bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding Hip Contact Stress Based on Types of Physical Activity: A Systematic Review
Authors: Prasetya Arief Indra Perdana , Ammarullah Muhammad Imam , Winarni Tri Indah , Pramono Adriyan , Jamari Jamari , Kamarul Tunku , Syahrom Ardiyansyah 
Published: January 2025

ABSTRACTBackground and AimsHigh contact stresses involving the hip have been shown to increase the risk of developing hip osteoarthritis (OA). Although several risk factors have been identified for OA, a holistic approach to predicting contributed factors toward increased hip contact stresses have not been explored. This study was conducted to comprehensively understand the effects of physical activity on high hip contact stress as predisposing factors of OA.MethodsThe protocol of this systematic review was registered in PROSPERO with registration number CRD42022296638 and conducted based on PRISMA guidelines. Full articles that matched our inclusion criteria were selected using PubMed, Web of Science, and Scopus search engines and keywords such as “hip contact stress,” “hip contact force,” and/or “hip contact pressure.” Category of factors, experimental design, results of the study, and evidence from each article were analyzed.ResultsIn total 7972 papers were screened, identified, and reviewed. Two independent authors read the collected fulltext of eligible articles resulting in 21 papers that fulfilled the inclusion criteria of this systematic review.ConclusionTypes of physical activity (n = 21) have correlation with high hip joint contact stress in various manner. Based on the research findings obtained from various inclusion papers, it can be broadly concluded that the more intense the physical activity, such as running and stair climbing, the greater the impact on the increase in hip contact stress values. However, the reviewed studies vary in their methods. This finding suggested that this area is not well investigated and warrants future research.
Predicting Factors Affecting Survival Rate in Patients Undergoing On‐Pump Coronary Artery Bypass Graft Surgery Using Machine Learning Methods: A Systematic Review
Authors: Jafarkhani Alireza , Imani Behzad , Saeedi Soheila , Shams Amir 
Published: January 2025

ABSTRACTBackground and AimCoronary artery bypass grafting (CABG) is a key treatment for coronary artery disease, but accurately predicting patient survival after the procedure presents significant challenges. This study aimed to systematically review articles using machine learning techniques to predict patient survival rates and identify factors affecting these rates after CABG surgery.MethodsFrom January 1, 2015, to January 20, 2024, a comprehensive literature search was conducted across PubMed, Scopus, IEEE Xplore, and Web of Science. The review adhered to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines. Inclusion criteria included studies that evaluated survival rates and predictors associated with CABG patients during the specified period.ResultsAfter eliminating duplicates, a total of 1330 articles were identified. Following a systematic screening, 24 studies met the inclusion criteria. Our findings revealed 43 distinct factors influencing survival rates in patients undergoing CABG. Notably, five factors—age, ejection fraction, diabetes mellitus, a history of cerebrovascular disease or accidents, and renal function—were consistently identified across multiple studies as significant predictors of postsurgical survival.ConclusionThis systematic review identifies key factors influencing survival rates after CABG surgery and highlights the role of machine learning in improving predictive accuracy. By identifying high‐risk patients through these key factors, our findings offer practical insights for healthcare providers, enhancing patient management and customizing therapeutic strategies after CABG. This study significantly enhances existing literature by combining machine learning techniques with clinical factors, thereby improving the understanding of patient outcomes in CABG surgery.
Artificial Intelligence in Pediatric Epilepsy Detection: Balancing Effectiveness With Ethical Considerations for Welfare
Authors: Mourid Marina Ramzy , Irfan Hamza , Oduoye Malik Olatunde 
Published: January 2025

