bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing Simulations of Forest Hurricane Disturbance and Recovery in Puerto Rico by ELM‐FATES Using Field Measurements
Authors: Shi Mingjie , Keller Michael , Bomfim Barbara , Kueppers Lara , Koven Charlie , Needham Jessica , Heartsill‐Scalley Tamara , Leung L. Ruby 
Published: January 2025

AbstractIn the past three decades, Puerto Rico (PR) experienced five hurricanes that met or exceeded category three, and they caused severe forest structural damage and elevated tree mortality. To improve our mechanistic understanding of hurricane impacts on tropical forests and assess hurricane‐affected forest dynamics in Earth system models, we use in situ forest measurements at the Bisley Experimental Watersheds in Northeast PR to evaluate the Functionally Assembled Terrestrial Ecosystem Simulator coupled with the Energy Exascale Earth System Model Land Model (ELM‐FATES). The observations show that before Hurricane Hugo, 77.3% of the aboveground biomass (AGB) is from the shade‐tolerant plant function type (PFT). The Hugo‐induced mortality rates are over ∼50%, and they induce a ∼39% AGB reduction, which recovers to a level like the pre‐Hugo condition in 2014, following a second, lower intensity hurricane, Georges. We perform numerical experiments that simulate damage from Hugo and Georges on the forests, including defoliation, sapwood and structural biomass damage, and hurricane‐induced mortality. ELM‐FATES can reasonably represent coexistence between the two PFTs–light‐demanding and shade‐tolerant–for both the pre‐Hugo and post‐Hugo conditions. The model represents a reasonable size distribution of mid‐and large‐sized trees although it underestimates AGB, likely due to the overestimated nonhurricane mortality. ELM‐FATES temporarily stimulated leaf biomass and diameter increment after Georges, an effect that should be tested with observations of future hurricane defoliation events. This research indicates that addressing model‐data mismatches in tree mortality and understory dynamics are essential to simulation of more extreme hurricane effects under climate change.
Role of Micrometeorological Memory in Modulating Sub‐Daily Scale Variability of Net Ecosystem Exchange
Authors: Verma Akash , Khadke Leena , Eldhose Elizabeth , Ghosh Subimal 
Published: January 2025

AbstractNet Ecosystem Exchange (NEE) is crucial for understanding the carbon balance in ecosystems, indicating whether they act as carbon sinks or sources. While the impact of hydrometeorological factors on NEE at daily and monthly scales has been well‐researched, the significance of sub‐daily variability and the influence of memory in micrometeorological variables remain understudied. This study addresses this gap by analyzing the temporal dynamics of NEE using half‐hourly data from 29 FLUXNET sites over at least 6 years. We found that sub‐daily variability of NEE contributes 10%–55% of 13‐day NEE variability, depending on seasonal cycles and biome characteristics. Using an information theory based transfer entropy (TE) approach, we identified the causal drivers of NEE variability at sub‐daily scales within a 6‐hr memory. Our results show that the memory of micrometeorological variables significantly impacts NEE, surpassing their instantaneous effects. Temperature (TA), vapor pressure deficit (VPD), and soil water content (SWCMean) consistently affect NEE within this 6‐hr memory, whereas the influence of sensible heat (H) and incoming shortwave radiation (SWIN) diminishes at higher lags. While the magnitude of average TE from micrometeorological variables to NEE exhibits notable seasonal variations, the temporal structure of how information is transferred does not significantly differ across seasons, as reflected by the shape of TE values over various time lags. SWCMean, VPD, and TA impact NEE jointly, while H and SWIN have overlapping effects. Additionally, precipitation influences NEE indirectly through SWCMean. Our findings highlight the importance of accounting for high‐frequency NEE variability and its underlying drivers when investigating the ecohydrological interactions, shedding light on the role of memory in carbon‐water interactions.
A Novel Back‐Calculation Approach to Estimate Ocean Anthropogenic Carbon Using Carbon‐Based Data and a Total Matrix Intercomparison Method
Authors: López‐Mozos M. , Pérez F. F. , Carracedo L. I. , Gebbie G. , Velo A. 
Published: January 2025

