bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mycorrhizal Types Regulate Tree Spatial Associations in Temperate Forests: Ectomycorrhizal Trees Might Favour Species Coexistence
Authors: Mao Zikun , Wiegand Thorsten , Corrales Adriana , Fang Shuai , Hao Zhanqing , Lin Fei , Ye Ji , Yuan Zuoqiang , Wang Xugao 
Published: October 2024

ABSTRACTIn temperate mixed forests, dominant ectomycorrhizal (EM) tree species usually coexist with diverse arbuscular mycorrhizal (AM) understorey tree species. Here, we investigated the spatial associations between AM and EM trees in two > 20 ha temperate forest mega‐plots to better understand the observed ‘EM‐dominant versus AM‐diverse’ coexistence. Overall, we found that positive spatial associations (e.g., facilitation) were mostly related to EM trees, while negative spatial associations (e.g., inhibition) were mainly related to AM trees. Because adult EM trees tended to facilitate surrounding AM and EM saplings and other EM adults in these two forests, facilitation hotspots that stabilize AM‐EM tree coexistence should be centred around EM tree species rather than around AM tree species. Together, we propose a novel EM‐stabilization mechanism, which emphasises how, despite some species‐specific variation, EM tree species foster ‘EM‐dominant versus AM‐diverse’ coexistence in temperate mixed forests by facilitating other trees.
The RARCrec: A rapid riparian vegetation assessment method for use in river systems undergoing vegetative and geomorphic recovery
Authors: Duxbury Elisha , Fryirs Kirstie , Leishman Michelle 
Published: October 2024

SummaryMonitoring the condition of returning vegetation over time is essential for effectively managing riparian vegetation. Rapid riparian assessment methods are standard tools for capturing a suite of variables relevant to river health and are accessible to a range of users with different levels of experience. Monitoring efforts are particularly important for rivers undergoing degrading impacts and subsequent management interventions. In coastal catchments of New South Wales, Australia, vegetation is returning to rivers that were historically cleared for agriculture and are now experiencing geomorphic recovery. We present a rapid riparian assessment method for rivers undergoing vegetative and geomorphic recovery in this region. It addresses a gap in available rapid assessments by providing a methodology that can be used at sites with no historical analogue. Our assessment method adapts and extends a widely used method called the Rapid Assessment of Riparian Condition (RARC) to capture the quality of returning riparian vegetation along recovering rivers (rec), including native species diversity and vegetation structure (hence the name RARCrec). The RARCrec incorporates four sub‐indices – vegetation cover, native species richness, proportion of native to exotic species, and features of vegetation health – to produce an overall vegetation condition score that classifies sites as poor, moderate, or good condition. Scores for each sub‐index are assessed for the vegetation strata (groundcover, graminoids, midstorey, vines, and canopy) on the landform units of river bars, benches, and floodplains. The RARCrec has been designed to be sufficiently general for use in the main Vegetation Formations in coastal New South Wales and has been trialled at 36 sites across this region. Assessments can be conducted within half a day by two technically competent users and can be used to monitor vegetation condition over time to inform where to prioritise implementation of management activities. Field methodology and data sheets, including a scoring system, are provided to support the implementation of the RARCrec.
Strategic foresight as a beacon for the new EU industrial policy
Authors: Lorenzani Dimitri 
Published: October 2024

AbstractThis article assesses the impact of strategic foresight in shaping the European Commission’s new industrial policy. It argues that, since it was introduced by President von der Leyen as a political portfolio, foresight has contributed to mainstreaming the concepts of ‘resilience’ and ‘open strategic autonomy’ into the EU's industrial strategy, via the Strategic Foresight Reports and new participatory structures inside and outside the Commission. This responded to the need for building up preparedness in the face of ‘radical uncertainty’ on future supply chain disruptions. We conclude that strategic foresight—if supported by an effective governance—will play an increasingly large role in shaping the EU's future policymaking. In particular, the concepts of ‘competitive sustainability’ and people's wellbeing, advanced by the 2023 Strategic Foresight Report as pillars of open strategic autonomy, may help futureproof the EU's green industrial policy going forward.
Dare scholars look to the future? Academia and strategic foresight for the European Union's foreign policy
Authors: Sus Monika 
Published: October 2024

