bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient Removal of Aqueous Heavy Metal Cd2+ by Alanine Intercalation of MgAl–LDH: Adsorbent Preparation, Characterization, Adsorption Performance, and Mechanisms
Authors: Shi Dandan , Ren Yinmei , Wang Xingquan , Han Xing , Zhu Xiang , Xu Naicai 
Published: February 2025

AbstractIn this work, MgAl‐NO3‐LDH was prepared by co‐precipitation method, and the alanine intercalation of MgAl‐Ala‐LDH was prepared by roasting and recovery method. The structure, morphology and pore size of prepared materials were systematically characterized by XRD, SEM, TEM, BET, XPS, TG‐DTG and FTIR. The (003) diffraction peak of MgAl‐Ala‐LDH shifted from 11.29° to 6.17° and the interlayer spacing of d(003) expanded from 0.79 nm to 1.33 nm, indicating that alanine was successfully inserted into the hydrotalcite interlayer. The effects of solution pH, initial concentration of Cd2+, time, temperature and quality of the adsorbent on Cd2+ adsorption performance were studied. The results indicate that when the pH value of CdCl2 solution is 5–6 and the temperature is 45℃, the Cd2+ adsorption capacity of MgAl‐NO3‐LDH and MgAl‐Ala‐LDH are 39.7 mg/g and 135.5 mg/g, respectively. The adsorption data conforms to the pseudo‐second‐order kinetic and Langmuir model, indicating that the adsorption process is monolayer adsorption and controlled by chemisorption. Thermodynamic investigations indicated that higher temperatures facilitated Cd2+ adsorption and strengthened the affinity with MgAl‐Ala‐LDH. The mechanisms of Cd2+ adsorption mainly include surface complexation, chelation and isomorphic substitution. MgAl‐Ala‐LDH may have a good application prospect in the removal of heavy metal ions.
Perspectives on the incorporation of self‐healing in the design practice of reinforced concrete structures
Authors: He Shan , Sayadi Sina , Patel Ravi A. , Schultheiß Annika Lidwina , Mihai Iulia C. , Jefferson Anthony , Jonkers Henk M. , Luković Mladena , Schlangen Erik , Dehn Frank 
Published: February 2025

AbstractSelf‐healing concrete, with its ability to autonomously repair damages, holds promise in enhancing its structural durability and resilience. Research on self‐healing concrete in the past decade has advanced in understanding the mechanisms behind healing, exploring various healing agents, and assessing their effectiveness in concrete structures. However, the full potential of self‐healing concrete remains untapped unless its effects are effectively integrated into the design practices of reinforced concrete structures. Realizing this challenge, this paper synthesizes the current research progress and discusses the possibilities to consider self‐healing into design codes. The focus was placed on two specific benefits of applying self‐healing concrete: one centered on durability and the other on mechanical performance. Specifically, the effect of self‐healing on impeding chloride penetration into cracked reinforced concrete was discussed first. Modifications of parameters in existing predictive models based on different types of healing approaches were recommended. Furthermore, the possible impact of the self‐healing capacity in mitigating the stiffness reduction of concrete was also discussed. Equations that can describe the stiffness regained due to healing action are presented. In each part of the case study, limitations and challenges still hindering standardization and wider application in the construction field are discussed.
Stokes flow past circular cylinders in an out‐phase slip patterned microchannel using boundary element method
Authors: Chhabra Vishal , Nishad Chandra Shekhar , Vijay K. G. , Sahni Manoj 
Published: February 2025

AbstractThe objective of the present study is to investigate a steady, pressure‐driven two‐dimensional viscous incompressible creeping flow characterized by low Reynold's limit around circular cylinders of equal diameter inside a microchannel exhibiting wall roughness. The wall roughness is modeled using Navier's slip condition on the horizontal surfaces in an alternative manner, which retains a phase difference (i.e., out‐phase arrangement). The governing equations are solved using the stream function‐vorticity variables approach of the boundary element method. We considered the two instances of wall roughness, namely large and fine patterned wall roughness depending on the periodicity of patterning. We studied the streamline and vorticity contour plots, flow profiles, and shear stresses with varying slip lengths and radii of the horizontally aligned configuration of circular cylinders to obtain an in‐depth understanding of flow mechanics. The flow velocity and the shear stress show larger values when fine‐patterned wall roughness is considered. The present framework has immense feasible implications such as optimizing microfluidic devices, enhancing thermal management in electronics, and advancing nanofluidic platforms for various molecular and biomedical applications, including drug delivery systems.
Bilateral Hippocampi Segmentation in Low Field MRIs Using Mutual Feature Learning via Dual-Views
Authors: Peiris Himashi , Chen Zhaolin 
Published: February 2025

