bluuebunny/crossref_metadata_2025_split huggingface dataset:
Global insight of tertiary lymphoid structures and inspiration: A visualized and bibliometric study
Authors: Wu Jianjun , You Siyao , Lai Sicen , Peng Yihao , Dong Jingyi , Zhang Wei , Cui Xinyan , Yan Fei , Liu Zefu , Liu Ousheng 
Published: November 2023

Abstract
Background
Various significant roles of tertiary lymphoid structures (TLSs) have been revealed, particularly as a predictor of better prognosis and high immunotherapy response in cancer. This study aims to present global insight and succedent potential hot topics of TLSs, facilitating its future application in the clinic.
Methods
A literature screening of research on TLSs from 1999 to 31 July 2023 was actualized by using the Web of Science Core Collection database. The number of publications, countries, institutes, authors, journals, hot spots, and potential trends were summarized with bibliometric and visualized analysis, applying software including VOSviewer, CiteSpace, and R package.
Results
A total of 1964 papers were included. A significant increase in annual publications was observed in 2016 and 2020, with the maximum number of publications (351 papers) occurring in 2022. France was the most influential country, while the United States was the most productive. In addition, the United Kingdom has persisted long for the research on TLSs. Udice French Research University has published the most documents. Frontiers in Immunology was the most productive journal. The latest trends showed that the roles of TLSs and even inclusive B cells in immunotherapy, particularly in clinical trials, have been concerning and will be explored more in-depth in the future.
Conclusions
This study provides the first global trend and characteristics of the literature on TLSs, which facilitates further research and clinical applications. Exploration of the role of TLSs in cancer and immunotherapy will continue to be an attractive direction, especially for the B cells in TLSs.
Persistent Poverty Disparities in Incidence and Outcomes Among Oral and Pharynx Cancer Patients
Authors: Karanth Shama , Mistry Shilpi , Wheeler Meghann , Akinyemiju Tomi , Divaker Joel , Yang Jae Jeong , Yoon Hyung-Suk , Braithwaite Dejana 
Published: November 2023

Abstract
Purpose
Disparities in oral cavity and pharyngeal cancer (OPC) based on race/ethnicity and socioeconomic status have been reported, but the impact of living within areas that are persistently poor at the time of OPC diagnosis and outcome is unknown. This study aimed to investigate whether the incidence, 5-year relative survival, stage at diagnosis, and mortality among patients with OPC varied by persistent poverty.
Methods
Data was drawn from the SEER database (2006-2017) and included individuals diagnosed with OPC. Persistent poverty (at census tract) is defined as areas in which ≥20% of the population lived below the poverty level for ~30 years.Age-adjusted incidence and 5-year survival rates were calculated. Multivariable logistic regression was used to estimate the association between persistent poverty and advanced stage. Cumulative incidence and multivariable subdistribution hazard models were used to evaluate mortality risk. Additionally, results were stratified by cancer primary site, sex, race/ethnicity, and rurality.
Results
Of the 90,631 patients included in the analysis (61.7% <65 years old, 71.6 % males) 8.8% lived in persistent poverty. Compared to non-persistent poverty, patients in persistent poverty had higher incidence and lower 5-year survival rates. Throughout 10 years, the cumulative incidence of cancer death was greater in patients from persistent poverty and were more likely to have advanced stage cancer and higher mortality risk. In the stratified analysis by primary site, patients in persistent poverty with oropharyngeal, oral cavity, and nasopharyngeal cancers had an increased risk of mortality compared to the patients in non-persistent poverty.
Conclusion
This study found an association between OPC outcomes among patients in persistent poverty indicating a multidimensional strategy to improve survival.
Identification of Potential Binding Region of Annexin II and Dengue Virus Envelop Glycoprotein
Authors: Aliyu Isah Abubakar , Chee Hui Yee , Chong Wei Lim , Lee Vannajan Sanghiran 
Published: November 2023

