bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modality-Projection Universal Model for Comprehensive Full-Body Medical Imaging Segmentation
Authors: Xie Zhaoheng , Chen Yixin , Gao Lin , Gao Yajuan , Wang Rui , Lian Jingge , Meng Xiangxi , Duan Yanhua , Chai Leiying , Han Hong-Bin , Cheng Zhaoping 
Published: January 2025

Abstract

The integration of deep learning in medical imaging has shown great promise for enhancing diagnostic, therapeutic, and research outcomes. However, applying universal models across multiple modalities remains challenging due to the inherent variability in data characteristics. This study aims to introduce and evaluate a Modality Projection Universal Model (MPUM). MPUM employs a novel modality-projection strategy, which allows the model to dynamically adjust its parameters to optimize performance across different imaging modalities. The MPUM demonstrated superior accuracy in identifying anatomical structures, enabling precise quantification for improved clinical decision-making. It also identifies metabolic associations within the brain-body axis, advancing research on brain-body physiological correlations. Furthermore, MPUM's unique controller-based convolution layer enables visualization of saliency maps across all network layers, significantly enhancing the model’s interpretability.
Design of a wearable textile piece for remote heart rate variability monitoring in dairy cows under grazing conditions
Authors: Betancourth–Chaves Patricia , Montoya–Zuluaga John , Rodríguez Berardo , Timarán–Rivera Andrés , Rios-Pena Lina , Hernández–Oviedo Filadelfo , Vallejo–Timarán Darío 
Published: January 2025

Abstract

In veterinary medicine, heart rate variability (HRV) has emerged as a tool for assessing welfare, comfort, stress responses, and physiological status. This study aimed to design and validate a vest-type wearable textile piece for remote HRV measurement and monitoring in dairy cows under rotational grazing conditions in high tropics. The vest-type textile piece was developed to protect and stabilize the Holter-type measurement devices in field conditions while ensuring it did not affect the animals' comfort and allowed for proper HRV measurements. For the HRV measurement, a Polar H10® Heart Rate Sensor and a Polar Unite® watch were used respectively. To evaluate the practical application of the vests and animal comfort, lactating Holstein healthy dairy cows (n = 74) were used. An ethogram was conducted to ensure the vest did not affect cow comfort. Behavioral and physiological responses showed the behaviors and social interaction patterns of the cows wearing the vest were similar to those of animals without the vest. Holter-type devices can be integrated into tools such as the vest-type textile piece designed in the present study and constitute an innovative and effective tool for continuous and non-invasive HRV monitoring in cows grazing in the high tropics preserving comfort and welfare.
A High-Conductivity and Adhesive Ionogel Strain Sensor for Monitoring Stimulus-Response Behavior of Aquatic Organism
Authors: Wen Yahui , Wang Xinghai , Zhao Jinxue , Zhai Xuejing , Xia Wei , Li Peiyi , Lai Keqiang , Zhu Meiwen , Lin Zhengde , Luo Tuyan , Wu Lidong 
Published: January 2025

Abstract

Ionogels have emerged as versatile materials with potential applications in flexible electronics and soft robotics. However, preparing high-performance ionogels with high conductivity and good mechanical strength remains challenging. Here, we report the development of a novel supramolecular ionogel as a wearable device for monitoring the stimulus-response behavior of aquatic animals. The integration of silver nanowires (AgNWs) endows the ionogel with good electrical conductivity (0.56 S m− 1) and mechanical robustness (strain tolerance › 1400%). The ionic liquid (IL) makes the AgIL ionogel exhibit superior adhesion properties (84.6 kPa) across diverse substrates, including biological tissues (e.g., pig skin). Furthermore, this wearable electronic exhibit an ultra-low detection limit (0.5%). The wearable electronics device consists of flexible AgIL ionogels as the sensing material, a microcontroller, a signal processing circuit, and a Bluetooth transceiver. Its electrical responsiveness and stable cyclic performance highlight its potential for wearable applications. This device can clearly and continuously monitor the regular or various stimuli-induced movements of the gills, tail, and body of aquatic animals such as the Chinese sturgeon and bullfrog. Comparative studies with traditional rigid ionogels and hydrogels underscore the significant enhancements in flexibility, adhesion, and conductivity by our design. This work provides a pathway for engineering multifunctional gels tailored for next generation soft electronic interfaces and broadens strain sensors' application range.
Validation of the diagnostic yield and safety of transbronchial lung cryobiopsy in diagnosis of interstitial lung disease: a retrospective study from a single center in China
Authors: Li Rui , Zhao Qian , Li Shanshan , Zhu Huifang , He Mingfeng , Miao Guiling 
Published: January 2025

