bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mapping the evolution of neurofeedback research: a bibliometric analysis of trends and future directions
Authors: Wider Walton , Mutang Jasmine Adela , Chua Bee Seok , Pang Nicholas Tze Ping , Jiang Leilei , Fauzi Muhammad Ashraf , Udang Lester Naces 
Published: May 2024

IntroductionThis study conducts a bibliometric analysis on neurofeedback research to assess its current state and potential future developments.MethodsIt examined 3,626 journal articles from the Web of Science (WoS) using co-citation and co-word methods.ResultsThe co-citation analysis identified three major clusters: “Real-Time fMRI Neurofeedback and Self-Regulation of Brain Activity,” “EEG Neurofeedback and Cognitive Performance Enhancement,” and “Treatment of ADHD Using Neurofeedback.” The co-word analysis highlighted four key clusters: “Neurofeedback in Mental Health Research,” “Brain-Computer Interfaces for Stroke Rehabilitation,” “Neurofeedback for ADHD in Youth,” and “Neural Mechanisms of Emotion and Self-Regulation with Advanced Neuroimaging.DiscussionThis in-depth bibliometric study significantly enhances our understanding of the dynamic field of neurofeedback, indicating its potential in treating ADHD and improving performance. It offers non-invasive, ethical alternatives to conventional psychopharmacology and aligns with the trend toward personalized medicine, suggesting specialized solutions for mental health and rehabilitation as a growing focus in medical practice.
An analysis of the influencing factors of false negative autoantibodies in patients with non-small cell lung cancer
Authors: Wang Ailin , Hao Ying , Huo Yunlong , Xu Xiaoman , Zhang Yi 
Published: May 2024

ObjectivesTo analyze the clinical significance of seven autoantibodies (P53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGE, and CAGE) in patients with non-small cell lung cancer (NSCLC) and the factors that influence false-negative results.MethodsSeven autoantibodies were measured in the serum of 502 patients with non-small cell lung cancer (NSCLC) using ELISA, and their correlations with age, sex, smoking history, pathological type, clinical stage, and PD-L1 gene expression were analyzed. The clinicopathological data of the false-negative and positive groups for the seven autoantibodies were compared to determine the influencing factors.ResultsP53 antibody expression level was correlated with lobulation sign, PGP9.5 antibody expression level with sex and vascular convergence; SOX2 antibody expression level with pathological type, clinical stage, and enlarged lymph nodes; and MAGE antibody expression level with the pathological type (P&lt;0.05). False-negative autoantibodies are prone to occur in lung cancer patients with ground-glass nodules, no enlarged lymph nodes, no vascular convergence, and PD-L1 gene expression &lt;1% (P &lt;0.05).ConclusionDetection of seven autoantibodies was clinically significant in patients with NSCLC. However, poor sensitivity should be considered in clinical diagnoses to prevent missed diagnoses.
MicroRNA-875-5p inhibits the growth and metastasis of cervical cancer cells by promoting autophagy and apoptosis and inhibiting the epithelial-mesenchymal transition
Authors: Liang Yingxiu , Li Chunyang , Hou Xiaohong , Lin Yiguang , Cheng Jing 
Published: May 2024

