bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of the Extent of Blood–Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model
Authors: Gülave Berfin , van den Maagdenberg Helle W. , van Boven Luke , van Westen Gerard J. P. , de Lange Elizabeth C. M. , van Hasselt J. G. Coen 
Published: February 2025

Abstract

Introduction
The unbound brain-to-plasma partition coefficient (Kp,uu,BBB) is an essential parameter for predicting central nervous system (CNS) drug disposition using physiologically-based pharmacokinetic (PBPK) modeling. Kp,uu,BBB values for specific compounds are however often unavailable, and are moreover time consuming to obtain experimentally. The aim of this study was to develop a quantitative structure–property relationship (QSPR) model to predict the Kp,uu,BBB and to demonstrate how QSPR-model predictions can be integrated into a physiologically-based pharmacokinetic model for the CNS.

Methods
Rat Kp,uu,BBB values were obtained for 98 compounds from literature or in house historical data. For all compounds, 2D and 3D physico-chemical and structural properties were derived using the Molecular Operating Environment (MOE) software. Multiple machine learning (ML) regression models were compared for prediction of the Kp,uu,BBB, including random forest, support vector machines, K-nearest neighbors, and (sparse-) partial least squares. Finally, we demonstrate how the developed QSPR model predictions can be integrated into a CNS PBPK modeling workflow.

Results
Among all ML algorithms, a random forest showed the best predictive performance for Kp,uu,BBB on test data with R2 value of 0.61 and 61% of all predictions were within twofold error. The obtained Kp,uu,BBB were successfully integrated into the LeiCNS-PK3.0 CNS PBPK model.

Conclusions
The developed random forest QSPR model for Kp,uu,BBB prediction was found to have adequate performance, and can support drug discovery and development of novel investigational drugs targeting the CNS in conjunction with CNS PBPK modeling.
Effect of Calcium Hydroxide and Nixtamalization Time on the In Vitro Starch and Protein Digestibility of Traditional Maize Tortillas
Authors: Escamilla-Urbina Izxayana , Totosaus-Sánchez Alfonso , Rodríguez-Huezo M. Eva , Vernon-Carter E. Jaime , Alvarez-Ramirez Jose 
Published: February 2025

Abstract
This work addressed the traditional nixtamalization processing conditions on the in vitro protein and starch digestibility of tortillas. Two levels of lime addition (1 and 2 g/100 g db) and three different cooking times (30, 45 and 60 min) were considered. FTIR analysis was used to evaluate the organization of water, proteins and starch in the tortilla matrix. Lime concentration impacted the random secondary structure formation of the protein, and cooking time the starch ordered structures content. Higher lime concentration led to lower protein digestibility, but longer cooking time increased it. Highest protein hydrolysis (74.36 ± 3.72%) was achieved in T1,60 after 120 min of enzymatic digestion. Higher RDS contents were found as lime concentration increased, probably due to starch chain fragmentation at all cooking temperatures. A multivariate analysis indicated that both the lime concentration and cooking time had a major effect on the tortilla’s digestibility. Both protein and starch digestibility can be modulated by using appropriate lime concentrations and cooking temperatures.
Ohm’s Law, the Reconnection Rate, and Energy Conversion in Collisionless Magnetic Reconnection
Authors: Liu Yi-Hsin , Hesse Michael , Genestreti Kevin , Nakamura Rumi , Burch James L. , Cassak Paul A. , Bessho Naoki , Eastwood Jonathan P. , Phan Tai , Swisdak Marc , Toledo-Redondo Sergio , Hoshino Masahiro , Norgren Cecilia , Ji Hantao , Nakamura Takuma K. M. 
Published: February 2025

