bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trends in electronic health record metadata use for management purposes
Authors: Xu Nuo , Badwaik Ishwar , Lee Gunwoo , Ford Eric W. 
Published: February 2025

AbstractObjectiveThis study aims to analyze hospitals' adoption and integration of electronic health record (EHR) metadata into their management processes.DesignThe study compares the rates of EHR metadata utilization across various hospitals over time. Hospitals' self‐reported use of EHR metadata is drawn from the AHA‐IT Supplements from 2018 to 2020. An analysis of metadata utilization by EHR vendors is also provided.MethodThe study uses Bass diffusion modeling to estimate EHR adoption parameters by fitting adoption rate data from 2018 to 2020, using Excel Solver to minimize prediction errors. The estimated internal and external influence coefficients reveal which factor primarily drives adoption, while the diffusion model enables future projection of tipping point and adoption level.ResultsAnalysis of EHR metadata utilization rates from 2018 to 2020 find a significant trend towards the integration of this data into hospital management practices. Among health systems responding to the items of interest, 69% of them are already using EHR metadata, and it is projected that nearly all will do so by 2035. Further, metadata use varied significantly depending on the vendor.DiscussionThe study underscores that hospital managers' intrinsic motivations, rather than external demands, are driving EHR metadata. As innovations with greater intrinsic appeal spread more rapidly and have greater staying power, EHR metadata use will continue to grow. These trends are indicative of the growing importance of EHR metadata in management decision‐making, clinical quality improvement, and optimizing workforce efficiency.ConclusionsEHR metadata holds great promise as a managerial and health service research source. The tools' utilities would be enhanced if EHR vendors created uniform metrics.
Sharp convergence rate on Schrödingertype operators
Authors: Wang Meng , Zhao Shuijiang 
Published: February 2025

AbstractFor Schrödinger‐type operators in one dimension, we consider the relationship between the convergence rate and the regularity for initial data. By establishing the associated frequency‐localized maximal estimates, we prove sharp results up to the endpoints. The optimal range for the wave operator in all dimensions is also obtained.
Texture Analysis of Magnetic Resonance Imaging: Differentiating Multicystic Ameloblastomas From Central Vascular Malformations
Authors: Muraoka Hirotaka , Kaneda Takashi , Kondo Takumi , Otsuka Kohei , Tokunaga Satoshi 
Published: February 2025

ABSTRACTPurposeThe aim of this study was to distinguish multicystic ameloblastomas (MABs) from central vascular malformations (CVMs) using magnetic resonance imaging (MRI) texture analysis.Materials and MethodsWe analyzed data from participants who underwent MRI between April 2006 and November 2021 at our university hospital's outpatient department. Participants were divided into two groups based on the lesion type. MRI texture features were the predictor variables. The outcome variable was the lesion type: MAB or CVM. Covariates included the demographic variables of age and sex. The Mann–Whitney U test was used to analyze bivariate statistics. Receiver operating characteristic curve analysis was used to assess the ability of MRI texture features to distinguish between lesions. Statistical significance was set at p < 0.05.ResultsThe MRI data of 27 participants (mean age ± standard deviation, 43.44 ± 17.49 years [range, 9–71], 18 men) were analyzed (22 had MAB, and 5 had CVM). The six MRI texture features differed significantly between MAB and CVM (p < 0.05). Areas under the curve values of MRI texture features ranged from 0.84 to 0.96.ConclusionThese results suggest that MABs and CVMs may be distinguished by analyzing MRI texture features, thus helping clinicians in decision‐making while selecting appropriate treatment.
Simpler Protein Domain Identification Using Spectral Clustering
Authors: Cazals Frédéric , Herrmann Jules , Sarti Edoardo 
Published: February 2025

