bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cardiotoxicity Monitoring and Cancer Therapy-Related Cardiac Dysfunction in a Heterogeneous Cancer Population: A Retrospective Study
Authors: Stevenson Madeline , Park Sihyeong , Hartshorne Taylor , Mendoza Zachary , Nguyen Vinh , Wong Lucas , Chiles Christopher , Widmer R. Jay 
Published: December 2024

Abstract

Background
Cardiotoxicity from chemotherapy can lead to significant heart damage, often without overt symptoms, mainly manifesting as cancer therapy-related cardiac dysfunction (CTRCD) when left ventricular ejection fraction (LVEF) declines by over 10% to below 53%. Current guidelines recommend thorough cardiovascular risk assessments for cancer patients, incorporating personal medical histories and potential biomarkers, yet a standardized risk stratification approach is lacking. This study aims to evaluate chemotherapeutics' effects on LVEF and the influence of patient characteristics on the risk of developing CTRCD.
Methods
This study is a retrospective chart review at a single center from 2013 to 2023, to assess the CTRCD prevalence in patients referred for transthoracic echocardiography due to cardiotoxicity risk. Data on demographics, comorbidities, medications, and echocardiographic parameters were extracted while maintaining confidentiality. Statistical analysis involved descriptive statistics for 532 patients, paired t-tests and risk-odds ratios for pre- and post-chemotherapy LVEF changes, and left ventricular global longitudinal strain (LVGLS) examination.
Results
The cohort included 532 patients with a median age of 69 (IQR = 61-78) years, who were predominantly female (57.9%), and had common comorbidities such as hypertension and diabetes. Among those assessed, the median LVEF decreased from 59.5% to 58%, with 9.2% meeting CTRCD criteria, particularly in breast and lung cancer patients. Lung disease and previous transient ischemic attacks (TIA) were associated with greater LVEF declines of 2.5% and 3.5%, respectively, whereas no subclinical cardiotoxicity was found in the limited LVGLS measurements.
Conclusion
In conclusion, this single-center cohort study highlights a clinical gap in comprehensive echocardiographic surveillance for patients undergoing chemotherapy, with less than half receiving necessary pre- and post-treatment assessments. Despite the moderate incidence of CTRCD (9.2%) in this cohort, reliance solely on LVEF as a marker for cardiotoxicity may overlook significant cardiovascular damage, underscoring the importance of early detection methods. The study revealed that pre-existing lung conditions and a history of TIA impacted LVEF changes, suggesting that these comorbidities should be considered in risk assessments. Overall, the findings advocate for improved cardiac monitoring and intervention strategies to protect the cardiovascular health of cancer patients throughout treatment.
Automated analysis of the difficulty of secondary school geometry theorems
Authors: Bartha Soma , Kerekes András , Kovács Zoltán , Recio Tomás 
Published: December 2024

Abstract

We elaborate, as a benchmark, a list of geometry theorems that are regularly used in Hungarian high schools, in specialized tracks for mathematics. Then, these statements are implemented as GeoGebra files, and algebraically proven (with certification) in GeoGebra Discovery. Next, these files are imported in Java Geometry Expert (JGEX), and geometrically proven with the associated Geometry Deductive Database method. In both programs, through quite different approaches in each case, we define and implement an algorithmic measure of the difficulty of a geometric theorem. Then, we compute the corresponding measures on the selected list of statements, and we analyze the obtained collection of pairs of difficulty grades, finding a moderate positive correlation (0.43) between GeoGebra Discovery's algebraic, and JGEX's deductive difficulty formulations. A correlation that seems to support the adequacy of the chosen approximation in our on-going work to algorithmically establish some ad-hoc measure of the difficulty of geometric statements that could be reasonably coincidental with the appreciation of human expert users (e.g. teachers).
Physical, Mechanical, Biological Properties and Characterization of Blended Films of Chitosan-Cellulose Diacetate Derived Waste Cigarette Filters
Authors: Htwe Aung Than , Kyaw May Thazin , Htun Hninn Wutt Yee , Tawng Margaret Hkawn , Thet Yamin 
Published: December 2024