IntroductionMicroRNA-875-5p (miR-875-5p) is a cancer-related microRNA. It has been demonstrated that miR−875−5p participates in the development of various types of cancer such as hepatocellular carcinoma, gastric carcinoma, prostate and bladder cancer. Previous research suggested that miR-875 is implicated in the development of cervical cancer cells. However, the exact role and function of miR−875−5p in cervical cancer remain unexplored. It is important to examine the role and function of miR-875-5p and the associated signaling pathway, as the findings may have diagnostic and therapeutic significance. Thus, in this study, we investigated the effect of miR-875-5p on the growth and metastasis of cervical cancer cells and the possible underlying mechanisms.MethodsReverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression of miR-875-5p in cervical cancer cells and normal cervical epithelium. After overexpression or co-expression of miR-875-5p in cells, the changes in cell function were analyzed. Western blot was used to detect the expression changes of epithelial-mesenchymal transition (EMT) -related proteins and autophagy-related proteins.ResultsFunctional studies demonstrated that miR-875-5p overexpression significantly inhibited the proliferation, migration, invasion, and EMT, and promotes apoptosis and autophagy of cervical cancer cells., while miR-875-5p knockdown promoted the proliferation, migration, invasion, and EMT, and inhibited apoptosis and autophagy cervical cancer cells. Furthermore, Western blot results showed that overexpression of miR-875-5p downregulated the expressions of N-cadherin, Snail, Vimentin and microtubule-associated protein 1 light chain 3B I (LC3B I). Conversely, miR-875-5p upregulated the expression of E-cadherin.ConclusionIn conclusion, our findings suggest that miR-875-5p functions as a tumor inhibitor suppressing the growth and metastasis of cervical cancer. Overexpression of miR-875-5p inhibits malignant behavior and promotes autophagy and apoptosis in cervical cancer cells. These findings advance our understanding of the role and function of miR-875-5p in cervical cancer and could facilitate the development of early genetic markers or biomarkers and therapeutic targets for cervical cancer.
The updated surgical steps of gasless transaxillary endoscopic thyroidectomy with neck level and region orientation for thyroid cancer
Authors: Zhou Yuqiu , Shui Chunyan , Ma Linjie , Cai Yongcong , Sun Ronghao , Jiang Jian , Zeng Dingfen , Wang Xu , Xu Xiaoli , Huang Pei , Li Chao 
Published: May 2024

IntroductionWe previously made a detailed expansion to the gasless transaxillary endoscopic thyroidectomy(GTET) procedure described in the previous literatures. In this study, we optimized the procedure focused on the limitation of the approach in terms of trauma and lymph node dissection and made a comparison with the early procedure.Materials and methodsThis paper gave a detailed description of the updated procedure and prospectively collected data about patients with papillary thyroid carcinoma(PTC) performed by the two procedures from December 2020 to April 2023. The differences in surgical outcome, surgical trauma and parathyroid gland(PG) function protection were analyzed.ResultsOf the 302 patients, 184 underwent with early procedure(EP), and 118 underwent with updated procedure(UP). The surgical outcomes of operative time, time of thyroidectomy and central neck dissection, blood loss, drainage and postoperative hospital stay were shorter in UP than that of the EP. The mean number of lymph nodes retrieved and weight of dissection lymphatic tissue in the UP were significantly more than that in EP without increasing the mean number of metastatic lymph nodes. Postoperative complications did not differ between the two procedures. The UP had more advantages in the identification and preservation of the superior parathyroid gland, however, it did not improve the preservation in situ of the inferior parathyroid gland. The visual analog scale score for pain and the changes among inflammation factors was lower in the UP.ConclusionThe UP of GTET could perform safely and efficiently while reducing surgical trauma in selected patients.
Incidence and risk factors for bone metastases at presentation in solid tumors
Authors: Knapp Brendan J. , Cittolin-Santos Giordano F. , Flanagan Mary E. , Grandhi Nikhil , Gao Feng , Samson Pamela P. , Govindan Ramaswamy , Morgensztern Daniel 
Published: May 2024

