bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hopelessness as a Mediator of the Association Between Parenting Factors and Adolescent Suicidality and Substance Use Among Juvenile Justice‐Referred Youth
Authors: Guerrero Natalie , O'Reilly Lauren , Dellucci Trey V. , Pederson Casey , Adams Zachary W. , Hulvershorn Leslie , Zapolski Tamika C. B. , Aalsma Matthew C. 
Published: February 2025

ABSTRACTYouth involved in the juvenile justice system are more likely to have a substance use disorder and/or suicidality (e.g., suicidal thoughts and behavior) compared to other youth. Although parental support and monitoring may play an important role in youth substance use and suicidality outcomes, the potential mechanisms have not been elucidated. Our purpose was to evaluate the extent to which parental support and monitoring were associated with latent, continuous construct scores of suicidality and substance use and to determine whether youths’ hopelessness may indirectly affect these relationships among a sample of youth referred to the juvenile justice system. The sample included juvenile justice‐referred youth aged 14–17 (N = 77; 69% White, 58% male, 74% non‐Hispanic). The primary predictors of interest were parental support and monitoring, measured by the Parent Support Scale and Parental Monitoring Scale. The primary potential mediator of interest was hopelessness. Linear regression was used to model continuous suicidality and substance use severity scores, measured via a computer adaptive test, on parental support and monitoring. We tested hopelessness as a potential mediator. All analyses controlled for age, sex assigned at birth, race, ethnicity, and family income. After adjustment, parental support was associated with decreased suicidality severity (β = −0.30, p = 0.002). Parent support and monitoring were associated with youth‐reported hopelessness. The indirect mediation effects of hopelessness in the relationship between parental support (β = −0.18 [SE, 1.73]), as well as parental monitoring (β = −0.17 [SE, 0.20]), and suicidality severity were statistically significant. Parental support and youth hopelessness may be important intervention targets for improving and addressing disparities in substance use and suicidality among juvenile justice‐referred youth. Hope‐based interventions may be effectively integrated into existing juvenile justice programs, and their potential to improve both mental health and behavioral outcomes among justice‐involved youth should be examined.
Frequency‐aware denoising using a diffusion model for enhanced band‐limited and white noise removal in x‐ray acoustic computed tomography
Authors: Peng Jiayuan , Lu Mengyang , Li Boyi , Wang Jiazhou , Hu Weigang , Liu Xin 
Published: February 2025

AbstractBackgroundRadiation therapy delivers precise doses to tumors, but accurately measuring internal tissue doses remains a challenge. Current methods, such as ionization chambers and radiographic films, rely on external measurements, which cannot provide direct, in vivo dose feedback. X‐ray acoustic computed tomography (XACT) was developed to generate thermoacoustic signals when x‐rays deposit energy into water or tissue, enabling the reconstruction of dose distribution patterns through acoustic signals. However, the longer pulse width of x‐rays from linear accelerators reduces the efficiency of thermoacoustic signal conversion, lowering the signal‐to‐noise ratio (SNR) of radiofrequency (RF) signals. This noise significantly affects the quality of reconstructed XACT images. Overcoming the impact of noise is essential for advancing XACT toward accurate dose detection.PurposeThis study aims to develop a frequency‐aware denoising (FAD) method for overcoming the impact of band‐limited and white noise in RF signals for XACT.MethodsReal RF signals were acquired from an XACT system using radiotherapy megavoltage (MV) x‐rays, a water tank, and an ultrasound transducer. To capture the frequency characteristics of these RF signals, we first estimated the probability density function (PDF) of their frequency spectrum. To generate synthetic RF data that closely approximates realistic noisy signals for model training, noise was sampled from this PDF, incorporating both magnitude and random phase components, and combined with simulated signals and white noise. A conditional diffusion model was trained on these synthetic signals to obtain the FAD model. A total of 3150 frequency‐aware RF data samples were used to train the FAD model. For testing, acoustic RF signal data excited by five different x‐ray shapes were measured, denoised by the FAD model, and finally reconstructed into XACT. The performance of the method was evaluated based on XACT image quality using SNR analysis and γ passing rate, and compared with results from Raw‐RF and background noise‐removed (BNR‐RF) methods.ResultsThe FAD‐RF method produced XACT images with clearer structural details and fewer artifacts. It achieved the highest SNR among the tested methods, with a mean SNR of 27.6 ± 5.0, outperforming both Raw‐RF (22.9 ± 2.2, p < 0.05) and BNR‐RF (22.0 ± 3.0, p < 0.05). In terms of spatial accuracy, the FAD‐RF method also outperformed in γ analysis, achieving a mean γ passing rate of 79.0% ± 2.4%, significantly higher than Raw‐RF (50.2% ± 20.0%, p < 0.05) and BNR‐RF (73.5% ± 3.6%, p = 0.078).ConclusionThe FAD‐RF method relies solely on the RF signals for denoising, making it practical and efficient for real‐world applications. It demonstrates effective noise suppression and enhanced spatial accuracy in XACT image reconstruction.
Neural architecture search with Deep Radon Prior for sparse‐view CT image reconstruction
Authors: Fu Jintao , Cong Peng , Xu Shuo , Chang Jiahao , Liu Ximing , Sun Yuewen 
Published: February 2025