Abstract
The tissue tropism of a virus is a key determinant of viral pathogenicity which is often modulated by the presence or absence of appropriate molecules on the surface of a host cell that can be used by the virus to gain entry into that cell. Annexin II was seen to interact with dengue virus (DENV) and enhanced infection. Herein, we aimed to explore this interaction as a potential target for the design of anti-DENV therapeutics. We demonstrated annexin II extracellular translocation in Vero cells upon exposure to DENV, extracellular and intracellular colocalization assays as well as co-immunoprecipitation assay were performed to further confirmed protein interaction. Molecular docking and molecular dynamic (MD) simulation were employed to identify the interaction sites. The result showed extracellular translocation of annexin II upon DENV exposure to the cell, the result further showed annexin II colocalizing with DENV E-glycoprotein extracellularly and intracellularly. Furthermore, the result of co-immunoprecipitation assay shows DENV E glycoprotein pulling down annexin II, and the result of molecular docking showed strong interaction between the two proteins. MD simulations has proposed the binding of two regions of annexin II (i) Y274-K280 and (ii) K369-Q327 with BR3 E glycoprotein of DENV2 (residue 380–389), with potential of infections abrogation upon inhibition.
Predicting Stock Prices in the Iranian Stock Market Using Convolutional Neural Network Optimization
Authors: Asl Mohsen Mahdavi , Kolahkaj Maral 
Published: November 2023

Abstract
One of the ways to assist investors in the stock market is by providing innovative patterns for predicting stock prices. Stock price information is a crucial metric that shareholders consider, and in most cases, it serves as a fundamental factor in investment decisions. In this study, deep learning algorithms are used for data mining and market prediction in Iran. The proposed method for predicting stock prices is based on an improved Convolutional Neural Network (CNN) using Harris Hawks Optimization (HHO). To create a high-precision stock price detection model, supervised learning within the CNN is employed to replace feature extraction with deep learning in the intermediate layers of the CNN. To evaluate the performance of the proposed method, data collected, including the stock prices of Bahman Khodro, listed on the stock exchange, from January 8, 2001, to December 14, 2020, is used. Daily stock data includes the number of transactions, trading volume, value, yesterday's price, opening price, closing price, lowest and highest price. Since the labels for samples (stock values) are continuous numerical values, the Mean Squared Error (MSE) is considered as the evaluation parameter for the model. The prediction results using the proposed method show that the accuracy of stock price predictions using a combination of Convolutional Neural Network and Harris Hawks Optimization is higher compared to conventional stock price prediction models, and the MSE error is lower with these mentioned features.
A Perturbation Approach for Refining Boolean Models of Cell Cycle Regulation
Authors: Banerjee Anand , Rahaman Asif Iqbal , Mehandale Alok , Kraikivski Pavel 
Published: November 2023

Abstract
Considerable effort is required to build mathematical models of large protein regulatory networks. Utilizing computational algorithms that guide model development can significantly streamline the process and enhance the reliability of the resulting models. In this article we present a perturbation approach for developing data-centric Boolean models of cell cycle regulation. We assign a score to a network based on the steady states of the network-dynamics, and the dynamical trajectories corresponding to the initial conditions. Then, perturbation analysis is used to find new networks with lower scores, in which dynamical trajectories traverse through the correct cell cycle path with high frequency. We apply this method to refine Boolean models of cell cycle regulation in budding yeast and mammalian cells.
Useful robotic stapler technique for division of intersegmental plane in robotic portal pulmonary segmentectomy
Authors: Okazaki Mikio , Suzawa Ken , Shien Kazuhiko , Hashimoto Kohei , Tanaka Shin , Miyoshi Kentaroh , Yamamoto Hiromasa , Sugimoto Seiichiro , Toyooka Shinichi 
Published: November 2023