Abstract

Background
Interstitial lung disease (ILD) is a group of rare lung disorders affecting the lung interstitium. Surgical lung biopsy (SLB) is considered the gold standard for the diagnosis of ILDs. However, the clinical use of SLB is limited by the procedure-associated complications. Although transbronchial lung cryobiopsy (TBLC) is reported to be safer than SLB and more effective than transbronchial lung biopsy (TBLB), it has not been widely used in clinical practice due to the small sample size reported. The aim of the present study was to validate the safety and diagnostic yield of TBLC in a large Chinese cohort from a single-center in China.
Methods
Included in this study were ILD patients who received TBLC at Drum Tower Hospital in Nanjing, China between 2017 and 2020. The clinical features of these ILD patients were obtained from the medical records. Risk factors associated with complication occurrence during TBLC were evaluated by student's t-tests or Fisher's exact tests as appropriate.
Results
Included in this study were 159 ILD patients with a mean age of 48.3 ± 11.3 years. The mean procedural duration for TBLC was 27.2 ± 5.92min. The mean number of biopsied specimens was 4.3 ± 0.9 with a mean diameter of 0.29 ± 0.13 mm. The overall occurrence of pneumothorax and severe bleeding was 15.7% and 16.3% respectively. The overall histopathologic diagnostic yield was 82.2%. Biopsied in the left lung and obtaining higher number of specimens had a much higher risk of developing pneumothorax. In addition, the larger diameter of specimen and longer procedural time were significantly associated with higher risk of bleeding.
Conclusion
TBLC is safe for the diagnosis of ILD with a high diagnostic yield. The associated complications could be tolerated and well controlled.
Funnel Random Forest: Inliers-Focused Ensemble Learning for Improved Prognostics of Heart Failure
Authors: Parisi Luca , Manaog Marianne Lyne 
Published: January 2025

Abstract

This study introduces a novel Funnel Random Forest (FRF) methodology to improve the accuracy and reliability of clinical prognostics, particularly for patients with heart failure. FRF identifies outliers using information theory-based metrics during training, reducing outliers by 11.04% compared to traditional methods. The model was trained on a dataset of 299 clinical records, achieving an 82.56% accuracy, a 1.67% improvement over standard Random Forest models. FRF outperformed existing models, with a 9.67% increase in accuracy and a 25.6% improvement in reliability, measured by the Precision-Recall Area Under the Curve (PR-AUC). These results demonstrate the model's potential to enhance clinical decision support, leading to better patient outcomes through early and precise prognostic predictions.
Association between METS-IR and Ischaemic Heart Disease: Results from National Health and Nutrition Examination Survey 2007–2018 Analyses
Authors: Guo Xia , Chu Haoxuan , Xu Hanchi , Guo Zhen , Tian Yulin , Gao Lu 
Published: January 2025

