bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive modeling of burnout based on organizational culture perceptions among health systems employees: a comparative study using correlation, decision tree, and Bayesian analyses
Authors: Johnson Teray , Shamroukh Sameh 
Published: March 2024

AbstractBurnout is a significant concern, particularly within the healthcare field, affecting both nurses and physicians. It is a common issue in health systems, which encompass a range of healthcare facilities, such as hospitals, physician practices, ambulatory sites, and administrative offices like finance. Despite this, there has not been an extensive exploration of burnout in employees working directly with patients versus those in non-patient-facing roles within these health systems. It is important to note that organizational culture plays a crucial role in influencing various aspects of employees' work-life balance and their experiences of burnout. This study adopts a cross-sectional design, involving the distribution of a 57-question Likert scale survey to employees in health systems. These employees serve in various roles, both patient-facing and non-patient-facing, within jointly owned healthcare organizations, which encompass hospitals, ambulatory sites, and administrative offices. The survey was disseminated through trade organizations and employees at the managerial level and above within these health systems. Data was collected between October 2022 and January 2023, resulting in a total of 67 responses. The study employs correlation analysis to explore the connection between organizational culture and burnout. Furthermore, a decision tree model is constructed to predict burnout scores based on survey responses, specifically the question regarding the perceived positivity of the organizational culture. The decision tree models indicate that perceiving organizational culture as positive, safety-oriented, and supportive predicts various outcomes for individuals, including job retention, positive experiences with patients, increased callousness, and stimulation while working with colleagues. Bayesian analysis, considering the small sample size, reinforces these findings and provides a different perspective, incorporating prior knowledge and credible intervals. An association test suggests a strong link between a positive organizational culture and burnout symptoms, while another test supports a connection with engagement signs. Similar to nurses and physicians, administrative health systems’ personnel are susceptible to burnout. Organizational culture can affect burnout. Therefore, health systems’ leaders should cultivate an organizational culture that protects against burnout.
MKRN1 regulates the expression profiles and transcription factor activity in HeLa cells inhibition suppresses cervical cancer cell progression
Authors: Dong Xiang , Zhan Yuling , Li Suwan , Yang Minghui , Gao Yu 
Published: March 2024

AbstractCervical cancer is one of the most common gynecologic malignancies worldwide, necessitating the identification of novel biomarkers and therapeutic targets. This study aimed to investigate the significance of MKRN1 in cervical cancer and explore its potential as a diagnostic marker and therapeutic target. The results indicated that MKRN1 expression was up-regulated in cervical cancer tissues and correlated with advanced tumor stage, higher grade, and poor patient survival. Functional studies demonstrated that targeting MKRN1 effectively inhibited cell proliferation, migration, and invasion, highlighting its critical role in tumor progression and metastasis. Moreover, the knockdown of MKRN1 resulted in altered expression patterns of six transcription factor-encoding genes, revealing its involvement in gene regulation. Co-expression network analysis unveiled complex regulatory mechanisms underlying the effects of MKRN1 knockdown on gene expression. Furthermore, the results suggested that MKRN1 might serve as a diagnostic marker for personalized treatment strategies and a therapeutic target to inhibit tumor growth, metastasis, and overcome drug resistance. The development of MKRN1-targeted interventions might hold promise for advancing personalized medicine approaches in cervical cancer treatment. Further research is warranted to validate these findings, elucidate underlying mechanisms, and translate these insights into improved management and outcomes for cervical cancer patients.
Regional impacts of warming on biodiversity and biomass in high latitude stream ecosystems across the Northern Hemisphere
Authors: Jackson Michelle C. , Friberg Nikolai , Moliner Cachazo Luis , Clark David R. , Mutinova Petra Thea , O’Gorman Eoin J. , Kordas Rebecca L. , Gallo Bruno , Pichler Doris E. , Bespalaya Yulia , Aksenova Olga V. , Milner Alexander , Brooks Stephen J. , Dunn Nicholas , Lee K.W.K. , Ólafsson Jón S. , Gíslason Gísli M. , Millan Lucia , Bell Thomas , Dumbrell Alex J. , Woodward Guy 
Published: March 2024