ABSTRACTThe decomposition of a biomolecular complex into domains is an important step to investigate biological functions and ease structure determination. A successful approach to do so is the SPECTRUS algorithm, which provides a segmentation based on spectral clustering applied to a graph coding inter‐atomic fluctuations derived from an elastic network model. We present SPECTRALDOM, which makes three straightforward and useful additions to SPECTRUS. For single structures, we show that high quality partitionings can be obtained from a graph Laplacian derived from pairwise interactions—without normal modes. For sets of homologous structures, we introduce a Multiple Sequence Alignment mode, exploiting both the sequence based information (MSA) and the geometric information embodied in experimental structures. Finally, we propose to analyze the clusters/domains delivered using the so‐called ‐family‐matching algorithm, which establishes a correspondence between domains yielded by two decompositions, and can be used to handle fragmentation issues. Our domains compare favorably to those of the original SPECTRUS, and those of the deep learning based method Chainsaw. Using two complex cases, we show in particular that SPECTRALDOM is the only method handling complex conformational changes involving several sub‐domains. Finally, a comparison of SPECTRALDOM and Chainsaw on the manually curated domain classification ECOD as a reference shows that high quality domains are obtained without using any evolutionary related piece of information. SPECTRALDOM is provided in the Structural Bioinformatics Library, see http://sbl.inria.fr and https://sbl.inria.fr/doc/Spectral_domain_explorer‐user‐manual.html.
From Psychiatry to Oncology: Exploring the Anti‐Neoplastic Mechanisms of Aripiprazole and Its Potential Use in Cancer Treatment
Authors: O'Callaghan Liam A. , Blum Ciara B. , Powell Katie , Chess‐Williams Russ , McDermott Catherine 
Published: February 2025

ABSTRACTDrug repurposing provides a cost‐effective and time‐saving approach to cancer therapy. Aripiprazole (ARI), a third‐generation antipsychotic, has shown potential anticancer properties by modulating pathways central to tumor progression and resistance. This scoping review systematically examines evidence on ARI's anticancer effects, mechanisms of action, and translational potential. A systematic search of PubMed, EMBASE, SCOPUS, and Web of Science was conducted following PRISMA‐ScR guidelines. Eligible studies included in vitro, in vivo, and clinical investigations. Data on cancer types, pathways, assays, and outcomes were extracted and synthesized to identify trends and gaps. Of 588 screened studies, 23 met inclusion criteria, spanning cancer types such as breast, colorectal, lung, and brain cancers. ARI modulates key pathways like PI3K/AKT/mTOR and Wnt/β‐catenin, induces apoptosis through mitochondrial dysfunction and ER stress, and overcomes drug resistance by inhibiting P‐glycoprotein activity and expression. It exhibits tumor‐suppressive effects in vivo and synergizes with chemotherapy and radiotherapy. Retrospective population studies suggest ARI's prolactin‐sparing properties may reduce the risk of hormone‐sensitive cancers such as breast and endometrial cancer compared to antipsychotics with stronger dopamine receptor blockade. Additionally, ARI's ability to target multiple Hallmarks of Cancer highlights its promise as a repurposed anticancer agent. However, current evidence is primarily preclinical and observational, with limited clinical validation. Large‐scale cohort studies and prospective trials are essential to confirm its efficacy and address translational challenges. By bridging these gaps, ARI could emerge as a valuable adjunctive therapy in oncology, leveraging its safety profile and versatility to address unmet needs in cancer treatment.
Use of an Indwelling Pleural Catheter in a Malignant Effusion With Concurrent Mycobacterium avium Infection and Advanced HIV
Authors: Mescall Naomi , Semprini Ruth 
Published: February 2025

ABSTRACTA 63‐year‐old male was diagnosed with a combination of three concurrent diseases: stage 4 lung adenocarcinoma, ipsilateral mycobacterium avium complex (MAC) pleural effusion, and advanced HIV. He has been successfully treated for each diagnosis. At 2 years from presentation he continues on immunotherapy, with his pleural culture clear of MAC, and he has an undetectable HIV viral load. An indwelling pleural catheter was inserted for management of the recurrent malignant pleural effusion. We describe our management approach to a combined malignant and MAC related effusion in a patient with co‐existing advanced HIV.
Catalytic Conversion of 2‐ Methyl Phenol to Salicylaldehyde Using Manganese‐Oxide Doped Cellulose‐Derived Carbon Spheres
Authors: T Divya , Arulraj James , Balakrishnan Sreeja P. 
Published: February 2025

