bluuebunny/crossref_metadata_2025_split huggingface dataset:
Advanced lung cancer inflammation index is associated with mortality in critically ill patients with heart failure
Authors: Sun Xiaoqian , Zhang Xinyu , Tang Rui , Tian Jiangyue , Li Ying , Hu Xiaoxia , Sun Ziru , Wu Anhu , Xiao Jie , Dong Mei , Yao Guihua , Lu Huixia 
Published: October 2024

AbstractAimsNutrition and inflammation status play a vital role in the prognosis of patients with heart failure (HF). This study aimed to investigate the association between the advanced lung cancer inflammation index (ALI), a novel composite indicator of inflammation and nutrition, and short‐term mortality among critically ill patients with HF.MethodsThis retrospective study included 548 critically ill patients with HF from the MIMIC‐IV database. ALI was computed using body mass index, serum albumin and neutrophil–lymphocyte ratio. The primary endpoint was all‐cause in‐hospital mortality, and the secondary endpoint was 90 day mortality. Kaplan–Meier survival curve analysis with long‐rank test and Cox proportional hazards regression models were employed to assess the relationship between baseline ALI and short‐term mortality risk. The incremental predictive ability of ALI was evaluated by C‐statistic, continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI).ResultsThe average age of 548 patients was 72.2 (61.9, 82.1) years, with 60% being male. Sixty‐three patients (11.5%) died in the hospital, and 114 patients (20.8%) died within 90 days of intensive care unit admission. The Kaplan–Meier analysis revealed that the cumulative incidences of both in‐hospital and 90 day mortality were significantly higher in patients with lower ALI (log‐rank test, in‐hospital mortality: P < 0.001; 90 day mortality: P < 0.001). The adjusted Cox proportional hazard model revealed that ALI was inversely associated with both in‐hospital and 90 day mortality after adjusting for confounders [hazard ratio (HR) (95% confidence interval) (CI): 0.97 (0.94, 0.99), P = 0.035; HR (95% CI): 0.62 (0.39, 0.99), P = 0.046]. A linear relationship was observed between ALI and in‐hospital mortality (P for non‐linearity = 0.211). The addition of ALI significantly improved the prognostic ability of GWTG‐HF score in the in‐hospital mortality [C‐statistic improved from 0.62 to 0.68, P = 0.001; continuous NRI (95% CI): 0.44 (0.20, 0.67), P < 0.001; IDI (95% CI): 0.03 (0.01, 0.04), P < 0.001] and 90 day mortality [C‐statistic improved from 0.63 to 0.70, P < 0.001; continuous NRI (95% CI): 0.31 (0.11, 0.50), P = 0.002; IDI (95% CI): 0.01 (0.00, 0.02), P = 0.034]. Subgroup analysis revealed stronger correlations between ALI and in‐hospital mortality in males and patients aged over 65 years (interaction P = 0.031 and 0.010, respectively). The C‐statistic of in‐hospital mortality in patients over 65 years was 0.66 (95% CI: 0.58, 0.74).ConclusionsALI at baseline can independently predict the risk of short‐term mortality in critically ill patients with HF, with lower ALI significantly associated with higher mortality. Further large prospective research with extended follow‐up periods is necessary to validate the findings of this study.
Forecasting Expected Shortfall and Value‐at‐Risk With Cross‐Sectional Aggregation
Authors: Wang Jie , Wang Yongqiao 
Published: October 2024

ABSTRACTThe combination of the conditional autoregressive value‐at‐risk (CAViaR) process with the Fissler–Ziegel (FZ) loss function generates a recently emerging framework (CAViaR‐FZ) for forecasting value‐at‐risk (VaR) and expected shortfall (ES). However, existing CAViaR‐FZ models typically overlook the presence of long‐range dependence, a stylized fact of financial time series. This paper proposes a long‐memory CAViaR‐FZ model using the cross‐sectional aggregation (CSA) method. The CSA method is well‐recognized for its ability to generate a long‐memory process by aggregating an infinite number of short‐memory processes cross‐sectionally. The proposed CSA‐CAViaR‐FZ model flexibly captures long‐memory dynamics in both VaR and ES and includes the original short‐memory CAViaR‐FZ model as a special case. Simulation and empirical results demonstrate that the proposed model outperforms various competing models.
Predicting Equity Premium: A New Momentum Indicator Selection Strategy With Machine Learning
Authors: Qu Yong , Yuan Ying 
Published: October 2024

