bluuebunny/crossref_metadata_2025_split huggingface dataset:
The New Method for Evaluating the Advanced Treatment Effect of Limestone Aquifers in the Roof and Floor of Deep Coal Seam Mining
Authors: Hu Yanbo , Jiang Jingzheng , Zheng Gang 
Published: October 2024

Abstract

The text discusses a new method for evaluating the effectiveness of advanced regional treatment of limestone aquifers in coal mining. Since the implementation of the "Technical specification for advanced regional treatment of limestone aquifer under coal seam" in early 2024, an effective evaluation method has been lacking. To fill this gap, this study is based on data from surface-directed multi-branch horizontal wells for advanced regional treatment. Using methods such as calculating the water-blocking capacity of the aquifer, statistical analysis of grouting data, and GIS model processing, a multi-factor evaluation model that affects the effectiveness of water hazard governance was constructed, and thematic distribution data of various influencing factors in the research area were obtained. Through mathematical modeling and GIS technology, various factor data were processed to form zoning evaluation data for the effectiveness of grouting transformation. This article proposes an innovative method for evaluating the effectiveness of advanced regional treatment using surface-directed multi-branch horizontal wells by comprehensively utilizing qualitative and quantitative evaluation modes, combined with supplementary exploration data from underground. Experimental results have shown that the evaluation system is effective and provides an important reference for research on water hazard prevention and control in deep coal seam mining.
A Study on the Effect of Blue Light on Kidney Stone Formation in Rats via the Brain-Kidney Axis
Authors: Fang Dao-Cheng , Hu Yuan-Yuan , Wang Chao , Fan Jie , Wen Hui 
Published: October 2024

Abstract

Kidney stones, a common disease in urology, are formed by multiple factors, among which the brain-kidney axis may play an important role in the occurrence and development of kidney stones, although the specific mechanism remains to be elucidated. This study aims to investigate the effects of blue light on relevant metabolic indicators and oxidative stress status in rats with kidney stones through the brain-kidney axis. To this end, we established a rat model of kidney stones and intervened with blue light, comparing it with normal rats. We found that compared with kidney stone rats without blue light intervention, those receiving blue light intervention exhibited significantly increased levels of antidiuretic hormone, intensified oxidative stress response, and augmented stone formation. However, in normal rats, blue light intervention did not cause significant changes in the aforementioned indicators. In summary, this study indicates that under pathological conditions, blue light may promote the secretion of antidiuretic hormone in serum and enhance oxidative stress response in renal tissues by affecting the brain-kidney axis, thereby accelerating the formation of kidney stones in rats.
Determinants of Harm in Fall Incidents in Hospital Settings with 200 or More Beds in Korea
Authors: Kang Youngmi , Hong Eunyoung 
Published: October 2024

Abstract

Falls are a significant patient safety concern in hospital settings, often resulting in unintended harm. This study aimed to investigate the prevalence and risk factors for falls in Korean hospitals with 200 or more beds, analyzing 13,034 incidents reported to the Korean Patient Safety Reporting and Learning System from 2017 to 2021. The level of harm was classified into three categories: near-miss, sentinel events, and adverse events. Hospital-related factors (hospital type, bed capacity, and location and time of fall incident) and patient-related factors (sex, age group, and admitting medical department) were included in the analysis. Chi-square tests were used to evaluate differences in fall severity, and binary logistic regression identified factors associated with harmful incidents. The study found that harmful falls were more likely in general hospitals, particularly those with over 500 beds and in emergency departments, as well as among older female patients and those admitted to internal medicine. Based on the results of this study, especially in general hospitals with more than 500 beds, comprehensive strategies for preventing falls, including the promotion of patient safety culture, are needed to reduce fall occurrence and its associated disabilities.
Fall-Related Injuries in Older Adult Cancer Survivors : A Decade of Racial Disparities
Authors: Namoos Asmaa , Thomson Nicholas , Sheppard Vanessa , Aboutanos Michel 
Published: October 2024