AbstractIn this study, we report on the hydrothermal synthesis of MnOx‐anchored carbon spheres as an effective catalyst. A new method is employed to prepare carbon spheres from cellulose. Using a solvent‐free process, the prepared catalyst is used to convert o‐cresol to salicylaldehyde. Methods including XRD, Raman spectroscopy, FE‐SEM, EDS mapping, and HR‐TEM are used to examine the structural and morphological characteristics of the catalyst. It is confirmed from the BET analysis that doping with MnOx increases the surface area of the carbon spheres. At standard atmospheric pressure, the conversion of o‐cresol to salicylaldehyde is highly selective due to the enhanced surface area and active sites of MnOx‐doped carbon spheres. Under atmospheric pressure, the MnOx/CS catalysts show excellent efficiency, yielding 96% salicylaldehyde in under 1 h. This study underscores the feasibility of using MnOx‐doped carbon spheres as a robust catalyst for the controlled oxidation of o‐cresol. The results show that the catalyst has a great deal of activity and effectiveness, as well as being cheap and reusable, which greatly increases its potential for real‐world catalytic applications.
Interfacial Confinement Derived High‐Strength MXene@Graphene Oxide Core‐Shell Fibers for Electromagnetic Wave Regulation, Thermochromic Alerts, and Visible Camouflage
Authors: Ye Lvxuan , Liu Liu‐Xin , Jin Meng , Zhou Xinfeng , Yin Guang , Yu Zhao Hao− , Yang Jinglei , Zhang Hao‐Bin , Yu Zhong‐Zhen 
Published: February 2025

AbstractAlthough electrically conductive Ti₃C₂Tx MXene fibers are promising for wearable electronics, the poor inter‐sheet interactions and the random stacking structure of MXene sheets seriously hinder electron transport and load transfer of the fibers. Herein, mechanically strong and electrically conductive MXene@graphene oxide (GO) core‐shell fibers are fabricated with a coaxial wet‐spinning methodology for electromagnetic wave regulation, thermochromic alerts, and visible camouflage. During the coaxial wet‐spinning, the trace‐carboxylated GO sheets in the shell align readily because of the spatial confinement of the coaxial needle, while the MXene sheets in the core are progressively oriented and flattened because of the spatial confinement of the GO shell. The positively charged chitosan in the coagulating solution enhances the interfacial interactions between the GO and MXene sheets and facilitates the sheet′s orientation inside the fibers. Consequently, the highly aligned core‐shell fibers exhibit an ultrahigh tensile strength of 613.7 MPa and an outstanding conductivity of ≈7766 S cm−1. Furthermore, fiber‐woven textiles not only offer excellent electromagnetic interference shielding performance but also achieve quantitative regulation of electromagnetic wave transmission by adjusting the angle of the double‐layered textiles. The textiles can combine with thermochromic coatings for thermotherapy alerts, visual thermochromic warnings, and visible camouflage.
Young Adult Patients With Paediatric‐Onset Inflammatory Bowel Disease Have a Higher Educational Level and a Higher Employment Rate Than the General Population
Authors: Sarter Hélène , Le Coniac Mathilde , Leroyer Ariane , Savoye Guillaume , Fumery Mathurin , Guillon Nathalie , Gower‐Rousseau Corinne , Ley Delphine , Turck Dominique ,   The EPIMAD study group
Published: February 2025

ABSTRACTBackground & AimsThere are few published data on the impact of paediatric‐onset inflammatory bowel diseases on education and employment. The objective of the present cross‐sectional study was to assess the educational level and occupational status of adult patients with paediatric‐onset inflammatory bowel diseases from the EPIMAD Registry.MethodsThe inclusion criteria were (i) a diagnosis of paediatric‐onset (< 17 years at diagnosis) inflammatory bowel diseases, and (ii) age 25 or over at the time of study. The patients answered a self‐questionnaire on their educational level and profession. The data were compared with those of the general population of the same age and geographic area.ResultsThree hundred and sixty‐one patients (286 with Crohn's disease and 75 with ulcerative colitis) filled out and returned the questionnaire. The median [interquartile] age was 15.0 [12.9; 16.3] years at diagnosis and 34.2 [29.6; 39.5] years at the time of the study. Patients were more likely to have a higher education degree than the general population (57% vs. 41%, p < 0.0001). The unemployment rate was significantly lower among study participants than among the general population (9% vs. 15%, p = 0.001). Salaried patients were significantly more likely to be employed in the healthcare sector (14% vs. 9% in the general population; p = 0.005) and in the public sector (34% vs. 22% in the general population; p < 0.0001).ConclusionOur results showed that relative to the general population, patients with paediatric‐onset inflammatory bowel diseases have a higher educational level and a higher employment rate, and are more likely to work in the healthcare and public sectors.
Antiviral strategies against influenza virus: an update on approved and innovative therapeutic approaches
Authors: Bonomini Anna , Mercorelli Beatrice , Loregian Arianna 
Published: February 2025