Abstract

Cigarette butts (CB) accumulate due to the poor biodegradability of cellulose acetate filters, and the toxic substances trapped therein pose a threat to human life, marine ecosystems and the environment if not disposed of properly increase. Due to growing concerns stemming from inadequate landfill sites and growing environmental concerns about toxic combustion gases, there is a great need for environmentally friendly alternative CB waste treatment processes. This research describes the preparation of blended films with chitosan (CS) and cellulose diacetate (CDA) derived waste cigarette filters as reinforcement. The aim was to evaluate their physical, mechanical and biodegradable properties, and to determine their potential for biomedical use. Blended films were prepared via solvent casting CDA suspensions in CS solution, at CDA amount of 0.5, 1.0, 1.5, 2.0 and 2.5 (w/w) with pure chitosan as a reference. The prepared blended films were investigated by using the physical parameters, the physico-mechanical properties, the degree of swelling, and water uptake. Comparative characterization of the prepared blended films included XRD, FT IR, SEM, and TG-DTA analysis. The various types of CS-CDA blended films were also tested for antimicrobial activity using an agar well diffusion method. Subsequently, the biodegradable nature of the prepared CS-CDA blended films was studied through the soil burial test. Based on the results, The CS/CDA blended films which could be reduce cigarette waste filters and increase the values. In the future, these CS-CDA blended films can be developed in the membrane to use for biomedical applications as face sheet and mash sheet of COVID-19 pendemic.
Self-contained relaxation-based dynamical Ising machines
Authors: Erementchouk Mikhail , Shukla Aditya , Mazumder Pinaki 
Published: December 2024

Abstract

Dynamical Ising machines are based on continuous dynamical systems evolving from a generic initial state to a state strongly related to the ground state of the classical Ising model on a graph. Reaching the ground state is equivalent to finding the maximum (weighted) cut of the graph, which presents the Ising machines as an alternative way to solving and investigating NP-complete problems. Among the dynamical models, relaxation-based models are distinguished by their relations with guarantees of performance achieved in time scaling polynomially with the problem size. However, the terminal states of such machines are essentially non-binary, necessitating special post-processing relying on disparate computing. We show that an Ising machine implementing a special continuous dynamical system (called the V2 model) solves the rounding problem dynamically. We prove that the V2 model, starting from an arbitrary non-binary state, terminates in a state that trivially rounds to a binary state with the cut at least as big as obtained by optimal rounding of the initial state. Besides showing that relaxation-based dynamical Ising machines can be made self-contained, this result presents a non-Boolean realization of solving a non-trivial information processing task on Ising machines. Moreover, we prove that if the initial state of the V2-machine is a random limited amplitude perturbation of a binary state, the machine progresses to a state with at least as high cut as that of the initial binary state. Since the probability of improving the cut is finite, this shows that the V2-machine with random agitations converges to a maximum cut state almost surely.
A New Auxetic Structure-based Hybrid Gripperfor Harvesting Tomato-like Soft Fruits
Authors: Ansari Shahid , Gohil Mahendra Kumar , Maeda Yusuke , Bhattacharya Bishakh 
Published: December 2024

Abstract

Modern agriculture is reaping the benefits of automation by harvesting fruits and vegetables using robots that have adaptive grasping force depending on the compliance or softness of the fruit or vegetable. The successful operation of fruit picking using a robotic system with a gripper as an end effector hinges on its manipulation capability and ability to interact safely with the crop without affecting its physical properties. In this paper, we have proposed a novel hybrid gripper with six soft, passive auxetic structures attached to the rigid linkage, which has high shape conformability during the grasping of tomatoes through caging. The gripper is actuated through a scotch-yoke mechanism using a servo motor. A deep learning-based fruit localization algorithm has been developed to perform the picking operation of tomatoes through the gripper. A ROS-based framework has been used to control the robotic arm to achieve an optimized trajectory for fruit picking and to control the desired grasping forces along with the actuation of the pedicel cutter.
Using a method that combines genomics and systems biology, CDKN2A is identified as a possible indicator of survival in liver cancer
Authors: Chen Xueqin , Zhao Ruonan , Wang Ruiping , Zhang Rongqiang 
Published: December 2024