AbstractOver the last decades, back‐calculation (BC) techniques for ocean anthropogenic carbon (Cant) estimation have improved and evolved into different methodologies that are not exempt from various assumptions and limitations. No single optimal BC method exists to date for computing Cant; therefore, it is necessary to continue advancing the broad range of approaches. Here, we present a novel method based on the BC fundamentals that combines marine‐carbonate‐system (MCS) data and the Total Matrix Intercomparison (TMI) framework. This MCS‐TMI approach differs from other BC methods by using the TMI to reconstruct deep‐ocean biogeochemical properties and their preformed conditions. It also incorporates a global sea‐air oxygen disequilibrium term, and a dynamic stoichiometric carbon‐to‐oxygen ratio that depends on the water‐mass ideal time. The MCS‐TMI yields a total Cant inventory of 124 ± 7 Pg C (referred to 1995), in good agreement with previous global Cant climatologies. The MCS‐TMI method uncertainty (±5.6 μmol kg−1) is controlled by input‐data errors that, nonetheless, have a minimal impact on the total Cant inventory. In contrast, our total Cant inventory uncertainty is governed by methodological errors, specifically those related to the TMI's boundary conditions. Our study demonstrates the effectiveness of MCS data‐based climatologies in reconstructing a 3D gridded Cant climatology, and the validity of ocean circulation transport operators for obtaining BC preformed conditions.
IFN-γ reprograms cardiac microvascular endothelial cells to mediate doxorubicin transport and influences the sensitivity of mice to doxorubicin-induced cardiotoxicity
Authors: Ji Haoyu , Ma Wenya , Liu Xu , Chen Hongyang , Liu Yining , Ren Zhongyu , Yin Daohong , Cai Ao , Zhang Zizhen , Wang Xin , Huang Wei , Shi Leping , Tian Yanan , Yu Yang , Wang Xiuxiu , Li Yang , Liu Yu , Cai Benzhi 
Published: January 2025

Abstract
Doxorubicin (DOX) is a first-line chemotherapy agent known for its cardiac toxicity. DOX-induced cardiotoxicity (DIC) severely limits the use for treating malignant tumors and is associated with a poor prognosis. The sensitivity to DIC varies among patients, but the precise mechanisms remain elusive. Here we constructed a mouse model of DIC using DOX to investigate potential mechanisms contributing to the differential susceptibility to DIC. Through surface-enhanced Raman spectroscopy and single-cell RNA sequencing, we explored the mechanisms underlying DIC phenotypic variations. In vitro and in vivo studies with small-molecule drugs were conducted. DIC-insensitive mice displayed preserved ejection fractions, lower DOX levels in cardiac tissues and higher levels in the serum. Single-cell RNA sequencing revealed differences of gene expression in cardiac endothelial cells between DIC-insensitive and DIC-sensitive groups. The expression of IFN-γ pathway-related genes was high in DIC-insensitive mice. IFN-γ administration decreased the DOX distribution in cardiac tissues, whereas PPAR-γ activation increased DIC susceptibility. IFN-γ stimulation upregulated P-glycoprotein expression, leading to increased DOX efflux and DIC insensitivity. Our model provides insights into the mechanisms of DIC sensitivity and potential preventive strategies.
Thy1-YFP: an effective tool for single cell tracing from neuronal progenitors to mature functionally active neurons
Authors: Plećaš Ante , Kapuralin Katarina , Grandverger Leonarda , Mitrečić Dinko , Alić Ivan 
Published: January 2025

