bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is myocardial bridge-related stenosis definitely a risk factor for altered coronary blood flow in patients with myocardial bridge?
Authors: Song Yingchun , Qiao Yu , Wang Shi , Yi Wanwan , Liu Si , Zhang Xiaoying , Sun Ming , Shen Jianying , Zhang Han , Ma Chao , Yu Fei , Lv Zhongwei , Cai Haidong 
Published: November 2023

Abstract
Objective
To explore the potential role MBRS may play in the hemodynamics of coronary arteries and the impact of non-MBRS on hemodynamic alterations in MB patients.
Methods
A total of 86 patients with MBs (located in the middle of LAD) and 50 non-MB controls were retrospectively enrolled according to coronary computed tomography angiography (CTA), coronary angiography (CA) and dynamic single-photon emission computed tomography (D-SPECT). Stenosis characteristics (incidence, location and degree of stenosis) and hemodynamics (absolute CBF, relative CBF and CFR) were compared between groups with and without MBRS (or non-MBRS).
Results
Regardless of whether it was complicated by non-MBRS, there was no difference in the incidence and location of MBRS, but it varied in the severity of stenosis. Compared to cases without MBRS, cases with MBRS had increased relative CBF in the proximal and middle segments of the LAD, and the relative CBF of the left circumflex artery (LCX) was increased at rest (both P<0.05). In addition, absolute CBF in LAD was reduced in MB with non-MBRS compared to those without non-MBRS.
Conclusion
MBRS can partially correct the CBF redistribution induced by the “milking effect” and increase the CBF in the LCX. Therefore, it is a possible protective factor to some extent. In addition, concomitant non-MRBS decreased the CBF of theLAD and aggravated the severity of MBRS but did not change the incidence or location of MBRS.
NISONet: Detecting fake news on social media with a nature-inspired memory efficient and space optimized deep learning approach
Authors: Kaliyar Rohit Kumar , Goswami Anurag , Narang Pratik 
Published: November 2023

Abstract
Numerous enhancements have been made to the mobile internet, which has led to an increase in people?s attention to posting more multi-modal posts among social media platforms. Detecting fake news continues to be a serious concern in today's social culture. Machine learning and deep learning algorithms have shown significant results in predicting and identifying fake news. In recent studies, existing deep learning 1-D CNN models have proved very effective for text classification problems. Due to a large number of floating-point operations, a large number of layers with many hidden units necessitates an enormous amount of memory space and a high response time. Today, the number of edge devices is growing exponentially, making it difficult to deploy CNN models that have been pre-trained directly on these devices. This paper addresses the compression issue by proposing a particle swarm-based optimization technique to retain the best-hidden units without compromising the classification model's accuracy. In this paper, we have chosen Top-1 accuracy and compression ratio as the dual objective fitness functions, so that accuracy should not degrade excessively after compression. The results of these experiments are examined using the proposed methodologies. The analysis of the results reveals positive performance with the use of the proposed deep neural network.
Causal Relationships between Immune Cells and Rheumatoid Arthritis
Authors: Tan Xin , Chen Shirong 
Published: November 2023

Abstract

Background
When it comes to the beginning, course, diagnosis, and management of rheumatoid arthritis (RA), immune cells (ICs) are crucial. However, because of the intricate relationships that exist between RA and the immune system, it is difficult to determine how a particular class or type of immune cell affects RA, and research on this topic is seldom able to rule out the possibility that RA will interfere with the reversal action of ICs.
Methods
To investigate and screen out the impacts on RA from 731 ICs, we mostly used MR analysis using IVW (inverse variance weighted), Weighted median, and MR-Egger regression methods. Then, the inverse effect of RA on ICs was explored by reversed MR. Finally, MR-Egger intercept, Cochran's Q test, and “Leave-one-out” are conducted to measure the degrees of of pleiotropy and heterogeneity.
Results
9 immune phenotypes were found significantly linked to RA risk: IgD- CD27- B cell %B cell (OR = 1.17 95%CI = 1.06–1.29), dendritic cell absolute count (OR = 1.07 95%CI = 1.02–1.13), CD86 + myeloid dendritic cell absolute count (OR = 1.06 95%CI = 1.02–1.11), CD25 on memory B cell (OR = 1.08 95%CI = 1.02–1.13), CD27 on memory B cell(OR = 0.91 95%CI = 0.85–0.98), CD3 on effector memory CD4 + T cell (OR = 0.97 95%CI = 0.94-1.00), CD25 on CD4 + T cell (OR = 0.93 95%CI = 0.87–0.98), CD45 on CD33br HLA DR + CD14dim(OR = 1.04 95%CI = 1.01–1.06), CD11b on CD33br HLA DR + CD14dim(OR = 0.95 95%CI = 0.91–0.99). While only RA on CD25 on memory B cell (OR = 0.95 95%CI = 0.90-1.00) and CD45 on CD33br HLA DR + CD14dim (OR = 0.92 95%CI = 0.87–0.98) were found in reverse MR. Besides, the results of MR-Egger intercept suggest that there exists no evidence of horizontal pleiotropy.
Conclusion
Our study identified an association between specific immune cells and RA, and this association could guide the future diagnosis and treatment of RA.
Anlotinib plus Tislelizumab for Recurrent Metastatic Pancreas Ductal Adenocarcinoma with Germline BRCA2 Mutation: A Case and Literature Review
Authors: Peng Sujuan , Huang Hongxiang , Zhu Xie , Chen Jinhong , Ding Xinjing , Wang Fen , Chen Li , Lu Zhihui 
Published: November 2023

