bluuebunny/crossref_metadata_2025_split huggingface dataset:
University Students' Sociodemographics, Physical Inactivity, and Inadequate and Poor‐Quality Sleep Are Associated With Their Overweight/Obesity: Findings From a Case–Control Study in Bangladesh
Authors: Banna Md. Hasan Al , Hamiduzzaman Mohammad , Akter Shammy , Seidu Abdul‐Aziz , Begum Ayesha , Yeasmin Nilufa , Kundu Satyajit , Begum Mst. Umme Hafsa , Sultana Mst Sadia , Kissi‐Abrokwah Bernard , Alshahrani Najim Z. , Khan Md. Shafiqul Islam , Hassan Md. Nazmul 
Published: February 2025

ABSTRACTBackground and AimsEvidence confirms a high prevalence of general and abdominal obesity among university students in Bangladesh. The primary objective of this case–control study was to examine the association between overweight/obesity and sleep patterns (including sleep duration and quality) among university students in Bangladesh. The secondary objective was to identify the sociodemographic and lifestyle‐related factors that predict overweight/obesity in the study population.MethodsThe sociodemographics and body mass index (BMI) were gathered from a sample of 330 university students (setting: one public university in Bangladesh). Sleep health was measured by the 19‐item Pittsburgh Sleep Quality Index (PSQI) and compared between the cases (BMI ≥ 23.0 kg/m2) and controls (BMI = 18.5–22.9 kg/m2). Bivariate and multiple stepwise regression analyses were performed.ResultsOne hundred and sixty‐five overweight/obesity students and 165 control subjects participated in the study. The peak age for overweight/obesity was 22–25 years in the students, and about 67% of the cases were poor‐quality sleepers compared to 53% of the students in the control group. Multiple stepwise regression analysis showed that students' overweight/obesity was associated with being female (adjusted odds ratio, aOR = 2.12; 95% confidence interval, CI: 1.25, 3.61), short sleep duration ( ≤ 7 h/night) (aOR = 1.12, 95% CI: 1.04, 2.66), poor quality of sleep (aOR = 1.82, 95% CI: 1.16, 2.87), and physical inactivity (aOR = 1.89; 95% CI: 1.12, 3.55).ConclusionKey factors associated with overweight/obesity among Bangladeshi university students include age (22–25 years), gender (higher prevalence in female students), sleep duration and quality, and physical inactivity. These findings highlight the need for targeted interventions addressing sleep health, physical activity, and healthy lifestyles to mitigate overweight/obesity among university students.
Granulocyte colony‐stimulating factor‐associated aortitis in a man with advanced prostate cancer
Authors: Ikadai Ryota , Kitano Goshi , Kato Manabu , Kojima Takahiro 
Published: February 2025

IntroductionGranulocyte colony‐stimulating factor‐associated aortitis remains poorly understood among clinicians.Case presentationWe present a case of G‐CSF‐associated aortitis in a 70‐year‐old male with stage IVb castration‐resistant prostate cancer (cT3bN0M1b) receiving docetaxel chemotherapy. Neutropenia (280/μL) developed on day 8 of the first chemotherapy cycle, prompting subcutaneous administration of filgrastim, a short‐acting G‐CSF, on days 8–10. On day 14, the patient presented to the outpatient clinic with fever but no other significant symptoms. Computed tomography revealed filgrastim‐induced thoracic aortitis. Daily prednisone treatment (equivalent to 25 mg prednisolone) was initiated on the following day. Although the initial episode of aortitis resolved within 5 weeks, subsequent pegfilgrastim resulted in recurrence around the left subclavian artery, necessitating further steroid therapy.ConclusionPersistent high fever following G‐CSF administration may indicate drug‐induced aortitis, highlighting the potential for aortitis recurrence with repeated G‐CSF use.
Trends and considerations for interprofessional continuing education activities for pharmacists and pharmacy technicians
Authors: Murry Logan T. , Kiersma Mary E. , Janis Steve , Catledge Kimberly , Travlos Dimitra V. , Engle Janet P. 
Published: February 2025