Abstract

Background: As the population ages and the number of cancer survivors in the USA continues to rise, fall-related injuries are becoming an increasingly critical public health issue. The purpose of this study is to assess the incidence and prevalence of fall-related injuries among older adult cancer survivors, with a particular focus on identifying and understanding racial disparities in fall risk between Black and White cohorts.
Methods: A retrospective cohort study using data from 19,370 older adult cancer survivors aged 65 and above, extracted from the TriNetX network at Virginia Commonwealth University Health System (VCUHS). The study spanned from January 1, 2013, to December 31, 2023. Demographic information, including age, sex, race, and ethnicity, as well as ICD-10 codes for cancer history and fall-related injuries, were analyzed. Incidence rates were calculated as cases per person-day.
Results: The study found that 7% of the cancer survivors experienced a new fall-related injury, with a prevalence rate of 8% over the study period. The incidence rate was calculated at 0.00005432 cases per person-day. Black or African American survivors exhibited a higher fall risk (4.915%) compared to their White counterparts (4.048%), with a statistically significant risk difference of 0.867% (95% CI: 0.199% to 1.534%).
Discussion
The findings of this study are consistent with existing literature that highlights the increased fall risk among older adult cancer survivors. The observed racial disparities in fall-related injuries underscore the need for targeted interventions that address the specific challenges faced by minority populations. The study's large sample size and comprehensive dataset strengthen the generalizability of the results, although the reliance on automated ICD-10 coding presents a potential limitation in data accuracy.
Conclusions
This study reveals significant racial disparities in fall-related injuries among older adult cancer survivors, particularly between Black and White individuals. The findings suggest the need for culturally sensitive and equitable healthcare strategies to improve the quality of life for all cancer survivors.
Developing a Master of Science in Research Ethics Program in Northern Nigeria: A Needs Assessment
Authors: Bieniek Caitlin , Tsiga-Ahmed Fatimah Ismail , Adamu Aishatu L. , Wudil Usman J. , Wester C. William , Iliyasu Zubairu , Aliyu Muktar H. , Gordon Elisa J. , Rose Elizabeth S. 
Published: October 2024

Abstract

Background
Nigeria is an emerging hub of biomedical research, requiring additional trained bioethicists for ethical oversight of research studies. There are currently two graduate-level research ethics programs in Nigeria. However, both are in the southern portion of the country and no training programs exist in north. Strengthening the research ethics skills and knowledge of Nigerian researchers across the country is necessary given the growing genetics research infrastructure.
Methods
To inform the creation of a Master of Science in Research Ethics program in northern Nigeria, we conducted a needs assessment comprised of semi-structured interviews with nine Nigerian bioethics experts. We used the Interpretive Phenomenological Analysis (IPA) method to analyze interview transcriptions. Two authors independently read and coded each participant’s transcription to identify emergent themes that represented each participant’s responses. Within these overarching themes, the data points were grouped into subthemes.
Results
Four primary themes emerged with ten subthemes. Respondents agreed that the program can fill a gap and strengthen capacity in research ethics; the curriculum should be developed with an interdisciplinary lens and locally contextualized. Students should be taught how to think critically through ethical scenarios since research ethics will need to be applied to real world situations. Leaders within the program should recruit faculty and students locally who have bandwidth to participate in the program; and the program should have university support.
Conclusion
Our findings will guide the creation of a program that establishes a research ethics capacity in northern Nigeria. Continuing to enhance the country’s growing prominence in global biomedical research. Through our needs assessment we identified structural and content factors that can guide us in leveraging strengths of the local institution and leaders in research ethics while mitigating challenges in establishing this master’s program.
INTNet: a deep learning approach for integron identification and classification
Authors: Lam Tommy , Pei Yao , Liao YunShi , Shum Marcus Ho-Hin , Williams Alexander , Smith David , Zheng Qi , Guan Yi , Luo Ruibang , Zhang Tong 
Published: October 2024