Abstract

Background: Ischemic heart disease (IHD) represents a significant global health burden. The Metabolic score for insulin resistance (METS-IR) represents an innovative tool for assessing insulin resistance (IR), a well-established factor linked to cardiovascular disease (CVD). However, the association between METS-IR and IHD within the United States population has yet to be fully clarified. This analysis seeks to investigate the possible relationship between METS-IR and IHD, providing insights into how metabolic factors may influence cardiovascular risk in this demographic.
Methods: A cross-sectional analysis was executed on a cohort of 14,305 participants selected from the 2007–2018 cycles of the National Health and Nutrition Examination Survey (NHANES). METS-IR was calculated, and IHD was recognized through self-reported diagnoses of coronary heart disease (CHD), heart attack, or angina pectoris. To assess the link between METS-IR and IHD, multivariate logistic regression was applied. Interaction effects were also assessed, and smoothed curve fitting was utilized to provide a more detailed analysis of the relationship.
Results: The analysis included 14,305 participants, among whom 1,050 were identified as having IHD. In the fully adjusted model, a one-unit unit increase in METS-IR was linked to a 2% rise in the odds of IHD (OR: 1.02; 95% CI: 1.01, 1.03). In the categorical analysis, individuals in the highest METS-IR quartile showed a 76% higher probability of IHD as opposed to those in the lowest quartile (OR: 1.76; 95% CI: 1.34, 2.31). Interaction analyses revealed significant effects based on age and gender, suggesting that the correlation between METS-IR and IHD varied across these subgroups.
Conclusion: Our findings indicate that increased METS-IR is linked to a heightened risk of IHD, highlighting its potential as an important biomarker for evaluating cardiovascular risk in the United States population. Additional longitudinal studies are necessary to ascertain a causal association between METS-IR and IHD.
New insights into the cis-regulation of the CFTR gene in pancreatic cells
Authors: Blotas Clara , Nabec Anaïs Le , Collobert Mégane , Bulcaen Mattijs , Carlon Marianne S. , Férec Claude , Moisan Stéphanie 
Published: January 2025

Abstract

Background
Spatial organization of the genome is fundamental for ensuring accurate gene expression. This process depends on the communication between gene promoters and distal cis-regulatory elements (CREs), which together make up 8% of the human genome and are supported by the chromatin structure. It is estimated that over 90% of disease-associated variants are located in the non-coding region of the genome and may affect CRE. For the cystic fibrosis transmembrane conductance regulator (CFTR) gene, a complete understanding of tissue-specific CFTR expression and regulation is missing, in particular in the pancreas. Mechanistic insights into tissue-specific expression may provide clarity on the clinical heterogeneity observed in Cystic Fibrosis and CFTR-related disorders.
Methods
To understand the role of 3D chromatin architecture in establishing tissue-specific expression of the CFTR gene, we mapped chromatin interactions via circular chromosome conformation capture (4C) and epigenomic regulation through H3K27ac and DNase Hypersensitive site I (DHS) in Capan-1 pancreatic cells. Candidate regulatory regions are validated by luciferase reporter assay and CRISPR-knock out.
Results
We identified active regulatory regions not only around the CFTR gene but also outside the topologically associating domain (TAD). By performing functional assays, we validated our targets and revealed a cooperative effect of the − 44 kb, -35 kb, + 15.6 kb and 37.7 kb regions, which share common predicted transcription factor (TF) motifs. Comparative 3D genomic analysis and functional assays using the Caco-2 intestinal cell line revealed the presence of tissue-specific CREs.
Conclusion
By studying the chromatin architecture of the CFTR locus in Capan-1 cells, we demonstrated the involvement of multiple CREs upstream and downstream of the CFTR gene. We also extend our analysis to compare intestinal and pancreatic cells and provide information on the tissue-specificity of CRE. These findings highlight the importance of expanding the search for causative variants beyond the gene coding sequence but also by considering the tissue-specific 3D genome.
Co-creating Norwegian DigiPer: a digital tool including peer support for managing mental, physical, and social health in serious mental illness
Authors: Skjærpe Jorunn Nærland , Fjellså Hilde Marie Hunsbedt , Fortuna Karen L. , Wang Bo , Storm Marianne 
Published: January 2025

