bluuebunny/crossref_metadata_2025_split huggingface dataset:
“You [God] Gotta Go Through It With Me”: Black Women Navigating Spirituality During the Breast Cancer Journey
Authors: Owoyemi Praise , Denyse Tammie , Pageot Yrvane K. , Martin Kimberly J. , DeLuz K. Denise , Kim Jacqueline H. J. , Stanton Annette L. 
Published: January 2025

ABSTRACTBackgroundBlack women generally report high levels of spirituality. Less is known about Black women's spiritual coping with a cancer diagnosis. Persisting health disparities between Black breast cancer survivors and other racial groups necessitate examining whether spirituality can be a contextual and personal resource for Black women with breast cancer.AimsThis qualitative study's goals were to: (1) characterize positive and negative dimensions of spirituality in a sample of Black women diagnosed with breast cancer; and (2) examine whether and how women used spirituality during their cancer experience.MethodsThree Gatherings (i.e., culturally curated focus groups) were conducted as part of Project SOAR (Speaking Our African American Realities), a community‐academic partnership. In these all‐Black women Gatherings, participants (N = 37) discussed their breast cancer experience, including how spirituality played a role.ResultsThrough reflexive thematic analysis, six themes were identified: (1) faith is central to my identity even through challenging times; (2) meaningful, ineffective, or non‐existent support from my spiritual community; (3) grappling with spiritual discontent during breast cancer; (4) God is omnipotent; (5) spiritual anchors helped me persevere through the breast cancer journey; (6) breast cancer reflections enhanced my spiritual gratitude and growth.ConclusionsParticipants' experiences highlight the complexities of spirituality when confronting breast cancer. Many Black women reflected on the centrality of spirituality to their lives and cited spirituality as a resource and effective coping process during their cancer experience. Findings have important implications for understanding how spirituality can be incorporated to support Black women with breast cancer.
Unicentric Castleman's Disease of Paraspinal Origin Requiring Differentiation From Schwannoma: Case Report
Authors: Fujimoto Hazuki , Okamura Kayoko , Tauchi Shunsuke , Tsukamoto Rei , Kida Nanami , Ikeda Miho , Hatakeyama Yukihisa , Ohnishi Hisashi 
Published: January 2025

ABSTRACTUnicentric Castleman's disease (UCD) typically presents as an asymptomatic tumour in the anterior or middle mediastinum. Occurrence in the paravertebral region is comparatively rare and it requires differentiation from neurogenic tumours by imaging. In our patient, preoperative imaging findings were atypical of schwannoma. Contrast‐enhanced MRI of the thoracic region showed a muscle‐like mass in contact with the pleura on T1‐weighted images. T2‐weighted images showed high signal, especially at the margins. Diffusion‐weighted images showed diffusion restriction around the limbus, and contrast‐enhanced T1‐weighted images displayed strong enhancement of the mass. Diagnosis could not be made preoperatively, although UCD was suspected. Thoracoscopic tumour resection was performed for definitive diagnosis and treatment and postoperative diagnosis was hyaline‐vascular‐type UCD. Diagnosis of neurogenic tumours can be difficult by imaging alone. When imaging findings are atypical, a definitive diagnosis is required, with consideration of the possibility of UCD.
A Case of Cavitary Lung Metastasis From Prostate Cancer
Authors: Ohnaka Shinnosuke , Aoyama Mayumi , Arai Rino , Hattori Saya , Kubo Yusuke , Suzuki Shugo , Yoshimura Toshihiro , Ebihara Akinori , Morikawa Toshiaki , Shigemitsu Hidenobu , Kuwahira Ichiro 
Published: January 2025

