bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comprehensive Flood Risk Assessment for Railroad Network: Case Study for Iowa
Authors: Cikmaz Atiye Beyza , Alabbad Yazeed , Yildirim Enes , Demir Ibrahim
Published: April 2024

Climate-induced disasters, particularly floods, pose a substantial risk to human well-being. These risks encompass economic losses, infrastructural damage, disruption of daily life, and potential loss of life. This study focuses on understanding flood risks to critical infrastructure, emphasizing the resilience and reliability of essential services during such disasters. In the United States, the railway network is vital for the distribution of goods and services. This research specifically targets the railway network in Iowa, a state where the impact of flooding on railways has not been extensively studied. We employ comprehensive GIS analysis to assess the vulnerability of the railway network, bridges, rail crossings, and facilities under 100- and 500-year flood scenarios at the state level. Additionally, we conduct a detailed investigation into the most flood-affected counties, focusing on the susceptibility of railway bridges. Our state-wide analysis reveals that in a 100-year flood scenario, up to 9% of railroads, 8% of rail crossings, 58% of bridges, and 6% of facilities are impacted. In a 500-year flood scenario, these figures increase to 16%, 14%, 61%, and 13%, respectively. Further, our secondary analysis using flood depth maps indicates that approximately half of the railway bridges in the flood zones of the studied counties could become non-functional in both flood scenarios. These findings are crucial for developing effective disaster risk management plans and strategies, ensuring adequate preparedness for climate change impacts on railway infrastructure.
Lifetime Cost Analysis of Concrete Barriers and Steel Guardrails
Authors: Nemati Alireza , Haas Meridian , Torick David , Nazari Shima
Published: April 2024

This study investigates the lifetime costs associated with concrete barriers and steel guardrails. We introduce a cost analysis methodology that incorporates critical factors such as construction costs, maintenance costs, exposure risks during maintenance activities, and the costs imposed to traveling public through the increased traffic and the crash outcomes. We integrate various parameters including economic factors, road geometry, general weather condition, and traffic mix to estimate a location-dependent cost for each type of barrier accurately. A software tool, named CalBarrier, was developed during this study to carry out the calculations and the comparison of lifetime cost of aforementioned barriers. An inherent strength of this research is its reliance on recent real data extracted from various databases of California Department of Transportation (Caltrans), ensuring precision and relevance in accounting for various influential factors. Drawing insights from Caltrans practices and interviews with their personnel, this study emphasizes the intricate decision-making process involved in mitigating safety risks and reducing operational expenses. Although our data originates from California, the methodology for life cycle cost analysis, and our software are applicable for regions with different socio-economic conditions by adjusting the baseline costs, making our findings a valuable resource for other areas facing comparable challenges.
Economic evaluation of a community dental care model for people experiencing homelessness.
Authors: Nguyen Tan , Withers Lyndsey , Witton Robert , Paisi Martha
Published: April 2024

Aim
The study aims to conduct economic evaluation of the Peninsula Dental Social Enterprise (PDSE) programme for people experiencing homelessness over an 18-month period, when compared to a hypothetical base-case scenario (‘status quo’).
Methods
A decision tree model was generated in Treeage Pro Healthcare 2024. Benefit-cost analysis and cost-effectiveness analysis were performed using data informed by the literature and probabilistic sensitivity analysis (Monte-Carlo simulation with 1,000 cycles). The predetermined willingness to pay threshold was estimated to be £59,502 per disability-adjusted life year (DALY) averted. Costs (£) and benefits were valued in 2020 prices. Health benefits in DALYs included dental treatment for dental caries, periodontitis and severe tooth loss.
Results
The hypothetical cohort of 89 patients costs £11,502 (SD 488) and £57,118 (SD 2,784) for the base-scenario and the PDSE programme, respectively. The health outcomes generated 0.9 (SD 0.2) DALYs averted for the base-case scenario, and 5.4 (SD 0.9) DALYs averted for the PDSE programme. The DALYs averted generated £26,648 (SD 4,805) and £163,910 (SD 28,542) in benefits for the base-scenario and the PDSE programme, respectively. The calculated incremental benefit-cost ratio was 3.02 (SD 0.5) and incremental cost-effectiveness ratio was £10,472 (SD 2,073) per DALY averted. Uncertainty analysis demonstrated that the PDSE programme was 100% cost-effective.
Conclusions
Funding a targeted dental programme from the UK healthcare perspective that provides timely and affordable access to dental services for people experiencing homelessness is cost-effective.
Muon Spin Relaxation Study of Spin Dynamics on a Kitaev honeycomb material H3LiIr2O6
Authors: Shu Lei , Shu Lei , Yang Yanxing , Yang Yanxing , Jiang Chengyu , Jiang Chengyu , Huang Liang-Long , Huang Liang-Long , zhu Zihao , zhu Zihao , Chen Changshen , Chen Changshen , Wu Qiong , Wu Qiong , Ding Zhao-Feng , Ding Zhao-Feng , Tan Cheng , Tan Cheng , Biswas Pabitra , Biswas Pabitra , Hillier Adrian , Hillier Adrian , Shi Youguo , Shi Youguo , Yu Dapeng , Yu Dapeng , Liu Cai , Liu Cai , Wang Le , Wang Le , Ye Fei , Ye Fei , Mei Jiawei , Mei Jiawei
Published: April 2024

