bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel pseudo-labeling framework based on matrix integration for adverse drug reaction prediction
Authors: Chen Junheng , Han Fangfang , He Mingxiu , Shi Yiyang , Cai Yongming 
Published: January 2024

Abstract

Background
Adverse drug reactions (ADRs) are one of the global public health events that seriously endanger human life and cause high economic burdens. Therefore, predicting the possibility of their occurrence and taking early and effective response measures are of great significance. The construction of a correlation matrix between drugs and their adverse reactions, followed by effective correlation data mining, is one of the current strategies to predict ADRs using accessible public data. Since the number of known ADRs in real-world data is far less than the number of their unknown counterparts, the drug-ADR association matrix is very sparse, which greatly affects the classification performance of machine learning methods.
Results
To effectively solve the problem of sparsity, we propose a novel pseudo-labeled data augmentation framework that mines potential unknown drug-ADR pairs by integrating multiple weighted matrix factorization (MF) models and treating them as pseudo-labeled drug-ADR pairs. Pseudo-labeled data is added to the training set and the MF model is fine-tuned to improve the classification performance.
Conclusions
This paper reproduces the baselines under the same experimental conditions to evaluate the performance of the proposed method on sparse data from the Side Effect Resource (SIDER) database. Experimental results showed that our method outperformed other baselines in the Area Under Precision-Recall (AUPR) and F1 scores, and still maintained the best performance in sparser scenarios. Furthermore, we conducted a case study and the results showed that our proposed framework efficiently predicted ADRs in the real world.
The prognostic impact of peripheral blood eosinophil counts in metastatic renal cell carcinoma patients treated with nivolumab
Authors: Yoshimura Akihiro , Nagahara Akira , Ishizuya Yu , Yamamoto Yoshiyuki , Hatano Koji , Kawashima Atsunari , Nakai Yasutomo , Nakayama Masashi , Nishimura Kazuo , Nonomura Norio , Kato Taigo 
Published: January 2024

Abstract

Background Although immune checkpoint inhibitors (ICIs) have gained approval for metastatic renal cell carcinoma (mRCC), the response rate is still limited. Therefore, it is urgent to explore novel and concise markers of responses to ICIs that can help assess clinical benefits. Recently, it has been noted that peripheral blood eosinophil counts is an independent factor correlated with clinical outcome of ICIs in some types of cancer. Methods We investigated peripheral blood absolute eosinophil counts (AECs) at baseline and 4 weeks after the initiation of nivolumab for mRCC patients between February 2016 to May 2022. In addition, we examined clinicopathological features including irAEs and analyzed the correlation between AECs and clinical efficacy of nivolumab. Results Of all patients, 22 patients (27.0%) developed irAEs. The median AECs in patients with irAEs was significantly higher at baseline and 4 weeks after the treatment compared to those without irAEs (p < 0.001 and p = 0.001, respectively). With the cutoff value of AECs of 329 cells/µL at 4 weeks after the treatment for prediction of irAEs, high-AECs groups had significantly higher number of responders compared with that in low-AECs group (p < 0.001). Accordingly, the progression-free survival (PFS) and overall survival (OS) were significantly better in patients with high-AECs group than those in low-AECs group (p = 0.03 and p = 0.009, respectively). Conclusion High AECs at 4 weeks after the treatment serve as the prominent surrogate marker associated with the incidence of irAEs and better clinical outcome in mRCC patients receiving nivolumab.
A computational investigation on the adsorption behavior of bromoacetone on B 36 borophene nanosheet
Authors: Taier Meriem , Allal Hamza , Bousba Salim , Bouhadiouche Fathi , Maza Soumeya , Damous Maamar , Boussadia Ahlem 
Published: January 2024