AbstractWarming can have profound impacts on ecological communities. However, explorations of how differences in biogeography and productivity might reshape the effect of warming have been limited to theoretical or proxy-based approaches: for instance, studies of latitudinal temperature gradients are often conflated with other drivers (e.g., species richness). Here, we overcome these limitations by using local geothermal temperature gradients across multiple high-latitude stream ecosystems. Each suite of streams (6-11 warmed by 1-15°C above ambient) is set within one of five regions (37 streams total); because the heating comes from the bedrock and is not confounded by changes in chemistry, we can isolate the effect of temperature. We found a negative overall relationship between diatom and invertebrate species richness and temperature, but the strength of the relationship varied regionally, declining more strongly in regions with low terrestrial productivity. Total invertebrate biomass increased with temperature in all regions. The latter pattern combined with the former suggests that the increased biomass of tolerant species might compensate for the loss of sensitive species. Our results show that the impact of warming can be dependent on regional conditions, demonstrating that local variation should be included in future climate projections rather than simply assuming universal relationships.
Classification of likely functional class for ligand binding sites identified from fragment screening
Authors: Utgés Javier S. , MacGowan Stuart A. , Ives Callum M. , Barton Geoffrey J. 
Published: March 2024

AbstractFragment screening is used to identify binding sites and leads in drug discovery, but it is often unclear which binding sites are functionally important. Here, data from 37 experiments, and 1309 protein structures binding to 1601 ligands were analysed. A method to group ligands by binding sites is introduced and sites clustered according to profiles of relative solvent accessibility. This identified 293 unique ligand binding sites, grouped into four clusters (C1-4). C1 includes larger, buried, conserved, and population missense-depleted sites, enriched in known functional sites. C4 comprises smaller, accessible, divergent, missense-enriched sites, depleted in functional sites. A site in C1 is 28 times more likely to be functional than one in C4. Seventeen sites, which to the best of our knowledge are novel, in 13 proteins are identified as likely to be functionally important with examples from human tenascin and 5-aminolevulinate synthase highlighted. A multi-layer perceptron, and K-nearest neighbours model are presented to predict cluster labels for ligand binding sites with an accuracy of 96% and 100%, respectively, so allowing functional classification of sites for proteins not in this set. Our findings will be of interest to those studying protein-ligand interactions and developing new drugs or function modulators.
A platform-independent AI tumor lineage and site (ATLAS) classifier
Authors: Rydzewski Nicholas R. , Shi Yue , Li Chenxuan , Chrostek Matthew R. , Bakhtiar Hamza , Helzer Kyle T. , Bootsma Matthew L. , Berg Tracy J. , Harari Paul M. , Floberg John M. , Blitzer Grace C. , Kosoff David , Taylor Amy K. , Sharifi Marina N. , Yu Menggang , Lang Joshua M. , Patel Krishnan R. , Citrin Deborah E. , Sundling Kaitlin E. , Zhao Shuang G. 
Published: March 2024

AbstractHistopathologic diagnosis and classification of cancer plays a critical role in guiding treatment. Advances in next-generation sequencing have ushered in new complementary molecular frameworks. However, existing approaches do not independently assess both site-of-origin (e.g. prostate) and lineage (e.g. adenocarcinoma) and have minimal validation in metastatic disease, where classification is more difficult. Utilizing gradient-boosted machine learning, we developed ATLAS, a pair of separate AI Tumor Lineage and Site-of-origin models from RNA expression data on 8249 tumor samples. We assessed performance independently in 10,376 total tumor samples, including 1490 metastatic samples, achieving an accuracy of 91.4% for cancer site-of-origin and 97.1% for cancer lineage. High confidence predictions (encompassing the majority of cases) were accurate 98–99% of the time in both localized and remarkably even in metastatic samples. We also identified emergent properties of our lineage scores for tumor types on which the model was never trained (zero-shot learning). Adenocarcinoma/sarcoma lineage scores differentiated epithelioid from biphasic/sarcomatoid mesothelioma. Also, predicted lineage de-differentiation identified neuroendocrine/small cell tumors and was associated with poor outcomes across tumor types. Our platform-independent single-sample approach can be easily translated to existing RNA-seq platforms. ATLAS can complement and guide traditional histopathologic assessment in challenging situations and tumors of unknown primary.
Post-ischemic ubiquitination at the postsynaptic density reversibly influences the activity of ischemia-relevant kinases
Authors: Dhawka Luvna , Palfini Victoria , Hambright Emma , Blanco Ismary , Poon Carrie , Kahl Anja , Resch Ulrike , Bhawal Ruchika , Benakis Corinne , Balachandran Vaishali , Holder Alana , Zhang Sheng , Iadecola Costantino , Hochrainer Karin 
Published: March 2024