Abstract
Purpose
While combined immunotherapy and anti-angiogenic therapy have demonstrated efficacy in renal cell carcinoma, non-small cell lung cancer, and hepatocellular carcinoma, the efficacy of first-line treatment for pancreatic ductal adenocarcinoma (PDAC) with germline BRCA2 mutation remains unproven.
Methods
We described a BRCA2-mutated PDAC patient who presented with posterior cardiac metastasis eight months after surgery. We performed anlotinib plus tislelizumab on him for systemic therapy.
Results
After receiving four cycles of anlotinib combined with tislelizumab, abdominal CT scans indicated a complete response. The patient sustained this response for over 13 months on the combination regimen, with no reported adverse events.
Conclusions
The combination of tislelizumab and anlotinib may offer a viable therapeutic option for recurrent metastatic BRCA2-mutated PDAC.
Effect of Learners’ Cultural Intelligence on Listening Anxiety: Toward Testing a Model with the mediating role of Language Learning Motivation
Authors: Manoochehrzadeh Mehdi , Barjesteh Hamed , Sadeghi Jamal 
Published: November 2023

Abstract

Listening comprehension anxiety (LCA) has received considerable research over the past few decades, but conceptual models to pinpoint the sources of LCA have not been adequately explored. The present study set out to probe the structural model hypothesizing the predictive role of cultural intelligence (CQ) and language learning motivation (LLM) in affecting LCA. To this end, 250 English as a foreign language) EFL) learners completed the three self-report scales measuring the variables under investigation. As for the data analysis, Pearson product moment correlations and structural equation modeling (SEM) were used to examine the interplay among the variables, and to test the fit of the model. The correlation analysis indicated that there was a statistically significant: (a) negative relationship between CQ and LCA, and (b) reverse correlation between LLM and LCA. Moreover, the SEM analysis revealed that CQ and LLM accounted for .39% of the variance in LCA. Specifically, CQ abated to − .33% of the variance while LLM decreased to − .29% of the variance in LCA. Additionally, it was established that while both predictors had a significant effect, LLM appeared to be a robust predictor of LCA reduction. This implies that students who had a higher level of LLM were less likely to experience LCA. Therefore, materials developers, curriculum planners, and language teachers, in particular, are advised to train learners to foster CQ and LLM, as both are known to reduce LCA. Detailed discussion of the results and implications of the study are provided in the paper.
Clinical simulation in the regulation of software as a medical device (SaMD): an eDelphi study
Authors: Ghafur Saira , Driscoll Fiona O , O'Brien Niki , Guo Chaohui , Prime Matthew , Darzi Ara 
Published: November 2023