Abstract

[Abstract] Objective The prognostic implications of cuproptosis-related genes (CRGs) in hepatocellular carcinoma (HCC) are still uncertain, as cuproptosis is a recently discovered programmed cell death mechanism in tumors.
Methods CRGs from TCGA were obtained and then screened based on their strong correlation with the expression matrix of lncRNA associated with cuproptosis in patients with HCC. LASSO-COX regression models were developed using data from the cancer genome atlas (TCGA) and the international cancer genome consortium (ICGC) databases to discover a prognostic signature related to cuproptosis. The models' accuracy was evaluated using Kaplan-Meier curves and ROC models. The prognostic signature related to cuproptosis was evaluated for its ability to predict outcomes in HCC through various survival models including OS, PFS, DFS, and DSS. To further investigate the prognostic signature related to cuproptosis in hepatoma cell lines, quantitative real-time PCR (qRT-PCR) and western blot techniques were utilized. It was then preceded by studying the proliferation, migration, and invasion through CCK-8 and transwell assays, while flow cytometry was used for studying apoptosis. The tumorigenesis in hepatoma cell lines concerning a cuproptosis-related prognostic signature was further studied using the lentivirus transfection method and a subcutaneous transplantation model.
Results The study results indicated that CDKN2A was the crucial prognostic signature for HCC, in addition to highly expressed mRNA and proteins in hepatoma cell lines. The CDKN2A was determined as an independent variable distinguishing it from other HCC clinical features. CDKN2A knockdown not only inhibited the proliferation, migration, and invasion of hepatoma cell lines, but also arrested cell growth in the G2/M phase and promoted cell apoptosis. It precluded the growth of subcutaneous tumors in naked mice.
Conclusion In this study, three original prognostic models for HCC were established based on identifying a cuproptosis-related prognostic signature, validated using cell assays and nude mice subcutaneous transplantation models. Thus, CDKN2A could potentially become a new target for treating HCC, providing a theoretical basis and recommendations for utilizing CRG targets in HCC therapy.
Understanding Attitudes Toward Zoster Vaccination in the Hospital Setting: A Multidisciplinary Model to Contrast Vaccine Hesitancy in Fragile Patients. A prospective longitudinal observational study
Authors: Martinelli Silvia , Regazzi Luca , Rizzo Federica , Tamburrini Enrica , Salvo Pierluigi Francesco , Bosello Silvia Laura , Landi Francesco , Sica Simona , Spadea Antonietta , Pascucci Domenico , Laurenti Patrizia 
Published: December 2024