Abstract
Density functional theory (DFT) methods are employed to investigate the capability of B36 borophene nanosheets as sensors for detecting the bromoacetone (BCT) molecule. An evaluation of the structural and electronic properties of both BCT and B36 borophene is conducted. Subsequently, through computed metrics such as adsorption energy, charge density difference (CDD), and density of states (DOS), the interaction between B36 and the BCT molecule is examined via dispersion-corrected density functional theory (DFT). Employing the reduced density gradient (RDG-NCI) approach for the analysis of non-covalent interactions, we further explored the nature of these interactions. The obtained results illustrate that B36 borophene nanosheets serve as effective sensors for the BCT molecule, showcasing their ability to adsorb up to five BCT molecules through an exothermic process. BCT molecules chemiadsorb onto B36 borophene by forming B‒O covalent bonds, engaging the oxygen atom of the carbonyl group in BCT with the edge boron atoms of B36 borophene. Additionally, BCT molecules physio-adsorb on both the concave and convex sides of B36 borophene, facilitated by van der Waals interactions. Ab-initio molecular dynamics (AIMD) simulations confirm the thermal stability of the BCT@B36 concave and convex complexes at both 300 K and 400 K.
Action recognition algorithm based on skeleton graph with multiple features and improved adjacency matrix
Authors: Zhang Shanqing , Jiao Shuheng , Chen Yujie , Xu Jiayi 
Published: January 2024

Abstract
Although graph convolutional networks have achieved good performances in skeleton graph-based action recognition, there are still some problems such as: incomplete utilization of skeleton graph features the adjacency matrix without logical adjacency information between nodes. The skeleton graph features and the graph convolutional operators demand further improvement. In this paper, we propose a human action recognition algorithm based on multiple features of the skeleton graph. Furthermore, an improved adjacency matrix make full use of the multiple skeleton graph features. These features include local differential features of the skeleton graph, multi-scale edge features and motion features of the original skeleton graph, in addition to the nodal features and nodal motion features. Extensive results are conducted on four standard datasets (NTU RGB-D 60, NTU RGB-D 120, Kinetics, and Northwestern-UCLA). The experimental results show that the proposed algorithm outperforms the SOTA action recognition algorithms.
Causal association between immune cell traits and Ankylosing Spondylitis: A bidirectional Mendelian randomization study
Authors: Zhang Xuhong , Zhou Lamei , Qian Xian 
Published: January 2024

Abstract
Background: Previous studies have observed a significant association between immune cell traits and Ankylosing spondylitis (AS); however, a causal relationship has not been established. Therefore, we conducted this bidirectional Mendelian randomization study to comprehensively evaluate the intricate interactions between 731 immune cell traitsand AS, aiming to uncover potential causal relationships while enhancing our understanding of disease development.
Methods: We retrieved extensive genome-wide association study (GWAS) data from two reputable sources, the IEU open GWAS database and the FinnGen studies, renowned for their extensive genetic information. We performed a bidirectional Mendelian randomization study to investigate the causal relationship between 731 immune cell traits and Ankylosing Spondylitis (AS). Our analysis utilized the Inverse Variance Weighted (IVW) method, along with MR-Egger, Weighted Median, and Weighted Mode. We assessed associations between 731 immune cell traits and AS using odds ratios (OR) and 95% confidence intervals (CI). Finally, we performed tests for horizontal pleiotropy, heterogeneity, and conducted a leave-one-out sensitivity analysis to validate our results.
Results: Our research has established that 10 distinct immune cell types significantly contribute to the development of Ankylosing Spondylitis (AS). We identified 3 types of monocytes, 1 type of T cell, 1 type of B cell, and 1 type of granulocyte as risk factors for AS. In contrast, a different group of immune cells, including 1 type of monocyte, 2 types of T cells, and 1 type of B cell, appears to offer protection against the disease. Concerning the onset of AS, its impact on immune traits is evident in the varied expressions across 41 T cell subgroups: 16 subtypes show high expression, while 25 demonstrate low expression. Similarly, in B cells, 3 subtypes are highly expressed, and 4 subtypes are lowly expressed. Likewise, variations in expression were observed in lymphocytes and monocytes, with 3 types of each showing high and low expression, respectively. Moreover, our study reveals a bidirectional causal relationship between the expression of CX3CR1 on CD14+ CD16- monocytes and on monocytes generally, and the occurrence of AS.
Conclusion: The goal of this research is dedicated to exploring the bidirectional causal relationship between immune cells traits and Ankylosing Spondylitis (AS). It aims to not only offer new avenues for unraveling the biological mechanisms of AS but also to guide clinical research towards novel investigative directions and to provide fresh clues for the development of new therapeutic approaches.
Concept and initial realization of PHYSER — A PHYsics-based framework for SpacebornE GNSS-R soil moisture retrieval with accurate soil reflectivity
Authors: Yang Ting , Guo Zhizhou , Lu Feng , Wan Wei 
Published: January 2024