Abstract
Accelerated digitalization in the health sector requires the development of appropriate evaluation methods to ensure digital health technologies (DHTs) are safe and effective. Clinical simulation can be used by researchers to test DHTs in an agile and low-cost way, yet there is limited research on criteria to assess the robustness of simulations and subsequently, their relevance for a regulatory decision. The aim of this study was to gain consensus the research question “What criteria should be used to assess clinical simulation being used to generate evidence for software as a medical device (SaMD)?” 39 international experts in the digital health field, including academics, regulators, policy makers, and industry representatives, participated in a three-round eDelphi exercise. Options were generated through the scoping questionnaire around key themes identified from the literature to obtain a comprehensive list of criteria and voted upon in two subsequent questionnaire rounds. Consensus was defined by two criteria: if <10% of the panelists deemed the criteria as ‘not important’ or ‘not important at all’ and >60% ‘important’ or ‘very important’. 43 criteria gained consensus from the panelists across seven domains and the Simulation for Regulation of SaMD (SIROS) framework was developed. We highlight key areas of concern identified by panelists, specifically on the importance of fidelity of simulation and its reporting, and the challenge of bias. Future research should prioritise the development of safe and effective SaMD, while implementing the criteria generated for regulating DHT based on clinical simulation evidence can enable faster uptake of technologies.
Non-invasive monitoring and classification of coronary heart disease by metabolomics and lipidomics
Authors: Wang Zhicai , Cang Yan , Li Yan , Zhang Yi , Hu Junyuan , Xu Yawei , Liu Li , Liu Zheng 
Published: November 2023

Abstract
Background
Coronary heart disease (CHD) stands as a prominent contributor to global mortality. CHD as a chronic disease usually develops over decades, and the resulting symptoms may go unnoticed until a severe blockage causes stroke or heart attack. Early screening enables timely detection of potential risk factors and signs of disease, facilitating preventive measures and lifestyle modifications.
Methods
154 suspected CHD subjects were prospectively enrolled and divided into four groups according to the results of coronary angiography. The plasma metabolites and lipids were detected by three MS-based platforms. OPLSDA was performed to discriminate the metabolic profiles between different groups. The differential metabolites were screened by statistical analysis (p < 0.05) and OPLSDA (VIP > 1.5). The associations of metabolites with stenosis and clinical markers were visualized by the Spearman’s rank correlation.
Results
CHD exhibited a distinct metabolic pattern, mainly involving organic acids, organoheterocyclic compounds and lipids. The perturbated metabolites possess the diagnostic potential and exhibited correlations with CHD clinical markers. Therein, specific triglyceride (TAG) species and N-epsilon,N-epsilon,N-epsilon-trimethyllysine were associated with CHD progression. We also found that TAG species have the potential to be metabolic risk factors for co-occurring CHD and diabetes. Furthermore, cluster of metabolites, primarily composed of amino acids and lipids, were significantly associated with the progression of coronary artery stenosis.
Conclusions
Blood metabolites and lipids are promising as innovative tools for accurate diagnosis, progression monitoring, deciphering and management of cardiovascular diseases.
Relationship Between Prediabetes and Coronary Artery Calcium Score
Authors: Barcia José Antonio Parada , Pérez Manuel Barreiro , López Pablo Pazos , Chia Tatiana Matajira , Iglesias Francisco Eugenio Calvo , Roubin Sergio Raposeiras , Abu-Assi Emad , Fernández-Obanza Emiliano , Pérez Álvaro Rodríguez , Ferraz Lisa Maria Costa Ribeiro , Romo Andrés Iñiguez 
Published: November 2023

Abstract
Introduction:
Prediabetes (pDM) is an extremely prevalent clinical entity which appears to be associated with an increased risk of cardiovascular (CV) disease. Coronary artery calcium (CAC) score has been shown to be a reliable risk predictor of CV disease too. The link between pDM and coronary CT (computed tomography) findings has not been explored yet.
The present study aimed to investigate the association between CAC and pDM.
Methods:
The study cohort included 259 patients who underwent a coronary CT between July 2021 and July 2022 in our center.
Prediabetes status was defined following the American Diabetes Association guidelines as HbA1c 5.7% to 6.4%. Significant CAC score was defined in ≥100 UA, as it is considered the common treatment threshold to iniate/consider statin.
Results:
73 patients (28.2%) were classified as pDM. Compared with those with euglycemia, patients with pDM were older (59.91±12.44; 64.42±9.72 years, respectively). Hypertension (including systolic and diastolic blood pressure), dyslipidemia and smoking did not differ between both groups.
After multivariate analysis, pDM was associated with significant CAC score (OR 2.08, CI 95% 1.02-4.28; p= 0.048).
Conclusions:
In our study, we found that prediabetes is associated with CAC score ≥100 UA. This association supports available evidence that pDM confers higher CV risk.
Integration of an Ultrasonic Sensor within a Robotic End Effector for application within Railway Track Flaw Detection
Authors: Cilia L. , Griffiths Christian Andrew , Rees A. , Thompson J. 
Published: November 2023

