authors: Cao Changfang , Zhang Zhongying
Published: October 2022

The competency model has an important role in human resource management (HRM) as a scientific and objective talent assessment theory. With the widespread use of machine learning methods, machine learning assistance for HRM job competency assessment and determination provides a new way of thinking for talent assessment and management. The establishment of HR competency models based on machine learning methods can quickly and accurately help companies gain a competitive advantage. Based on this paper, we take Company C as the research object and establish the HR management job, competency model, based on a genetic algorithm optimized BP neural network (GA-BP). The results show that the model can be better applied to the analysis of the HR management job competency model of Company C. The prediction accuracy reaches 91.16% classification accuracy, which has a certain reference significance, and it has a certain reference and value for the HRM job industry.
Evaluation of Loess Collapsibility Based on Random Field Theory in Xi’an, China
Authors: Zhang Yanjie , Han Jianlong , Wang Xu , Jiang Daijun , Li Jiandong
Published: October 2022

The engineering properties of collapsible loess have significant uncertainty. Accurate prediction of collapsible deformation is crucial for the safety of engineering construction in loess areas. Taking the typical collapsible loess stratum as the research object in Xi’an, based on the random field theory, combined with the Monte Carlo strategy and modulus reduction method, the stochastic finite element analysis of loess self-weight collapsibility is carried out to study the influence of the spatial variability of compression modulus on the self-weight collapsibility of loess. The results show that the loess tends to be stratified and average along the depth direction with the increase of transverse correlation distance. The random field result of self-weight collapsibility considering the spatial variability of compression modulus is significantly greater than the deterministic result of layered average and the calculated value of loess code. Considering the low compression modulus dominance effect of compression modulus with positive skewed distribution of random field, the equivalent characteristic value of the compression modulus calculated by the layered average modeling for the collapsibility evaluation of typical loess strata in Xi'an area is proposed.
CDX2 as a Predictive Biomarker Involved in Immunotherapy Response Suppresses Metastasis through EMT in Colorectal Cancer
Authors: Wang Yun-shuai , Kou Yu , Zhu Ren-tao , Han Bao-wei , Li Chao-hui , Wang Huang-jian , Wu Hui-bin , Xia Tian-ming , Che Xiang-ming
Published: October 2022

Background. Studies have confirmed that Caudal Type Homeobox 2 (CDX2) plays a tumor suppressor role in colorectal cancer (CRC) and as a prognostic and predictive marker for colorectal cancer. The epithelial to mesenchymal transition (EMT) is a transdifferentiation process, providing migratory and invasive properties to cancer cells during tumor progression. However, the role of CDX2 during the activation of EMT in CRC maintains controversial. Aim. To investigate whether CDX2 is associated with EMT in CRC. Methods. Forty-six CRC patients were included in the study. Expressions of CDX2, E-cadherin, and N-cadherin in all CRC patients were detected by IHC. ROC assays were applied to detect cut-off points for IHC scores to distinguish high and low expressions of CDX2 in 46 CRC samples. The prognostic value of CDX2 was statistically analyzed. MTT, Western blot, invasion, and migration assays in vitro were employed to explore the function of CDX2. Results. We observed that high expressions of CDX2 and E-cadherin as well as low expressions of N-cadherin were significantly correlated with favorable prognosis. The levels of CDX2 protein exhibited a positive associated with E-cadherin while negative correlation with N-cadherin. Then, the low expression of CDX2 and high expression of CA199 in combination are positively related with poor prognosis. Overexpression of CDX2 reduced expression of MMP-2 and diminished cell proliferation, invasion, and migration, while knockdown CDX2 enhanced MMP-2 expression and increased cell proliferation, invasion, and migration in HCT-116 cells. CDX2 was correlated with expression of EMT markers. Overexpression of CDX2 suppressed the EMT markers indicating that CDX2 suppresses CRC cell viability, invasion, and metastasis through inhibiting EMT. Finally, we found that the expression of CDX2 was negatively associated with Th1 cells, macrophages, Th2 cells, cytotoxic cells, T cells, and T helper cells. Conclusions. These results indicated CDX2 as prognostic biomarkers involved in immunotherapy response for CRC. CDX2 loss promotes metastasis in CRC through a CDX2-dependent mechanism.
Methylation-Mediated Silencing of RBP7 Promotes Breast Cancer Progression through PPAR and PI3K/AKT Pathway
Authors: Lin Hong , Han Qizheng , Wang Junhao , Zhong Zhaoqian , Luo Haihua , Hao Yibin , Jiang Yong
Published: October 2022

