bluuebunny/crossref_metadata_2025_split huggingface dataset:
Knowledge, attitudes, and practices of cervical cancer and cervical cancer screening in a rural setting of a low-income country: A cross-sectional study in the Busoga Region of Uganda
Authors: Einarson Troels Alnor , Musana Emmanuel , Balonde Joseph , Lorentzen Katinka Bolette , Kallestrup Rasmus , Juncker Margrethe , Damoi Joseph Okello , Nakami Sylvia , Kallestrup Per 
Published: December 2024

Abstract

Background: Cervical cancer (CC) is a major non-communicable health issue in low- and lower-middle income countries, such as Uganda. Effective cervical cancer screening (CCS) and vaccination can effectively eliminate the disease as a public health issue, but these initiatives are lacking behind as CC is the most common cancer in Uganda. Future information-, screening-, and vaccinationcampaigns should be founded on a scientific depiction of the women’s understanding of the issue and solutions, to ensure a sustainable public health benefit.
Methods: We performed a cross-sectional study in 5 districts of the Busoga Region of Uganda to assess rural women’s knowledge, attitudes, and practices of CC and CCS. Women ≥18 years old were included through random sampling. Data was collected using a digital questionnaire administered by trained research assistants recruited from the study area. Results are presented with descriptive statistics and logistic regression for sociodemographic predictors of KAP scores via crude and adjusted models, at a p-value of .05.
Results: 585 participants were included. 57% had primary education and 83.9% were farmers. 92.1% had heard about cancer and 87.5% CC, while a minority knew of any symptoms (36.8%), risk factors (42.5%), and preventive measures (49%) of CC. Lay beliefs included poor hygiene and contraceptives as risk factors. Attitudes showed a good understanding of CC severity, preventability, and curability, and little indication of taboo. The respondent’s attitudes lacked clarity on vaccination and screening benefits as 35.6% did not know that HPV vaccination prevents CC and 24.1% did not know that screening could detect early CC. 9.1% had ever attended CCS with 12% in the 30 - 49-year-old target group. Predictors of KAP scores were identified and discussed from the perspective of similar studies.
Conclusions: This study identified CC knowledge gaps in symptom awareness, risk, and preventive factors. Most women held favourable attitudes towards the disease, but less favourable towards preventive measures. Low screening prevalence indicated a need to improve public health initiatives.
A rapid prediction model for trauma-induced coagulopathy in severe trauma: a retrospective study
Authors: Zhuang Xinsuo , Zhou Qian , Wang Yadong , Geng Xiaonan , Chen Naiyun , Yang Xiaofeng , Bai Xueli 
Published: December 2024

Abstract

Background
There is little data regarding the method for predicting trauma-induced coagulopathy (TIC) in patients with severe trauma to facilitate early intervention. This study aimed to establish a prediction model for the early diagnosis of TIC in trauma patients.
Methods
The patients included were divided into two groups based on the presence or absence of TIC. Fourteen potential variables were included in this study. These data were subjected to univariate analysis, followed by logistic multivariate regression analysis to identify independent risk factors affecting the occurrence of TIC. Subsequently, a predictive model for TIC was established. Finally, the predictive model was evaluated, and a clinical application decision tree was constructed.
Results
A total of 214 patients were included. Hemoglobin, prothrombin time (PT), fibrinogen (Fbg), base excess (BE), lactic acid, and LnD-dimer levels were associated with TIC. Further analysis showed that PT, Fbg level, BE level, and LnD-dimer level were independent risk factors of TIC. Based on these parameters, the TIC prediction model was established. The model displayed excellent discrimination (area under the curve: 0.877; 95% confidence interval: 0.827–0.988). The cut-off value was-0.705. Model scores≥-0.705 indicated the existence of TIC, and patients with these scores were considered the high-risk group. The incidence of TIC was significantly different between the high- and low-risk groups (90.4% vs. 25.6%, p < 0.001).
Conclusion
Our study developed a prediction model to guide early effective interventions of TIC and improve the prognosis in severe trauma patients.
Successful collection of patient-reported outcomes shows improvement in quality of life, depression, and disease activity among patients with Inflammatory Bowel Disease: A real-world study
Authors: Gu Cihang , Bennett Audrey , Bachmann Justin , Schwartz David A. , Beaulieu Dawn , Scoville Elizabeth , Dalal Robin , Pabla Baldeep , McCoy Allison , Slaughter James C. , Horst Sara 
Published: December 2024