Abstract
The rail industry is constantly facing challenges related to safety with regards to the detection of surface cracks and internal defects within rail tracks. Significant focus has been placed on developing sensor technologies that would facilitate the detection of flaws that compromise rail safety. In parallel, robot automation has demonstrated significant advancements in the integration of sensor technologies within end effectors. This study investigates the novel integration of an ultrasonic sensor within a robotic platform specifically for the application of surface crack and internal defects within rail tracks. The performance of the robotic sensor system has been assessed on a rail track specimen containing sacrificial surface cracks and internal defects and then compared against a manual detection system. The investigation concludes that the robotic sensor system successfully identified internal defects in the web region of the rail track when utilising a 60° and 70° wedged probe, with a frequency range between 4 MHz and 5 MHz. However, the surface crack investigation proved that the transducer was insensitive to the detection of cracks, possibly due to the inadequate angle of the wedged probe. The overall outcome of the study highlights the potential that robotic sensor systems have in the detection of internal defects and characterises the limitation of surface crack identification to assist in enhancing rail safety.
Phenotypic diversity of key adaptive traits in advanced Nordic and Baltic spring wheat (Triticum aestivum L) breeding material
Authors: Ingver Anne , Gorash Andrii , Ivandi Elena , Strazdina Vija , Aleliunas Andrius , Kaart Tanel , Fetere Valentina , Meigas Egon , Jansone Zaiga , Shafiee Sahameh , Mroz Tomasz , Bleidere Mara , Merilo Ebe , Lillemo Morten , Kollist Hannes , Brazauskas Gintaras , Tamm Ilmar 
Published: November 2023

Abstract

Wheat (Triticum aestivum L.) has become the most widely grown cereal crop in the Nordic-Baltic region, however, due to climate change its yields are under increasing risk. Here we present results of international effort harnessing available wheat germplasm in the region for identification of tools and genotypes for breeding wheat varieties with improved yield stability. We formed a panel comprising 300 spring wheat genotypes from Nordic-Baltic region and studied their phenotypic diversity across different environments to identify genotypes with high potential for adaptation to changing climate. Field experiments were carried out in 2021 and 2022 in Estonia, Latvia, Lithuania and Norway. The performance and stability of yield (GY), protein content (PC), thousand kernel weight (TKW), test weight (TW), length of growing period (GP), and nine other traits – were studied. Drought and excessive rainfall occurred in the Baltic countries in 2021–2022, whereas weather was more stable in Norway. High variability for most, and significant GxE effect for all the studied traits was identified. We found out genotypes combining yield and quality with stability using the AMMI model-based Weighted Average of Absolute Scores index (WAASB). Finally, we selected nineteen superior genotypes that combined high yield with high values of important quality traits. Thus, combining broad Nordic-Baltic wheat germplasm with extensive field phenotyping, we identified promising breeding material to develop climate ready spring wheat varieties for the region.
Full endoscopic laminotomy decompression versus anterior cervical discectomy and fusion for the treatment of single-segment cervical spinal stenosis: A retrospective, propensity score-matched study
Authors: Li Tusheng , Huang Jie , Zhang Hanshuo , Lu Zhengcao , Liu Jiang , Ding Yu 
Published: November 2023

Abstract
Objective
Anterior cervical discectomy and fusion (ACDF) is the standard procedure for the treatment of cervical spinal stenosis (CSS), but complications such as adjacent segment degeneration can seriously affect the long-term efficacy. Currently, posterior endoscopic surgery has been increasingly used in the clinical treatment of CSS. The aim of this study was to compare the clinical outcomes of single-segment CSS patients who underwent full endoscopic laminotomy decompression or ACDF.
Methods
138 CSS patients who met the inclusion criteria from June 2018 to August 2020 were retrospectively analyzed and divided into endoscopic and ACDF groups. The propensity score matching (PSM) method was used to adjust the imbalanced confounding variables between the groups. Then, perioperative data were recorded and clinical outcomes were compared, including functional scores and imaging data. Functional scores included Visual Analog Scale of Arms (A-VAS) and Neck pain (N-VAS), Japanese Orthopedic Association score (JOA), Neck Disability Index (NDI), and imaging data included Disc Height Index (DHI), Cervical range of motion (ROM), and Ratio of grey scale (RVG).
Results
After PSM, 84 patients were included in the study. The endoscopic group was significantly superior to the ACDF group in terms of operative time, intraoperative blood loss, incision length, and hospital stay (P < 0.001). Postoperative N-VAS, A-VAS, JOA, and NDI were significantly improved in both groups compared with the preoperative period (P < 0.001), and the endoscopic group showed better improvement at 7 days postoperatively (P < 0.05). The ROM changes of adjacent segments were significantly larger in the ACDF group at 12 months postoperatively and at the last follow-up (P < 0.05). The RVG of adjacent segments showed a decreasing trend, and the decrease was more marked in the ACDF group at last follow-up (P < 0.05). According to the modified MacNab criteria, the excellent and good rates in the endoscopic group and ACDF group were 90.48% and 88.10%, respectively, with no statistically significant difference (P > 0.05).
Conclusion
Full endoscopic laminotomy decompression was demonstrated to be an efficacious alternative technique to traditional ACDF for the treatment of single-segment CSS, with the advantages of less trauma, faster recovery, and less impact on cervical spine kinematics and adjacent segmental degeneration.
THUMPD3-AS1 inhibits ovarian cancer cell apoptosis through the miR-320d/ARF1 axis
Authors: Mu Qingling , Wang Xin , Huang Kui , Xia Baoguo , Bi Shuna , Kong Yujie 
Published: November 2023