AbstractBackgroundSparse‐view computed tomography (CT) reduces radiation exposure but suffers from severe artifacts caused by insufficient sampling and data scarcity, which compromise image fidelity. Recent advancements in deep learning (DL)‐based methods for inverse problems have shown promise for CT reconstruction but often require high‐quality paired datasets and lack interpretability.PurposeThis paper aims to advance the field of CT reconstruction by introducing a novel unsupervised deep learning method. It builds on the foundation of Deep Radon Prior (DRP), which utilizes an untrained encoder–decoder network to extract implicit features from the Radon domain, and leverages Neural Architecture Search (NAS) to optimize network structures.MethodsWe propose a novel unsupervised deep learning method for image reconstruction, termed NAS‐DRP. This method leverages reinforcement learning‐based NAS to explore diverse architectural spaces and integrates reinforcement learning with data inconsistency in the Radon domain. Building on previous DRP research, NAS‐DRP utilizes an untrained encoder–decoder network to extract implicit features from the Radon domain. It further incorporates insights from studies on Deep Image Prior (DIP) regarding the critical impact of upsampling layers on image quality restoration. The method employs NAS to search for the optimal network architecture for upsampling unit tasks, while using Recurrent Neural Networks (RNNs) to constrain the optimization process, ensuring task‐specific improvements in sparse‐view CT image reconstruction.ResultsExtensive experiments demonstrate that the NAS‐DRP method achieves significant performance improvements in multiple CT image reconstruction tasks. The proposed method outperforms traditional reconstruction methods and other DL‐based techniques in terms of both objective metrics (PSNR, SSIM, and LPIPS) and subjective visual quality. By automatically optimizing network structures, NAS‐DRP effectively enhances the detail and accuracy of reconstructed images while minimizing artifacts.ConclusionsNAS‐DRP represents a significant advancement in the field of CT image reconstruction. By integrating NAS with deep learning and leveraging Radon domain‐specific adaptations, this method effectively addresses the inherent challenges of sparse‐view CT imaging. Additionally, it reduces the cost and complexity of data acquisition, demonstrating substantial potential for broader application in medical imaging. The evaluation code will be available at https://github.com/fujintao1999/NAS‐DRP/.
Perineal and Rectal Nerve Recruitment Order Varies During Pudendal Neurostimulator Implant Surgery
Authors: Chen Po‐Ju , Lagunas Amador C. , Soriano Vanessa , Gupta Priyanka , Bruns Tim M. 
Published: February 2025