Abstract
Magnetic reconnection is a ubiquitous plasma process that transforms magnetic energy into particle energy during eruptive events throughout the universe. Reconnection not only converts energy during solar flares and geomagnetic substorms that drive space weather near Earth, but it may also play critical roles in the high energy emissions from the magnetospheres of neutron stars and black holes. In this review article, we focus on collisionless plasmas that are most relevant to reconnection in many space and astrophysical plasmas. Guided by first-principles kinetic simulations and spaceborne in-situ observations, we highlight the most recent progress in understanding this fundamental plasma process. We start by discussing the non-ideal electric field in the generalized Ohm’s law that breaks the frozen-in flux condition in ideal magnetohydrodynamics and allows magnetic reconnection to occur. We point out that this same reconnection electric field also plays an important role in sustaining the current and pressure in the current sheet and then discuss the determination of its magnitude (i.e., the reconnection rate), based on force balance and energy conservation. This approach to determining the reconnection rate is applied to kinetic current sheets with a wide variety of magnetic geometries, parameters, and background conditions. We also briefly review the key diagnostics and modeling of energy conversion around the reconnection diffusion region, seeking insights from recently developed theories. Finally, future prospects and open questions are discussed.
Fuzzy K-expectiles clustering
Authors: D’Urso Pierpaolo , De Giovanni Livia , Federico Lorenzo , Vitale Vincenzina 
Published: February 2025

Abstract
In this paper the Fuzzy K-expectiles clustering model is proposed. The model takes into account the asymmetry inherent in the data distribution, extending its applicability to a broader spectrum of data than the Fuzzy K-means. To achieve this, the Fuzzy K-expectiles clustering model introduces the cluster centroid expectile, and assigns data points based on expectile distances. An adaptive asymmetry parameter is specified for each variable and for each cluster The performance of the adaptive Fuzzy K-expectiles model is compared with other clustering models suggested in the literature. To show the performances of the proposed model three simulation studies and three applications to real datasets are presented.
Multicast Scaling in Heterogeneous Wireless Sensor Networks for Security and Time Efficiency
Authors: Vankdothu Ramdas , Hameed Mohd Abdul , Fatima Husnah , Subbarao Akkala 
Published: February 2025

Abstract
Heterogeneous wireless sensor networks (HWSNs) satisfy researchers' requirements for developing real-world solutions that handle unattended challenges. However, the primary constraint of researchers is the privacy of the sensor nodes. It safeguards the sensor nodes and extensions in the HWSNs. Therefore, it is necessary to develop secure operational systems. Multicast scaling with security and time efficiency is described in heterogeneous wireless sensor networks to maximize network performance while also successfully protecting network privacy. This study evaluates the initial security and time efficiency measures, such as execution time, transmission delay, processing delay, congestion level, and trust measure. Subsequently, the optimal location of the heterogeneous nodes is determined using sigmoid-based fuzzy c-means clustering. Finally, successful cluster routing was achieved via support-value-based particle swarm optimization. The experimental results indicate that the proposed strategy surpasses existing strategies in terms of network delivery ratio, end-to-end delay, throughput, packet delivery, and node remaining energy level.
Atmospheric emission assessment for LNG carriers: a state-of-the-art semi-empirical methodology
Authors: Gutiérrez Carlos Gonzalez , Martínez Álvaro Herrero , de Navamuel Emma Diaz Ruiz , Piris Andrés Ortega , Rojo Beatriz Blanco 
Published: February 2025

Abstract
This research establishes an extensive set of algorithms for the precise evaluation of fuel consumption across a range of engine types and systems onboard LNG carriers (LNGCs). The principal objective of this research is the development of a modern, universally applicable, and refined methodology tailored to LNGCs. This methodology encompasses the comprehensive calculation of both fuel consumption and atmospheric emissions, accommodating the variability in engine configurations. Furthermore, the integration of empirical data derived from 73 operational LNGCs yields a meticulously crafted operational profile. This consequential outcome of our study carries significant implications for addressing forthcoming modeling complexities specific to LNGCs.
GC/MS-based quantitative analysis of sulfide ion in whole blood using ethenesulfonyl fluoride as a derivatization reagent
Authors: Shiraki Ryosuke , Ogawa Shin , Wakigawa Kengo , Okazaki Hidehiko , Gohda Akinaga , Mori Takeshi , Katayama Yoshiki 
Published: February 2025

Abstract

Purpose
Identification and quantification of sulfide ion in biological samples are required in forensic purpose. Gas chromatography-mass spectrometry (GC/MS) has been used for the analysis of sulfide ion by using derivatization reagents. However, conventional derivatization reagents require special attention for derivatization. To simplify the derivatization protocol, we examined ethenesulfonyl fluoride (ESF) as a derivatizing reagent of sulfide ion.