The vacancy effect in quantum spin liquid (QSL) has been extensively studied. A finite density of random vacancies in the Kitaev model can lead to a pileup of low-energy density of states (DOS), which is generally experimentally determined by a scaling behavior of thermodynamic or magnetization quantities. Here, we report detailed muon spin relaxation (μSR) results of H3LiIr2O6, a Kitaev QSL candidate with vacancies. The absence of magnetic order is confirmed down to 80 mK, and the dynamical spin fluctuations are found to be persistent at low temperatures. Intriguingly, the time-field scaling law of longitudinal-field μSR polarization is observed with the critical exponent of 0.46, exhibiting excellent consistency with scaling behavior of specific heat and magnetization data. This points to the finite DOS with the form of N(E) ~ Eν, wihch is expected for the Kitaev QSL in the presence of vacanncies.
Enhancing Mixed Methods Research with your generative AI assistant – A Tutorial and Evaluation for Scholars
Authors: Combrinck Celeste
Published: April 2024

Scholars from all disciplines can benefit from learning how to use generative Artificial Intelligence (GAI or AI) for data analysis. The current article used real data to demonstrate the analysis and synthesis of mixed methods research (MMR) data with generative AI. I also explore how reliable and valid data outputs are and how to improve the use of generative AI for research. The demonstration data used emanated from a study done in South Africa, with a quantitative sample size of 969 first-year engineering students and, for the qualitative part, 14 second-year students. In the current article, I compare my original analysis to ChatGPT results. Generative AI is a mind tool that is ideal when utilised with human insight to check the cohesion, consistency, and accuracy of the data analysis. The current content is geared towards enhancing methodological application regardless of field or discipline and includes access to a prompt library and examples of using outputs. For the qualitative analysis, I found that ChatGPT could detect similar themes but missed some, and its write-up was shallower than our human version. The quantitative analysis was accurate for the descriptive statistics, but the researcher had to use best judgment to select the correct inferential analysis. A quantitative and qualitative analysis should be conducted separately in generative AI before asking the bot for help with mixed methods research. I give guidelines and a tutorial on how to use chatbots in an ethically responsible and scientifically sound manner for research in social and human sciences.
Sustainable Wardrobe: Recycled Clothing Towards Sustainability and Eco-Friendliness
Authors: K.P Jaheer Mukthar , Nagadeepa C , Selvaratnam Doris Padmini , Pushpa A
Published: April 2024

Apparel is an essential aspect of our daily lives, but it comes with a high environmental cost. The production and disposal of clothing contribute to pollution, greenhouse gas emissions, and the depletion of natural resources. However, recycled clothing presents an opportunity to reduce the impact of the fashion industry on the environment. The fashion industry is a major contributor to both social and environmental issues, starting from the manufacturing process and ending with consumer disposal habits. Despite up to 95% of discarded clothing being reusable or recyclable, every year, about 150 million tons of apparel and footwear are sold worldwide, with 85% of them ending up in landfills or being incinerated. The lack of consumer awareness and inadequate infrastructures in many countries are key reasons for this. To tackle this issue, the industry needs to move away from the current linear "take-make-dispose" system. Many clothing brands have already adopted recycling and sustainability as their slogans, and new clothing technologies such as producing fibers from discarded materials, dyeing fabrics without water, and creating zero-waste patterns are providing innovative ways to ensure a clean and green environment. This study investigates the impact of environmental concerns, perceived value, personal norms, and willingness to pay on consumers' intentions to buy recycled clothing, providing valuable insights for recycled clothing marketers and filling a research gap in consumer behavior literature. By choosing recycled clothing, consumers can support sustainable production practices and contribute to a cleaner and healthier planet. Individuals can contribute positively to the environment by making conscientious choices when they make purchases.
Comprehensive genomic analysis of sporadic multiple meningiomas reveals clonal origin and histotype-specific evolution: a case report
Authors: Sakaguchi Maki , Horie Masafumi , Ito Yukinobu , Tanaka Shingo , Mizuguchi Keishi , Ikeda Hiroko , Kiyokawa Etsuko , Nakada Mitsutoshi , Maeda Daichi
Published: April 2024

Meningioma is the most common primary intracranial tumor in adults, with up to 10% manifesting as multiple tumors. Data on the genomic and molecular changes in sporadic multiple meningiomas are scarce, leading to ongoing debates regarding their evolutionary processes. A comprehensive genetic analysis of a large number of lesions, including minute occult meningiomas (MOMs), is necessary to explore these two possible origins: clonal and independent. In the present study, we performed whole-exome sequencing and analyzed somatic single-nucleotide variants (SNVs), insertions/deletions (INDELs), and copy number alterations (CNAs) in a patient with sporadic multiple meningiomas. These meningiomas included two mass-forming lesions of different histological subtypes (transitional and chordoid) and three MOMs. Genetic analysis revealed CNAs on chromosomes 22q and Y as common abnormalities in the two largest tumors. Furthermore, we identified SNV/INDELs unique to each focus, with NF2 mutation prevalent in the transitional meningioma and CREBBP mutation in the chordoid meningioma. Loss of chromosome 22 was detected in all three MOMs, whereas an NF2 somatic mutation was found only in the largest MOM. Overall, we elucidated the clonal origin and histotype-specific evolution of multiple meningiomas in this case. CNAs may serve as the initial driving event in meningioma development.
Pretreatment with BTK inhibitors could improve the sensitivity of DLBCL cells to CAR-T cells in co-culture system by down-regulating the polarization of M2 macrophages
Authors: Deng Qi , Qi Yao , Wang Jia , Li Xin , Mu Juan , Cui Rui
Published: April 2024

