bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient and reproducible generation of human induced pluripotent stem cell-derived expandable liver organoids for disease modeling
Authors: Mun Seon Ju , Hong Yeon-Hwa , Shin Yongbo , Lee Jaeseo , Cho Hyun-Soo , Kim Dae-Soo , Chung Kyung-Sook , Son Myung Jin 
Published: December 2023

AbstractGenetic liver disease modeling is difficult because it is challenging to access patient tissue samples and to develop practical and relevant model systems. Previously, we developed novel proliferative and functional liver organoids from pluripotent stem cells; however, the protocol requires improvement for standardization and reproducible mass production. Here, we improved the method such that it is suitable for scalable expansion and relatively homogenous production, resulting in an efficient and reproducible process. Moreover, three medium components critical for long-term expansion were defined. Detailed transcriptome analysis revealed that fibroblast growth factor signaling, the essential pathway for hepatocyte proliferation during liver regeneration, was mainly enriched in proliferative liver organoids. Short hairpin RNA-mediated knockdown of FGFR4 impaired the generation and proliferation of organoids. Finally, glycogen storage disease type Ia (GSD1a) patient-specific liver organoids were efficiently and reproducibly generated using the new protocol. They well maintained disease-specific phenotypes such as higher lipid and glycogen accumulation in the liver organoids and lactate secretion into the medium consistent with the main pathologic characteristics of patients with GSD1a. Therefore, our newly established liver organoid platform can provide scalable and practical personalized disease models and help to find new therapies for incurable liver diseases including genetic liver diseases.
TRIM25 dictates selective miRNA loading into extracellular vesicles during inflammation
Authors: King Kayla E. , Ghosh Priyanka , Wozniak Ann L. 
Published: December 2023

AbstractExtracellular vesicles (EVs) such as exosomes are loaded with specific biomolecules in order to perform cell-to-cell communication. Understanding the mechanism of selective cargo loading is important to better understand the physiological and pathological function of EVs. Here we describe a novel target of the E3 ligase TRIM25 and show that inflammation-mediated EV loading of the RNA binding protein FMR1 and its associated microRNA, miR-155, is promoted by TRIM25-mediated K63-ubiquitination of FMR1. This ubiquitination promotes an interaction between FMR1 and the EV loading machinery via the cleavage of the trafficking adaptor protein RILP. These interactions are lost when TRIM25 is knocked down. Loss of TRIM25 also prevents the loading of both FMR1 and miR-155. These findings suggest that inflammation-mediated loading of FMR1 and its associated microRNAs into the EV are dependent on K63-ubiquitination by TRIM25 and provide novel insights and tools to manipulate EV biogenesis for therapeutic benefit.
SARS-CoV-2 NSP14 MTase activity is critical for inducing canonical NF-κB activation
Authors: Tofaute Marie J. , Weller Benjamin , Graß Carina , Halder Hridi , Dohai Bushra , Falter-Braun Pascal , Krappmann Daniel 
Published: December 2023

Abstract
Upon SARS-CoV-2 infection, patients with severe forms of COVID-19 often suffer from a dysregulated immune response and hyperinflammation. Aberrant expression of cytokines and chemokines is associated with strong activation of the immunoregulatory transcription factor NF-κB, which can be directly induced by the SARS-CoV-2 protein NSP14. Here, we use NSP14 mutants and generated cells with host factor knockouts (KOs) in the NF-κB signaling pathways to characterize the molecular mechanism of NSP14-induced NF-κB activation. We demonstrate that full-length NSP14 requires methyltransferase (MTase) activity to drive NF-κB induction. NSP14 WT, but not an MTase-defective mutant, is poorly expressed and inherent post-translational instability is mediated by proteasomal degradation. Binding of SARS-CoV-2 NSP10 or addition of the co-factor S-adenosylmethionine (SAM) stabilizes NSP14 and augments its potential to activate NF-κB. Using CRISPR/Cas9-engineered KO cells, we demonstrate that NSP14 stimulation of canonical NF-κB activation relies on NF-κB factor p65/RELA downstream of the NEMO/IKK complex, while c-Rel or non-canonical RelB are not required to induce NF-κB transcriptional activity. However, NSP14 overexpression is unable to induce canonical IκB kinase β (IKKβ)/NF-κB signaling and in co-immunoprecipitation assays we do not detect stable associations between NSP14 and NEMO or p65, suggesting that NSP14 activates NF-κB indirectly through its methyltransferase activity. Taken together, our data provide a framework how NSP14 can augment basal NF-κB activation, which may enhance cytokine expression in SARS-CoV-2 infected cells.
Metabolic hormones are integral regulators of female reproductive health and function
Authors: Athar Faria , Karmani Muskan , Templeman Nicole M. 
Published: December 2023