Abstract

Background
People with serious mental illness (SMI) often encounter physical health issues, a lack of focus on self-management, and persistent symptoms of mental illness. Strategies to empower people with SMI to self-manage their mental, physical, and social health are needed. The PeerTECH application is an American digital peer support intervention that can help manage health issues and promote self-management skills for people with SMI. This study aims to co-create a Norwegian version of PeerTECH, DigiPer, with service users, peer support workers, and professionals from Norwegian community mental healthcare.
Methods
This study employs a qualitative design using principles of co-creation to develop the Norwegian DigiPer. We conducted workshops, videoconference demonstrations, and application testing with key stakeholders in the co-creation process. The data collected were analyzed using thematic analysis.
Results
Five themes and ten subthemes were developed in the data analysis. The first theme reflected feedback and challenges in DigiPer functioning, with the subthemes of Usability in DigiPer and Managing complexity in DigiPer classes. The second theme focused on the peer support worker's role, with subthemes of recognizing and addressing user challenges and balancing self-responsibility and support. The third theme focused on the content of DigiPer in addressing day-to-day challenges, with subthemes of supporting personal growth and goal setting and DigiPer as a tool to build supportive networks. The fourth theme highlighted the use of DigiPer to encourage a healthy lifestyle, with subthemes of addressing substance use and smoking habits and improving sleep and stress management. The fifth theme provided a holistic view of health, with subthemes of connecting users to relevant services and a need for support to overcome financial challenges.
Conclusions
DigiPer has good usability among community mental healthcare stakeholders and has proper functionality, which is relevant to the Norwegian context. Although challenges exist, all participants perceived DigiPer as a meaningful and promising tool to help people with SMI improve their self-management of their mental, physical, and social health. Future studies should assess the accessibility and feasibility of the Norwegian DigiPer.
Global, regional, and national childhood brain and central nervous system cancer burden: An analysis based on the Global Burden of Disease Study
Authors: Su Zhenjin , Lu Jie , Shi Yuheng , Li Tian , Qi Bin , Guo Zeshang 
Published: January 2025

Abstract

Objectives
We assessed the global, regional, and national burden of childhood brain and central nervous system cancer from 1990 to 2021 (the latest year).
Methods
We utilized data from the 2021 Global Burden of Disease Study, we analyzed trends in childhood brain and central nervous system cancer through joinpoint regression. We assessed the global burden of childhood brain and central nervous system cancer from various perspectives. Lastly, The Bayesian age-period-cohort model was employed to forecast future trends through 2030
Results
Childhood brain and CNS cancers are the most common solid tumors and the leading cause of death in children. From 1990 to 2021, age-standardized incidence, prevalence, mortality, and DALYs have shown a decreasing trend. The incidence is slightly higher in boys than in girls and peaking at ages 0–4 years, decreasing with age. The disease burden correlates with socio-demographic indices, with higher burdens observed in regions with higher socio-demographic indices. Future projections indicate a continued decline in incidence, prevalence, mortality, and DALYs.
Conclusions
While the global burden of childhood brain and CNS cancer has significantly decreased due to medical advancements, it continues to be a major cause of childhood mortality. Further optimization of global health resources is crucial to alleviating this burden.
COVID-19 and maxillofacial trauma: are we back to where we left off?
Authors: Qooz Fahad Al , Olaimat Mohammed S. Al , Alzoubi Zaid R. , Alanazi Mohammed Opaidallah , Murdif Ali S. Al , Algerafi Mohammed H. , Alqahtani Abdulkarim M. , Alzoubi Hamzeh Z. 
Published: January 2025

Abstract

Design: This wasa single-centre cross-sectional retrospective study.
Background: Facial trauma is inevitable in the field of maxillofacial surgery. Restrictive measures imposed during the pandemic increased patients’ anxiety and social awareness. Despite these changes, trauma continues through the mechanisms of falls, motor‒vehicle accidents (MVAs), alleged assaults, and other aetiologies.
Objective: To identify the changes in the patterns of maxillofacial trauma and types of fractures that occurred during and after the pandemic and the impact of the pandemic on maxillofacial trauma in the Middle East.
Patients & Methods: This study was conducted retrospectively at the King Hussein Medical Center, Hashemite Kingdom of Jordan, from May 2022 to May 2024. The inclusion criterion wasthe surgical repair of facial fractures during and after the COVID-19 pandemic. Patients of both sexes were included if they were under the age of 75. The exclusion criterion was the failure to fulfil the inclusion criterion. Statistical analysis was performed with IBM SPSS v29 (IBM Corp, Armonk, NY, US), with significant results indicated by a p value <0.05.
Results: Patients were divided into two groups: patients in group 1 underwent surgery during the pandemic, and patients in group 2 underwent surgery after it had been declared that the pandemic was over. A total of 136 patients were included in this retrospective analysis. Fall injuries were the most common mechanism of injury in group 1, although the proportion of patients who had experienced MVAs was also high, whereas in group 2, the prevalence of MVA was twice as high as in group 1. There were statistically significant differences in the mechanism of trauma and the type of fracture between both groups, both when considered together and separately (p <0.001). Sex was not found to be a significant factor affecting the mechanism or type of fracture (p > 0.05).
Conclusion: Maxillofacial trauma can be controlled but cannot be prevented. An emphasis on educating the population about safety measures at home, in workplaces, and/or while driving is needed. Coordination between civil defence departments and hospitals playsan important role in educating the population and reducing the incidence and prevalence of trauma.
Establishing a Comprehensive Data Protection Impact Assessment Methodology for Big Data Analytics in Compliance with the General Data Protection Regulation
Authors: Georgiadis Georgios , Poels Geert 
Published: January 2025