AbstractIntroductionDespite an increased focus on the importance and value of interprofessional education (IP), there is limited literature on the extent to which IP plays a role in continuing education (CE) for pharmacy learners.ObjectivesThis study sought to describe interprofessional continuing education (IPCE) activities available to pharmacy learners from 2019 to 2023 and discuss considerations for the development of IPCE activities for pharmacists and pharmacy technicians.MethodsThis was a descriptive study using retrospective analysis of data collected from the Accreditation Council for Pharmacy Education (ACPE) Provider Web Tool and the Joint Accreditation Program and Activity Reporting system (JA‐PARS), the repositories for all continuing pharmacy education (CPE) activities and continuing education activities offered by ACPE‐accredited CE providers and Jointly Accredited CE providers, respectively. All activities available from 2019 to 2023 were collected for analysis, with descriptive statistics calculated for activities in each year including the total number of CE providers, number of activities, number of activities per ACPE topic designator, target audience, and activity type. All analyses were conducted in R Statistical software (2021).ResultsThe year with the largest number of CE providers awarding IPCE credit was 2023, with a total of 105 CE providers. A total of 35 427 activities awarding IPCE credit were available to pharmacy learners from 2019 to 2023, with the largest number of activities available in 2023 (n = 12 184; 34.6% of total activities). Most activities available during the time period were designed for pharmacists (n = 28 115; 79.4% of total activities) and were knowledge‐based (n = 32 627; 92.1% of total activities). The topic designator with the largest number of activities available during the time period was 01: Disease State Management/Drug Therapy (n = 16 806; 47.4% of total activities).ConclusionsWhile the number of IPCE activities has increased since 2019, additional focus on designing interprofessional education which includes pharmacy technicians, developing activities designed to help learners apply knowledge to practice, and designing activities around competencies reflective of team‐based care is necessary.
Isolation and characterization of phenolic substances from pomegranate residues
Authors: Papageorgiou Costas S , Kyriazis Anastasios , Zentelis Αndreas D , Ioannidis Vassilis A , Lamari Fotini N , Sygouni Varvara , Lianou Alexandra , Paraskeva Christakis A , Aggelis George 
Published: February 2025

AbstractBACKGROUNDPomegranate Residues (PRs) can be utilized for the development of a fermentation substrate for bioethanol production, while the contained bioactive substances could be recovered with physicochemical separation processes to be used in pharmaceutics or cosmetic products. Herein, we focused on the phenolics' characterization at each step of the proposed procedure and their isolation. First, thermal hydrolysis was conducted on PRs and the product was separated into liquid phase and pulp. The liquid phase was subjected to pH adjustment and to a second thermal treatment (to ensure sterility and its exploitability as a fermentation substrate), while pulp was submitted to extraction tests. The total phenolic content (TPC) and total carbohydrates concentration (TCC) were measured at each stage and the contained phenolics were identified using LC‐MS. Adsorption and desorption experiments in a column packed with XAD16 N resin were conducted on the liquid extracts to isolate phenolic substances.RESULTSSignificant amounts of high‐added value substances (punicalagins, ellagic acid, gallic acid) were found in the liquid samples and in the pulp extract. The appropriate stages to recover the contained phenolics were identified. The adsorption and desorption curves and the HPLC‐DAD analysis showed that for the tested experimental conditions, gallic acid and galloyl‐hexoside was recovered at ~3 min, punicalagin ~at 15 min and ellagic acid, ellagic acid hexoside at ~15–30 min.CONCLUSIONThis work showed that during the treatment of PRs to produce fermentation substrate, it is possible to isolate significant phenolic compounds with the use of physicochemical processes. © 2025 The Author(s). Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).
Extreme hypercalcemia secondary to parathyroid adenoma obscured by excessive coffee consumption and premature ventricular complexes
Authors: Avidan Yuval , Kassem Sameer 
Published: February 2025

AbstractSevere hypercalcemia has an arrhythmogenic effect. We present a case of a young male falsely diagnosed with premature ventricular complexes attributed to heavy coffee consumption, while symptoms and electrocardiographic findings of hypercalcemia were disregarded. Delayed work‐up identified extreme hypercalcemia, and subsequently, parathyroid adenoma was diagnosed. Medical and surgical management resulted in complete resolution. The misdiagnosis led to a substantial diagnostic delay.
Tumor Necrosis Factor‐Alpha Inhibits the Replication of Patient‐Derived Archetype BK Polyomavirus While Activating Rearranged Strains
Authors: Lauterbach‐Rivière Lise , Thuringer Lucia , Feld Pascal , Toews Lina Kathrin , Schüssler Jessica , Klinz Jonas , Gläser Lars , Lohse Stefan , Sternjakob Anna , Gasparoni Gilles , Kattler‐Lackes Kathrin , Walter Jörn , Lauterbach Marcel A. , Rahmann Sven , Möller Lars , Laue Michael , Janssen Martin , Stöckle Michael , Schmit David , Fliser Danilo , Smola Sigrun 
Published: February 2025

