bluuebunny/crossref_metadata_2025_split huggingface dataset:
A psychometric assessment of a novel scale for evaluating vaccination attitudes amidst a major public health crisis
Authors: Cheng Linan , Kong Jianhui , Xie Xiaofeng , Zhang Fengying 
Published: May 2024

AbstractDespite abundant scientific evidence supporting immunization benefits, vaccine hesitancy remains a significant global health concern, particularly during public health crises. Exploring public attitudes towards vaccination is crucial. This study aimed to develop and validate a tailored Public Vaccination Attitudes Scale specifically under the unique circumstances of a public health crisis. A psychometric evaluation was conducted using a cross-sectional study during the peak of a major public health crisis. The scale was developed and its psychometric properties validated using three approaches: (1) generating the item pool through literature research and focus group discussions; (2) assessing the items through expert consultation; and (3) evaluating construct validity, content validity, and internal consistency reliability through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Data from a total of 3921 respondents were randomly divided into two subsets, one for EFA (n = 1935) and the other for CFA (n = 1986). A 22-item draft scale with five factors was created after literature research and focus group discussion. The content validity of this scale ranged between 0.88 and 1.00. EFA showed a 17-item scale with four factors (Cronbach’s α > 0.7) accounting for 68.044% of the total variance. CFA showed that the values of the fit indices, including convergent validity and discriminant validity, were excellent or acceptable. The overall Cronbach’s α was 0.874, and each factor ranged from 0.726 to 0.885. This study introduces a valuable tool for assessing vaccination attitudes during public health crises, aiding researchers, policymakers, and nurses in combating vaccine hesitancy. Emphasizing the importance of fostering vaccine acceptance, it enhances disease control during emergencies, contributing to the knowledge needed for more effective public health strategies and crisis responses
SDPR expression in human trabecular meshwork and its potential role in racial disparities of glaucoma
Authors: Shui Ying-Bo , Liu Ying , Huang Andrew J. W. , Siegfried Carla J. 
Published: May 2024

AbstractIn order to identify how differential gene expression in the trabecular meshwork (TM) contributes to racial disparities of caveolar protein expression, TM dysfunction and development of primary open angle glaucoma (POAG), RNA sequencing was performed to compare TM tissue obtained from White and Black POAG surgical (trabeculectomy) specimens. Healthy donor TM tissue from White and Black donors was analyzed by PCR, qPCR, immunohistochemistry staining, and Western blot to evaluate SDPR (serum deprivation protein response; Cavin 2) and CAV1/CAV2 (Caveolin 1/Caveolin 2). Standard transmission electron microscopy (TEM) and immunogold labeled studies were performed. RNA sequencing demonstrated reduced SDPR expression in TM from Black vs White POAG patients’ surgical specimens, with no significant expression differences in other caveolae-associated genes, confirmed by qPCR analysis. No racial differences in SDPR gene expression were noted in healthy donor tissue by PCR analysis, but there was greater expression as compared to specimens from patients with glaucoma. Analysis of SDPR protein expression confirmed specific expression in the TM regions, but not in adjacent tissues. TEM studies of TM specimens from healthy donors did not demonstrate any racial differences in caveolar morphology, but a significant reduction of caveolae with normal morphology and immuno-gold staining of SDPR were noted in glaucomatous TM as compared to TM from healthy donors. Linkage of SDPR expression levels in TM, POAG development, and caveolar ultrastructural morphology may provide the basis for a novel pathway of exploration of the pathologic mechanisms of glaucoma. Differential gene expression of SDPR in TM from Black vs White subjects with glaucoma may further our understanding of the important public health implications of the racial disparities of this blinding disease.
Examining a 12-year experience within Kazakhstan’s national heart transplantation program
Authors: Semenova Yuliya , Shaisultanova Saule , Beyembetova Altynay , Asanova Aruzhan , Sailybayeva Aliya , Novikova Svetlana , Myrzakhmetova Gulzhan , Pya Yuriy 
Published: May 2024