Abstract
The differentiation of mouse neurons is a complex process involving cell maturation and branching, occurring during both, embryonic development and differentiation in vitro. To study mouse neuronal morphology, we used the Thy1 YFP-16 mouse strain. Although this mouse strain was described over twenty years ago, detailed studies on projections outgrowth and morphology of neurons are still lacking. The main goal of our study was to analyse the differentiation patterns of neural stem cells, including markers of differentiation, colocalization patterns, synaptic markers and the tracing of cell projections during differentiation in vitro. The neural stem cells were isolated from embryos at embryonic day 14.5 as well as newborn pups and differentiated into neurons and astrocytes. Our data showed a significant decrease of neural stem cells markers and a substantial increase in neuronal markers during differentiation, analysed by immunocytochemistry, quantitative PCR and western blot. To assess synaptic maturation, neurons were further analysed by quantitative PCR and immunocytochemistry. Expression of synaptic markers were increased during differentiation in vitro. At the 7th day in vitro differentiation, expression of synaptic markers in both YFP positive and YFP negative neurons were at comparable levels. Finally, our data revealed a significant increase in all measured morphological parameters: Filament Area, Filament Length, Filament No. Terminal Points and Sholl Intersections in YFP positive/MAP2 positive neurons compared to YFP negative/MAP2 positive neurons. These findings suggest that YFP is an effective tool for cell tracing both in vivo and in vitro, making it valuable for morphological studies during development as well as in the context of neurodegenerative disorders.
Rapid and scalable personalized ASO screening in patient-derived organoids
Authors: Means John C. , Martinez-Bengochea Anabel L. , Louiselle Daniel A. , Nemechek Jacqelyn M. , Perry John M. , Farrow Emily G. , Pastinen Tomi , Younger Scott T. 
Published: January 2025

Abstract
Personalized antisense oligonucleotides (ASOs) have achieved positive results in the treatment of rare genetic disease1. As clinical sequencing technologies continue to advance, the ability to identify patients with rare disease harbouring pathogenic genetic variants amenable to this therapeutic strategy will probably improve. Here we describe a scalable platform for generating patient-derived cellular models and demonstrate that these personalized models can be used for preclinical evaluation of patient-specific ASOs. We describe protocols for delivery of ASOs to patient-derived organoid models and confirm reversal of disease-associated phenotypes in cardiac organoids derived from a patient with Duchenne muscular dystrophy (DMD) with a structural deletion in the gene encoding dystrophin (DMD) that is amenable to treatment with existing ASO therapeutics. Furthermore, we designed novel patient-specific ASOs for two additional patients with DMD (siblings) with a deep intronic variant in the DMD gene that gives rise to a novel splice acceptor site, incorporation of a cryptic exon and premature transcript termination. We showed that treatment of patient-derived cardiac organoids with patient-specific ASOs results in restoration of DMD expression and reversal of disease-associated phenotypes. The approach outlined here provides the foundation for an expedited path towards the design and preclinical evaluation of personalized ASO therapeutics for a broad range of rare diseases.
Synthesis, H2S releasing properties, antiviral and antioxidant activities and acute cardiac effects of nucleoside 5′-dithioacetates
Authors: Bege Miklós , Lovas Miklós , Priksz Dániel , Bernát Brigitta , Bereczki Ilona , Kattoub Rasha Ghanem , Kajtár Richárd , Eskeif Simon , Novák Levente , Hodek Jan , Weber Jan , Herczegh Pál , Lekli István , Borbás Anikó 
Published: January 2025

Abstract
Hydrogen sulfide (H2S) is an endogenous gasotransmitter with cardioprotective and antiviral effects. In this work, new cysteine-selective nucleoside-H2S-donor hybrid molecules were prepared by conjugating nucleoside biomolecules with a thiol-activatable dithioacetyl group. 5′-Dithioacetate derivatives were synthesized from the canonical nucleosides (uridine, adenosine, cytidine, guanosine and thymidine), and the putative 5′-thio metabolites were also produced from uridine and adenosine. According to our measurements made with an H2S-specific sensor, nucleoside dithioacetates are moderately fast H2S donors, the guanosine derivative showed the fastest kinetics and the adenosine derivative the slowest. The antioxidant activity of 5′-thionucleosides is significantly higher than that of trolox, but lower than that of ascorbic acid, while intact dithioacetates have no remarkable antioxidant effect. In human Calu cells, the guanosine derivative showed a moderate anti-SARS-CoV-2 effect which was also confirmed by virus yield reduction assay. Dithioacetyl-adenosine and its metabolite showed similar acute cardiac effects as adenosine, however, it is noteworthy that both 5′-thio modified adenosines increased left ventricular ejection fraction or stroke volume, which was not observed with native adenosine.
Lactiplantibacillus plantarum N1 derived lipoteichoic acid alleviates insulin resistance in association with modulation of the gut microbiota and amino acid metabolism
Authors: Zhong Hao , Yu Yufen , Abdullah  , Zhang Haoxuan , Du Juan , Sun Jiangwei , Chen Ling , Feng Fengqin , Guan Rongfa 
Published: January 2025