Abstract
The female reproductive system is strongly influenced by nutrition and energy balance. It is well known that food restriction or energy depletion can induce suppression of reproductive processes, while overnutrition is associated with reproductive dysfunction. However, the intricate mechanisms through which nutritional inputs and metabolic health are integrated into the coordination of reproduction are still being defined. In this review, we describe evidence for essential contributions by hormones that are responsive to food intake or fuel stores. Key metabolic hormones—including insulin, the incretins (glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1), growth hormone, ghrelin, leptin, and adiponectin—signal throughout the hypothalamic–pituitary–gonadal axis to support or suppress reproduction. We synthesize current knowledge on how these multifaceted hormones interact with the brain, pituitary, and ovaries to regulate functioning of the female reproductive system, incorporating in vitro and in vivo data from animal models and humans. Metabolic hormones are involved in orchestrating reproductive processes in healthy states, but some also play a significant role in the pathophysiology or treatment strategies of female reproductive disorders. Further understanding of the complex interrelationships between metabolic health and female reproductive function has important implications for improving women’s health overall.
A novel spatial electric load forecasting method based on LDTW and GCN
Authors: Wei Minjie , wen Mi , Zhang Yi 
Published: December 2023

AbstractSpatial power load forecasting is crucial for power grid planning, generation planning, dispatching, efficient power utilization, and sustainable development. The integration of new energy sources and electric vehicles has significantly altered grid loads, increasing the complexity of spatial load forecasting. However, existing techniques fail to fully consider the temporal and spatial correlation characteristics of data, leading to challenges in data identification and summarization. This reduces load forecasting accuracy and prolongs prediction time. To address these issues, a spatial electric load forecasting method based on improved scale limited dynamic time warping (LDTW) and graph convolutional network (GCN) are proposed. Firstly, the improved scale LDTW is used to improve the clustering effect of K‐Mediods++, refine the type of load data, and make the subsequent model training more targeted. Secondly, the interconnections and distances of substations in a real network structure is used to build a graph model to capture the power load distribution. Finally, based on the clustering results and the graph model, GCN‐LSTM is used to construct the spatio‐temporal forecasting algorithm. The proposed algorithm is tested using load data from a region in Shanghai and compared with other advanced algorithms. Results show that the algorithm achieves higher prediction accuracy and efficiency.
Sequence‐to‐sequence transfer transformer network for automatic flight plan generation
Authors: Yang Yang , Qian Shengsheng , Zhang Minghua , Cai Kaiquan 
Published: December 2023

AbstractIn this work, a machine translation framework is proposed to tackle the flight plan generation in the air transport field. Diverging from the traditional human expert‐based way, a novel sequence‐to‐sequence transfer transformer network to automatic flight plan generation with enhanced operational acceptability is presented. It allows the user to translate the departure and arrival airport pairs denoted as test sentences, into the flyable waypoint sequences denoted as the corresponding source sentences. The approach leverages deep neural networks to autonomously learn air transport specialized knowledge and human expert insights from industry legacy data. Moreover, a multi‐head attention mechanism is adopted to model the complex correlation between airport pairs. Besides, we introduce an innovative waypoint embedding layer to learn effective embeddings for waypoint sequences. Additionally, an extensive flight plan dataset is constructed utilizing real‐world data in China spanning from July to September 2019. Employing the proposed model, rigorous training and testing procedures are conducted on this dataset, yielding remarkably favourable outcomes based on automatic evaluation metrics that are BLEU and METEOR, which outperform other popular approaches. More importantly, the proposed approach achieves high performance in the operational validation and visualization, showing its application potential for real‐world air traffic operation.
Power synergistic control between of power‐to‐hydrogen and SCESS‐DFIG considering “source–load” turbulence
Authors: Sun Dongyang , Ruan Junlin , Zheng Wenyuan , Wang Nan , Zu Guangxin 
Published: December 2023