ABSTRACTTo date, no drugs are approved for BK polyomavirus (BKPyV) reactivation, a major cause of nephropathy after kidney transplantation. Recently, tumor necrosis factor‐α (TNF‐α) blockade has been proposed as a promising therapy, however, the effect of TNF‐α on the clinically most common archetype (ww) BKPyV remained unclear. Assays in primary renal proximal tubule epithelial cells (RPTEC) allowed efficient replication only of BKPyV strains with rearranged (rr) non‐coding control regions (NCCR), which may develop at later disease stages, but not of ww‐BKPyV. Here, we optimized culture conditions allowing robust replication of patient‐derived ww‐BKPyV, while efficiently preserving their ww‐NCCR. TNF‐α promoted rr‐BKPyV replication, while the TH1 cytokine IFN‐γ suppressed it, also in the presence of TNF‐α. Surprisingly, TNF‐α alone was sufficient to suppress all ww‐BKPyV strains tested. Comprehensive analysis using siRNAs, and chimeric or mutated BKPyV‐strains revealed that the response to TNF‐α depends on the NCCR type, and that the NF‐κB p65 pathway but not the conserved NF‐κB binding site is essential for the TNF‐α‐induced enhancement of rr‐BKPyV replication. Our data suggest that in immunosuppressed patients with archetype‐dominated infections, TNF‐α blockade could interfere with natural TNF‐α‐mediated anti‐BKPyviral control, and this could be detrimental when IFN‐γ‐driven TH1 responses are impaired. Ongoing inflammation, however, could lead to the selection of rearrangements responding to NCCR‐activating pathways downstream of NF‐κB p65 signaling, that may overcome the initial TNF‐α‐mediated suppression. Our findings also highlight the importance of using clinically relevant BKPyV isolates for drug testing and discovery, for which this new assay paves the way.
Linear Electrical Circuits Described by a Novel Constant Proportional Caputo Hybrid Operator
Authors: Morales‐Delgado V. F. , Gómez‐Aguilar J. F. , Taneco‐Hernández M. A. , Pérez‐Careta E. , Torres‐Jiménez J. , Samei Mohammad Esmael 
Published: February 2025

ABSTRACTIn this work, we obtain analytical solutions via Laplace transform of fractional electrical circuits by using the proportional Caputo derivative with power law. Numerical simulations were obtained to see the impact of the memory concept represented by the fractional parameter order. Also, we collect a lot of experimental data obtained in our laboratory for an circuit, and for each case, we calculate the value of the fractional‐order by using a particle swarm optimization approach. The results obtained reveals that the experimental data deviate slightly from that obtained in the integer‐order behavior and the application of the proportional Caputo derivative best fits the experimental data.
Improved quadriceps efficiency with a medial pivot in comparison to a cruciate‐retaining design in total knee arthroplasty
Authors: Bauer Leandra , Niethammer Thomas R. , Thorwächter Christoph , Woiczinski Matthias , Müller Peter E. , Simon Florian , Holzapfel Boris M. , Simon Johanna‐Maria 
Published: February 2025

AbstractPurposeThe posterior cruciate‐retaining (CR) design offers rotational freedom but risks abnormal kinematics and instability. The medial pivot (MP) design mimics native joint motion with a high‐conformity medial and flat lateral interface. Within clinical studies, the MP design outclassed the CR design, but biomechanical studies are lacking. This study investigates the tibiofemoral and patellofemoral kinematics of both implant designs compared to native kinematics.MethodsEight fresh‐frozen cadaveric knee specimens underwent total knee arthroplasty using MP and CR designs. Testing was performed in a dynamic knee rig simulating active knee flexion (30–130°) under muscle load. Biomechanical assessments included tibial rotation, tibiofemoral translation, patellar tilt/shift, patellofemoral contact/pressure patterns and quadriceps force. Functional regressions were used to analyse the effects of the component designs on the native situation.ResultsThe MP design exhibited increased tibial rotation (130° flexion: MP 9.4° vs. CR 6.6°) and lateral anterior tibial translation during flexion (130° flexion: MP 25.8 mm vs. CR 22.6 mm). Both designs showed no significant differences in patellar tilt or shift and similar patellofemoral pressure (CR 3.2 MPa, MP 3.4 MPa) and contact patterns (CR 213.8 mm2 vs. MP 230.4 mm2). The MP design required lower quadriceps force, particularly in deep flexion (NS 452.6 N, CR 407.8 N and MP 367.3 N).ConclusionThe MP design provides a more native‐like knee kinematic profile than the CR design, with a more pronounced MP motion pattern and reduced quadriceps loading.Level of EvidenceNot applicable.
Accurate estimation of photosynthetic available radiation from multispectral downwelling irradiance profiles
Authors: Pitarch Jaime , Leymarie Edouard , Vellucci Vincenzo , Massi Luca , Claustre Hervé , Poteau Antoine , Antoine David , Organelli Emanuele 
Published: February 2025