The Tumor microenvironment (TME) of relapsed/refractory (R/R) diffuse large B-Cell lymphoma (DLBCL) patients is associated with resistance of DLBCL cells to CD19 CAR-T cells. How to improve TME in DLBCL and improve the efficacy of CAR-T cell therapy remains to be further explored. We observed the sensitivity of HBL-1/U2932 cells pretreated with BTK inhibitors to CAR-T cells with flow cytometry (FCM), then observed the sensitivity of HBL-1 cells extracted from the co-culture system to CAR-T cells. Effect of pretreatment of BTK inhibitors on the substitute activated M2 macrophages was observed with FCM, Real-time PCR and Western blot method. Then the expression consistency of Notch-1 and RBP-J in activated M2 macrophages was observed by siRNA transfection of Notch-1. After substitute activated M2 macrophages and HBL-1 cells were pretreated with ibrutinib/orelabrutinib respectively, the cytotoxicity of CAR-T cells to HBL-1 cells was higher than that of in substitute activated M2 macrophages pretreated with ibrutinib/orelabrutinib group, and higher than that of in HBL-1 cells pretreated with ibrutinib/orelabrutinib group. Pretreatment with BTK inhibitors could down-regulate the expression of CD206 and IL-10 in activated M2 macrophages. Pretreatment with BTK inhibitors down-regulated the expression of Arg-1 and up-regulated the expression of iNOS in activated M2 macrophages. The up-regulation polarization of M2 macrophages by Notch1 agonists could be reversed by BTK inhibitors. Expression of RBP-J protein decreased in substitute activated M2 macrophages by siRNA silencing Notch 1. Pretreatment with BTK inhibitors could down-regulate the polarization of M2 macrophages and reverse the resistance of DLBCL cells which were co-cultured with substitute activated M2 macrophages to CAR-T cells. This effect might be achieved by down-regulating the Notch-RBP-J pathway.
Trustworthy and Self-explanatory Artificial Intelligence for the Classification of Non-Hodgkin Lymphoma by Immunophenotype
Authors: Thrun Michael , Hoffmann Jörg , Krause Stefan , Weit Nicole , Krawitz Peter , Stier Quirin , NEUBAUER Andreas , Brendel Cornelia , Ultsch Alfred
Published: April 2024

Diagnostic immunophenotyping of malignant non-Hodgkin-lymphoma (NHL) by multiparameter flow cytometry (MFC) relies on highly trained physicians. Artificial intelligence (AI) systems have been proposed for this diagnostic task, often requiring more learning examples than are usually available. In contrast, Flow XAI has reduced the number of needed learning data by a factor of 100. It selects and reports diagnostically relevant cell populations and expression patterns in a discernable and clear manner so that immunophenotyping experts can understand the rationale behind the AI’s decisions.
A self-organized and unsupervised view of the complex multidimensional MFC data provides information about the immunophenotypic structures in the data. Flow XAIintegrates human expert knowledge into its decision process. It reports a self-competence estimation for each case and delivers human-understandable explanations for its decisions. Flow XAI outperformed comparable AI systems in qualitative and quantitative assessments. This self-explanatory AI system can be used for real-world AI lymphoma immunophenotyping.
Elucidating the pathway activity and prognostic significance of diverse cell-death patterns in idiopathic pulmonary fibrosis
Authors: Sun Jiazheng , Sun Yalu , Guo Hehua , Nie Yalan , Zhou Sirui , Zeng Yulan
Published: April 2024

Background
Idiopathic pulmonary fibrosis (IPF) is one of the interstitial lung diseases (ILDs) with poor prognosis. Multiple regulated cell death (RCD) pathways are involved in regulating the progression of pulmonary fibrosis at different stages.
Methods
A total of 20 RCD pathways and crucial regulatory genes were collected from available literature. The study initially elucidated the profiling of 20 kinds of RCD pathways in normal and fibrotic lung tissues based on the scRNAseq dataset and bulk-RNAseq dataset. Targets associated with IPF were identified by Mendelian randomization analysis, and univariate Cox regression was used to further identify RCD-related genes significantly associated with overall survival (OS). A combination of 101 distinct machine-learning algorithms was utilized to develop a prognostic signature. In addition, we investigated the relationship between prognostic signature and clinical characteristics.
Results
By integrating scRNAseq data and bulk-RNAseq data, the study initially elucidated the pathway activity associated with distinct RCD patterns in IPF patients. In addition, following detailed research of various RCD patterns, the study developed the CDI signature with 13 genes, which combined with multiple machine learning methods to generate CDI signature has a strong predictive influence on the prognosis of IPF patients. As proven by independent datasets, IPF patients with high CDI had a poorer outcome. From the clinical characteristics, IPF patients with high CDI have impaired lung function. Finally, a nomogram with strong predictive ability was generated by integrating CDI with clinical characteristics.
Conclusion
In summary, we have developed a novel CDI model that effectively forecasts the clinical prognosis of patients with IPF by integrating various cell death patterns.
Educational Resilience among Tausug Indigenous People in Remote Communities: Basis for Policy Formulation
Authors: Talikan Allen I. , Ajan Rozia A. , Mami Wedar S. , Mohammad Abdulla I. , Salapuddin Rufaida S. , Busaňa Maryjoy A. , Radjuni Abubakar J. , Undug Nurjia , Jayani Padzmahal , Samain Wijra
Published: April 2024