ABSTRACTWe propose a new momentum‐determined indicator‐switching (N‐MDIS) strategy, harnessing the power of machine learning to enhance the accuracy of equity premium prediction. Specifically, we re‐examine the regime‐dependent feature of univariate predictive regression relative to the benchmark. Furthermore, we investigate the prediction mechanism of the momentum‐determined indicator‐switching (MDIS) strategy and validate the significance of market regime information for the MDIS. Our findings demonstrate an overwhelmingly superior ex‐post forecasting performance compared with the MDIS. More notably, our empirical results substantiate that machine learning greatly aids in momentum indicator selection. The results show that the N‐MDIS with machine learning generates more accurate ex‐ante equity premium forecasts than both MDIS strategy and N‐MDIS strategy with logistic regression, yielding statistically and economically significant results. Moreover, our new approach exhibits robust forecasting performance across a series of robustness tests.
The activation of asparagine synthetase by the transcription factor FOXM1 plays a pivotal role in the initiation and progression of ESCC
Authors: Lian Jing‐Jing , Li Zhao‐Xing , Lin Hui‐ling , Sun Ming‐Chuang , Wu Hao , Feng An‐Qi , Fang Kang , Wang Xiao‐Yuan , Xu Ai‐Ping , Chu Yuan , Zhang Li , Chen Tao , Xu Mei‐Dong 
Published: October 2024

AbstractThis study explores the role of the transcription factor FOXM1 in the initiation and progression of oesophageal squamous cell carcinoma (ESCC). Our findings reveal that FOXM1 is highly expressed in ESCC and correlates with the prognosis of the disease. The relationship between FOXM1 and asparagine synthetase (ASNS) is investigated, and the study demonstrates that FOXM1 activates ASNS, impacting the tumour stemness of ESCC. In this study, we reveal the association between FOXM1 and ESCC development, as well as FOXM1’s promotion of migration and proliferation in ESCC cells. The study also highlights FOXM1’s regulation of ASNS transcription and the functional role of ASNS in ESCC metastasis and growth. Furthermore, the study explores the impact of FOXM1 and ASNS on ESCC stemness and their potential implications for chemotherapy resistance.
Beyond myeloid neoplasms germline guidelines: Validation of the thresholds criteria in the search of germline predisposition variants
Authors: Mestre Julia , Chaparro Lorea , Manzanares Ana , Xicoy Blanca , Zamora Lurdes , Sole Francesc , Calvete Oriol 
Published: October 2024

AbstractIntroductionGermline predisposition to myeloid neoplasms can be suspected in patients younger than 50 years or when harboring mutations with a variant allele frequency (VAF) higher than 30% for point mutations in specific genes. To investigate the VAF thresholds’ accuracy we have explored the prevalence of germline variants below the 30% VAF threshold.MethodsA total of 40 variants with VAF lower than 30% in bone marrow samples of myeloid neoplasm patients were selected and studied in CD3+ cells.ResultsAll the selected variants were not found in CD3+ cells except one variant in the SF3B1 gene. However, the whole series was found somatic. Selected variants were also evaluated with our previously studied series of 52 variants with VAF higher than 30%.ConclusionOur study suggests that variants with VAF below 30% are strong somatic candidates but the variants with VAF higher than 30% cannot be considered of germline origin.
Synthesis of Benzannulated Spiroketals Derived From Stigmasterol and Sitosterol by Pd‐Catalyzed Spirocyclization. NMR and X‐ray Characterization. Evaluation of Cytotoxicity and Anti‐Inflammatory Activity
Authors: Garcia‐Santos William H. , Mayorquin‐Torres Martha C. , Campos‐Xolalpa Nimsi , Pérez‐Gutiérrez Salud , Flores‐Álamo Marcos , Iglesias‐Arteaga Martín A. 
Published: October 2024

ABSTRACTFive new benzannulated steroid spiroketals were synthesized by Pd‐catalyzed spiroketalization of 5α and 5β‐alkynediols derived from stigmasterol and sitosterol. The detailed nuclear magnetic resonance (NMR) and X‐ray characterization of the newly obtained spiroketals are presented. While the obtained compounds showed null or very low cytotoxicity, two of them inhibited more than 60% of the nitrous oxide production in J774A.1 macrophages stimulated with LPS, showing promising properties as anti‐inflammatory agents.
Gender of a manager and firm performance in Africa: Does the business environment play a moderating role?
Authors: Okumu Ibrahim Mike , Nathan Sunday , Bbaale Edward 
Published: October 2024