IntroductionBone metastases are associated with increased morbidity and decreased quality of life in patients with solid tumors. Identifying patients at increased risk of bone metastases at diagnosis could lead to earlier interventions. We sought to retrospectively identify the incidence and predictive factors for bone metastases at initial diagnosis in a large population-based dataset.MethodsThe Surveillance, Epidemiology, and End Results (SEER) database was used to identify patients 18 years-old or older diagnosed with solid cancers from 2010 to 2019. Patients with hematologic malignancies and primary tumors of the bone were excluded. We calculated the incidence and predictive factors for bone metastases according to demographic and tumor characteristics.ResultsAmong 1,132,154 patients identified, 1,075,070 (95.0%) had known bone metastasis status and were eligible for the study. Bone metastases were detected in 55,903 patients (5.2% of those with known bone metastases status). Among patients with bone metastases, the most common primary tumors arose from lung (44.4%), prostate (19.3%), breast (12.3%), kidney (4.0%), and colon (2.2%). Bone metastases at presentation were most common in small cell lung cancer (25.2%), non-small cell lung cancer (18.0%), and esophageal adenocarcinoma (9.4%). In addition to stage classification, predictors for bone metastases included Gleason score (OR 95.7 (95% CI 73.1 – 125.4) for Grade Group 5 vs 1 and OR 42.6 (95% CI 32.3 – 55.9) for Group 4 vs 1) and PSA (OR 14.2 (95% CI 12.6 – 16.0) for PSA &gt; 97 vs 0 – 9.9) for prostate cancer, HER2 and hormonal receptor (HR) status (OR 2.2 (95% CI 1.9 – 2.6) for HR+/HER2+ vs HR-/HER2-) for breast cancer, histology (OR 2.5 (95% CI 2.3 – 2.6) for adenocarcinoma vs squamous) for lung cancer, and rectal primary (OR 1.2 (95% 1.1 – 1.4) vs colon primary) and liver metastases (OR 8.6 (95% CI 7.3 – 10.0) vs no liver metastases) for colorectal tumors.ConclusionsBone metastases at presentation are commonly seen in solid tumors, particularly lung, prostate, breast, and kidney cancers. Clinical and pathologic factors are associated with a significantly increased risk for bone metastases.
A comprehensive bibliometric analysis (2000–2022) on the mapping of knowledge regarding immunotherapeutic treatments for advanced, recurrent, or metastatic cervical cancer
Authors: Duan Yuanqiong , Yang Lin , Wang Wenxiang , Zhang Peixuan , Fu Kaiyu , Li Wen , Yin Rutie 
Published: May 2024

BackgroundDespite extensive literature on therapeutic strategies for cervical cancer, a bibliometric analysis specifically focused on immunotherapy for advanced, recurrent, or metastatic (A/R/M) cervical malignancies remains unexplored. This study aims to address this gap by presenting a comprehensive overview that includes general characteristics, research focal points, the trajectory of evolution, and current emerging trends in this under-researched area.MethodsA systematic search was conducted using the Web of Science Core Collection (WOSCC) to identify articles related to A/R/M cervical cancer published between 2000 and 2022. Citespace and VOS viewer were the primary tools used to identify research focal points, intriguing future patterns, and to evaluate contributions and co-occurrences among authors, institutions, countries, and journals.ResultsA total of 1,001 original articles were identified, involving 6,387 authors from 66 countries and 1,474 institutions, and published across 366 academic journals. The United States contributed most significantly. The most productive researcher was Van der Burg SH from Leiden University Medical Center. The International Journal of Cancer and Cancer Research were identified as the most productive and influential journals, respectively. Analysis of co-citation clusters highlighted 25 clusters, primarily focusing on potential predictive biomarkers, dendritic cell-based tumor vaccines, therapeutic HPV vaccinations, peptide-based cancer vaccines, tumor immune microenvironments, and adoptive cell transfer (ACT). The latest significant trends in A/R/M cervical cancer immunotherapy research included ACT, CAR-T, and immune checkpoint inhibitors (ICIs), as revealed by keyword and reference burst detection.ConclusionThis pioneering study provides a detailed landscape of immunotherapy research in A/R/M cervical cancer. It underscores the importance of global collaboration, enriches our understanding of the immunology of A/R/M cervical cancer, expands on potential beneficiaries of immunotherapy, and explores clinical applications of various therapies, including therapeutic vaccines, adoptive cell transfer, and ICIs, particularly in combination with established treatments such as chemotherapy, radiotherapy, and targeted therapy.
Knowledge mapping of graph neural networks for drug discovery: a bibliometric and visualized analysis
Authors: Yao Rufan , Shen Zhenhua , Xu Xinyi , Ling Guixia , Xiang Rongwu , Song Tingyan , Zhai Fei , Zhai Yuxuan 
Published: May 2024