This study examined the educational resilience among the Tausug people, an indigenous Muslim group living in the Sulu Archipelago, Philippines. Despite their rich cultural heritage, the Tausug face various challenges in accessing quality education, such as geographic isolation, poverty, cultural barriers, and social conflict. The concept of educational resilience focuses on how individual, familial, community, and systemic factors interact to influence educational achievement. This research investigated how the Tausug way of life, rooted in Islamic tradition and cultural practices, promotes educational resilience. The study employed a descriptive research method, conducting individual unstructured interviews. The participants included different school stakeholders. The data analysis revealed the challenges faced by the Tausug, such as remote locations, limited resources, financial constraints, and traditional gender roles. However, the study also identified coping strategies such as communal support systems, valuing education for improving lives, and aspiring for a better future. The Tausug's resilient spirit is evident in their strong sense of respect for elders, and cultural values on knowledge. These elements create an environment that nurtures learning and provides the necessary support to achieve educational goals. Based on these findings, the study proposes policy recommendations to enhance educational access, including decentralized education with targeted funding and resource sharing, culturally responsive teacher training programs, scholarships and financial aid programs to address financial barriers, addressing geographic isolation through infrastructure development and transportation solutions, culturally sensitive curriculum materials, and integration of local knowledge, as well as community engagement initiatives to encourage parental involvement and establish community learning centers.
Development of a premenstrual syndrome scale for workplaces
Authors: Takenoshita Chihiro , Shimizu Kisho , Iida Miho , Taka Fumiaki , Maeda Eri , Nomura Kyoko
Published: April 2024

We aimed to develop a new screening tool for premenstrual syndrome (PMS) to be used in the workplace. In October 2021, we recruited 3,239 working women with menstruation via an internet research company and asked 47 questions about PMS-related symptoms. Of the participants, 331 women had experienced PMS (10%), and 393 women had taken sick leave because of PMS-associated symptoms. Explanatory factor analyses with maximum likelihood and Promax rotation identified four domains with 27 items, including "Autonomic dysfunction symptoms'' (13 items, Cronbach’s α = 0.93), "Psychiatric symptoms" (6 items, Cronbach’s α = 0.94), "Lack of work efficiency" (5 items, Cronbach’s α = 0.93), and “Abdominal symptoms” (3 items, Cronbach’s α = 0.95). Using a split-half sample for the confirmatory factor analysis, moderately fit model indices for the four-factor solution were confirmed. We also confirmed the developed scale’s criterion validity using existing PMS screening criteria and its concurrent validity through high correlation coefficients with Copenhagen Burnout Inventory scores. The receiver operating characteristic curve yielded a good predictive ability for work absenteeism, including a sensitivity of 78%, a specificity of 57%, and an area under the curve of 0.735. A highly reliable and valid new scale for PMS was developed with efficacy for screening for work absenteeism.
Predictive potential of cuproptosis-related genes in multiple myeloma: Comprehensive analysis based on bone marrow whole-genome sequencing
Authors: Kang Zhongmin , Li Licheng , Huang Yuying , Wang Jishi , Li Mengxing , Li Qinshan
Published: April 2024

Purpose: The primary objective of this study was to identify potential CRGs in patients with MM and develop a predictive model to enhance prognostic outcomes for individuals with MM.
Methods: We leveraged transcriptome sequencing data from patients with MM, combined with clinical information from the TCGA-MMRF dataset and the GSE4581 dataset from the GEO database. Through analysis, we pinpointed three genes—CDKN2A, PDE3B, and UBE2D1 that exhibited a significant association with the prognosis of patients with MM. This association was confirmed through a combination of univariate and multivariate Cox regression analyses. Subsequently, we employed LASSO-Cox regression analysis to construct a risk-prognostic model centered around these three CRGs.
Results: Notably, the model revealed that high-risk patients with MM experienced significantly shorter overall survival times. Intriguingly, We have unveiled a propensity for high-risk patients with MM to develop an immunosuppressive tumor microenvironment. Finally, to substantiate our findings, we conducted in-depth examinations of the expression of these three CRGs at the cellular level using quantitative reverse transcription–polymerase chain reaction and Western blotting.
Conclusion: Our research collectively reveals the molecular scenery in the MM microenvironment through the development of a prognostic model focused on CRGs.
Convolutional Neural Network Applied in Anaerobic Reactors of Domestic Sewage
Authors: Pykosz Leandro Correa , Diogenes Alysson Nunes , Guerios Maura H. S.
Published: April 2024