Abstract
Accurate hippocampus segmentation in brain MRI is critical for studying cognitive and memory functions and diagnosing neurodevelopmental disorders. While high-field MRIs provide detailed imaging, low-field MRIs are more accessible and cost-effective, which eliminates the need for sedation in children, though they often suffer from lower image quality. In this paper, we present a novel deep-learning approach for the automatic segmentation of bilateral hippocampi in low-field MRIs. Extending recent advancements in infant brain segmentation to underserved communities through the use of low-field MRIs ensures broader access to essential diagnostic tools, thereby supporting better healthcare outcomes for all children. Inspired by our previous work, Co-BioNet, the proposed model employs a dual-view structure to enable mutual feature learning via high-frequency masking, enhancing segmentation accuracy by leveraging complementary information from different perspectives. Extensive experiments demonstrate that our method provides reliable segmentation outcomes for hippocampal analysis in low-resource settings. The code is publicly available at: https://github.com/himashi92/LoFiHippSeg.
Automated Quality Assessment Using Appearance-Based Simulations and Hippocampus Segmentation on Low-Field Paediatric Brain MR Images
Authors: Sundaresan Vaanathi , Dinsdale Nicola K 
Published: February 2025

Abstract
Understanding the structural growth of paediatric brains is a key step in the identification of various neuro-developmental disorders. However, our knowledge is limited by many factors, including the lack of automated image analysis tools, especially in Low and Middle Income Countries from the lack of high field MR images available. Low-field systems are being increasingly explored in these countries, and, therefore, there is a need to develop automated image analysis tools for these images. In this work, as a preliminary step, we consider two tasks: 1) automated quality assurance and 2) hippocampal segmentation, where we compare multiple approaches. For the automated quality assurance task a DenseNet combined with appearance-based transformations for synthesising artefacts produced the best performance, with a weighted accuracy of 82.3%, thus ranking in the 1st place in the LISA2024 Challenge. For the segmentation task, registration of an average atlas performed the best, with a final Dice score of 0.61. Our results show that although the images can provide understanding of large scale pathologies and gross scale anatomical development, there still remain barriers for their use for more granular analyses.
Axis-Guided Quality Assessment and Multi-label Hippocampal and Ventricular Segmentation in Low-Resolution Pediatric Brain MRI
Authors: Kim Hyunwook , Seo Jinew , Ryu Seiyoung , Park Joon hyung , On Sungchul , Choi Jinwha 
Published: February 2025

Abstract
The Swoop system of Hyperfine Inc. is an affordable, ultra-low-field MRI developed for use in a clinical setting. However, despite its advantages, the relatively low resolution of 64mT MRI data poses additional challenges, especially in examining small structures such as the hippocampus or vessels. As a part of our attempt at the Low field pediatric brain magnetic resonance Image Segmentation and Quality Assurance (LISA) Challenge 2024, we developed two deep learning-based models. First, to evaluate the image quality of 64mT T2 brain MRI data, we implemented an axis classifier module to improve the model performance. Second, for segmentation of the hippocampus in the MRI, a multi-label learning method was used for more accurate segmentation. With these models, we expect to alleviate the accessibility barrier to brain MRI.
Perimeter of Triangles Inscribed in the Unit Ball of Normed Planes
Authors: Alonso J. , Martín P. , Papini P. L. 
Published: February 2025

Abstract
Given a normed plane, we consider the ranges of perimeters concerning some classes of triangles whose vertices are points on the unit sphere. The problems studied are essentially geometric. We try to collect several results that are scattered in different journals, comparing and improving some of them. Some illustrative examples are presented. Finally, some open problems are proposed.
Impaired mitochondrial integrity and compromised energy production underscore the mechanism underlying CoASY protein-associated neurodegeneration
Authors: Shao Yuzhuo , Hu Jiaxin , Yan Kunhao , Zheng Keke , Sha Wenchi , Wang Jinlong , Wu Jiarui , Huang Yunpeng 
Published: February 2025