AbstractPhotosynthetic available radiation (PAR) is the light usable by photosynthetic organisms. Photosynthetic available radiation measurements at depth are required to quantify the light availability for primary production. Direct PAR measurements may be measured with full‐spectrum quantum sensors for the range 400 to 700 nm. When spectrally resolved light is measured, as for the downwelling irradiance spectrum , PAR may be computed by numerically integrating within those limits. As radiation varies across a spectral continuum, needs to be resolved at a sufficiently large number of bands, to provide an unbiased PAR estimate. When is available at a small number of spectral bands, as for multispectral sensors, it is still possible to numerically integrate , but the estimation will contain errors. Here, we propose a method that delivers unbiased PAR estimates, based on two‐layer neural networks, formulable in a small number of matrix equations, and thus exportable to any software platform. The method was calibrated with a dataset of hyperspectral acquired by new types of BioGeoChemical (BGC)‐Argo floats deployed in a variety of open ocean locations, representative of a wide range of bio‐optical properties. This procedure was repeated for several band configurations, including those existing on multispectral radiometers presently the standard for the BGC‐Argo fleet. Validation results against independent data were highly satisfactory, displaying minimal uncertainties across a wide PAR range, with the performance varying as a function of each sensor configuration, overall supporting the operational implementation in the Argo program. Model codes are findable at https://github.com/jaipipor/PAR_BGC_Argo.
Bio‐Based Epoxy Resins Derived from Eugenol with High Glass Transition Temperatures as Substitutes for DGEBA
Authors: Schamel Elisabeth , Bauer Florian , Schlachter Herbert , Wehnert Gerd , Söthje Dominik 
Published: February 2025

AbstractEpoxy resins (EPs) are crucial for high‐performance applications like lightweight materials, due to their excellent properties. However, the commonly used diglycidyl ether of bisphenol A (DGEBA) has two major disadvantages: it is synthesized mainly from petrochemicals and includes the health concerning bisphenol A. Eugenol is a bio‐based aromatic compound that can be modified into di‐ or triglycidyl ether. Through investigations four monomers are obtained based on eugenol and crosslinked with two curing agents isophorone diamine and 4,4′‐diaminodiphenyl sulfone to compare the properties of the resulting EPs with references containing DGEBA. Using new synthesis routes, the bio‐content of the monomers can be increased up to 94 wt%. Intramolecular cyclization occurs if a hydroxy group is in ortho‐position to the glycidyl ether group. The crosslinking conditions of the bio‐based monomers are comparable to or lower than those of DGEBA. The eugenol‐based triglycidyl monomers exhibit very high glass transition temperatures of up to 271 °C, almost 50 °C above the reference value, which can enable their use for lightweight construction such as matrices for fiber‐reinforced plastics. The char content of all bio‐based EPs after pyrolysis is significantly higher in comparison to the references, which may have a favorable effect on fire resistance.
Revolutionizing Brain Tumor Detection Using Explainable AI in MRI Images
Authors: Ariful Islam Md. , Mridha M. F. , Safran Mejdl , Alfarhood Sultan , Mohsin Kabir Md. 
Published: February 2025