The need for sustainability within the ETES (sewage treatment stations), to take advantage of the residue and turn it into raw materials, depends on an important step which is the care with the anaerobic reactor variables. Only with care at the beginning of the sewage treatment process will it be possible to ensure a waste that can be used as a raw material for commercial use or in the station itself. To this end, based on monitoring data obtained in scientific work, convolutional neural networks were trained to model and indicate that the use of artificial intelligence in domestic sewage treatment stations was feasible. Data obtained from two scientific papers were grouped in the same ETE, in the same temporal lapse, the data were refined and normalized. In this article, RNA was applied to predict the methane flow (CH4), the model has good estimates for the data sets. The results obtained show that the developed model provides reliable estimates with response variables and shows that the most effective architecture of forecasts was using convolutional networks with a hidden layer with 8 neurons and sigmoid activation function, this configuration was obtained in the greatest convergence in Prediction of methane flow.
Development of a DXA-Based Risk Score for Cardiovascular Outcomes Among Older Adults: The Health, Aging, and Body Composition Study
Authors: Chen Lihui , Wang Xinran , Lin Tian-Ze , Xiang Hao , Liu Hua , Xu Shen , Yue Jirong , Wu Chenkai
Published: April 2024

Cardiovascular disease (CVD) is the leading cause of death worldwide and its risk factors have long been investigating in epidemiological studies. Although the Framingham Risk Score provided an estimate for cardiovascular risk, it did not utilize the body compositions biomarkers. Therefore, our study aims to develop a body composition-based score and incorporate the score into the FRS for better predicting cardiovascular disease among initially well-functioning older adults. 1,882 older adults in the Health, Aging and Body Composition (Health ABC) study were included in our study to screen body composition variables obtained from the Dual-energy X-ray absorptiometry (DXA). We developed the 4-DXA risk score model from the selected variables, refitted the Framingham Risk Score (FRS), incorporated the 4-DXA risk score into the FRS, and compared these developed prediction models. C-statistics were 0.58, 0.62, and 0.63 respectively. Compared to the refit FRS, the net reclassification index and the integrated discrimination index was 0.012 (95% CI: 0.0068–0.018) and 0.12 (95% CI = 0.021, 0.22) for the refit FRS plus the 4-DXA model. Inclusion of body composition indices slightly improved the model performance for predicting CVD. Further research is needed to validate the score accuracy in a higher-risk population.
Cardiorespiratory and Aerobic Demands of Squat Exercise
Authors: Hong Sunghyun , Oh Minsuk , Oh Chang-Geun , Lee Hae-Dong , Suh Sang-Hoon , Park Hyon , Lalande Sophie , Tanaka Hirofumi , Jeon Justin Y.
Published: April 2024

Squatting, a traditional resistance exercise classified as strength training, relies on anaerobic pathways, but its aerobic aspects remain unclear. We examined heart rate and oxygen demand during squats, exploring variations across different strength statuses. It fills gaps in understanding the cardiorespiratory effects of squatting, especially during multiple sets. Twenty-two young healthy resistance trained men (age: 28±4 years) participated. Maximal oxygen consumption (V̇O2max) and 1 repetition maximum (RM) of squat were measured. Participants performed 5 sets of squat exercises at 65% of 1RM for 10 repetitions with 3-min rest intervals. Heart rate and pulmonary gas exchange were measured during the squat exercise. Participants were divided into high strength (HS) and low strength (LS) groups based on a median split of their 1 RM squat values. During 5 sets of squat exercise, oxygen consumption (V̇O2) increased up to 47.8 ± 8.9 ml/kg/min, corresponding to 100.6% of predetermined V̇O2max. The HS group achieved a greater highest point of V̇O2in relation to V̇O2max than the LS group (108.0 vs. 93.7%). During the exercise intervals, V̇O2exceeded V̇CO2, while during the rest intervals, V̇CO2surpassed V̇O2. Our findings suggest that the oxygen demand during squatting is notably substantial, which may vary according to the training status.
Therapeutic Drug Monitoring of Vancomycin in Pediatric Patients: Defining a Therapeutic Drug Window
Authors: Zhang Tao , Yi Jingjing , Cheng Hua , Han Xinyan , Wang Yan , Xie Jiao , Yang Qianting , Hu Sasa , Dong Yalin
Published: April 2024

Background
Methicillin-resistant Staphylococcus aureus (MRSA) infections among children are escalating annually. Vancomycin stands as the frontline therapeutic agent against MRSA infections. However, determining the therapeutic window for vancomycin in pediatric patients remains a challenge.
Methods
This retrospective study collected data from hospitalized children aged 1 month to 18 years, who underwent routine therapeutic drug monitoring for vancomycin. We analyzed the distribution patterns of vancomycin concentrations in these patients. Factors influencing clinical outcomes and adverse reaction (nephrotoxicity) were investigated. ROC analysis was used to establish the therapeutic window for vancomycin in pediatric patients.
Results
A comprehensive dataset encompassing 183 pediatric patients with 330 samples was analyzed. The mean trough concentration (Cmin) of vancomycin was 7.6 ± 5.5 mg/L. 74.3% of patients exhibited concentrations below the conventionally recommended therapeutic window of 10–20 mg/L. Patients responding positively to treatment exhibited significantly higher Cmin values (8.4 ± 5.7 mg/L) compared to those with treatment failure (5.9 ± 4.4 mg/L, P = 0.006). Similarly, patients who developed nephrotoxicity had significantly elevated Cmin levels (17.8 ± 5.3 mg/L) compared to those without nephrotoxicity (6.4 ± 3.9 mg/L, P < 0.001). Both univariate and multivariate logistic regressions revealed that the Cmin of vancomycin was the predictor of both clinical outcomes and adverse reaction. Furthermore, receiver operating characteristic curve analysis pinpointed that Cmin of vancomycin with 5.9 mg/L and 14.8 mg/L associated with clinical effectiveness and safety, respectively.
Conclusion
Referring to the therapeutic window of adults, vancomycin underexposure in pediatrics is serious extremely. Based on our findings, we propose a revised therapeutic window of 5.9–14.8 mg/L for vancomycin in pediatric patients, which could aid in optimizing treatment outcomes and minimizing adverse effects.
Classification of accident prevention practices against unintentional injuries of preschool children at home: Developmental process and associations with other variables in Japanese families
Authors: Kojima Yasuo
Published: April 2024