ABSTRACTBackground and AimEpilepsy is a major neurological challenge, especially for pediatric populations. It profoundly impacts both developmental progress and quality of life in affected children. With the advent of artificial intelligence (AI), there's a growing interest in leveraging its capabilities to improve the diagnosis and management of pediatric epilepsy. This review aims to assess the effectiveness of AI in pediatric epilepsy detection while considering the ethical implications surrounding its implementation.MethodologyA comprehensive systematic review was conducted across multiple databases including PubMed, EMBASE, Google Scholar, Scopus, and Medline. Search terms encompassed “pediatric epilepsy,” “artificial intelligence,” “machine learning,” “ethical considerations,” and “data security.” Publications from the past decade were scrutinized for methodological rigor, with a focus on studies evaluating AI's efficacy in pediatric epilepsy detection and management.ResultsAI systems have demonstrated strong potential in diagnosing and monitoring pediatric epilepsy, often matching clinical accuracy. For example, AI‐driven decision support achieved 93.4% accuracy in diagnosis, closely aligning with expert assessments. Specific methods, like EEG‐based AI for detecting interictal discharges, showed high specificity (93.33%–96.67%) and sensitivity (76.67%–93.33%), while neuroimaging approaches using rs‐fMRI and DTI reached up to 97.5% accuracy in identifying microstructural abnormalities. Deep learning models, such as CNN‐LSTM, have also enhanced seizure detection from video by capturing subtle movement and expression cues. Non‐EEG sensor‐based methods effectively identified nocturnal seizures, offering promising support for pediatric care. However, ethical considerations around privacy, data security, and model bias remain crucial for responsible AI integration.ConclusionWhile AI holds immense potential to enhance pediatric epilepsy management, ethical considerations surrounding transparency, fairness, and data security must be rigorously addressed. Collaborative efforts among stakeholders are imperative to navigate these ethical challenges effectively, ensuring responsible AI integration and optimizing patient outcomes in pediatric epilepsy care.
Cerebral Malaria in Adults: A Retrospective Descriptive Analysis of 80 Cases in a Tertiary Hospital in The Gambia, 2020–2023
Authors: Bittaye Sheikh Omar , Jagne Abubacarr , Jaiteh Lamin E. S. , Amambua‐Ngwa Alfred , Sesay Abdul Karim , Ramirez Williams Estrada , Ramos Asmell , Effa Emmanuel , Nyan Ousman , Njie Ramou 
Published: January 2025

ABSTRACTBackground and AimCerebral malaria in Gambian children has been studied but there is limited information on CM in adults. The study assesses the clinical features and outcome of CM in adult patients admitted at the Edward Francis Small Teaching Hospital.MethodThis was a retrospective review of all adult patients with malaria admitted to the internal medicine department from October 18, 2020 to February 2, 2022.ResultsA total number of 319 adults were admitted with malaria. Eighty (25%) patients met the criteria for CM. The median age of the CM patients was 19 years. CM patients were younger (p < 0.001), more likely to be of the adolescent age group (p < 0.001), more likely to be referred from a lower‐level health facility (p < 0.001), and more likely to be admitted in intensive care p < 0.001) as compared to NSCM or UM patients. The total in‐hospital mortality of CM patients was 23.8%. Ten (52.6%) out of the 19 patients died within the first 24 h of admission. In multivariate analysis, CM patients with acute kidney injury at presentation was an independent predictor of mortality in this study.ConclusionCM seems to affect the adolescent age group more than the older adults in The Gambia. The clinicians should be able to identify these high‐risk patient group and institute prompt critical care interventions and/or treatment. The findings in this study also identify the need to expand access of critical care interventions and hemodialysis to help improve the prognosis of adult CM patients in The Gambia.
An alternative for hysteroscopic myomectomy: Ultrasound‐guided single‐step myomectomy for submucous myoma uteri with ring forceps, a retrospective study
Authors: Ozcivit Erkan Ipek Betul , Kuru Oguzhan , Acar Ilkin , Oztas Atakan Mahmut , Gezer Altay 
Published: January 2025