Retinoid-binding protein7 (RBP7) is a member of the cellular retinol-binding protein (CRBP) family, which is involved in the pathogenesis of breast cancer. The study aims to illustrate the prognostic value and the potential regulatory mechanisms of RBP7 expression in breast cancer. Bioinformatics analysis with the TCGA and CPTAC databases revealed that the mRNA and protein expression levels of RBP7 in normal were higher compared to breast cancer tissues. Survival analysis displayed that the lower expression of RBP7, the worse the prognosis in ER-positive (ER+) breast cancer patients. Genomic analysis showed that low expression of RBP7 correlates with its promoter hypermethylation in breast cancer. Functional enrichment analysis demonstrated that downregulation of RBP7 expression may exert its biological influence on breast cancer through the PPAR pathway and the PI3K/AKT pathway. In summary, we identified RBP7 as a novel biomarker that is helpful for the prognosis of ER+ breast cancer patients. Promoter methylation of RBP7 is involved in its gene silencing in breast cancer, thus regulating the occurrence and development of ER+ breast cancer through the PPAR and PI3K/AKT pathways.
New Developments on Ostrowski Type Inequalities via
q
-Fractional Integrals Involving
s
-Convex Functions
Authors: Wang Xiaoming , Khan Khuram Ali , Ditta Allah , Nosheen Ammara , Awan Khalid Mahmood , Mabela Rostin Matendo
Published: October 2022

In the present paper,

q

-fractional integral operators are used to construct quantum analogue of Ostrowski type inequalities for the class of

s

-convex functions. The limiting cases include the nonfractional existing cases from literature. Specially, Ostrowski type inequalities for

q

-integrals and Ostrowski type inequalities for convex functions are deduced.
A Novel Oxidative Stress-Related lncRNA Signature That Predicts the Prognosis and Tumor Immune Microenvironment of Breast Cancer
Authors: Zhao Jinlai , Ma Haiyan , Feng Ruigang , Li Dan , Liu Bowen , YueYu  , Cao Xuchen , Wang Xin
Published: October 2022

Background. The association between oxidative stress and lncRNAs within the cancer-related researching field has been a controversial subject. At present, the exact function of oxidative stress as well as lncRNAs exert in breast cancer (BC) are still unclear. Therefore, the present study examined the lncRNAs oxidative stress-related in BC. Methods. Transcriptome data of BC obtained from TCGA (The Cancer Genome Atlas) database were used to generate synthetic matrices. Patients with breast cancer were randomly assigned to training, testing, or combined groups. The prognostic signature of oxidative stress was created using the selection operator Cox regression method, and the difference in prognosis between groups was examined using Kaplan-Meier curves, the accuracy of which was calculated using a receiver-operating characteristic-area through the curve (ROC-AUC) analysis with internal validation. Also, the Gene Set Enrichment Analyses (GSEA) was applied for the analysis of the risk groups. To conclude, the half-maximal inhibitory concentration (IC50) of these groups were investigated by immunoassay assay. Results. A model based on 7 lncRNAs related to oxidative stress was proposed, and the calibration plots and projected prognosis matched well. For prognosis at 5, 3, and 1 year, the area under the ROC curve (AUC) values were 0.777, 0.777, and 0.759. The functions of target genes identified by GSEA appear to be mainly expressed in metabolism, signal transduction, tumorigenesis, and also the progression. The remarkable differences in IC50 and gene expression between risk groups in this study provide a deep insight for further systemic treatment. Higher macrophage scores were acquired in the high-risk group, of which patients showed more response to conventional chemotherapy drugs, such as AKT inhibitor VIII and Lapatinib, as well as immunotherapy strategies including anti-CD80, TNF SF4, CD276, and NRP1. Conclusion. The prognosis of breast cancer can be independently predicted by the markers, which sheds light on further research of the specific role of lncRNAs which are oxidative stress-related and clinical treatment of breast cancer.
Prediction of Major Adverse Cardiovascular Events in Patients With Hypertrophic Cardiomyopathy Using Proteomics Profiling
Authors: Shimada Yuichi J. , Raita Yoshihiko , Liang Lusha W. , Maurer Mathew S. , Hasegawa Kohei , Fifer Michael A. , Reilly Muredach P.
Published: October 2022

Background:

Hypertrophic cardiomyopathy often causes major adverse cardiovascular events (MACE), for example, arrhythmias, stroke, heart failure, and sudden cardiac death. Currently, there are no models available to predict MACE. Furthermore, it remains unclear which signaling pathways mediate MACE. Therefore, we aimed to prospectively determine protein biomarkers that predict MACE in hypertrophic cardiomyopathy and to identify signaling pathways differentially regulated in patients who subsequently develop MACE.

Methods:

In this multi-centre prospective cohort study of patients with hypertrophic cardiomyopathy, we conducted plasma proteomics profiling of 4979 proteins upon enrollment. We developed a proteomics-based model to predict MACE using data from one institution (training set). We tested the predictive ability in independent samples from the other institution (test set) and performed time-to-event analysis. Additionally, we executed pathway analysis of predictive proteins using a false discovery rate threshold of <0.001.