AbstractDrawing on examples of foresight projects situated at the interface between academia and foreign policy practice, this article reflects on the role of academics in informing the practice of foreign policy‐making in the EU. The study explores why academics have rarely engaged in foresight over the past two decades and why this has changed in recent years. It argues that this shift is triggered, on the one hand, by the strategic blunders of the last decade and, on the other hand, by the conceptual developments within the disciplines of political science or international relations. After demonstrating the growing trend of scholarly engagement in foresight with a series of illustrative examples, the article discusses the added value and limitations of academic‐generated foresight for EU foreign policy. Taking these into account, the analysis indicates best practice solutions, such as foresight exercises, with the joint involvement of researchers and policymakers.
Buddhism as ‘Chinese Philosophy’: Buddhism in Hegel's History of Philosophy1
Authors: Martin Jay 
Published: October 2024

AbstractThe question of Hegel's views on Buddhism and its place within his system must be asked again as the history of effects, transmission, and reception continues to unfold. This unfolding highlights not only Hegel's effect on the Western European reception and understanding of Buddhism (and its sharp orientalist critique), but also the canny use of Hegel's philosophy by certain members of the so‐called Kyoto School of Japanese neo‐Buddhist philosophy, who, though primarily concerning themselves with Heidegger, were notable in their creative use of Hegel's philosophy of spirit (especially Nishida, Nishitani, Tanabe, and Abe). Our present task is likewise to look back to Hegel's own writing on Buddhism through the lens of the history of its effects—that is, to read Hegel again with his legacy in mind—so that we might, as strange as it may perhaps seem, see things more clearly. Our goal is relatively modest, as it aims only to seek out and coordinate Buddhism within Hegel's history of philosophy. Thus, as we have a proximate goal in mind, we also have an order of importance with respect to Hegel's texts, which, of course, brings the Lectures on the History of Philosophy to the fore.
The Neuroaesthetics of Art and Design Education
Authors: Wild Carol 
Published: October 2024

AbstractTeaching is increasingly defined through the syntax of cognitive science, by retrieval practice, spaced learning, and interleaving, generating a computational rhythm for learning as a system of inputs and outputs that builds up an individual's memory over time. This, I argue, is at odds with the choreography of art and design education as an aesthetic, social, and material practice. An alternative mapping is required to fully understand the chronology of learning that takes place in and through the subject of art and design with human and nonhuman others. Drawing from a review of research in the field of Neuroaesthetics, I will seek to defend the unique temporality of art and design education and imagine different visualisations of learning in the subject beyond the computational.
Enhancing osteogenic differentiation of diabetic tendon stem/progenitor cells through hyperoxia: Unveiling ROS/HIF‐1α signalling axis
Authors: Zhang Ming , Dai Guan‐Chun , Zhang Yuan‐Wei , Lu Pan‐Pan , Wang Hao , Li Ying‐Juan , Rui Yun‐Feng 
Published: October 2024

AbstractDiabetic calcific tendinopathy is the leading cause of chronic pain, mobility restriction, and tendon rupture in patients with diabetes. Tendon stem/progenitor cells (TSPCs) have been implicated in the development of diabetic calcified tendinopathy, but the molecular mechanisms remain unclear. This study found that diabetic tendons have a hyperoxic environment, characterized by increased oxygen delivery channels and carriers. In hyperoxic environment, TSPCs showed enhanced osteogenic differentiation and increased levels of reactive oxygen species (ROS). Additionally, hypoxia‐inducible factor‐1a (HIF‐1a), a protein involved in regulating cellular responses to hyperoxia, was decreased in TSPCs by the ubiquitin‐proteasome system. By intervening with antioxidant N‐acetyl‐L‐cysteine (NAC) and overexpressing HIF‐1a, we discovered that blocking the ROS/HIF‐1a signalling axis significantly inhibited the osteogenic differentiation ability of TSPCs. Animal experiments further confirmed that hyperoxic environment could cause calcification in the Achilles tendon tissue of rats, while NAC intervention prevented calcification. These findings demonstrate that hyperoxia in diabetic tendons promotes osteogenic differentiation of TSPCs through the ROS/HIF‐1a signalling axis. This study provides a new theoretical basis and research target for preventing and treating diabetic calcified tendinopathy.
Pairwise analysis of gene expression for oral squamous cell carcinoma via a large‐scale transcriptome integration
Authors: Li Nan , Hu Zunkai , Zhang Ning , Liang Yining , Feng Yating , Ding Wanfu , Cheng Lixin , Zheng Yuyan 
Published: October 2024