AbstractUbiquitin modifications alter protein function and stability, thereby regulating cell homeostasis and viability, particularly under stress. Ischemic stroke induces protein ubiquitination at the ischemic periphery, wherein cells remain viable, however the identity of ubiquitinated proteins is unknown. Here, we employed a proteomics approach to identify these proteins in mice undergoing ischemic stroke. The data are available in a searchable web interface (https://hochrainerlab.shinyapps.io/StrokeUbiOmics/). We detected increased ubiquitination of 198 proteins, many of which localize to the postsynaptic density (PSD) of glutamatergic neurons. Among these were proteins essential for maintaining PSD architecture, such as PSD95, as well as NMDA and AMPA receptor subunits. The largest enzymatic group at the PSD with elevated post-ischemic ubiquitination were kinases, such as CaMKII, PKC, Cdk5, and Pyk2, whose aberrant activities are well-known to contribute to post-ischemic neuronal death. Concurrent phospho-proteomics revealed altered PSD-associated phosphorylation patterns, indicative of modified kinase activities following stroke. PSD-located CaMKII, PKC, and Cdk5 activities were decreased while Pyk2 activity was increased after stroke. Removal of ubiquitin restored kinase activities to pre-stroke levels, identifying ubiquitination as the responsible molecular mechanism for post-ischemic kinase regulation. These findings unveil a previously unrecognized role of ubiquitination in the regulation of essential kinases involved in ischemic injury.
Emergence of quantum confinement in topological kagome superconductor CsV3Sb5
Authors: Cai Yongqing , Wang Yuan , Hao Zhanyang , Liu Yixuan , Sui Xuelei , Liang Zuowei , Ma Xiao-Ming , Zhang Fayuan , Shen Zecheng , Zhang Chengcheng , Jiang Zhicheng , Yang Yichen , Liu Wanling , Jiang Qi , Liu Zhengtai , Ye Mao , Shen Dawei , Gao Han , Xiao Hanbo , Liu Zhongkai , Sun Zhe , Liu Yi , Cui Shengtao , Chen Jiabin , Wang Le , Liu Cai , Lin Junhao , Huang Bing , Wang Zhenyu , Chen Xianhui , Mei Jia-Wei , Wang Jianfeng , Chen Chaoyu 
Published: March 2024

AbstractQuantum confinement is a restriction on the motion of electrons in a material to specific region, resulting in discrete energy levels rather than continuous energy bands. In certain materials, quantum confinement could dramatically reshape the electronic structure and properties of the surface with respect to the bulk. Here, in the recently discovered kagome superconductors CsV3Sb5, we unveil the dominant role of quantum confinement in determining their surface electronic structure. Combining angle-resolved photoemission spectroscopy (ARPES) measurement and density-functional theory simulation, we report the observations of two-dimensional quantum well states due to the confinement of bulk electron pocket and Dirac cone to the nearly isolated surface layer. The theoretical calculations on the slab model also suggest that the ARPES observed spectra are almost entirely contributed by the top two layers. Our results not only explain the disagreement of band structures between the recent experiments and calculations, but also suggest an equally important role played by quantum confinement, together with strong correlation and band topology, in shaping the electronic properties of this material.
How, when and where current mass flows in Martian gullies are driven by CO2 sublimation
Authors: Roelofs Lonneke , Conway Susan J. , de Haas Tjalling , Dundas Colin , Lewis Stephen R. , McElwaine Jim , Pasquon Kelly , Raack Jan , Sylvest Matthew , Patel Manish R. 
Published: March 2024

AbstractMartian gullies resemble water-carved gullies on Earth, yet their present-day activity cannot be explained by water-driven processes. The sublimation of CO2 has been proposed as an alternative driver for sediment transport, but how this mechanism works remains unknown. Here we combine laboratory experiments of CO2-driven granular flows under Martian atmospheric pressure with 1D climate simulation modelling to unravel how, where, and when CO2 can drive present-day gully activity. Our work shows that sublimation of CO2 ice, under Martian atmospheric conditions can fluidize sediment and creates morphologies similar to those observed on Mars. Furthermore, the modelled climatic and topographic boundary conditions for this process, align with present-day gully activity. These results have implications for the influence of water versus CO2-driven processes in gully formation and for the interpretation of gully landforms on other planets, as their existence is no longer definitive proof for flowing liquids.
Development and prospective validation of an artificial intelligence-based smartphone app for rapid intraoperative pituitary adenoma identification
Authors: Bou-Nassif Rabih , Reiner Anne S. , Pease Matthew , Bale Tejus , Cohen Marc A. , Rosenblum Marc , Tabar Viviane 
Published: March 2024