Abstract

Global soil moisture (SM) observation using the spaceborne Global Navigation Satellite Reflectometry (GNSS-R) is becoming an effective supplement and enhancement to traditional microwave remote sensing observations. The state-of-the-art SM retrieval frameworks for spaceborne GNSS-R are based on empirical or semi-empirical modeling, which relies on reference SM data from other sources (e.g., microwave radiometer or in situ SM products) to eliminate the effects of land surface random errors (e.g., surface roughness and vegetation). This study defines a generic framework for PHYsics-based SpacebornE GNSS-R SM retrieval, namely PHYSER, and proposes initial strategies to realize the framework. The framework concept devotes to deriving accurate soil reflectivity and retrieving SM by estimating soil permittivity from Fresnel reflection coefficients, thus wholly independent of external SM products. It assumes that GNSS-R surface reflectivity and its related soil reflectivity are affected by observing system errors and land surface random errors. The framework is initially realized by deriving accurate soil reflectivity from empirical corrections to avoid the grand challenge of building a forward scattering model under complex land surface conditions. Accurate soil reflectivity is derived through two steps: 1) Surface Reflectivity CALibrating (SuR-CAL), aiming to calibrate the system errors using the reflectivity of inland water bodies, and 2) Soil Reflectivity CORrecting (SoR-COR), aiming to correct the random errors mainly from surface roughness and vegetation using the zeroth-order radiative transfer (τ–ω) model. The framework is validated using one-year data from BuFeng-1 A/B (BF-1) twin satellites. The findings and conclusions mainly include: 1) PHYSER reveals that independent spaceborne GNSS-R SM retrieval without reference SM products is achievable through deriving accurate soil reflectivity. 2) Land surface random errors play a more significant role in influencing soil reflectivity than system errors. The SuR-CAL and SoR-COR steps improve the correlation coefficient (R) between BF-1 reflectivity and the SMAP SM up to ~ 7% and ~ 36%, respectively. 3) The BF-1 SM estimates agree well with the SMAP SM and ERA5 SM (ubRMSD = 0.067 m3m− 3 and MAE = 0.073 m3m− 3 against SMAP; ubRMSD = 0.079 m3m− 3 and MAE = 0.088 m3m− 3 against ERA5). The BF-1 SM also agrees well with the in-situ measurements with mean ubRMSE = 0.055 m3m− 3 and MAE = 0.066 m3m− 3. The proposed framework provides a promising physics-based concept to independently retrieve SM for the GNSS-R community, which is expected to considerably support the in-orbit and next-generation GNSS-R missions to promote operational SM retrieval and applications.
A new combined prognostic model involving SLC44A4 improves the predictive ability for colorectal cancer patients
Authors: Li Pan-Yuan , Cheng Xiao-Qing , Wu Yan-Chuang , Zhu Jia , Sheng Cai-Xia , Jiang Zhi-Nong , Hu Xiao-tong , Fu Guo-Xiang 
Published: January 2024

Abstract
Prognosis prediction is crucial for improving therapeutic strategies and achieving better clinical outcomes in patients with colorectal cancer (CRC). Solute carrier family 44 member 4 (SLC44A4) is a prognostic marker in head and neck cancer, renal cancer, and urothelial cancer. However, its prognostic value in CRC has not been evaluated. To determine the prognostic significance of SLC44A4 in CRC, we evaluated this gene using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Next, we used tissue-microarray-based immunohistochemistry to assess the expression level of SLC44A4 protein in colorectal cancer tissues and analyzed the prognostic significance of SLC44A4. The online databases revealed that SLC44A4 was downregulated in CRC, and high expression of SLC44A4 was related to better overall survival (OS). Then, univariate and multivariate analysis of tissue-microarray-based immunohistochemistry data showed that SLC44A4 was an independent favorable prognostic factor for OS. Furthermore, the new prognostic model, including pM classification, absence or presence of relapse, and SLC44A4 expression level, had better predictive ability than the model without SLC44A4 expression level. So SLC44A4 gene could be a biomarker to predict the prognosis of CRC patients. In addition, this new prognostic model we proposed can improve the predictive ability to evaluate the prognosis and clinical outcomes of CRC patients.
Pathogenesis Analysis of Idiopathic Macular Hole Based on Proteomic Approach
Authors: Ding Jingjing , Liu Siyuan , Wang Xue , Cao Fan , Tao Liming , Bao Ning , Liu Dongwei 
Published: January 2024