AbstractThis study explores the moderating role of the business environment in the relationship between top manager gender and firm performance, using firm‐level data from 29 African countries. Controlling for endogeneity and country fixed effects, we find that female‐managed firms generally underperform male‐managed firms, except among large firms where female managers excel. The performance gap is exacerbated by a weak business environment, highlighting the need for reforms to close the managerial gender gap in Africa. Strengthening the business environment is essential for improving female‐led firm performance and by extension promoting gender equality in African business leadership.
Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression
Authors: Lee Do Weon , Han Hyuk‐Soo , Ro Du Hyun , Lee Yong Seuk 
Published: October 2024

AbstractMany models using the aid of artificial intelligence have been recently proposed to predict the progression of knee osteoarthritis. However, previous models have not been properly validated with an external data set or have reported poor predictive performances. Therefore, the purpose of this study was to design a machine learning model for knee osteoarthritis progression, focusing on high validation quality and clinical applicability. A retrospective analysis was conducted on prospectively collected data, using the Osteoarthritis Initiative data set (5966 knees) for model development and the Multicenter Osteoarthritis Study data set (3392 knees) for validation. The analysis aimed to predict Kellgren–Lawrence grade (KLG) progression over 4–5 years in knees with initial KLG of 0, 1, or 2. Possible predictors included demographics, comorbidities, history of meniscectomy, gait speed, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, and radiological findings. The Random Forest algorithm was employed for the predictive model development. Baseline KLG, contralateral knee osteoarthritis, lateral joint space narrowing (JSN) grade, BMI, medial JSN grade, and total WOMAC score were six features selected for the model in descending order of importance. Odds ratios of baseline KLG, contralateral knee osteoarthritis, and lateral JSN grade were 1.76, 2.59, and 4.74, respectively (all p < 0.001). The area‐under‐the‐curve of the ROC curve in the validation set was 0.76 with an accuracy of 0.68 and an F1‐score of 0.56. The progression of knee osteoarthritis in 4 ~ 5 years could be well‐predicted using easily available variables. This simple and validated model may aid surgeons in knee osteoarthritis patient management.
Application of surfactants for the resolution of emulsions and suspensions in slop oil storage tanks, cleaning, and final disposal
Authors: López José , Marfisi Valladares Shirley , Lobo Mario , Guerrero Alix , Carvajal Carlos 
Published: October 2024

AbstractIn order to provide environmental solutions for the treatment of oily residues (slop oil) from refineries, formulations with surfactants were proposed according to the type of dispersed system of the slop (crude oil emulsified with water and/or solid particles). Samples were collected in 12 tanks located at the Oxialquilados Venezolanos C.A., Barcelona Plant (Anzoátegui, Venezuela), performing physicochemical tests for the identification of the dispersed system (solubility, wettability, stability, water content) and microscopic observations (morphology and particle size). The results indicated heterogeneous slop samples with a water content of 2%–60% vol/vol consisting of single or multiple emulsions, with droplet sizes between approximately 10 and 30 micron; others formed by sludge or suspension (solids/oil/water). For the destabilization of these systems, aqueous and organic cleaning solutions were designed, determining the percentage of oil separated in the bottle tests at optimal and simulated field conditions. Field tests with volume scaling of the slop tank reported efficiencies of 63%, 85%, and 100% when treating the slop TK‐17, TK‐36, EE, respectively; for the mixture (Pulmon‐2) an efficiency of 47%. By combining heat treatment and two demulsifiers was possible to treat the slop TK‐17 (multiple emulsion). A considerable volume of water can be drained from the tanks for use in the plant. In conclusion, the surfactant formulas were effective in the recovery of a significant amount of crude oil, making it feasible to return it to the generating entity.
Postoperative Complications in Lingual Versus Palatine Tonsillectomies
Authors: Cottone Chloe , Rosi‐Schumacher Mattie , Gawel Erin M. , Corbin Alexandra F. , Riccio David , Carr Michele M. 
Published: October 2024