ABSTRACTA 79‐year‐old man was found to have multiple nodules in the lung fields on chest computed tomography. Metastatic lung cancer was suspected; however, the primary site remained elusive. After 1 year of follow‐up, both the nodules had enlarged. After 2 years, one of the nodules continued to enlarge; however, the other nodule cavitated and decreased in size. Concomitantly, the previously observed fluorodeoxyglucose uptake in the cavitated nodules disappeared. A comprehensive search for the primary cancer included a thoracoscopic lung biopsy which revealed that these nodules were metastatic lung lesions from prostate cancer. Pathological examination revealed necrosis within these metastatic lesions. To date, only three case reports of cavitary lung metastases from prostate cancer have been published; however, no explanation has been provided for the pathological mechanism of cavitation. To our knowledge, this is the first case to provide a potential explanation for cavitation in metastatic lung lesions from prostate cancer.
Bayesian Spatial Relative Survival Model to Estimate the Loss in Life Expectancy and Crude Probability of Death for Cancer Patients
Authors: Leontyeva Yuliya , Huang Yuxin , Cramb Susanna , Cameron Jessica , Baade Peter , Mengersen Kerrie , Thompson Helen 
Published: January 2025

ABSTRACTTo date, there have not been any population‐based cancer studies quantifying geographical patterns of the loss in life expectancy (LLE) and crude probability of death due to cancer (). These absolute measures of survival are complementary to the more typically used relative measures of excess mortality and relative survival, and, together, they provide a fuller understanding of geographical disparities in survival outcomes for cancer patients. We propose using a spatially flexible parametric relative survival model in the Bayesian framework, which allows for the inclusion of spatial effects in hazard‐level model components. The relative survival framework is the preferred approach to analyze cancer survival data because it does not require information on the cause of death, and the Bayesian spatial modeling approach allows complex and robust small‐area estimation. The calculation of spatial estimates for LLE and are demonstrated using publicly available simulated datasets. The associated computer program scripts are available to support the understanding and implementation of our methodology in other spatial cancer modelling applications.
A Simple Sensitivity Analysis Method for Unmeasured Confounders via Linear Programming With Estimating Equation Constraints
Authors: Tang Chengyao , Zhou Yi , Huang Ao , Hattori Satoshi 
Published: January 2025

ABSTRACTIn estimating the average treatment effect in observational studies, the influence of confounders should be appropriately addressed. To this end, the propensity score is widely used. If the propensity scores are known for all the subjects, bias due to confounders can be adjusted by using the inverse probability weighting (IPW) by the propensity score. Since the propensity score is unknown in general, it is usually estimated by the parametric logistic regression model with unknown parameters estimated by solving the score equation under the strongly ignorable treatment assignment (SITA) assumption. Violation of the SITA assumption and/or misspecification of the propensity score model can cause serious bias in estimating the average treatment effect (ATE). To relax the SITA assumption, the IPW estimator based on the outcome‐dependent propensity score has been successfully introduced. However, it still depends on the correctly specified parametric model and its identification. In this paper, we propose a simple sensitivity analysis method for unmeasured confounders. In the standard practice, the estimating equation is used to estimate the unknown parameters in the parametric propensity score model. Our idea is to make inferences on the (ATE) by removing restrictive parametric model assumptions while still utilizing the estimating equation. Using estimating equations as constraints, which the true propensity scores asymptotically satisfy, we construct the worst‐case bounds for the ATE with linear programming. Differently from the existing sensitivity analysis methods, we construct the worst‐case bounds with minimal assumptions. We illustrate our proposal by simulation studies and a real‐world example.
Between‐ and Within‐Cluster Spearman Rank Correlations
Authors: Tu Shengxin , Li Chun , Shepherd Bryan E. 
Published: January 2025

ABSTRACTClustered data are common in practice. Clustering arises when subjects are measured repeatedly, or subjects are nested in groups (e.g., households, schools). It is often of interest to evaluate the correlation between two variables with clustered data. There are three commonly used Pearson correlation coefficients (total, between‐, and within‐cluster), which together provide an enriched perspective of the correlation. However, these Pearson correlation coefficients are sensitive to extreme values and skewed distributions. They also vary with data transformation, which is arbitrary and often difficult to choose, and they are not applicable to ordered categorical data. Current nonparametric correlation measures for clustered data are only for the total correlation. Here we define population parameters for the between‐ and within‐cluster Spearman rank correlations. The definitions are natural extensions of the Pearson between‐ and within‐cluster correlations to the rank scale. We show that the total Spearman rank correlation approximates a linear combination of the between‐ and within‐cluster Spearman rank correlations, where the weights are functions of rank intraclass correlations of the two random variables. We also discuss the equivalence between the within‐cluster Spearman rank correlation and the covariate‐adjusted partial Spearman rank correlation. Furthermore, we describe estimation and inference for the three Spearman rank correlations, conduct simulations to evaluate the performance of our estimators, and illustrate their use with data from a longitudinal biomarker study and a clustered randomized trial.
Non‐Parametric Estimation for Semi‐Competing Risks Data With Event Misascertainment
Authors: Wu Ruiqian , Zhang Ying , Bakoyannis Giorgos 
Published: January 2025