Abstract
Background: Idiopathic macular hole (IMH) severely impairs patients' vision and quality of life, and its pathogenesis is still unclear. We applied a proteomic approach to analyze the pathogenesis of IMH to promote the diagnosis and treatment of IMH.
Methods: We performed LC-MS/MS analysis of vitreous bodies from three patients with IMH and three control patients. Vitreous proteins were identified and subjected to quantitative analysis using MaxQuant 1.6.14 software. Hierarchical cluster analysis was performed using Java Treeview and Cluster 3.0 software. Motifs were analyzed using MEME. Fisher's exact test was used for the enrichment analysis.
Results: A total of 1263 proteins were identified in the IMH and control groups using LC-MS/MS for vitreous samples. Among these, 122 proteins were uniquely present in the IMH group, while 292 proteins were present only in the control group. When comparing the two groups, 18 significantly different proteins were found in the IMH group, with 4 proteins being upregulated and 14 proteins being downregulated. The expression of proteins involved in lipoprotein metabolism, extracellular matrix (ECM), cell adhesion and migration, the complement and coagulation cascade pathway, fibrosis，and the epithelial-mesenchymal transition (EMT) pathway is associated with IMH.
Conclusion: A proteomic approach revealed that the pathways of the complement and coagulation cascade, cell adhesion and migration, ECM remodeling, EMT, fibrosis, and lipoprotein metabolism may be involved in the pathogenesis of IMH.
Identification of potential biomarkers in myelodysplastic syndromes by weighted gene co-expression network analysis
Authors: Li Kongfei , Wang Yuxiao , Lu Ying , Pei Renzhi 
Published: January 2024

Abstract
MDS is characterized by great heterogeneity in clinical manifestations, cytogenetic and molecular biological manifestations, therapeutic options and efficacy. The lack of specific molecular mechanism discovery and effective targeted therapy is a well-known problem of MDS. Therefore, finding critical target molecules and therapeutic targets is at the forefront of current research. Using data from the Gene Expression Omnibus (GEO), we performed a thorough investigation of the mRNA expression profile of MDS in this work. Three mRNA microarray datasets (GSE58831, GSE4619, GSE19429) with MDS and control samples were used to creation of co-expression networks by using weighted correlation network analysis (WGCNA). A total of 15 key apoptosis-related differentially expressed genes (ARDEGs) genes were obtained by performing weighted gene co-expression network analysis (WGCNA) analysis. The GO analyses indicated that key genes are mainly enriched in B cell activation, beta-catenin-TCF complex, and DNA-binding transcription repressor activity. The GSEA and GSVA suggested that hypoxia, TGF-β signaling, and IL2 STAT5 signaling are crucial in the gene changes of MDS. Furthermore, A total of 5 differentially expressed genes (VPREB3, LEF1-AS1, PAX5, CD79A, LEF1) were related to the survival of MDS patients. Our findings may provide novel insight into the molecular characteristics of MDS through integrative analysis of GEO data by using weighted gene co-expression network analysis, and suggest potential biomarkers and therapeutic targets for MDS.
The Importance of Evaluation of Hemoglobin and Hematocrit Values in 0-2 Age Group Patients with Head Trauma
Authors: YUCEER Ömer 
Published: January 2024