AbstractHydrogen production from wind power can reduce wind abandonment and improve the utilization rate of wind power. However, both “source” turbulence caused by unstable wind speed and “load” turbulence caused by sudden load changes will adversely affect the stable operation of power‐to‐hydrogen systems and the grid connection stability of wind farms. A synergistic control strategy between a supercapacitor and power‐to‐hydrogen system is proposed to solve this problem. The strategy is based on the ensemble empirical‐mode decomposition algorithm. By using the supercapacitor to stabilize the high‐frequency component in the “source–load” turbulence, the stability of the power‐to‐hydrogen system is improved. An optimal allocation method of supercapacitor capacity suitable for the control strategy is then proposed. Considering the different states of each fan and supercapacitor, the unit inertia time constant variance is reduced by reasonably distributing the output of each unit. This effectively improves the inertia time constant and grid connection stability of the wind farm. Finally, the effectiveness of the strategy is verified by Simulink simulations.
Research on optimal dispatch model of power grid considering the uncertainty of flexible resource demand response on the residential side
Authors: Ding Guili , Shu Zhan , Xin Jianbo , Lin Zhenzhi , Zhong Zhiqiang , Zhou Shiyang , Ji Qingzhao , Xiao Hui , Han Xin 
Published: December 2023

AbstractResidential side flexible load participation in demand response (DR) has been widely used in recent years. However, there are uncertainties in the response willingness and response volume of residential customers, which have a non‐negligible impact on the security and economic dispatch of the power sector. This paper analyzes the uncertainty factors in the demand response process of residential users from the equipment load layer–user layer, establishes for the first time a refined model of residential users' participation in DR from the perspectives of participation uncertainty and response uncertainty, and further constructs a grid optimal dispatch model considering DR uncertainty. The experimental simulation results show that the model established in this paper is able to adjust the operation strategy according to the requirements of user comfort, enhance the enthusiasm of users to participate in DR, and at the same time reduce the dispatch security risk and economic loss caused by the uncertainty of residents' DR on the power grid.
Three‐level secondary negawatt trading market mechanism with capability of congestion management
Authors: Amirmahani Amirhossein , Bagheri Abed , Jadid Shahram 
Published: December 2023

AbstractModern power markets are witnessing various energy transactions, and the participants are focusing on different objectives like energy cost, profit, and environmental concerns as key parts of their strategy. In recent years, producers, prosumers, and other participants found ways to act freely in the grid and maximise their profit. By using negawatt trading (selling the right of buying to other participants), consumers will find a way to choose their role (seller, buyer, or negawatt trader) as they desire in the market and can join the market to maximise their utility function. A three‐level secondary market is proposed that would work besides the day‐ahead market. In the designed market, the network manager first determines the value of negawatt for each time in each region by considering the network conditions, and then by exchanging the information specific to each group, buyers and sellers have an opportunity to trade negawatt as much as they desire with the specified price in each time. The designed market also provides a mechanism to control the exchanges between different areas, which allows the network manager to control the grid conditions. The results show that the introduced market can be profitable for each participant including the DSO and work without interfering with the day‐ahead market process.
Radio-astronomical image reconstruction with a conditional denoising diffusion model
Authors: Drozdova M. , Kinakh V. , Bait O. , Taran O. , Lastufka E. , Dessauges-Zavadsky M. , Holotyak T. , Schaerer D. , Voloshynovskiy S. 
Published: December 2023