Abstract
Background
Intraoperative pathology consultation plays a crucial role in tumor surgery. The ability to accurately and rapidly distinguish tumor from normal tissue can greatly impact intraoperative surgical oncology management. However, this is dependent on the availability of a specialized pathologist for a reliable diagnosis. We developed and prospectively validated an artificial intelligence-based smartphone app capable of differentiating between pituitary adenoma and normal pituitary gland using stimulated Raman histology, almost instantly.

Methods
The study consisted of three parts. After data collection (part 1) and development of a deep learning-based smartphone app (part 2), we conducted a prospective study that included 40 consecutive patients with 194 samples to evaluate the app in real-time in a surgical setting (part 3). The smartphone app’s sensitivity, specificity, positive predictive value, and negative predictive value were evaluated by comparing the diagnosis rendered by the app to the ground-truth diagnosis set by a neuropathologist.

Results
The app exhibits a sensitivity of 96.1% (95% CI: 89.9–99.0%), specificity of 92.7% (95% CI: 74–99.3%), positive predictive value of 98% (95% CI: 92.2–99.8%), and negative predictive value of 86.4% (95% CI: 66.2–96.8%). An external validation of the smartphone app on 40 different adenoma tumors and a total of 191 scanned SRH specimens from a public database shows a sensitivity of 93.7% (95% CI: 89.3–96.7%).

Conclusions
The app can be readily expanded and repurposed to work on different types of tumors and optical images. Rapid recognition of normal versus tumor tissue during surgery may contribute to improved intraoperative surgical management and oncologic outcomes. In addition to the accelerated pathological assessments during surgery, this platform can be of great benefit in community hospitals and developing countries, where immediate access to a specialized pathologist during surgery is limited.
Assessing the sustainability of the European Green Deal and its interlin kages with the SDGs
Authors: Koundouri Phoebe , Alamanos Angelos , Plataniotis Angelos , Stavridis Charis , Perifanos Konstantinos , Devves Stathis 
Published: March 2024

AbstractThe European Green Deal (EGD) is the growth strategy for Europe, covering multiple domains, and aiming to an equitable, climate neutral European Union by 2050. The UN Agenda 2030, encompassing 17 Sustainable Development Goals (SDGs), establishes the foundation for a global sustainability transition. The integration of the SDGs into the EGD is an overlooked issue in the literature, despite Europe’s slow progress to achieve the sustainability targets. We employed a machine-learning text-mining method to evaluate the extent of SDG integration within the 74 EGD policy documents published during 2019–2023. The findings reveal a substantial alignment of EGD policies with SDGs related to clean energy (SDG7), climate action (SDG13), and sustainable consumption and production (SDG12). In contrast, there is a significant underrepresentation in areas related to social issues such as inequalities, poverty, hunger, health, education, gender equality, decent work, and peace, as indicated by lower alignment with SDGs 1, 2, 3, 4, 5, 8, 10, and 16. Temporal trends suggest a marginal increase in the attention given to environmental health (especially water and marine life) and gender equality. Furthermore, we illustrate the alignment of EGD policies with the six essential sustainability transformations proposed by the Sustainable Development Solutions Network (SDSN) in 2019 for the operationalization of the SDGs. The results indicate that besides the prevalence of “Energy Decarbonization and Sustainable Industry”, all areas have received attention, except for the “Health, Wellbeing and Demography”. The findings call for a more integrated approach to address the complete spectrum of sustainability in a balanced manner.
PRODH safeguards human naive pluripotency by limiting mitochondrial oxidative phosphorylation and reactive oxygen species production
Authors: Chen Cheng , Liu Qianyu , Chen Wenjie , Gong Zhiyuan , Kang Bo , Sui Meihua , Huang Liming , Wang Ying-Jie 
Published: March 2024