AbstractKazakhstan has one of the lowest heart transplantation (HTx) rates globally, but there are no studies evaluating the outcomes of HTx. This study aimed to provide a comprehensive analysis of the national HTx program over a 12-year period (2012–2023). Survival analysis of the national HTx cohort was conducted using life tables, Kaplan‒Meier curves, and Cox regression methods. Time series analysis was applied to analyze historical trends in HTx per million population (pmp) and to make future projections until 2030. The number of patients awaiting HTx in Kazakhstan was evaluated with a regional breakdown. The pmp rates of HTx ranged from 0.06 to 1.08, with no discernible increasing trend. Survival analysis revealed a rapid decrease in the first year after HTx, reaching 77.0% at 379 days, with an overall survival rate of 58.1% at the end of the follow-up period. Among the various factors analyzed, recipient blood levels of creatinine and total bilirubin before surgery, as well as the presence of infection or sepsis and the use of ECMO after surgery, were found to be significant contributors to the survival of HTx patients. There is a need for public health action to improve the HTx programme.
High histone crotonylation modification in bovine fibroblasts promotes cell proliferation and the developmental efficiency of preimplantation nuclear transfer embryos
Authors: Zhao Xiaoyu , Du Mengxin , Wu Shanshan , Du Zhiwen , Liu Shuqin , Yang Lei , Ma Haoran , Zhang Liguo , Song Lishuang , Bai Chunling , Su Guanghua , Li Guangpeng 
Published: May 2024

AbstractLysine crotonylation (Kcr) is a recently discovered histone acylation modification that is closely associated with gene expression, cell proliferation, and the maintenance of stem cell pluripotency and indicates the transcriptional activity of genes and the regulation of various biological processes. During cell culture, the introduction of exogenous croconic acid disodium salt (Nacr) has been shown to modulate intracellular Kcr levels. Although research on Kcr has increased, its role in cell growth and proliferation and its potential regulatory mechanisms remain unclear compared to those of histone methylation and acetylation. Our investigation demonstrated that the addition of 5 mM Nacr to cultured bovine fibroblasts increased the expression of genes associated with Kcr modification, ultimately promoting cell growth and stimulating cell proliferation. Somatic cell nuclear transfer of donor cells cultured in 5 mM Nacr resulted in 38.1% blastocyst development, which was significantly greater than that in the control group (25.2%). This research is important for elucidating the crotonylation modification mechanism in fibroblast proliferation to promote the efficacy of somatic cell nuclear transfer.
Transcription factor 4 promotes increased corneal endothelial cellular migration by altering microtubules in Fuchs endothelial corneal dystrophy
Authors: Yan Judy , Mehta Shanti , Patel Keya , Dhupar Narisa , Little Ness , Ong Tone Stephan 
Published: May 2024

AbstractFuchs endothelial corneal dystrophy (FECD) is a complex corneal disease characterized by the progressive decline and morphological changes of corneal endothelial cells (CECs) that leads to corneal edema and vision loss. The most common mutation in FECD is an intronic CTG repeat expansion in transcription factor 4 (TCF4) that leads to its altered expression. Corneal endothelial wound healing occurs primarily through cell enlargement and migration, and FECD CECs have been shown to display increased migration speeds. In this study, we aim to determine whether TCF4 can promote cellular migration in FECD CECs. We generated stable CEC lines derived from FECD patients that overexpressed different TCF4 isoforms and investigated epithelial-to-mesenchymal (EMT) expression, morphological analysis and cellular migration speeds. We found that full length TCF4-B isoform overexpression promotes cellular migration in FECD CECs in an EMT-independent manner. RNA-sequencing identified several pathways including the negative regulation of microtubules, withTUBB4A(tubulin beta 4A class IVa) as the top upregulated gene. TUBB4A expression was increased in FECD ex vivo specimens, and there was altered expression of cytoskeleton proteins, tubulin and actin, compared to normal healthy donor ex vivo specimens. Additionally, there was increased acetylation and detyrosination of microtubules in FECD supporting that microtubule stability is altered in FECD and could promote cellular migration. Future studies could be aimed at investigating if targeting the cytoskeleton and microtubules would have therapeutic potential for FECD by promoting cellular migration and regeneration.
Sync fast and solve things—best practices for responsible digital health
Authors: Landers Constantin , Blasimme Alessandro , Vayena Effy 
Published: May 2024