ObjectiveThe aim of this study was to investigate the risks of lingual tonsillectomy (LT) in a large cohort and compare these risks to those of palatine tonsillectomy (PT).MethodsA retrospective cohort study was conducted using data from the United States collaborative network within TriNetX. The LT group was defined using Current Procedural Terminology (CPT) code 42870 and PT group using CPT codes 42820, 42821, 42825, or 42826. Groups were further subdivided into pediatric and adult populations and matched based on propensity scores within the cohorts. Complications occurring within 14 days of procedure were compared within each cohort.ResultsThere were 1,357 adult patients (mean age, 42.9 years) and 863 pediatric patients (mean age, 8.1 years). Adults who had LT were more likely to experience postoperative dysphagia (OR = 2.6, p < 0.001) and require admission to the hospital (OR = 4.3, p < 0.001) or intensive care unit (OR = 6.1, p < 0.001). There was no significant difference in bleeding between adult PT and LT groups, occurring at rates of 3.8% and 4.4%, respectively (p = 0.50). Pediatric patients who had LT were also more likely to experience postoperative dysphagia (OR = 2.4, p = 0.017) and require admission to the hospital (OR = 8.2, p < 0.001) or intensive care unit (OR = 2.7, p = 0.012). The postoperative bleed rate was 3.2% in the pediatric PT cohort, which was 2.4 times higher compared to those who underwent LT (1.5%, p = 0.016).ConclusionPostoperative complications after lingual tonsillectomy are more common than after palatine tonsillectomy in both adults and children.Level of Evidence3 Laryngoscope, 135:1054–1059, 2025
Optimal financing strategies for low‐carbon supply chains: A Stackelberg game perspective
Authors: Wang Lei , Zhang Lin , Zhang Xiaoli 
Published: October 2024

AbstractThis study constructs a Stackelberg game model between low‐carbon manufacturers and capital‐constrained retailers. Considering the manufacturer's financing model, the manufacturer's investment model, and the internal blended financing model, it studies the optimal wholesale price of manufacturers. This paper investigates the impact of consumers' low‐carbon preference, the financing interest rate of manufacturers, investment ratio, investment return on carbon emission reduction investment, and supply chain pricing. The conditions for low‐carbon supply chain participants to choose the best financing mode and the impact of different financing models on the performance of low‐carbon supply chains were obtained.
Financial hedging incentive contracts in global supply chains: A distributionally robust approach
Authors: Li Xiaoyi , Yu Hui , Sun Caihong 
Published: October 2024

AbstractThis paper developed a global supply chain with a supplier and a retailer in different countries. When exchange rate and demand risks are concentrated in retailer, a distributionally robust approach is used to formulate an optimized robust ordering strategy. Furthermore, the effect of financial hedging incentive contracts on the robust decisions and the profits of the global supply chain is explored. Our findings show that the correlation between exchange rate and demand does not affect the robust decisions of retailer. The effectiveness of financial hedging incentive contracts depends on the trade‐off between transaction costs of financial hedging and the degree of supplier incentives and the growth rate of order quantity.
Facile synthesis of triple‐network organo‐hydrogel for all‐temperature flexible supercapacitors
Authors: Cao Yang , Qing Liming , Wang Yan , Liu Zixuan , Gu Ning , Bian Yuehao , Fu Qiang , Sun Youyi 
Published: October 2024

AbstractA new triple‐network organo‐hydrogel with high anti‐freezing and thermally‐stable performance is prepared for application in all‐temperature flexible supercapacitor. It is composed of boric acid/graphene/polyvinyl alcohol matrix and H2SO4/dimethyl sulfoxide mixing solution. The incorporation of graphene and boric acid into polymer matrix can improve thermal stability and ionic conductivity of organo‐hydrogel. The H2SO4 and dimethyl sulfoxide are key roles for improving anti‐freezing of organo‐hydrogel. The organo‐hydrogel exhibits high ionic conductivity of 1.6 and 3.1 S/m at −80 and 90°C, respectively. As a result, the assembled supercapacitor delivers a high capacitance retention of 84.5% and 113.3% at ultra‐low temperature (−80.0°C) and high temperature (90.0°C), respectively. The work provides a new route to design and prepare flexible supercapacitor with wide temperature range.
Polyhydroxybutyrate/poly(ε‐caprolactone)‐based electrospun membranes loaded with amoxicillin‐potassium clavulanate halloysite nanotubes for biomedical applications
Authors: Verma Deepak , Okhawilai Manunya , Senthilkumar Nangan , Thirumalaivasan Natesan , Incharoensakdi Aran , Uyama Hiroshi 
Published: October 2024