ABSTRACTIntroductionPudendal nerve stimulation (PNS) is an off‐label therapy for patients experiencing pelvic pain and voiding dysfunction. The pudendal nerve has two efferent branches to the rectum and perineum. Only the rectal branch is monitored via external anal sphincter electromyography during the implant procedure to help determine the lead position. We examined intraoperative PNS‐driven urethral pressures to infer nerve recruitment order and tracked patient reported outcomes.MethodsPatients receiving PNS for pelvic pain and/or urinary symptoms were recruited. During the implant surgery, urethral pressure was measured with a multi‐sensor pressure catheter placed in the lower urinary tract. PNS‐driven changes in urethral pressure and external anal sphincter (EAS) electromyography were compared to determine the relative perineal and rectal nerve recruitment order. Participants completed pelvic pain, bladder, bowel, and sexual function surveys before and after the surgery. The primary outcome measure was the relative nerve recruitment order during PNS. Secondary outcome measures were the PNS‐driven urethral responses and changes in survey symptom scores due to PNS.ResultsData was collected from thirteen intraoperative sessions. Seven participants had rectal nerve recruitment first, four participants had perineal nerve recruitment first, and two participants had mixed nerve recruitment during intraoperative PNS. The average normalized urethral pressure change was 4.7% at the EAS threshold, 59.2% at twice EAS threshold, and 68.2% at three times the EAS threshold. Urethral pressure changes for each participant often varied between different active PNS electrodes. Participants had significant improvements in pelvic pain and bladder function survey scores with PNS (p < 0.04). There was no relationship between nerve recruitment order and changes in any surveys.ConclusionPNS can recruit the perineal nerve before the rectal nerve. Each lead electrode may trigger different urethral response patterns within a participant. This study provided new insights into the effect of PNS on the recruitment of nerves in the pelvis and may help guide future surgical placement of PNS systems.Clinical Trial RegistrationThis study was registered at clinicaltrials.gov (NCT04236596).
Characterization, Antibacterial Evaluation and Computational Study of Synthesized 4,5‐bis(Hydroxymethyl)‐2‐Methylpyridin‐3‐ol Tetraphenylborate Ion‐Pair Complex
Authors: Bakheit Ahmed H. , Al‐Agamy Mohamed H. , Al‐Salahi Rashad , Ali Essam , Alrabiah Haitham , Mostafa Gamal A.E. 
Published: February 2025

AbstractThe synthesis of 4,5‐bis(hydroxymethyl)‐2‐methylpyridin‐3‐ol tetraphenylborate complex in water using an anion exchange process yielded more than 76 %. The resulting white complex was obtained and characterized using various spectroscopic and analytical techniques, including ultraviolet, infrared radiation (IR), mass, elemental analysis, and nuclear magnetic resonance (NMR). The antimicrobial activity of the formed ion‐associate complex was evaluated. The structural, electrical, and bonding properties of a novel pyridoxine‐tetraphenylborate ion‐pair complex was explored using B3LYP/6‐311G(d,p) DFT simulations. Geometries designed for negative complexation energy showed thermodynamically beneficial complex formation. Reduced density gradient (RDG) analysis and non‐covalent interaction (NCI) plots showed that van der Waals forces are essential to complex stability. Quantum Theory of Atoms in Molecules (QTAIM) study detected weak and moderate hydrogen bonds in the complex using bond critical point (BCP) features. These results reveal how molecules form and stabilize the pyridoxine‐tetraphenylborate ion‐pair complex. To know the interaction between receptors and bioactive chemicals, one must understand the mechanism of the ionic complexes formed between bioactive chemicals and/or organic molecules.
Pathways between people, wildlife and environmental justice in cities
Authors: McInturff Alex , Volski Lara , Callahan Megan M. , Sneegas Gretchen , Pellow David N. 
Published: February 2025

Abstract

Wildlife are increasingly recognized as critical to urban ecosystems, but the impacts and benefits of wildlife on people in cities are poorly understood. Environmental justice scholarship has concluded that elements of the urban environment can create or exacerbate social inequity, but human–wildlife interactions have not been considered through this lens.

We conducted a literature review on urban wildlife, human–wildlife interactions and environmental justice. We triangulated between these three bodies of literature to identify trends, gaps and research needs.

We identified six pathways through which wildlife presence or absence, wildlife management and human–wildlife interactions in cities may lead to social injustice for people. Our review shows that wildlife affect nearly all aspects of urban life for people, including economics, participation in decision‐making, patterns of urban space, human health, psychological well‐being and cultural discourses.