Abstract

In today’s digital landscape, as big data analytics (BDA) gain increasing significance, it is vital to have robust strategies for safeguarding privacy and data protection. This paper focuses on improving data protection impact assessments (DPIAs) in the context of BDA, aligning them with the principles of the General Data Protection Regulation (GDPR). Through a study that combines a Delphi approach with individual expert interviews, we have validated nine critical privacy touch points (PTPs) for adapting DPIA methodology to BDA environments. These PTPs, identified in our previous research, address key privacy and data protection issues in BDA, including consent nuances, definitions of data control, and challenges such as re-identification and discrimination. The result is a framework tailored to the unique landscape of BDA technologies. This research stands out by thoroughly analysing and validating these nine PTPs and offering actionable recommendations to enhance the existing DPIA framework. With the anticipated growth of artificial intelligence and large language models, BDA will continue to attract attention. Our research therefore contributes both academically and practically by supporting the evolution of thorough DPIA practices while providing guidance for policymakers, businesses, and privacy advocates.
A Novel Multi-Factor Authentication Approach Integrating Dynamic Image Grids and Cell Addresses Algorithm
Authors: Yeboah Donald , Addo Prince Clement , Dagadu Joshua Caleb 
Published: January 2025

Abstract

This study introduces a novel graphical multi-factor authentication (MFA) algorithm that integrates user image hashes and dynamic image grids with cell addresses (DIGCA) to optimize storage requirements with robust security. The algorithm stores image hashes rather than actual images, significantly reducing storage space while maintaining security integrity. In contrast to the existing image recognition algorithm, the algorithm shows a drastic reduction of 99.9% in storage requirements. Performance analysis demonstrates that the algorithm provides a high level of accuracy with a 95.36% success rate in user authentication over an extended period. Again, the image grid and cell addresses prove an ample password space and entropy. With the minimum assumption grid size, it achieves a password space of 1.36 × 1040 , Which makes it virtually impossible for an attacker to guess the correct combination. The results underscore the algorithm’s potential as a superior alternative to existing MFA schemes, offering both security and practicality in modern authentication systems.
A Mathematical Review on EEG Channel Selection Techniques for Motor Imagery Classification
Authors: Lee Seungjun 
Published: January 2025

Abstract

Brain Computer Interface (BCI) technology is recently being spotlighted as the performance of Artificial Intelligence (AI) increased drastically. Although there are several instruments to measure brain's activity, Electroencephalography(EEG) signal is in limelight as it has high temporal resolution and is non-invasive, while being extremely portable. However, the raw EEG signals can not be directly used in BCI systems as it includes a lot of artifacts, and has numerous channels. Therefore, selecting only the needed channels and rejecting ones that include big noises are crucial to increase the performance of classification.
Motor Imagery EEG (MI-EEG) is a type of EEG where subjects imagine that they are moving their body. MI-EEG channel selection techniques can be divided into two big groups: Common Spatial Pattern (CSP) based models and non-CSP based models. Therefore in this paper, we introduce the models classified in the criteria above, using detailed and strict mathematical terms, and compare each approach's accuracies.