AbstractObjectiveHysteroscopic myomectomy is widely regarded as safe and feasible, although achieving single‐session results for larger myomas often requires alternative methods. This study introduces a novel approach: ultrasound‐guided myoma extirpation using ring forceps combined with hysteroscopy.MethodsThis retrospective, single‐center study includes patients who underwent ultrasound‐guided myoma extirpation between 2016 and 2024. Data were collected retrospectively, and myomas were classified according to the International Federation of Gynecology and Obstetrics leiomyoma subclassification system. Under ultrasound guidance, the myoma was extirpated using ring forceps. The pre‐, peri‐, and postoperative outcomes were recorded and analyzed.ResultsA total of 25 patients were included, with a mean age of 44.76 ± 8.09 years. Most patients (92%) were premenopausal, and the primary symptoms were irregular bleeding (76%) and menorrhagia (68%). The median myoma size was 3 cm (interquartile range [IQR]: 2–4 cm). The median operation time was 30 min (IQR: 20–42 min). There was no statistically significant correlation between the duration of the operation and the diameter of the myoma uteri. Most myomas were located in the fundus, left side, or anterior wall (20% each), with 60% classified as type 0. Postoperative assessments revealed no residual myomas in 84% of cases. Uterine perforation and cervical laceration occurred as complications in two cases, while four cases required an additional session. Two patients with infertility achieved full‐term pregnancies post‐surgery.ConclusionThis new, minimally invasive technique might be a feasible option for large myomas, particularly in low‐resource settings. It minimizes the need for multiple sessions, providing reassuring results for patients with suitable indications.
NIR‐II Fluorescence Image Translation via Latent Space Disentanglement
Authors: Yu Xiaoming , Tian Jie , Hu Zhenhua 
Published: January 2025

ABSTRACTThe second near‐infrared window (NIR‐II) fluorescence imaging is an excellent optical in vivo imaging method. Compared with NIR‐IIa window (1000–1300 nm), NIR‐IIb window (1500–1700 nm) imaging can significantly improve the imaging effect. However, due to the limitation that there are no molecular probes approved for NIR‐IIb imaging in humans, we expect to achieve the translation of NIR‐IIa images to NIR‐IIb images through artificial intelligence. NIR‐II fluorescence imaging is divided into macroscopic imaging of animal bodies and microscopic imaging of tissue and nerves. The two imaging scenarios are different. To realize the translation of two scene images at the same time, this paper designs a generative adversarial network model. The core idea is to disentangle the information in the encoded latent space into the information shared by the macroscopic and microscopic images and information specific to both to extract the high‐quality feature maps for decoding. In addition, we improve the contrastive loss and use the attention‐aware sampling strategy to select patches, which further maintains the source image content structure. The experiment results demonstrate the superiority and effectiveness of the proposed method.
Suitability of Water Quality for Irrigation Purposes Using GIS‐Based Irrigation Water Quality Index
Authors: Şimşir Mehmet , Yıldız Sayiter , Karakuş Can Bülent , Özbek Dilara Ülger 
Published: January 2025