Context.Reconstructing sky models from dirty radio images for accurate source extraction, including source localization and flux estimation, is a complex yet critical task, and has important applications in galaxy evolution studies at high redshift, particularly in deep extragalactic fields using for example the Atacama Large Millimetre Array (ALMA). With the development of large-scale projects, such as the Square Kilometre Array (SKA), we anticipate the need for more advanced source-extraction methods. Existing techniques, such as CLEAN and PyBDSF, currently struggle to effectively extract faint sources, highlighting the necessity for the development of more precise and robust methods.Aims.The success of the source-extraction process critically depends on the quality and accuracy of image reconstruction. As the imaging process represents an “information-lossy” operator, the reconstruction is characterized by uncertainty. The current study proposes the application of stochastic neural networks for the direct reconstruction of sky models from “dirty” images. This approach allows us to localize radio sources and to determine their fluxes with corresponding uncertainties, providing a potential advancement in the field of radio-source characterization.Methods.We used a dataset of 10 164 images simulated with the CASA tool based on the ALMA Cycle 5.3 antenna configuration. We applied conditional denoising diffusion probabilistic models (DDPMs) to directly reconstruct sky models from these dirty images, and then processed these models using Photutils to extract the coordinates and fluxes of the sources. To test the robustness of the proposed model, which was trained on a fixed water vapor value, we examined its performance under varying levels of water vapor.Results.We demonstrate that the proposed approach is state of the art in terms of source localisation, achieving over 90% completeness at a signal-to-noise ratio (S/N) of as low as 2. Additionally, the described method offers an inherent measure of prediction reliability thanks to the stochastic nature of the chosen model. In terms of flux estimation, the proposed model surpasses PyBDSF in terms of performance, accurately extracting fluxes for 96% of the sources in the test set, a notable improvement over the 57% achieved by CLEAN+ PyBDSF.Conclusions.Conditional DDPMs are a powerful tool for image-to-image translation, yielding accurate and robust characterization of radio sources, and outperforming existing methodologies. While this study underscores the significant potential of DDPMs for applications in radio astronomy, we also acknowledge certain limitations that accompany their use, and suggest directions for further refinement and research.
Partizipatives Design im Kontext gesundheitsbezogener Technologien
– Herausforderungen und Handlungserfordernisse aus Perspektive der
Versorgungsforschung
Authors: Kernebeck Sven , Busse Theresa Sophie , Fischer Florian , Ehlers Jan P. 
Published: December 2023

ZusammenfassungPartizipatives Design (PD) ermöglicht den Einbezug von Nutzer:innen in
den Entwicklungsprozess digitaler Technologien im Gesundheitswesen. Der Einsatz
von PD birgt jedoch Hürden, da theoretische und methodische
Entscheidungen zu treffen sind. Oftmals werden diese in Forschungsarbeiten in
der Versorgungsforschung nicht hinreichend dargestellt oder begründet.
Dies kann zu einer eingeschränkten Bewertbarkeit und Nachvollziehbarkeit
der Ergebnisse führen. Der vorliegende Beitrag thematisiert drei
Schwerpunkte: Erstens wird ein Überblick über die wesentlichen
theoretischen und methodischen Entscheidungen gegeben, die im Rahmen des PD aus
Perspektive der Versorgungsforschung getroffen werden müssen. Zweitens
werden die damit einhergehenden Herausforderungen aufgezeigt und drittens
Erfordernisse für die zukünftige Anwendung und
(Weiter-)Entwicklung des PD in der Versorgungsforschung beschrieben.
Quality by Design in Pharmaceuticals: A Review of its Impact on
Regulatory Compliance and Product Quality
Authors: Azeeze Mohamed Sheik Tharik Abdul , Nunavath Raja Shekhar , Singh Madhu Tanya , Jain Anubha , Chakma Marjita , Arivuselvam Rajaguru 
Published: December 2023