Abstract

Introduction:
Patient reported outcomes (PRO) including patient disease activity scores, quality of life, and depressive symptoms are increasingly being used for clinical care in patients with inflammatory bowel disease (IBD). However, little is known about performance of PROs over time in a real-world setting.
Methods:
PROs were collected from a tertiary care IBD center from the electronic medical records (EMR) from 2018–2020. Quality of life was measured with the Simple Inflammatory Bowel Disease Questionnaire (SIBDQ). Disease activity was measured using the Harvey Bradshaw Index (HBI) for Crohn’s disease (CD) and the Simple Clinical Colitis Activity Index (SCCAI) for ulcerative colitis (UC). Depressive symptoms were measured using the Patient Health Questionnaire-8 (PHQ-8).
Results:
PRO collection rate from 1,373 patients was 88%. PHQ and SIBDQ were highly correlated (0.718, p < 0.05). HBI and PHQ-8 (0.528, p < 0.05) and SIBDQ (-0.676, p < 0.05) were moderately correlated. For CD patients, age 40–65, corticosteroid use, and psychiatric medication use were associated with lower HBI and SIBDQ and higher PHQ scores. Age 40–65, corticosteroid use, and psychiatric medication use were associated with lower SCCAI and SIBDQ and higher PHQ-8 scores for CD and UC patients. Mean change [95% CI] increased for SIBDQ by 2.9 [2.3 to 3.6] in CD and 4.7 [3.8 to 5.6] in UC. Mean change [95% CI] decreased for PHQ-8: -1.0 [-1.3 to -0.8] in CD and − 1.7 [-2.2 to -1.3] in UC. This remained significant in both cognitive and somatic subscales.
Conclusion:
PRO collection was highly successful using EMR implementation in a tertiary care clinic setting. Corticosteroid use and psychiatric medication use were associated with worse disease activity, depressive symptom and quality of life scores. Moreover, PROs demonstrated depressive symptoms (both cognitive and somatic subscales), and quality of life symptom scores improved over time.
Combined metabolome and transcriptome to analyze the regulatory network of key enzymes in the synthesis of Senkirkine in Emilia sonchifolia
Authors: Yao Jinli , Qin Yanqing , Tu Dongping , Huang Yumei , Liang Liuguan , Cai Wenhui , Huang Mingli , Zhu Xiaoqi , Lao Xinling 
Published: December 2024

Abstract

Emilia sonchifolia (L.) DC. is a commonly used medicinal and edible plant in the folk, and its toxic component of Senkirkine (Sek) has hepatotoxicity, which can lead to sinusoidal obstruction syndrome if exposed in large amounts, and will cause hepatic megaloblastosis and hepatic fibrosis if ingested in small amounts over a long period of time. This study was based on the metabolomics of Emilia sonchifolia, which analysed and identified the alkaloid constituents of 4 parts of Emilia sonchifolia, namely, the root, stem, leaf and flower. A total of 91 differential metabolites were detected, belonging to 10 alkaloids, among which pyrrolizidine alkaloids accounted for 13%. The relative content of Senkirkine differed most significantly between the group of root and flower comparison, and the relative content of Senkirkine in root was significantly higher than in flower. A total of 119,886 unigenes and 32,797 differentially expressed genes were identified in the transcriptome data, and the 45 key enzymes of the biological synthesis pathway of Senkirkine were selected, which belonged to 7 categories. There are a total of 172 candidate enzyme genes in it, of which methyltransferase, alcohol dehydrogenase, acyltransferase, and cyclooxygenase genes were significantly more expressed in roots than in flowers, and the metabolome and transcriptome expression patterns were basically the same. The 5 key enzyme gene sequences of the biological synthesis pathway of Senkirkine were selected for qRT-PCR. The results showed that, using flowers as the control group, 4 key enzyme genes (BAHD-Ats, CCoAOMT, BOMT, 3AT) were all highest in roots, while the relative expression of CAD was highest in stems, which was basically consistent with the transcriptome pattern. This study provided a reference for the functional expression analysis of the genes of Emilia sonchifolia, and laid a foundation for the future analysis of the Senkirkine synthesis pathway and the regulation of the key enzyme genes of the toxic components, so as to obtain the low-toxic raw materials of Emilia sonchifolia.
The Use of Endoscopic Ultrasound Guided Fine Needle Biopsy for the Diagnosis of Microcystic Serous Cystic Neoplasms of the Pancreas
Authors: Garg Kanika , Boupapanh Kesany , Zilberstein Netanel , Wang Thomas , Kakked Gaurav , Al-Sabti Ram , Mehta Neal , Chapman Christopher , Waxman Irving , Singh Ajaypal 
Published: December 2024

