bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lung pneumonia severity scoring in chest X-ray images using transformers
Authors: Slika Bouthaina , Dornaika Fadi , Merdji Hamid , Hammoudi Karim 
Published: April 2024

Abstract
To create robust and adaptable methods for lung pneumonia diagnosis and the assessment of its severity using chest X-rays (CXR), access to well-curated, extensive datasets is crucial. Many current severity quantification approaches require resource-intensive training for optimal results. Healthcare practitioners require efficient computational tools to swiftly identify COVID-19 cases and predict the severity of the condition. In this research, we introduce a novel image augmentation scheme as well as a neural network model founded on Vision Transformers (ViT) with a small number of trainable parameters for quantifying COVID-19 severity and other lung diseases. Our method, named Vision Transformer Regressor Infection Prediction (ViTReg-IP), leverages a ViT architecture and a regression head. To assess the model’s adaptability, we evaluate its performance on diverse chest radiograph datasets from various open sources. We conduct a comparative analysis against several competing deep learning methods. Our results achieved a minimum Mean Absolute Error (MAE) of 0.569 and 0.512 and a maximum Pearson Correlation Coefficient (PC) of 0.923 and 0.855 for the geographic extent score and the lung opacity score, respectively, when the CXRs from the RALO dataset were used in training. The experimental results reveal that our model delivers exceptional performance in severity quantification while maintaining robust generalizability, all with relatively modest computational requirements. The source codes used in our work are publicly available at https://github.com/bouthainas/ViTReg-IP.

Graphical abstract
Knowledge, Attitudes and Practices of Chagas a Neglected Tropical Disease in Rural Communities of the Colombian Caribbean, CHAGCOV Study
Authors: Ochoa-Diaz Margarita M , Orozco-Garcia Daniela , Fernandez-Vasquez Ronald S. , Eyes-Escalante Melisa 
Published: April 2024

Abstract
Purpose
Chagas disease (CD) a Neglected Tropical Diseases is an important public health issue in countries where is still endemic, included in the Sustainable Development Goals (SDG). Traditionally restricted to rural areas with diverse routes of transmissions from vectorial to oral with acute manifestations but being more common diagnosed in chronic stages. The aim of this investigation was to characterize the Knowledge, Attitudes and Practices (KAP) related to Chagas disease (CD) in two rural settlements of the Colombian Caribbean with previous records of the disease and/or the parasite.

Methods
A cross-sectional descriptive study was made in two rural settlements in Colombia and surveillance instrument was developed to measure Knowledge, Attitudes and Practices (KAP) related to Chagas disease (CD).

Results
In a population with > 60% women and access to social security around 66.5%; 81,6% were homeowners with access to water and electricity > 90% but only 9% of sewerage. The level of knowledge about CD was around 62% but lack of specificity about comprehension of transmission routes (74,6%), and symptoms (85,3%) were found; concluding that 86% of the surveyed sample had very poor level of knowledge about the disease despite preventive campaigns carried out in the two communities studied.

Conclusions
Despite of a low frequency of CD in this Caribbean areas, the presence of vector, risk factors plus poor level of knowledge about the disease justify that public health intervention strategies should be implemented and monitored over time to maintain uninterrupted surveillance of Chagas Disease.
Population Genetics of Culex tritaeniorhynchus (Diptera: Culicidae) in Türkiye
Authors: Bursali Fatma , Simsek Fatih Mehmet 
Published: April 2024

Abstract
Purpose
Mosquitoes are important vectors of pathogens that can affect humans and animals. Culex tritaeniorhynchus is an important vector of arboviruses such as Japanese encephalitis virus, West Nile virus among various human and animal communities. These diseases are of major public health concern and can have huge economic and health burdens in prevalent countries. Although populations of this important mosquito species have been detected in the Mediterranean and Aegean regions of Türkiye; little is known about its population structure. Our study is to examine the population genetics and genetic composition of Cx. tritaeniorhynchus mosquitoes collected from several localities using cytochrome oxidase subunit I (COI) and the NADH dehydrogenase subunit 5 genes (ND5). This is the first extensive study of Cx. tritaeniorhynchus in the mainland Türkiye with sampling spanning many of provinces.