AbstractAmong all cancers occurring in the head and neck region, oral squamous cell carcinoma (OSCC) is the most common oral malignant tumours characterized by its aggressiveness and metastasis. The development of transcriptomics technology has greatly facilitated the diagnosis of various cancers. However, identifying genetic biomarkers is limited by data from a single batch of OSCC samples, and integrating analysis across different platforms remains a great challenge. In this study, we integrated five OSCC transcriptome datasets using an innovative strategy capable of mitigating batch effect, and extracting information from different datasets based on changes in the relative expression of gene pairs. By leveraging a machine learning method, we developed a prediction model including 27 differential gene pairs (DGPs) to discriminate OSCC from control samples, achieving an area under the receiver operating characteristic curve (AUC) of 0.8987 for the training set. Moreover, the model demonstrated commendable performance in four external validation sets, with AUCs of 0.9926, 0.9688, 0.8052 and 0.8565, respectively. Subsequently, a prognostic model was constructed based on six key gene pairs through univariate and multivariate Cox regression analysis. The AUCs of the model at 1‐year and 3‐year overall survival time prediction were 0.717 and 0.779 in an independent dataset. Our result demonstrates the effectiveness of this new method of integrating data and identifying DGPs. Using DGPs can significantly improve the performance of both diagnostic and prognostic models.
Exploring the prognostic value and potential therapeutic strategies of MS4A6A in glioblastoma: A comprehensive analysis of single‐cell and multi‐omics data
Authors: Wan Fangchao , Li Yanling , Zhu Jianming , Yu Dandan , Liu Hongjuan , Hu Bohong 
Published: October 2024

AbstractGlioblastoma (GBM) is a highly aggressive and treatment‐resistant malignancy that poses a significant challenge in modern medicine. Despite advances in surgical resection, radiotherapy and chemotherapy, complete eradication of GBM remains elusive due to its diffuse invasion into the brain parenchyma and propensity for recurrence. The tumour microenvironment (TME), particularly macrophages, has emerged as a critical player in GBM progression, invasion and metastasis. In the immune microenvironment of glioma, MS4A6A exhibits unique expression characteristics in macrophages. This study aimed to investigate the potential role of MS4A6A, a gene associated with aging and neurodegenerative diseases, in GBM and its potential as a prognostic biomarker and therapeutic target.
Epiphytic, Attached, and Internal Escherichia coliO157:H7 Subpopulations Associating With Romaine Lettuce Are Strain‐Dependent and Affected by Relative Humidity and Pre‐ and Postharvest Plant State
Authors: Hudson Claire L. , Micallef Shirley A. 
Published: October 2024

ABSTRACTRomaine lettuce is susceptible to Escherichia coli O157:H7 contamination. We evaluated strain and pre‐ and postharvest lettuce product differences in E. coli O157:H7 subpopulation distribution on romaine lettuce at two relative humidity (RH) levels. Plants of romaine lettuce cultivar 'Carlsbad' harvested and processed 'Carlsbad' leaves, and store‐bought ready‐to‐eat romaine lettuce were inoculated with E. coli O157:H7 reference strain EDL933 and romaine lettuce outbreak strain 2705C. Using four processing methods, we determined pathogen cell fractions representing All (entire population), Epiphytic (loosely attached cells), Strongly Attached + Internal (excluding loosely attached cells), and Internal (excluding epiphytic cells) subpopulations. Preharvest, 80% RH favored subpopulations in each cell fraction, compared to 40% RH (p < 0.01 for both strains) and yielded 92%–100% internalization incidence of E. coli O157:H7, compared to 50%–57% at 40% RH. Levels of internal EDL933 cells were also 1.1 log higher than 2705C cells from plants kept at 80% RH (p < 0.001). While EDL933 had lower measures of Strongly Attached + Internal cells compared to All and Epiphytic fractions (p < 0.01), 2705C yielded no difference. Taken together, data suggest that the lettuce outbreak strain had a higher propensity for strong attachment to leaves and EDL933 internalized more successfully. Moreover, the Strongly Attached + Internal fractions of both strains were lower on preharvest 'Carlsbad' compared to 'Carlsbad' processed leaves (p < 0.01), suggesting that E. coli O157:H7 attached less strongly to preharvest plants than postharvest cut and stored leaves of the same variety. Our study uncovers important factors influencing cultivar‐ and strain‐specific differences in association and internalization of enteric pathogens on leafy greens.
Gastric neoplasm detection of computer‐aided detection‐assisted esophagogastroduodenoscopy changes with implement scenarios: a real‐world study
Authors: Huang Li , Xu Ming , Li Yanxia , Dong Zehua , Lin Jiejun , Wang Wen , Wu Lianlian , Yu Honggang 
Published: October 2024