Abstract

Background: Pancreatic cysts, frequently identified incidentally on imaging, present diagnostic challenges due to their variable malignant potential. Serous cystic neoplasms (SCNs) are benign and account for 1-2% of pancreatic lesions. However, imaging techniques alone often lack the accuracy to definitively diagnose these lesions, leading to unnecessary surveillance and interventions.
Aims: This study evaluates the safety and diagnostic efficacy of endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) for identifying microcystic SCNs.
Methods: We conducted a retrospective analysis of 39 patients who underwent EUS-FNB for solitary pancreatic lesions with microcystic features, identified through cross-sectional imaging at our medical center between 2018 and 2024. Patients with a stellate scar or definitive imaging features of microcystic SCNs were excluded. Outcomes assessed included histologic results and complications.
Results: Histological confirmation of microcystic SCN was achieved in 79.5% of cases, eliminating the need for further imaging and surveillance. A single complication—mild intra-lesional bleeding—occurred in one patient, which resolved without further intervention.
Conclusions: EUS-FNB is a safe and effective method for diagnosing microcystic SCNs, offering a definitive diagnosis and reducing unnecessary surveillance and interventions. This approach provides a favorable risk-benefit profile for managing SCNs. However, future multicenter studies with larger cohorts are needed to further validate these findings and refine diagnostic protocols for pancreatic cystic neoplasms.
Quantum-Powered Personalized Learning
Authors: Zhou Yifan , Xh Chong Cheng , Song Mingi , Wong Yew Kee 
Published: December 2024

Abstract

This paper explores the transformative potential of quan- tum computing in the realm of personalized learning. Tradi- tional machine learning models and GPU-based approaches have long been utilized to tailor educational experiences to individual student needs. However, these methods face significant challenges in terms of scalability, computational efficiency, and real-time adaptation to the dynamic nature of educational data. This study proposes leveraging quantum computing to address these limitations. We review existing personalized learning systems, classical machine learning methods, and emerging quantum computing applications in education. We then outline a protocol for data collection, privacy preservation using quantum techniques, and prepro- cessing, followed by the development and implementation of quantum algorithms specifically designed for personalized learning. Our findings indicate that quantum algorithms of- fer substantial improvements in efficiency, scalability, and personalization quality compared to classical methods. This paper discusses the implications of integrating quantum com- puting into educational systems, highlighting the potential for enhanced teaching methodologies, curriculum design, and overall student experiences. We conclude by summariz- ing the advantages of quantum computing in education and suggesting future research directions.
Hybrid Red Fox and Remora Optimization Algorithm Expedites Optimal Load Balancing in Cloud Computing
Authors: Umrao Lokendra Singh , Mishra Chandra Mani 
Published: December 2024

Abstract

Cloud task scheduling poses a complex optimization challenge due to dynamic nature of the cloud system and varying user demands. The system's load, determined by the cloud architecture and user requirements, can lead to failures such as increased power consumption and machine failures when the system is either under loaded or overloaded. Consequently, achieving task-load balancing on virtual machines (VMs) becomes crucial in cloud task scheduling to mitigate these issues. In this manuscript, proposed the Hybrid Red Fox and Remora Optimization Algorithm Expedites Optimum Load Balancing in Cloud Computing (HYB-RF-RO-LB-CC) to address the load equalizing problem in cloud networks. By incorporating the Red fox optimization algorithm (RFOA) into Remora Optimization Algorithm (ROA), achieve a useful load balancing algorithm. The proposed method focuses on identifying the optimal under load that considers multiple objective functions, like cost, response time, and resource utilization, ultimately minimizing the fitness function of load equalizing. The process HYB-RF-RO-LB-CC effectively assesses and balances the load of each virtual machine (VM) using fitness function. The proposed HYB-RF-RO-LB-CC approach is executed in CloudSim tool. The performance of the proposed HYB-RF-RO-LB-CC approach attains 3.101%, 7.12% and 6.7% higher makes span, 24.13%, 13.04% and 17.81% minimum energy utilization, 5.262%, 8.375% and 7.945% better throughput compared with existing methods such as Harris Hawk Optimization (HHO), Manta Ray Forging Optimization (MRFO) approach and Grey Wolf Optimization (GWO) algorithm respectively.
A Semi-Empirical Model for Fracture Energy Evaluation of a Ni2MnGa Magnetic Shape Memory Alloy
Authors: D'Silva Glen , Ciocanel Constantin 
Published: December 2024