Methods
In this study, DNA extraction, amplification of mitochondrial COI and ND5 genes and population genetic analyses were performed on ten geographic populations of Culex tritaeniorhynchus in the Aegean and Mediterranean region of Türkiye.

Results
Between 2019 and 2020, 96 samples were collected from 10 geographic populations in the Aegean and Mediterranean regions; they were molecularly analyzed and 139 sequences (50 sequence for COI and 89 sequence for ND5) were used to determine the population structure and genetic diversity. For ND5 gene region, the samples produced 24 haplotypes derived from 15 variable sites and for COI gene region, 43 haplotypes were derived from 17 variable sites. The haplotype for both gene regions was higher than nucleotide diversity. Haplotype phylogeny revealed two groups present in all populations. AMOVA test results show that the geographical populations were the same for all gene regions. Results suggest that Cx. tritaeniorhynchus is a native population in Türkiye, the species is progressing towards speciation and there is no genetic differentiation between provinces and regions.

Conclusion
This study provides useful information on the molecular identifcation and genetic diversity of Cx. tritaeniorhynchus; these results are important to improve mosquito control programs.
Teaching quality in kindergarten: professional development and quality of adaptive learning support enhances mathematical competency
Authors: Dunekacke Simone , Wullschleger Andrea , Grob Urs , Heinze Aiso , Lindmeier Anke , Vogt Franziska , Geeler Susanne Kuratli , Leuchter Miriam , Meier-Wyder Anuschka , Seemann Selma , Opitz Elisabeth Moser 
Published: April 2024

AbstractAdaptive learning support provided by kindergarten teachers before and after (macro-adaptive learning support) as well as during mathematical learning activities (micro-adaptive learning support) is a cross-cutting concept of teaching quality. Effective adaptive learning support enhances children’s learning. However, providing it is challenging and teachers need professional development (PD) to improve the quality of their support. This study investigates the mediating role of teaching quality between PD programs for kindergarten teachers and the development of children’s mathematical competency. 122 kindergarten teachers and their 825 pupils participated in the study. The teachers were randomly assigned to three groups. Two groups attended PD sessions designed to foster either macro- or micro-adaptive learning support. The third was the materials-only control group. The data was analyzed using a self-developed rating instrument focusing on generic and domain-specific elements of teaching quality related to macro- and micro-adaptive learning support. The multilevel latent change model analysis revealed that the PD programs had positive and significant effects on the teaching quality of kindergarten teachers. A significant positive relationship was also found between micro-adaptive learning support and changes in children’s mathematical competency. However, an indirect effect of teaching quality could not be detected, and the PD programs did not have a total effect on children’s mathematical competency. The study reinforces the importance of PD that specifically targets macro- and micro-adaptive learning support for kindergarten teachers. The mediation between PD and mathematical competency development requires further investigation.
Epidemiological analysis to identify predictors of X-linked hypophosphatemia (XLH) diagnosis in an Italian pediatric population: the EPIX project
Authors: Crisafulli Salvatore , Ingrasciotta Ylenia , Vitturi Giacomo , Fontana Andrea , L’Abbate Luca , Alessi Ylenia , Ferraù Francesco , Cantarutti Luigi , Lazzerini Debora , Cannavò Salvatore , Trifirò Gianluca 
Published: April 2024

Abstract
Purpose
X-linked hypophosphatemia (XLH) is a rare multi-systemic disease characterized by low plasma phosphate levels. The aim of this study was to investigate the annual XLH prevalence and internally evaluate predictive algorithms’ application performance for the early diagnosis of XLH.

Methods
The PediaNet database, containing data on more than 400,000 children aged up to 14 years, was used to identify a cohort of XLH patients, which were matched with up to 10 controls by date of birth and gender. The annual prevalence of XLH cases per 100,000 patients registered in PediaNet database was estimated. To identify possible predictors associated with XLH diagnosis, a logistic regression model and two machine learning algorithms were applied. Predictive analyses were separately carried out including patients with at least 1 or 2 years of database history in PediaNet.