Abstract

Antibiotic resistance, which is exacerbated by the emergence of multidrug-resistant bacteria, is a substantial and persistent global threat to human health. Antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) are central to the dissemination of bacterial resistance, with integrons playing a major role in the acquisition, expression, and transmission of ARGs, particularly in clinical environments. Rapid and accurate identification and classification of integrons would greatly aid clinical practice and environmental surveillance of pathogens. In this study, a comprehensive integron sequence database (INTNet-DB) was built, expanding on INTGRALL by over 8-fold, and the evolutionary history of integrons was analysed. Utilizing INTNet-DB, a multi-task multilabel deep learning program, INTNet, was designed and developed to accurately identify and classify integron integrases, their bacterial hosts, and associated ARGs based on the genetic sequences. INTNet is the first deep learning model as such and demonstrated high performance, achieving precision over 90%, recall above 91%, and accuracy exceeding 94% across validation tests. When compared to IntegronFinder 2, INTNet exhibited markedly higher sensitivity and maintained consistent performance on partial sequences. INTNet is freely available at https://github.com/id-bioinfo/INTNet and provides a valuable tool for clinical and environmental genomic surveillance.
Enhancement of Flexural Strength in Polymethylmethacrylate (PMMA) Through the Incorporation of Graphene Nanoparticles: A Comparative In Vitro Study
Authors: Selvam Divyabharathi , Vasudevan Karthikeyan , Rizwana Noorul , Selvam Deepika 
Published: October 2024

Abstract

Background Polymethylmethacrylate (PMMA) is a common material in dental prosthetics, but its mechanical limitations, particularly in flexural strength, can affect its performance. Graphene nanoparticles, known for their exceptional mechanical properties, present a potential solution to enhance PMMA’s strength.Aim This study investigates the impact of incorporating graphene oxide (GO) and reduced graphene oxide (RGO) nanoparticles into PMMA on its flexural strength, comparing the effects of different nanoparticle concentrations.Materials and Methods Seventy heat-polymerized PMMA specimens (65 × 10 × 3 mm) were prepared following ISO 1567 standards. These specimens were divided into three groups: Control (no nanoparticles), Experimental Group A (GO), and Experimental Group B (RGO). Each experimental group was further subdivided based on the nanoparticle concentration: 0.10g, 0.20g, and 0.30g. Flexural strength was measured using a three-point bending test on a Universal Testing Machine with a crosshead speed of 1.50 mm/min and a span length of 40 mm. Data were analyzed using ANOVA and post-hoc Tukey-HSD tests.Results The control group recorded a mean flexural strength of 49.25 N. Incorporating GO and RGO nanoparticles significantly improved PMMA's flexural strength, with the highest strength observed in the RGO 0.30g group, showing a mean value of 213.6 N.Conclusion Reinforcing PMMA with graphene nanoparticles, including GO and RGO at various concentrations, significantly enhances its flexural strength compared to unreinforced PMMA. These findings highlight the potential of graphene-based nanoparticles to improve the durability of dental materials, offering superior mechanical properties critical for long-term clinical use.
The Foundational Capabilities of Large LanguageModels in Predicting Postoperative Risks UsingClinical Notes
Authors: Alba Charles , Xue Bing , Abraham Joanna , Kannampallil Thomas , Lu Chenyang 
Published: October 2024

Abstract

Clinical notes recorded during a patient's perioperative journey holds immense informational value. Advances in large language models (LLMs) offer opportunities for bridging this gap. Using 84,875 pre-operative notes and its associated surgical cases from 2018 to 2021, we examine the performance of LLMs in predicting six postoperative risks using various fine-tuning strategies. Pretrained LLMs outperformed traditional word embeddings by an absolute AUROC of 38.3\% and AUPRC of 33.2%. Self-supervised fine-tuning further improved performance by 3.2% and 1.5%. Incorporating labels into training further increased AUROC by 1.8% and AUPRC by 2%. The highest performance was achieved with a unified foundation model, with improvements of 3.6% for AUROC and 2.6% for AUPRC compared to self-supervision, highlighting the foundational capabilities of LLMs in predicting postoperative risks, which could be potentially beneficial when deployed for perioperative care.
Dynamics of Cattaneo-Christov Model for Blood-Based Molybdenum Disulfide Nanofluid Flow on Variable Porous Bi-Directional Stretching Sheet Subject to effects of Inter-Particle Spacing and Nanoparticle’s Radius
Authors: Algehyne Ebrahem A. , Alamrani Fahad Maqbul , AL-Essa Laila A. , Lone Showkat Ahmad , Khan Arshad , Younis Jihad 
Published: October 2024