AbstractDigital health innovation is expected to transform healthcare, but it also generates ethical and societal concerns, such as privacy risks, and biases that can compound existing health inequalities. While such concerns are widely recognized, existing regulatory principles, oversight methods and ethical frameworks seem out of sync with digital health innovation. New governance and innovation best practices are thus needed to bring such principles to bear with the reality of business, innovation, and regulation.To grant practical insight into best practices for responsible digital health innovation, we conducted a qualitative study based on an interactive engagement methodology. We engaged key stakeholders (n = 46) operating at the translational frontier of digital health. This approach allowed us to identify three clusters of governance and innovation best practices in digital health innovation: i) inclusive co-creation, ii) responsive regulation, and iii) value-driven innovation. Our study shows that realizing responsible digital health requires diverse stakeholders’ commitment to adapt innovation and regulation practices, embracing co-creation as the default modus operandi for digital health development. We describe these collaborative practices and show how they can ensure that innovation is neither slowed by overregulation, nor leads to unethical outcomes.
Artificial intelligence in digital pathology: a systematic review and meta-analysis of diagnostic test accuracy
Authors: McGenity Clare , Clarke Emily L. , Jennings Charlotte , Matthews Gillian , Cartlidge Caroline , Freduah-Agyemang Henschel , Stocken Deborah D. , Treanor Darren 
Published: May 2024

AbstractEnsuring diagnostic performance of artificial intelligence (AI) before introduction into clinical practice is essential. Growing numbers of studies using AI for digital pathology have been reported over recent years. The aim of this work is to examine the diagnostic accuracy of AI in digital pathology images for any disease. This systematic review and meta-analysis included diagnostic accuracy studies using any type of AI applied to whole slide images (WSIs) for any disease. The reference standard was diagnosis by histopathological assessment and/or immunohistochemistry. Searches were conducted in PubMed, EMBASE and CENTRAL in June 2022. Risk of bias and concerns of applicability were assessed using the QUADAS-2 tool. Data extraction was conducted by two investigators and meta-analysis was performed using a bivariate random effects model, with additional subgroup analyses also performed. Of 2976 identified studies, 100 were included in the review and 48 in the meta-analysis. Studies were from a range of countries, including over 152,000 whole slide images (WSIs), representing many diseases. These studies reported a mean sensitivity of 96.3% (CI 94.1–97.7) and mean specificity of 93.3% (CI 90.5–95.4). There was heterogeneity in study design and 99% of studies identified for inclusion had at least one area at high or unclear risk of bias or applicability concerns. Details on selection of cases, division of model development and validation data and raw performance data were frequently ambiguous or missing. AI is reported as having high diagnostic accuracy in the reported areas but requires more rigorous evaluation of its performance.
Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer’s disease
Authors: Sanchez-Rodriguez Lazaro M. , Bezgin Gleb , Carbonell Felix , Therriault Joseph , Fernandez-Arias Jaime , Servaes Stijn , Rahmouni Nesrine , Tissot Cécile , Stevenson Jenna , Karikari Thomas K. , Ashton Nicholas J. , Benedet Andréa L. , Zetterberg Henrik , Blennow Kaj , Triana-Baltzer Gallen , Kolb Hartmuth C. , Rosa-Neto Pedro , Iturria-Medina Yasser 
Published: May 2024