ABSTRACTThe semi‐competing risks data model is a special type of disease‐state model that focuses on studying the association between an intermediate event and a terminal event and proves to be a useful tool in modeling disease progression. The study of the semi‐competing risk data model not only allows us to evaluate whether a disease episode is related to death but also provides a toolkit to predict death, given that the episode occurred at a certain time. However, the computation of the semi‐competing risk models is a numerically challenging task. The Gamma‐Frailty conditional Markov model has been shown to be an efficient computation model for studying semi‐competing risks data. Building on recent advances in studying semi‐competing risks data, this work proposes a non‐parametric pseudo‐likelihood method equipped with an EM‐like algorithm to study semi‐competing risks data with event misascertainment under the restricted Gamma‐Frailty conditional Markov model. A thorough simulation study is conducted to demonstrate the inference validity of the proposed method and its numerical stability. The proposed method is applied to a large HIV cohort study, EA‐IeDEA, that has a severe death under‐reporting issue to assess the degree of adverse impact of the interruption of ART care on HIV mortality.
Insights on Fabrication Strategies and Energy Storage Mechanisms of Transition Metal Dichalcogenides Cathodes for Aqueous Zn‐Based Batteries
Authors: Li Shengwei , Das Pratteek , Wang Xiao , Li Chenyang , Wu Zhong‐Shuai , Cheng Hui‐Ming 
Published: January 2025

AbstractAqueous zinc‐based batteries (AZBs) are gaining widespread attention owing to their intrinsic safety, relatively low electrode potential, and high theoretical capacity. Transition metal dichalcogenides (TMDs) have convenient 2D ion diffusion channels, so they have been identified as promising host materials for AZBs, but face several key challenges such as the narrow interlayer spacing and the lack of in‐deep understanding energy storage mechanisms. This review presents a comprehensive summary and discussion of the intrinsic structure, charge storage mechanisms, and key fabrication strategies of TMD‐based cathodes for AZBs. Firstly, the structural features including phase types and electrical properties of TMDs are underscored. Then, the charge storage mechanisms and activation principles in TMDs are elaborated along with the discussions about their influence on electrochemical performance. Afterward, specific attention is focused on the fabrication strategies of high‐performance TMD cathodes, including interlayer expansion, defect creation, phase transition, and heteroatom doping. Finally, the key challenges are considered and potential effective strategies are proposed to design high‐performance aqueous Zn‐TMDs batteries.
Modulating Electronic Density of Single‐Atom Ni Center by Heteroatoms for Efficient CO2 Electroreduction
Authors: Chen Yang , Pan Xiaoli , Li Lin , Chen Meixin , Cao Hongchen , Zhao Yang , Wang Xiaodong , Lin Jian 
Published: January 2025

AbstractSingle‐atom catalysts (SACs) with unique geometric and electronic configurations have triggered great interest in many important reactions. However, controllably modulating the electronic structure of metal centers to enhance catalytic performance remains a challenge. Here, the electronic structure of Ni centers over Ni1‐NC SACs by introducing electron‐rich phosphorus or electron‐deficient boron for electrochemical CO2 reduction (CO2RR) is systematically tailored. It is found that the Ni1‐PNC with Ni1‐N3P site exhibits superior performance with a current density of 14.6 mA cm−2 and a Faradaic efficiency of 90.6% at −0.8 V versus RHE for CO production, far exceeding Ni1‐NC and Ni1‐BNC SACs. Detailed characterizations and theoretical calculations reveal a linear relationship between the valence state of Ni species and the CO2RR performance. The incorporation of P species facilitates the electronic localization around the Ni1 center, significantly promoting the adsorption of CO2 and the formation of key *COOH intermediate to enhance CO2RR. This work provides a feasible approach to quantitatively manipulate the electronic structure of single‐atom metal sites and to rationally design highly efficient catalysts for boosted performance.
Nanomaterials‐Induced Pyroptosis: Advancing Novel Therapeutic Pathways in Nanomedicine
Authors: Yu Siqi , Zhang Yumo , Zhou Zhuoran , Li Jiulong , Meng Huan 
Published: January 2025