AbstractBackground and AimThe implementation of computer‐aided detection (CAD) devices in esophagogastroduodenoscopy (EGD) could autonomously identify gastric precancerous lesions and neoplasms and reduce the miss rate of gastric neoplasms in prospective trials. However, there is still insufficient evidence of their use in real‐life clinical practice.MethodsA real‐world, two‐center study was conducted at Wenzhou Central Hospital (WCH) and Renmin Hospital of Wuhan University (RHWU). High biopsy rate and low biopsy rate strategies were adopted, and CAD devices were applied in 2019 and 2021 at WCH and RHWU, respectively. We compared differences in gastric precancerous and neoplasm detection of EGD before and after the use of CAD devices in the first half of the year.ResultsA total of 33 885 patients were included and 32 886 patients were ultimately analyzed. In WCH of which biopsy rate >95%, with the implementation of CAD, more the number of early gastric cancer divided by all gastric neoplasm (EGC/GN) (0.35% vs 0.59%, P = 0.028, OR [95% CI] = 1.65 [1.0–2.60]) was found, while gastric neoplasm detection rate (1.39% vs 1.36%, P = 0.897, OR [95% CI] = 0.98 [0.76–1.26]) remained stable. In RHWU of which biopsy rate <20%, the gastric neoplasm detection rate (1.78% vs 3.23%, P < 0.001, OR [95% CI] = 1.84 [1.33–2.54]) nearly doubled after the implementation of CAD, while there was no significant change in the EGC/GN.ConclusionThe application of CAD devices devoted to distinct increases in gastric neoplasm detection according to different biopsy strategies, which implied that CAD devices demonstrated assistance on gastric neoplasm detection while varied effectiveness according to different implementation scenarios.
Predicting High‐Flow Nasal Cannula Oxygen Therapy Failure in Patients With Acute Hypoxaemic Respiratory Failure Using Machine Learning: Model Development and External Validation
Authors: Cheng Hongtao , Wang Zichen , Feng Mei , Tang Yonglan , Zheng Xiaoyu , Zhang Xiaoshen , Lyu Jun 
Published: October 2024

ABSTRACTAims and ObjectivesTo develop and validate a prediction model for high‐flow nasal cannula (HFNC) failure in patients with acute hypoxaemic respiratory failure (AHRF).BackgroundAHRF accounts for a major proportion of intensive care unit (ICU) admissions and is associated with high mortality. HFNC is a non‐invasive respiratory support technique that can improve patient oxygenation. However, HFNC failure, defined as the need for escalation to invasive mechanical ventilation, can lead to delayed intubation, prolonged mechanical ventilation and increased risk of mortality. Timely and accurate prediction of HFNC failure has important clinical implications. Machine learning (ML) can improve clinical prediction.DesignMulticentre observational study.MethodsThis study analysed 581 patients from an academic medical centre in Boston and 180 patients from Guangzhou, China treated with HFNC for AHRF. The Boston dataset was randomly divided into a training set (90%, n = 522) and an internal validation set (10%, n = 59), and the model was externally validated using the Guangzhou dataset (n = 180). A random forest (RF)‐based feature selection method was used to identify predictive factors. Nine machine learning algorithms were selected to build the predictive model. The area under the receiver operating characteristic curve (AUC) and performance evaluation parameters were used to evaluate the models.ResultsThe final model included 38 features selected using the RF method, with additional input from clinical specialists. Models based on ensemble learning outperformed other models (internal validation AUC: 0.83; external validation AUC: 0.75). Important predictors of HFNC failure include Glasgow Coma Scale scores and Sequential Organ Failure Assessment scores, albumin levels measured during HFNC treatment, ROX index at ICU admission and sepsis.ConclusionsThis study developed an interpretable ML model that accurately predicts the risk of HFNC failure in patients with AHRF.Relevance to Clinical PracticeClinicians and nurses can use ML models for early risk assessment and decision support in AHRF patients receiving HFNC.Reporting MethodTRIPOD checklist for prediction model studies was followed in this study.Patient or Public ContributionPatients were involved in the sample of the study.
Effect of build orientation on the fabrication trueness of additively manufactured implant‐supported complete arch interim fixed prostheses
Authors: Nejat Amir H. , Güven Mehmet Esad , Çakmak Gülce , Yilmaz Burak , Donmez Mustafa Borga 
Published: October 2024