Heat-killed Lactiplantibacillus plantarum N1, primarily through lipoteichoic acid, increased insulin sensitivity by regulating the gut microbiota and amino acid metabolism, offering a potential therapeutic strategy for type 2 diabetes mellitus.
NBCDC‐YOLOv8: A new framework to improve blood cell detection and classification based on YOLOv8
Authors: Chen Xuan , Li Linxuan , Liu Xiaoyu , Yin Fengjuan , Liu Xue , Zhu Xiaoxiao , Wang Yufeng , Meng Fanbin 
Published: January 2025

AbstractIn recent years, computer technology has successfully permeated all areas of medicine and its management, and it now offers doctors an accurate and rapid means of diagnosis. Existing blood cell detection methods suffer from low accuracy, which is caused by the uneven distribution, high density, and mutual occlusion of different blood cell types in blood microscope images, this article introduces NBCDC‐YOLOv8: a new framework to improve blood cell detection and classification based on YOLOv8. Our framework innovates on several fronts: it uses Mosaic data augmentation to enrich the dataset and add small targets, incorporates a space to depth convolution (SPD‐Conv) tailored for cells that are small and have low resolution, and introduces the Multi‐Separated and Enhancement Attention Module (MultiSEAM) to enhance feature map resolution. Additionally, it integrates a bidirectional feature pyramid network (BiFPN) for effective multi‐scale feature fusion and includes four detection heads to improve recognition accuracy of various cell sizes, especially small target platelets. Evaluated on the Blood Cell Classification Dataset (BCCD), NBCDC‐YOLOv8 obtains a mean average precision (mAP) of 94.7%, and thus surpasses the original YOLOv8n by 2.3%.
A two‐level optimal scheduling control strategy for air source heat pump loads with phase change energy storage
Authors: Liu Meng , Xie Xin , Yang Wenhui , Xu Fujia , Gao Song , Ding Lei , Liang Haiping 
Published: January 2025

AbstractReasonable scheduling and control of air‐source heat pumps (ASHPs) contribute to reducing operational costs for users while encouraging their participation in grid demand response. This article proposes a two‐layer optimal scheduling and control strategy for ASHP loads incorporating phase change energy storage (PCES). First, an electricity‐heat coupling model for ASHP loads is proposed. This model integrates PCES technology and considers the influence of outlet water temperature, ambient temperature, and the cold island effect on the coefficient of performance. Subsequently, a PCES capacity configuration model is established with the objective of maximizing the overall benefits of the PCES device. Finally, a two‐layer optimal scheduling and control strategy for ASHPs is introduced: The upper‐layer model employs model predictive control to minimize heating costs based on user comfort, leveraging PCES and building thermal storage characteristics, in conjunction with time‐of‐use electricity pricing. The lower‐layer model schedules periodic start–stop cycles of the ASHP units to respond to the upper‐layer power demand and mitigates the impact of the cold island effect on ASHP performance through unit interval sequencing. The simulation results show that the proposed strategy reduces the daily operation cost and power consumption by 38.9% and 25.0%, respectively, significantly improving the building's regulation capability.
State‐of‐the‐art of cybersecurity in the power system: Simulation, detection, mitigation, and research gaps
Authors: Beikbabaei Milad , Mehrizi‐Sani Ali , Liu Chen‐Ching 
Published: January 2025