IntroductionIn recent years, graph neural network has been extensively applied to drug discovery research. Although researchers have made significant progress in this field, there is less research on bibliometrics. The purpose of this study is to conduct a comprehensive bibliometric analysis of graph neural network applications in drug discovery in order to identify current research hotspots and trends, as well as serve as a reference for future research.MethodsPublications from 2017 to 2023 about the application of graph neural network in drug discovery were collected from the Web of Science Core Collection. Bibliometrix, VOSviewer, and Citespace were mainly used for bibliometric studies.Results and DiscussionIn this paper, a total of 652 papers from 48 countries/regions were included. Research interest in this field is continuously increasing. China and the United States have a significant advantage in terms of funding, the number of publications, and collaborations with other institutions and countries. Although some cooperation networks have been formed in this field, extensive worldwide cooperation still needs to be strengthened. The results of the keyword analysis clarified that graph neural network has primarily been applied to drug-target interaction, drug repurposing, and drug-drug interaction, while graph convolutional neural network and its related optimization methods are currently the core algorithms in this field. Data availability and ethical supervision, balancing computing resources, and developing novel graph neural network models with better interpretability are the key technical issues currently faced. This paper analyzes the current state, hot spots, and trends of graph neural network applications in drug discovery through bibliometric approaches, as well as the current issues and challenges in this field. These findings provide researchers with valuable insights on the current status and future directions of this field.
Psychological factors enhanced heterogeneous learning interactive graph knowledge tracing for understanding the learning process
Authors: Wang Zhifeng , Wu Wanxuan , Zeng Chunyan , Luo Heng , Sun Jianwen 
Published: May 2024

IntroductionWith the rapid expansion of online education, there is a burgeoning interest within the EdTech space to offer tailored learning experiences that cater to individual student's abilities and needs. Within this framework, knowledge tracing tasks have garnered considerable attention. The primary objective of knowledge tracing is to develop a model that assesses a student's proficiency in a particular skill based on their historical performance in exercises, enabling predictions regarding the likelihood of correct responses in future exercises. While existing knowledge tracing models often incorporate information such as students' exercise answering history and skill mastery level, they frequently overlook the students' mental states during the learning process.MethodsThis paper addresses this gap by introducing a novel psychological factors-enhanced heterogeneous learning interactive graph knowledge tracing model (Psy-KT). This model delineates the interactions among students, exercises, and skills through a heterogeneous graph, supplementing it with four psychological factors that capture students' mental states during the learning process: frustration level, confusion level, concentration level, and boredom level. In the modeling of students' learning processes, we incorporate the forgetting curve and construct relevant cognitive parameters from the features. Additionally, we employ the Item Response Theory (IRT) model to predict students' performance in answering exercises at the subsequent time step. This model not only delves into the psychological aspects of students during the learning process but also integrates the simulation of forgetting, a natural phenomenon in the learning journey. The inclusion of cognitive parameters enhances the description of changes in students' abilities throughout the learning process. This dual focus allows for a more comprehensive understanding of students' learning behaviors while providing a high level of interpretability for the model.Results and discussionEmpirical validation of the Psy-KT model is conducted using four publicly available datasets, demonstrating its superior performance in predicting students' future performance. Through rigorous experimentation, the integration of psychological and forgetting factors in the Psy-KT model not only improves predictive accuracy but also enables educators to offer more targeted tutoring and advice, enhancing the overall efficacy of the learning experience.
Clinical effectiveness of internet-based cognitive behavioral therapy for insomnia in routine secondary care: results of a randomized controlled trial
Authors: Pchelina Polina , Poluektov Mikhail , Krieger Tobias , Duss Simone B. , Berger Thomas 
Published: May 2024