AbstractThe pharmaceutical industry has embraced the quality-by-design (QbD) approach as
a promising development, formulation and manufacturing strategy. QbD provides a
systematic and science-based framework for designing and producing high-quality
products, with a particular focus on identifying, assessing and controlling
risks throughout the development process. This review aims to assess the
benefits of implementing QbD in pharmaceutical processes, evaluate its impact on
regulatory compliance and explore its potential to enhance drug product quality.
The primary objective of this review is to evaluate the influence of QbD on
pharmaceutical development and manufacturing processes. It also seeks to examine
the regulatory requirements associated with the implementation of QbD and
highlight the advantages of this approach in terms of product quality and
cost-effectiveness. Additionally, the review aims to explore the potential of
QbD in improving the safety and efficacy of drug products. The QbD approach
holds tremendous potential to revolutionize the pharmaceutical industry by
optimizing drug development & manufacturing processes, reducing costs
and enhancing product quality and consistency. However, implementing QbD
requires a comprehensive understanding of the underlying science, as well as
strict adherence to regulatory requirements in drug development and
manufacturing. In conclusion, by embracing the QbD approach, the pharmaceutical
industry can ensure the production of safe, effective and regulation-compliant
products while simultaneously improving process efficiency. This strategic shift
toward QbD represents a pivotal step in advancing pharmaceutical research and
manufacturing capabilities, ultimately benefiting both the industry and more
importantly, patients worldwide.
Acute abdomen in pediatric radiology
Authors: Lochbühler Nina , Bölle Petra , Müller-Abt Peter 
Published: December 2023

Background Imaging is a common part of the workup for acute abdomen in childhood and adolescence. Rapid diagnosis is crucial for adequate therapy, especially in young children.
Method This review is intended to provide an overview of the typical causes of acute abdomen in children and adolescents and is specifically aimed at radiologists who do not regularly work in pediatric radiology.
Results and Conclusion Age-specific peculiarities make a division into three age groups useful: Newborns, infants and toddlers, and schoolchildren. Possible causes of acute abdomen in children range from congenital lesions, particularly in newborns, to entities well known in adult radiology, more commonly in school-aged children. Since younger children have a higher sensitivity to radiation and often a limited ability to cooperate, sonography and conventional X-ray are the primary imaging modalities used. Decisive advantages of sonography, especially in younger children, include its widespread availability, the lack of need for sedation, and the possibility of bedside examination. Supplementary cross-sectional imaging, usually MRI, is reserved for special clinical questions. Close interdisciplinary cooperation between attending clinicians and radiologists is essential for efficient diagnostics in this patient group.
Key points:
Citation Format
Okulare Flusssäureexposition – Fallbericht einer erfolgreichen gemeinsamen Patientenversorgung durch Telenotarzt und bodengebundenen Notarzt
Authors: von Au Josephine , Brinkrolf Peter , Rübsam Marie-Luise 
Published: December 2023

ZusammenfassungWir berichten über einen 42-jährigen Mann, der im Rahmen seiner beruflichen Tätigkeit eine
akzidentielle Exposition mit dem Gefahrstoff „Flusssäure“, einer wässrigen Lösung von
Fluorwasserstoff, hatte. Bereits auf der Anfahrt konnte die diensthabende Telenotärztin die
Notärztin mit fundierten Fachinformationen zum Gefahrstoff, den voraussichtlichen Symptomen
und Dosierungen der Notfallmedikamente unterstützen, sodass die Notärztin beim Eintreffen am
Einsatzort bereits über alle Informationen zu notwendigen Maßnahmen und entsprechende
Berechnungen der Verdünnungsreihe verfügte. Der kreislaufstabile Patient klagte über
Fremdkörpergefühl im linken Auge. Nach einer prioritätsgeleiteten Untersuchung wurde die
begonnene Augendusche fortgesetzt und eine 1%ige Calciumgluconat-Lösung lokal aufgetragen. Der
Patient wurde zur weiteren Behandlung in die nahe gelegene Universitätsklinik gebracht.