Through these six pathways, urban wildlife management disproportionately impacts marginalized and vulnerable communities and benefits affluent urban residents. Contemporary intersections of urban planning, wildlife management and histories of systemic bias exacerbate existing injustices in cities.

Synthesis and applications. Though wildlife are often characterized as ‘good’ or ‘bad’ based on their effects on people, we conclude that this dichotomy perpetuates injustice for people and wildlife. Instead, we argue that a ‘just city’ fosters healthy wildlife populations through equitable decision‐making. The pathways we lay out here offer a road map for incorporating environmental justice into urban wildlife management.

Read the free Plain Language Summary for this article on the Journal blog.
A comprehensive review on valorization of chestnut processing wastes into bio‐based composites and bioplastics
Authors: Silva Simão B. , Freitas Olga M. , Vieira Elsa F. , Delerue‐Matos Cristina , Domingues Valentina F. 
Published: February 2025

AbstractThis review examines the characterization and utilization of chestnut processing wastes (35%) in the production of bioplastics and biocomposites. In this review, a Web of Science search without any publishing year restriction on the biochemical compositions of all the components of Castanea sativa. The obtaining of bioplastics and biocomposites based on C. sativa was reviewed. First, it highlights the biochemical composition and antioxidant properties of chestnut fruit, shell, burrs, leaves, flowers, and wood focusing on the most important compounds, such as phenolic acids, flavonoids, carbohydrates, Klason lignin, cellulose, and glucan, which can enhance the properties of these materials. Then the review covers using several chestnut extracts and fillers in bioplastics production through solvent casting technique. The mechanical, structural, bioactive properties, and moisture content were optimized through the composition and production. The color, UV absorption, antioxidant, and antimicrobial activity were also discussed. Biocomposites reinforced with chestnut burs, shells, or wood flour increased the intended properties. The enhancements in tensile strength, elastic modulus, and the effects of a pre‐treatment were evaluated. Additionally, it discusses material recovery, recycling, and reuse, particularly how it affects the biodegradability of composites incorporating chestnut waste residues.Highlights
Chestnut fruit, shells, and burrs are rich in starch, lignin, and cellulose.
The waste of chestnut processing can be used in bioplastics and biocomposites.
Chestnut‐based films and biocomposites exhibit promising mechanical properties.
The antimicrobial activity, making films, and composites proper for food packaging.
New techniques boost performance, offering alternatives to conventional plastics.
Characterization and analysis of printing challenges with high filled alumina filament in low‐cost extrusion‐based additive manufacturing
Authors: Santana Leonardo , Nagata Ester Y. , Barra Guilherme M. O. , Netto Aurélio C. S. , Pallone Elíria M. J. , Ambrósio Carlos E. , de Castro Silveira Zilda 
Published: February 2025

AbstractFused Filament Fabrication (FFF) offers promising solutions for producing fully ceramic parts using highly filled composite filaments made of polymeric binders and ceramic particles. However, the literature presents critical gaps: what materials constitute the binder, and how can the material's brittleness during the 3D printing process be managed? Addressing these questions is essential for understanding the printability of these materials and expanding their use across a wider range of 3D printers. Nanoe/Zetamix™ alumina‐filled filaments, with potential applications in Tissue Engineering, particularly in 3D‐printed scaffolds, highlight these challenges. This study focuses on three aspects: (i) material characterization; (ii) 3D printing method development; and (iii) evaluation of printed parts. Material characterization identified the filament as polyolefin‐based, likely blended with polyester, with transition temperatures indicating efficient processing and strong layer bonding. A dual‐filament method was developed to overcome brittleness, enabling the printing of small parts without damaging the filament or disrupting extrusion. Printed parts demonstrated stability, but mechanical properties varied after sintering. While the filament extruded well, brittleness impacted printability, and low viscosity affected layer stacking. This study underscores the potential of filament for scaffold fabrication but highlights the need for further research to optimize porous structure printing.Highlights
Fragility of highly filled alumina composite filament limits its overall printability
3D printing with this material needs advanced knowledge and a special method
Buildability depends on precise extrusion temperature and layer stacking strategy
Aligned layer stacking improves material's self‐support and layer bonding capacity
Material's properties are promising for 3D printing ceramic structures for bone recovery
Clinical Proteomics, Quo Vadis?
Authors: Mischak Harald , Schanstra Joost P. , Vlahou Antonia , Beige Joachim 
Published: February 2025