Abstract

The effects of inter-particle spacing and radius of molybdenum disulfide nanoparticle on nanofluid flow have significant applications in various fields. In biomedical engineering, optimizing these parameters enhance drug delivery systems, enabling more efficient targeting and controlled release of therapeutics. For such important applications, this work investigates nanofluid flow on a bi-directional elongating surface with effects of inclined magnetic field. The surface of sheet is characterized with variable porous features. This work specifically examines how the radii of nanoparticles and the spaces between them influence the overall dynamics of flow system. The Cattaneo-Christov heat and mass flux model is also taken into consideration to investigate the heat and mass flow. The impacts of chemical reaction and activation energy have used in this work with, Brownian motion and thermophoresis impacts. Main equations have converted to dimensionless form and then solved by implementing bvp4c approach. It has revealed in this work that with upsurge in magnetic factor, angle of inclination of magnetic field and variable porous factor there is reduction in primary and secondary velocities both for inter-particles spaces (say\(h=1/2\,\,\& \,\,10\)) and radius of nanoparticles (say\(Rp=3/2\,\,\& \,\,5/2\)). This reduction is more significant in case of large inter-particles spaces (say\(h=\,\,10\)) and large radius of nanoparticles (say\(Rp=\,5/2\)). With growth in radiation factor, thermal Biot number, and Brownian motion factor there is escalation in thermal distribution. The findings from this study can be utilized in designing drug carriers with controllable porous structures, allowing for the regulation of drug movement and release rates within the body. For example, carriers with larger inter-particle spaces can be engineered to provide a slower, more controlled drug release. This approach ensures sustained delivery to target sites, thereby enhancing therapeutic efficacy.
2D-GAN: Dual-Decoding Generative Adversarial Networks for Infrared Image Enhancement
Authors: Yu Yang , Jiang Lin , Hu Qijun , Zeng Qiang , Sun Xin 
Published: October 2024

Abstract

Infrared imaging technology finds wide application across various fields, yet suffers from issues such as atmospheric thermal radiation interference, resulting in poor contrast, blurred details, and noise in infrared images. Consequently, enhancing infrared images is essential as a preprocessing step to obtain high-quality data. This paper proposes an infrared image enhancement algorithm based on Dual-Decoding Generative Adversarial Networks(2D-GAN) to address these challenges.The proposed algorithm employs a two-step decoding structure within the 2D-GAN framework to enhance the network's capability to comprehend and represent input data effectively. Internal and external skip connections are incorporated to bolster the network's perceptual ability, addressing the loss of detailed information during the encoding and decoding processes. Additionally, a cross-level attention module is designed to dynamically allocate positional weights to feature maps, thereby enhancing the natural appearance of the generated images.The effectiveness of the 2D-GAN-based enhancement algorithm is validated through comparative experiments, supplemented by ablation studies that delineate the contributions of each module within the network. Experimental results demonstrate significant enhancement in infrared image quality, affirming the efficacy of the proposed algorithm.
Analysis of Clinical Characteristics of 145 MGTB patients in three provincial teaching hospitals in Gansu province
Authors: Guo Chenhao , Zhang Jing , Zhang Yongjuan , Jiang Nan , Zhang Ke , Tian Yixin , Yang Meiling , Ma Lilong , Huang Xueyi , Li Weiping , Huang Xiande , Shang Panfeng 
Published: October 2024

Abstract

Objective
To explore the strengths and weaknesses of current diagnostic and therapeutic approaches for MGTB.
Methods
The clinical data of 145 patients diagnosed with MGTB from January 2013 to September 2023 were retrospectively analyzed to determine better diagnosis and treatment methods to guide clinical practice.
Results
Among 145 male patients with MGTB, 29 (20%) were accompanied by urinary TB, and 116 (80%) were only associated with MGTB. TSPOT and ultrasound are the most valuable laboratory and imaging methods. Surgical resection was still the first choice for the cure of germline tuberculosis, 113 patients chose surgical resection, the resection rate was 77.93%, the cure rate was 75%, and the recurrence and progression rate were 5.36%. The symptoms of MGTB are insidious, and the accurate diagnosis requires a combination of laboratory tests and imaging examinations. TSPOT and ultrasound are the most valuable diagnostic methods and are recommended as the first choice.
Conclusion
Preoperative and postoperative anti-tuberculosis drug therapy is necessary to reduce the incidence of complications and the risk of recurrence. When treating germline tuberculosis, we should pay attention to the patient's sexual function and fertility.
Bowel Perforation in neonates with Hirschsprung's disease
Authors: Liu Zhaozhou , Zhang Yanan , Sun Dayan , Chen Yongwei , Guo Weihong , Du Jingbin , Huang# Jinshi 
Published: October 2024