Abstract
Coenzyme A (CoA) is a crucial metabolite involved in various biological processes, encompassing lipid metabolism, regulation of mitochondrial function, and membrane modeling. CoA deficiency is associated with severe human diseases, such as Pantothenate Kinase-Associated Neurodegeneration (PKAN) and CoASY protein-associated neurodegeneration (CoPAN), which are linked to genetic mutations in Pantothenate Kinase 2 (PANK2) and CoA Synthase (CoASY). Although the association between CoA deficiency and mitochondrial dysfunction has been established, the underlying molecular alterations and mechanisms remain largely elusive. In this study, we investigated the detailed changes resulting from the functional decline of CoASY using the Drosophila model. Our findings revealed that a reduction of CoASY in muscle and brain led to degenerative phenotypes and apoptosis, accompanied by impaired mitochondrial integrity. The release of mitochondrial DNA was notably augmented, while the assembly and activity of mitochondrial electron transport chain (ETC) complexes, particularly complex I and III, were diminished. Consequently, this resulted in decreased ATP generation, rendering the fly more susceptible to energy insufficiency. Our findings suggest that compromised mitochondrial integrity and energy supply play a crucial role in the pathogenesis associated with CoA deficiency, thereby implying that enhancing mitochondrial integrity can be considered a potential therapeutic strategy in future interventions.
37 kDa LRP::FLAG enhances telomerase activity and reduces ageing markers in vivo
Authors: Otgaar Tyrone C. , Bernert Martin , Morris Gavin , Baichan Pavan , Bignoux Monique J. , Letsolo Boitelo , Weiss Stefan F. T. , Ferreira Eloise 
Published: February 2025

Abstract
Ageing is a degenerative process characterised by a decline in physiological functioning of the organism. One of the core regulators of cellular ageing are telomeres, repetitive DNA sequences of TTAGGG that cap the ends of chromosomes and are maintained by the ribonucleoprotein complex, telomerase. Age-dependent progressive loss of the telomere ends eventually induces cell cycle arrest for the induction of either replicative senescence or apoptosis. It was previously established that overexpression of the 37 kDa/ 67 kDa laminin receptor (LRP/LR) increased telomerase activity and telomere length while concomitantly reducing senescence markers in aged normal cells in vitro. Therefore, it was hypothesized that elevating LRP/LR in vivo may increase telomerase activity and hinder the ageing process on an organism scale. To this end, aged C57BL/6J mice were treated/transfected to induce an overexpression of LRP::FLAG. Various physiological tests and histological analyses were performed to assess overall organism fitness as well as to discern the treatments’ ability at reducing tissue degeneration and atrophy. It was found that mice overexpressing LRP::FLAG displayed improved physiological characteristics and markedly less tissue degeneration and atrophy when compared to control and non-treated mice. Alongside these improvements, certain organs displayed increased telomerase activity with a corresponding elongation in average telomere length. In addition the overexpression of LRP::FLAG significantly improved various proliferative and anti-ageing associated proteins while causing a concomitant decrease in senescence associated proteins. These findings are therefore indicative of a novel function of LRP/LR delaying the onset of senescence, while also promoting healthier ageing through elevating TERT and telomerase activity.
Almost Sure GOE Fluctuations of Energy Levels for Hyperbolic Surfaces of High Genus
Authors: Rudnick Zeév , Wigman Igor 
Published: February 2025

Abstract
We study the variance of a linear statistic of the Laplace eigenvalues on a hyperbolic surface, when the surface varies over the moduli space of all surfaces of fixed genus, sampled at random according to the Weil–Petersson measure. The ensemble variance of the linear statistic was recently shown to coincide with that of the corresponding statistic in the Gaussian orthogonal ensemble (GOE) of random matrix theory, in the double limit of first taking large genus and then shrinking size of the energy window. In this note, we show that in this same limit, the (smooth) energy variance for a typical surface is close to the GOE result, a feature called “ergodicity” in the random matrix theory literature.
Traffic volume measurement using nonlinear count-lines
Authors: Iwao Yuwa , Yamamoto Yota , Yaginuma Hideki , Taniguchi Yukinobu 
Published: February 2025