Abstract
Influenza viruses still represent a great concern for Public Health by causing yearly seasonal epidemics and occasionally worldwide pandemics. Moreover, spillover events at the animal-human interface are becoming more frequent nowadays, also involving animal species not previously found as reservoirs. To restrict the effects of influenza virus epidemics, especially in at-risk population, and to prepare a drug arsenal for possible future pandemics, researchers worldwide have been working on the development of antiviral strategies since the 80’s of the last century. One of the main obstacles is the considerable genomic variability of influenza viruses, which constantly poses the issues of drug-resistance emergence and immune evasion. This review summarizes the approved therapeutics for clinical management of influenza, promising new anti-flu compounds and monoclonal antibodies currently undergoing clinical evaluation, and molecules with efficacy against influenza virus in preclinical studies. Moreover, we discuss some innovative anti-influenza therapeutic approaches such as combination therapies and targeted protein degradation. Given the limited number of drugs approved for influenza treatment, there is a still strong need for novel potent anti-influenza drugs endowed with a high barrier to drug resistance and broad-spectrum activity against influenza viruses of animal origin that may be responsible of future large outbreaks and pandemics.
Math Sorting: Unintended Consequences of Developmental Education Reforms in Community Colleges
Authors: Mishra Soumya , Swanson Elise , Yucel Elif , Ngo Federick , Melguizo Tatiana , Ching Cheryl 
Published: February 2025

Abstract
Beginning in 2019, California community colleges were required to use multiple measures to determine students’ placement into initial math courses. Community colleges also created structured BSTEM and liberal arts (SLAM) math pathways beginning in 2017. This contemporaneous implementation could reproduce racialized stratification in math course-taking. This study analyzes changes in math course-taking between Fall 2017 and Summer 2021 using multinomial logistic regression. We find that after the reforms, fewer students across racial/ethnic groups took developmental math and more students attempted SLAM and BSTEM math in the first year of enrollment. Students of color were more likely to take SLAM math and slightly less likely to take BSTEM math, even among academically prepared students. We find some evidence of racial tracking in the steeper increase in SLAM course-taking among Latina/o/x students compared to other racial/ethnic groups. We discuss implications for future policy and practice given these results.
Is serum AMH a suitable biomarker to determine litter size or fetal sex in goats?: A preliminary study
Authors: Koldaş Ürer Ece , Köse Ayşe Merve , Pir Yağcı İlknur , Pekcan Mert , Gözer Ahmet , Bahan Onur 
Published: February 2025

Abstract
This study was conducted in Damascus goats to i) investigate the relationship between serum AMH concentrations and litter size, ii) evaluate the change in serum AMH concentration between the 35th and 135th days of pregnancy, iii) determine whether fetal sex affected the maternal AMH level. Estrus was synchronized in 110 goats (intravaginal sponge containing medroxyprogesterone acetate for nine days, combined with d-cloprostenol and Pregnant Mare Serum Gonadotropin at sponge removal). Blood samples were taken on the 4th and 9th days of synchronization. Goats at estrus were mated naturally. Study groups were established based on the number of fetuses on ultrasound examination as Group I (n = 18, goats carrying one fetus) and Group II (n = 18, goats carrying multiple fetuses) (Experiment I). Additionally, blood samples were taken every 20 days between the 35th and 135th days of pregnancy. After the parturition, groups were formed according to the sex of the kids; single/multiple male fetuses (GroupM, n = 8), single/multiple female fetuses (GroupF, n = 8), and fetuses of the opposite sex (GroupFM, n = 8), (Experiment II). There was no significant relationship between serum AMH concentration and litter size (P > 0.05). As pregnancy progressed maternal AMH concentration tended to decrease (P < 0.001), and fetal sex did not affect maternal AMH (P > 0.05). In conclution circulating AMH was not an ideally biomarker for determining litter size on natural breeding or predicting fetal sex in goats. Futher studies with larger sample sizes and the reduced individual variables (age and ovarian activity) are recommened.
Review of the Effects of Trace Metal Concentrations on the Anaerobic Digestion of Organic Solid Waste
Authors: Salazar-Batres Karina J. , Moreno-Andrade Iván 
Published: February 2025