Abstract

Introduction:
The efficacy of recombinant adjuvanted vaccine (RZV) against Herpes Zoster (HZ) is universally recognized and is the only safe vaccine in immunocompromised persons and in higher-risk individuals. Higher-risk patients with primary or acquired immunodeficiencies are characterized by an increased risk of disseminated infection after HZ infection or after reactivation of HZ virus, due to their clinically fragile condition. To date, the rate of vaccination with RZV through non-hospital health services in this population does not reach optimal standards, either because of difficulties in accessing care or because of vaccine hesitancy (VH). According to the latest international guidelines, interventions to support community medicine are needed to increase vaccination coverage and to counteract VH.
Methods
The Fondazione Policlinico Universitario Agostino Gemelli IRCCS Hospital in Rome performed an organizational management model including the hospital and non-hospital health services (ASL Roma 1) dedicated to vaccine counseling and contrasting VH in frail patients with an indication for RZV vaccination. Multiple linear regression was used to analyze the impact of results.
Results
From July 2022 to July 2023, 178 patients underwent vaccine counseling and received two doses of RZV vaccine, of which, 90 responded to the recall to evaluate side effects, breakthrough HZ Infections and answered to the VAX Scale questionnaire. 34.27% were affected by HIV infection, 23% by HZ relapses or severe forms, and 21.35% by rheumatologic diseases. Total VH score tot 2.291. A statistically significant correlation was demonstrated between age/rheumatology patients/female sex and overall vaccine hesitancy. 80% and 74.44% of patients had no short-term side effects after the first and second doses, respectively. 3.33% had breakthrough HZ Infections. No patients had minor or major long-term (1 year) side effects. Comparison of responses to VAX scale in the first and recall phase, showed positive changes about VH, with differences ranging from 2.9 to 3.0 points.
Conclusions
This study demonstrates that a multidisciplinary approach to vaccine counseling can significantly reduce vaccine hesitancy and improve adherence among frail, high-risk patients.
Trial registration:
ClinicalTrials.gov ID: NCT06334861; date of registration: 2023-03-13
Predictive Modeling for Healthcare: Leveraging Categorical and Binary Data for Enhanced Accuracy
Authors: Saxena Tanuj , Maurya Ujjwal 
Published: December 2024

Abstract

Such dramatic growth in healthcare data has increased the necessity of developing predictive models capable of manipulating and processing categorical and binary data, which would constitute significant improvements in the predictability of diseases and patient management strategies. Traditional statistical approaches such as Logistic Regression have been utilized frequently but often fail when managing these complex relationships inherent to large health care datasets. Several studies recently shown that, in comparison with traditional methods, advanced machine learning techniques such as Random Forest, CatBoost, and Gradient Boosting can better capture complex, non-linear patterns and data interactions toward a high level of predictive accuracy. This paper systematically applies and evaluates these new techniques on healthcare datasets while focusing on the optimization of main performance metrics: accuracy, sensitivity, and specificity. Experimental results demonstrate that ensemble models, especially CatBoost, outperform traditional models in terms of prediction accuracy, and thus can be adapted to robust solutions in patient risk classification and early detection of diseases. The findings imply the importance of advanced machine learning methods in supporting the personalization of treatment plans and allocation of resources, leading towards exact, data-driven decision-making in healthcare systems.
Guided phase transition for mitigating voltage hysteresis of iron fluoride cathode materials in lithium-ion batteries
Authors: Jung Sung-Kyun , Jo Hyoi , Gong Minjeong , Kim Se Young , Seo Dong-Hwa 
Published: December 2024

Abstract

Despite the high capacity attained by conversion-reaction-based metal-fluoride cathode materials in lithium-ion batteries through multiple electron storage, the large voltage hysteresis and low structural reversibility constrain their use. Herein, we propose guided phase transitions for designing conversion cathode materials that undergo minimal structural changes upon lithium-ion storage. This approach reduces the compositional inhomogeneity, a culprit of the voltage hysteresis, while providing high structural reversibility. Unlike the thermodynamically stable rhombohedral FeF3 (R-FeF3), which suffers from irreversible phase transitions accompanied by drastic structural evolution, tetragonal FeF3 (T-FeF3), a thermodynamically metastable phase guided by fluoride-ion incorporation into FeF2 from the electrochemical splitting of LiF, undergoes facile and reversible phase transitions during intercalation and conversion reactions by sustaining its structural integrity upon charge and discharge. Our research provides valuable insights into the significance of avoiding an irreversible reaction pathway and inducing it to minimize changes in the crystal structure for the design of conversion cathode materials with low voltage hysteresis and excellent cycle stability.
A high-resolution compound vulnerability function for European winter storm losses
Authors: Ederen D. , Cerda S. Fonseca , Botzen W. J.W. , Aerts J. C.J.H. , Lupi V. , Scussolini P. , Gubbels K. B. 
Published: December 2024