ABSTRACTIn this study, surface water quality was assessed on the basis of irrigation water quality indices and the irrigation water quality index (IWQI) via GIS. The study was carried out on the basis of analyses of samples collected in August (dry) and November (wet) 2023 from 12 designated points along the Yıldız River in Sivas. The sodium adsorption ratio (SAR), Kelly index (KI), sodium percentage (Na%), permeability index (PI), residual sodium carbonate (RSC), magnesium hazard (MH) indices and IWQI were calculated to determine the classification of irrigation water quality. Additionally, analyses of Ca2+, Cl−, Fe2+, K+, HCO3−, Mg2+, Mn, Na+, pH and SO42− were conducted on the samples. The spatial distributions of the calculated parameters were mapped via GIS, and irrigation water quality assessment was performed according to the US Salinity Diagram and irrigation water quality standards. The IWQI values ranged from 401 to 61 during the rainy season and from 42 to 67 during the dry season. In the rainy season, two surface water samples were classified as ‘poor (MR: moderate restriction, IWQI: 55–70)’ and nine as ‘very poor (HR: high restriction, IWQI: 40–55)’. In the dry season, three surface water samples were classified as ‘poor (MR: moderate restriction)’ and nine as ‘very poor (HR: high restriction)’. According to the US Salinity Diagram, the majority of surface water samples in both the rainy and dry seasons fell into categories C3S1 (high‐salinity hazard–low‐sodium hazard) and C2S1 (medium‐salinity hazard–low‐sodium hazard), respectively. The results highlight the effectiveness of these methodologies in evaluating surface water quality, assisting in the development of informed management strategies for sustainable water resource use in agricultural environments. The IWQI has proven to be a good tool for assessing the quality of irrigation water in the study area and managing water quality and can help decision makers manage water resources more effectively for sustainable agriculture.
Microfluidics Based Particle and Droplet Generation for Gene and Drug Delivery Approaches
Authors: Onan Deniz , Özder Melike , Sipahi Meryem İrem , Poyraz Nazlıcan , Apaydın Ceylin , Erel‐Akbaba Gülşah , Akbaba Hasan 
Published: January 2025

ABSTRACTMicrofluidics‐based droplets have emerged as a powerful technology for biomedical research, offering precise control over droplet size and structure, optimal mixing of solutions, and prevention of cross‐contamination. It is a major branch of microfluidic technology with applications in diagnostic testing, imaging, separation, and gene amplification. This review discusses the different aspects of microfluidic devices, droplet generation techniques, droplet types, and the production of micro/nano particles, along with their advantages and limitations. Passive and active methods for droplet formation are discussed, as well as the manipulation of droplet shape and content. This review also highlights the potential applications of droplet microfluidics in tissue engineering, cancer therapy, and drug delivery systems. The use of microfluidics in the production of lipid nanoparticles and polymeric microparticles is also presented, with emphasis on their potential in drug delivery and biomedical research. Finally, the contributions of microfluidics to vaccines, gene therapy, personalized medicine, and future perspectives are discussed, emphasizing the need for continuous innovation and integration with other technologies, such as AI and wearable devices, to further enhance its potential in personalized medicine and drug delivery. However, it is also noted that challenges in commercialization and widespread adoption still need to be addressed.
Mfgnn: Multi‐Scale Feature‐Attentive Graph Neural Networks for Molecular Property Prediction
Authors: Ye Weiting , Li Jingcheng , Cai Xianfa 
Published: January 2025

ABSTRACTIn the realm of artificial intelligence‐driven drug discovery (AIDD), accurately predicting the influence of molecular structures on their properties is a critical research focus. While deep learning models based on graph neural networks (GNNs) have made significant advancements in this area, prior studies have primarily concentrated on molecule‐level representations, often neglecting the impact of functional group structures and the potential relationships between fragments on molecular property predictions. To address this gap, we introduce the multi‐scale feature attention graph neural network (MfGNN), which enhances traditional atom‐based molecular graph representations by incorporating fragment‐level representations derived from chemically synthesizable BRICS fragments. MfGNN not only effectively captures both the structural information of molecules and the features of functional groups but also pays special attention to the potential relationships between fragments, exploring how they collectively influence molecular properties. This model integrates two core mechanisms: a graph attention mechanism that captures embeddings of molecules and functional groups, and a feature extraction module that systematically processes BRICS fragment‐level features to uncover relationships among the fragments. Our comprehensive experiments demonstrate that MfGNN outperforms leading machine learning and deep learning models, achieving state‐of‐the‐art performance in 8 out of 11 learning tasks across various domains, including physical chemistry, biophysics, physiology, and toxicology. Furthermore, ablation studies reveal that the integration of multi‐scale feature information and the feature extraction module enhances the richness of molecular features, thereby improving the model's predictive capabilities.
Ready for the next storm? An analysis of Florida's hurricane preparedness for its residents with disabilities
Authors: Mimbs Hope , Barrett Anne E. , Soulie Brianna , Noblitt Jessica , Michael Cherish 
Published: January 2025