Abstract

Ni2MnGa magnetic shape memory alloys (MSMAs) experience the shape memory effect due to magnetic field-induced or mechanical stress-induced microstructure reorientation. Crack nucleation and growth in Ni2MnGa is impacted by the alloy's evolving twin microstructure under magneto-mechanical loading conditions, eventually hampering its function in applications. This study reports on the evaluation of the fracture energy of a Ni2MnGa alloy under various magneto-mechanical loading conditions. The fracture energy of the alloy was evaluated through Vickers microindentation experiments that allowed the investigation of crack nucleation and growth under various magneto-mechanical loading conditions. The length of the cracks and the dimensions of the microindentation impressions were used to develop a semi-empirical relationship that predicts the fracture energy of the alloy as a function of magneto-mechanical loading conditions. The results confirm that the magnetic field (particularly the transversely applied magnetic field) facilitates crack growth, decreasing the fracture energy, while axial compressive stress impedes crack growth, increasing the fracture energy of the alloy. The proposed empirical relationship for the evaluation of fracture energy helps identify the magneto-mechanical loading conditions that are least conducive to fracture initiation and growth in MSMAs.
Modelling the Efficiency of Transportation Survey Recruitment and Reminder Methods
Authors: Davanzo Elis , Orvin Muntahith Mehadil , Fatmi Mahmudur Rahman 
Published: December 2024

Abstract

Transportation surveys are vital to generating data for informed infrastructure investment decision-making, developing travel demand models, and monitoring progress. By employing diverse recruitment and data collection strategies, it is possible to improve the overall effectiveness and accuracy of the surveys. With this motivation, this paper examines the efficiency of various survey recruitment and reminder methods. The dataset comes from a time-use survey deployed in Province of British Columbia, which utilized mail and self-registration as recruitment methods. In case of reminders, we used several methods including telephone calls, SMS, emails and social media postings. To further identify factors that influence the effectiveness of reminders and no reminders towards survey completion rates, statistical models are developed. Specifically, an ordered logit model is developed to examine households' need for frequent reminders to complete the survey. Additionally, a hazard model is developed to investigate the time it takes for the households to complete the survey without any reminders. Results indicate that among the self-registrants, about 69% of households that received an SMS completed the survey on the same day, with approximately 40.5% finishing within one hour. Results also revealed that self-registrants, older adults and single individuals are more likely to need more frequent communication to finalize the survey. In contrast, without reminders, residents of Metro Vancouver tend to complete surveys more quickly, while full-time workers may require more time. The findings of this study evaluate the effectiveness of various recruitment methods and reminder techniques, aiding in better targeting and communication to improve response rates.
Synthesis, characterization, and biological activity assessment of quaternary ammonium- functionalized cellulose: Enhancing antimicrobial features, free radical scavenging property, and thermal stability
Authors: Xuang Xin , Ganie Showkat Ali , Rather Luqman Jameel , Mir Shazia Shaheen , Assiri Mohammed A. , Mady Mohamed F. , Li Qing 
Published: December 2024