ABSTRACTThe field of clinical proteomics has seen enormous growth in the past 20 years, with over 40,000 scientific manuscripts published to date. At the same time, actual clinical application of the reported findings is obviously scarce. In this viewpoint article, we discuss the key issues that may be responsible for this apparent lack of success. We conclude that success must not be assessed based on the number of publications, but via the impact on patient management and treatment. We proceed with specific suggestions for potential solutions, which include keeping a strict focus on potential patient benefit. We hope this article can help shape the field, so it can in fact deliver on its realistic promise to bring significant improvement in management and care to patients.
Comparative Analysis Between Olink‐PEA and Alamar‐NULISA Proteomic Technologies Applied to a Critically Ill COVID‐19 Cohort
Authors: Taleb Sara , Stephan Nisha , Chennakkandathil Sareena , Sohail Muhammad Umar , Yousef Sondos , Sarwath Hina , Al‐Noubi Muna , Suhre Karsten , Ait Hssain Ali , Schmidt Frank 
Published: February 2025

ABSTRACTWe aim to verify and validate low‐abundant plasma proteins from severe COVID‐19 cases and controls through a comparative analysis between Olink and Alamar performances. Eighty‐three severe cases and 44 controls were measured for proteomics using three Olink panels and one Alamar panel, which share 94 targets. CV, pairwise correlation of intensity signals, and detectability range were compared across platforms. Statistical comparisons were performed using FDR‐adjusted linear models with age as a covariate to construct differential protein abundance volcano plots between cases and controls per platform and heatmaps between our cohort and five public cohorts. Overall, pairwise comparisons (n = 94) showed strong correlations among cases (r = 0.82) and controls (r = 0.7). 60/94 proteins had mutual significance on both platforms; of which 54 showed concordant effect direction, and six showed opposite effect direction (IL‐6R, IL‐1R2, KITLG, TSLP, IL‐17C, and IL‐4R). Alamar verified 80 and 60 targets from cases and controls, respectively, along with 54 differential proteins from Olink. Compared to public cohorts measured by Olink, our Olink data showed consistent findings from 28 proteins, of which 27 were validated by Alamar.
Using Drawings to Measure Emotional Processing in Breast Cancer Survivors and Its Association With Depression, Pain, and Fatigue
Authors: Weinfeld‐Yehoudayan Asnat , Czamanski‐Cohen Johanna , Weihs Karen L. , Cohen Miri 
Published: February 2025

ABSTRACTBackgroundConscious and unconscious emotional processing (EP) may be related to breast cancer survivors' (BCS) response to the stress of dealing with cancer and its treatment, and often entails myriad psychological and physical symptoms.AimsTo examine the relationship between EP expressed by BCS in drawings made during art therapy and its relationship with depression, pain, and fatigue.MethodsThis cross‐sectional secondary analysis used data from the Role of Emotional Processing in Art Therapy study. BCS (N = 81) answered self‐report questionnaires measuring depression, pain, and fatigue at baseline. Their drawings were coded for EP using the Drawing‐Based Emotional Processing Scale (DRAWEP).ResultsLevels of depression, pain intensity and interference, and fatigue, were high, and a substantial percentage of participants were beyond the cutoff scores for severe symptoms. Controlling for background variables, EP subscales of making sense and organization were negatively associated with pain intensity, pain interference, and depression, but not with fatigue. These relationships are demonstrated with selected drawings.ConclusionsSince drawing involves embodied processes and has the potential to capture latent aspects of EP, examining drawings can provide a means of investigating EP among BCS and its relationship to depression and pain and learn more about the emotional experiences of BCS.Implications for PracticeThe DRAWEP can assist art therapists in increasing their awareness of EP, which may benefit their ability to identify women at risk. Moreover, this article can contribute to the development and enhancement of art therapists' awareness of EP.