Background
Preschool children often experience unintentional injuries at home, which are an important public health issue worldwide. In this study, the content and types of accident prevention practices for unintentional injuries of preschool children in families were investigated using a Japanese sample.
Methods
A total of 875 mothers with children between the ages of 6 months and 6 years and 11 months participated in the online survey. Respondents answered the items regarding specific strategies to prevent unintentional injuries at home, temperament and independence of lifestyle habits and behaviors of their child, as well as their parenting attitudes.
Results
Correspondence analysis was conducted based on 26 items of accident prevention practices against unintentional injuries to extract two dimensions (eigenvalues: .286, .062, cumulative contribution rate: 34.8%), and cluster analysis was conducted using Ward's method with the Euclidean distance measure based on the scores of each of these two dimensions, deriving three clusters. The first cluster (n=517) comprised the preventative group which kept objects that could lead to injuries away from children in advance; the second cluster (173 participants) explicitly prevented children from approaching or contacting dangerous places or objects; and the third cluster (185 participants) was attentive to each effort to discourage children's contact with dangerous places. Cluster 1 was more common in the 0-year age group, Cluster 2 in the 1- and 2-year age groups, and Cluster 3 in the 4–6-year age groups. Logistic regression analysis revealed that the more independent the children were regarding lifestyle habits and behavior, the more likely they were to be classified in the second cluster, and the more parents had an encouraging attitude for their children to take on challenges, the more likely they were to be classified in the third cluster.
Conclusion
The process of changing strategies to prevent unintentional injuries indicated that the home space gradually opened up to children as they aged.
Subthalamic and Nigral Stimulation for Freezing of Gait in Parkinson disease: randomized pilot trial
Authors: Artusi Carlo Alberto , Ledda Claudia , Gallo Silvia , Rinaldi Domiziana , Campisi Corrado , Rousseau Vanessa , Thalamas Claire , Barbosa Raquel , Fabienne Ory-Magne , Brefel-Courbon Christine , Rascol Olivier , de Barros Amaury , Harroch Estelle , zibetti maurizio , Rizzone Mario Giorgio , Romagnolo Alberto , Imbalzano Gabriele , Lopiano Leonardo , Houeto Jean Luc , Fabbri Margherita
Published: April 2024

Background
Freezing of gait (FoG) is a debilitating symptom of Parkinson's disease (PD) with limited response to dopaminergic medication and subthalamic deep brain stimulation (STN-DBS). Substantia nigra pars reticulata (SNr) stimulation could improve FoG.
Objectives
To analyze the effect of combined STN-SNr stimulation at different frequencies on FoG.
Methods
We performed a double-blind, cross-over, randomized pilot trial involving STN-DBS treated PD patients with FoG. Participants received: high-frequency (HF) STN-DBS (S), combined HF-STN and SNr stimulation (C1), and combined HF-STN and low-frequency (LF) SNr stimulation (C2), for one month each. The primary endpoint was the score change in the New-Freezing-of-Gait-Questionnaire (NFOG-Q). Secondary analyses were performed on motor complications, axial symptoms, daily living activities, psychiatric symptoms, sleep, and patient preference.
Results
Fifteen patients received at least one combined stimulation. No significant difference in NFOG-Q scores was found between S, C1, and C2; one-third of patients showed a clinically significant improvement (≥ 8 points) with combined stimulations. Motor complications improved significantly with C1 and C2 (C1-S: 3.6 ± 3.8 vs. 4.9 ± 3.8, p = 0.046; C2-S: 2.7 ± 3.1 vs. 4.9 ± 3.8, p = 0.005). 80% of patients preferred the combined STN-SNr stimulation while blinded. All adverse events were manageable.
Conclusions
Our study did not prove a statistically significant improvement in NFOG-Q with STN-SNr stimulation; however, one-third of patients experienced a clinically meaningful FoG improvement, and the majority preferred to maintain STN-SNr stimulation. STN-SNr stimulation was both safe and effective in addressing motor complications and improving sleep quality, highlighting the importance of further exploration into the effects of combined STN-SNr stimulation.
Utility of a Three-dimensional Convolutional Neural Network-based Renal Function Prediction Using Kidney MRI in Chronic Kidney Disease
Authors: Nagawa Keita , Hara Yuki , Inoue Kaiji , Yamagishi Yosuke , Koyama Masahiro , Shimizu Hirokazu , Matsuura Koichiro , Osawa Iichiro , Inoue Tsutomu , Okada Hirokazu , Kobayashi Naoki , Kozawa Eito
Published: April 2024