Methods
To 100 μL of whole blood sample containing sulfide ion, 100 μL of boric acid buffer (pH 8.0), 100 μL of acetone solution containing internal standard, 100 μL of acetone solution containing 600 mM concentration of ESF, and 100 μL of hexane were added in a 1.5-mL plastic tube. The mixture was vortexed at room temperature, the tubes were centrifuged, and the organic layer was injected into the GC/MS.

Results
ESF exhibited higher reactivity toward sulfide ion than interfering compounds present in whole blood, allowing for selective derivatization. With the optimized protocol, the detection limit for sulfide ion was 0.01 μg/mL. The calibration curve showed good linearity (R
2 = 0.9999) in the range of 0.05–10.0 μg/mL, and the precision (% relative standard deviation) and the accuracy (% bias) were within ± 10% (intra- and inter-day).

Conclusion
This GC/MS-based method is a valuable tool for forensic investigations and various analytical fields, offering reliable quantification of sulfide ion in whole blood.
Supportive care needs among head and neck cancer patients in the recovery phase from 6 months to 2 years after treatment: which factors matter?
Authors: Molenaar D. , Verdonck-de Leeuw I. M. , Lissenberg-Witte B. I. , Takes R. P. , de Bree R. , Langendijk J. A. , Hardillo J. A. , Lamers F. , Leemans C. R. , Jansen F. 
Published: February 2025

Abstract

Purpose
To investigate which demographic, personal, clinical, physical, psychological, social, lifestyle, and cancer-related quality of life (QoL) factors are associated with (changes in) supportive care needs (SCNs) from 6 months to 2 years after treatment in head and neck cancer (HNC) patients.

Methods
Data from the prospective NETherlands QUality of life and BIomedical Cohort (NET-QUBIC) study among HNC patients treated with curative intent was used. SCNs were measured using the Supportive Care Needs Survey 34-item Short-Form (SCNS-SF34) (6 months, 1 and 2 years after treatment) and the 11-item HNC-specific module (SCNS-HNC) (2 years). Multivariable linear mixed model analyses and linear regression analyses were used to study factors associated with changes in SCNs over time (SCNS-SF34) and the level of SCNs at 2 years follow-up (SCNS-SF34 and SCNS-HNC).

Results
Data from 483 patients was used. SCNs in the physical and daily living (PDL), psychological (PSY), and health system, information, and patient support (HSIPS) domains decreased significantly over time. At 2 years follow-up, the highest SCNs were reported regarding lack of energy/tiredness (10.8%). Changes in SCNs and the absolute level of SCNs at 2 years were associated with personal and clinical factors and post-treatment (6 months) with psychological, lifestyle, and cancer-related QoL factors.

Conclusions
Personal, clinical, psychological, lifestyle, and cancer-related QoL factors were associated with SCNs. These results can be used to develop predictive models to personalize supportive care for HNC patients.

Implications for Cancer Survivors
SCNs decrease over time, but a subgroup of patients still presents with SCNs 2 years after treatment.
Nanotechnology-Based Therapeutics for Airway Inflammatory Diseases
Authors: Cui Limei , Yang Yujuan , Hao Yan , Zhao Hongfei , Zhang Yu , Wu Tong , Song Xicheng 
Published: February 2025