AbstractNeuronal dysfunction and cognitive deterioration in Alzheimer’s disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.
Excessive endometrial PlGF- Rac1 signalling underlies endometrial cell stiffness linked to pre-eclampsia
Authors: Raja Xavier Janet P. , Rianna Carmela , Hellwich Emily , Nikolou Iliana , Lankapalli Aditya Kumar , Brucker Sara Y. , Singh Yogesh , Lang Florian , Schäffer Tilman E. , Salker Madhuri S. 
Published: May 2024

AbstractCell stiffness is regulated by dynamic interaction between ras-related C3 botulinum toxin substrate 1 (Rac1) and p21 protein-activated kinase 1 (PAK1) proteins, besides other biochemical and molecular regulators. In this study, we investigated how the Placental Growth Factor (PlGF) changes endometrial mechanics by modifying the actin cytoskeleton at the maternal interface. We explored the global effects of PlGF in endometrial stromal cells (EnSCs) using the concerted approach of proteomics, atomic force microscopy (AFM), and electrical impedance spectroscopy (EIS). Proteomic analysis shows PlGF upregulated RhoGTPases activating proteins and extracellular matrix organization-associated proteins in EnSCs. Rac1 and PAK1 transcript levels, activity, and actin polymerization were significantly increased with PlGF treatment. AFM further revealed an increase in cell stiffness with PlGF treatment. The additive effect of PlGF on actin polymerization was suppressed with siRNA-mediated inhibition of Rac1, PAK1, and WAVE2. Interestingly, the increase in cell stiffness by PlGF treatment was pharmacologically reversed with pravastatin, resulting in improved trophoblast cell invasion. Taken together, aberrant PlGF levels in the endometrium can contribute to an altered pre-pregnancy maternal microenvironment and offer a unifying explanation for the pathological changes observed in conditions such as pre-eclampsia (PE).
Synthetic dimensions for topological and quantum phases
Authors: Argüello-Luengo Javier , Bhattacharya Utso , Celi Alessio , Chhajlany Ravindra W. , Grass Tobias , Płodzień Marcin , Rakshit Debraj , Salamon Tymoteusz , Stornati Paolo , Tarruell Leticia , Lewenstein Maciej 
Published: May 2024

AbstractThe concept of synthetic dimensions works particularly well in atomic physics, quantum optics, and photonics, where the internal degrees of freedom (Zeeman sublevels of the ground state, metastable excited states, or motional states for atoms, and angular momentum states or transverse modes for photons) provide the synthetic space. In this Perspective article we report on recent progress on studies of synthetic dimensions, mostly, but not only, based on the research realized around the Barcelona groups (ICFO, UAB), Donostia (DIPC), Poznan (UAM), Kraków (UJ), and Allahabad (HRI). We describe our attempts to design quantum simulators with synthetic dimensions, to mimic curved spaces, artificial gauge fields, lattice gauge theories, twistronics, quantum random walks, and more.
Plasmonic chemistry for sustainable ammonia production
Authors: Choudhary Arsha , Halder Anubhab , Aggarwal Pooja , Govind Rao Vishal 
Published: May 2024

AbstractThe traditional Haber-Bosch process for ammonia production is energy-intensive and relies on harsh conditions. Plasmonic materials are considered a sustainable alternative to this process. In plasmonics, the ability to localize and enhance light fields beyond the diffraction limit offers a promising avenue for harnessing visible light for photocatalysis. Moreover, the integration of plasmonic metals with various catalysts presents a promising avenue to improve efficiency and selectivity. However, cost and stability challenges hinder large-scale applications. Researchers are actively exploring new materials, optimizing catalyst design, and improving stability to overcome these hurdles. This Review delves into the intricacies of plasmonic catalysis, including material design, co-catalyst selection, and the use of nanotechnologies for precise control of metal properties in plasmonic catalysis. It emphasizes understanding energy flow at material interfaces. Ultimately, the Review aims to establish a foundation for efficient nitrogen fixation through plasmonic photocatalysis, paving the way for a more sustainable future.
Anthropogenic eutrophication and stratification strength control hypoxia in the Yangtze Estuary
Authors: Sheng Hui , Darby Stephen E. , Zhao Ning , Liu Dongyan , Kettner Albert J. , Lu Xixi , Yang Yang , Gao Jianhua , Zhao Yaqing , Wang Ya Ping 
Published: May 2024