Abstract
Objective
The aim of this study was to investigate the incidence of moderate and severe head trauma in patients aged between 0–2 years who admitted to the emergency department and were hospitalized in the service or intensive care unit, the type of trauma, the age group in which the trauma occurred, the most common localization of the trauma on the head, the severity of the trauma and the rate of decrease in hemoglobin (HGB) and hematocrit (HCT), and to understand the relationship between the rate of decrease in HGB and HCT and the severity of the trauma in this age group who cannot be fully cooperative in anamnesis and examination.
Method
In this study, patients, who were admitted to the emergency department of Niğde Ömer Halisdemir Training and Research Hospital between 2019 and 2022, with a Glasgow Coma Scale (GCS) of 13 and below and who were hospitalized in the service or intensive care unit, were evaluated. Among these hospitalized patients, 180 patients who underwent brain computed tomography (CT) before being hospitalized in the emergency department, whose clinical findings were determined according to PECARN rules, whose hemogram blood was taken and who were found to have no hemolysis were retrospectively analyzed.
Discussion
In the study, 97 male and 83 female patients were evaluated. The majority of the cases were falls with 124 (68.8%) cases. (Head traumas were evaluated according to the Pediatric Emergency Care Applied Research Network (PECARN) estimation rules and falls from a height of less than 3 feet (90cm) were considered as falls, while falls from a higher height were considered as falls from a height). It was observed that most of the trauma-related lesions occurred in the temporal region in 62 cases (34.44%). The most common lesion detected was skull bone fractures without parenchymal hemorrhage in 112 cases (62.2%). It was determined that 167 (92.8%) and 13 (7.2%) patients were hospitalized in the service and intensive care unit, respectively. Patients were classified according to their ages as between 0–1 years and between 1–2 years. There were 103 cases (57.22%) aged between 0–1 years and 77 cases (42.78%) aged between 1–2 years.
Conclusion
At the end of this study, it was determined that as the severity of trauma increased, the decrease in HGB and HCT values increased.
Feasibility and Acceptability Evaluation of a Digital Therapeutic Program for Improving Cancer Prevention: A Pre-Post Interventional Study
Authors: Zhang Xianwei , Zhang Sheng , Zhang Haiyan , Xiong Ziyou , Li Yi , Li Lufeng , Pi Xitian , Liu Hongying 
Published: January 2024

Abstract
Previous studies have proved that healthy behaviors hinder the onset and progression of tumors. Digital therapeutics (DTx), playing pivotal role in facilitating behavioral adjustments through educational interventions, lifestyle support, and symptom monitoring, contributes to the goal of tumor prevention. Our study aimed to assess the feasibility of using the AITI app, employing the DTx approach for cancer prevention and examining its impact on lifestyle modifications and SF-36. In a 4-week trial with 57 participants engaging actively, we found both the average daily activity rate and 4-week retention rate at 35 (61.4%). The USE Questionnaire scores (validity, ease of use, acquisition, and satisfaction) ranged from 68.06 to 83.10, indicating AITI's user-friendliness. Participants noted enhanced awareness and positive habit changes, particularly in exercise and diet (p＜0.0001), suggesting the DTx approach's potential for advancing cancer prevention. The study highlights the feasibility and acceptability of this lifestyle intervention using DTx via AITI, demonstrating effectiveness in altering behaviors. However, larger and longer studies are needed to comprehensively assess its impact.
Qualitative Descriptive Study on the Use of Instructional Videos by Undergraduate Students
Authors: McFerren Belinda P. 
Published: January 2024

Abstract

This qualitative descriptive study explored the use of instructional videos by undergraduate students at community colleges and universities in the southeastern United States. The technology acceptance model (TAM) was used as the framework for this study. According to the TAM, the use of technology is influenced by perceptions related to the ease of use, enjoyment, and usefulness of the technology. Therefore, the research questions were, “How do undergraduate students describe their use of instructional videos?” and “How do undergraduate students describe their perceptions of the ease of use, usefulness, and enjoyment of instructional videos?” The sample included 20 research participants. Eleven participants chose to be interviewed individually, and nine participants chose to attend one of three focus groups. Reflexive thematic analysis identified seven themes: use, usefulness, enjoyment, ease of use, length of video, video characteristics, and student factors. Usefulness, the most important determinant for use, is increased when the videos contain the specific information that is needed for success in the class. Students also consider the length, and occasionally enjoyment, when deciding whether to watch videos and how they watch videos. Students employ a variety of strategies, such as speeding up the video, to obtain the information needed using the least amount of time. The use of instructional videos is also influenced by certain video characteristics and student factors. Although ease of use does not influence intention to use, actual usage can be impacted by challenges related to ease of use. The findings from this study increase understanding related to the use of instructional videos and can be applied to increase the likelihood that students will use, and therefore benefit, from instructional videos.