Abstract
Under the concept of “one airway, one disease”, upper and lower airway inflammatory diseases share similar pathogenic mechanisms and are collectively referred to as airway inflammatory diseases. With industrial development and environmental changes, the incidence of these diseases has gradually increased. Traditional treatments, including glucocorticoids, antihistamines, and bronchodilators, have alleviated much of the discomfort experienced by patients. However, conventional drug delivery routes have inherent flaws, such as significant side effects, irritation of the respiratory mucosa, and issues related to drug deactivation. In recent years, nanomaterials have emerged as excellent carriers for drug delivery and are being increasingly utilized in the treatment of airway inflammatory diseases. These materials not only optimize the delivery of traditional medications but also facilitate the administration of various new drugs that target novel pathways, thereby enhancing the treatment outcomes of inflammatory diseases. This study reviews the latest research on nano-drug delivery systems used in the treatment of airway inflammatory diseases, covering traditional drugs, immunotherapy drugs, antimicrobial drugs, plant-derived drugs, and RNA drugs. The challenges involved in developing nano-delivery systems for these diseases are discussed, along with a future outlook. This review offers new insights that researchers can utilize to advance further research into the clinical application of nano-drug delivery systems for treating airway inflammatory diseases.
Addressing the Contemporary Challenges of Business Process Compliance
Authors: Adams Nigel , Augusto Adriano , Davern Michael , Rosa Marcello La 
Published: February 2025

Abstract
The aim of business process compliance (BPC) is to ensure that business processes are executed in accordance with a prescribed set of rules. In practice, the evidence would suggest that achieving this goal is challenging. Penalties and subsequent remediation costs in the Australian banking industry amounted to over A$10bn between 2017 and 2022. The research community has identified many challenges, but the industry perspective is typically missing from that research. The study takes advantage of recent events in the Australian banking industry that saw detailed regulatory reports made public, highlighting the challenges the industry faces trying to maintain compliance. The study supplements these reports with BPC-related insights from practitioners and consultancy groups to develop an industry perspective on the challenges. Consolidating the two perspectives presents a comprehensive view of BPC’s challenges and the differing emphasis that each stakeholder group places on the challenges. Process mining may provide a pathway to reconciling these different perspectives. Both the BPC literature and industry have promoted process mining’s potential to address the challenges. To explore this proposition, the study details the features of representative commercial process mining software and then maps these features to the challenges. The resultant conceptual map is used to analyze known and novel BPC challenges. It outlines the limitations that must be addressed, from both a research and industry perspective, to maintain and improve compliance.
New insights into immobilized bacterial systems for removal of heavy metals from wastewater
Authors: Jhariya U. , Chien M.-F. , Umetsu M. , Kamitakahara M. 
Published: February 2025

Abstract
Industrial and anthropogenic activities release heavy metals (HMs) from natural resources, transforming them into toxic elements. HMs can be extremely toxic, even at very low concentrations; their bioaccumulative nature damages ecosystem endurance and human health. Bacterial bioremediation of HMs is an effective, sustainable, and reliable method owing to inherent and adaptive systems of bacteria that facilitate significant HMs removal via adsorption, ion exchange, and bioaccumulation. However, the use of free cells in wastewater treatment compromises bioremediation efficiency. Bacterial immobilization emerges as a promising visionary technique for treating HMs-contaminated wastewater. Therefore, the present review elucidates the potential of various bacterial remediation mechanisms and highlights current research outcomes in the field of metal ion bioremediation. Furthermore, this review explores the importance and potential applications of bacterial immobilization in the context of metal ion bioremediation. A comprehensive literature review was conducted to demonstrate the advantages of immobilized bacterial cells in HM-contaminated wastewater treatment. The groundbreaking relationship between bacterial HM removal mechanisms and immobilization methods has been conclusively established. Future research that integrates bacterial HM removal mechanisms and bacterial immobilization methods could play an instrumental role in the effective treatment strategies and efficient recovery of HMs from wastewater.
Influence of quality features, disturbances, sensor data, and measurement time on quality prediction for ultrasonic metal welding
Authors: Müller Florian Werner , Mirz Christian , Schiebahn Alexander , Reisgen Uwe 
Published: February 2025