AbstractPyroptosis, a form of programmed cell death characterized by cell lysis and inflammation, has significant implications for disease treatment. Nanomaterials (NMs), with their unique physicochemical properties, can precisely modulate pyroptosis, offering novel and intelligent therapeutic strategies for cancer, infectious diseases, and chronic inflammatory conditions with targeted activation and reduced systemic toxicity. This review explores the mechanisms by which NMs regulate pyroptosis, comparing molecular and NM inducers, and examines the role of intrinsic properties such as size, shape, surface charge, and chemical composition in these processes. It also discusses the balance between the beneficial and adverse effects of NM‐induced pyroptosis, highlighting targeted delivery systems, surface modifications, and controlled activation as strategies to enhance therapeutic efficacy and intelligence while minimizing toxicity. Notably, mRNA‐based nanomedicine can be precisely and intelligently designed to activate pyroptosis, achieving desired therapeutic outcomes tailored to the evolving microenvironment of diseases. By understanding these interactions, the therapeutic potential of NMs can be harnessed to develop innovative treatments and manage pyroptosis‐associated diseases safely, effectively, and intelligently. This review also highlights their transformative potential in clinical applications.
Cosim‐Gres: Towards Similarity Queries Optimization Inside RDBMS
Authors: Eleutério Igor Alberte R. , de Oliveira Willian D. , Teixeira Larissa R. , Vespa Thiago G. , Silva William Z. , Traina Agma Juci M. , Traina Caetano 
Published: January 2025

ABSTRACTIntroductionThis paper presents CoSIM‐Gres, a new module implemented over Postgres capable of performing exact similarity searches to answer both Range and ‐ queries, using any of three access methods: Sequential Access, the Slim‐tree Metric Access Method (MAM), or the Gist R‐tree. To the best of the authors' knowledge, this is the first system currently capable of performing both types of queries with the possibility of choosing different access methods while maintaining full integration of the similarity‐related syntax with the other SQL statements.ContributionOur main contribution is an in‐depth comparison of cases when each access method is better for processing similarity queries. It is an essential first step that any attempt to optimize similarity queries within DBMS must consider.MethodsExperiments were performed to compare Slim‐tree with Sequential Access and Gist R‐tree available in Postgres Cube extension, analyzing the impact of varying dimensionality and distance functions on the execution time.ResultsThey show that the Slim‐tree is up to 18.0 times faster than Sequential Access, whereas the Gist R‐tree may be up to 5.8 times faster than the Slim‐tree, although the Gist R‐tree in Postgres is restricted to index only dimensional data, with at most 100 dimensions, and is applicable only for ‐ queries. The experiments also revealed that the growth of data dimensionality negatively impacts both the MAM and Gist R‐tree performance when compared to the Sequential Access. Also, more complex distance functions reduce the advantage of MAM over Sequential Access. This makes choosing the best option to execute a query a decision that should be carefully evaluated before the query execution.
An Event Frequency‐Inverse Session Frequency Based Weighting Mechanism for Data Embedding Methodologies
Authors: Tasgetiren Nail , Safak Ilgin , Aktas Mehmet S. 
Published: January 2025