IntroductionDelivering cognitive behavioral therapy for insomnia over the internet bears the advantage of accessibility and uptake to many patients suffering from chronic insomnia. In the current study, we aimed to investigate the effectiveness of internet-based cognitive behavioral therapy for insomnia (iCBT-I) in routine care.Materials and methodsWe conducted a two-arm non-blinded randomized controlled trial with care as usual (CAU) as a control condition. Participants were recruited in a specialized outpatient sleep medicine department. Both arms had access to other healthcare resources, and the intervention group had access to the iCBT-I program for 2 months. The primary outcome was insomnia severity, measured by the Insomnia Severity Index (ISI). Secondary outcomes were fatigue severity, daytime sleepiness, affective symptoms, dysfunctional beliefs and attitudes about sleep, sleep locus of control, sleep hygiene, sleep efficiency (SE), sleep onset latency, wake time after sleep onset (WASO), and total sleep time (TST). Linear mixed models for repeated measures were used to analyze the longitudinal data at baseline, post-treatment, and after 3 months of follow-up. The trial was registered at www.clinicaltrials.gov (NCT04300218 21.04.2020).ResultsThe results showed a significant time*group interaction effect (p = 0.001) at post-treatment with between-group effect size (d = 0.51), indicating that the ISI decreased by a score of 3.8-fold in the iCBT-I group than in the CAU group. There was no significant difference in ISI between groups at follow-up. Regarding secondary outcomes, dysfunctional beliefs about sleep, SE, and WASO decreased significantly during treatment in the intervention group with between-group effect sizes d = 0.35, d = −0.51, and d = 0.47, respectively. At the follow-up, between-group effects on DBAS and SE remained significant: d = 0.36 and d = −0.63, respectively. For TST, we observed a significant time*group effect of d = −0.38 only after follow-up.ConclusionOur findings suggest that iCBT-I has a significant effect on insomnia severity at post-treatment compared to CAU. iCBT-I further improved dysfunctional beliefs about sleep and improved subjective sleep characteristics, such as SE, WASO, and TST during 3 months after treatment.Clinical trial registrationwww.clinicaltrials.gov, identifier (NCT04300218).
The relationship between sleeptime and depression among middle-aged and elderly Chinese participant during COVID-19 epidemic and non-epidemic phases
Authors: Du Chaonan , Wang Cong , Liu Zhiwei , Bai Nan , Zhu Junhao , Ali Alleyar , Geng Yuanming , Zeng Xinrui , Yang Yu , Li Zhenxing , Ma Chiyuan 
Published: May 2024

BackgroundThe global impact of the COVID-19 pandemic had significantly altered the daily routines of people worldwide. This study aimed to compare how sleeptime and depression among Chinese residents had differed between periods during and outside the epidemic. Furthermore, it delved into the interactive effect of age in this relationship.MethodUtilizing data from the China Health and Retirement Longitudinal Study (CHARLS) study in 2015 and the recently released data from 2020, which covered the pandemic period. Depression was assessed using Center for Epidemiologic Studies Depression Scale (CESD-10), considering a score of 10 or higher as indicative of depression. Participants were categorized based on age, specifically those aged 60 years and older. multivariate logistic regression and interaction analyses were employed to assess the interplay of age, supported by subgroup and sensitivity analyses to reinforce our findings.ResultsThe 2020 database comprised 19,331 participants, while the 2015 database had 10,507 participants. Our findings demonstrated a significant correlation between sleeptime and depression in both unadjusted models and models adjusted for all variables in both datasets (p&lt;0.001). Upon stratifying by age and adjusting for relevant factors, we identified an interaction effect among age, sleeptime, and depression (p=0.004 for the interaction in the 2020 database, compared to 0.004 in 2015). The restricted cubic spline analysis in both datasets showcased a nonlinear relationship between sleeptime and depression.ConclusionsDuring both epidemic and non-epidemic periods in China, there existed a correlation between sleep duration and depression, which interacts with age.
Associations between dietary habits and bipolar disorder: a diet-wide mendelian randomization study
Authors: Li Junyao , Hu Renqin , Luo Huirong , Guo Yanwei , Zhang Zheng , Luo Qinghua , Xia Pingyou 
Published: May 2024

BackgroundDiet/nutrition is critically important in the pathogenesis, progression, and treatment outcomes of various mental disorders. Current research predominantly focuses on the role of diet in the development and treatment of depression, with less attention given to the relationship between diet and Bipolar Disorder (BD).MethodWe employed Mendelian Randomization (MR) to investigate the relationship between 28 dietary habits and BD. An analysis was conducted using publicly available genome-wide association study data from the UK Biobank dataset. Various dietary habits were analyzed as exposures with BD as the outcome, mainly using the Inverse Variance Weighted (IVW) method.ResultsIntake of non-oily fish and sponge pudding both have a positive association with BD. Oily fish, dried fruit, apples, salt, and cooked vegetables intake also appeared potentially risky for BD, although the possibility of false positives cannot be ruled out. Sensitivity analysis further confirmed the robustness of these findings.ConclusionOur research provides evidence of a relationship between various dietary habits and BD. It underscores the need for careful dietary management and balance to reduce the risk of BD, suggesting caution with dietary preferences for fish and sponge pudding. Furthermore, more detailed studies are needed to further understand the potential impacts of high-sugar and high-protein diets on BD development.