A three-dimensional convolutional neural network model was developed to predict renal function in patients with chronic kidney disease (CKD) using magnetic resonance imaging (MRI) Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images. Seventy-three patients with severe renal dysfunction (estimated glomerular filtration rate [eGFR] <30 mL/min/1.73 m2, CKD stage G4–5); 172 with moderate renal dysfunction (30≤ eGFR <60 mL/min/1.73 m2, CKD stage G3a/b); and 76 in the control (eGFR ≥60 mL/min/1.73 m2, CKD stage G1–2) groups participated in this study. The model was applied to the right, left, and both kidneys, as well as for each imaging method (T1-weighted IP/OP/WO images). The best performance was obtained when using bilateral kidneys and IP images, with an accuracy of 0.862 ± 0.036. The overall accuracy was better for bilateral kidney models than that for unilateral kidney models. Our deep-learning approach using kidney MRI could apply to the evaluation of renal function in patients with CKD.
Evaluation of environmental radioactivity and heavy metal pollution in mining areas in Malatya (Turkey)
Authors: Kayakökü Halime , Kuluöztürk Muhammed Fatih
Published: April 2024

The radioactivity levels of 226Ra, 232Th, 40K and 137Cs radionuclides were measured in soil samples collected from Hekimhan-Kuluncak mining areas in Turkey using gamma spectrometry with high-purity coaxial Ge detector. In soil samples, the 226Ra, 232Th and 40K concentrations obtained for the S-10 (Bıyıkboğazı) sample and the P15 (Deveci) sample are above the world average limit values. The average Raeq value was calculated as 87.8 Bq/kg. The Raeq values for all soil samples were below the world average value of 370 Bq/kg. Furthermore, the calculated average value of the air-absorbed gamma dose rate from terrestrial gamma radiation was 43.3 nGy/h. The average value obtained for the calculated values of the air absorbed gamma dose rate is lower than the worldwide recommended average value of 60 nGy/h. The average value calculated for the annual effective dose rate is 53.1 µSv/y, which is below the average value of 70 µSv/y. In addition, the mean values for the internal and external hazard indices were 0.31 and 0.28, respectively, which are smaller than the limit value of 1. Based on the results obtained, it can be said that the level of radioactivity in the region cannot cause radiological harm to the health of living organisms. The average excess lifetime cancer risk value for all samples in the study was 0.18×10-3, which is lower than the world average of 0.29×10-3. As a result of heavy metal analysis, the results obtained for Zn, Cr and Cu in soil samples were found to be below the limit values. The results obtained for Ni were below the limit values except for P3 (Çayköy) and P12 (Hasançelebi). All PLI values calculated for the present study are less than 1. This means that there is no pollution in the area under investigation.
Resolving Distal Vessel Occlusions Caused by Migrated Emboli: Outcomes of Modified Stent Retrieval Technique
Authors: Ahn Hong Suk , Park Jung Hyun , Ahn Jun Hyong , Jeon Hong Jun , Cho Byung Moon
Published: April 2024

This study aimed to retrospectively evaluate the safety and effectiveness of a modified stent retrieval technique that controls the unsheathing level of the microcatheter in resolving distal vessel occlusions caused by migrated emboli. From January 2016 to February 2022, the modified stent retrieval technique was applied to 24 of 445 patients with acute large vessel occlusion strokes in the anterior circulation, featuring secondary embolus migration into M2, M3, A2, or A3 branches. The procedure included radiopaque stent retrieval systems, including Trevo XP 4 x 20 mm and Solitaire Platinum 4 x 20 mm. Coverage range was adjusted through partial re-sheathing of the delivery microcatheter after full unsheathing. After recanalizing the primary large vessel occlusion, secondary distal vessel occlusion occurred in 12/6/4/2 patients in the M2/M3/A2/A3 branches, respectively (time from puncture to primary large vessel occlusion recanalization: 45.5 ± 17 min). The modified TICI score was 2a and 2b in 8 and 16 patients, respectively, for primary large vessel occlusion. The one-pass rate of secondary distal vessel occlusions was 70.8%, and 23 of 24 patients achieved a final recanalization rate of at least TICI 2c at the migrated distal vessel occlusion (mean duration: 23.2 ± 14 min) without significant complications. At 3 months, 16 patients achieved favorable functional outcome (mRS, 0–2). Thus, this modified technique was simple and effective, demonstrating both safety and efficacy in resolving distal vessel occlusion caused by migrated emboli.
Coronary artery dilatation associated with streptococcus pneumoniae infection misdiagnosed as coronary artery aneurysm: A case report
Authors: Zhao Li , Yang Lixia , Duan Hongyu , Liu Xiaoliang , Zhou Kaiyu , Shao Shuran , Wang Chuan
Published: April 2024

Kawasaki disease (KD) is the leading cause of coronary artery dilatation (CAD) in children. As clinicians tend to have an inadequate understanding of other febrile diseases that can caused CAD, febrile patients with CAD are easily misdiagnosed as KD and treated accordingly. Therefore, improving the understanding of CAD which is not caused by KD has important clinical significance for avoiding misdiagnosis as KD and improving the prognosis of patients. Although rare, various infections and inflammatory diseases can cause CAD. However, there are no reports of CAD caused by S. pneumoniae infection. We firstly report a case of invasive S. pneumoniae systemic infection and meningoencephalitis that was misdiagnosed as KD due to fever and CAD at the beginning of the disease, resulting in delayed treatment and serious neurological complications. These findings highlight the possibility of CAD due to non-KD causes and suggest that for febrile children with CAD, invasive S. pneumoniae infection should be considered as differential diagnosis. Furthermore, this case also has important clinical value in improving clinicians’ understanding of the involvement of S. pneumoniae infection in the cardiovascular system.
Evaluating Frontoparietal Network Topography for Diagnostic Markers of Alzheimer’s Disease
Authors: Rogers Bayard
Published: April 2024