Abstract

The incorporation of chemical entities that confer antimicrobial properties represents a novel direction in cellulose material modification. This innovative strategy expands the potential applications of cellulose-based materials, particularly in sectors where antimicrobial efficacy is paramount. Through meticulous synthesis and characterization, we elucidate the structural and functional attributes of the modified cellulose, paving the way for its utilization in diverse biomedical settings. This study reports the successful synthesis and characterization of quaternary ammonium iodide salt of cellulose along with other intermediates using a comprehensive array of instrumental (SEM and TGA) and spectroscopic (FT-IR and NMR) techniques. The chemical functionalization of cellulose was accomplished through the process of tosylation, amination, and subsequent quaternization with ethylenediamine. The method used in this research pays way for cellulose modification under alkaline medium (H2O/NaOH/triethylamine) at a low temperature (5 oC) and time (5 h). A thorough assessment of the structural characterization and stability of the components revealed that the modified cellulose demonstrated superior antibacterial properties (disc diffusion assay), accompanied by improved thermal properties. The inhibition patterns clearly show the potency of synthesized cellulose derivative with 100% inhibition of bacterial strains at 16 mg/L concentration for both E. coli (gram negative) and S. aureus (gram positive). The potential free radical-scavenging mechanism, including the quantity of hydroxyl groups and the existence of ortho dihydroxy substitution for antioxidant efficacy, was examined. The quaternized group of cellulose adds to its antioxidant activity, as shown by our data, which indicated that the antioxidant abilities were in the order of Q-cell > cellulose. Consequently, Q-cell has significant antioxidant activity and may serve as a potential material in the food and pharmaceutical sectors.
Harnessing Protein Language Model for Structure-Based Discovery of Highly Efficient and Robust PET Hydrolases
Authors: Zheng Lirong , Wu Banghao , Zhong Bozitao , Huang Runye , Jiang Shifeng , Li Mingchen , Tan Pan , Hong Liang 
Published: December 2024

Abstract

Plastic waste, particularly polyethylene terephthalate (PET), poses significant environmental challenges, prompting extensive research into enzymatic biodegradation. However, existing PET hydrolases (PETases) are constrained to a narrow sequence space and exhibited limited performance for effective biodegradation. This study introduces a protein discovery pipeline, ProMine, which integrates protein language models (PLMs) with a representation tree to identify PETase based on structural similarity using sequence information. Using the crystal structure of IsPETase as a template, we employed ProMine to search for and cluster target proteins. PETase candidates were further screened using PLM-based assessments of solubility and thermostability, leading to the selection of 34 proteins for biochemical experiments. The results showed that 14 candidates exhibited PET degradation activity across a temperature range of 30-60 ℃. Notably, we identified a PET hydrolase from Kibdelosporangium banguiense (KbPETase), which has a melting temperature 32 ℃ higher than that of IsPETase and exhibits the highest PET degradation activity within 30-60 ℃ compared to other wild-type PETases. KbPETase also shows higher catalytic efficiency than FastPETase. X-ray crystallography and molecular dynamics simulations revealed that KbPETase has a conserved catalytic domain and enhanced intramolecular interactions, contributing to its improved functionality and thermostability. This work demonstrates a novel deep learning approach for discovering natural PETases with enhanced properties.
Immediate Redo Hepatic Artery Reconstruction in Living Donor Liver Transplantation
Authors: Zafar Muhammad 
Published: December 2024

Abstract

Background: In living donor liver transplant, vascular complications by compromising the blood flow to the graft can have significant and sometimes might lead to life-threatening consequences for the patient.
Aim: To evaluate the practice of immediate redo hepatic artery reconstruction in living donor liver transplant.
Methods: Across sectional study (June 2003-August 2015) included recipients with hepatic artery complication who underwent living donor liver transplantation at Chang Gung Memorial Hospital, Kaohsiung, Taiwan. Intraoperative complications necessitating immediate redo reconstruction of hepatic arterywere recorded. Vascular patency was evaluated by intraoperative and postoperative Doppler Ultrasonography. Immediate redo reconstruction was carried out when either arterial wall problem or low flow or RI less than 0.55. Late redo reconstruction (> 24 hours) was carried out to patients developed HAT postoperatively. The data was analyzed by SPSS version 21. P value less than 0.05 was regarded as significant.
Results: A59 recipients developed hepatic artery complication,and underwent redo reconstruction with incidence of 6.6%. Immediate redo reconstruction was performed in 86.4%, and 13.6% underwent late redo reconstruction (>24 hours). Minimal discrepancy was encountered in 71.2%, and there was significant correlation between discrepancy and RI, (p=0.048). RI <0.55 was seen in 25.4%. There was significant difference in the outcome between the groups of patient managed by early versus late HA redo reconstruction, (p=0.031).
Conclusion: Preliminary results show that immediate redo HA reconstruction preserving blood flow, maintaining perfusion and preventing post-transplant graft loss.