ABSTRACTDue to the complex structure of the brain, variations in tumor shapes and sizes, and the resemblance between tumor and healthy tissues, the reliable and efficient identification of brain tumors through magnetic resonance imaging (MRI) presents a persistent challenge. Given that manual identification of tumors is often time‐consuming and prone to errors, there is a clear need for advanced automated procedures to enhance detection accuracy and efficiency. Our study addresses the difficulty by creating an improved convolutional neural network (CNN) framework derived from DenseNet121 to augment the accuracy of brain tumor detection. The proposed model was comprehensively evaluated against 12 baseline CNN models and 5 state‐of‐the‐art architectures, namely Vision Transformer (ViT), ConvNeXt, MobileNetV3, FastViT, and InternImage. The proposed model achieved exceptional accuracy rates of 98.4% and 99.3% on two separate datasets, outperforming all 17 models evaluated. Our improved model was integrated using Explainable AI (XAI) techniques, particularly Grad‐CAM++, facilitating accurate diagnosis and localization of complex tumor instances, including small metastatic lesions and nonenhancing low‐grade gliomas. The XAI framework distinctly highlights essential areas signifying tumor presence, hence enhancing the model's accuracy and interpretability. The results highlight the potential of our method as a reliable diagnostic instrument for healthcare practitioners' ability to comprehend and confirm artificial intelligence (AI)‐driven predictions but also bring transparency to the model's decision‐making process, ultimately improving patient outcomes. This advancement signifies a significant progression in the use of AI in neuro‐oncology, enhancing diagnostic interpretability and precision.
CO2 Photoreduction Improvement by Carbon Nitride Utilizing the Synergism of Na Ion and Cyano Defects
Authors: Li Weize , Hu Zhizhong , Song Lingyong , Lv Yangbo , Liu Jincang , Lu Changtong , Xu Chunping 
Published: February 2025

AbstractConversion of CO2 to high value products was considered as a focused issue towards carbon neutrality. Photocatalysis held the potential to realize the target, and graphitic carbon nitride (g‐C3N4) was a competitive candidate. The photocatalytic efficiency of g‐C3N4 limited by the weak adsorption of CO2 and easy recombination of charge carriers. Herein, Na ion and cyano defects was induced into g‐C3N4 simultaneously using NaHSO3 as alkali molten salt to work out these obstacles. The optimized photocatalyst 3 Na‐CN (the weight of NaHSO3 was 1.5 g) exhibited the highest CO yield (21.5 μmol g−1 h−1), which was 5 times than that of pristine g‐C3N4 (4.29 μmol g−1 h−1). By means of experiments and characterization, 3 Na‐CN displayed better performance in both light utilization and charge separation, which was reflected by the improved photocurrent response, decreased electrochemical impedance, markedly diminished fluorescence intensity, and shortened fluorescence lifetime. This result could be ascribed to the facilitation of electron‐hole separation induced by cyano defects, as well as the enhancement in CO2 adsorption and activation mediated by the Na ion. This work offers a new perspective on dual modulation of graphitic carbon nitride and paves the way for the design of CO2 reduction photocatalyst.
Characterization of immune microenvironment associated with medulloblastoma metastasis based on explainable machine learning
Authors: Zhao Fengmao , Liu Xiangjun , Gui Jingang , Sun Hailang , Zhang Nan , Peng Yun , Ge Ming , Wang Wei 
Published: February 2025

ABSTRACTImportanceMedulloblastoma (MB) is the most common malignant brain tumor in children, with metastasis being the primary cause of recurrence and mortality. The tumor microenvironment (TME) plays a critical role in driving metastasis; however, the mechanisms underlying TME alterations in MB metastasis remain poorly understood.ObjectiveTo develop and validate machine learning (ML) models for predicting patient outcomes in MB and to investigate the role of TME components, particularly immune cells and immunoregulatory molecules, in metastasis.MethodsML models were constructed and validated to predict prognosis and metastasis in MB patients. Eight algorithms were evaluated, and the optimal model was selected. Lasso regression was employed for feature selection, and SHapley Additive exPlanations values were used to interpret the contribution of individual features to model predictions. Immune cell infiltration in tumor tissues was quantified using the microenvironment cell populations‐counter method, and immunohistochemistry was applied to analyze the expression and distribution of specific proteins in tumor tissues.ResultsThe ML models identified metastasis as the strongest predictor of poor prognosis in MB patients, with significantly worse survival outcomes observed in metastatic cases. High infiltration of CD8+ T cells and cytotoxic T lymphocytes (CTLs), along with elevated expression of the TGFB1 gene encoding transforming growth factor beta 1 (TGF‐β1), were strongly associated with metastasis. Independent transcriptomic and immunohistochemical analyses confirmed significantly higher CD8+ T cell/CTL infiltration and TGF‐β1 expression in metastatic compared to nonmetastatic MB samples. Patients with both high CD8+ T cell/CTL infiltration and elevated TGFB1 expression in the context of metastasis exhibited significantly worse survival outcomes compared to patients with low expression and no metastasis.InterpretationThis study identifies metastasis as the key prognostic factor in MB and reveals the pivotal roles of CD8+ T cells, CTLs, and TGF‐β1 within the TME in promoting metastasis and poor outcomes. These findings provide a foundation for developing future therapeutic strategies targeting the TME to improve MB patient outcomes.