Abstract
The production of electrical components for vehicles, battery systems, and power electronics components using ultrasonic metal welding is now well established. The industrial applications take advantage of the large joining surface and the associated excellent electrical and thermal conduction properties. However, this also prevents the weld quality from being monitored based on resistance measurements. For this reason, mechanical properties are used as a substituting quality criterion for process optimization and control. The type of mechanical testing depends on the component geometry, resulting in different quality features not necessarily comparable to each other. The ultrasonic metal welding process takes place in successive phases, which are characterized by the varying relative movements of the parts to be joined and the welding tools, prone to changes of material hardness, surface cleanliness, and geometric deviations. In this study, we investigate the influence of different mechanical quality features as target parameters for quality prediction on prediction accuracy and robustness. For this purpose, we consider the joint formation and the mechanical strength over the welding time for different quality parameters, fracture behaviors, and joint geometries. Supervised machine-learning quality prediction models are developed for the respective processes. The predictions are based on external and internal welding machine sensors. In addition to the sensor configuration, the importance of the individual process phases as a data source for the prediction accuracy is also investigated. We show that the overall process predictability strongly depends on the quality of the quality feature itself. Combining different sensor signals improves prediction quality. Furthermore, an analysis of the first process phases is sufficient for a robust quality prediction.
Eicosanoids in Coronary Sinus Correlate with NT-proBNP in Heart Failure with Reduced Ejection Fraction Indicated to Resynchronization Therapy: Insights from Eicosanoids in Human Heart Failure Study
Authors: Kala P. , Hnat T. , Mikula J. , Jezdikova K. , Kotaska K. , Honek J. , Ostadal P. 
Published: February 2025

Abstract

Introduction
The diagnostic potential of eicosanoids, metabolites of arachidonic acid with cardio-renal activity, in chronic heart failure with reduced ejection fraction (HFrEF) remains unclear. The aim was to investigate levels of eicosanoids in different body compartments and their relation to natriuretic peptides.

Material and methods
Eleven HFrEF patients indicated to cardiac resynchronization therapy (CRT) were enrolled to measure 14,15-epoxyeicosatrienoic acid (14,15-EET), 14,15-dihydroxyicosatrienoic acid (14,15-DHET) and N-terminal pro B-type natriuretic peptide (NT-proBNP) levels from venous, arterial, and coronary sinus (CS) blood samples.

Results
In CS, NT-proBNP negatively correlated with plasmatic 14,15-EET (r = − 0.63, p = 0.03) and positively with the DHET/EET ratio (r = 0.73, p = 0.02). This correlation was not found in the other compartments. Plasmatic 14,15-EET nor 14,15-DHET levels in measured compartments did not differ statistically (p = 0.21, p = 0,64, respectively). In individual patients, the levels of both eicosanoids correlated across all compartments. Peripheral plasma 14,15-EET levels in controls were lower compared to HFrEF patients.

Conclusions
Peripheral venous eicosanoid (14,15-EET, 14,15-DHET) levels correlate and do not differ from arterial and CS levels in patients with HFrEF indicated to CRT. In CS, NT-proBNP negatively correlates with plasmatic 14,15-EET and positively with the DHET/EET ratio, an indirect measurement of soluble epoxide hydrolase (sEH) activity, suggesting an important role of eicosanoids and sEH in HFrEF pathophysiology.

Graphical abstract
Accessory Spleen: An Anatomical Variation or Developmental Defect? Surgical, Anatomical and Embryological Perspectives
Authors: Mayer Alexander , Varga Ivan , Kachlik David , Voller Jaroslav , Fuljer Ivan , Jackuliak Peter 
Published: February 2025

Abstract
As the spleen is a morphologically highly variable organ, radiologists and surgeons frequently encounter normal variants which might be misinterpreted. Accessory spleen is quite a common anatomical variation and generally does not causes any symptoms. However, the finding of an accessory spleen located outside its usual position—the splenic hilum or surrounding. peritoneal folds—is relatively rare in clinical practice and can cause serious diagnostic and/or therapeutic complications: It may mimic a solid tumour or an enlarged lymph. In the review, we summarise the possible anatomical localisations of the accessory spleens (from the thoracic cavity to lesser pelvis and scrotum in males), as well as the diagnostic problems and challenges that the atypical anatomical localisation often causes. We also summarise recent knowledge about the embryological background of accessory spleen formation and address the classification of such a finding—is it a harmless anatomical variation, a developmental defect or a pathological condition of the spleen? According to the recent scientific literature and based the modern imaging techniques, the frequency of accessory spleens is so high that it should be considered rather an anatomical variation than a developmental defect.