AbstractNaive human embryonic stem cells (hESCs) that resemble the pre-implantation epiblasts are fueled by a combination of aerobic glycolysis and oxidative phosphorylation, but their mitochondrial regulators are poorly understood. Here we report that, proline dehydrogenase (PRODH), a mitochondria-localized proline metabolism enzyme, is dramatically upregulated in naive hESCs compared to their primed counterparts. The upregulation of PRODH is induced by a reduction in c-Myc expression that is dependent on PD0325901, a MEK inhibitor routinely present in naive hESC culture media. PRODH knockdown in naive hESCs significantly promoted mitochondrial oxidative phosphorylation (mtOXPHOS) and reactive oxygen species (ROS) production that triggered autophagy, DNA damage, and apoptosis. Remarkably, MitoQ, a mitochondria-targeted antioxidant, effectively restored the pluripotency and proliferation of PRODH-knockdown naive hESCs, indicating that PRODH maintains naive pluripotency by preventing excessive ROS production. Concomitantly, PRODH knockdown significantly slowed down the proteolytic degradation of multiple key mitochondrial electron transport chain complex proteins. Thus, we revealed a crucial role of PRODH in limiting mtOXPHOS and ROS production, and thereby safeguarding naive pluripotency of hESCs.
Crucial size effect on dicarbonylation of acetylene over Pd/CsHPMo heterogeneous catalysts
Authors: Xuemei Wei , Kai Wang , Guofeng Wu , Guoqi Yu , Hualiang Shen , Tao Cai , Yanjuan Luo , Tianbo Shang , Xinzhi Chen , Runpu Shen , Bin Hu 
Published: March 2024

Carbonylation reaction shows “volcanic curve” with increasing Pd particle size, and 5 nm Pd nanoparticles with stronger “SMSI effect” was preferred. Electron-deficient Pd accelerated Pdδ+ ↔ Pd (0) cycle, which endows its high catalytic efficiency.
DPT‐tracker: Dual pooling transformer for efficient visual tracking
Authors: Fang Yang , Xie Bailian , Khairuddin Uswah , Min Zijian , Jiang Bingbing , Li Weisheng 
Published: March 2024

AbstractTransformer tracking always takes paired template and search images as encoder input and conduct feature extraction and target‐search feature correlation by self and/or cross attention operations, thus the model complexity will grow quadratically with the number of input images. To alleviate the burden of this tracking paradigm and facilitate practical deployment of Transformer‐based trackers, we propose a dual pooling transformer tracking framework, dubbed as DPT, which consists of three components: a simple yet efficient spatiotemporal attention model (SAM), a mutual correlation pooling Transformer (MCPT) and a multiscale aggregation pooling Transformer (MAPT). SAM is designed to gracefully aggregates temporal dynamics and spatial appearance information of multi‐frame templates along space‐time dimensions. MCPT aims to capture multi‐scale pooled and correlated contextual features, which is followed by MAPT that aggregates multi‐scale features into a unified feature representation for tracking prediction. DPT tracker achieves AUC score of 69.5 on LaSOT and precision score of 82.8 on TrackingNet while maintaining a shorter sequence length of attention tokens, fewer parameters and FLOPs compared to existing state‐of‐the‐art (SOTA) Transformer tracking methods. Extensive experiments demonstrate that DPT tracker yields a strong real‐time tracking baseline with a good trade‐off between tracking performance and inference efficiency.
Multi‐granularity feature enhancement network for maritime ship detection
Authors: Ying Li , Miao Duoqian , Zhang Zhifei , Zhang Hongyun , Pedrycz Witold 
Published: March 2024

AbstractDue to the characteristics of high resolution and rich texture information, visible light images are widely used for maritime ship detection. However, these images are susceptible to sea fog and ships of different sizes, which can result in missed detections and false alarms, ultimately resulting in lower detection accuracy. To address these issues, a novel multi‐granularity feature enhancement network, MFENet, which includes a three‐way dehazing module (3WDM) and a multi‐granularity feature enhancement module (MFEM) is proposed. The 3WDM eliminates sea fog interference by using an image clarity automatic classification algorithm based on three‐way decisions and FFA‐Net to obtain clear image samples. Additionally, the MFEM improves the accuracy of detecting ships of different sizes by utilising an improved super‐resolution reconstruction convolutional neural network to enhance the resolution and semantic representation capability of the feature maps from YOLOv7. Experimental results demonstrate that MFENet surpasses the other 15 competing models in terms of the mean Average Precision metric on two benchmark datasets, achieving 96.28% on the McShips dataset and 97.71% on the SeaShips dataset.