Abstract
Objectives: Robot assisted thoracoscopic (RATS) segmentectomy is becoming increasingly common due to the expanded indications for segmentectomy and the widespread adoption of robotic surgery. Precise division of intersegmental plane is necessary to ensure oncologic margins from the tumor and preserve lung function. In this study, we present our strategy for accurately dividing the intersegmental plane using a robotic stapler and review the surgical outcomes.
Methods: RATS portal segmentectomy was performed using Da Vinci Xi system and the intersegmental plane was dissected using robotic stapler. During dissection of the pulmonary hilum, the silk threads stapled with the blood vessels and bronchi were pulled to widen the view of the pulmonary hilum and outline the correct line of dissection. We evaluated the perioperative outcomes of 92 patients who underwent RATS portal segmentectomy using this technique between May 2020 and January 2023. These results were compared with 82 patients who underwent complete video-assisted thoracoscopic surgery (CVATS) during the same period.
Results: The operative time and console time was 162 minutes and 97 minutes, respectively. No intraoperative complication occurred, andpostoperative complications were observed in 4 cases (4.3%). The operative time, blood loss, postoperative complications and maximum incision size were significantly lower in RATS compared to CVATS. However, RATS required a significantly higher number of staplers than CVATS.
Conclusions: Our technique for dividing theintersegmental plane using a robotic stapler in RATS portal segmentectomy was found to be safe and effective.
Mediator Kinase Inhibition Impedes Transcriptional Plasticity and Prevents Resistance to ERK/MAPK-Targeted Therapy in KRAS-Mutant Cancers
Authors: Wood Kris , Nussbaum Daniel , Martz Colin , Waters Andrew , Barrera Alejandro , Rutter Justine , Cerda-Smith Christian , Stewart Amy , Wu Chao , Cakir Merve , Levandowski Cecilia , Kantrowitz David , McCall Shannon , Pierobon Mariaelena , III Emanuel Petricoin , Smith J , Der Channing , Taatjes Dylan 
Published: November 2023

Abstract

Acquired resistance remains a major challenge for therapies targeting oncogene activated pathways. KRAS is the most frequently mutated oncogene in human cancers, yet strategies targeting its downstream signaling kinases have failed to produce durable treatment responses. Here, we developed multiple models of acquired resistance to dual-mechanism ERK/MAPK inhibitors across KRAS-mutant pancreatic, colorectal, and lung cancers, and then probed the long-term events enabling survival against this class of drugs. These studies revealed that resistance emerges secondary to large-scale transcriptional adaptations that are diverse and cell line-specific. Transcriptional reprogramming extends beyond the well-established early response, and instead represents a dynamic, evolved process that is refined to attain a stably resistant phenotype. Mechanistic and translational studies reveal that resistance to dual-mechanism ERK/MAPK inhibition is broadly susceptible to manipulation of the epigenetic machinery, and that Mediator kinase, in particular, can be co-targeted at a bottleneck point to prevent diverse, cell line-specific resistance programs.
A Bioluminescent and homogenous assay for monitoring GPCR-mediated cAMP modulation and PDE activity
Authors: mikheil Dareen , larsen Matthew , hsiao kevin , murray nathan , Ugo Tim , Wang Hui , Goueli Said 
Published: November 2023

Abstract
3’,5’-cyclic adenosine monophosphate (cAMP), the first identified second messenger, is implicated in diverse cellular processes involving cellular metabolism, cell proliferation and differentiation, apoptosis, and gene expression. cAMP is synthesized by adenylyl cyclase (AC), which converts ATP to cAMP upon activation of Gαs-protein coupled receptors (GPCRs) in most cases and hydrolyzed by cyclic nucleotide phosphodiesterases (PDEs) to 5’-AMP. Dysregulation of cAMP signaling is implicated in a wide range of pathophysiological conditions such as cardiovascular diseases, neurodegenerative and behavioral disorders, cancers, diabetes, obesity, cataracts, and others. Therefore, cAMP targeted therapies have been and are still undergoing intense investigation for the treatment of these and other diseases. This highlights the need for developing assays to detect and monitor cAMP levels. In this study, we show cAMP Lumit assay as a highly specific homogenous bioluminescent assay suitable for high throughput screenings with a large assay window and a wide dynamic range for cAMP detection. We believe that this assay will aid and simplify drug discovery screening efforts for cAMP signaling targeted therapies.
Cross-cultural Translation of the Adolescent Menstrual Bleeding Questionnaire (AMBQ)
Authors: Howie Chelsea , Cameron Hannah , Bouchard Mandy , Price Victoria , Young Nancy , Pike Meghan 
Published: November 2023