Results
Among 431,021 patients registered in the PediaNet database between 2007–2020, a total of 12 cases were identified with a mean annual prevalence of 1.78 cases per 100,000 patients registered in PediaNet database. Overall, 8 cases and 60 matched controls were included in the analysis. The random forest algorithm achieved the highest area under the receiver operating characteristic curve (AUC) value both in the one-year prior ID (AUC = 0.99, 95% CI = 0.99–1.00) and the two-year prior ID (AUC = 1.00, 95% CI = 1.00–1.00) analysis. Overall, the XLH predictors selected by the three predictive methods were: the number of vitamin D prescriptions, the number of recorded diagnoses of acute respiratory infections, the number of prescriptions of antihistamine for systemic use, the number of prescriptions of X-ray of the lower limbs and pelvis and the number of allergology visits.

Conclusion
Findings showed that data-driven machine learning models may play a prominent role for the prediction of the diagnosis of rare diseases such as XLH.
Blood vessel organoids generated by base editing and harboring single nucleotide variation in Notch3 effectively recapitulate CADASIL-related pathogenesis
Authors: Ahn Yujin , An Ju-Hyun , Yang Hae-Jun , Lee Wi-Jae , Lee Sang-Hee , Park Young-Ho , Lee Jong-Hee , Lee Hong J. , Lee Seung Hwan , Kim Sun-Uk 
Published: April 2024

AbstractHuman blood vessel organoids (hBVOs) offer a promising platform for investigating vascular diseases and identifying therapeutic targets. In this study, we focused on in vitro modeling and therapeutic target finding of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), the most common form of hereditary stroke disorder caused by mutations in the NOTCH3 gene. Despite the identification of these mutations, the underlying pathological mechanism is elusive, and effective therapeutic approaches are lacking. CADASIL primarily affects the blood vessels in the brain, leading to ischemic strokes, migraines, and dementia. By employing CRISPR/Cas9 base-editing technology, we generated human induced pluripotent stem cells (hiPSCs) carrying Notch3 mutations. These mutant hiPSCs were differentiated into hBVOs. The NOTCH3 mutated hBVOs exhibited CADASIL-like pathology, characterized by a reduced vessel diameter and degeneration of mural cells. Furthermore, we observed an accumulation of Notch3 extracellular domain (Notch3ECD), increased apoptosis, and cytoskeletal alterations in the NOTCH3 mutant hBVOs. Notably, treatment with ROCK inhibitors partially restored the disconnection between endothelial cells and mural cells in the mutant hBVOs. These findings shed light on the pathogenesis of CADASIL and highlight the potential of hBVOs for studying and developing therapeutic interventions for this debilitating human vascular disorder.
Network analysis in peace and state building: revealing power elites
Authors: Luna-Pla Issa 
Published: April 2024

Abstract
This paper examines the potential role of network analysis in understanding the powerful elites that pose a significant threat to peace and state-building within post-conflict contexts. This paper makes a threefold contribution. First, it identifies a caveat in the scholarship surrounding international interventions, shedding light on shortcomings in their design and implementation strategies, and elucidating the influence these elites wield in the political and economic realms. Next, it delineates the essentials of the network analysis approach, addressing the information and data requirements and limitations inherent in its application in conflict environments. Finally, the paper provides valuable insights gleaned from the international operation in Guatemala known as the International Commission for Impunity in Guatemala, which specifically targeted illicit networks. The argument asserts that network analysis functions as a dual-purpose tool—serving as both a descriptive instrument to reveal, identify, and address the root causes of conflict and a predictive tool to enhance peace agreement implementation and improve decision-making. Simultaneously, it underscores the challenge of data analysis and translating network interventions into tangible real-life consequences for long-lasting results.
Understanding, diagnosing, and treating pancreatic cancer from the perspective of telomeres and telomerase
Authors: Shou Songting , Li Yuanliang , Chen Jiaqin , Zhang Xing , Zhang Chuanlong , Jiang Xiaochen , Liu Fudong , Yi Li , Zhang Xiyuan , Geer En , Pu Zhenqing , Pang Bo 
Published: April 2024