Results:

The study included 245 patients (n=174 in the training set and n=71 in the test set). Using the proteomics-based model to predict MACE derived from the training set, the area under the receiver-operating-characteristic curve was 0.81 (95% CI, 0.68–0.93) in the test set. In the test set, the high-risk group determined by the proteomics-based predictive model had a significantly higher rate of developing MACE (hazard ratio, 13.6 [95% CI, 1.7–107];
P
=0.01). The
Ras
-MAPK (mitogen-activated protein kinase) pathway was upregulated in patients who subsequently developed MACE (false discovery rate<1.0×10
-7
). Pathways involved in inflammation and fibrosis—for example, the TGF (transforming growth factor)-β pathway—were also upregulated.

Conclusions:

This study serves as the first to demonstrate the ability of proteomics profiling to predict MACE in hypertrophic cardiomyopathy, exhibiting both novel (eg,
Ras
-MAPK) and known (eg, TGF-β) pathways differentially regulated in patients who subsequently experience MACE.
Machine Learning From Quantitative Coronary Computed Tomography Angiography Predicts Fractional Flow Reserve–Defined Ischemia and Impaired Myocardial Blood Flow
Authors: Lin Andrew , van Diemen Pepijn A. , Motwani Manish , McElhinney Priscilla , Otaki Yuka , Han Donghee , Kwan Alan , Tzolos Evangelos , Klein Eyal , Kuronuma Keiichiro , Grodecki Kajetan , Shou Benjamin , Rios Richard , Manral Nipun , Cadet Sebastien , Danad Ibrahim , Driessen Roel S. , Berman Daniel S. , Nørgaard Bjarne L. , Slomka Piotr J. , Knaapen Paul , Dey Damini
Published: October 2022

Background:

A pathophysiological interplay exists between plaque morphology and coronary physiology. Machine learning (ML) is increasingly being applied to coronary computed tomography angiography (CCTA) for cardiovascular risk stratification. We sought to assess the performance of a ML score integrating CCTA-based quantitative plaque features for predicting vessel-specific ischemia by invasive fractional flow reserve (FFR) and impaired myocardial blood flow (MBF) by positron emission tomography (PET).

Methods:

This post-hoc analysis of the PACIFIC trial (Prospective Comparison of Cardiac Positron Emission Tomography/Computed Tomography [CT]‚ Single Photon Emission Computed Tomography/CT Perfusion Imaging and CT Coronary Angiography with Invasive Coronary Angiography) included 208 patients with suspected coronary artery disease who prospectively underwent CCTA‚ [
15
O]H
2
O PET, and invasive FFR. Plaque quantification from CCTA was performed using semiautomated software. An ML algorithm trained on the prospective NXT trial (484 vessels) was used to develop a ML score for the prediction of ischemia (FFR≤0.80), which was then evaluated in 581 vessels from the PACIFIC trial. Thereafter, the ML score was applied for predicting impaired hyperemic MBF (≤2.30 mL/min per g) from corresponding PET scans. The performance of the ML score was compared with CCTA reads and noninvasive FFR derived from CCTA (FFR
CT
).

Results:

One hundred thirty-nine (23.9%) vessels had FFR-defined ischemia, and 195 (33.6%) vessels had impaired hyperemic MBF. For the prediction of FFR-defined ischemia, the ML score yielded an area under the receiver-operating characteristic curve of 0.92, which was significantly higher than that of visual stenosis grade (0.84;
P
<0.001) and comparable with that of FFR
CT
(0.93;
P
=0.34). Quantitative percent diameter stenosis and low-density noncalcified plaque volume had the greatest ML feature importance for predicting FFR-defined ischemia. When applied for impaired MBF prediction, the ML score exhibited an area under the receiver-operating characteristic curve of 0.80; significantly higher than visual stenosis grade (area under the receiver-operating characteristic curve 0.74;
P
=0.02) and comparable with FFR
CT
(area under the receiver-operating characteristic curve 0.77;
P
=0.16).

Conclusions:

An externally validated ML score integrating CCTA-based quantitative plaque features accurately predicts FFR-defined ischemia and impaired MBF by PET, performing superiorly to standard CCTA stenosis evaluation and comparably to FFR
CT
.
Gut-Immune-Kidney Axis: Influence of Dietary Protein in Salt-Sensitive Hypertension
Authors: Mattson David L. , Dasinger John Henry , Abais-Battad Justine M.
Published: October 2022

Humans with salt-sensitive hypertension demonstrate increased morbidity, increased mortality, and renal end-organ damage when compared with normotensive subjects or those with salt-resistant hypertension. Substantial evidence from humans and animals has also demonstrated the role of dietary components other than salt to modulate hypertension. Evidence presented in this review provides support for the view that immunity and inflammation serve to amplify the development of salt-sensitive hypertension and leads to malignant disease accompanied by end-organ damage. Interestingly, salt-sensitive disease is modulated by changes in dietary protein intake, which also influences immune mechanisms. Together, the evidence presented in this review from animal and human studies indicates that changes in dietary protein source have profound effects on the gut microbiota, microbiota-derived metabolites, DNA methylation, gene expression, immune cell activation, the production of cytokines and other factors, and the development of salt-sensitive hypertension and related disease phenotypes.