Abstract
Background
Heavy menstrual bleeding (HMB) affects up to 37% of adolescents. Many aspects of their lives are affected by HMB, including school attendance and participation in sports and social activities, underscoring the importance of evaluating patient reported outcomes in addition to physical outcomes in the assessment of HMB. Given the paucity of available tools to assess health-related quality of life (HRQoL) in adolescents with HMB, we developed the Adolescent Menstrual Bleeding Questionnaire (aMBQ), a valid and reliable measure of bleeding-related quality-of-life. The aim of this study was cross-cultural translation and adaptation of the English aMBQ into French to ensure accessibility for all Canadian adolescents who menstruate.
Methods
A 5-step process was followed: 1) forward translation of English aMBQ to Canadian French; 2) backward translation of aMBQ in French to English by a professional translation service; 3) review of the source and translated aMBQ to create a reconciled version; 4) cognitive debriefing to ensure linguistic, cultural, and clinical equivalence, and 5) review of cognitive debriefings to determine if changes were required and to produce the final version of the French aMBQ. This process identified words, concepts, and response options which are not clear. Results of cognitive debriefings were reviewed after every 3 participants; items were revised if presented as an issue by ≥ 2 participants. These changes were implemented and tested in cognitive debriefings until saturation was reached.
Results
Lingustic changes were made to 9 (33%) of the questions and one (3.7%) answer options. Major changes were made to 4 of the 27 questions (15%), and minor changes were made to 5 of the 27 questions (19%). One instruction item has changed, and multiple items were bolded for attention to specific words.
Conclusions
Professional translators, clinical experts, and patient input through cognitive debriefing are pivotal to successful cross-cultural translation. Results of cognitive debriefing interviews suggest the French aMBQ is easily understood and confirms its face validity. The French aMBQ will be made available on the mobile health application, WeThrive, in the near future.
Long-term evaluation of machine learning based methods for air emission monitoring
Authors: Si Minxing , Wiens Brett M. , Du Ke 
Published: November 2023

Abstract

Machine learning (ML) techniques have been researched and used in various environmental monitoring applications. Few studies have reported the long-term evaluation of such applications. Discussions regarding the risks and regulatory frameworks of ML applications in environmental monitoring have been rare. We monitored the performance of six ML-based predictive models for 28 months. The six ML models used to predict NOx emissions were developed using six different algorithms. The model developed with a moderate complexity algorithm, adaptive boosting, had the best performance in long-term monitoring, with a root mean square error (RMSE) of 0.48 kg/hr in the 28-month monitoring period, and passed two of the three relative accuracy test audits. High complexity models based on gradient boosting and neural network algorithms had the best training performance, with a minimum RMSE of 0.23 kg/hr and 0.26 kg/hr, but also had the worst RMSE scores, of 0.51 kg/hr and 0.57 kg/hr, during the monitoring period. In addition, all six models failed all three relative accuracy test audits. The following problems were observed: 1) Complex ML models tended to have overfitting problems, thus indicating the importance of the trade-off between model accuracy and complexity. 2) Model input sensor drift or out of high-frequency ranges from the training data resulted in inaccurate predictions or an accuracy lower than the minimum allowed by regulators. 3) Existing regulatory frameworks must be modernized to keep pace with current machine learning practices. Some statistical tests are unsuitable for applications developed by using ML methods.
Promoting or inhibiting: establishment of eco-industrial parks and green development
Authors: Tan Feifei , Niu Zhiyuan 
Published: November 2023