AbstractThe increasing frequency and severity of hurricanes induced by climate change, heighten the importance of understanding the emergency preparedness and needs of older adults with disabilities. This segment of the population faces an elevated risk of injury or death in hurricanes and other weather‐related emergencies, but little is known about their preparation for and evacuation intentions regarding such emergencies. Even less is known about communities' readiness to address older adults with disabilities' needs during emergencies. We examine hurricane readiness at the individual level using data from an online survey of Floridians aged 50 and older (n = 3918) and at the county level using administrative data from 65 of Florida's 67 counties. Results of individual‐level analyses revealed that older adults with self‐reported mobility or vision impairments had lower odds of being hurricane prepared, suggesting they may have unmet needs in such emergencies. Results of county‐level analyses yielded mixed results. Although counties with higher proportions of their residents having limited abilities tended to have more special needs emergency shelters, counties with higher proportions of their residents using special equipment tended to have fewer—rather than more—such shelters. Our study provides insight that can inform policies aimed at safeguarding older adults with disabilities from the risks posed by the warming planet's intensifying storms.
Does Cerebrospinal Fluid Leak in Pituitary Surgery Affect Patient Reported Quality of Life?
Authors: Duggal Camille , Detombe Sarah , Lefteris Ashton , Van Uum Stan , Sowerby Leigh , Duggal Neil , Rotenberg Brian 
Published: January 2025

BackgroundEndoscopic techniques allow for improved visualization and tumor debulking of pituitary adenomas. More thorough tumor resection, however, can be associated with higher rates of CSF leaks. We set out to determine if CSF leaks influenced patient perceived quality of life outcomes.MethodsThis retrospective study included 152 patients who underwent endoscopic pituitary tumor resection over a 10‐year period. QoL was assessed using the SF‐36 questionnaire and completed before surgery, 6 weeks and 6 months post‐operatively. Statistical analysis was conducted using a equivalence test and a two‐way mixed model ANOVA to assess intraoperative CSF leak, postoperative CSF leak, redo surgery, and the use of a lumbar drain.ResultsOf the 152 patients, 98 had a potential intraoperative CSF leak. Intra‐ and postoperative CSF leaks did not significantly impact patient reported QoL outcomes at 6 months following surgery. There was clinical equivalence in mental scores as early as 6 weeks and 6 months for physical scores. There was no statistically significant difference in physical (p‐value = 0.975) and mental (p = 0.204) scores for patients who experienced a postoperative CSF leak. There was no statistically significant difference in QoL in the mental and physical scores for patients that received a lumbar drain (physical score p = 0.832; mental score p = 0.915) or redo surgery (physical score p = 0.830; mental score p = 0.204).ConclusionThis article demonstrates that CSF leaks do not impact patient‐reported QoL outcomes at 6 months post‐surgery. This will allow surgeons to better provide insight and counsel patients regarding the relevance of CSF leaks in the setting of pituitary procedures.Level of EvidenceIII Laryngoscope, 2025
Release Strategy of Competing Retailers for Reserved Produce Under the Government's Emergency Reserves With Order Constraints
Authors: Lei Ting , Dan Bin , Yuan Yongqi , Tian Yu , Ding Yu 
Published: January 2025

ABSTRACTThe government establishes an emergency reserve system and releases reserved produce through competing retailers in a fresh produce supply chain. We study the release strategy of competing retailers for reserved produce under the government's emergency reserves with order constraints. Our results reveal that competing retailers are willing to release reserved produce despite intensifying market competition. The release of reserved produce does not necessarily cannibalize supplies of fresh produce; however, the order constraints on reserved produce may instead reduce fresh produce supplies. It can also simultaneously improve or reduce supply chain performance and consumer surplus, bringing a “win‐win” or “lose‐lose” situation.