AbstractMany large estuaries are threatened by intensifying hypoxia. However, due to the limited duration of available observations, uncertainties persist regarding the level of contemporary hypoxia intensity in a longer-term context and the relative contributions of climate versus human factors. Here we present sediment records for the hypoxia intensity and associated environmental parameters in the Yangtze Estuary over the past three centuries. The results show that the hypoxia intensity has been increasing during the last half century due to anthropogenic eutrophication, but the current hypoxia condition is not as severe as some preindustrial periods due to weaker stratification in the water column. Our findings suggest that if anthropogenic and climatic forcing coincide in the foreseeable future, the hypoxia intensity of the Yangtze Estuary may reach unprecedented levels.
Research on vehicle path planning of automated guided vehicle with simultaneous pickup and delivery with mixed time windows
Authors: Jiang Zhengrui , Chen Wang , Zheng Xiaojun , Gao Feng 
Published: May 2024

AbstractThe authors investigate new Automated Guided Vehicle (AGV) Routing Problem with Simultaneous Pickup and Delivery with Mixed Time Windows (VRPSPDMTW) in smart workshops, a variation of the classic Vehicle Routing Problem (VRP). A mixed time window vehicle routing model was developed for simultaneous deliveries. This model reduces the cost of AGVs used and distribution cost, along with time window penalties. To address this complex challenge, a Hybrid Adaptive Genetic Algorithm using Variable Neighbourhood Search (AGA‐VNS) is proposed. This algorithm enhances the genetic algorithm's local search capabilities while preserving solution diversity, thereby improving both efficiency and quality of solutions. Comprehensive computational experiments are conducted, which include both VRPSPDTW test benchmark and real‐world smart factory instance studies. The outcomes reveal that the AGA‐VNS algorithm outperforms both professional solver software and advanced heuristic methods significantly. Moreover, the newly developed mixed time window model is more aligned with the requirements of real‐world production processes compared to the traditional time window model. Thus, this research not only presents novel insights into the domain of vehicle routing problems but also demonstrates its significant applicability and potential in the background of intelligent workshops.
DeepGCN based on variable multi‐graph and multimodal data for ASD diagnosis
Authors: Liu Shuaiqi , Wang Siqi , Sun Chaolei , Li Bing , Wang Shuihua , Li Fei 
Published: May 2024

AbstractDiagnosing individuals with autism spectrum disorder (ASD) accurately faces great challenges in clinical practice, primarily due to the data's high heterogeneity and limited sample size. To tackle this issue, the authors constructed a deep graph convolutional network (GCN) based on variable multi‐graph and multimodal data (VMM‐DGCN) for ASD diagnosis. Firstly, the functional connectivity matrix was constructed to extract primary features. Then, the authors constructed a variable multi‐graph construction strategy to capture the multi‐scale feature representations of each subject by utilising convolutional filters with varying kernel sizes. Furthermore, the authors brought the non‐imaging information into the feature representation at each scale and constructed multiple population graphs based on multimodal data by fully considering the correlation between subjects. After extracting the deeper features of population graphs using the deep GCN(DeepGCN), the authors fused the node features of multiple subgraphs to perform node classification tasks for typical control and ASD patients. The proposed algorithm was evaluated on the Autism Brain Imaging Data Exchange I (ABIDE I) dataset, achieving an accuracy of 91.62% and an area under the curve value of 95.74%. These results demonstrated its outstanding performance compared to other ASD diagnostic algorithms.