ABSTRACTContextWith the rapid increase in data complexity and volume, analyzing and understanding large‐scale datasets has become a critical challenge, especially in domains like e‐commerce. This paper addresses this challenge by introducing a novel business process that utilizes an event frequency‐inverse session frequency (EF‐ISF) based weighting mechanism for embedding user navigational behavior in e‐commerce websites.ObjectiveThe primary research problem tackled in this study is the detection of patterns and distributions within user behavior data, which is often complicated by dynamic page content and session sparsity. We aim to enhance the interpretability and accuracy of user behavior analysis by integrating EF‐ISF with various embedding techniques, including Word2Vec, Node2Vec, DeepWalk, Struc2Vec, and LSTM Autoencoder.MethodologyOur approach is particularly effective in datasets where page refreshes lead to event repetitions, where sequential events with temporal dependencies are prevalent, and where event distributions across sessions are sparse. By applying this methodology across multiple e‐commerce datasets, we observe consistent performance in clustering quality, successfully detecting underlying patterns and groups within the data.ResultsA prototype implementation demonstrates the practical utility of the proposed method, with evaluation metrics confirming that EF‐ISF weighting not only enhances the embeddings but also facilitates a more nuanced and significant segmentation of users' browsing behaviors.ConclusionThese findings provide a valuable contribution to the field of e‐commerce data analytics, offering businesses a refined approach to optimizing user experience and engagement through a deeper understanding of user behavior patterns. This methodology can significantly improve the quality of insights derived from user behavior data, ultimately leading to better decision‐making and enhanced user satisfaction.
Flexural design of alkali‐activated reinforced concrete beams: Evaluating model errors using standards for Portland concrete
Authors: Lenticchia Erica , Vescovi Marialorenza 
Published: January 2025

AbstractThe article examines the potential of utilizing existing standard codes, although originally designed for Portland cement, in the flexural design of geopolymer (GP) concrete beams. In particular, the article collects experimental data from the literature on the cracking and ultimate moment of reinforced GP concrete beams, with and without steel fibers (SFs). The experimental moments are compared with those calculated using different standard codes for Portland cement (2nd generation EC2, ACI318, ACI363, AS3600) and GP concrete (SATS199). The purpose of this comparison is to evaluate the model error obtained with the different codes. The same procedure is applied on experimental data from RC beams made with Portland cement. To study the model error, the results obtained with different precursor materials (granulated blast furnace slag or fly ash), concrete compressive strengths, and reinforcement percentages are analyzed. The different codes have different levels of conservatism, resulting in different average model errors. However, within the same code, the average model errors for GP and Portland concretes are similar. Therefore, the existing codes can be used to calculate the cracking moment and ultimate moment of GP concrete beams. However, some uncertainty remains for the ultimate moment of over‐reinforced beams, for which the number of experimental data is still limited.
Rapid and Environment‐Friendly LC–MS/MS for Simultaneous Analysis of Amino Acids in Veterinary Medicine
Authors: Chae HyunYoung , Byun Jae Won , Ku Bok‐Kyung , Jeong Ok‐Mi , Her Moon , Kim TaeWan , Kang JeongWoo 
Published: January 2025

ABSTRACTBackgroundAmino acid supplements are crucial for animal health and productivity. Traditional analysis methods face limitations like complexity, long testing times and toxic reagents. Therefore, a more efficient and reliable method is needed.ObjectivesThis study aimed to develop and validate an efficient method for the simultaneous analysis of eight amino acids commonly used in veterinary medicine: alanine, arginine, glutathione, lysine, ornithine, methionine, threonine and tryptophan.MethodsWe analysed eight veterinary amino acid preparations. From 100 registered products, we selected 35. After confirming ingredients, we diluted them to 1 mg/L with 50% acetonitrile (ACN) and filtered them using a 0.2 µm RC filter for liquid chromatography with tandem mass spectrometry (LC–MS/MS) analysis.ResultsAll analytes showed excellent linearity (r2 > 0.99) within 0–10 mg/L. The limits of detection (LOD) ranged from 0.04 to 0.83 mg/L, and the limits of quantification (LOQ) ranged from 0.12 to 2.52 mg/L. Average recovery ranged from 92.96% to 105.61%, with relative standard deviations (RSD) from 0.27% to 3.50%, meeting CD 2002/657/EC standards. Six out of the 35 products (17.14%) did not meet regulations.ConclusionsThe method developed in this study offers an efficient and reliable approach for the simultaneous analysis of essential amino acids in veterinary medicine. Implementing this method can improve the quality control of amino acid products, enhancing animal health and productivity. This study also highlights the need for stringent domestic management and continuous monitoring. By overcoming traditional technique limitations, this validated method ensures the quality and efficacy of amino acid supplements in the veterinary industry.