Abstract
Traffic volume measurements are increasingly recognized as important for improving society’s infrastructure, by functions such as managing congestion and enhancing logistics. Dedicated traffic data capture devices that use sensors embedded in the road enable accurate measurements but have the problems of high cost and limited installation locations, which make it difficult to expand the coverage of traffic volume measurements. To address this issue, the approach that combines already deployed Closed-Circuit Television (CCTV) cameras with image recognition technology has attracted attention and offers practical performance in ordinary situations. One remaining problem is that accuracy is degraded by the presence of headlight flare at nighttime and occlusion by large vehicles on busy roads. In this paper, we propose a method for measuring traffic volume that automatically sets count-lines using the Kernel Support Vector Machine (Kernel SVM) at optimal positions less affected by these issues. In addition, to make the proposal robust to illumination changes and occlusion we introduce nonlinear count-lines. Extensive experiments on Japanese road video footage shows that our method improves accuracy by
$$5.9\%$$
at night and
$$2.1\%$$
in situations prone to occlusion compared to the most basic fixed count-line method. Additionally, experiments on a public dataset, UA-DETRAC, demonstrate the proposal’s effectiveness in countries other than Japan.
The seen and unseen: the unintended impact of a conditional cash transfer program on prenatal sex selection
Authors: Javadekar Sayli , Saxena Kritika 
Published: February 2025

Abstract
This study examines the unintended consequences of the Janani Suraksha Yojana, a conditional cash transfer program in India, on prenatal sex-selective behaviour within a son-preference culture. This program unintentionally altered existing trends in prenatal sex selection through its simultaneous provision of cash incentives to households and community health workers as well as access to prenatal sex detection technology such as ultrasound scans. Using difference-in-differences and triple difference estimators we find that the program causes an increase in the likelihood of female births. Furthermore, we observe a rise in under-5 mortality for girls born at higher birth orders, suggesting a shift in discrimination against girls from prenatal to postnatal. Our calculations suggest that the net impact was approximately 300,000 girls surviving in treated states between 2006 and 2015. Finally, we find suggestive evidence that the involvement of community health workers in facilitating the program is a key driver of this trend. Overall, this study sheds light on the complex interplay between policy interventions, cultural norms, and gender disparities in shaping demographic outcomes.
PFC/PFAS concentrations in human milk and infant exposure through lactation: a comprehensive review of the scientific literature
Authors: González Neus , Domingo Jose L. 
Published: February 2025

Abstract
Per- and polyfluoroalkyl substances (PFAS), previously known as perfluorinated compounds (PFC), are a group of synthetic chemicals widely used over the past decades. Their extensive application, combined with their environmental persistence, has contributed to their ubiquitous presence in the environment and the associated toxicological risks. Regarding humans, blood serum testing remains the primary method for biomonitoring PFAS exposure, while breast milk has also been used due to the transfer of these substances from mothers to infants during lactation. This paper aims to review the scientific literature (using PubMed and Scopus databases) on PFAS concentrations in the breast milk of non-occupationally exposed women. Where available, the estimated daily intake of these compounds by breastfeeding infants is also examined. The reviewed studies are categorized by continent and country/region, revealing a significant lack of data for many countries, including both developed and developing nations. The findings indicate substantial variability in PFAS concentrations, influenced by factors such as geographic location, sampling year, and the specific PFAS analyzed. Among the identified compounds, perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are most commonly detected, along with perfluorohexanesulfonic acid (PFHxS) and perfluorononanoic acid (PFNA), being the only PFAS with regulated maximum levels in certain foodstuffs. Most studies were conducted before the implementation of the current (updated) tolerable weekly intake (TWI) values for these substances. Consequently, the majority reported a low health risk for breastfeeding infants, even in high-intake scenarios. Nevertheless, biomonitoring studies are urgently needed in countries with limited or no data, and new investigations should assess whether current estimated intakes exceed the updated TWI. Special focus should be given to rural and industrial areas where exposure levels remain poorly understood.
Efficacy, safety and mechanistic insights of pentoxifylline in major depressive disorder: a systematic review and meta-analysis of randomized controlled trials
Authors: Kassar Omar , Farag NourAllah , Selim Abdullah , Taman Lamees , Alaa Menna , Elshahat Ahmed , Abouelmagd Moaz Elsayed 
Published: February 2025