AbstractTelomerase is associated with cellular aging, and its presence limits cellular lifespan. Telomerase by preventing telomere shortening can extend the number of cell divisions for cancer cells. In adult pancreatic cells, telomeres gradually shorten, while in precancerous lesions of cancer, telomeres in cells are usually significantly shortened. At this time, telomerase is still in an inactive state, and it is not until before and after the onset of cancer that telomerase is reactivated, causing cancer cells to proliferate. Methylation of the telomerase reverse transcriptase (TERT) promoter and regulation of telomerase by lactate dehydrogenase B (LDHB) is the mechanism of telomerase reactivation in pancreatic cancer. Understanding the role of telomeres and telomerase in pancreatic cancer will help to diagnose and initiate targeted therapy as early as possible. This article reviews the role of telomeres and telomerase as biomarkers in the development of pancreatic cancer and the progress of research on telomeres and telomerase as targets for therapeutic intervention.
Vision transformer to differentiate between benign and malignant slices in 18F-FDG PET/CT
Authors: Nishigaki Daiki , Suzuki Yuki , Watabe Tadashi , Katayama Daisuke , Kato Hiroki , Wataya Tomohiro , Kita Kosuke , Sato Junya , Tomiyama Noriyuki , Kido Shoji 
Published: April 2024

AbstractFluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is widely used for the detection, diagnosis, and clinical decision-making in oncological diseases. However, in daily medical practice, it is often difficult to make clinical decisions because of physiological FDG uptake or cancers with poor FDG uptake. False negative clinical diagnoses of malignant lesions are critical issues that require attention. In this study, Vision Transformer (ViT) was used to automatically classify 18F-FDG PET/CT slices as benign or malignant. This retrospective study included 18F-FDG PET/CT data of 207 (143 malignant and 64 benign) patients from a medical institute to train and test our models. The ViT model achieved an area under the receiver operating characteristic curve (AUC) of 0.90 [95% CI 0.89, 0.91], which was superior to the baseline Convolutional Neural Network (CNN) models (EfficientNet, 0.87 [95% CI 0.86, 0.88], P < 0.001; DenseNet, 0.87 [95% CI 0.86, 0.88], P < 0.001). Even when FDG uptake was low, ViT produced an AUC of 0.81 [95% CI 0.77, 0.85], which was higher than that of the CNN (DenseNet, 0.65 [95% CI 0.59, 0.70], P < 0.001). We demonstrated the clinical value of ViT by showing its sensitive analysis of easy-to-miss cases of oncological diseases.
Deep learning assists in acute leukemia detection and cell classification via flow cytometry using the acute leukemia orientation tube
Authors: Cheng Fu-Ming , Lo Shih-Chang , Lin Ching-Chan , Lo Wen-Jyi , Chien Shang-Yu , Sun Ting-Hsuan , Hsu Kai-Cheng 
Published: April 2024

AbstractThis study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to classify either physiological or pathological cells. Utilizing an acute leukemia orientation tube (ALOT), one of the protocols of Euroflow, flow cytometry efficiently identifies various forms of acute leukemia. However, the analysis of flow cytometry can be time-consuming work. This retrospective study included 241 patients who underwent flow cytometry examination using ALOT between 2017 and 2022. The collected flow cytometry data were used to train an artificial intelligence using deep learning. The trained AI demonstrated a 94.6% sensitivity in detecting acute myeloid leukemia (AML) patients and a 98.2% sensitivity for B-lymphoblastic leukemia (B-ALL) patients. The sensitivities of physiological cells were at least 80%, with variable performance for pathological cells. In conclusion, the AI, trained with ResNet-50 and EverFlow, shows promising results in identifying patients with AML and B-ALL, as well as classifying physiological cells.
Temporal and spatial distribution of polycyclic aromatic hydrocarbons (PAHs) in the Danube River in Hungary
Authors: Grmasha Ruqayah Ali , Stenger-Kovács Csilla , Al-sareji Osamah J. , Al-Juboori Raed A. , Meiczinger Mónika , Andredaki Manolia , Idowu Ibijoke A. , Majdi Hasan Sh. , Hashim Khalid , Al-Ansari Nadhir 
Published: April 2024