AbstractIn a power system, the communication link can be compromised by intruders who can launch cyberattacks by capturing data packets, sending falsified packets, or stopping data packets from reaching their destination. Moreover, intruders can compromise control devices using supply chain attacks, firmware patching attacks, and insider attackers. Numerous cyberattacks have been reported previously, and cyberattacks are becoming more frequent since attackers are aware of their socioeconomic impacts. Extensive research has been conducted on developing platforms to simulate cyberattacks, studying different types of cyberattacks, investigating the adverse effects of a successful cyberattack on different components of the power system, designing ways to detect anomalies in the power system using electrical measurements, and proposing ways to mitigate the adverse effects of the detected cyberattack. This paper presents a review of state‐of‐the‐art of cybersecurity in the power system, reviewing available simulation tools for studying the cybersecurity of the power system, classifying components of the power system vulnerable to cyberattacks, and summarizing the adverse effects of a successful cyberattack on each component in the power system. Furthermore, different types of cyberattacks and detection and mitigation methods are classified. Research gaps in the cybersecurity of the power system are also discussed.
ELW‐CNN: An extremely lightweight convolutional neural network for enhancing interoperability in colon and lung cancer identification using explainable AI
Authors: Opee Shaiful Ajam , Eva Arifa Akter , Noor Ahmed Taj , Hasan Sayem Mustak , Mridha M. F. 
Published: January 2025

AbstractCancer is a condition in which cells in the body grow uncontrollably, often forming tumours and potentially spreading to various areas of the body. Cancer is a hazardous medical case in medical history analysis. Every year, many people die of cancer at an early stage. Therefore, it is necessary to accurately and early identify cancer to effectively treat and save human lives. However, various machine and deep learning models are effective for cancer identification. Therefore, the effectiveness of these efforts is limited by the small dataset size, poor data quality, interclass changes between lung squamous cell carcinoma and adenocarcinoma, difficulties with mobile device deployment, and lack of image and individual‐level accuracy tests. To overcome these difficulties, this study proposed an extremely lightweight model using a convolutional neural network that achieved 98.16% accuracy for a large lung and colon dataset and individually achieved 99.02% for lung cancer and 99.40% for colon cancer. The proposed lightweight model used only 70 thousand parameters, which is highly effective for real‐time solutions. Explainability methods such as Grad‐CAM and symmetric explanation highlight specific regions of input data that affect the decision of the proposed model, helping to identify potential challenges. The proposed models will aid medical professionals in developing an automated and accurate approach for detecting various types of colon and lung cancer.
A two‐channel data and power synchronous transmission method for SRG‐integrated power networks through piecewise composite modulation
Authors: Wang Tan , Shao Zhiyi , Yang Kunbo , Yu Dongsheng , Yu Samson Shenglong , Hu Yihua 
Published: January 2025

AbstractReliable communication is key to achieving remote control, status monitoring, and early fault detection in SRG‐integrated power networks. This paper proposes a novel piecewise composite modulation method to simultaneously modulate data and power during the excitation and power generation stages in each phase of an SRG system. By adopting a frequency‐shift keying modulation strategy, two‐channel data can be modulated and injected into the bus voltage as voltage ripples, allowing for more efficient use of the bus voltage frequency band. Welch's algorithm‐based power spectrum method is innovatively employed to demodulate the transmitted data on the SRG's output bus. Experimental results confirm the feasibility of the proposed data and power synchronous transmission (DPST) strategy, which shows significant potential in SRG‐integrated power networks.
An active‐support control strategy for multi‐winding medium‐frequency power electronics transformer for renewable generation
Authors: Li Xuejiao , Man Jiawei , Wang Mingyan , Zhu Bingda , Liu Chuang 
Published: January 2025

AbstractA high proportion of renewable energy is connected to the current power grid through power electronics interface devices, which makes the power system to have the low‐inertia dynamic characteristics. In order to improve the inertial response and voltage supporting capability, this article proposes a third‐order model of the synchronous generator based active support control strategy for the power electronics transformer (PET) based on a single multi‐winding medium‐frequency transformer (MWMFT) and AC choppers (ACCs) for renewable generation. First, the structure of the multi‐winding medium‐frequency power electronics transformer (MWMFPET) is introduced. Second, the average model of the MWMFPET is especially established through two modulation ratios. Third, the active support control strategy for this PET has been elaborated in detail. Finally, the simulation results verify the feasibility and effectiveness of the proposed control strategy for the MWMFPET.