Abstract

Background
Ovarian cancer is one of the most common gynecologic malignancies that has a poor prognosis. THUMPD3-AS1 is an oncogenic long noncoding RNA (lncRNA) in several cancers. Nevertheless, the role of THUMPD3-AS1 in ovarian cancer and the underlying mechanism has yet to be elucidated.
Methods
Human normal ovarian epithelial cells (IOSE80) and ovarian cancer cell lines (CAVO3, A2780, SKOV3, OVCAR3 and HEY) were adopted for in vitro experiments. The functional roles of THUMPD3-AS1 in cell viability and apoptosis were determined using CCK-8, flow cytometry and TUNEL assays. Western blot and RT-qPCR were performed to assess the levels of ARF1, Bax, Bcl-2 and caspase 3, THUMPD3-AS1and miR-320d, respectively. The targeting relationship between miR-320d and THUMPD3-AS1 or ARF1 was validated with dual luciferase assay.
Results
THUMPD3-AS1 and ARF1 were highly expressed in ovarian cancer cells, whereas miR-320d level was lowly expressed. THUMPD3-AS1 knockdown was able to repress cell viability and accelerate apoptosis of OVCAR3 and SKOV3 cells. Also, THUMPD3-AS1 acted as a sponge for miR-320d, preventing the degradation of its target gene ARF1. MiR-320d downregulation reversed the tumor suppressive function induced by THUMPD3-AS1 depletion. Additionally, miR-320d overexpression inhibited ovarian cancer cell viability and accelerated apoptosis, which was overturned by overexpression of ARF1.
Conclusion
THUMPD3-AS1 inhibited ovarian cancer cell apoptosis by modulation of miR-320d/ARF1 axis. The discoveries might provide a prospective target for ovarian cancer treatment.
Preoperative MR - based model for predicting prognosis in patients with intracranial extraventricular ependymoma
Authors: Li Liyan , Wang Xueying , Tan Zeming , Mao Yipu , Huang Deyou , Yi Xiaoping , Jiang Muliang , Chen Bihong T. 
Published: November 2023

Abstract
Objectives:To develop and validate a machine learning model based on MR to predict disease-free survival (DFS) and overall survival (OS) for patients with intracranial extraventricular ependymoma (IEE).
Methods:The study included 114 patients with pathology-proven IEE, of whom 80 were randomly assigned to a training group and 34 to a validation group. Preoperative brain MRI images were assessed with the VASARI (Visually AcceSAble Rembrandt Images) feature set. Multivariate Cox proportional hazards regression analysis was performed to select the independent prognostic factors.
Results: Eosinophil, blood urea nitrogen, serum creatinine, and definition of the non-enhancing margin (F13) were significantly correlated with the prognosis of DFS. And blood urea nitrogen, D-dimer, tumor location (F1), T1/FLAIR ratio (F3), and T1/FLAIR ratio (F10) were independent predictors of OS. Based on these factors, survival models with the clinical variables, MR-VASARI features, and with both the clinical and MR-VASARI features were constructed for DFS and OS respectively. The c-indices of the three survival models for OS were 0.732, 0.729, and 0.768, respectively. For DFS, the c-indices were respectively 0.694, 0.576, and 0.714.
Conclusion:Predictive modelling combining both clinical and MR-VASARI features is robust and may assist in the assessment of prognosis in patients with IEE.