Abstract
Novel treatments that act beyond the conventionally targeted monoamine system are urgently needed to provide more effective relief for patients with major depressive disorder. Pentoxifylline (PTX) is a phosphodiesterase inhibitor with potent anti-inflammatory and antioxidant effects, with additional pleiotropic effects. This is the first systematic review and meta-analysis to examine the role of PTX in major depressive disorder. A comprehensive search of electronic databases, including PubMed, Scopus, Cochrane, and Web of Science, was performed in October 2024. We included only randomized controlled trials (RCTs), and their data were extracted and analyzed using Reman 5.4 software. The primary outcome was the change in Hamilton Depression Rating Scale (HAM-D). Four RCTs with 318 patients were included in the study. PTX showed a statistically significant improvement in HAM-D scores at the primary endpoint compared to the placebo (MD = –3.84, 95% CI [–4.87 to –2.81], P < 0.00001). Moreover, PTX showed a statistically significant increase in serotonin and BDNF levels (MD = 20.76 ng/mL, 95% CI [5.49 to 36.04], P = 0.008; and MD = 10.83 ng/mL, 95% CI [-0.22 to 21.88], P = 0.05, respectively) and a statistically significant decrease in TNF-α and IL-6 levels (MD = –3.24 pg/mL, 95% CI [–4.12 to –2.36], P < 0.00001; and MD = –2.64 pig/mL, 95% CI [–3.79 to –1.48], P < 0.00001, respectively). There was no statistically significant difference between the PTX and placebo in any of the reported side effects. The study findings suggest that PTX may be effective and safe as an adjuvant antidepressant agent in patients with MDD, demonstrating a significant reduction in HAM-D scores. The results of this study need to be interpreted with caution considering several limitations.
GlycoDash: automated, visually assisted curation of glycoproteomics datasets for large sample numbers
Authors: Pongracz Tamas , Gijze Steinar , Hipgrave Ederveen Agnes L. , Derks Rico J. E. , Falck David 
Published: February 2025

Abstract
The challenge of robust and automated glycopeptide quantitation from liquid chromatography-mass spectrometry (LC–MS) data has yet to be adequately addressed by commercial software. Recently, open-source tools like Skyline and LaCyTools have advanced the field of label-free MS1 level quantitation. Yet, important steps late in the data processing workflow remain manual. Because manual data curation is time-consuming and error-prone, it presents a bottleneck, especially in an era of emerging high-throughput methodologies and increasingly complex analyses such as antigen-specific antibody glycosylation. We addressed this gap by developing GlycoDash, an R Shiny-based interactive web application designed to democratize label-free high-throughput glycoproteomics data analysis. The software comes in at a stage where analytes have been identified and quantified, but whole measurement and individual analyte signals of insufficient quality for quantitation remain and reduce the quality of the overall dataset. GlycoDash focuses on these challenges by incorporating several options for measurement and metadata linking, spectral and analyte curation, normalization, and repeatability assessment, and additionally includes glycosylation trait calculation, data visualization, and reporting capabilities that adhere to FAIR principles. The performance and versatility of GlycoDash were demonstrated across antibody glycoproteomics data of increasing complexity, ranging from relatively simple monoclonal antibody glycosylation analysis to a clinical cohort with over a thousand measurements. In a matter of hours, these large, diverse, and complex datasets were curated and explored. High-quality datasets with integrated metadata ready for final analysis and visualization were obtained. Critical aspects of the curation strategy underlying GlycoDash are discussed. GlycoDash effectively automates and streamlines the curation of glycopeptide quantitation data, addressing a critical need for high-throughput glycoproteomics data analysis. Its robust performance across diverse datasets and its comprehensive feature toolbox significantly enhance both research and clinical applications in glycoproteomics.

Graphical Abstract