Abstract

Background
Bowel perforation is a severe complication of Hirschsprung's disease (HD) that necessitates prompt diagnosis and aggressive management to reduce mortality and morbidity. This study aimed to provide insights into the clinical management of neonatal HD cases complicated by bowel perforation.
Methods
A retrospective review was conducted on neonates diagnosed with HD and bowel perforation at Beijing Children’s Hospital from January 2007 to January 2024. Inclusion criteria included neonates ≤ 28 days old with confirmed HD diagnosis based on postoperative histology. Data collected included perinatal history, patient characteristics, HD classification, clinical presentations, surgical interventions, and outcomes. Statistical analysis was performed using SPSS 26.0.
Results
Among 300 neonates diagnosed with HD, 18 (6.0%) developed preoperative bowel perforation. Most perforations were in the proximal ganglionic bowel, with short-segment HD (7/18, 38.9%) and long-segment HD (9/18, 50.0%) being most common. All patients underwent surgery within 24 hours of perforation detection, with 94.4% (17/18) requiring stoma creation. Postoperative complications included stoma retraction, Hirschsprung disease-associated enterocolitis, and adhesive bowel obstruction, but no mortality was reported.
Conclusion
The incidence of preoperative bowel perforation in neonates with HD was 6.0%, primarily in cases of short-segment and long-segment HD. Perforations were mainly located in the proximal ganglionic segments. Prompt surgical intervention, particularly stoma creation, resulted in favorable outcomes for most patients.
Improving COVID-19 Mortality Predictions: A Stacking Ensemble Approach with Diverse Classifiers
Authors: Mohtasham Farideh , Pourhoseingholi MohamadAmin , Nazari Seyed Saeed Hashemi , Kavousi Kaveh , Zali Mohammad Reza 
Published: October 2024

Abstract

Ensemble approaches are vital for developing effective machine learning methods by integrating multiple models to enhance performance and reduce bias and variance. This study utilized ensemble techniques to predict COVID-19 mortality using various classifiers. We first mapped the original dataset to a lower-dimensional space to improve training diversity. We then trained multiple base classifiers and ensemble methods, assessing their diversity through pairwise evaluations to create diverse combinations. A Stacking ensemble method was implemented with different meta-learners for improved predictive performance. All models were rigorously evaluated using standard discrimination and calibration metrics, along with statistical tests to identify significant performance differences. Various feature importance methods were applied to clarify the contributors to our model's predictions. The experimental results demonstrated the superiority of our stacking framework, specifically combining Random Forest and Extreme Gradient Boosting (XGBoost) with a Neural Network as the meta-learner on COVID-19 mortality prediction. This model achieved an accuracy of 0.914 (95% CI: 0.898, 0.928), precision of 0.818, F1-score of 0.801, Matthew’s correlation coefficient (MCC) of 0.746, and a ROC AUC of 0.955. These findings indicate that our framework is more effective than individual classifiers and existing ensemble methods, providing valuable insights for medical decision-making.
Climate-driven introduction of an opportunistic symbiont in the most extensive reef system of the Southwestern Atlantic Ocean
Authors: Vilella Livia B. , Aiube Yuri R. , Silva-Lima Arthur W. , Moura Rodrigo L. , Salomon Paulo S. 
Published: October 2024

Abstract

Coral symbionts of the Symbiodiniaceae family range from strictly mutualistic to highly opportunistic species. Symbiodinium necroappetens is an opportunistic species and a putative necrophile of dead coral tissue, hitherto reported as endemic to the Caribbean. Symbiodiniaceae were characterized by ITS2 barcoding along the most severe thermal anomaly registered in the Abrolhos Bank, southwestern Atlantic Ocean (SWAO). S. necroappetens relative abundance and prevalence went from undetectable before the anomaly to as much as 73% and 100%, respectively, during and after the heatwave. Sequences were still detectable four years after being initially observed. We are likely observing a climate-driven introduction of S. necroappetens in the SWAO. Given the increasing frequency and intensity of thermal anomalies hitting the global ocean, we can only speculate on the ecological consequences of such invasion for the Abrolhos reefs.