Numerous prospective biomarkers are being studied for their ability to diagnose various stages of Alzheimer’s disease (AD). High-density electroencephalogram (EEG) methods show promise as an accurate, economical, non-invasive approach to measuring the electrical potentials of brains associated with AD. Event-related potentials (ERPs) may serve as clinically useful biomarkers of AD. Through analysis of secondary data, the present study examined the performance and distribution of N4/P6 ERPs across the frontoparietal network (FPN) using EEG topographic mapping. ERP measures and memory as a function of reaction time (RT) were compared between a group of (n = 63) mild untreated AD patients and a control group of (n = 73) healthy age-matched adults. Based on the literature presented, it was expected that healthy controls would outperform patients in peak amplitude and mean component latency across three parameters of memory when measured at optimal N4 (frontal) and P6 (parietal) locations. It was also predicted that the control group would exhibit neural cohesion through FPN integration during cross-modal tasks, thus demonstrating healthy cognitive functioning consistent with older healthy adults. By targeting select frontal and parietal EEG reference channels based on N4/P6 component time windows and positivity, our findings demonstrated statistically significant group variations between controls and patients in N4/P6 peak amplitudes and latencies during cross-modal testing. Our results also support that the N4 ERP might be stronger than its P6 counterpart as a possible candidate biomarker. We conclude through topographic mapping that FPN integration occurs in healthy controls but is absent in AD patients during cross-modal memory tasks.
Optimization for Turbomachinery Performance Using Inverse Design Method: Integrating Cascade System and Flow Characteristics
Authors: Ke Zhifang , Wei Wei , Guo Meng , Liu Cheng , Yan Qingdong
Published: April 2024

Conventional optimization approaches for torque converters often rely on iterative trial-and-error methods, resulting in inherent limitations and uncertainties. To address these challenges and achieve performance optimization based on flow characteristics, this study proposes an inverse design method for turbomachinery. Introducing a novel index for blade loads, denoted as rvt , enables simultaneous optimization for both the cascade system and the flow field. Furthermore, a pump’s driven loads are introduced for the directional design of the blade load characteristics of high-capacity torque converters. Building upon the inverse design method, a directional optimization strategy is developed to enhance the pump capacity or torque ratio, guided by the concept of driven loads. The inverse design method allows for the targeted design of blade shapes while ensuring optimal blade shape and flow field distribution. The design results and the prototype demonstrate a significant 8.28% increase in pump capacity and a notable 4.9% reduction in the magnitude of blade loads in the internal flow field. These findings confirm the efficacy of the inverse design method in achieving directional enhancement of pump capacity while optimizing the smoothness of the internal flow field.
Ethical implications related to processing of personal data and artificial intelligence in humanitarian crises: A scoping review
Authors: Kreutzer Tino , Orbinski James , Appel Lora , An Aijun , Vinck Patrick
Published: April 2024

Background
Humanitarian organizations are rapidly expanding their use of data in the pursuit of operational gains in effectiveness and efficiency. Ethical risks, particularly from artificial intelligence (AI) data processing, are increasingly recognized yet inadequately addressed by current humanitarian data protection guidelines. This study reports on a scoping review that maps the range of ethical issues that have been raised in the academic literature regarding data processing of people affected by humanitarian crises.
Methods
We systematically searched databases to identify peer-reviewed studies published since 2010. Data and findings were standardized, grouping ethical issues into the value categories of autonomy, beneficence, non-maleficence, and justice. The study protocol followed Arksey and O’Malley’s approach and PRISMA reporting guidelines.
Results
We identified 8,387 unique records and retained 98 relevant studies. One in four (n = 25) discussed technologies related to artificial intelligence. Seven studies included an author from a lower-middle income country while none included an author from a low-income country. We identified 22 ethical issues which were then grouped along the four ethical value categories of autonomy, beneficence, non-maleficence, and justice. Slightly over half of included studies (n = 52) identified ethical issues based on real-world examples. The most-cited ethical issue (n = 74) was a concern for privacy in cases where personal or sensitive data might be inadvertently shared with third parties. The technologies most frequently discussed in these studies included social media, crowdsourcing, and mapping tools.
Conclusions
Studies highlight significant concerns that data processing in humanitarian contexts can cause additional harm, may not provide direct benefits, may limit affected populations’ autonomy, and can lead to the unfair distribution of scarce resources. The anticipated increase in AI tool deployment for humanitarian assistance amplifies these concerns. Urgent development of specific, comprehensive guidelines, training, and auditing methods are required to address these ethical challenges. Moreover, empirical research from low and middle-income countries, disproportionally affected by humanitarian crises, is vital to ensure inclusive and diverse perspectives. This research should focus on the ethical implications of both emerging AI systems as well as established humanitarian data management practices.
Trial registration:
Not applicable.