AbstractPurposeTo evaluate how build orientation affects the fabrication trueness of additively manufactured implant‐supported complete arch prostheses by comparing them to subtractively manufactured high‐impact polymer‐based prostheses.Materials and MethodsAn edentulous maxillary model with four implants at canine and first molar regions bilaterally was digitized (ATOS Core 80 5MP) to design a reference implant‐supported complete arch prosthesis standard tessellation language file (RF‐STL). The STL file was used to manufacture prostheses additively in five different orientations according to the build platform (AM‐0, 0‐degree; AM‐15, 15‐degree; AM‐30, 30‐degree; AM‐45, 45‐degree; AM‐90, 90‐degree) or subtractively (SM‐HIP, control) (n = 10). The prostheses were digitized with an intraoral scanner (Trios 3) to generate their STLs (TF‐STL). After superimposing TF‐STLs over the RF‐STL with a metrology‐grade analysis software program (Geomagic Control X), surface deviations at four regions (overall, occlusal, overall without occlusal, and abutments), linear deviations at each abutment site, and interimplant distance deviations (canine‐to‐molar, canine‐to‐canine, and molar‐to‐molar) were calculated. One‐way analysis of variance and Tukey HSD tests were used for the statistical analyses (α = 0.05).ResultsAM‐90 mostly had the highest surface deviations, while AM‐0 had the lowest overall, and lowest overall without occlusal region deviations (p ≤ 0.022). SM‐HIP had the lowest occlusal region deviations (p < 0.001). AM‐90 had the highest linear deviations (p < 0.001). AM‐15 had higher canine‐to‐molar deviations than SM‐HIP (p = 0.042). SM‐HIP had the highest canine‐to‐canine deviations, while AM‐90 had higher deviations than AM‐0 and AM‐30 (p ≤ 0.026). AM‐45 and AM‐90 had the highest and AM‐0 had the lowest molar‐to‐molar deviations (p ≤ 0.013).ConclusionsAM‐0 mostly had higher trueness and AM‐90 mostly had lower trueness within tested outcomes. Additively manufactured prostheses mostly had lower canine‐to‐molar distances and higher molar‐to‐molar distances, whereas SM‐HIP prostheses consistently had higher distances than the design file.
A Meta‐Analytic Review of Personality and Teacher–Student Relationships
Authors: Mammadov Sakhavat , Avci Ayse Hilal 
Published: October 2024

ABSTRACTObjectiveThis meta‐analysis provides the first comprehensive synthesis of associations between student and teacher personality traits and the quality of teacher–student relationships.MethodFifty‐five studies met the eligibility criteria, contributing a total of 238 effect sizes. We used multivariate meta‐analysis with robust variance estimation (RVE) to model the dependency of effect sizes.ResultsStudent prosocial behavior (ρ = 0.59) and proactive personality (ρ = 0.48) were the strongest predictors of positive teacher–student relationship quality. All Big Five traits of students, except neuroticism, showed significant positive associations, with all correlations exceeding 0.4 when holding constant with all other moderators. Teacher agreeableness (ρ = 0.31) and conscientiousness (ρ = 0.29) yielded modest associations. Students with less emotional stability or aggressive behaviors were more likely to experience negative teacher–student relationships, such as conflict and dependency.ConclusionOur findings highlight the critical role of student personality in explaining the quality of teacher–student interactions. Multiple traits appear equally important, as indicated by comparable effect sizes. The literature is relatively limited when it comes to teacher personality. We were unable to examine teacher traits in relation to teacher–student conflict and dependency, but, overall, agreeable and conscientious teacher behaviors appeared to be important for favorable interactions, whereas teacher neuroticism may undermine the quality of such interactions.