Abstract

Economic losses from European winter storms impose a significant burden on society and are expected to increase due to exposure growth and climate change. Vulnerability functions play a key role in estimating such losses as they describe the relationship between a natural hazard’s intensity and damage to the exposed asset. This study fills an important gap in the literature by providing a vulnerability function for residential buildings which, for the first time, is able to account for damage from both the wind and the precipitation that winter storms produce. This compound vulnerability function is estimated using truncated beta regressions, and based on a large number of object-level insurance claims from The Netherlands and ultra-high resolution meteorological observations. Comparing our vulnerability function to the conventional specification, which only considers damage from wind, shows that the latter underestimates the damage by 5% [21%] {57%} for winter storms with 24-hour cumulative precipitation levels of 50 mm [75 mm] {100 mm}. Given that climate change is projected to further increase the frequency and intensity of such precipitation extremes in Europe, our study provides evidence in favor of using compound vulnerability functions to estimate future winter storm losses more accurately. Our vulnerability function can be used in natural catastrophe models to accurately estimate damage to residential buildings from European winter storms.
The Development of Data Structures for Preventing Data Loss and Enhancing Data Analysis in Distributed Communication Networks
Authors: Supamid Tipaporn , Wongkumsin Suwit 
Published: December 2024

Abstract

In the contemporary digital landscape, distributed communication networks are integral to the transmission of data and the interconnection of various devices. Nevertheless, a prevalent issue encountered is the phenomenon of data loss during transmission, which complicates the analysis of the data obtained from these networks. This research endeavor is centered on the formulation of a data structure aimed at mitigating data loss and enhancing the efficacy of data analysis. The architecture integrates mechanisms for data encryption, data replication, and error detection to uphold data integrity. Furthermore, methodologies for parallel processing and task distribution are employed to adeptly manage extensive and intricate datasets. The investigation revealed that this methodology has the potential to diminish data loss by 30% and augment data analysis efficiency by as much as 90%, thereby facilitating a more stable and effective operation of distributed communication networks.
Impact of Introducing an Advanced Care Paramedic Program on Clinical Outcomes for Out-of-Hospital Cardiac Arrest Patients Transported to Hospital
Authors: McGraw Mark , Chandra Kavish , Mekwan Jay , Fraser Jacqueline , McDougall Pamela , Pishe Tushar , Atkinson Paul 
Published: December 2024

Abstract

Introduction:
Out-of-hospital cardiac arrest is a leading cause of mortality. Timely advanced life support, including the administration of epinephrine, improves clinical outcomes. This study evaluated the impact of introducing an advanced care paramedic program on key clinical outcomes, including return of spontaneous circulation, survival to hospital admission, and survival to hospital discharge.
Methods:
A retrospective health records review was conducted on patients with out-of-hospital cardiac arrest transported to a tertiary Canadian hospital. Patients were included if they were transported by emergency medical services to the emergency department between January 2010 and March 2019. Exclusion criteria included age under 18 years, arrest in the emergency department, trauma, or overdose-related arrests. Data were analyzed using chi-square tests, with a p-value <0.05 considered statistically significant.
Results:
Of the 390 patients identified, 228 (58.5%) from the pre-advanced care paramedic cohort and 162 (41.5%) from the post-advanced care paramedic cohort were included. Following the introduction of the advanced care paramedic program, return of spontaneous circulation was achieved by 67 out of 162 patients (41.3%) in the post-implementation group compared to 72 out of 228 patients (31.6%) in the pre-implementation group (OR 1.5, 95% CI 1.0-2.3, p=0.05). Survival to hospital admission increased from 34 out of 228 patients (14.9%) to 40 out of 162 patients (24.7%) (OR 2.0, 95% CI 1.2-3.3, p=0.015). Survival to hospital discharge increased from 7 out of 228 patients (3.1%) to 18 out of 162 patients (11.1%) (OR 4.8, 95% CI 2.0-11.5, p<0.001).
Conclusion:
The introduction of a regional advanced care paramedic program significantly improved clinical outcomes for patients experiencing out-of-hospital cardiac arrest. These findings support the integration of advanced care paramedics into prehospital care protocols.