AbstractThe Danube is a significant transboundary river on a global scale, with several tributaries. The effluents from industrial operations and wastewater treatment plants have an impact on the river's aquatic ecosystem. These discharges provide a significant threat to aquatic life by deteriorating the quality of water and sediment. Hence, a total of 16 Polycyclic Aromatic Hydrocarbons (PAHs) compounds were analyzed at six locations along the river, covering a period of 12 months. The objective was to explore the temporal and spatial fluctuations of these chemicals in both water and sediment. The study revealed a significant fluctuation in the concentration of PAHs in water throughout the year, with levels ranging from 224.8 ng/L during the summer to 365.8 ng/L during the winter. Similarly, the concentration of PAHs in sediment samples varied from 316.7 ng/g in dry weight during the summer to 422.9 ng/g in dry weight during the winter. According to the Europe Drinking Water Directive, the levels of PAHs exceeded the permitted limit of 100 ng/L, resulting in a 124.8% rise in summer and a 265.8% increase in winter. The results suggest that the potential human-caused sources of PAHs were mostly derived from pyrolytic and pyrogenic processes, with pyrogenic sources being more dominant. Assessment of sediment quality standards (SQGs) showed that the levels of PAHs in sediments were below the Effect Range Low (ERL), except for acenaphthylene (Acy) and fluorene (Fl) concentrations. This suggests that there could be occasional biological consequences. The cumulative Individual Lifetime Cancer Risk (ILCR) exceeds 1/104 for both adults and children in all sites.
Impact of center volume on in-hospital mortality in adult patients with out‑of‑hospital cardiac arrest resuscitated using extracorporeal cardiopulmonary resuscitation: a secondary analysis of the SAVE-J II study
Authors: Misumi Kayo , Hagiwara Yoshihiro , Kimura Takuya , Hifumi Toru , Inoue Akihiko , Sakamoto Tetsuya , Kuroda Yasuhiro , Ogura Takayuki ,   the SAVE-J II. study group, Sawano Hirotaka , Egawa Yuko , Kato Shunichi , Sugiyama Kazuhiro , Bunya Naofumi , Kasai Takehiko , Ijuin Shinichi , Nakayama Shinichi , Kanda Jun , Kanou Seiya , Takiguchi Toru , Yokobori Shoji , Takada Hiroaki , Inoue Kazushige , Takeuchi Ichiro , Honzawa Hiroshi , Kobayashi Makoto , Hamagami Tomohiro , Takayama Wataru , Otomo Yasuhiro , Maekawa Kunihiko , Shimizu Takafumi , Nara Satoshi , Nasu Michitaka , Takahashi Kuniko , Fukuda Reo , Shiraishi Shinichiro , Zushi Ryosuke , Otani Norio , Kikuchi Migaku , Watanabe Kazuhiro , Nakagami Takuo , Shoko Tomohisa , Kitamura Nobuya , Otani Takayuki , Matsuoka Yoshinori , Sakuraya Masaaki , Arimoto Hideki , Homma Koichiro , Naito Hiromichi , Nakao Shunichiro , Okazaki Tomoya , Tahara Yoshio , Okamoto Hiroshi , Kunikata Jun , Yokoi Hideto 
Published: April 2024

AbstractRecently, patients with out-of-hospital cardiac arrest (OHCA) refractory to conventional resuscitation have started undergoing extracorporeal cardiopulmonary resuscitation (ECPR). However, the mortality rate of these patients remains high. This study aimed to clarify whether a center ECPR volume was associated with the survival rates of adult patients with OHCA resuscitated using ECPR. This was a secondary analysis of a retrospective multicenter registry study, the SAVE-J II study, involving 36 participating institutions in Japan. Centers were divided into three groups according to the tertiles of the annual average number of patients undergoing ECPR: high-volume (≥ 21 sessions per year), medium-volume (11–20 sessions per year), or low-volume (< 11 sessions per year). The primary outcome was survival rate at the time of discharge. Patient characteristics and outcomes were compared among the three groups. Moreover, a multivariable-adjusted logistic regression model was applied to study the impact of center ECPR volume. A total of 1740 patients were included in this study. The center ECPR volume was strongly associated with survival rate at the time of discharge; furthermore, survival rate was best in high-volume compared with medium- and low-volume centers (33.4%, 24.1%, and 26.8%, respectively; P = 0.001). After adjusting for patient characteristics, undergoing ECPR at high-volume centers was associated with an increased likelihood of survival compared to middle- (adjusted odds ratio 0.657; P = 0.003) and low-volume centers (adjusted odds ratio 0.983; P = 0.006). The annual number of ECPR sessions was associated with favorable survival rates and lower complication rates of the ECPR procedure.Clinical trial registration: https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000041577 (unique identifier: UMIN000036490).