AbstractBiopolymers exhibit distinct properties for biomedical applications. Different biopolymer classes are utilized for various applications, for example antibacterial properties, drug delivery, tissue engineering, tissue scaffolds etc. In the present investigation, a nano‐bioengineering approach was followed to prepare polyhydroxybutyrate and polycaprolactone polymer‐based drug‐loaded halloysite nanotube electrospun membranes for biomedical applications. Functionalized halloysite nanotubes ((3‐aminopropyl)triethoxysilane acid treated halloysite nanotubes) at different weight percentages (1, 3, 5 and 7 wt%) were loaded with a broad‐spectrum antibiotic amoxicillin trihydrate‐potassium clavulanate, incorporated into the electrospun membranes, and characterized by different techniques such as XRD, FTIR, SEM, TEM and TGA. Different physical and mechanical properties were evaluated, such as porosity, water uptake, water vapor transmission rate, wettability and tensile properties. The developed membranes exhibited good in vitro biological properties, for example antibacterial, effective cell migration and less toxicity, as confirmed by disk diffusion, MTT (3‐(4,5‐dimethylthiazolyl‐2)‐2,5‐diphenyltetrazolium bromide) and cell scratch assays. A sustained drug release profile was observed from all the developed membranes. Overall results on the characterization of the developed membranes confirm the suitability of their use for different biomedical applications and as a wound dressing application. © 2024 Society of Chemical Industry.
Explaining preservice teachers' intention and behavior to use technology‐enabled learning in China: A multi‐group analysis across experiences
Authors: Hou Mingdi , Shen Yafei 
Published: October 2024

AbstractThis study examines the development of preservice teachers' intention and behavior to use of Technology‐Enabled Learning (TEL) within the Theory of Planned Behavior (TPB) framework. Despite growing interest, the effective integration of TEL among preservice teachers remains a challenge. Engaging 1023 participants ‐ senior undergraduates with practical TEL experience in real classroom settings ‐ the study employed structural equation modeling (SEM) to analyze the relationships between key factors ‐ experience, subjective norms, attitudes, and perceived behavioral control ‐ and their influence on the intention and behavior to use of TEL. The findings revealed that behavioral intention did not significantly influence the actual use of TEL, whereas perceived behavioral control acted both as a determinant of TEL use and as a mediator in the relationship between subjective norms and TEL usage. Additionally, while subjective norms showed minimal impact on behavioral intention, attitudes and perceived behavioral control emerged as crucial antecedent variables and mediators. The multi‐group analysis using SEM revealed that preservice teachers' experience with TEL moderated the first half of the mediating pathway between subjective norms, perceived behavioral control and the actual use of TEL. Notably, multi‐group analysis indicated that as preservice teachers gained more experience with TEL, the influence of subjective norms on perceived behavioral control weakened. This study contributes to a deeper understanding of the TPB framework and its extended models in the context of TEL in teacher education, offering valuable insights for developing more effective TEL training and guidance strategies, ultimately aiming to enhance preservice teachers' proficiency and engagement with TEL.
Walking the Talk: “Reflexivity” to Advance Integration of Patient Reported Outcomes for Cancer Care Screening
Authors: Przybylak‐Brouillard Antoine , Nugus Peter , Lambert Sylvie 
Published: October 2024

ABSTRACTIn this commentary, we propose the use of video‐reflexive ethnography (VRE) as a means to support integration of patient‐reported outcomes (PROs) in cancer care screening. As for any policy or intervention, the optimization of PROs depends on moving beyond their mere formal introduction, and depends on the integration of PROs in the everyday practice contexts of health care professionals (HPEs). The use of VRE allows for video‐playback sessions among oncology professionals to support team‐based learning and practice‐change grounded in “reflexivity.” Through a review of previous methods used to support organizational change in healthcare settings (e.g., policies, quality improvement initiatives, simulation sessions), we present some unsung advantages of VRE that can be applied to a complex integrated setting, such as cancer care. As opposed to other methods to create change, VRE does not dictate new measures, but rather supports “bottom‐up” provider‐initiated changes to health care practices and contexts, grounded in collaborative day‐to‐day practice. We argue that VRE optimizes PROs in cancer care by facilitating their effective and sustainable integration, to promote improved patient care.