Abstract
Anaerobic digestion is a promising technology for producing methane-rich biogas. Various wastes, including waste activated sludge, food waste, farm waste, agricultural waste, and wastewater, have been used as substrates to generate biogas, which can be transformed into electrical or thermal energy. However, process instability and low methane yield restrict the widespread application of this process. Several strategies have been employed to increase methane yield and energy production, including adding trace elements, such as iron, cobalt, molybdenum, and nickel. Trace elements are part of the cofactors of enzymes involved in methane synthesis and microbial growth. This review aims to analyze the effects of trace elements on methane yield and propose concentrations at which methane production increases, as well as potential inhibitory effects. The addition of trace metals to the anaerobic digestion process has been found to have positive effects, such as enhanced methane yields and productivities, volatile fatty acid (VFA) removal, and chemical oxygen demand removal. An analysis of previously published data from other researchers was adjusted to a variant of the Haldane equation, suggesting that ranges of mg of trace metals per gram of substrate added promote an increase in methane production (0.56–1.67 mg/g VS for iron, 0.01–0.1 mg/g VS for cobalt, 0.03–0.5 mg Mo/g VS for molybdenum, and 0.04–0.5 mg Mo/g VS for nickel). Furthermore, the literature review revealed that the efficiency of the process decreases with increasing metal dose beyond the proposed range. The frequency of trace elements addition directly influences VFA removal. Some trace elements, such as nickel, generate VFAs of higher molecular weight, modifying the process performance. Notably, the process efficiency decreases with higher doses of trace elements, although this promotes the VFA removal.
Challenging the Performance-Interpretability Trade-Off: An Evaluation of Interpretable Machine Learning Models
Authors: Kruschel Sven , Hambauer Nico , Weinzierl Sven , Zilker Sandra , Kraus Mathias , Zschech Patrick 
Published: February 2025

Abstract
Machine learning is permeating every conceivable domain to promote data-driven decision support. The focus is often on advanced black-box models due to their assumed performance advantages, whereas interpretable models are often associated with inferior predictive qualities. More recently, however, a new generation of generalized additive models (GAMs) has been proposed that offer promising properties for capturing complex, non-linear patterns while remaining fully interpretable. To uncover the merits and limitations of these models, the study examines the predictive performance of seven different GAMs in comparison to seven commonly used machine learning models based on a collection of twenty tabular benchmark datasets. To ensure a fair and robust model comparison, an extensive hyperparameter search combined with cross-validation was performed, resulting in 68,500 model runs. In addition, this study qualitatively examines the visual output of the models to assess their level of interpretability. Based on these results, the paper dispels the misconception that only black-box models can achieve high accuracy by demonstrating that there is no strict trade-off between predictive performance and model interpretability for tabular data. Furthermore, the paper discusses the importance of GAMs as powerful interpretable models for the field of information systems and derives implications for future work from a socio-technical perspective.
Five commentaries on ‘Waves Dangerous, Domesticated and Diagnostic’ plus Stefan Helmreich’s response
Authors: Colenbrander Darryl , Driessen Clemens , Fisch Michael , Mizukawa Jun , Steinberg Philip , Taddei Renzo , Helmreich Stefan 
Published: February 2025

Abstract
This review article engages with Stefan Helmreich’s paper ‘Waves dangerous, domesticated, and diagnostic’ as well as his ‘A Book of Waves’. It offers a set of critical commentaries on key themes raised in these works unpacking the role of wave science, technology and power in various contexts: On treating waves as an outside enemy to be fought by hard barriers between land and water, or as objects of commodification when models functions as ways to claim and export knowledge thereby overriding other forms of knowing waves and protecting coasts; On the role of the state in coastal governance in the Global South and on transdisciplinary approaches dealing with the systemic nature of coastal risks and resilience; On comparison and integration of modern wave science with indigenous knowledges; On the importance of social besides physical oceanography; On practices of attuning not only to the daily tidal schedule and coastal weather, but also to the oceanic rhythms, tempos, and shifts that materialize the ocean’s potentials and risks, and on waves as carriers of meaning. The review paper ends with a response by Helmreich.