Abstract
Green development, focused on resource conservation and environmental improvement, has become a new imperative for economic progress. In the current era of high-quality and green development, eco-industrial parks (EIPs) are powerful engines for promoting both green transformation of industrial development and ecological civilization. However, despite the large-scale establishment of EIPs in China in recent years, their effectiveness in promoting green development is still unknown. To address this gap, this study employs the difference-in-difference (DID) framework to explore the effect of EIPs construction on green development in China. Results indicate that the establishment of EIPs significantly promotes the green development, with the central region having a more significant impact than the eastern and western regions. While EIPs in the western region have some inhibiting effect on green development, urban green development can be enhanced more effectively through EIPs establishment in cities with higher administrative levels. Moreover, the study identifies the influence paths through technological innovation and industrial agglomeration. Robustness tests confirm the positive effect of EIPs construction on green development. These findings provide a foundation for optimizing EIPs construction and achieving a win-win situation between economic and environmental performance, thereby transforming the development mode of a green economy.
Research on Safety Level Evaluation of Xi'an Metro Operation Based on SEM-MEA
Authors: Li Yingwei , Feng Taozhu , Liu Yuchen 
Published: November 2023

Abstract
In order to ensure the safety of Xi'an Metro, a comprehensive evaluation model based on the 4M theory has been implemented. By analyzing both domestic and international Metro accident cases and literature, four perspective risk factors were identified as personnel, equipment, management, and environment. To accurately assess the safety risk of Xi'an Metro, a risk assessment index system consisting of 44 factors was developed. The index weights were determined using the Structural Equation Model (SEM), and a comprehensive evaluation utilizing the Matter-Element Extension Method (MEA) was conducted to obtain precise safety evaluation results. The model was applied to Xi'an Metro Line 2, and the results indicated that the operation safety level of Xi'an Metro Line 2 is relatively secure. These findings are consistent with actual conditions and provide valuable information for enhancing the operation safety management of Xi'an Metro.
The expectations and acceptability of a smart nursing home model among Chinese older adults: A mixed methods study
Authors: Zhao Yuanyuan , Sazlina Shariff-Ghazali , Rokhani Fakhrul Zaman , Chinna Karuthan , Su Jing , Chew Boon-How 
Published: November 2023

Abstract
Background
Integrated smart technologies in nursing homes can enhance the quality of care. This study expands upon prior research, including a scoping review defining smart nursing homes and a qualitative study exploring the expectations and acceptability of such facilities among Chinese older adults and their families. It investigates the levels of these expectations, acceptability, and related sociodemographic factors.
Methods
This study presents the development and validation of the 24-item Expectation and Acceptability of Smart Nursing Homes Questionnaire (EASNH-Q), and a cross-sectional study conducted in four major cities in China in an exploratory sequential mixed methods study design.
Results
The newly developed EASNH-Q with Likert Scale from 1 (strongly disagree) to 5 (strongly agree) demonstrated commendable validity, reliability, and stability. The overall mean (SD) scores for expectations and acceptability were 4.0 (0.60) for each. The highest tertile of expectations (62/70, 88.6%, ꭓ2=28.89, p<0.001) and acceptability (68/83, 81.9%, ꭓ2=25.64, p<0.001) towards smart nursing homes were significantly associated with the willingness to relocate to such facilities. Older adults with self-efficacy in applying smart technologies (OR: 28.0, 95% CI: 5.92-132.66) and those expressing a willingness to move to a nursing home (OR: 3.0, 95% CI: 1.06-8.37) were more likely to have the highest tertile of expectations compared to those in the lowest tertile. Similarly, older adults with self-efficacy in applying smart technologies were more likely to be in the highest tertile of acceptability of smart nursing homes compared to those in the lowest tertile (OR: 13.8, 95% CI: 4.33-43.95).
Conclusions
The majority of Chinese older adults were willing to move to a smart nursing home. Self-efficacy in applying smart technologies links to the high expectations and acceptability of smart nursing homes. The willingness to relocate to a nursing home increased the high expectations of smart nursing homes.